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• What is brain fog?
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• http://orcid.org/0000-0001-9839-6549 Laura McWhirter 1 ,
• http://orcid.org/0000-0002-8671-2134 Heather Smyth 2 ,
• http://orcid.org/0000-0001-6742-7197 Ingrid Hoeritzauer 1 ,
• Anna Couturier 3 ,
• http://orcid.org/0000-0001-9829-8092 Jon Stone 1 ,
• Alan J Carson 1
• 1 Centre for Clinical Brain Sciences , The University of Edinburgh , Edinburgh , UK
• 2 Edinburgh Medical School , The University of Edinburgh , Edinburgh , UK
• 3 Institute for the Study of Science, Technology and Innovation , The University of Edinburgh , Edinburgh , UK
• Correspondence to Dr Laura McWhirter, Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh EH16 4SB, UK; laura.mcwhirter{at}ed.ac.uk

Background The term ‘brain fog’ is increasingly used colloquially to describe difficulties in the cognitive realm. But what is brain fog? What sort of experiences do people talk about when they talk about brain fog? And, in turn, what might this tell us about potential underlying pathophysiological mechanisms? This study examined first-person descriptions in order to better understand the phenomenology of brain fog.

Methods Posts containing ‘brain fog’ were scraped from the social media platform Reddit, using python, over a week in October 2021. We examined descriptions of brain fog, themes of containing subreddits (topic-specific discussion forums), and causal attributions.

Results 1663 posts containing ‘brain fog’ were identified, 717 meeting inclusion criteria. 141 first person phenomenological descriptions depicted forgetfulness (51), difficulty concentrating (43), dissociative phenomena (34), cognitive ‘slowness’ and excessive effort (26), communication difficulties (22), ‘fuzziness’ or pressure (10) and fatigue (9). 50% (363/717) posts were in subreddits concerned with illness and disease: including COVID-19 (87), psychiatric, neurodevelopmental, autoimmune and functional disorders. 134 posts were in subreddits about drug use or discontinuation, and 44 in subreddits about abstention from masturbation. 570 posts included the poster’s causal attribution, the most frequent attribution being long COVID in 60/570 (10%).

Conclusions ‘Brain fog’ is used on Reddit to describe heterogeneous experiences, including of dissociation, fatigue, forgetfulness and excessive cognitive effort, and in association with a range of illnesses, drugs and behaviours. Encouraging detailed description of these experiences will help us better understand pathophysiological mechanisms underlying cognitive symptoms in health and disease.

• chronic fatigue syndrome
• neuropsychiatry

Data availability statement

Data are available on reasonable request. Data will be shared on reasonable request.

This article is made freely available for personal use in accordance with BMJ’s website terms and conditions for the duration of the covid-19 pandemic or until otherwise determined by BMJ. You may use, download and print the article for any lawful, non-commercial purpose (including text and data mining) provided that all copyright notices and trade marks are retained.

https://doi.org/10.1136/jnnp-2022-329683

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Twitter @lauramcw, @IngridHoeritza1, @jonstoneneuro, @alancarson15

Contributors LM, HS, AC, IH, JS and AJC formulated the study question and methods. AC provided specific guidance regarding the extraction and analysis of social media data. LM wrote the code and extracted the data. HS summarised and tabulated the data. LM drafted the manuscript which was subsequently reviewed and revised by all authors. LM, as guarantor, accepts full responsibility for the work and conduct of the study, had access to the data, and controlled the decision to publish.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests LM is funded by the Scottish Government Chief Scientist’s Office to undertake long COVID research. LM provides independent medical testimony in court cases regarding patients with functional disorders and other neuropsychiatric conditions. IH has received honoraria for speaking at medical conferences, undertakes medicolegal work, and is an NRS clinical fellow. JS reports personal fees from UptoDate, outside the submitted work, runs a selfhelp website for patients with functional neurological symptoms (www.neurosymptoms.org) which is free and has no advertising, provides independent medical testimony in personal injury and negligence cases regarding patients with functional disorders, and is secretary of the International Functional Neurological Disorder Society. He is a Chief Scientists Office NHS Research Scotland Career Researcher. AJC is a director of a limited personal services company that provides independent medical testimony in court cases on a range of neuropsychiatric topics on a 50% pursuer 50% defender basis, a paid associate editor of the Journal of Neurology Neurosurgery and Psychiatry, and unpaid president elect of the International Functional Neurological Disorder Society.

Provenance and peer review Not commissioned; externally peer reviewed.

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REVIEW article

Caught in the thickness of brain fog: exploring the cognitive symptoms of chronic fatigue syndrome.

• Departments of Physiology/Medicine, Center for Hypotension, New York Medical College, Valhalla, NY, USA

Chronic Fatigue Syndrome (CFS) is defined as greater than 6 months of persistent fatigue that is experienced physically and cognitively. The cognitive symptoms are generally thought to be a mild cognitive impairment, but individuals with CFS subjectively describe them as “brain fog.” The impairment is not fully understood and often is described as slow thinking, difficulty focusing, confusion, lack of concentration, forgetfulness, or a haziness in thought processes. Causes of “brain fog” and mild cognitive impairment have been investigated. Possible physiological correlates may be due to the effects of chronic orthostatic intolerance (OI) in the form of the Postural Tachycardia Syndrome (POTS) and decreases in cerebral blood flow (CBF). In addition, fMRI studies suggest that individuals with CFS may require increased cortical and subcortical brain activation to complete difficult mental tasks. Furthermore, neurocognitive testing in CFS has demonstrated deficits in speed and efficiency of information processing, attention, concentration, and working memory. The cognitive impairments are then perceived as an exaggerated mental fatigue. As a whole, this is experienced by those with CFS as “brain fog” and may be viewed as the interaction of physiological, cognitive, and perceptual factors. Thus, the cognitive symptoms of CFS may be due to altered CBF activation and regulation that are exacerbated by a stressor, such as orthostasis or a difficult mental task, resulting in the decreased ability to readily process information, which is then perceived as fatiguing and experienced as “brain fog.” Future research looks to further explore these interactions, how they produce cognitive impairments, and explain the perception of “brain fog” from a mechanistic standpoint.

Introduction

Chronic Fatigue Syndrome (CFS) is a clinically defined set of symptoms of unknown etiology most notable for persistent fatigue lasting greater than 6 months. In 1994, the Center for Disease Control and Prevention (CDC) uniformly defined CFS. The CDC requiring the fatigue to be of new onset, non-exertional, not improved with rest, and debilitating to a person's lifestyle ( Fukuda et al., 1994 ). Additionally, at least four of the following symptoms must be concurrently present: pharyngeal pain, cervical or axillary lymphadenopathy, myalgia, polyarthritis without erythema or edema, headache, non-restful sleep, prolonged post-exercise fatigue, and/or debilitating cognitive impairments in short-term memory and concentration ( Fukuda et al., 1994 ). While the exact symptoms of each case of CFS are heterogeneous, up to 85% of individuals describe experiencing cognitive impairments ( Komaroff, 1993 ). These cognitive impairments have subjectively been described by patients with CFS as “brain fog.” Descriptions of “brain fog” include slow thinking, difficulty focusing, confusion, lack of concentration, forgetfulness, or a haziness in thought processes. In fact, “brain fog” may be one of the most debilitating aspects of CFS ( Jain and DeLisa, 1998 ; Natelson and Lange, 2002 ; Afari and Buchwald, 2003 ; Jorgensen, 2008 ). However, a precise definition of CFS “brain fog” has yet to be formulated. Thus, “brain fog” may be conceptionally defined as the perception and experience of mental fatigue that is associated with and related to mild cognitive impairments in CFS. Research has focused on describing “brain fog” and mild cognitive impairment in regards to CFS using objective measurements. Physiologically, areas of study have investigated mental fatigue and impairment as the effects of orthostatic stress, in relationship to changes in cerebral blood flow (CBF), and as a perception. In addition, neurocognitive testing has localized the cognitive impairments in CFS to the domains of attention, information processing, memory, and reaction time ( Cockshell and Mathias, 2010 ). Furthermore, functional magnetic resonance imaging (fMRI) of the brain has associated changes in anatomical structures to the cognitive fatigue experienced in CFS. However, while much research has been done to analyze the individual components of the cognitive symptoms in CFS, no single source has compiled a comprehensive description of the multiple factors and their interactions that may play a role in the CFS patient's experience of “brain fog” (see Figure 1 ). Thus, to better understand cognitive impairment and “brain fog” in CFS, as well as to guide future research, the goal of this review is to summarize, standardize, and analyze the cognitive symptoms which lead to impairment.

Figure 1. Interactions between multiple factors may contribute to the cognitive symptoms subjectively described as “brain fog” in Chronic Fatigue Syndrome (CFS). POTS, Postural Tachycardia Syndrome.

Neurocognitive Testing Demonstrates Specific Cognitive Deficits in CFS

If “brain fog” truly is the subjective experience of cognitive impairment in CFS, the impairment should be measurable. Early work using sensory and cognitive event-related potentials broadly demonstrated deficits in CFS subjects compared to control subjects in areas of memory, concentration, attention, information processing, and reaction time ( Prasher et al., 1990 ). Research has attempted to use more focused tests to narrow in on what exactly these deficits are. A table of cognitive tests that have been used to study impairments in CFS is listed (see Table 1 ).

Table 1. List of cognitive tests used to study Chronic Fatigue Syndrome cognitive impairments .

Using the Paced Auditory Serial Addition Test (PASAT) and the Digit Span Test, tests of memory, attention, and data processing, DeLuca et al. (1993) found that CFS subjects scored lower than control subjects, suggesting deficits in information processing of complex material. Further work by DeLuca et al. (1995) showed that CFS subjects have intact memory storage, consolidation, and retrieval and “higher order” cognitive function; however, they exhibit decreased speed and efficiency in information processing, especially with auditory material, and subjectively perceive a more generalized cognitive impairment ( DeLuca et al., 1995 ). Interestingly, this perception of generalized cognitive impairment fits the concept of “brain fog.”

In addition to information processing, deficits in memory have been studied in CFS. Work by Grafman et al. (1993) compared responses to a battery of memory and neuropsychological tests (see Table 1 ) between CFS and control subjects. While overall memory consolidation and storage were intact, CFS subjects demonstrated selective deficits in memory processing ( Grafman et al., 1993 ). Joyce et al. (1996) used the Cambridge neuropsychological test automated battery (CANTAB), which is a set of tests that measure various aspects of memory, attention, reaction time, executive functioning, and decision making, and found that CFS subjects exhibited deficits in working memory and impaired attention. Working memory may be defined as a transient cognitive storage system that is able to process information and use it to complete a task ( Baddeley, 1986 ). Similarly, Dobbs et al. (2001) reported that CFS subjects had working memory deficits based on results from the Digit Span Forward test, Digit Span Backward test, Trails A test, and Trails B test, which are a set of memory and attention tests. These deficits were mainly apparent during challenging tasks that needed sustained attention and efficient mental processing ( Dobbs et al., 2001 ). Work by Capuron et al. (2006) , using the CANTAB, further distinguished that working memory and impaired attention were only impaired compared to control subjects in a subgroup of CFS patients who subjectively stated experiencing increased mental fatigue. When they compared CFS who did not report mental fatigue, they did not find a difference ( Capuron et al., 2006 ).

Of note, children with CFS have also been studied and have been shown to exhibit cognitive impairment in the areas of focusing, splitting, switching attention, working memory, and auditory learning ( Haig-Ferguson et al., 2009 ). Interestingly, a recent study in children with CFS found that treatment with both cognitive behavioral therapy and pharmacotherapy lead to improvements in attention ( Kawatani et al., 2011 ).

In summary, research has demonstrated cognitive impairment in CFS, particularly in working memory, information processing, attention, and reaction time. Deficiencies in these cognitive areas may be perceived on a day-to-day basis as “brain fog.” Mental fatigue is necessary and must be experienced in order for CFS subjects to have cognitive symptoms. Comprehensively, the cognitive impairments associated with CFS impair the ability to maintain attention for an extended period of time, disrupt efficient and speedy information processing, and results in an inability to plan or order responses from memory ( Joyce et al., 1996 ). Functionally, this is translated into increased reaction time while completing tasks. The deficits in information processing and working memory are similar and most likely related. Task difficulty plays a role in the perception of mental fatigue, with CFS subjects feeling most fatigued following the more difficult tasks. Additionally, the greatest degree of impairment and disability has been noted in CFS subjects who perform the worst on neurocognitive tests ( Christodoulou et al., 1998 ).

Psychiatric Comorbidities are not Associated with Cognitive Impairment in CFS

Depression and anxiety often co-exist in subjects with CFS and may in themselves be associated with cognitive impairment ( Afari and Buchwald, 2003 ). Studies have focused on determining whether comorbid psychiatric illness is the cause of cognitive impairment in CFS.

An early study prior to the 1994 CDC definition suggested that subjective cognitive impairment in individuals with CFS may be associated with depression ( McDonald et al., 1993 ). However, a study by DeLuca et al. (1997) suggested otherwise. This group separated CFS subjects into a cohort with psychiatric comorbidity and a cohort without. When compared to healthy control subjects' performance on neurocognitive tests, CFS subjects without psychiatric comorbidities exhibit neurocognitive impairment, whereas those with comorbidities did not ( DeLuca et al., 1997 ). More recent work by the same group similarly concluded that CFS subjects without psychiatric comorbidities exhibit deficits in working memory and information processing, while those with psychiatric comorbidities were not different from controls ( DeLuca et al., 2004 ). Further work by other groups similarly has concluded that the cognitive impairment in CFS is not due to depression ( Constant et al., 2011 ; Santamarina-Perez et al., 2011 ).

From these studies, two distinct groups of CFS subjects have been identified. It appears that cognitive symptoms occur only in CFS subjects without psychiatric comorbidities. More studies are needed to elucidate the factors which may explain this. There is a clear need in future studies to appropriately stratify CFS subjects into those with and without psychiatric comorbidities.

Orthostatic Stress Impairs Cognitive Performance in CFS

Cognitive impairment has been associated with the physiological onset of orthostatic intolerance (OI). OI is defined by the onset of signs and symptoms that occur when an individual assumes the upright posture, with the signs and symptoms being alleviated by resuming the supine position. Rowe et al. (1995) first described OI in CFS in 1995. Both adults and adolescents with CFS often experience OI in the form of the Postural Tachycardia Syndrome (POTS), with syncope being less common ( De et al., 1996 ; Rowe and Calkins, 1998 ; Stewart et al., 1999 ; Karas et al., 2000 ; Hoad et al., 2008 ). POTS is defined in adults as symptomatic OI with an increase in HR of at least 30 beats per minute (bpm) or a maximum HR of 120 bpm ( Schondorf and Low, 1993 ). Typical symptoms of OI that occur include dizziness, neurocognitive impairment, tremulousness, nausea, and long-term fatigue ( Schondorf and Freeman, 1999 ; Medow and Stewart, 2007 ). Some individuals with POTS experience migraine headaches ( Piovesan et al., 2008 ). While standing upright, physiologic changes noted in POTS include increased diastolic BP and total peripheral resistance, decreased stroke volume, and impaired venoconstriction ( Low et al., 1994 ). Regional venous blood pooling may occur while upright, particularly in the splanchnic region and in the legs ( Stewart and Montgomery, 2004 ). POTS subjects tend to have decreased total blood volumes, red cell volume, and plasma aldosterone ( Raj et al., 2005 ). About half of the individuals with POTS exhibit orthostatic hyperventilation and hypocapnia, while the other half breathe normally and are eucapnic ( Stewart et al., 2006 ). A similar respiratory pattern of orthostatic hypocapnia has been noted in about a third of CFS subjects ( Naschitz et al., 2000 , 2006 ; Natelson et al., 2007 ).

Limited psychological testing has occurred in POTS subjects. Work by Raj et al. (2009) found mild depression and moderate anxiety to be prevalent in POTS subjects, but lifetime prevalence of psychiatric diseases overall was not different than that of control subjects. They determined that the anxiety experienced in POTS was more related to the symptoms of the disease and how those symptoms may affect the individual ( Raj et al., 2009 ). Similar to CFS, POTS subjects may also experience attention deficits ( Raj et al., 2009 ).

Moreover, some of the symptoms of CFS and POTS overlap in their clinical descriptions as well as in their associations with cognitive impairment, and individuals commonly present with symptoms of both syndromes ( De et al., 1996 ; Hoad et al., 2008 ). Of note, some individuals with CFS and/or POTS also suffer from Ehlers–Danlos Syndrome, a genetic disorder that causes a defect in the synthesis of collagen which affects connective tissue ( Rowe et al., 1999 ; Mathias et al., 2012 ). This syndrome may predispose to OI due to the occurrence of excessive venous pooling because of exaggerated venous wall distention and dysfunctional venous valves ( Rowe et al., 1999 ).

Neurocognitive impairment is often described as a symptom of OI. The subjective descriptions of the cognitive impairments in POTS are similar to those in CFS. Therefore, OI, in particular POTS, may be connected to the “brain fog” experienced in CFS. Limited work has looked at neurocognitive testing during orthostatic stress. One study by Karas et al. (2000) found that adolescents with POTS experience cognitive impairment, although no formal neurocognitive testing was used to determine the exact areas that were affected. Using more objective measures, work by Ocon et al. (2012) studied subjects with both CFS and POTS (CFS/POTS) during graded orthostatic stress, using a n -back task as a cognitive stressor. The n -back task is a cognitive test of progressively increasing difficulty that stresses domains of working memory and information processing while measuring reaction time ( Braver et al., 1997 ). Results showed that subject with CFS/POTS exhibited no differences in accuracy or reaction time compared to control subjects while supine ( Ocon et al., 2012 ). However, during moderate to severe levels of orthostatic stress, CFS/POTS subjects were less accurate and had a longer reaction time compared to control subjects, particularly during the difficult stages of the n -back task ( Ocon et al., 2012 ). This study demonstrated that orthostatic stress may impair the cognitive abilities of those with CFS/POTS, especially during difficult tasks. Thus, working memory, information processing, and reaction time may be impaired with prolonged orthostatic stress. These cognitive deficiencies may be perceived as “brain fog.” Speculatively, one may consider physiological changes during orthostasis to potentially be a cause of the cognitive impairment. In particular, alterations in CBF regulation may be related to the cognitive symptoms as described below.

Cerebral Blood Flow is Decreased in CFS

Much research has studied CBF alterations in CFS. Early work measured regional CBF using single photon emission computed tomography (SPECT) in those with CFS. Ichise et al. (1992) found that 80% of CFS subjects exhibited decreased regional CBF particularly in the frontal, temporal, parietal, occipital, and basal ganglia regions compared to control subjects without CFS or other neurological/neuropsychiatric disorders. Similarly using SPECT, Schwartz et al. (1994) found decreased regional CBF in CFS subjects in the frontal and temporal lobes. Costa et al. (1995) studied brainstem perfusion in CFS subjects and found hypoperfusion compared to both control subjects and subjects with major depression. However, work by Fischler et al. (1996) did not find significant differences in regional CBF between CFS and control subjects, and MacHale et al. (2000) actually found increased CBF in CFS subjects in the thalamus, pallidum, and putamen regions. Technical differences with SPECT and methodological inconsistencies between studies may account for the contradictory results.

Other techniques of measuring CBF have been applied to determine whether decreased CBF does occur in CFS. Positron emission tomography was used by Tirelli et al. (1998) to look at cerebral metabolism in CFS subjects. They found that CFS subjects exhibited hypometabolism in the right mediofrontal cortex and brainstem compared to control subjects ( Tirelli et al., 1998 ). Near-infrared spectroscopy (NIRS) is another method which looks at changes in brain oxygenation of hemoglobin. NIRS measurements by Tanaka et al. (2002) found that CFS subjects had lower brain oxy-hemoglobin while standing upright compared to control subjects. This suggests that orthostatic stress may negatively influence cerebral oxygenation in CFS. Similarly, Patrick et al. (2008) used NIRS during maximal incremental cycle exercise in female CFS subjects. They found that the CFS subjects exhibited exercise intolerance that was associated with decreased prefrontal oxygenation ( Patrick et al., 2008 ). Additionally, Natelson et al. used more advanced imaging techniques of Xenon gas diffusion computerized tomography ( Yoshiuchi et al., 2006 ) and magnetic resonance arterial spin labeling ( Biswal et al., 2011 ) to demonstrate reduced total CBF in CFS subjects compared to controls, especially in CFS subjects without psychiatric comorbidities.

In order to study whether altered CBF affected cognitive performance, Schmaling et al. (2003) used SPECT measurements of CBF during the PASAT test to see whether impaired CBF in CFS could be associated with decreased cognitive impairment. Prior to testing, CFS subjects had decreased perfusion in the anterior cingulate region of the brain compared to control subjects ( Schmaling et al., 2003 ). During testing, there was a greater increase in blood flow to the left anterior cingulate region in CFS subjects ( Schmaling et al., 2003 ). Furthermore, CFS subjects exhibited a wide-spread, diffuse pattern of CBF in the frontal lobe, temporal lobe, and thalamus compared to a small, focal pattern in the right frontal lobe and right temporal lobe in control subjects ( Schmaling et al., 2003 ). No differences in test performance occurred between groups, but CFS subjects reported greater mental fatigue following testing. This suggested that an increased change in cerebral perfusion with greater activation of more brain regions was necessary for CFS subjects to perform at the same level as that of control subjects ( Schmaling et al., 2003 ). This may be due to the need to overcome the decreased baseline CBF. These subjects also subjectively experienced “brain fog” as mental fatigue, suggesting that the increased change in cerebral perfusion and activation during cognitive tasks was perceived as stressful and exaggerated exhaustion. Speculatively, this may be related to altered cerebral metabolism, with increased production of metabolites affecting neuronal biochemical pathways. Further research measuring cerebral metabolism during neurocognitive testing is needed to detail the processes of mental fatigue and impairment in CFS.

As mentioned above, orthostatic stress is related to neurocognitive impairments in CFS and POTS and may induce changes in CBF. Since some POTS symptoms overlap with CFS, it is important to look at how CBF is affected in this syndrome. In most studies, CBF was estimated by measurements of CBF velocity (CBFv) using transcranial Doppler sonography. Work by Novak et al. (1998) found that during orthostatic stress, POTS subjects have decreased CBFv. This may be related to hyperventilation and hypocapnia-induced increased cerebrovascular resistance ( Novak et al., 1998 ). Similarly, Low et al. (1999) suggested that the altered CBFv in POTS was explained solely by respiratory changes and their concomitant affect on cerebrovasomotor tone. Other research suggested that ineffective cerebral autoregulation also played a role in the decreased CBFv seen in POTS ( Jacob et al., 1999 ; Hermosillo et al., 2002 ). Ocon et al. (2009) found a relationship between decreased CBFv and altered cerebral autoregulation in a cohort of POTS subjects who were eucapnic during orthostatic stress. However, Schondorf et al. (2005) reported normal cerebral autoregulation in POTS subjects, though the group did not measure changes in CO 2 . Thus, CBF appears to be decreased in POTS subjects similarly to how it is decreased in CFS subjects, but the mechanisms involved are controversial and probably multifactorial. The decreased CBF in POTS and CFS during orthostatic stress may play a role in their perceived cognitive impairment.

To study this, work by Stewart et al. (2012) looked at how CBFv changed during increasing mental and orthostatic stress in a group of subjects with both CFS and POTS. Mental stress was induced by the n -back task, while orthostatic stress was induced with graded tilt-table testing. In control subjects, CBFv increased as the level of n -back difficulty increased, independent of orthostatic stress ( Stewart et al., 2012 ). In contrast, CFS/POTS subjects did not exhibit an increase in CBFv with increasing n -back difficulty. Additionally, decreasing CBFv in CFS/POTS subjects was dependent on the level of orthostatic stress ( Stewart et al., 2012 ). This study concluded that control subjects demonstrated appropriate neurovascular coupling to mental stress, whereas CBFv is not activated by mental stress in CFS/POTS subjects ( Stewart et al., 2012 ). This may be due to an uncoupling of cognitive–vasomotor interactions ( Stewart et al., 2012 ). Additionally, superimposed orthostatic stress appears to further negatively impact the cerebral vasomotor responses to mental stress in CFS/POTS subjects ( Stewart et al., 2012 ).

Therefore, cognitive impairments in CFS/POTS may be related to impaired activation and regulation of CBF, especially during challenging mental tasks and orthostatic stress. Adequate cerebral perfusion is necessary for the brain to function. In those with CFS and/or POTS, a gradual and chronic hypoperfusion of the brain may occur, especially during orthostatic stress ( Ocon et al., 2009 ). Animal studies suggest that chronic cerebral hypoperfusion may cause cognitive impairment ( Ni et al., 1994 ; Liu et al., 2012 ). Thus, if CBF is decreased chronically in CFS, mild cognitive impairment may be the result.

Functional MRI Finds Altered Regional Cerebral Activation in CFS

Cerebral imaging techniques have tried to associate cognitive impairments with specific cerebral regions. An early MRI study by Lange et al. (1999) found increased hyperintensities in the frontal lobe subcortical white matter of CFS subjects without psychiatric comorbidities compared to those with comorbidities and control subjects, suggesting nonspecific cerebral lesions as the basis for cognitive impairment. Using fMRI to measure cerebral changes during cognitive tasks (see Table 1 ), de Lange et al. (2004) found that CFS subjects exhibited decreased caudate nucleus activity, increased recruitment of cerebral regions, and an inactive ventral anterior cingulated cortex during errors compared to control subjects. They suggested that these changes may be associated with fatigue, the need for additional neural activation to complete a task, and reduced motivation ( de Lange et al., 2004 ). Additional work using fMRI found that demanding working memory tasks elicited activation in more regions of the brain in CFS subjects than in control subjects ( Lange et al., 2005 ). It is tempting to speculate that CFS subjects may require more brain activation during working memory tasks. Consistent with this speculation, Caseras et al. (2006) used the n -back task to monitor how CFS subjects' brains respond to different levels of mental stress compared to control subjects. They found that during lower difficulty n -back testing, CFS patients exhibited increased activation of working memory centers ( Caseras et al., 2006 ). However, during higher difficulty testing, they had decreased activation compared to control subjects ( Caseras et al., 2006 ). Similarly, Cook et al. (2007) showed that CFS subjects, when compared to control subjects, have increased cortical and subcortical cerebral activation during fatiguing, stressful mental tasks (see Table 1 ). They suggested that increased brain activation may be related to the perception of mental fatigue ( Cook et al., 2007 ).

Physical and Cognitive Symptoms of CFS may be a Mental Perception of Stimuli

Prior to the 1994 CDC definition of CFS, Kent-Braun et al. (1993) theorized that the physical symptoms of fatigue in CFS were in part related to a central nervous system perception of the body's response to a stressor. They hypothesized that CFS did not induce true muscle fatigue, but rather the experience of fatigue was a mental discernment of peripheral sensations and stimuli. To test this hypothesis, the group studied muscle fatigue in the tibialis anterior muscle following exercise. They found that CFS subjects failed to voluntarily activate the muscle after prolonged stress, despite no detectable metabolic or functional changes having occurred ( Kent-Braun et al., 1993 ). This suggested that in CFS bodily fatigue during and following exercise was perceived mentally rather than there being true peripheral muscle exhaustion. Another study further examined fatigue as a perception. While studying post-exertion fatigue in females with CFS, Sisto et al. (1998) found that the experience of fatigue following exercise was exaggerated compared to control subjects, and it may experienced in a prolonged manner for 12–14 days. Together, these studies suggest that the perception of fatigue in CFS is a mental experience of physical fatigue following exercise, or potentially any a stressful stimulus, even if no such physical exhaustion occurs. In addition to the cognitive component, this mental experience is part of the subjective “brain fog” that patients with CFS describe. This perception may be exaggerated, continual, and prolonged, despite true muscle exhaustion not occurring.

In an attempt to detail a mechanism describing the perception of fatigue in CFS, recent work has looked at neuroactive amino acids and metabolite concentrations following exercise. A study found increased tryptophan, decreased branch chain amino acids, and decreased tyrosine following exercise in the plasma of CFS subjects compared to controls ( Georgiades et al., 2003 ). The exact meaning of these changes is difficult to discern, but speculatively this may suggest that metabolic alterations in precurors involved in the serotonergic and dopaminergic pathways may be involved in the central perception of fatigue. Moreover, another study showed that CFS subjects exhibit electroencephalogram changes during fatiguing exercise. Again, how this relates to the perception of fatigue is speculative, but it may suggest that altered cerebral signaling, particularly that involved with motor activity, may be experienced as mental fatigue ( Siemionow et al., 2004 ). Further work is needed to determine how mental fatigue, cognitive impairment, and the subjective experience of “brain fog” relate biochemically, physiologically, and mechanistically to the changes that occur in CFS following exercise or any stressor.

The Experience of “Brain Fog” in CFS as a Collection of Physiological, Cognitive, and Perceptual Factors

Over the past 20 years, research has answered many questions regarding cognitive symptoms in CFS. The experience of “brain fog” in those with CFS appears to be the conscious perception of cognitive impairment and is related to mental fatigue. Individuals with CFS do not exhibit complete cognitive disability or dementia. However, they may experience deficits in working memory, information processing, and attention, which then may translate into a longer reaction time during tasks. It is logical that the perception of such deficits would be described as mental cloudiness and difficulty thinking.

Drawing from an overview of the above studies, cognitive impairment in CFS is exacerbated by stressful stimuli such as a difficult mental task, exercise, and/or orthostatic stress. Physiologically, the cognitive impairments may be associated with impaired cardiovascular hemodynamics as seen in POTS, decreased total CBF, and altered activation of CBF during mental tasks. Psychiatric diseases do not seem to be related to cognitive impairment. Importantly, the perception of the symptoms of CFS is often exaggerated and excessive compared to what is measured. Aside from the cognitive impairments noted above, this perception may be disabling. Thus, “brain fog” is caused by measurable cognitive impairments but also the more subjective perception of mental fatigue and its impact on the individual with CFS. As shown in Figure 1 , interactions of multiple factors clearly play a role. Based on the above research, one speculative view of the mechanisms behind the cognitive symptoms of CFS is that altered CBF activation and regulation are exacerbated by a stressor, such as orthostasis or a difficult mental task, that results in the decreased ability to readily process information, which is then perceived as fatiguing and experienced as “brain fog.” Thus, future research will study if interventions that modify CBF affect the cognitive symptoms of CFS. Additionally, more work will look at how orthostatic stress impacts neurocognition. Finally, since the impaired cognitive domains in CFS have been determined, interventions to improve these domains will be tested.

To date, treatment of CFS has been focused on improving the physical fatigued state rather than the cognitive impairment. Meta-analyses demonstrate that cognitive behavioral therapy and graded exercise therapy effectively treat CFS in many individuals ( Edmonds et al., 2004 ; Price et al., 2008 ). It would not be surprising if mental fatigue also is improved with such therapies, but future studies are necessary to formally determine this.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

Much gratitude is given toward the members of the Research Division of Pediatric Cardiology at New York Medical College, especially Dr. Julian Stewart, Dr. Marvin Medow, and the members of their laboratory. Additional thanks goes to Department of Physiology at New York Medical College.

This work was supported by the National Heart, Lung, and Blood Institute Grants 1-F30-HL-097380.

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Keywords: Chronic Fatigue Syndrome, postural orthostatic tachycardia syndrome, neurocognition, cerebral blood flow (CBF), functional magnetic resonance imaging (fMRI), brain fog, orthostatic intolerance

Citation: Ocon AJ (2013) Caught in the thickness of brain fog: exploring the cognitive symptoms of Chronic Fatigue Syndrome. Front. Physiol . 4 :63. doi: 10.3389/fphys.2013.00063

Received: 26 December 2012; Accepted: 15 March 2013; Published online: 05 April 2013.

Reviewed by:

Copyright © 2013 Ocon. This is an open-access article distributed under the terms of the Creative Commons Attribution License , which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

*Correspondence: Anthony J. Ocon, Departments of Physiology/Medicine, Center for Hypotension, New York Medical College, 19 Bradhurst Ave., Suite 1600S, Hawthorne, NY 10532, USA. e-mail: [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Multidisciplinary Approach to Brain Fog and Related Persisting Symptoms Post COVID-19

• Published: 02 February 2022
• Volume 48 , pages 31–38, ( 2022 )

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• Kamini Krishnan 1 ,
• YuFang Lin 1 ,
• Kia-Rai M. Prewitt 1 &
• Dawn A. Potter 1  

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A third of patients who developed COVID-19 experience a persisting, diverse array of symptoms including respiratory, neurological, and psychiatric complaints referred to as post-acute sequelae of COVID-19 (PASC). Symptoms can last for months after the original infection and appear unrelated to the severity of the initial illness, which suggests that even patients who did not require extensive interventions at the acute stage may experience new and/or long-term symptoms. Brain fog is a colloquial term for a common complaint among patients with PASC and generally implies cognitive impairment in domains of attention and processing speed. There are multiple hypotheses for etiologies and explanations of mechanisms contributing to brain fog in PASC. In this paper, we describe some of the mechanisms associated with brain fog post COVID-19 and provide readers with treatment recommendations that encompass cognition, mood disorders, sleep disorders, and neuroinflammation.

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Clinical Vignette

Ms. Ella Smith is a 35-year-old Critical Care Nurse who identifies as female. She tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) about 3 months ago. She was hospitalized for 1 day but did not require mechanical ventilation. Initial symptoms included shortness of breath, cough, fever, fatigue, and difficulty sleeping, which have persisted. She also complains of significant “brain fog,” which she defines as difficulty maintaining her attention and recalling information.

She reports significant fatigue and concerns about her work performance. Based on her cognitive complaints, she is referred for a neuropsychological evaluation. During the neuropsychological evaluation, Ms. Smith describes difficulty recalling details of conversations. She is more reliant on notes that she was before she had COVID-19. She sometimes feels drowsy during work hours and has made some inattentive mistakes. She is concerned about her ability to continue her current workload.

Ms. Smith discloses prior psychiatric history of major depressive disorder that was relatively stable prior to developing COVID-19. Her current mood includes reports of depressive and anxiety symptoms every day, nearly all day, such as feeling bad about herself, a loss of interest in her favorite hobbies, feelings of hopelessness, frequent worries about her recovery, and overeating to cope. She also describes insomnia and reports difficulty staying asleep. She says that she is frequently awoken by coughing and then tends to stay awake due to ruminating thoughts about her recovery.

Ms. Smith reports a 30-lb weight gain since she contracted COVID-19. She attributes this to decreased physical activity due to the shortness of breath and increased eating, which she associates with depressive symptoms. Her current body mass index is 31.2, classified in the obese range. Her primary medical history includes diabetes mellitus type II, hypertension, and hyperlipidemia. She rarely drinks alcohol and does not use tobacco or other substances.

Ms. Smith’s neuropsychological test results reflected an individual with a high average baseline intelligence with variability in her test performance. Results were moderately impaired on tests assessing sustained attention and problem-solving and some aspects of processing speed. Simple attention, reasoning, language, memory, other aspects of processing speed, and visuospatial function were generally within normal limits.

During the neuropsychology feedback session, the neuropsychologist provided psychoeducation about the impact of poor sleep, mood disorder, and changes in eating patterns on cognitive health. Using her neuropsychological evaluation as a guide, Ms. Smith was also provided with cognitive compensation strategies for inattention and difficulty problem-solving. Ms. Smith was then referred to specialists in psychology, integrated wellness, and sleep medicine to address other factors thought to be contributing to her chief complaint of brain fog.

Background on COVID-19 and Brain Fog

The clinical presentation of COVID-19 resulting from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is primarily characterized by respiratory symptoms but can involve a diverse array of features including pulmonary (e.g., pneumonia, dyspnea on exertion), cardiac (e.g., ischemia, arrhythmias, myocarditis), gastrointestinal (e.g., anorexia, diarrhea), and neurological (e.g., headache, dizziness, ageusia, anosmia; Taquet et al., 2021 ). It is now well known that almost a third of patients across the world will experience persisting symptoms weeks and months, sometimes 1-year after diagnosis (Taquet et al., 2021 ). These findings are similar to recovery from SARS in 2000, especially for patients who experienced severe symptoms and spent weeks in intensive care. However, COVID-19 varies in that a large subset of patients who did not require hospitalization appear to experience reoccurring, persisting, or new symptoms months after the initial infection (Almeria et al., 2020 ).

The persisting symptoms after COVID-19 are referred to as “long COVID” or post-acute sequelae of COVID-19 (PASC). Of the diverse constellation of symptoms that constitute PASC, the neurological and psychiatric symptoms include fatigue, post-exertional malaise, cognitive complaints, sensorimotor symptoms, headaches, insomnia, depression, and post-traumatic stress disorder (Taquet et al., 2021 ). The mechanisms involved in developing PASC and factors affecting recovery from COVID-19 are still in the nascent stages. Current hypotheses include psychological factors, inflammatory and immune reactions, and physical deconditioning (Deng et al., 2021 ; Calabrese, 2020 ). The diversity in symptoms, involvement of multiple organ systems, and varying possible mechanisms suggest that a multi-pronged approach to treatment may be quintessential in recovery from PASC.

The colloquial term “brain fog” is among the top three symptoms reported by millions of individuals with PASC. While the term “brain fog” is used commonly by patients and the healthcare community, there is no widely accepted definition of this term. In general, it refers to a constellation of symptoms including inattention, short-term memory loss, and reduced mental acuity (Ocon, 2013 ; Garg et al., 2021 ). In the scientific literature, brain fog has been associated with disorders affecting the central nervous system (e.g., chronic fatigue syndrome and fibromyalgia) or treatments affecting the immune system such as chemotherapy for cancer (Ocon, 2013 ).

Subsequently, there are multiple theories on the etiology of symptoms that are associated with brain fog. Clinical observation and research in the last two years suggests severe COVID-19 disease is a consequence of the immune system producing excessive inflammatory proteins called cytokines, sometimes referred to as a cytokine storm, and PASC is a consequence of the exaggerated, prolonged immune response. This mechanism has the potential for crossing the blood–brain barrier and affecting neural regions and function, including cognition.

Brain fog and fatigue, commonly reported in patients with PASC, can be viewed as a consequence of neuroinflammation. Other mechanisms suggest sleep disruption and psychiatric disorders that are impacted post-COVID have a secondary impact on cognition presenting as brain fog (Deng et al., 2021 ). Given that brain fog is among the top symptoms reported by patients with PASC and is often accompanied by presence of mood symptoms, mental health providers are likely to see patients who present with brain fog as a prominent concern post-recovery from the acute phase of COVID-19. This paper provides operationalization and general treatment recommendations for health service psychologists who are working with patients presenting with post-COVID-19 brain fog symptoms.

Multidisciplinary Approach to Treating Brain Fog in COVID-19

In this section, we provide further background on symptoms and etiology associated with brain fog including (1) cognition, (2) sleep, (3) psychological factors, and (4) neuroinflammation.

Studies evaluating cognitive deficits post COVID-19 generally illustrate impairments in cognitive domains of attention and executive function (Almeria et al., 2020 ). These deficits are primarily observed in the acute stages—typically in the first month after COVID-19 diagnosis. It is recognized that cognitive impairments in patients with PASC can exist even among those who did not require hospitalization or experience events associated with severe COVID-19. The pattern of cognitive deficits in domains of attention and executive function is also present in these patients and recent research demonstrates presence of cognitive impairment even 4 months after COVID-19 (Hampshire et al., 2021 ). Possible contributors to impaired cognition, in the absence of any quantifiable neural involvement (e.g., stroke, hypoxia), include factors such as sleep quality, nutrition, and psychological function.

For Ms. Smith, the neurocognitive evaluation was used as a basis for quantifying the brain fog related cognitive complaints. In this case, the results assisted in ruling out possible causes of cognitive impairment from COVID-19 such as an anoxic injury or undiagnosed seizures. However, other factors were identified that could contribute to brain fog including sleep disruption, psychological symptoms (e.g., changes in mood), and possible neuroinflammation, especially given Ms. Smith’s prior vascular history.

Sleep disordered breathing (SDB) has been associated with comorbidities generally associated with increased risk of developing COVID-19, such as diabetes, obesity, hypertension, and older age. This association suggests a strong overlap between pre-existing SDB and adverse COVID-19 outcomes, including brain fog. Furthermore, consequences of COVID-19, such as hypoxia, are known to potentiate inflammation and may amplify symptoms associated with COVID-19 resulting in the worsening of existing sleep disorders and/or a new diagnosis of a sleep disorder (Orbea et al., 2021 ). Other factors to assess include history of insomnia prior to COVID-19, poor sleep hygiene, and previous history of obstructive sleep apnea. Lastly, patients experiencing psychological distress may manifest as insomnia or other SDB.

Sleep disorders are known to have an impact on cognition—especially in the domains of attention and processing speed. These cognitive domains are also affected in patients recovering from COVID-19. While research focuses on understanding the interplay between SDB and COVID-19, clinical evaluation and treatment plans for patients with brain fog post COVID-19 should include screening for sleep disorders and general sleep quality.

Psychological Factors

Disorders such as depression, anxiety, and post-traumatic stress disorder (PTSD) are all concerns for patients following infection with COVID-19 and should be considered when approaching a patient with brain fog. A recent meta-analysis (Deng et al., 2021 ) showed a pooled prevalence of 45% for depression and 47% for anxiety in patients diagnosed with COVID-19. A large retrospective cohort study of patients in the 6 months following COVID-19 diagnosis (Taquet et al., 2021 ) revealed higher incidence of first onset mood, anxiety, and psychotic disorders for patients who had a COVID-19 diagnosis compared to patients with influenza or with another respiratory tract infection. Overall, this study reported prevalence of any mood, anxiety, or psychotic disorder at 23.98% and first onset of any of these disorders at 8.63%. Another study estimated prevalence for PTSD at 6.5% in patients diagnosed with COVID-19 within 2 months of infection, which is higher than for patients diagnosed with other respiratory illnesses (Horn et al., 2020 ).

Preliminary research suggests cognitive changes and mood symptoms are associated in patients recovered from COVID-19 (Almeria et al., 2020 ). In this small study of previously hospitalized patients diagnosed with COVID-19 assessed 10-35 days after discharge, cognitive complaints were associated with increased anxiety and depression. This association may indicate patients are experiencing distress because of cognitive symptoms, and this is consistent with our clinical observations. However, it also is important to note that poor concentration is a common diagnostic criterion for many mood and anxiety disorders. In addition, depression has been associated with a wide array of cognitive impairments including global cognition, episodic memory, executive functioning, processing speed, visuospatial memory, attention, and working memory as summarized in a recent systematic review (Jamieson et al., 2019 ). Therefore, a careful assessment of psychological factors is needed to disentangle symptoms when making a differential diagnosis.

Neuroinflammation

Recent clinical observations and research suggest much of the COVID-19 complications are also inflammatory-based (Calabrese, 2020 ). One treatment option is to reduce neuroinflammation by augmenting lifestyle practices, starting with nutrition to treat the symptoms associated with brain fog. Poor-quality food that is high in simple carbohydrates, trans fat, food additives and low in nutrient density has been associated with increased systemic inflammation and neuroinflammation. Research on the gut-brain axis further demonstrates that the nervous system between the gut and brain are intimately connected. Nutrient deficiency is common among Americans four years and older. Even with fortified food and supplements, 70% of Americans remain vitamin D deficient (Drake, 2017 ).

Among patients with high risk for COVID-19 complications or PASC, those with a significant number of pre-existing medical conditions are often treated with polypharmacy, which has also been related to micronutrient deficiency (Mohn et al., 2018 ). For example, long-term use metformin, a common antidiabetic medicine, has been associated with vitamin B12 deficiency, which is a nutrient critical for nerve health. These factors highlight the importance of consideration of a referral to a qualified expert, such as a registered dietitian, for nutrition management following chronic illnesses, which could help in alleviating neuroinflammation associated with brain fog post COVID-19.

Ms. Smith in our vignette has multiple chronic illnesses prior to COVID-19, including hypertension, hyperlipidemia, and diabetes. Furthermore, she reported a recent diagnosis of vitamin B12 deficiency and had started taking supplements. She attributed her 30-pound weight gain to changes in her eating habits (i.e., increased intake of sweets and fried food) to cope with depressive symptoms, and decreased exercise. Thus, a referral to a registered dietitian is indicated. Decreasing her recently elevated BMI through work with a registered dietitian could help decrease some inflammation, which may help with symptoms of brain fog.

Evidence-Based Assessment or Practice Considerations For Health Service Psychologists

Given the many facets of brain fog in COVID-19 and hypotheses on potential mechanisms, it can be difficult to design a pre-packaged intervention plan for health service psychologists that will work for all patients with PASC. However, there are some primary tenets to consider within each factor described below that are known to be associated with brain fog in COVID-19.

Neuropsychological Evaluation

Neuropsychological evaluations are designed to detect cognitive impairments compared to an individual’s peer group. They can also serve as a measurable outcome to address the impact of interventions in the treatment of brain fog post COVID-19. Research on cognition in PASC suggests that patients with mild symptoms generally demonstrate minimal deficits in attention or executive function or may perform within the expected range (i.e., are cognitively intact). The latter can be attributed to the structured nature of the test setting with a quiet environment and minimal distractions. While it is possible that neuropsychological evaluations may be less sensitive to cognitive changes during the COVID-19 recovery process than detecting differences in functioning pre-illness, it is still worthwhile to assess throughout the treatment process. The cognitive complaints associated with psychological disorders, sleep disordered breathing, and signs of neuroinflammation may still be associated with notable changes for an individual patient and will inform the treatment process.

While the effects of COVID-19 on neural structures are still being investigated, there is a precedent for an association between self-reported cognitive symptoms and psychological disorders in the concussion/mild traumatic brain injury literature (Venkatesan & Ramanathan-Elion, 2021 ) and may provide valuable information in the treatment of PASC and brain fog.

For example, cognitive rehabilitation for traumatic brain injury is often recommended for individuals with cognitive complaints and includes a component of patient education or “psychoeducation” along with training of cognitive skills deemed to be a weakness for that individual. Clinicians may use this concept in treatment for individuals presenting with brain fog to include an educational component to provide an overview of brain fog. This psychoeducation can include the definition of brain fog, possible etiology, and general factors that can impact the recovery process. When this psychoeducation is supported with group intervention with patient’s peers, the validation, reassurance, and access to qualified health care providers can facilitate the recovery process (Venkatesan & Ramanathan-Elion, 2021 ).

Another component of cognitive rehabilitation for traumatic brain injury that may apply to brain fog is remediation. This aspect relies on the neuropsychological assessment to determine areas of cognitive deficits or weaknesses. The goal here is to help the patient learn compensatory strategies consistent with the areas of cognitive impairment identified. For example, if attention is impaired, cognitive remediation would include providing cognitive strategies for poor attention such as prioritizing, reducing distractions, or working with patients on attention process training (Cicerone et al., 2019 ).

While patients with brain fog following COVID-19 are different from traumatic brain injury, there are some common characteristics in the rehabilitation of cognitive symptoms that can be generalized across disorders. Physical exercise is often a useful component in rehabilitation of attention and processing speed as well as mood symptoms. Patients with PASC are encouraged to increase physical activities, starting with gentle exercises such as walking, chair yoga, or stretching, and to increase their activity as tolerated. These suggestions may be helpful for health service psychologists to include in their resources to aid in the recovery from brain fog in PASC.

Mental Health Assessment & Psychotherapy

Assessment of mental health history prior to infection with COVID-19 is an important factor in understanding potential etiologies and interventions for cognitive symptoms. This can be completed using mental health screening measures such as the Generalized Anxiety Disorder–7 (GAD-7; Spitzer et al., 2006 ), Patient Health Questionnaire–9 (PHQ-9; Kroenke et al., 2001 ), and the Patient-Reported Outcomes Measurement Information System (PROMIS; Hays et al., 2009 ) Global Health Questionnaire. If patients indicate suicidal ideation, the Columbia Suicide Severity Rating Scale (CSSRS; Posner et al., 2011 ) can be administered to assess for severity and risk. Additionally, if patients present with trauma symptoms such as nightmares, hyperarousal, and avoidance of anything that reminds them of their experience having COVID-19, a brief screening tool such as the Primary Care PTSD Screen for DSM-5 (PC-PTSD 5; Prins et al., 2015 ) can be given. These questionnaires provide measurable markers of mood symptoms, facilitate appropriate referrals to specialists, and assist in tracking change in symptoms over time. These screeners are recommendations for what is used frequently in our clinic. Health service psychologists may choose to use other screeners for assessing mood symptoms and suicide risk as they deem necessary.

Both patients with previous mental health history experiencing relapse of mental health symptoms following COVID-19 illness and patients with new onset mental health symptoms can benefit from evidence-based psychotherapy. For patients with previous mental health treatment, it can be helpful to review which evidence-based treatments were successful in the past to inform present treatment plans. For example, brief cognitive-behavioral therapy (CBT) may be considered for patients with primarily cognitive complaints without a clinically significant mental health condition to support adjustment to illness or disability. This brief CBT could include the application of skills to manage cognitive complaints. Additionally, patients with milder symptoms who are not interested in individual psychotherapy may benefit from support through formal or informal groups of other people experiencing persistent COVID-19 symptoms. Formal evidence-based group treatment can also help alleviate symptoms, while peer-led support groups may provide connection and decrease feelings of isolation.

Clinically, we have observed distress centered on performance at work in our patients with PASC. Patients often worry that problems with attention, word-finding, and memory will be noticed by supervisors and others at work. In addition to worrying about performance, patients may also report feeling embarrassment about cognitive changes and worry about the judgments of others. They may also feel down and self-critical about changes in perceived workplace performance even if these changes are not detected by others.

With some patients it can be helpful for health service psychologists engaged in evidence-based psychotherapy to determine if there is concrete evidence to support the patient’s report of performance declines at work. When patients are experiencing self-consciousness or social anxiety about cognitive changes, taking steps to see if there is clear evidence for these changes may be beneficial. Then health services psychologists can consider engaging in cognitive restructuring with the patient to help shift the patient’s focus to areas of strength. With patients who have been unable to return to work or have returned with significant changes or limitations in their roles, evidence-based psychotherapy may focus more on self-acceptance, adjustment to change, and cognitive or behavioral strategies to manage or accommodate new limitations.

From a psychological perspective, Ms. Smith, the patient in the vignette, has a previous diagnosis of major depressive disorder and is currently experiencing symptoms of depression and anxiety. Given that, it is appropriate to consider cognitive-behavioral techniques in her treatment plan. This cognitive-behavioral treatment could include normalizing the frustration that she is experiencing, engaging in cognitive restructuring, and identifying healthy self-compassion behaviors that she can engage in when she is struggling.

Sleep Hygiene

Often, the first goal for health service psychologists with respect to sleep is to determine whether the patient’s sleep is disrupted. This can be achieved through sleep questionnaires designed to assess sleep quality. Kong et al. ( 2019 ) provided a great overview of different sleep related questionnaires and their general purposes. For example, some are designed specifically to assess disorders such as insomnia, obstructive sleep apnea, or restless legs syndrome while others have a more general purpose. Results from the screen may warrant a referral to a sleep specialist for further diagnostic clarification. For example, the type of sleep disorder (e.g., insomnia, obstructive sleep apnea) often diagnosed through polysomnography may then determine further treatment. Health service psychologists can help initiate this important step and provide appropriate treatment options to address concerns for insomnia or poor sleep hygiene.

Clinical and Ethical Challenges

Given the multitude of symptoms that constitute brain fog and the diverse etiologies it may represent, patients often struggle to find appropriate resources for treatment. Developing a treatment plan that adequately addresses a patient’s symptoms without overwhelming them can be challenging. From an individual patient perspective, the diversity and persisting nature of symptoms can be isolating. These symptoms can be compounded by the unknown trajectory of the recovery process with a relatively new problem, such as PASC. In addition, support from friends and family may wane over time due to the persisting and complex nature of brain fog.

Symptoms of fatigue that often accompany brain fog can make it challenging to seek professional help while also managing personal and professional demands. For example, patients with inflexible work schedules may not be able to go to health care providers or join the shared appointments easily. This challenge is consistent with prior research on other disorders with chronic presentations (Ocon, 2013 ). Furthermore, patients may experience negative interactions with medical providers who suspect patients of exaggerating their symptoms. Lastly, PASC is often just one of the health issues a patient may be managing. Many patients often present with multiple prior medical and psychiatric comorbidities that also require ongoing treatment, compounding the recovery trajectory.

Diversity Considerations

The prevalence of COVID-19 is higher in Black, Hispanic, and other underrepresented communities—as are mortality rates. Racial disparities have been revealed in healthcare since the beginning of the pandemic highlighting the lack of access to appropriate healthcare facilities for preventative health (Rogers et al., 2020 ). In addition to inequitable access to healthcare, there may be stigma and lack of trust in the healthcare system preventing Black, Hispanic, and other underrepresented Americans from seeking mental health services if they are experiencing these challenges related to PASC. Furthermore, patients from low-income backgrounds may find it financially difficult to maintain key health behaviors, including those related to diet, that may not be covered by health insurance or feasible on a limited budget. When working with patients from underrepresented or low socioeconomic status backgrounds, health service psychologists should assess barriers to treatment including factors discussed here related to stigma and culturally informed care.

Conclusions and Lessons Learned Relating to Vignette

In the vignette, Ms. Smith’s brain fog evaluation began with an assessment of her cognition through neuropsychological tests, which helped determine areas of cognitive impairment and identify strengths and weaknesses. Possible etiologies for the brain fog were identified including undertreated mood disorder, possible sleep disorder, and changes in eating patterns, which prompted referrals to a psychologist, sleep disorder specialist, and a registered dietitian respectively.

Brain fog is a common symptom that patients may report to health service psychologists when recovering from COVID-19 infection. In fact, it is one of the most common complaints in PASC. Using our clinical practice as a model, this paper provides readers with a rubric of four factors to consider in patients with brain fog post COVID-19 that can aid in the recovery process. First, in some patients with complaints of brain fog, especially those who required intensive care at the acute stage, it is important to rule out neurological causes of brain fog such as strokes and seizures that may warrant additional evaluation and medications. Second, when those factors are better controlled or have been ruled out, we advocate for a multi-prong approach for the evaluation of (1) cognition, (2) neuroinflammation markers, (3) psychological factors, and (4) sleep disorders in the treatment of brain fog. Each patient will likely need an individualized approach to treat brain fog as the four components may not be applicable to all. Third, we encourage health service psychologists to use the factors outlined here as a rubric for the initial evaluation and for determining further referrals based on two broad categories: (a) the patient—their medical and psychiatric history, current symptoms, their goals and motivation to improve, and their limitations (inflexible work schedules or financial constraints), and (b) the health service psychologist’s ability to treat these symptoms or make appropriate referrals. Fourth, while some health service psychologists may be well-trained to manage sleep, mood, and related disorders, they should keep in mind referrals to specialists as outlined in this paper.

In conclusion, Ms. Smith’s vignette represents many of the complications that patients are reporting when experiencing post-COVID-19 symptoms. These symptoms can be extremely distressing to patients and present unique challenges to health service psychologists because research is still developing in treating brain fog post COVID-19. Utilizing the information that we presented in this paper, it is encouraged that providers take a multi- disciplinary approach when assessing patients to make appropriate treatment recommendations. A team approach with appropriate referrals and opportunities for interdisciplinary consultation can provide optimal resources for the patient to receive services to recover from brain fog post COVID-19.

Key Clinical Considerations

Brain fog is a common symptom post COVID-19. A multi-disciplinary approach to addressing brain fog is paramount to a patient’s success.

Cognitive impairment may be present in patients post COVID-19, even among those who did not require hospitalization at the acute stage.

Appropriate psychological assessment and treatment of metal health conditions associated with and/or exacerbated by persistent symptoms post COVID-19 is important.

Neuropsychological evaluations may be helpful in quantifying the cognitive disorder.

Assessing adequacy of treatable lifestyle factors and educating patients with tools to optimize health behaviors including stress management, sleep quality, and exercise is critical in managing chronic disease such as PASC and brain fog.

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Krishnan, K., Lin, Y., Prewitt, KR.M. et al. Multidisciplinary Approach to Brain Fog and Related Persisting Symptoms Post COVID-19. J Health Serv Psychol 48 , 31–38 (2022). https://doi.org/10.1007/s42843-022-00056-7

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Brain fog after COVID-19 has similarities to ‘chemo brain,’ Stanford-led study finds

Researchers found that damage to the brain’s white matter after COVID-19 resembles that seen after cancer chemotherapy, raising hope for treatments to help both conditions.

June 13, 2022 - By Erin Digitale

Researchers at Stanford Medicine have found biological similarities between "chemo brain" — cognitive impairment from cancer treatment — and brain fog after COVID-19. Jolygon/Shutterstock.com

Brain fog after COVID-19 is biologically similar to cognitive impairment caused by cancer chemotherapy, something doctors often refer to as “chemo brain.” In both cases, excessive inflammation damages the same brain cells and processes, according to research led by  Stanford University School of Medicine .

The discovery, described in a paper that published online June 12 in  Cell , relied on studies of mice with mild SARS-CoV-2 infection and postmortem human brain tissue collected early in the pandemic. The findings may help guide treatments for cognitive effects of COVID-19, the scientists said.

“We found that even mild COVID can cause prominent inflammation in the brain that dysregulates brain cells and would be expected to contribute to cognitive impairment,” said  Michelle Monje , MD, PhD, professor of neurology and neurological sciences.

Monje shares senior authorship of the study with Akiko Iwasaki, PhD, professor of immunology and of molecular, cellular and developmental biology at Yale University. The study’s lead authors are  Anthony Fernandez-Castaneda , PhD, a postdoctoral scholar at Stanford;  Anna Geraghty , PhD, an instructor of neurology at Stanford; and Peiwen Lu, PhD, and graduate student Eric Song, both of Yale.

The overlap between what happens in COVID-19’s cognitive aftermath and chemo brain, as it’s colloquially known, could be good news for patients because it may speed research on treatments, Monje said. “The exciting message is that because the pathophysiology is so similar, the last couple of decades in cancer therapy-related research can guide us to treatments that may help COVID brain fog.”

Nerves’ insulation damaged

Monje’s team has spent two decades studying cognitive impairment after cancer. They uncovered key details in how chemotherapy impairs the function of the brain’s white matter, regions of the brain normally rich in well-insulated nerve fibers that quickly transmit signals from one place to another. Myelin, the fatty coating insulating the long arms of the neurons, helps speed the transmission of nerve signals. In chemo brain, damage to myelin slows their transmission.

“When the pandemic started, I started worrying that we would see similar neurological consequences of this profoundly immunogenic virus,” Monje said. Because the virus caused such a strong immune response, including widespread inflammation, she suspected it might also cause cognitive problems.

Many COVID-19 survivors experience cognitive impairment. Stanford research published in March 2021, covering the first year of the pandemic, found that about one in four COVID-19 patients had cognitive symptoms that lingered at least two months, even after mild infections. Patients’ symptoms included impairments to attention, concentration, memory and executive function, as well as slower information processing — all of which are also common among people who experience chemo brain after cancer treatment.

Monje and her colleagues examined brain changes in mice in which the researchers had induced SARS-CoV-2 infections confined to the respiratory system. Mice lack the cellular receptors that the SARS-CoV-2 virus uses to invade human cells, but animals in the study were genetically engineered to express the necessary receptors in the respiratory tract. After exposure to SARS-CoV-2, the mice had mild infections: They did not lose weight or behave as though they were ill, and the virus was not found in their brains.

Michelle Monje

Nevertheless, scientists saw more of several inflammatory cytokines in the blood and cerebrospinal fluid of the mice, increases that could be detected one and seven weeks after infection. In their white matter, the microglia — brain cells that support neurons and “eat” cellular debris in the brain — were much more active than normal, an abnormality that persisted seven weeks after infection.

After mild COVID-19, analysis of gene activity in single cells uncovered more microglia with high levels of pro-inflammatory molecules called chemokines and more activity in genes involved in inflammation. The genes expressed in microglia after COVID-19 overlapped closely with those expressed by microglia in other disease contexts, including cognitive decline in aging and in neurological conditions such as Alzheimer’s disease. This finding lines up with prior work linking microglial reactivity to poor cognitive function.

Microglial reactivity was particularly high in the hippocampus, a brain center involved in learning and memory. The researchers found that one of the elevated chemokines called CCL11 can directly cause microglial reactivity specifically in the hippocampus. The formation of new neurons in the hippocampus of the mice was impaired, likely due to the cytokine changes and the increased reactivity of microglia.

After infection, the mice also showed changes among cells in the white matter that help coat the neurons in insulating myelin. The cells that create myelin, called oligodendrocytes, were harmed by mild COVID-19, with the number of mature oligodendrocytes and cells destined to be oligodendrocytes declining in the brains of mice following SARS-CoV-2 infection. The researchers also found a loss of myelin, evident as a decrease in the density of myelinated axons in the white matter, which could be detected by one week and persisted seven weeks after infection.

Because other viral infections can cause brain inflammation, the researchers studied brain changes in mice after mild respiratory infection with H1N1 influenza, the viral strain that caused the 2009 “swine flu” and 1918 “Spanish flu” pandemics. The goal was to compare cognition-linked molecular changes after H1N1 to those seen after COVID-19. One week after infection, the H1N1 flu and SARS-CoV-2 infections caused similar patterns of cytokine elevation in the central nervous system, microglial reactivity and loss of oligodendrocytes in white matter. But seven weeks after infection, although the cytokine profiles had some overlap, including increased inflammatory chemokine CCL11, they differed. Effects on the hippocampus were similar in the two types of infections, but microglial reactivity and oligodendrocyte loss in white matter were not present after seven weeks following H1N1 infection.

The shorter-lasting and less-severe brain changes seen in mice after H1N1 infection are consistent with less prevalent reports of cognitive symptoms after this type of infection, highlighting that respiratory infections can change the brain even if the virus does not infect the brain, the researchers said.

Human data similar to animal findings

To further confirm their findings, the researchers examined data from brain tissue collected from a small group of people who had died suddenly in New York City in the spring of 2020. The human brain tissue came from five people who died with incidental SARS-CoV-2 infection (meaning they died for reasons that may have been unrelated to COVID-19, such as accidents); four people who died with known COVID-19 symptoms, including two who had been hospitalized in intensive care; and nine people in the control group who died without SARS-CoV-2 infection. People with SARS-CoV-2 infection were examined for lung injury and were not found to have had the most severe form of pneumonia. These people had no evidence of brain infection. However, those with COVID-19 had greater microglial reactivity than those in the control group, in a pattern that matched what was found in the mice.

In another group of 48 people who developed long COVID-19 with cognitive symptoms, the inflammatory cytokine CCL11 blood levels were elevated compared with those of 15 long- COVID patients who did not have cognitive symptoms.

Monje’s team is already conducting research on medications that could alleviate brain fog after chemotherapy, and they plan to investigate whether these drugs are helpful after SARS-CoV-2 infection.

“While there are many similarities to cognitive impairment after cancer, there are probably differences, too,” she said. “We need to test any potential therapies explicitly for COVID.”

Monje is a member of  Stanford Bio-X , the  Stanford Institute for Stem Cell Biology and Regenerative Medicine , Stanford’s  Maternal and Child Health Research Institute , the  Stanford Cancer Institute , and the  Stanford Wu Tsai Neurosciences Institute .

Scientists from Yale University, the National Institute of Neurological Disorders and Stroke, the Mount Sinai School of Medicine, New York University Grossman School of Medicine, the National Cancer Institute, the Uniformed Services University of Health Sciences, University of Iowa, the Office of the Chief Medical Examiner (New York City), and the Howard Hughes Medical Institute (at Yale and at Stanford) also contributed to the research.

The research was supported by the National Institute of Neurological Disorders and Stroke (grants R01NS092597, NS003130 and NS003157), the National Institute of Allergy and Infectious Diseases (grant R01AI157488), an NIH Director’s Pioneer Award (DP1NS111132), the Robert J. Kleberg, Jr. and Helen C. Kleberg Foundation, Cancer Research UK, the Waxman Family Research Fund, Fast Grant for Emergent Ventures at the Mercatus Center, and the Howard Hughes Medical Institute.

About Stanford Medicine

Stanford Medicine is an integrated academic health system comprising the Stanford School of Medicine and adult and pediatric health care delivery systems. Together, they harness the full potential of biomedicine through collaborative research, education and clinical care for patients. For more information, please visit med.stanford.edu .

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Comprehensive clinical characterisation of brain fog in adults reporting long covid symptoms.

1. Introduction

2. methods and materials, 2.1. study and cohort description, 2.2. procedures, 2.2.1. demographics, 2.2.2. symptomatology, 2.2.3. computer-assisted cognitive tasks, 2.2.4. neurocardiovascular assessment, 2.2.5. physical performance assessments, 2.3. statistical analyses, 2.4. ethical approval, 3.1. sociodemographics and medical history, 3.2. long covid symptomatology, 3.3. battery of clinical assessments, 3.3.1. computer-assisted cognitive tasks, 3.3.2. neurocardiovascular assessment, 3.3.3. gait assessments, 3.3.4. strength assessments, 3.4. multivariable analyses, 3.4.1. binary logistic regression model, 3.4.2. cluster analysis, 3.4.3. structural equation model, 4. discussion, 4.1. statement of principal findings, 4.2. strengths and weaknesses of the study, 4.3. meaning of the study, 4.4. unanswered questions and future research, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Jennings, G.; Monaghan, A.; Xue, F.; Duggan, E.; Romero-Ortuño, R. Comprehensive Clinical Characterisation of Brain Fog in Adults Reporting Long COVID Symptoms. J. Clin. Med. 2022 , 11 , 3440. https://doi.org/10.3390/jcm11123440

Jennings G, Monaghan A, Xue F, Duggan E, Romero-Ortuño R. Comprehensive Clinical Characterisation of Brain Fog in Adults Reporting Long COVID Symptoms. Journal of Clinical Medicine . 2022; 11(12):3440. https://doi.org/10.3390/jcm11123440

Jennings, Glenn, Ann Monaghan, Feng Xue, Eoin Duggan, and Román Romero-Ortuño. 2022. "Comprehensive Clinical Characterisation of Brain Fog in Adults Reporting Long COVID Symptoms" Journal of Clinical Medicine 11, no. 12: 3440. https://doi.org/10.3390/jcm11123440

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• http://orcid.org/0000-0001-9839-6549 Laura McWhirter
• Centre for Clinical Brain Sciences , University of Edinburgh , Edinburgh , UK
• Correspondence to Dr Laura McWhirter; laura.mcwhirter{at}ed.ac.uk

‘Brain fog’ is a term that patients use increasingly frequently in the neurology clinic. We may think that we know what patients are talking about but at least some of the time we are likely to be getting it wrong. Patients use the term ‘brain fog’ to describe a wide range of subjective phenomena and symptoms. This paper suggests useful lines of questioning, and discusses the clinical correlates of a range of common ‘brain fog’ experiences.

• neuropsychiatry
• clinical neurology
• chronic fatigue syndrome

Data availability statement

No data are available.

https://doi.org/10.1136/pn-2024-004112

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Contributors This manuscript is the sole work of LM.

Funding LM has previously received funding from the Scottish Government Chief Scientist Office to undertake clinical research into post-COVID symptoms.

Competing interests LM is secretary (unpaid) of the British Neuropsychiatry Association. LM undertakes paid expert witness work in court cases on neuropsychiatric matters. LM has previously received funding from the Scottish Government Chief Scientist Office to undertake clinical research into post-COVID symptoms. No current research funding.

Provenance and peer review Commissioned; externally peer reviewed by Biba Stanton, London, UK, and Jonathan Schott, London, UK.

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Language: English | French

Understanding the Experience and Impacts of Brain Fog in Chronic Pain: A Scoping Review

Ronessa dass.

a School of Rehabilitation Sciences, McMaster University, Hamilton, Ontario, Canada

Mohini Kalia

b Faculty of Sciences, Carleton University, Ottawa, Ontario, Canada

Jocelyn Harris

Tara packham, introduction.

Approximately 15% to 40% of persons with chronic pain as a primary disorder experience brain fog. Prior research has investigated the etiology of “brain fog” in conditions in which pain presents as a key feature (e.g., fibromyalgia). However, it remains understudied in the context of chronic 10 musculoskeletal pain. Following current scoping review guidelines, we obtained stakeholder input from patient and health care professionals (HCPs) to define this phenomenon. Specific aims of this review were to (1) identify factors contributing to brain fog, (2) identify the functional correlates of brain fog and assessments used to measure them, and (3) establish a definition of brain fog that can be employed by researchers and HCPs to advance research and care.

A scoping review was conducted using recommendations of the Joanna Briggs Institute methodology of scoping reviews and the Levac et al methodology. Embase, Cinahl, PsycINFO, and Medline was searched to identify relevant sources. Findings were verified with patient and healthcare professionals.

We identified four 15 key features of brain fog: perceived variability, subjective cognitive dysfunction, participation limitations, and changes in functional activities. We developed a model of brain fog illustrating the overlapping categories of contributors to brain fog in chronic musculoskeletal pain: (1) neuroanatomical and neurophysiological, (2) mental health/emotional, and (3) environmental/lifestyle.

The results of this scoping review conclude that the inconsistency in research regarding brain fog in 20 chronic musculoskeletal pain is obstructing a clear understanding of the phenomenon and therefore may be impeding persons with chronic pain and brain fog from receiving optimal care.

RÉSUMÉ

Introduction: Environ 15 % à 40 % des personnes souffrant de douleur chronique en tant que trouble primaire ressentent un brouillard cérébral. Des recherches antérieures ont étudié l’étiologie du « brouillard cérébral » dans des affections dans lesquelles la douleur se présente comme une caractéristique clé (par exemple, la fibromyalgie). Cependant, elle reste sous-étudiée dans le contexte de la douleur musculo-squelettiques chronique. Conformément aux lignes directrices actuelles en matière d’examen de la portée, nous avons obtenu les commentaires des parties prenantes provenant de patients et de professionnels de la santé (PS) pour définir ce phénomène. Les objectifs spécifiques de cet examen étaient de (1) déterminer les facteurs contribuant au brouillard cérébral, (2) déterminer les corrélats fonctionnels du brouillard cérébral et les évaluations utilisées pour les mesurer, et (3) établir une définition du brouillard cérébral qui peut être utilisée par les chercheurs et les professionnels de la santé pour faire progresser la recherche et les soins.

Méthodes: Un examen de la portée a été mené en utilisant les recommandations de la méthodologie pour les examens de la portée de l’Institut Joanna Briggs et de la méthodologie de Levac et al. Des recherches ont été effectuées dans Embase, Cinahl, PsycINFO et Medline pour réertorier les sources pertinentes. Les résultats ont été vérifiés auprès des patients et des professionnels de la santé.

Résultats: Nous avons recensé quatre caractéristiques clés du brouillard cérébral : la variabilité perçue, le dysfonctionnement cognitif subjectif, les limites à la participation et les changements dans les activités fonctionnelles. Nous avons élaboré un modèle de brouillard cérébral illustrant les catégories se de facteurs contributeurs au brouillard cérébral dans le système musculo-squelettique chronique Douleur qui se chevauchent : (1) neuroanatomique et neurophysiologique, (2) santé mentale/émotionnelle, et (3) environnement/mode de vie.

Conclusion: Les résultats de cet examen de la portée concluent que l’incohérence de la recherche en ce qui concerne le brouillard cérébral dans la douleur musculo-squelettique chronique ne permet pas d’avoir une compréhension claire du phénomène et peut donc empêcher les personnes souffrant de douleur chronique et de brouillard cérébral de recevoir des soins optimaux.

“Brain fog” is a term used in both social discourses and the literature to describe a subjective phenomenon of perceived cognitive dysfunction. Brain fog is a multifaceted experience associated with numerous conditions where chronic pain is also a key feature. Approximately 15% to 40% of individuals with chronic pain as a primary disorder experience brain fog. 1 Chronic pain is a life-altering condition that affects one’s physical, cognitive, emotional, and social well-being, and the experience of brain fog may further worsen quality of life. 2 Seventeen to 29% of individuals with chronic pain may also experience comorbid mental health disorders: it has been posited these mental health changes may worsen their cognitive capacity and increase the likelihood of experiencing brain fog. 3

Brain fog does not have a widely accepted definition in the scholarly literature and is most often referred to as issues with attention, memory, and thinking. 4 One prior narrative review has investigated the etiology of “brain fog” in fibromyalgia, autoimmune disorders, and postural tachycardia syndrome; however, brain fog has yet to be studied in the specific context of chronic pain. 4 Previous studies have drawn associations between brain fog and memory, attention, and executive function. 4 However, the potential mechanisms of brain fog in chronic musculoskeletal pain are further obscured by unclear relationships to neuroplasticity, central sensitization, and other changes in brain structure and functional connectivity associated with both primary and secondary chronic pain conditions. 5 , 6

Because brain fog may originate differently depending on the specific disorder, it is necessary to understand its development in chronic musculoskeletal pain. For example, some disorders, such as lupus, have no defined biomarker for brain fog. 7 In long COVID, where COVID-19 symptoms persist for 4 weeks or longer, evolving understanding suggests that decreases in oxygen availability impair mitochondrial functioning, leading to perceived cognitive dysfunction and periods of brain fog. 8 , 9 In most cases, disorders have several pathologies that may contribute to the experience of brain fog.

Further, symptoms and severity of brain fog may vary depending on the disorder and based on individual differences and activity demands. In chronic fatigue syndrome, patients often describe brain fog as a generalized “exaggerated state of exhaustion” 10 (p4) However, symptoms may be more specific in some conditions, such as celiac disease, where brain fog is believed to result in slowed executive function. 11 Similarly, in fibromyalgia, “fibro-fog” is commonly associated with issues in executive function, attention, and memory. 4 Frequency and severity also differ based on condition. Ninety percent of patients with neuropsychiatric disorders experience brain fog every day, 12 whereas patients with COVID-19 may experience brain fog temporarily and infrequently. 8

Though nonprimary sources have addressed causes and treatment for brain fog in chronic musculoskeletal pain, 9 , 13 few studies have actively investigated the topic. Additionally, there have been models developed to explain specific cognitive disruptions in pain, such as Legrain and colleagues’ neurocognitive model of attention to pain. 14 However, brain fog has not been explicitly described. 14 Thus, the overarching objective of this review is to investigate the scope and nature of the medical literature defining the concept of brain fog and its corresponding perceived cognitive impairments in persons with chronic pain. For the purpose of this article, all future mentions of chronic pain will refer to primary chronic musculoskeletal pain. Research aims included (1) identifying factors contributing to brain fog, (2) identifying the functional correlates of brain fog and assessments used to measure them, and (3) establishing a definition of brain fog that can be employed by researchers and health care professionals (HCPs).

The findings of these aims can support researchers in investigating brain fog in persons with chronic pain, by providing a definition to include it as an outcome in future studies. In turn, this may assist with the development of reliable assessment measures and effective interventions to help persons with chronic pain manage symptoms of brain fog.

Scoping reviews are a form of evidence synthesis that focus on identifying the breadth of knowledge and types of sources on a topic; quality of these sources is not evaluated. 15 This form of review can be useful to map what is known, identify gaps, and consolidate terminology. 16 We therefore elected to conduct a scoping review, drawing on the recommended methods from the Joanna Briggs Institute methodology for scoping reviews. 15 This review was also informed by Levac et al.’s methodology 17 and sought triangulation of the findings and conclusions from health professionals and lived experience partners.

Search Strategy

Before beginning any formal search or study screening, a nonexhaustive search of the literature was used to inform a working definition of brain fog. We formulated the following initial definition: “‘Brain fog’ is the term used in the literature to identify a poorly defined phenomenon representing possible variable states of perceived cognitive dysfunction leading to challenges in the day-to-day application of cognitive skills in individuals’ participation in daily activities.” Then, following Levac et al.’s methodology, 17 this definition was provided to four patient partners and two HCPs specializing in chronic pain. These stakeholders were asked to critically analyze and refine the initial definition. Stakeholders were asked to refine the definition because the initial definition was based upon a rough search of the literature. The authors wanted to ensure that the proposed definition was reflective of patient and HCP perspectives. As a result, we reformulated our working definition for brain fog as “a phenomenon of fluctuating states of perceived cognitive dysfunction that could have implications in the functional application of cognitive skills in people’s participation in daily activities” (see Figure 1 for elaboration). Key features of this definition include possible variability, participation limits, perceived cognitive dysfunction, and functional activities, as highlighted in Figure 1 .

Working definition of brain fog and embedded constructs.

The formal search strategy was developed along alongside a librarian and was translated into four electronic health databases: MEDLINE, EMBASE, CINAHL, and PsycINFO. Twenty-seven keywords were identified related to the two main subject areas: (1) chronic pain and (2) brain fog or cognitive dysfunction. Keywords were identified from the literature and patient perspectives. Because our initial nonsystematic search of the literature suggested that brain fog was not explicitly referenced or used as a keyword in studies, a comprehensive list of cognition terms was combined with dysfunction terms (see Appendix A for details). Keywords were combined through Boolean logic terms “AND” and “OR.” Searches were limited to items published by June 6, 2020, when the draft protocol was posted to osf.org ( https://osf.io/svr7t ) and was updated July 18, 2022. References were exported to the citation manager Mendeley 16 for deduplication and then to Covidence 18 to facilitate and track the review process.

Eligibility Criteria

The same eligibility criteria were used for both abstract and full-text screening.

All selected studies met the following inclusion criteria: (1) sources with participants diagnosed with chronic pain as their primary diagnosis and who are experiencing brain fog or symptoms concordant with our working definition, (2) sources written in English, (3) peer-reviewed primary data sources, and (4) either peer-reviewed or non-peer-reviewed secondary data sources, including reviews. As recommended by the Joanna Briggs Institute, secondary data (e.g., systematic and meta-analytical reviews) are useful sources of information in scoping reviews because they assist in providing a comprehensive understanding of a broader area of knowledge. 15 Studies were excluded if they primarily focused on participants younger than age 18 because youth may have underdeveloped cognitive abilities in comparison to adult populations. 19 Similarly, studies focusing on adults older than 65 were excluded because cognitive abilities change with age. 19 Sources describing participants with chronic pain as a symptom of their primary disorder (e.g., irritable bowel syndrome) were excluded because these disorders were not the main focus of the review and may have complicating comorbidities and their own specific variation of the concept of brain fog. Next, we excluded studies concentrating on participants with traumatic brain injuries, neurodevelopmental disorders (e.g., autism spectrum disorder) or other cognition-impairing disorders (e.g., dementia) because these conditions may have unique effects on cognition that may confound the potential effects of pain. 19 , 20 Sources that primarily investigated changes in cognition due to medication were excluded. Additionally, sources for which full text could not be obtained were excluded; however, attempts to contact authors were made using e-mail and professional networking sites such as ResearchGate and LinkedIn. Lastly, we excluded gray literature (e.g., blog post, books, scripts, conference abstracts, etc.). We report that this is a deviation from our published protocol, because it was initially stated we would include gray literature such as dissertations and opinion papers. Upon screening, the authors decided to limit the inclusion criteria to peer-reviewed papers only to support the quality of reported results.

Titles and study abstracts were independently screened by two reviewers (R.D. and M.K.). Studies selected for full-text screening were independently analyzed by two reviewers (R.D. and M.K.). Conflicts from all stages were resolved by discussion between all three reviewers (R.D., M.K., and T.P.).

Data Collection

The study design characteristics extracted included (1) author and year, (2) type of study and study rating as suggested by the Centre for Evidence-Based Medicine, 21 (3) sample size, (4) type of task and/or treatment, 22 (5) method of analysis, and (6) professionals involved. Patient demographic information was compiled, including sex, race, pain diagnosis, socioeconomic status, and age. Further, available detailed information on brain fog was extracted: (a) any definition of brain fog, (b) cognitive ability measurements, (c) sleep measurements, and (d) quality of life measurements and effects. These categories were informed by the constructs we identified within our working definition of brain fog (see Figure 1 ). We also extracted information to inform future studies including proposed next steps for research, described evidence gaps, and study implications and limitations.

Study Selection

The electronic search yielded 4869 abstracts for screening after removal of duplicates (see Figure 2 for PRISMA [Preferred Reporting Items for Systematic Reviews and Meta-Analyses] diagram). A final total of 79 papers were included for data extraction.

Prisma diagram.

Thematic Summary

The thematic summary was conducted through an iterative process, following guidance of Braun and Clark. 23 After familiarization with the extracted data, two authors (R.D. and M.K.) independently noted patterns and salient themes in the data. The themes were further refined through regular meetings and discussion with the research team for crystallization 23 until consensus was achieved.

Description of Studies

The literature identified relied on quantitative methods with the exception of a sole qualitative paper that described a focus group exploring the experience of exercise in persons with fibromyalgia. 24 A broad spectrum of empirical study designs was recorded, including three meta-analytical reviews, 25–27 two systematic reviews, 28 , 29 three reviews, 30–32 and three randomized controlled trials (RCTs) 33–35 ; however, the majority were lower levels of evidence such as cross-sectional ( n = 55) or uncontrolled cohort designs ( n = 2) exploring some aspect of cognition, attention, judgment, or memory in persons with chronic pain (see Appendix B for a complete account of the designs and foci and additional study information).

Description of Population

The majority of the studies included female participants with either chronic pain or fibromyalgia. The exception was studies investigating low back pain, which generally consisted of equal numbers of males and females or included comparatively more male subjects. 36–38 Mean age of chronic pain manifestation ranged from 32.9 to 48.4 years of age. For fibromyalgia, this was slightly later: patients developed symptoms starting at 38.0 to 52.0 years old. Though most studies primarily included White participants, some literature investigated chronic pain symptoms among different ethnicities. Though socioeconomic status and education were not frequently addressed in the collected literature, one study stated that pain symptoms were more common in patients with an annual income of at least $45,000. 39 Two studies reported that chronic pain symptoms in their samples were more frequent in individuals who had obtained either secondary or university education. 40 , 41

How Is Brain Fog Currently Defined in the Literature?

Of the 79 papers, the majority ( n = 78) of articles did not explicitly define brain fog (see Appendix B for a summary table for included papers). Eight papers defined fibro-fog as a specific phenomenon in patients diagnosed with fibromyalgia. 27 , 40 , 42–47 Fibro-fog has been broadly described as cognitive impairments in fibromyalgia 27 , 47 , 48 ; however, the most common features include issues with attention and memory. 45 , 46 For example, Gunendi et al. 44 described fibro-fog as a state of impaired central processing of sensory stimuli characterized by difficulty focusing attention, remembering new information, making decisions, and performing tasks. Glass et al 43 suggested that it was primarily patients who called problems with memory and concentration fibro-fog but suggested that “dyscognition” was the term used more often in the medical literature. 30 , 43 A single study offered brain fog as a synonym for fibro-fog, noting that it represented neuropsychological changes including memory, concentration, and attention deficits. 49 Williams et al. studied cognitive dysfunction in fibromyalgia with a focus on elucidating the multiple experiences and broad spectrum of patient reports related to dyscognition or fibro-fog, arguing that it was more than memory problems. 50 Interestingly, the publication listed brain fog as a keyword in addition to fibro-fog; however, the main manuscript failed to use the term brain fog. 50

Taylor et al. used brain fog in their survey as a plain-language synonym for cognitive dysfunction but did not provide a definition to either survey participants or in their manuscript. 51 Two additional papers used the term brain fog related to refer to cognitive changes; however, they did not explicitly define it, nor was brain fog the main focus of either article. 43 , 51

From these definitions and descriptions, we identified three overlapping categories to organize factors contributing to brain fog in chronic pain: neurophysiological, mental health and emotional, and environmental/lifestyle factors. This thematic summary is depicted in Figure 2 , with all papers corresponding to the brain fog factors ( Figure 3a,b ).

Brainfog contributors model.

Does Brain Fog Vary across Chronic Pain States?

The majority of papers included in this review used homogenous patient samples, with persons having the same diagnosis and at times even came from the same clinic or community. 45 Few studies directly compared different pain populations; however, some papers did find cognitive differences between pain groups. 52–59 Koutanji et al. compared pain interference in cognition in individuals with higher or lower levels of chronic pain. 56 Dick et al. found that persons with fibromyalgia and rheumatoid arthritis had lower cognitive performance in comparison to persons with musculoskeletal pain and pain-free individuals. 53 , Interestingly, patients with musculoskeletal pain performed similarly to pain-free individuals. Similarly, Castel et al. found that participants with fibromyalgia self-reported more memory complaints than participants with chronic pain. 60 Further, Coppieters et al. reported that women with chronic whiplash-associated disorders both self-reported more cognitive deficits and performed lower on objective measures of cognition than women with chronic idiopathic neck pain. 61

Thematic Summary: Aim #1 Factors Contributing to Brain Fog

The following sections outline a thematic analysis of identified contributors that have been correlated to the subjective experience of brain fog, namely, (1) neurophysiological contributors, (2) mental health and emotional contributors, and (3) environmental lifestyle contributors.

Neurophysiological Contributors

Thirty-one papers discussing the neurophysiological contributors of brain fog were identified. A 2018 literature review by Mazza et al. noted several studies have found an association between chronic pain and structural changes in the brain. 32 Several authors posited that pain modulation dysfunction may create symptoms of brain fog, because pain processing takes away from mental resources and therefore decreases the brain’s ability to attend to other cognitive functions. 27 , 43 , 62 , 63 Hence, increased intensity and chronicity of pain are theorized to increase both objective and self-reported severity of brain fog symptoms. 32 , 48 , 61 , 63–66 Pain interference, especially when it involves multiple aspects of one’s daily activities, has been found to be predictive of objective and subjective cognitive impairments. 67 , 68

Glass et al. stated that pain processing overused resources in the prefrontal cortex (PFC), which decreased cortical inhibition during cognitive assessments. 43 Similarly, Ren et al. noted that decreased activation of the PFC as well as decreased oxygen-hemoglobin flow may contribute to some cognitive deficits. 66 Neural network changes have also been reported, including reduced neuronal inhibition, which may indicate that neural signaling between networks is slowed. 69 Changes in hormone levels were also identified. For example, changes in dopaminergic neurotransmission or hypoperfusion have been documented in the thalamus and insula. 41 , 49

Mental Health and Emotional Contributors

Sixteen papers discussed mental health and emotional contributors to brain fog. Mental health comorbidities and emotional stress are prevalent in persons with chronic pain. Emotional states or conditions, such as anxiety and depression, use an abundance of cognitive resources, potentially overwhelming and prohibiting typical cognitive functioning. 32 , 41 , 70 , 71

This was demonstrated in a 2021 study by Castel et al. in which, which participants with depression were excluded from the analysis, participants with fibromyalgia and chronic pain had similar levels of sustained attention. 60 Similarly, Galvez-Sánchez et al. concluded that negative affect, higher levels of anxiety, alexithymia, and pain catastrophizing, as well as lower levels of self-esteem, were all correlated with worse performance on neuropsychological measures. 42

An RCT using computerized training to aid in the improvement of cognitive impairments in chronic pain found that improved objective and self-reported levels of anxiety, depression, and catastrophizing were associated with improved self-report levels of cognition. 33 Additionally, Sephton et al. reported excessive cortisol release associated with stress, chronic pain, and the prevalence of mental health comorbidities. 72 These factors contribute to release of excessive amounts of glucocorticoid hormones, which impairs declarative memory and were thought to contribute to the subjective experience of brain fog. 72

Environmental and Lifestyle Contributors

Lifestyle and environmental factors were discussed in six papers. McCracken and Iverson described how stressful life factors can act as a contributor to brain fog. 65 For example, financial, familial, or work stressors can cause rumination and depressive symptoms that affect cognitive functioning. 65 Medications to alleviate pain symptoms may also produce side effects that hinder cognition. 65 , 68 , 73 Another aspect of lifestyle that may contribute to brain fog is frequency of sleep. Self-report measures indicate that a lack of sleep, or irregular sleep, has been theorized to hinder cognitive processing and decrease levels of attention, memory, and executive functioning. 41 , 74–76 Conversely, two studies identified in the search argued that sleep disturbances have little effect on cognitive performance. 68 , 75 , 108 For more information regarding sleep, please see thematic summary #2.

Overview of Contributors

As demonstrated above, pain-induced neurophysiological changes, mental health and emotional contributors, as well as environment/lifestyle contributors can act independently to contribute to the experience of brain fog. However, factors may also act synergistically. For example, mental health comorbidities 74 and high pain intensity 50 , 63–65 both use an abundance of cognitive resources, and a combination of the two may lead to cognitive overload. Further, factors can have dual effects, meaning that they influence each other. As an example, the presence of chronic pain has been found to affect brain morphology by reducing gray matter volume in the ventromedial PFC, the insula, and the dorsolateral PFC. 77 These morphological changes may in turn affect the ability of these regions to engage in their typical cognitive functioning. 77 Additionally, inadequate sleep may contribute to symptoms of brain fog; however, the occurrence of brain fog could also hinder one’s sleep. 75 , 78 The presence of chronic pain could also affect both of these factors. 42 , 53 Similarly, continuous stress from life stressors can contribute to brain fog, and the experience of brain fog can also increase one’s stress. 65 The exact causality of these relationships is unclear.

Figure 3 provides a Venn diagram illustrating the complexity of the contributors of brain fog. The independent circle represents the three primary types of contributors acting independently. The overlapping regions of the Venn diagram demonstrate that contributors may act synergistically. Finally, the arrows illustrate that contributors can have a correlational and bidirectional relationship.

Thematic Summary: Aim #2 What Functional Correlates of Brain Fog Have Been Described and How Are They Assessed?

Impairments attributed to brain fog were reported by 42 papers and thematically grouped into three main areas: cognitive function, sleep, and quality of life.

Cognitive Function

Brain fog in chronic pain was reported to affect a wide range of cognitive processes (32 studies). Identified impairments related to brain fog included changes in memory, language, executive function, attention, and global cognition (see Appendix C for a summary of impairments and the tests used to measure them). The tests used to measure the listed impairments were inconsistent across studies, with over 65 different tests being used. Tests were primarily of three types: cognitive screening (e.g., Montreal Cognition Assessment 74 ) performance-based (e.g., Iowa Gambling Task 52 ), and self-report (e.g., Multiple Ability Self-Report Questionnaire 50 ). Measures used were appropriate for the patient population and overall had strong reliability and validity; however, they were mostly general measures of screening (e.g., Weschler Memory Scale and Stroop task). Some studies did use assessments that were more specific and assessed how cognitive impairments intervened with one’s ability to participate in daily activities (e.g., Everyday Memory Questionnaire 79 and Test of Everyday Attention 53 ).

The fact that numerous questionnaires were used across studies is problematic because this makes it difficult to compare cognitive abilities among different study samples and obtain an understanding of how cognition is affected by chronic pain. This statement echoes a 2022 systematic review performed by Zhang et al. that declared the need for a unified method of cognitive evaluation in chronic pain studies. 29 Further, questionnaires currently used in most studies do not capture the subjective experience of brain fog in persons with chronic pain and its effect on daily living.

Twenty-five studies addressed the relationship between brain fog, chronic pain, and sleep. Sleep deficits have been reported as a direct symptom of fibro-fog. 45 , 50 , 51 Other studies have described it as a probable symptom and have measured it through self-report questionnaires. 27 , 37 , 41 , 43 , 45 , 53 , 56 , 61 , 67 , 68 , 72 , 76 , 78 , 80–85 Interestingly, three studies measured sleep disturbances in patients with chronic pain and perceived cognitive dysfunction; however, they did not describe sleep impairments as a symptom of brain fog. 38 , 53 , 86 The bidirectional relationship between brain fog, chronic pain, and sleep has also been documented in the literature. 32

Two studies theorized that sleep disturbances can exacerbate perceived cognitive dysfunction and that brain fog can contribute to problems with sleep. 75 , 78 To make matters even more complex, chronic pain can also contribute to both sleep disturbances and perceived cognitive dysfunction. 75 , 78 This relationship has not been confirmed, because other studies did not find that sleep disturbances were correlated with perceived cognitive dysfunction. 14 , 68 , 74

It is important to note that sleep assessments were mostly self-report and are therefore subject to self-report bias; however, no objective measurements were identified. Additionally, most study findings regarding sleep, brain fog, and chronic pain were correlational in nature and did not directly study their relationship.

Participation in Daily Activities and Quality of Life

Because quality of life is a broad term that may have different meanings depending on the context, this article defined quality of life as pain experiences and beliefs, the interaction between pain and emotional state, and one’s participation in daily activities. McCracken and Iverson used a self-report measure to examine the frequency of cognitive complaints and the resulting challenges these complaints produced in the ability of persons with chronic pain to engage in daily activities. 65 They found that 23.4% of participants reported forgetfulness, 23.1% minor accidents, 20.5% difficulty with task completion, 18.7% difficulty with attention, and 54% impairments in with at least one cognition function. 65 Similarly, Iezzi et al. noted that participants often stated they experience difficulty in managing medication, daily tasks, decision making, and social interactions. 82 Further, Seward et al. found that driving abilities were reduced in participants with higher pain intensity and emotional dysfunction. 38

Similar to cognitive impairments, the assessments used to measure activity and quality of life in persons with chronic pain experiencing brain fog were inconsistent across studies: we recorded use of 26 different instruments addressing a variety of constructs including general health, mental health, the pain experience, and overall ability to perform daily activities (see Appendix D for papers describing impairments to quality of life and how they were measured). Measures used are commonly used in the chronic pain population and had strong validity; however, it was once again difficult to make comparisons across studies because of the high variability of assessments used. Further, the utility given the context of the assessments’ usage and patients’ understanding of questionnaires is unclear. For example, the Brief Pain Inventory is a self-report measure used to assess one’s pain interference scores. Although we were not able to identify any empirical linkages, we hypothesize that patients may perceive cognitive dysfunction as an example of pain interference, rather than seeing it as something distinct. This uncertainty and lack of distinction may act as a barrier toward our understanding of the unique impact of brain fog in persons with chronic pain.

Aim #3: Definition

Our working definition (see Figure 1 ) includes three key elements or constructs of brain fog that were developed within this literature review. The first construct is possible variability in the symptoms, frequency, and severity of brain fog. 50 This variability was framed as complex in the work of Williams et al. who described multifaceted contributions and drew on patient self-report measures to capture the fluctuations. However, we were unable to identify any longitudinal studies on dyscognition in chronic pain, and thus empiric evidence for within-subject temporal variability is lacking. The heterogeneity seen within groups can not only be attributed to temporal fluctuations in frequency and indeed may be a better representation of the possible variable severity, contributing to the sometimes small differences seen between persons with pain and healthy controls. 69 , 72 , 78 The second construct in the working definition that merits highlighting is participation limitations. Participation limitations refers to the challenges that individuals encounter when performing daily activities. The findings of this review represented participation most clearly in measures of quality of life. This relates to third construct of functional activities. The last construct is perceived cognitive dysfunction, which is an umbrella term accounting for impairments to attention, memory, executive, and overall cognitive function. 43 , 50 , 55 , 69 After analysis of the literature, we propose that the definition “brain fog is an amorphous subjective phenomenon used in the literature to describe the experience of (1) possible variable states of perceived cognitive dysfunction that may lead to (2) challenges in the (3) functional application of cognitive skills for participation in (4) daily activities” be used in future research investigating brain fog in chronic pain.

The inconsistent and vague use of brain fog seen in the medical literature illustrates the importance of the present scoping review and established definition. Despite the reported importance to persons living with chronic pain conditions, 44 at present there is no clear or widely accepted definition or diagnostic criteria for the brain fog phenomena in persons with chronic pain. Correspondingly, this review was guided by a consensus definition from clinical and patient stakeholders in an attempt to provide a clear understanding and definition of brain fog. Overall, the model developed from our findings demonstrated that cognitive, biological, and environmental factors may act independently or synergistically to produce symptoms of brain fog. These symptoms primarily appear as impairments to cognition, sleep, and quality of life and may act bidirectionally to contribute to the experience of brain fog (see Figure 3 ). While sharing the conception of bidirectional influences, our model expands on the neurocognitive model of attention to pain proposed by Legrain et al. 14 because we have chosen to look more broadly at dyscognition.

Further, the current method of assessment is problematic and prevents a proper understanding of brain fog. Given that studies do not use consistent metrics of brain fog, it is difficult to make meaningful comparisons and to obtain a coherent understanding of individuals’ experiences. Currently, the measurements that are used do not explicitly account for the subjective phenomenon of brain fog and do not capture its multidimensional nature (see Appendixes C and D ). Because most assessments are standardized and because there are few qualitative studies investigating brain fog, the real burden of brain fog in patients’ lives is unclear. Further, we excluded any papers primarily focusing on addressing changes in cognition related to medication management; however, we acknowledge the need to understand the independent contributions of brain fog and medication as well as to understand whether the experience of brain fog differs in persons taking pain medications with known cognitive sequelae.

Is Brain Fog a Synonym or Subtype of Dyscognition?

When conducting this review, we made the assumption that brain fog and dyscognition were similar in nature and thus included both terms in our search. However, our findings demonstrate that the similarities and differences between the two terms are unclear, because they may both be overly or incorrectly used in the medical literature. Glass et al. stated that dyscognition may be the official term for brain fog used in medical literature. 43 Dyscognition has been described as both self-reported symptoms and objective impairments. 30 This suggests that brain fog and dyscognition may represent the same phenomenon. However, dyscognition has also been mentioned as a feature of brain fog. 43 , 50 , 55 , 69 The inconsistent and broad use of the two terms demonstrates the urgent need for the terms to be properly defined. If dyscognition and brain fog are the same experience, then establishing this definition will facilitate comparisons between studies and patient experiences. Conversely, if brain fog is a different (perhaps more specific) experience than dyscognition, a coherent definition will help to distinguish the two phenomena. This can inform the selection of formal assessments and personalized treatment planning.

Gaps in the Literature

Our review highlights important research gaps. For example, brain fog in chronic pain is a complex disorder that manifests uniquely in each individual; however, little is known about the effects of individual differences and factors. Empirical research investigating these factors may help to provide a better understanding of this perplexing phenomenon. For example, much of the research on chronic pain and brain fog focuses on fibromyalgia, and brain fog in other chronic pain conditions remains understudied. 2 Research investigating the experiences of other chronic pain conditions is necessary, because brain fog can be initiated or affected uniquely in different conditions. Some studies have found that neuropathic pain produces stronger cognitive impairments than other pain conditions. 5–7 , 87 , 88 , 89 Additionally, individual factors such as differences in gender, sex, culture, age, socioeconomic status, fatigue, mental health, and personality traits may contribute to the experience of brain fog and explain the variation in prevalence in persons with chronic pain. 8–13 , 32 Moreover, the understanding of how these factors interact to produce symptoms of brain fog is unclear. As an example, emotional difficulties (e.g., depressive and anxious symptoms) use cognitive resources, which, when combined with pain, may produce brain fog. 32 , 60 , 68 , 82 However, emotional difficulties may also be a result of the experience of brain fog. The nature of this interaction should be investigated in future studies and should consider other potential mediators and/or moderators such as pain intensity and sleep in these relationships. 5–7 The interactive, or additive effect, that medication may have on the relationship between chronic pain and brain fog also requires further investigations, because some studies reported an effect, 87 whereas others did not. 8 , 32

Further, the role of hormones and immune influences in the experience of brain fog are worthy of exploration. However, given the lack of a clear definition of brain fog, it is difficult to compare the experience of brain fog across conditions or pain states, again highlighting the need for a clear definition and robust metrics.

To account for the heterogeneity of brain fog in chronic pain, we echo necessary modifications to study design that have been proposed or illustrated by the existing literature. First, larger sample sizes with diverse pain populations are crucial for future research, because brain fog is a complex disorder that is affected by multiple factors. 35 , 36 , 43 , 61 , 63 , 67 , 77 , 89–92 Currently, sample sizes are smaller in nature and more frequently focus on homogenous pain samples. Understanding these factors will facilitate HCPs’ ability to follow a precision medicine approach, which may be the only appropriate method to treat the variability of brain fog in persons with chronic pain. Study designs that are necessary to investigate these factors include longitudinal studies, prospective studies, and RCTs. Longitudinal studies that examine the temporal variability and potential progression of brain fog and its effects on brain morphology, connectivity, cognitive processing, and quality of life have been called for. 36 , 43 , 56 , 58 , 82 , 90 , 93 Next, prospective cohort studies will provide insight into the onset of brain fog, because currently there is no clear explanation. 89 , 93 Last, RCTs are necessary to evaluate the quality and efficacy of proposed interventions. 92

Regardless of the type of study, future research should also include both subjective and objective neuropsychological measures. Well-validated subjective measures are important to understand patient experiences; however, some studies have posited that they may be insufficient. 79

Objective measures are important to support precise statistical modeling; however, neuropsychological measures are time- and resource-consuming and do not capture the holistic experience of chronic pain. 46 The incorporation of both types of assessments, when possible, can counterbalance each assessment’s limitations. 10 , 46 , 68 , 79 , 82 , 84 , 87 , 93

Limitations

The findings of this review should be weighed with consideration of its limitations. The first obstacle encountered was that brain fog in chronic pain was ill defined and was not explicitly used in the literature, with the exception of one study. Thus, we were reliant on our pre-established definition based on a thematic summary of a nonexhaustive literature search, which was vetted by patient and health care partners. We chose to construct our own definition relative to chronic pain rather than rely on definitions from similar populations because of the variability of brain fog origins and symptoms in different disorders. 10–12 Though our established definition is similar to existing definitions of brain fog in other conditions, we have uniquely emphasized that brain fog is a heterogenous phenomenon leading to limitations for participation in functional activities. Other definitions have instead focused solely on cognitive impairments. For example, chemo fog was defined as “differences in issues with memory, attention, processing speed, and executive function.” 88 (p1345)(P1345) Next, in chronic fatigue syndrome it has been defined as “slow thinking, difficulty focusing, confusion, lack of concentration, forgetfulness, or a haziness of thought process.” 94 (p1) Thirdly, in neuropsychiatric diseases (e.g., schizophrenia), brain fog has been described as “reduced cognition, inability to concentrate and multitask, as well as loss of short term and long-term memory.” 9 (p1)(P1) This limitation also speaks to the pressing need for a consistent definition of brain fog that can be applied in research and health care settings. A second limitation is that we used the construct of cognitive dysfunction to help guide our search. However, as noted in our discussion, the findings from the literature demonstrate that this term also has a broad scope, which may have influenced the relevance of our findings. A third limitation is that the search was limited to studies published in English, which introduces a potential language bias. Additionally, although medication is a potential confounder in brain function, it was not possible to exclude sources that included participants who used medication, because the majority of persons with chronic pain typically rely on a form of medication to manage their pain. Therefore, the possibility of brain fog in chronic pain being merely a symptom of pain medication cannot be excluded. However, given the prevalence of brain fog in other conditions (e.g., depression, 7 long COVID, 8 and chronic fatigue syndrome 10 ), it is likely to be linked to numerous causal factors. Lastly, we deviated from our protocol and did not include gray literature as was originally intended. Because many authors suggested that brain fog and fibro-fog are the common terminology used by patients, 44 , 49–51 excluding gray literature may have missed important lay discourses and lived experience insights on this phenomenon.

Recommendations for Future Research

This review has demonstrated the urgent need for a coherent definition of brain fog. As such, we propose that a Delphi study investigating the differences in how patients and HCPs perceive and define brain fog should be conducted. Delphi studies are used to obtain consensus on a construct from a group of experts. Comparing lived experiences with HCPs’ perceptions will help us understand identify any gaps in understanding between these stakeholder groups. Importantly, using lived patient experiences will help us understand which areas of research are most important to patients’ overall quality of life.

Clinical Implications

In recent years there has been considerable focus on cognitive-based strategies for the management of chronic pain, including pain neuroscience education, 95 , 96 cognitive behavioral therapy, and mindfulness training. 96–98 These interventions require sufficient cognitive resources to support success and, as such, may have limited efficacy in persons with brain fog who may not have the cognitive capacity to engage with the treatment. 26 To obtain an understanding of how brain fog may be affecting treatment response and engagement, it needs to be included as a modifiable outcome and/or effect modifier in studies. This will provide an understanding of how brain fog can potentially be affected by interventions or how it could affect other outcomes such as patient satisfaction, quality of life, and sleep. However, for brain fog to be included as a modifiable outcome in research studies, it requires a consistent definition.

This review collated the notable challenges produced by brain fog in persons with chronic pain, current literature gaps, the constraints of past research, and evidence-based suggestions for future research. These factors emphasize the pressing need for research to systematically address the evaluation and treatment of the effects of brain fog in persons with chronic pain. Through a collaboration with HCPs and patient partners, we proposed a model and definition rooted in the existing evidence.

Currently, there are only measures for surrogates of brain fog but not for the actual multidimensional subjective experience of this phenomenon. We are calling for the development of specific measures to comprehensively address the effect of brain fog on one’s ability to meaningfully engage in their daily living. This development may benefit from qualitative research that investigates the lived experiences of persons with chronic pain and brain fog. The provided model of the contributors of brain fog ( Figure 3 ) and proposed definition can be used to guide researchers as they investigate robust and relevant assessments and clinical interventions to address brain fog. It may also help in generating hypotheses to test when modeling risks and predictors of outcomes and inform subgroup analysis of patient characteristics, ensuring consideration of important variables. To summarize, there is an urgent need for earnest academic and clinical consideration of brain fog in chronic pain. The current inconsistency in research regarding brain fog in chronic pain is obstructing a clear understanding of the phenomenon and therefore may be impeding persons with chronic pain and brain fog from receiving optimal care.

Acknowledgment

We thank Ryan Tucci (Carleton University) for his tremendous support in developing, translating, and organizing the search strategy.

Appendices. Appendix A.

Category 1: Chronic pain

Category 2: Brain Fog

1. Brain Fog

2. Cognitive Impairment/ dysfunction/ dysregulation Category

3: Cognitive abilities

1. Mental competency/ processes

3. Perception

4. Emotion cognition

5. Attention

6. Critical thinking

7. Executive function

Appendix B. Paper information

Level of evidence defined by the Centre for Evidence-Based Medicine.

HC = healthy control; FM = fibromyalgia; RA = rheumatoid arthritis; MSK = musculoskeletal pain; CRPS = complex regional pain syndrome; CIP = chronic idiopathic disorder; CWAD = chronic whiplash-associated disorder; CP = chronic pain.

Appendix C. Cognitive impairments

Appendix D. Participation in daily activities and quality of life impairments

Funding Statement

The authors have no funding to report.

Disclosure Statement

No potential conflict of interest was reported by the authors.

IRB Approval and Informed Consent

This project did not require IRB approval or informed consent.