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Google Maps: a decade of transforming the mapping landscape

Google Maps launched 10 years ago developed by a team of 50, now it has revolutionised the world of digital maps with more than one billion users

T en years ago, a weekend journey to a friend’s wedding was likely to involve typing a postcode into Multimap, printing out step-by-step instructions and then enduring amateur navigation from your partner in the passenger seat.

A decade on, digital maps and the inexorable rise of the smartphone have radically changed how we locate, navigate and plan our journeys. Mobiles, satnavs and computers act as our guides for everything from driving holidays to nipping to the shops.

Apps such as Google Maps have become the de facto interface between the the physical and the digital world, meaning people need never be lost again - even if they don’t have a sense of direction.

While Sir Tim Berners-Lee’s nascent world wide web supported the first online maps in 1993, it wasn’t until the launch of Google Maps ten years ago today that digital maps began to enter the mainstream.

In 2004, Danish brothers Lars and Jens Eilstrup Rasmussen went to Google with an idea for a web app that would not only display static maps, but provide people with a searchable, scrollable, zoomable map.

Google acquired their company Where 2 Technologies - along with a second company called Keyhole developing the geospatial visualisation software that would become Google Earth - and the new team of 50 people set out building Google Maps.

Google Maps launched in the US on 8 February 2005 and in the UK two months later, though by that time it wasn’t the first digital map of its kind: Yahoo had beaten Google to it with a redevelopment of its long-standing Yahoo Maps in 2004.

“Yahoo beat Google to web maps and MapQuest beat it to turn-by-turn directions, but people didn’t stand up and take notice until Google Maps came along,” said Gary Gale, the Ordnance Survey’s head of APIs. “It wasn’t the first out there, but the role of Google Maps in transforming digital maps, making them popular and bringing them from a tech niche into the public consciousness cannot be underplayed.”

Google Maps didn’t stand still. Later in 2005 Google launched driving and public transport directions, but it wasn’t until the launch of satellite imagery that Hanke saw how committed Google was to the project.

“Our aim was to create one seamless, browsable map of the entire world – an Earth that you could browse,” John Hanke, co-founder of Keyhole and vice president of Google’s geospatial division until 2011 told the Guardian. Google’s co-founders Sergey Brin and Larry Page, he said, thought that geospatial – data and information related to maps and location services - was a key element of Google’s organising the world’s information.

“At the time satellite imagery was quite expensive to acquire and scarce because there weren’t that many satellites available. I went to show Sergey on the map all the major cities we wanted to acquire. He looked and he just said, ‘why don’t we do all of it?’”

Street View was Larry and Sergey’s idea

Street View has proved to be one of Google Map’s most controversial but popular features. Launched for select US cities in 2006, and rolled out to Europe, Japan and Australia in 2008, the service relied on building up pictures of every street in the city using a specially equipped camera mounted on a car.

“Larry and Sergey had toured around the Stanford campus with Larry taking photos out the window of a car with a dSLR camera to experiment with stitching them together,” said Hanke. “That was their idea, but it took a partnership with Stanford and Sebastian Blune to make it work.”

Each car was fitted with a range of sensors including GPS, which allowed Google to trace routes and meant the company no longer had to reply on data from third parties.

The cameras also captured road signs, house numbers and other data not visible from the sky, giving its maps local knowledge of no-turns, speed limits and other street rules. This was all part of what Google termed “Ground Truth”, aiming to create the most accurate, detailed maps possible.

Google Maps debuts on Apple’s first iPhone

Google Maps first appeared on a smartphone in 2007 on Apple’s first iPhone - a very different era when Google and Apple were partners more than rivals as they are today.

“Smartphones were the key crystallising moment causing people to fall back in love with the map,” said Gale. “Digital maps are essential to everyday life – you wouldn’t buy a smartphone without them.”

“Steve Jobs called me at my desk to ask me to help out on a project – he wouldn’t tell me what it was, but of course I knew,” said Hanke. “We worked closely with Apple to get maps ready for the launch of the first iPhone, which opened up so many possibilities.”

Google Maps has since added turn-by-turn satellite navigation, Zagat restaurant ratings, traffic updates and expanded Street View to include Venetian canals and the Grand Canyon - yet progress has not always been smooth.

In 2010 it was revealed that Street View cars had also been capturing information about private Wi-Fi networks as they roamed the streets of US and Europe, prompting a $7m fine from US authorities . The service’s expansion into Europe, especially in Germany, also caused home owners to take issue with their property being captured and placed online for the world to see without their permission.

“We were doing something that hadn’t been done before,” said Hanke. “People had put up with surveyors going out with range finders and survey equipment, but now cars with cameras were doing the work. It was a learning process for us, the whole idea of photography in a public space and what it means; it was a big cultural shock and we were part of it.”

And the competition?

Google Maps faces ever increasing competition. Some, such as popular third party travel app Citymapper, use Google’s own mapping data, while other services have created their own geospatial resources.

Apple turned from partner to competitor in 2012, deciding to dump Google Maps from the iPhone for Apple Maps. The company quickly learned that making a solid map service was more difficult than it looked, forcing chief executive Tim Cook to publicly apologise for the bug-ridden product. Today it is a viable alternative and gaining in popularity as the default maps app for the iPhone, iPad and Mac computers.

Microsoft’s Bing Maps was one of the first to improve upon top-down aerial images, introducing a birds-eye view that allows browsers to see streets and buildings from a 45-degree angle.

Nokia also acquired the largest maker of automotive-grade map data, Navteq, in 2007 and has been using it to build highly accurate maps which it sells to other companies, including Garmin, BMW and Amazon.

Beyond the professional maps, there are also collaborative projects such Open Street Map creating free, editable maps of the world and relying on users to correct things that are wrong in much the same way as Wikipedia.

“The mapping war isn’t over, and it won’t ever be,” said Gale. “It’s all about the fight to keep the map accurate and to give it context. A map is never finished, there is always more to be done. Anyone who gives people and business what they want, making it valuable to them will win.”

The future of maps is indoors, and offline

For Gale, the next five years in mapping technology will be about a new generation of sensors to take over from GPS and mobile phone signal triangulation.

“The moment we get cut off from GPS the mapping experience becomes rubbish. We need something to fill the gap for mapping indoors, where accurate positioning is difficult. We’re not clear on what that will be yet – whether Bluetooth beacons or another suite of sensors,” Gale said.

The future of the digital map, however, is not actually of the map, but using the map. Projects like those created by Hanke’s own Niantic Labs are good examples.

Field Trip , for instance, uses location awareness to notify users of interesting landmarks, features and places in the real world. Another, Ingress , is a location aware game that overlays a virtual playing field on top of our towns and cities.

These are the next evolution of the map, humanising and contextualising location to make it more relevant to us.

• Smartphones
• Google Street View
• Mapping technologies

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With more than a billion people using Google Maps every month and more than 5 million active apps and websites using Google Maps Platform core products every week, we get questions about where our maps data come from, how we keep it accurate, and more. So before we get to our third installment of the Beyond the Map series, we sat down with product director Ethan Russell to get answers to a few frequently asked questions about our maps data and how you can help us keep it up to date for your very own applications and experiences. 

How do you make sure Google’s maps data is accurate?   The world is a vast and constantly changing place. Think about how frequently restaurants in your neighborhood come and go, and then consider all the businesses, buildings, homes and roads that are built–and then scale that up to more than 220 countries and regions that are home to more than 7 billion people in the world. We want everyone on the planet to have an accurate, up-to-date map, but there’s a lot going on! So our work is never done and we have a variety of different efforts and technologies helping us keep our maps data as up to date as possible. If you haven’t read the first two installments of the Beyond the Map series, they’re a good start in learning more about how we map the world and keep our data up to date. The first post gives you an overview of our mapping efforts and the second post explains how imagery is the foundation of our mapping techniques. But something we haven’t highlighted in the series yet is how we empower our customers, businesses, and users to contribute what they know about the world and keep our data up to date for themselves and each other. 

How can I submit updated information?   There are a few different channels for people, businesses, and customers to help update our maps data when something’s not right. Anyone who uses Google Maps can let us know about data issues via the Send Feedback (desktop Maps) and Suggest an Edit (place profiles on Maps and Search) tools. For Google Maps Platform customers using one of our industry solutions (like gaming), the product includes an API for reporting bad points, enabling our game studio partners to report issues to us so we can take action accordingly. And of course if a customer is working closely with our customer engineering teams or an account manager, then they can always work directly with them or the support team to get the information updated. Businesses and agencies that manage business info can also update their business information via Google My Business . 

**Are there any other ways that Google finds updated information beyond user contributions?** Within Google, we have a dedicated team working on keeping our data up to date day in and day out. This covers things like incorporating data from third party resources, developing algorithms to automatically update data and identify spam or fraud, and reaching out directly to businesses and organizations to get accurate info.

**How often is your maps data updated?** The map is updated constantly–literally, every second of every day! We’re constantly collecting new information about the world, whether from satellite imagery and Street View cars, or Google Maps users and local business owners, and using that information to update the map. Google Maps users contribute more than 20 million pieces of information every day–that’s more than 200 contributions every second. In addition to the updates we make from what people tell us, we’re making countless updates uncovered through other means like the imagery and machine learning efforts we’ve shared with you in the recent Beyond the Map blog posts posts. 

If a business or organization has a lot of data to contribute, how can they do that?   For organizations like governments, non-profits, and educational institutions that have large amounts of data about things like new roads or addresses of new buildings, they can use the new Geo Data Upload tool. When submitting via the tool, it’s important that you send data in the right format, so we can ingest the files easier–a shapefile (.shp) or .csv with spatial attributes are preferred file types. If you’re ready to submit your data, it’s helpful that you and your team review our upload content requirements (which you can do at this support page ).  

Agencies that manage online marketing for a variety of businesses can use Google My Business to add and update business information. Not only does it get business info into our Places APIs, but it offers a wide range of tools to help businesses better connect with consumers through features like messaging, product inventory, and more on Google Maps and Search. 

How do you manage the vast amounts of data it takes to keep up with the changing world?   Given that we’re building maps at a truly global scale, you can imagine we process a lot of information. We have many different types of data–roads, buildings, addresses, businesses, and all their various attributes–and imagery from different viewpoints at high resolution. Luckily, we’re not starting from scratch here. From processing and storage systems like Dataflow and Cloud Spanner to machine learning libraries and frameworks like TensorFlow , we’re able to make sense of a river of incoming data.

**Why are there differences in data quality in various parts of the world? And how do you address these differences to make sure businesses everywhere can use Google Maps Platform?** Part of what’s fun and challenging about mapping the entire planet is dealing with all the regional differences. This starts with different political constructs, like how granular the postal codes are, or whether addresses for buildings run linearly from one end of a street to the other or are distributed around a block. Then there are physical differences, like with buildings being attached to each other in a city, and with multiple businesses–and private residences!–on different floors. Or when an area has lots of tree cover that makes it hard to see roads underneath, or no tree cover but dry riverbeds that look like dirt roads. And then there are economic differences like how quickly new roads and buildings are constructed, and how quickly new businesses open up. Add in the fact of different languages and different scripts that our algorithms, machine learning and human operators need to understand, and you have a lot of complicating factors leading to different kinds of problems in different parts of the world.

To address these differences we take new and different mapping approaches to these areas. For an area with few authoritative data sources to reference, we use satellite and street-level imagery and machine learning to identify roads or businesses and add the information to our maps data. Or for an area with roads too narrow to map we created a “Street View 3-wheeler” to capture imagery to help us add those roads. As we uncover new mapping challenges, we’re always eager to develop a new solution. 

What’s the most interesting way that Google or another organization has contributed maps data?   Sheep View is my personal favorite. Solar-powered cameras were strapped to sheep’s woolly backs to collect imagery of the Faroe Islands for Street View. The 18 Faroe Islands are home to just 50,000 people, but—fittingly for a country whose name means “Sheep Island”—there are 70,000 sheep roaming the green hills and volcanic cliffs of the archipelago. So sheep were a brilliant way to capture imagery of the area–and definitely the most creative I’ve seen. 

With Halloween around the corner, what’s up with all those spooky Street View images of people with three legs or a plane submerged in a lake?   The imagery you see on Google Maps and that’s available via our Maps and Street View APIs is a compilation of billions of photos combined together. Sometimes when we stitch together photos of the same scene, things don’t line up exactly right. This happens especially with things that are moving, like a person walking or an airplane flying. We’re always tweaking our systems and algorithms to handle these situations better. Last Halloween, we actually explained some of the photography challenges behind the most common types of “spooky” imagery in  this blog post . 

Now that we’ve answered some of the most common questions about our maps data, stay tuned for upcoming Beyond the Maps posts for more in-depth looks at how we’re mapping the world and how that helps businesses build location-based experiences worldwide. 

 For more information on Google Maps Platform,  visit our website .

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The Working of Google Maps, and the Commercial Usage of Navigation Systems

This research paper particularly provides an overview of the operation of navigation software, particularly Google Maps. Firstly, the paper discusses the working of the Google maps with respect to operations research and elaborates on the algorithms used by Google Maps to find the optimal, time-saving for the user. 3 distinct routing algorithms are discussed that could potentially be used in navigation software. Secondly, the paper discusses the use of navigation software in different industries, and the mechanism used by businesses to increase efficiency. Finally, the paper discusses the limitations of the use of Google Maps in logistics, and elaborates on the reasons due to which many businesses choose not to utilise the software.

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Utilization of Geographic Information System (GIS) provides the ease to humans to dig information and take decisions from a set of geographic data with an effective and efficient manner. One application in the field of transportation is to extract information about the shortest route from a point to another point in order to save travel costs and shorten travel time. This article discusses the development of a GIS to help driver taxi online Sidoarjo District, especially in the District of Taman, to in obtain information on the shortest travel route. It is expected to help the driver be to able to go to the intended location in a short time, so the quality of service to consumers can increase. The route search technique used in this research Dijkstra is Algorithm combined with Node Combination algorithm with the aim to speed up computing time while saving memory consumption on computer. Geographic information in the form of two-dimensional maps obtained from Google Maps API that can be freely used.

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GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: data reliability, data processing and the related application. This thesis aims to study the GPS tracking from the methodological, technical and practical aspects. It first evaluates the reliability of GPS-based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost.

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The following paper outlines an arts-based research project that uses drawing and performance to critically examine the perceptual conditions generated by locative media, specifically the dominant Google Maps platform. The research is based on a series of wayfinding encounters in four major urban centres—Toronto, ON, New York, NY, London, UK, and Amsterdam, NL—during which the artist-researcher asked passers-by for directions with the additional request the directions be drawn using the instruments provided. The paper considers the street-level behaviours and practices of location-awareness and orientation set against the constructions of trust, seamlessness, and claim to space Google Maps deploys.

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In large urban areas, until recently, people used to choose a route having in mind the general, high-level mental map of the urban traffic network. With the dissemination of the use of navigation devices such as GPS, all roads may now be part of a path. Therefore two questions arise, that are related to the performance of the traffic network as a whole, and to the effects of the use of these navigation devices on travelers that usually only do short trips in their own neighborhoods. Our preliminary results show that the average overall travel times indeed decrease with the use of GPS. However, travelers who used to avoid arterial roads are strongly penalized.

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A Complete Guide to Google Maps Marketing

In this guide, discover what Google Maps marketing is, why it matters for local SEO, and how business can do it the right way.

Ensuring that your business shows up in Google Maps is paramount to long-term viability.

Prospective customers are often skeptical of businesses with little or no online presence.

Fortunately, Google Maps provide one of the easiest and fastest ways to get online.

Business owners now have an opportunity to market their goods and services in real-time to anyone with a mobile device.

What Is Google Maps Marketing?

Google Maps marketing is simply the optimization of your business presence on Google Maps.

The goal is simple: by ranking higher in search, you have an opportunity to significantly increase your business.

The better your profile optimization, the better your chances are for showing up in a Google Maps search for your business type in your area.

Why Is Google Maps Marketing So Important?

Google handles about 3.5 billion searches per day and accounts for nearly 88% of all mobile searches.

Local Google searches also directly translate into sales with 76% of those searching for local products visiting a store within the day.

Google Maps marketing can impact the way Google views your business and how or if it appears in organic search in what is known as the local 3-pack.

Google Map Results (local 3-pack) appear at the top of the page in this Google Search.

Google Maps can channel thousands of potential customers toward your business.

Unless your business ranks in the 3-pack, your chance of being found is exponentially lower.

That is why Google Maps Marketing is generally considered the most important facet of local SEO work.

Setting up & Optimizing Your Google My Business (GMB) Listing

Creating a Google My Business (GMB) listing is totally free.

This is because it technically isn’t an advertisement at all – you are simply letting Google know that your business exists.

That said, the end goal is to get your business to rank higher than your competitors.

Setting Up Google My Business

To set up your Google My Business listing:

• Sign in to Google and go to https://www.google.com/business/
• Then locate or create a listing for your business. Sometimes other factors or inputs have led to an impromptu assumption listing about your business. Make sure you claim and correct it if that happened.
• Fill out all of the information to the best of your ability.
• Make sure to select the correct category and to add a contact.
• Verify your account. This can be done with Google via phone, email, or traditional mail.
• Add quality photos.
• Double-check all of your information.

Read this guide to learn how to completely optimize your GMB listing.

How to Rank Better in Google Maps

Google Maps take into account a number of factors when it decides how to rank results.

The geographic distance from the person conducting the search and the business category relevant to their search are the most obvious.

Perhaps more important is how complete and accurate your GMB listing is. This could be the tie-breaker among you and your competitors in determining who appears in the search.

Finally, positive sentiment (good reviews) can be a deciding factor.

Getting Good Reviews

Many companies have developed systems around cultivating positive reviews.

Some will ask customers directly, at the conclusion of a transaction, to give them a review.

Other businesses put a request for a review prominently, at checkout. Some even have used QR codes.

One effective method is to leave a review request, on a business card, attached to a “Thank You” memento. Something as simple as a complimentary air freshener can go a long way.

In all of your promotional materials, it’s good business practice to provide a link for customers to leave a Google review.

What About Bad Reviews?

Handle bad reviews calmly. Work hard to overcome them with more good reviews.

When you get a bad review, apologize, accept responsibility and offer to make it right; even if it wasn’t your fault.

It’s a losing proposition to get defensive or aggressive in your reply.

A bad review give you the chance to demonstrate your professionalism, helping to mitigate any potential damage.

Posting on Google as Your Business

This is an underused feature.

Business owners can “publish … offers, events, products, and services directly to Google Search and maps.”

This can be another effective way to stand apart from your competitors.

Google Maps Optimization Checklist

To give your business a better chance of showing up in Google Maps for relevant searches, just follow the checklist below.

• Claim or create a listing for your business.
• Correct service area and address.
• Business hours / workdays.
• Website / URL for them to make a purchase.
• List your specific offerings. Clearly and simply. Try to add keywords in naturally when possible.
• Pick the most relevant and common categories for your business.
• Ensure information is consistent across the web.
• Add high-quality photos.
• Cultivate good reviews.
• Talk about your business in Google My Business .
• List your business in other directories.
• Use analytics to adapt your strategies.

Paid Advertising & Local Search Ads

Google gives you the tools to target your local area with local search ads .

This is paid advertising that can help you appear at the top of the Google search page or Map App when someone searches for your relevant services.

If you are struggling to bring in customers and can’t wait for your organic efforts to pay off, you may want to consider paid advertising.

Many businesses have had great success in employing local search ads on Google. It can be the perfect complement to organic marketing efforts.

Tracking Your Google Maps Marketing Performance

Tracking your performance on Google Maps is done via analytics offered with your Google My Business account.

This is necessary for evaluating your current web presence and optimizing it, moving forward

Following are the key metrics you should pay close attention to:

The Google Services That Customers Use to Find Your Business

An important metric to pay attention to is the type of searches leading to your website.

This will let you know the volume of users that are searching for you by name, vs those discovering you via the keywords relevant to your brand, location, and industry.

This may help you gauge the percentage of new versus repeat customers coming to your site via Google.

Where Customers View Your Business on Google

This section will let you know the frequency that you are being found on general search vs map listings.

Taken in conjunction with the first metric you can gauge the general success of your Google Map Listings in attracting new customers.

As you make changes, monitor these stats to ensure you are making the right decisions and moving in a positive direction.

Listing Visitor Action Taken

“Customer actions” will show you what actions people are taking in response to your listing.

You will discover if your listing is helping people find your location, your website, or leading to some form of contact.

This is perhaps the most important metric as you embark on optimizing your listing.

Working to improve customer engagements and interactions is your best path to success.

Where Customers Are Coming From

“Directions requests” shows where customers are requesting directions to your business from.

With this information, you can begin to localize and better target your other marketing ventures as well as perhaps adjust your target keywords.

The Performance of Your Photos

“ Photo views and Photo quantity ” shows how your photos are performing as compared to competing businesses.

It also shows the mix of photos coming from you versus those posted by your customers.

Humans react positively to appealing visuals, so you should take the time to capture the best possible photos of your business.

The Final Takeaway

While getting the basics right is simple enough, fine-tuning will set you apart from the competition.

Pay attention to your analytics.

The best way to market yourself across all Google apps is to:

• Keep your information up to date.
• Keep your social proof (customer reviews) positive.
• Make certain that your visual presentation is always top-notch.

More Resources:

• Local SEO: The Definitive Guide to Improve Your Local Search Rankings
• How to Completely Optimize Your Google My Business Listing
• Top 25 Local Search Ranking Signals You Need to Know

Image Credits

All screenshots taken by author, October 2019

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Google helped make an exquisitely detailed map of a tiny piece of the human brain

A small brain sample was sliced into 5,000 pieces, and machine learning helped stitch it back together.

• Cassandra Willyard archive page

A team led by scientists from Harvard and Google has created a 3D, nanoscale-resolution map of a single cubic millimeter of the human brain. Although the map covers just a fraction of the organ—a whole brain is a million times larger—that piece contains roughly 57,000 cells, about 230 millimeters of blood vessels, and nearly 150 million synapses. It is currently the highest-resolution picture of the human brain ever created.

To make a map this finely detailed, the team had to cut the tissue sample into 5,000 slices and scan them with a high-speed electron microscope. Then they used a machine-learning model to help electronically stitch the slices back together and label the features. The raw data set alone took up 1.4 petabytes. “It’s probably the most computer-intensive work in all of neuroscience,” says Michael Hawrylycz, a computational neuroscientist at the Allen Institute for Brain Science, who was not involved in the research. “There is a Herculean amount of work involved.”

Many other brain atlases exist, but most provide much lower-resolution data. At the nanoscale, researchers can trace the brain’s wiring one neuron at a time to the synapses, the places where they connect. “To really understand how the human brain works, how it processes information, how it stores memories, we will ultimately need a map that’s at that resolution,” says Viren Jain, a senior research scientist at Google and coauthor on the paper, published in Science on May 9 . The data set itself and a preprint version of this paper were released in 2021 .

Brain atlases come in many forms. Some reveal how the cells are organized. Others cover gene expression. This one focuses on connections between cells, a field called “connectomics.” The outermost layer of the brain contains roughly 16 billion neurons that link up with each other to form trillions of connections. A single neuron might receive information from hundreds or even thousands of other neurons and send information to a similar number. That makes tracing these connections an exceedingly complex task, even in just a small piece of the brain..  

To create this map, the team faced a number of hurdles. The first problem was finding a sample of brain tissue. The brain deteriorates quickly after death, so cadaver tissue doesn’t work. Instead, the team used a piece of tissue removed from a woman with epilepsy during brain surgery that was meant to help control her seizures.

Once the researchers had the sample, they had to carefully preserve it in resin so that it could be cut into slices, each about a thousandth the thickness of a human hair. Then they imaged the sections using a high-speed electron microscope designed specifically for this project. 

Next came the computational challenge. “You have all of these wires traversing everywhere in three dimensions, making all kinds of different connections,” Jain says. The team at Google used a machine-learning model to stitch the slices back together, align each one with the next, color-code the wiring, and find the connections. This is harder than it might seem. “If you make a single mistake, then all of the connections attached to that wire are now incorrect,” Jain says. 

“The ability to get this deep a reconstruction of any human brain sample is an important advance,” says Seth Ament, a neuroscientist at the University of Maryland. The map is “the closest to the  ground truth that we can get right now.” But he also cautions that it’s a single brain specimen taken from a single individual. 

The map, which is freely available at a web platform called Neuroglancer , is meant to be a resource other researchers can use to make their own discoveries. “Now anybody who’s interested in studying the human cortex in this level of detail can go into the data themselves. They can proofread certain structures to make sure everything is correct, and then publish their own findings,” Jain says. (The preprint has already been cited at least 136 times .) 

The team has already identified some surprises. For example, some of the long tendrils that carry signals from one neuron to the next formed “whorls,” spots where they twirled around themselves. Axons typically form a single synapse to transmit information to the next cell. The team identified single axons that formed repeated connections—in some cases, 50 separate synapses. Why that might be isn’t yet clear, but the strong bonds could help facilitate very quick or strong reactions to certain stimuli, Jain says. “It’s a very simple finding about the organization of the human cortex,” he says. But “we didn’t know this before because we didn’t have maps at this resolution.”

The data set was full of surprises, says Jeff Lichtman, a neuroscientist at Harvard University who helped lead the research. “There were just so many things in it that were incompatible with what you would read in a textbook.” The researchers may not have explanations for what they’re seeing, but they have plenty of new questions: “That’s the way science moves forward.” 

Biotechnology and health

How scientists traced a mysterious covid case back to six toilets.

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

An AI-driven “factory of drugs” claims to have hit a big milestone

Insilico is part of a wave of companies betting on AI as the "next amazing revolution" in biology

• Antonio Regalado archive page

There is a new most expensive drug in the world. Price tag: $4.25 million

But will the latest gene therapy suffer the curse of the costliest drug?

Beyond Neuralink: Meet the other companies developing brain-computer interfaces

Companies like Synchron, Paradromics, and Precision Neuroscience are also racing to develop brain implants

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Open Buildings

A dataset of building footprints to support social good applications

Building footprints are useful for a range of important applications, from population estimation, urban planning and humanitarian response, to environmental and climate science. This large-scale open dataset contains the outlines of buildings derived from high-resolution satellite imagery in order to support these types of uses. The project is based in Google's Ghana office , focusing on the continent of Africa and the Global South at large.

Dataset description.

The dataset contains 1.8 billion building detections, across an inference area of 58M km 2 within Africa, South Asia, South-East Asia, Latin America and the Caribbean.

The current dataset is in its 3rd version (v3), covering detections from Sub-Saharan Africa, South and South-East Asia, Latin America and the Caribbean.

For each building in this dataset we include the polygon describing its footprint on the ground, a confidence score indicating how sure we are that this is a building, and a  Plus Code  corresponding to the centre of the building. There is no information about the type of building, its street address, or any details other than its geometry.

Uses of the data

Potential use cases of the data include:

Population mapping: Building footprints are a key ingredient for estimating population density. In areas of rapid change, or where census information is out of date, population estimates are vital for many kinds of planning and statistics.

Humanitarian response: To plan the response to a flood, drought, or other natural disaster, it is useful to assess the number of buildings or households affected. This is also useful for disaster risk reduction, e.g. to estimate the number of buildings in a particular hazard area.

Environmental science: Knowledge of settlement density is useful for understanding human impact on the natural environment. For example, it helps with estimating energy needs and carbon emissions in a certain area, or pressure on protected areas and wildlife due to urbanisation.

Addressing systems: In many areas buildings do not have formal addresses, which can make it difficult for people to access social benefits and economic opportunities. Building footprint data can help with the rollout of digital addressing systems such as  Plus Codes .

Vaccination planning: Knowing the density of population and settlements helps to anticipate demand for vaccines and the best locations for facilities. This data is also useful for precision epidemiology, as well as eradication efforts such as mosquito net distribution.

Statistical indicators: Buildings data can be used to help calculate statistical indicators for national planning, such as the numbers of houses in the catchment areas of schools and health centres; mean travel distances to the nearest hospital or forecast of demand for transportation systems.

How Partners Have Leveraged the Open Buildings Dataset

Sunbird AI is a Ugandan nonprofit that uses data technology for social good. They have used Open Buildings to support planning at the Ministry of Energy in Uganda. With building footprint data, they can see which are the priority areas for electrification, estimating where commercial centers are, and areas with large population, or areas with essential services like schools and hospitals. Some of these are settlements which otherwise might be overlooked because they are literally not on the map.

The UN Refugee Agency, UNHCR , has used Open Buildings for survey sampling. It’s common to do household surveys in regions where people have been displaced, in order to know what people need. But UNHCR needs to first have an assessment of where the households actually are, which is where the Open Buildings project has been useful.

UN Habitat has used Open Buildings to study urbanization across the African continent. Having detail on the way that cities are laid out enables them to make recommendations on urban planning.

The International Energy Agency has used Open Buildings to estimate energy needs. With data about individual buildings, they can assess the needs of communities at a new level of precision and know how much energy is needed for cooking, lighting and for operating machinery. This will help with planning sustainable energy policy.

Explore the open buildings data.

Click here to explore the data in Earth Engine. If you'd like to know more about our methods, quality and data limitations, check out the FAQs  and  technical report .

Data format

The dataset consists of 3 parts: building polygons, building points and score thresholds.

Building polygons and points

Building polygons and points are stored in spatially sharded CSVs with one CSV per S2 cell level 4. Each row in the CSV represents one building polygon or point and has the following columns:

latitude : latitude of the building polygon centroid,

longitude : longitude of the building polygon centroid,

area_in_meters : area in square meters of the polygon,

confidence : confidence score [0.65;1.0] assigned by the model,

geometry : the building polygon in the WKT format (POLYGON or MULTIPOLYGON). This feature is present in only in polygons data,

full_plus_code : the full Plus Code at the building polygon centroid.

Score thresholds

The estimated score thresholds are stored as one CSV. Each row in the CSV represents one S2 cell level 4 bucket and has the following columns:

s2_token : S2 cell token of the bucket,

geometry : geometry in the WKT format of the S2 cell bucket,

confidence_threshold_80%_precision , confidence_threshold_85%_precision , confidence_threshold_90%_precision : estimated confidence score threshold to get specific precision for building polygons in this S2 cell bucket,

building_count_80%_precision , building_count_85%_precision , building_count_90%_precision : number of building polygons in this S2 cell bucket with confidence score greater than or equal to the score threshold needed to get the specific precision,

building_count : number of building polygons in this S2 cell bucket,

num_samples : number of samples used for generating the score threshold. This feature exists from v2 onwards.

The polygon data (178 GB total) is composed of a set of CSV files, with one file per level 4  S2 cell  that are up to 7.8 GB in size. Similarly, the points data (48 GB total) are up to 2.1 GB per file. Select a download method below.

Download from the map

To manually download polygons data for a specific cell, click on the map below.

Download polygons or points data for a specific country or region

This  Colab notebook  shows how data can be downloaded for a specific country or region.

Download all data

Download all polygons using  gsutil (178 GB total):

gsutil cp -R gs://open-buildings-data/v3/polygons_s2_level_4_gzip

Download all points (48 GB total):

gsutil cp -R gs://open-buildings-data/v3/points_s2_level_4_gzip

Download metadata

Metadata files can be downloaded as follows:

Tile geometry and URLs in geojson format.

Score thresholds CSV file.

Download score thresholds using gsutil :

gsutil cp gs://open-buildings-data/v3/score_thresholds_s2_level_4.csv

Version history

v1 : inference carried out during April 2021 on imagery covering 19.4M km 2  of Africa.

v2 : inference carried out during August 2022 on imagery covering 39.1M km 2  of Africa, South and South-East Asia.

v3 : inference carried out during May 2023 on imagery covering 58M km 2  of Africa, South and South-East Asia, Latin America and the Caribbean. See FAQ for comparison of versions.

A deep learning model was trained to determine the footprints of buildings from high resolution satellite imagery. Our accompanying  technical report  describes the methodology used to generate the first version of the dataset. We however made further improvements for the subsequent versions, v2 and v3.

The data is shared under the  Creative Commons Attribution (CC BY-4.0) license  and the  Open Data Commons Open Database License (ODbL) v1.0 license . As the user, you can pick which of the two licenses you prefer and use the data under the terms of that license. However, please note the liability disclaimer in the footnotes ^ 1 .

We wanted to make the data compatible for ingestion by those working with ODbL-licensed datasets (namely the OpenStreetMap community) while enabling people who don't use ODbL licensing to use it under the terms of the CC BY-4.0 license. We hoped to take away the burden of figuring out whether the two licenses were compatible and simply release the data set under both licenses.

Yes – however, to maintain the quality of OSM, please be mindful of the need for human review when adding machine-generated features, and where possible to do this with the benefit of local knowledge. Errors in the data to look out for include false detections and inaccurate shapes (see more about accuracy below). We also recommend starting by filtering out building detections that have a confidence score below the estimated  90% precision threshold .

The buildings on Google Maps come from a variety of sources, including the model used to generate this dataset. So there is some overlap, but the sets of footprints are not exactly the same.

As the imagery in Google Maps is updated over time, the specific images used to identify these buildings are not necessarily the same images that are currently published in Google Maps. If there is a misalignment between these two sets of imagery, buildings displayed in the  data explorer map  may appear to be offset from the underlying imagery.

You can view a timeline of the imagery for a specific area using the  Historical Imagery  feature in  Google Earth Pro  which may show this imagery offset between different images and dates. To learn a little more about satellite imagery offset see these sites ( 1 ,  2 ). Also see the  technical report  for details about data limitations and quality.

Despite having a diverse set of training data, some scenarios are challenging for the building detection pipeline, including: 1) geological or vegetation features which can be confused with built structures; 2) settlements with many contiguous buildings not having clear delineations; 3) areas characterised by small buildings, which can appear only a few pixels wide at the given image resolution; 4) rural or desert areas, where buildings constructed with natural materials tend to visually blend into the surrounding area; 5) areas with high-rise buildings: our model is trained to detect building rooftop rather than base and as a result, depending on satellite image's viewing angle, roofs of high rise buildings jump around which makes it challenging to track buildings across a stack of imagery in a given location. See the  technical report  for more details.

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Map making is an ancient human endeavour and one that those of us working on Google Maps are honoured to continue to pursue

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Mums who map

A group of Local Guides, Mums who Map, dedicated their time to help parents find kid-friendly places in Melbourne, Australia.

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Mapping Tonga

Tania Wolfgramm and Wikuki Kingi set out to bring Tonga to Street View for the whole world to see.

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Together with the Mars Institute and NASA, Google Maps documented the research that goes on Devon Island, the most Mars-like place on Earth.

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Mapping Italy’s Recovery

One Local Guide records the aftermath of Italy’s earthquakes to show the world that they still need help in recovering.

Kerala, India

Kerala Flood Rescue

Bobby Kurian used Google Maps to tag her parents’ location to help rescue them in the Kerala floods.

Supporting Women’s Rights

With the help of Local Guides and Google Maps, Princess Ilonze got hospitals and police stations on the map to help save lives.

Kids in India

The India Literacy Project teamed up with Google to help students in exploring the world through photos uploaded by Local Guide.

Bozeman, Montana

Connecting to Bozeman

One Local Guide was inspired to celebrate and show off her hometown in a unique way.

Sao Paulo, Brazil

Mapping Blood Donation Sites

Local Guide Adriano Anjos in Brazil mapped Sao Paulo’s blood donation centres on Google Maps.

London, England

Wheelchair Accessible Routes

Wheelchair-accessible routes on Google Maps has made getting around easier for Meridtyh, Omari, Adam, and Lucy.

Kolkata, India

Plus Codes creates geographical coordinates that provide an address to those who previously had none.

Grand Canyon National Park

Vets Kayak The Grand Canyon

Five blind veterans kayaked through the Grand Canyon and documented their journey on Street View.

Google Maps Blog

Read articles, interviews, and more to learn what’s new on Google Maps

Want the best prices for your trip? Google can help.

Take off to your next destination with Google Maps

Hip-hop dancers show Paris in a new light on Street View

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Google Maps, Google Earth, and Street View

If you want to use one of these products in your work, review these guidelines to see if your specific use is allowed and whether you need to submit a request for approval.

• General guidelines General

Copyright fair use

Personalizing your map, use of trademarks.

• Google Maps Maps

Web and apps

Television and film, online video.

• Google Earth Earth

Television, film, and online video

• Street View Street View
• Required attribution Attribution

General guidelines

You generally don’t need to submit a request to use our mapping products for the purposes covered in these guidelines. As long as you’re following our Terms of Service and these guidelines, as well as attributing properly , feel free to move forward with your project. But do continue to read these guidelines thoroughly to make sure your use is permitted. If your use isn’t allowed, we’re not able to grant exceptions, so please don’t submit a request.

For commercial uses where our mapping products are used for revenue-generating purposes, such as integrating Google Maps or Street View into a mobile or web app, use Google Maps Platform instead.

Your use of our content may be acceptable under principles of fair use (or other similar concepts in other countries). Fair use is a concept under copyright law in the U.S. that, generally speaking, permits you to use a copyrighted work in certain ways without obtaining a license from the copyright holder. Google can ’ t tell you if your use of this content would be fair use. You may wish to obtain your own legal advice.

You may annotate our maps with additional information – like points, lines, or labels. In fact, many of our tools have built-in features that make it easy to do just that. For example, Google My Maps lets you draw lines and shapes on a Google map. We also offer a Styling Wizard and a cloud-based styling tool that allow you to edit the colors of individual map components (for example, changing water to purple), as well as toggle visibility for each component (for example, making roads invisible).

If neither of those fit your needs, you may export an image from Google Earth or Earth Studio, or capture a screenshot from Google Maps, to add custom labels or graphics using third-party software.

While we encourage annotations, you must not significantly alter how Google Maps, Google Earth, Earth Studio, or Street View would look online. For example, you’re not allowed to make any changes to the colors of the product interface or remove attribution.

For Google Earth and Earth Studio content, you’re not allowed to significantly alter our imagery without providing clear context that it’s a simulation, projection, or fictional content.

Our trademarks are our valuable assets, and we want to make sure our users and partners use them correctly. These trademarks include the Google Earth word mark, Google Maps word mark, Google Earth logo, Google Maps logo, Google Maps red pin element, Street View word mark, Street View icon, Pegman word mark, the Pegman logo, Local Guides icon, and the Plus Codes logo.

You may use our trademarks to accurately refer to our products or services, as long as such references are appropriate and consistent with our trademark guidelines. You may only use approved versions of our marks, and you must follow all of the general trademark usage guidelines , the Google Maps Platform Terms of Service , and the Street View Trusted badge usage guidelines . The trademark usage guidelines apply even to marks that were previously (but are no longer) used in connection with our products.

Refer to our brand elements guidelines for more information about using our icons, logos, and names.

Google Maps

You may print Google Maps content for non-commercial or personal use (for example, a map with directions). In all uses where you’ll distribute printed materials that include the content, first be sure to read the general guidelines above, especially with regard to fair use and attribution .

Even if your use isn ’t covered by fair use or some other doctrine, you can still use our content without submitting a request as long as you follow these guidelines. Note that we’re not able to grant exceptions to these rules.

Inside of books, including textbooks (up to 5k copies)

Periodicals (Newspapers, magazines, journals, etc.)

Business documents such as company reports, proposals, presentations, etc.

Supplemental navigational use in printed promotional materials, such as business cards, pamphlets, handouts, flyers, etc. (up to 5k copies) Example: A local dentist’s office using a small map at the bottom of a mail ad to show where it’s located

Print links to a Google Maps location, such as with short links or QR codes

don’t do this

Inside of books (more than 5k copies), or as cover art for a book

Used as the core part of printed navigational material (for example, tour books or guide books).

Consumer & retail goods or packaging (t-shirts, beach towels, shower curtains, mugs, posters, stationery, etc.)

Primary or creative use in printed promotional or advertising materials: Example: A full-page magazine ad for a car company using a Google Maps screenshot to show how far the car can travel

If you simply need to embed a Google map on your website , you don’t need our permission. You’re also welcome to link to Google Maps with text or a button on your website, such as “View on Google Maps” or “Open with Google Maps.”

If you need more integrated uses of our products for commercial use, we have multiple APIs available through Google Maps Platform to help you build and embed custom maps for your website or mobile app. When using these APIs, certain restrictions may apply.

If you’d like to use our content in a digital advertisement, please first review the general guidelines , especially with regard to attribution. Any use of Google Maps in digital advertisements must not significantly alter how the products and imagery would look online. See Personalizing your map for specifics.

If you’re using Google Maps for film or television (including streaming services)   – for example, if an actor uses Google Maps on a phone, or an interview subject demonstrates how they used Google Maps in their research – you should submit your project for approval according to the guidelines on the Entertainment and Media page.

If you’re using Google Maps content in an online video (e.g. YouTube) primarily for educational, instructional, recreational, or entertainment purposes, you don’t need to request permission   – but you must still follow our general guidelines and attribute properly .

If you’re using Google Maps in an online video advertisement or for promotional purposes (e.g. a real estate company showing where rental properties are available), submit your project for approval according to the guidelines on the Entertainment and Media page. Only standard Google Maps imagery may be used for this purpose, since Satellite View imagery falls under the same commercial restrictions as Google Earth.

Google Earth

Google earth or earth studio can be used for purposes such as research, education, film and nonprofit use without needing permission..

All content created from Google Earth or Earth Studio must always be properly attributed .

Google Earth content may not be used for any commercial or promotional purposes.

You may print Google Earth content for non-commercial or personal use, with some restrictions as noted below. In all uses where you’ll distribute printed materials that include the content, first be sure to read the general guidelines above, especially with regard to fair use and attribution .

As long as you follow these guidelines, you don’t need to submit a request. Note that we’re not able to grant exceptions to these rules.

Used in printed advertisements or promotional materials of any kind (flyers, pamphlets, magazines ads, etc.)

Google Earth may not be embedded online or in apps. However, you’re welcome to export and use a handful of static images, with proper attribution , for non-commercial purposes such as news, blogs, educational, recreational, or instructional use.

You may not use Google Earth imagery on the web for any commercial or promotional purposes, such as, but not limited to:

Real estate listings or company profiles

Construction site locations

Website header or social media banner images

Digital advertisements

You may not use output, or use third party tools to capture output, from Google Earth, Google Earth Pro, or Earth Studio to reconstruct 3D models or create similar content, or to create other content, products, or services that may violate our Terms of Service .

For gaming purposes, you may be interested in Google Maps Platform gaming services to create immersive, real-world games with millions of customizable 3D structures, up-to-date global data, and seamless integration with Unity.

You may use Google Earth and Earth Studio content for news broadcasts, television shows, films, documentaries, music videos, and any educational purposes. You don’t need to submit a request, but you must follow all guidelines on this page and in related resources, especially with regard to on-screen attribution . Google Earth content can never be used without attribution.

Before using Google Earth or Earth Studio, review our License Terms and Terms of Service . We also ask that you register your usage here   – we love seeing creative uses of Google Earth and appreciate the insights you share.

This license to use Google Earth and Earth Studio content applies to all types of film regardless of platform (and technology) distributed on, but doesn’t extend to content distributed from or to these territories .

Don’t do this

You may not use Google Earth or Earth Studio content (or Google Maps satellite view imagery) for promotional films, advertisements or commercials. This includes anything used specifically to sell or promote a product, business, or organization. For example, this includes uses such as, but not limited to:

A real estate company showing where their properties are located in a company video

A documentary-style film being used to promote a business or organization

A sports team using Google Earth images of their stadium in a TV commercial

If you’re using Google Earth content in an online video (e.g. YouTube) primarily for educational, instructional, recreational, or entertainment purposes, you don’t need to request permission, even if your work is monetized. But you must still follow our general guidelines and attribute properly .

Street View

Street View imagery may not be used for any print purposes. This includes:

Books, guidebooks, and textbooks

Magazines, newspapers, and journals

Advertisements or promotional materials of any kind

Consumer or retail goods (posters, t-shirts, mugs, etc.)

If you simply need to embed a Street View image or panorama on your website , you don’t need our permission. You’re also welcome to do so with our various APIs for web or mobile .

If you need more integrated use of Street View for commercial use, we have multiple APIs available through Google Maps Platform to bring the real world to your users with Street View imagery, including unique markers, overlays, and photos. When using these APIs, certain restrictions may apply.

Street View imagery can only be used in digital advertisements where you’re using the Google Maps APIs or the imagery is embedded or linked to on your website using HTML and URL provided on Google Maps .

You may not screenshot Street View imagery or remove it from embedded sources for any purpose. This ensures that if Google edits or removes imagery in response to user requests, these changes will be reflected in your project too.

Street View may only be used in television, film, or online video projects if it’s filmed directly in the context of an actor or subject using the product as-is in a device such as a laptop or phone. Street View images may not be taken out of context or removed from the software to be used for other purposes. You must submit a request if you’d like to use Street View in your project.

Additional restrictions

While we’re excited to see many uses of Street View, there are some use cases that are prohibited, including but not limited to:

Creating data from Street View images, such as digitizing or tracing information from the imagery

Using applications to analyze and extract information from the Street View imagery

Downloading Street View images to use separately from Google services (such as an offline copy)

Merging or stitching together multiple Street View images into a larger image

These restrictions apply to all academic, nonprofit, and commercial projects.

Required attribution

All uses of Google Maps, Google Earth, and Street View content must provide attribution to Google and, if applicable, to our data providers.

We do not approve of any use of content without proper attribution, in any circumstances, and we require attribution while the content is shown. Requests for exceptions will not be answered or granted.

Where do I find the attribution?

You can find the attribution in the line(s) shown on the bottom of the content in our mapping products along with copyright notices, such as “Map data ©2019 Google”. Note that the exact text of the attribution changes based on geography and content type.

When using content from Google Maps, Google Earth, or Street View in your work, follow these guidelines to ensure you’re properly crediting Google and any relevant third-party data providers.

done Use provided tools

Attribution information will appear automatically on certain types of imagery when using Google-provided tools, such as web embeds , APIs , or exports from Google Earth Pro or Earth Studio . Please use these methods whenever possible.

close Don’t modify the attribution

Don’t remove, obscure, or crop out the attribution information. Note that Google logos cannot be used in-line (for example, “These maps from [Google logo].”)

done Keep the attribution close

If using screenshots of our imagery outside of direct embeds, include the standard attribution as it appears in the image. If necessary, you may customize the style and placement of the attribution text, as long as the text is within close proximity of the content and legible to the average viewer or reader.

close Don’t separate the attribution

You may not move the attribution away from the content, such as to the end of your book, the credits of your film or show, or the footer of your website.

done Include third-party data providers

Some of the data and images on our mapping products come from providers other than Google. If using such imagery, the text of your attribution must say the name “Google” and the relevant data provider(s), such as “Map data: Google, Maxar Technologies”.

close Don’t give us all the credit

When there are third-party data providers cited with the imagery, only including “Google” or the Google logo is not proper attribution.

Not what you need?

View all of our guidance on using Google brand elements

Google Maps is getting geospatial AR content later this year

At its annual Google I/O 2024 conference , Google announced that users will soon be able to access geospatial augmented reality (AR) content directly on Google Maps on their phones. The feature will first appear in Singapore and Paris as part of a pilot program launching later this year.

Users will be able to access the AR content by first searching for a location in Google Maps. If the location has AR content and the user is near the place, they will have to tap on the image that says “AR Experience” and then lift their phone. 

If someone is exploring a place remotely, they can see the same AR experience in Street View. After exploring the AR content, users can share the experience through a deep link URL or QR code on social media.

In Singapore, users will be able to explore popular landmarks like Singapore’s Chinatown and Gardens by the Bay, as well as check out the local dishes and watch a ceremonial dragon dance. In Paris, users will be able to see the scene of the 1900 Exposition Universelle country pavilions along the Seine River and visualize the different modifications to the famous Eiffel Tower.

Google says these AR capabilities lay the foundation for the extended reality (XR) platform that it’s building in collaboration with Samsung and Qualcomm for the Android ecosystem.

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Ten years ago, Dr. Jeff Lichtman — a professor of molecular and cellular biology at Harvard University — received a small brain sample in his lab.

Although tiny, the 1 cubic millimeter of tissue was big enough to contain 57,000 cells, 230 millimeters of blood vessels and 150 million synapses.

“It was less than a grain of rice, but we began to cut it and look at it, and it was really beautiful,” he said. “But as we were accumulating the data, I realized that we just had way, way more than we could handle.”

Eventually, Lichtman and his team ended up with 1,400 terabytes of data from the sample — roughly the content of over 1 billion books . Now, after the lab team’s decade of close collaboration with scientists at Google, that data has turned into the most detailed map of a human brain sample ever created.

300 million images

The brain sample came from a patient with severe epilepsy. It’s standard procedure, Lichtman said, to remove a small portion of the brain to stop the seizures, and then look at the tissue to make sure it’s normal. “But it was anonymized, so I knew next to nothing about the patient, other than their age and gender,” he said.

To analyze the sample, Lichtman and his team first cut it into thin sections using a knife with a blade edge made of diamond. The sections were then embedded into a hard resin and sliced again, very thinly. “About 30 nanometers, or roughly 1,000th of the thickness of a human hair. They were virtually invisible, if it weren’t for the fact that we had stained them with heavy metals, which made them visible when doing electron imaging,” he said.

The team ended up with several thousand slices, which were picked up with a custom-made tape, creating a sort of film strip: “If you take a picture of each of those sections and align those pictures, you get a three-dimensional piece of brain at the microscopic level.”

That’s when the researchers realized they needed help with the data, because the resulting images would take up a significant amount of storage.

Lichtman knew that Google was working on a digital map of a fruit fly’s brain , released in 2019, and had the right computer hardware for the job. He got in touch with Viren Jain, a senior staff research scientist at Google who was working on the fruit fly project.

“There were 300 million separate images (in Harvard’s data),” Jain said. “What makes it so much data is that you’re imaging at a very high resolution, the level of an individual synapse. And just in that small sample of brain tissue there were 150 million synapses.”

To make sense of the images, scientists at Google used AI-based processing and analysis, identifying what type of cells were in each picture and how they were connected. The result is an interactive 3D model of the brain tissue, and the largest dataset ever made at this resolution of a human brain structure. Google made it available online as “ Neuroglancer ,” and a study was published in the journal Science at the same time, with Lichtman and Jain among the coauthors.

Understanding the brain

The collaboration between the Harvard and Google teams resulted in colorized images that make the individual components more visible, but they are otherwise a truthful representation of the tissue.

“The colors are completely arbitrary,” Jain explained, “but beyond that, there’s not much artistic license here. The whole point of this is that we’re not making it up — these are the real neurons, the real wires that exist in this brain, and we’re really just making it convenient and accessible for biologists to view and study.”

The data contained some surprises. For example, rather than forming a single connection, pairs of neurons instead have more than 50. “This is kind of like if two houses on a block had 50 separate phone lines connecting them. What’s going on there? Why are they so strongly connected? We don’t know what the function or significance of this phenomenon is yet, we’re going to have to study it further,” he said.

Eventually, observing the brain at this level of detail could help researchers make sense of unresolved medical conditions, according to Lichtman.

“What does it mean to understand our brain? The best we may be able to do is describe it, and hope that from these descriptions will come a realization, for example, about how normal brains are different from brains that are disordered, in adult psychiatric diseases or developmental disorders like the autism spectrum — that kind of comparison will be very valuable,” he said. “Eventually, it will give us some insight into what’s wrong, which, in most cases, we’re still in the dark about.”

Lichtman also believes that the dataset may be filled with other amazing details that, because of its size, haven’t been discovered yet: “And that’s why we’re sharing it online, so anyone can look at it and find things,” he added.

Next up, the team behind the project aims to create a full map of the brain of a mouse, which would require between 500 and 1,000 times the amount of data of the human brain sample.

“That would mean 1 exabyte, which is 1,000 petabytes,” Lichtman said. “A lot of people are thinking hard about how we’re going to do this, and we’re in the first year of a five-year proof of principle. I think that would be a watershed moment for neuroscience, to have a complete mammalian brain’s wiring diagram; it would answer many, many questions. And of course, it would reveal many more problems, things we hadn’t expected.”

What about mapping an entire human brain? That would be another 1,000 times bigger, Lichtman explained, which means the data would amount to 1 zettabyte . In 2016, that was the size of the entire internet traffic for the year, according to Cisco . At the moment, Lichtman said, it would not only be difficult to even store that much data, but there would be no ethically acceptable way of sourcing a pristine, well-preserved human brain.

Breaking new ground

Researchers in the same field who were not involved with the work expressed their enthusiasm when approached by CNN for comment.

“This study is wonderful, and there is so much to learn from data like this,” said Michael Bienkowski, an assistant professor of physiology and neuroscience at the University of Southern California’s Keck School of Medicine.

“Much of what we think we understand about the human brain is extrapolated from animals, but research like this is critical for revealing what truly makes us human. Visualizing neurons and other brain cells is really challenging due to their sheer density and complexity, and the current dataset does not capture the longer-range connections,” Bienkowski said.

“What other brain regions are these inputs originating from, and where do the outputs go once they leave the area? But to see all these different cell types and their interactions is incredible and makes you appreciate what a masterpiece of architecture life has given us,” he added.

Andreas Tolias, a professor of ophthalmology at Stanford University in California, agreed. “This is a remarkable technical study that reconstructs the structure of the human cortex at high resolution,” he said. “I was particularly excited about the discovery of rare axons capable of forming up to 50 synapses. This finding is intriguing and raises important questions about their computational roles.”

The brain-mapping project opens the door for future investigations, according to neuroscientist Olaf Sporns.

“Each human brain is a vast network of billions of nerve cells,” said Sporns, distinguished professor of psychological and brain sciences at Indiana University. “This network allows cells to communicate, in very specific patterns that are fundamental for memory, thought, and behavior. Mapping this network, the human connectome, is critical for figuring out how the brain works,” he added, noting that the study breaks new ground toward this important goal, and offers exciting new opportunities for exploration and discovery.

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• 09 May 2024

Cubic millimetre of brain mapped in spectacular detail

• Carissa Wong

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Rendering based on electron-microscope data, showing the positions of neurons in a fragment of the brain cortex. Neurons are coloured according to size. Credit: Google Research & Lichtman Lab (Harvard University). Renderings by D. Berger (Harvard University)

Researchers have mapped a tiny piece of the human brain in astonishing detail. The resulting cell atlas, which was described today in Science 1 and is available online , reveals new patterns of connections between brain cells called neurons, as well as cells that wrap around themselves to form knots, and pairs of neurons that are almost mirror images of each other.

The 3D map covers a volume of about one cubic millimetre, one-millionth of a whole brain, and contains roughly 57,000 cells and 150 million synapses — the connections between neurons. It incorporates a colossal 1.4 petabytes of data. “It’s a little bit humbling,” says Viren Jain, a neuroscientist at Google in Mountain View, California, and a co-author of the paper. “How are we ever going to really come to terms with all this complexity?”

Slivers of brain

The brain fragment was taken from a 45-year-old woman when she underwent surgery to treat her epilepsy. It came from the cortex, a part of the brain involved in learning, problem-solving and processing sensory signals. The sample was immersed in preservatives and stained with heavy metals to make the cells easier to see. Neuroscientist Jeff Lichtman at Harvard University in Cambridge, Massachusetts, and his colleagues then cut the sample into around 5,000 slices — each just 34 nanometres thick — that could be imaged using electron microscopes.

Jain’s team then built artificial-intelligence models that were able to stitch the microscope images together to reconstruct the whole sample in 3D. “I remember this moment, going into the map and looking at one individual synapse from this woman’s brain, and then zooming out into these other millions of pixels,” says Jain. “It felt sort of spiritual.”

A single neuron (white) shown with 5,600 of the axons (blue) that connect to it. The synapses that make these connections are shown in green. Credit: Google Research & Lichtman Lab (Harvard University). Renderings by D. Berger (Harvard University)

When examining the model in detail, the researchers discovered unconventional neurons, including some that made up to 50 connections with each other. “In general, you would find a couple of connections at most between two neurons,” says Jain. Elsewhere, the model showed neurons with tendrils that formed knots around themselves. “Nobody had seen anything like this before,” Jain adds.

The team also found pairs of neurons that were near-perfect mirror images of each other. “We found two groups that would send their dendrites in two different directions, and sometimes there was a kind of mirror symmetry,” Jain says. It is unclear what role these features have in the brain.

Proofreaders needed

The map is so large that most of it has yet to be manually checked, and it could still contain errors created by the process of stitching so many images together. “Hundreds of cells have been ‘proofread’, but that’s obviously a few per cent of the 50,000 cells in there,” says Jain. He hopes that others will help to proofread parts of the map they are interested in. The team plans to produce similar maps of brain samples from other people — but a map of the entire brain is unlikely in the next few decades, he says.

“This paper is really the tour de force creation of a human cortex data set,” says Hongkui Zeng, director of the Allen Institute for Brain Science in Seattle. The vast amount of data that has been made freely accessible will “allow the community to look deeper into the micro-circuitry in the human cortex”, she adds.

Gaining a deeper understanding of how the cortex works could offer clues about how to treat some psychiatric and neurodegenerative diseases. “This map provides unprecedented details that can unveil new rules of neural connections and help to decipher the inner working of the human brain,” says Yongsoo Kim, a neuroscientist at Pennsylvania State University in Hershey.

doi: https://doi.org/10.1038/d41586-024-01387-9

Shapson-Coe, A. et al. Science 384 , eadk4858 (2024).

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Epic science inside a cubic millimeter of brain.

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Researchers publish largest-ever dataset of neural connections

A cubic millimeter of brain tissue may not sound like much. But considering that that tiny square contains 57,000 cells, 230 millimeters of blood vessels, and 150 million synapses, all amounting to 1,400 terabytes of data, Harvard and Google researchers have just accomplished something stupendous.   

Led by Jeff Lichtman, the Jeremy R. Knowles Professor of Molecular and Cellular Biology and newly appointed dean of science , the Harvard team helped create the largest 3D brain reconstruction to date, showing in vivid detail each cell and its web of connections in a piece of temporal cortex about half the size of a rice grain.

Published in Science, the study is the latest development in a nearly 10-year collaboration with scientists at Google Research, combining Lichtman’s electron microscopy imaging with AI algorithms to color-code and reconstruct the extremely complex wiring of mammal brains. The paper’s three first co-authors are former Harvard postdoc Alexander Shapson-Coe, Michał Januszewski of Google Research, and Harvard postdoc Daniel Berger.

The ultimate goal, supported by the National Institutes of Health BRAIN Initiative , is to create a comprehensive, high-resolution map of a mouse’s neural wiring, which would entail about 1,000 times the amount of data the group just produced from the 1-cubic-millimeter fragment of human cortex.  

“The word ‘fragment’ is ironic,” Lichtman said. “A terabyte is, for most people, gigantic, yet a fragment of a human brain — just a minuscule, teeny-weeny little bit of human brain — is still thousands of terabytes.”  

Jeff Lichtman.

Kris Snibbe/Harvard Staff Photographer

The latest map contains never-before-seen details of brain structure, including a rare but powerful set of axons connected by up to 50 synapses. The team also noted oddities in the tissue, such as a small number of axons that formed extensive whorls. Because the sample was taken from a patient with epilepsy, the researchers don’t know whether such formations are pathological or simply rare.

Lichtman’s field is connectomics, which seeks to create comprehensive catalogs of brain structure, down to individual cells. Such completed maps would unlock insights into brain function and disease, about which scientists still know very little.

Google’s state-of-the-art AI algorithms allow for reconstruction and mapping of brain tissue in three dimensions. The team has also developed a suite of publicly available tools researchers can use to examine and annotate the connectome.

“Given the enormous investment put into this project, it was important to present the results in a way that anybody else can now go and benefit from them,” said Google collaborator Viren Jain.

Next the team will tackle the mouse hippocampal formation, which is important to neuroscience for its role in memory and neurological disease.

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See the most detailed map of human brain matter ever created

Explore the tiny 'pizza slice' down to the neuron.

By Lauren Leffer | Published May 9, 2024 2:00 PM EDT

A cubic millimeter is, by all accounts, tiny. It’s barely noticeable–a speck or fleck or crumb. But look closely enough and you can uncover an entire world inside a particle of material. A team of neuroscientists and engineers, aided by machine learning tools, have charted a cubic millimeter volume of the human brain at nanoscale resolution, tracing every neuron, synapse, blood vessel, and supporting cell within the fragment and reconstructing a 3D model of the tissue. Though it represents just one-millionth of the total brain volume, it is the most detailed map of a piece of human brain matter ever created. It could spur a wave of scientific discovery about neurological disorders, brain structure, and the origins of our behavior. 

“In one respect, our data set is miniscule,” Jeff Lichtman , co-senior study researcher and a neuroscientist and professor of molecular and cellular biology at Harvard University, tells PopSci . “But it doesn’t feel small because when you get in it, you see it’s like a gigantic forest. It’s a very tiny forest, but it’s a very, very, very complicated forest,” he adds. 

All that complexity is on display in a study documenting the construction of this bit of comprehensive brain map or “connectome,” published May 9 in the journal Science . The first connectome was of a nematode brain, completed in 1986 . Since then, neuroscientists have continued to plot out increasingly large and complicated brains–including those of fruit flies, maggots, a tadpole, and an earthworm. Yet human brains pose a unique mapping challenge in their intricacy and inaccessibility. The new, partial human connectome is available online for anyone to explore.

“Not only is this an impressive technological feat, this is a tool and a resource that is really aimed at sharing with the world and getting all of this scientific information out there,” Tim Mosca , a neuroscientist at Thomas Jefferson University who was uninvolved in the new work, tells PopSci . “This group has done an amazing job designing all of the new tools and the pipelines to make this available to anyone who wants to look at it, wants to think about it, wants to use this in their research.” 

Serving up brain pizza

The study sample was collected over a decade ago from an anonymous patient undergoing epilepsy surgery. The surgeon removed a small piece of the temporal lobe to access and treat an underlying lesion, quickly preserved the tissue, and later shared it with scientists. Though the total volume of the fragment is about 1 cubic millimeter, it is not cube shaped. Instead, “it’s like a thick piece of pizza–but it’s not that thick,” says Lichtman. This blunt, triangular chunk, longer than it is wide, enabled the researchers to capture a bit of all six layers of the 3mm thick cerebral cortex. 

The first step to mapping the brain pizza was to slice it into 5,019 individual cross sections (each 30 nanometers thin) mounted on tape using a specially designed machine that cuts with a diamond knife. From there, the researchers spent a full year carefully imaging each slice via electron microscope. Then, they digitally aligned and stitched together the slices and used multiple machine learning tools to fill out the 3-D form and label and color each component. 

The segment’s neuron density is 16,000 neurons per cubic millimeter– about one-third lower than a previous density estimate of the same brain section and 10 times less dense than the corresponding section of a mouse’s brain, per the study. Glial cells, the connective glue that keeps brain tissue together, outnumber neurons in the fragment by a two to one ratio. 

Neural explorers

The physical size of the brain fragment may be teeny, but the level of detail means the data captured by the mapping effort is massive. The reconstructed segment is 1.4 petabytes in digital size, or 1,400 terabytes (equivalent to the storage capacity of about 2,800 average laptops). Within that, there is lots to potentially discover: individual neural circuits, previously unobserved cellular ratios and shapes, the makeup of each cortical layer, and more. 

“It’s like being an explorer that lands on a new island,” says Lichtman. “You keep looking around and you’re just going to keep finding new things.” 

Already, Lichtman and his many co-researchers have made some interesting observations. Amid the ~150 million synapses they mapped, they found a rare type of particularly strong connection. In the vast majority (96.5%) of cases, axons–the outgoing transmission line of neurons– formed one connection with a target cell. Some (about 3%) made 2 connections. But less than .01% forged more than four synapses, including some axons and target cells that were connected at over 50 points. 

“We’ve always had a theory that there would be super connections, if you will, amongst certain cells,” says Mosca. “But it’s something we’ve never had the resolution to prove…Now we know that it exists and we can go after the question of what it does.” Lichtman’s current hypothesis is that these extra-fortified connections are the sort of hyper-fast pathways that enable “automatic use of the brain” for well-established, learned actions. 

Another new observation: many dendrites (the branching extensions of neurons that generally receive inputs) seem to mirror each other–pointing symmetrically in one of just two directional arrangements out of infinite three-dimensional possibilities. “We’d never seen anything like that [before],” says Lichtman. “Why are they doing that? We don’t know… [it is] a complete mystery.” 

The scientists further found a new type of unexplained structure that they’ve named an “axon whorl,” wherein long axon cables appear to tangle around themselves. Though it wasn’t every neuron, some axons contained multiple knots, says Viren Jain , co-senior study author and a senior staff scientist at Google where he leads the company’s Connectomics research team. Again, the function and cause of these whorls is unknown. “We were not expecting to find such a structure. It’s very peculiar… like a big jumble of wiring that sort of contravenes the purpose of a wire to begin with, which is to go places and contact other things.” 

These three findings are likely just the tip of the iceberg. “The data set is so large that one human being or lab group can not explore it [all], but a bunch of human beings can,” Lichtman says. Because of the open nature of the project, more than 200 papers have cited the brain reconstruction since it was first released as a pre-print, Jain points out.

In addition to being a large, fundamental advance in science, discoveries resulting from this partial connectome could eventually help us better understand and treat brain diseases. “The ability to measure neural wiring of human brains in such detail opens up exciting opportunities for advancing human health,” says Andrew Leifer , a physicist and neuroscientist at Princeton University who wasn’t involved in the project. “One could imagine comparing different brains to understand how brain wiring changes when a healthy brain suffers from a disease or falls into dysfunction,” he adds. 

Pushing into future frontiers 

But though there is lots to be discovered, there are also limits. The automated machine learning methods which were key to enabling such a large-scale endeavor carry a margin of error that requires human oversight to correct. Editing will be an ongoing project, and is a community science effort anyone who wants to can apply to participate in . 

The sample is also only one small piece of one person’s brain. There is much that can’t yet be inferred about human brains generally or other brain regions beyond the temporal lobe based on this single fragment without more samples and maps for comparison, notes Lichtman. 

And, perhaps most critically, the brain segment came from someone undergoing surgery for epilepsy–it may not represent a “normal” brain and there’s no way to know for sure unless and until we have more bits to assess, say Jain and Lichtman. “But we are planning many follow-ups to this,” Jain adds. 

The team has ambitions to construct multiple partial connectomes representing additional human brain samples. They are also working on zebrafish connectome, and are planning to tackle increasingly large segments of the mouse brain. Mammalian brains share many similarities, so a complete mouse connectome could offer new insights into our own brain as well as the evolution of brains across animals, Lichtman says. 

At the moment, with currently available technologies (and the ethical implications), a complete connectome of the human brian is “a bridge too far,” says Lichtman. “Literally, we’re a million times away from that,” says Jain. But through this study, the scientists have taken an early (if miniscule) step in that direction, and even the smallest peephole can be a portal into a whole universe of knowledge. 

“I would love people to think about this the same way they think about the Hubble or James Webb telescope,” says Lichtman. “We’re peering into an unknown domain, and one that is much more relevant to us than distant outer space. It’s this inner space that each of us have on our shoulders that we use, but know almost nothing about.” 

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6 incredible images of the human brain built with the help of Google's AI

May 09, 2024

[[read-time]] min read

A team of researchers and neuroscientists have collaborated to unravel the brain’s intricacies.

General summary

Incredible brain imagery is now possible with the help of Google's AI. A joint team of Google researchers and Harvard neuroscientists have reconstructed nearly every cell and all of its connections within a small volume of human brain tissue. This 3D mapping required a monumental 1.4 petabytes of data and provides an unprecedented view into the human brain, which could help researchers understand neurological disorders and answer fundamental questions about how the brain works. The team's findings include the discovery of mirror-image clusters of cells, "axon whorls," and intricate networks of axons that communicate with neurons.

One of the ways artificial intelligence (AI) can be used is to help researchers make sense of huge amounts of data — including in science and medicine. We are members of a joint team of Google researchers and Harvard neuroscientists who have come together to build an unprecedented view into the human brain, which could help researchers understand neurological disorders and answer fundamental questions about how the brain works. By combining brain imaging with AI-based image processing and analysis, our teams have reconstructed nearly every cell and all of its connections within a small volume of human brain tissue about half the size of a grain of rice. Though it's of a small region of brain, this 3D mapping – which we’ve made freely available to the scientific community – nonetheless requires a monumental 1.4 petabytes (1.4 million gigabytes) to encode. Here’s what we found:

1. A view through six layers of the brain

Harvard researchers began by collecting thousands of extremely thin cross-sectional images from a donated brain sample. The small piece of healthy brain had to be removed during surgery on a woman with epilepsy to allow surgeons to reach the part they needed to operate on. A small piece of that otherwise discarded tissue was preserved as part of an IRB-approved study for later analysis.

The Google Research team developed advanced AI tools to construct an interactive 3D model of the brain tissue. The model underscores how complex the human brain is: describing just this small sample — one-millionth of the total human brain and about 3 mm long — requires more than a million Gigabytes of data: 1.4 Petabytes. This is the largest dataset ever made of human brain structure at this resolution.

Credit: Google Research & Lichtman Lab (Harvard University). Renderings by D. Berger (Harvard University)

The sample came from a part of the cortex (gray matter) called the anterior temporal lobe (see figure). The cortex has six layers, and by coloring the neurons according to their size and type, the layers are visible in this zoomed-out view of all of the neurons. The surface of the brain is at the top edge of the image.

Credit: Google

2. A dense and intricate map

The one cubic millimeter tissue sample contained about 50,000 cells and about 150 million synapses — the points of connection where signals cross from one neuron to another. Some neuron pairs had the surprising property of being connected to each other extremely strongly — through as many as 50 synapses. Researchers don’t know why they do this. This image shows a closeup of all of one type of neuron — the excitatory neuron — colored by size with red largest and blue smallest. The cells are about 15-30 micrometers across at their core.

3. A mirrored dance

An intriguing finding in the reconstruction was the existence of clusters of cells that tended to occur in mirror-image orientation to one another. This image shows a particularly symmetric pair.

4. Swimming in synapses

Neurons in the brain are intensely connected. This single neuron (white) has more than 5,000 axons (blue) arriving from other neurons to bring signals — and at least that many synapses where the signals cross from the axon to the receiving neuron. The synapses are shown in green.

5. A curious finding: whorls of axons

A surprising finding of this research was the occurrence of “axon whorls.” Axons (blue) are the filamentous part of a nerve cell that carries a signal away from the cell. These looped piles of axon were rare in the sample, and in some cases they sat on the surface of another cell (yellow). Their function is unknown.

6. Serious networking

A single neuron (white) receives signals that determine whether or not the neuron fires. This image shows all of the axons that can tell it to fire (green) and all of those that can tell it not to (blue). Multiply this by the whole brain and that’s a lot of talking!

There is still a lot more to observe and understand from our reconstruction of this piece of human brain, and we hope other researchers will use the data to make additional discoveries. Scientists believe that by continuing research into the brain’s connections, they can one day understand things like how our memories form or what leads to neurological disorders and diseases like autism and Alzheimer’s.

Find out more about Google’s work on our Neural Mapping site , and learn more about this study at the Google Research Blog

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