The first complete activity map of the brain has been unveiled by a large international collaboration of neuroscientists including at UCLA Health.
The International Brain Laboratory (IBL) researchers published their findings today in two papers in Nature, revealing insights into how decision-making unfolds across the entire brain in mice at the resolution of single cells. This brain-wide activity map challenges the traditional hierarchical view of information processing in the brain and shows that decision-making is distributed across many regions in a highly coordinated way.
“This is the first time anyone has produced a full, brain-wide map of the activity of single neurons during decision-making. The scale is unprecedented as we recorded from over half a million neurons across mice in 12 labs, covering 279 brain areas, which together represent 95% of the mouse brain volume. The decision-making activity, and particularly reward, lit up the brain like a Christmas tree,” explained Professor Alexandre Pouget, Co-Founder of IBL and Group Leader at the University of Geneva.
Brain-wide map showing 75,000 analysed neurons lighting up during different stages of decision-making. Credit: International Brain Laboratory
The brain map was made possible by a major international collaboration of neuroscientists from multiple universities across Europe and the US. Officially launched in 2017, IBL introduced a new model of collaboration in neuroscience that uses a standardized set of tools and data processing pipelines shared across multiple labs, ensuring data reproducibility. This visionary approach, supported by Wellcome and the Simons Foundation, draws inspiration from large-scale collaborations in physics and biology, such as CERN and the Human Genome Project.
“We’d seen how successful large-scale collaborations in physics had been at tackling questions no single lab could answer, and we wanted to try that same approach in neuroscience. The brain is the most complex structure we know of in the universe and understanding how it drives behavior requires international collaboration on a scale that matches that complexity,” commented Professor Tom Mrsic-Flogel, Director of the Sainsbury Wellcome Centre at UCL and one of the core members of IBL.
Researchers across 12 labs used state-of-the-art electrodes for simultaneous neural recordings, called Neuropixels probes, to measure brain activity while mice were carrying out a decision-making task. In the task, a mouse sits in front of a screen and a light appears on the left or right side. The mouse then responds by moving a small wheel in the appropriate direction to receive a reward.
However, in some trials, the light is so faint that the animal must guess which way to turn the wheel. The mouse uses how often the light has appeared on the left or right previously to help them make this guess. These challenging trials therefore allowed the researchers to study how prior expectations influence perception and decision-making.
The first paper, “A brain-wide map of neural activity during complex behaviour,” showed that decision-making signals are surprisingly distributed across the brain, not localized to specific regions. This adds to a growing number of studies that challenge the traditional hierarchical model of brain function and emphasizes that there is constant communication across brain areas during decision-making, movement onset, and even reward. This brain-wide activity means that neuroscientists will need to take a more holistic, brain-wide approach when studying complex behaviors in future.
The second paper, “Brain-wide representations of prior information,” showed that prior expectations, our beliefs about what is likely to happen based on our recent experience, are encoded throughout the brain. Surprisingly, these expectations are not only found in cognitive areas, but also brain areas that process sensory information and control actions. For example, expectations are even encoded in early sensory areas such as the thalamus, the brain’s first relay for visual input from the eye. This supports the view that the brain acts as a prediction machine, but with expectations encoded across multiple brain structures playing a central role in guiding behavior responses. These findings could have implications for understanding conditions such as schizophrenia and autism, which are thought to be caused by differences in the way expectations are updated in the brain.
“The efforts of our collaboration generated fundamental insights about the brain-wide circuits that support complex cognition; this is really exciting and a major step forward relative to the “piecemeal” approach (1-2 brain areas at a time) that was previously the accepted method in the field. Moreover, our team took rigor and reproducibility very seriously. We developed an entire task force that leveraged our unique, multi-lab approach to determine the extent to which our efforts at standardization enhanced reproducibility. My hope going forward is that both our scientific discoveries and our new insights on reproducibility will have an impact in the field,” commented Dr. Anne Churchland, professor of Neurobiology at the University of California, Los Angeles (UCLA) and one of the core members of IBL.
“Traditionally, neuroscience has looked at brain regions in isolation. Recording the whole brain means we now have an opportunity to understand how all the pieces fit together. This was too big of a project for any one lab, and a collaboration on this scale was only possible because of the dedication and talent of our staff scientists, who are the best in the business,” commented Dr Kenneth Harris, Professor of Quantitative Neuroscience at UCL and one of the core members of IBL.
“It’s immensely gratifying to see the IBL deliver the first brain-wide map of neural activity with such high spatial and temporal resolution. The map describes the activity of over 650,000 individual neurons with single-spike resolution. This activity underlies the brain’s sensory and motor activity that constitutes a decision. The map is a fantastic resource that is already being mined by myriad scientists, and yielding unexpected discoveries. It’s a great success for team science and open science,” commented Dr Matteo Carandini, Professor of Visual Neuroscience at UCL and one of the core members of IBL.
Looking ahead, the team at IBL plan to expand beyond their initial focus on decision-making to explore a broader range of neuroscience questions. With renewed funding in hand, IBL aims to expand its research scope and continue to support large-scale, standardized experiments. As per the IBL model, it will continue to share its tools, data pipelines and platforms with the global scientific community to democratize and accelerate science and enhance data reproducibility.
“The brain-wide map is undoubtedly an impressive achievement, but it marks a beginning, not the grand finale. The IBL has shown how a global team of scientists can unite, pushing each other beyond comfort zones into uncharted territories no single lab could reach alone. For me, working within the IBL meant constantly confronting the limits of my own knowledge while learning from the extraordinary expertise of colleagues. The IBL has set the highest standards for sharing high-quality data, tools, and resources to accelerate scientific progress. Now, the next horizon is to extend this collective expertise to the entire community. We envision diverse groups of scientists joining IBL to pursue their own projects, leveraging the unique expertise of the IBL staff and benefiting from the open exchange of data and ideas that only large-scale collaboration can offer,” commented Tatiana Engel, Associate Professor at Princeton University and one of the core members of IBL.
All data from these studies, along with detailed specifications of the tools and protocols used for data collection, are openly accessible to the neuroscience community for further analysis and research. Summaries of these resources can be viewed and downloaded on the IBL website under the sections: Data, Tools, Protocols.
This research was supported by grants from Wellcome (209558 and 216324), the Simons Foundation, The National Institutes of Health (NIH U19NS12371601), the National Science Foundation (NSF 1707398), the Gatsby Charitable Foundation (GAT3708), and by the Max Planck Society and the Humboldt Foundation.
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Read the full papers in Nature:
