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Structural basis for connections between brain neurons revealed

Image: iLexx/iStock

Even the simplest networks of neurons in the brain are composed of millions of connections. Examining these vast networks is critical to understanding how the brain works. 

Now, an international team of researchers, led by Wei-Chung Allen Lee, instructor in neurobiology at Harvard Medical School, R. Clay Reid of the Allen Institute for Brain Science in Seattle and Vincent Bonin of Neuro-Electronics Research Flanders (NERF), has published the largest network to date of connections between neurons in the visual cortex.

This work has revealed several crucial elements of how networks in the brain are organized. The results appear in the journal Nature.

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“This study marks a landmark moment in a substantial chapter of work,” said Lee, who is lead author on the paper. “But it is just the beginning. We now have the tools to embark on reverse engineering the brain by discovering relationships between circuit wiring and neuronal and network computations.” 

“For decades,” added Bonin, a principal investigator at NERF, “researchers have studied brain activity and wiring in isolation, unable to link the two. Our work bridges these two realms with unprecedented detail, linking electrical activity in neurons with the nanoscale synaptic connections they make with one another.”

Lee and Bonin began this research by identifying neurons in the mouse visual cortex that responded to particular visual stimuli, such as vertical or horizontal bars on a screen. Lee then made ultrathin slices of brain and captured millions of detailed images of those targeted cells and synapses, which were then reconstructed in three dimensions. Teams of annotators on both coasts of the United States simultaneously traced individual neurons through the 3-D stacks of images and located connections between individual neurons.

Analyzing this wealth of data yielded several results, including the first direct structural evidence to support the idea that neurons that do similar tasks are more likely to be connected to each other than to neurons that carry out different tasks. Furthermore, those connections are larger, despite the fact that they are tangled with many other neurons that perform entirely different functions.

“We have found some of the first anatomical evidence for modular architecture in a cortical network as well as the structural basis for functionally specific connectivity between neurons,” Lee noted. “The approaches we used allowed us to define the organizational principles of neural circuits. We are now poised to discover cortical connectivity motifs, which may act as building blocks for cerebral network function.”

“Part of what makes this study unique is the combination of functional imaging and detailed microscopy,” said Reid, a senior investigator at the Allen Institute. “The microscopic data is of unprecedented scale and detail. We gain some very powerful knowledge by first learning what function a particular neuron performs, and then seeing how it connects with neurons that do similar or dissimilar things.

“It’s like a symphony orchestra with players sitting in random seats,” Reid added. “If you listen to only a few nearby musicians, it won’t make sense. By listening to everyone, you will understand the music. If you then ask who each musician is listening to, you might even figure out how they make the music.”

The data from the present study are being made available online for other researchers to investigate.

This work was supported by the National Institutes of Health (R01 EY10115, R01 NS075436 and R21 NS085320); through resources provided by the National Resource for Biomedical Supercomputing at the Pittsburgh Supercomputing Center (P41 RR06009) and the National Center for Multiscale Modeling of Biological Systems (P41 GM103712); the Harvard Medical School Vision Core Grant (P30 EY12196); the Bertarelli Foundation; the Edward R. and Anne G. Lefler Center; the Stanley and Theodora Feldberg Fund; Neuro-Electronics Research Flanders (NERF); and the Allen Institute for Brain Science.

Adapted from an Allen Institute news release.