MacLean lab observes that the brain represents sound and touch using the same basic circuit wiring diagram
According to a new study from Jason Maclean's lab, sensory regions of the brain responsible for processing sound and touch are built upon common principles of organization.
The study, published in the August issue of The Journal of Neuroscience, supports the hypothesis that the brain is organized in basic repeating units called microcircuits. This idea was first suggested in the 1950s, but only recently has the technology existed to test this hypothesis on the large scale.
“The brain is made up of billions of cells so understanding how it works is a daunting task,” said study author Alexander Sadovsky, a PhD student in the MacLean Lab. “Our goal is to simplify the problem by understanding how groups of cells work in circuits to create Lego-like building blocks for computation. If we are able to find patterns in neural organization, we can understand how the brain works at a more general level.”
The study focuses on describing circuits in the primary auditory and primary somatosensory cortex, some of the first brain areas information from the outside world is relayed to after a sound or touch. These regions are in physically different locations but share similar physical traits. Anatomical work has shown that the regions have similar looking cells, but the functional activity of complete circuits had not previously been explored.
In order to study the brain at this circuit level Sadovsky and other members of the MacLean lab have developed a custom laser scanning methodology that allows them to record the firing patterns of up to a thousand neurons at a time. The technology, termed HOPS (Heuristically Optimal Path Scanning), gives the lab a unique position to explore the activity of entire circuits as opposed to being limited to the behavior of single cells.
“No single neuron can communicate the full information in a neural circuit on which the brain relies for its functioning,” said Jason MacLean, PhD. “These organized circuit patterns are analogous to the scrolling text in a large LCD billboard like in Times Square: While no single light can convey even a single word, the array of lights can convey a full phrase or sentence through their patterned activity.”
Analyzing patterns of interaction between so many neurons was a difficult task, which the group solved using techniques originally designed to explore social networks. “The problem of neural connectivity naturally lends itself to a graph based analysis,” explained Sadovsky. “We can ask questions about how neurons are clustered, arranged into modules, or have similar shortest circuit path distances. These topics are analogous to asking if your friends are friends with each other, members of unique cliques, or have mutual acquaintances on a site like Facebook.” The group applied these approaches to 350 datasets comprising 21,338 neurons across the two sensory cortical regions.
The group found that while both areas of the brain showed similar circuit activity, somatosensory cortex showed activity that was a scaled up version of the patterns measured in auditory cortex. Computer modeling using high end graphic card hardware confirmed these results. Furthermore, computer models demonstrated that any changes to the unique wiring diagram of each region would dramatically change how the region processed information. The work suggests that the rules that govern neural connectivity generalize across sensory cortices. These rules result in hallmarks of efficient information processing, like the existence of “hub” neurons, which serve as relay points that transmit information to many other neurons, being common to both sensory brain regions.
The work ultimately helps to elucidate the wiring diagram underlying neuronal information processing in the brain. It provides scientists a foundation to make generalizations that allow the study of patterns of cells rather than attempting to understand the individual behavior of single neurons. Studying the activity of neuronal circuits is not only critical to the understanding of cognition, learning, memory and behavior, but also has implications for how neural diseases and disorders affect the carefully patterned networks of the brain.
(see full publication)