How Do Different Brain Regions Communicate?
Post by Anastasia Sares
What’s the science?
Scientists have been mapping out the brain and its connections for over a century. Still, we are very far away from a complete understanding of how the brain functions. Understanding the brain on a deeper level will require us to understand how physically distant groups of neurons can interact. This week in Trends in Neurosciences, Kohn and colleagues reviewed four possible mechanisms for communication between brain regions.
What do we already know?
Though new discoveries are still being made, we have a decent understanding of the architecture of the brain. Chemical stains and even viruses can be used to trace neural circuits forwards and backward. However, making a simple circuit diagram won’t explain what is really going on, just like having a map of a building doesn’t tell you how the people inside are interacting. We must measure the working brain.
Scientists can use electrodes inserted into the brain to measure the firing activity of small groups of neurons, giving us a zoomed-in picture of brain activity. MRI, when combined with advanced statistical techniques, can reveal large patterns of activity that tend to occur on average—a zoomed-out picture. What we don’t understand as well is the middle-range: communication between different local brain regions is complex, and very flexible, changing from one moment to the next.
What’s new?
The authors highlighted four different theories that might help explain how different brain regions communicate:
1. Synchronized neurons in the source region— an organized firing of neurons from a source region is much more likely to get picked up by downstream neurons. The same amount of firing, if disorganized, will have less of an effect.
2. Coherence—neurons go through cycles of potential, being more or less likely to fire at different points in this cycle. If a signal arrives from a different area during a point of low firing potential, it probably won’t get picked up. But when two distant areas have coordinated cycles of low and high firing, communication between them will be strong. However, it takes some time to synchronize oscillations, which might not be fast enough to account for some of the brain’s more quick and flexible communication.
3. Communication subspace— this one has to do with the specific pattern of neurons that fire. Like a pin lock on your phone, it doesn’t matter if any of the individual numbers is right; all of them have to be right at the same time in order to get access. This behavior has been seen in the motor cortex, which is often active without actually causing movement. However, when the pattern of neurons in the motor cortex is just right, it sends a signal to a specific muscle to move.
4. Pulvinar-mediated communication— the pulvinar is a deep brain structure that receives input from many different regions of the cortex. It is possible that this structure is responsible for regulating communication strength between different areas of the brain. It could do this by way of one of the methods mentioned above (for example, changing synchrony or coherence between the regions), or by activating key messenger neurons in the source area.
After establishing a few of the ways that neural populations might communicate, it is important to account for one more factor. Signals from “lower” regions (basic perception) send strong signals up to the next level of the brain’s hierarchy: we can think of these as feedforward signals. Information from “higher” regions (attention, context, etc.) is also sent back down the hierarchy, but these feedback connections are more diffuse. Feedforward and feedback connections may behave in very different ways.
What's the bottom line?
Brains are wonderfully complex, and though we have made great strides in understanding how they work, there are still a lot of questions about how distant neurons communicate. Moving forward, we will need to determine which of the theories of brain communication above are the most realistic and consistent with experimental data, keeping in mind that they may not be mutually exclusive.
Kohn et al. Principles of Corticocortical Communication: Proposed Schemes and Design Considerations. Trends in Neurosciences (2020). Access the original scientific publication here.