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Medicine

Brain's hemispheres talk to each other through shared signals

Researchers discover how prefrontal cortex processing is connected across the brain.

Illustration: Blue Dot News

1 min read

In a fascinating study published in Nature communications, researchers shed light on how our brains process information. They discovered that brain functions involve two types of processing: local networks and modulation from other parts of the brain, such as arousal.

The researchers used a unique approach to understand these interactions. They recorded the activity of neurons in both hemispheres of the prefrontal cortex while monkeys performed a spatial memory task. By analyzing trial-to-trial variability in neuronal activity, they found that many neurons within each population shared patterns of activity with other populations. This suggests that there is more to our brains than meets the eye.

This discovery matters because it shows us how we can use recordings from different parts of the brain to better understand its functions. By uncovering these hidden aspects, we can gain a deeper understanding of how our brains work and potentially develop new ways to diagnose or treat cognitive disorders.

The people behind the work

  • McDonnell ME et al.

    Author

    Published in Nature communications

Source: Nature communications

Sources & Verification

Every statement in this story is drawn from the facts below. Each is linked to a primary or reputable source — follow any citation to check it for yourself.

  1. Brain functions involve processing in local networks as well as modulation from brainwide signals, such as arousal. Nature communications
  2. Dissecting the contributions of populations of neurons to these functions requires knowledge of interactions between brain areas. Nature communications
  3. We investigated these interactions using dual hemisphere recordings of prefrontal cortex in monkeys performing a spatial memory task. Nature communications
  4. To tease apart global processing from local interactions, we applied a novel statistical approach called pCCA-FA (a combination of probabilistic canonical correlation analysis and factor analysis) to analyze trial-to-trial variability in neuronal activity. Nature communications
  5. We found substantial shared variability among neurons within each population, much of which was actually shared across populations and linked to an arousal process. Nature communications
  6. Our work presents a path by which we can leverage multi-area recordings to reveal aspects of brain functions that are hidden in single-area recordings. Nature communications

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