Communication among sensorimotor cortices: Where state space meets biology

  • Awardees
  • Matthew Kaufman, Ph.D. University of Chicago

Movement is the primary way animals interact with the world. To produce the incredibly adaptable and complex behavior of mammals, many areas of the brain must work together to generate control signals and incorporate feedback. Yet because feedback is extensive throughout these circuits, it’s a challenge to understand the differential roles of heavily connected areas, and to tease apart what information is inherited from inputs, what is computed locally, and what is fed back from downstream areas. To tackle the question of information flow and inter-area communication, we will link three complementary approaches in the mouse: advanced behavior, state-space methods and projection tracing.

At least three cortical structures are believed to be important for voluntary forelimb movements in the mouse: the primary motor cortex, secondary motor cortex and somatosensory cortex. Activity in these three areas shares a number of properties. From work in the monkey using sophisticated state-space analysis techniques, it is known that some patterns of activity are shared among motor areas or between sensory and motor areas, while other patterns are unique to one or another area. But it has not been possible to determine the direction of information flow, identify where any of these patterns originate, or even determine whether the strongly expressed shared activity patterns correspond to the signals sent most strongly from one area to the next.

To bridge the gap between our understanding of effective inter-area communication and its biological underpinnings, we will use two-photon calcium imaging to record activity simultaneously from these cortical areas while a mouse performs a complex reaching task requiring sensory feedback. In addition, the neurons that project from one area will be labeled using retrograde viral tracing. This combination will allow us not only to identify the shared patterns of activity among these neural populations, but also to directly determine what signals are sent from one area to the next. This additional information will allow us to distinguish inherited signals from those produced locally and to determine what signals each area prioritizes sending to the others and how feedback alters ongoing activity. For the two motor areas, these experiments will disambiguate the roles of each area in generating control signals and transforming from abstract motor goals to detailed instructions to muscles. For the sensory and motor areas, they will reveal how sensory feedback affects motor command generation, and how motor commands are processed in sensory areas to modulate sensation. Together, these findings will help us move beyond treating brain areas as isolated units, and toward an understanding of the broader network.

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