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Cortical-to-Subcortical Information Transfer Underlying Skill Learning

Periodic Reporting for period 1 - CSIT (Cortical-to-Subcortical Information Transfer Underlying Skill Learning)

Período documentado: 2021-01-01 hasta 2021-12-31

The project entitled "Cortical-subcortical information transfer underlying skill learning" (CSIT) was aimed at understanding the brain's stability-plasticity dilemma. The stability-plasticity dilemma is a critical constraint in brain networks underlying learning and memory. The dilemma is how the brain can acquire new information (plasticity) without overriding older knowledge (stability). In this project, we studied this dilemma by examining how brain activity changes as a new behavior is learned: are there specific brain areas involved only in learning, while brain areas store learned behaviors? Or do networks of brain areas interact to mediate both processes? We specifically studied two brain areas associated with learning and storage of behaviors, the motor cortex and the subcortical basal ganglia. Neural signals were recorded across both regions in the rat brain as rats learned a specific motor task that allowed for the precise behavioral quantification of learning. We then measured the behaviorally relevant information carried by neural signals in each brain area, as well as the information flow between areas. We found that while both motor cortex and the basal ganglia contained behaviorally relevant information during the initial learning of the task and the production of the stored, learned behavior, the flow of information changed dramatically. During learning, information flow was "top-down", originating from motor cortex and flowing subcortically, however, when the stored behavior was performed after learning, information flow was "bottom-up", originating from the basal ganglia and flowing to cortex. This revealed to us that there are not separate regions in the brain that underlie the learning and storage of a behavior. Rather, distributed networks of cortical and subcortical brain regions mediate both processes, with changes in the dynamics of communication within the networks allowing them to switch functions. To achieve the results of this project, we developed a new computational tool that allowed us to isolate the dynamics of behaviorally relevant information flow in the brain. Our tool will help advance our understanding of brain function, both within the context of the brain's stability-plasticity dilemma, as well as other complex functions of the brain. The results of this project shed light on how distributed networks in the brain, spanning both cortical and subcortical areas, work together to generate behavior. This understanding is fundamental for understanding of how brain areas communicate, as well as our understanding of how brain injuries impact both the ability to learn new behaviors and perform stored behaviors.
Throughout the CSIT project we (1) developed a new information-theoretic tool and disseminated this tool, along with implementations of several other established information-theoretic tools, in an open-source toolbox to the scientific community and (2) achieved new results studying the interaction of cortical and subcortical brain areas that have led to two articles that we have prepared for submission to open-source peer-reviewed journals. At the start of the CSIT project, we sought to answer several questions regarding how different brain areas communicate to generate behavior, and how this communication may evolve as a new behavior is learned. To answer these questions, we developed a new method called Feature-specific Information Transfer (FIT) that allowed us to track information flow about specific features of the learned behavior, allowing us to uncover dynamics in the brain that could not be observed using traditional methods. Once developed, we utilized FIT to study the information flow between two areas of the rat brain, the motor cortex and the basal ganglia, which are closely associated with learning new motor tasks. We observed a dramatic change in how these brain regions communicated from naive performance of the motor task to skilled performance after several weeks of daily training. This change shed light on the function of these brain areas, and the role of cross-area communication in regulating complex functions. To disseminate the results of the CSIT project, we have prepared two articles for submission to open-source academic journals and released a toolbox to allow the broader scientific community to utilize the information-theoretic methods we have developed.
The CSIT project has advanced the suite of information-theoretic tools available for studying brain function. We developed a new tool that characterizes the details of how brain areas communicate, beyond what can be understood from traditional methods. We utilize this tool within the CSIT project to understand the neural correlates of learning and provide evidence of how the brain may solve the stability-plasticity dilemma. We demonstrate that the communication between distributed networks of brain areas, rather than local changes in specific brain areas, underlies complex functions such as learning a new behavior. This understanding can help us understand the disparate impacts of brain injuries and may inform novel specific neurorehabilitation approaches to improve brain function after injury.
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