Neural population geometry and dynamics underlying multi-step cognitive-motor sequencing - Activities of daily living require a distributed group of brain areas to perform a series of computations that determine and drive action sequences. Compromising even one of these areas (e.g., due to injury or disease) can cause severe behavioral deficits. Thus, many disorders (e.g., Parkinson’s disease) often result in some degradation in planning and/or execution of sequences. Studying the neural mechanism of sequence generation has been challenging due to the distributed nature of the neural operations that drive them. Prior work on primary motor and dorsal premotor cortex (PMd/M1) has established that these areas are critical for sequencing. Yet during motor preparation, PMd/M1 activity reflects only the first movement within a sequence. Information regarding each subsequent movement arrives ‘just in time’ as the previous movement ends. Thus, PMd/M1 must rely on upstream areas to determine which actions should be performed in what order. To assess what these upstream areas are, and through what mechanism they facilitate determination and generation of sequences, I developed a new cognitive-motor behavioral paradigm for Rhesus macaques. My platform requires subjects to deploy previously learned abstract rules to determine a multi-step sequence on never-before-seen trials, while I perform large-scale electrophysiology from a circuit that spans prefrontal cortex, supplementary motor area, premotor cortex, and the basal ganglia. Analysis of these measurements using neural network modeling and population analyses, will help me elucidate the neural mechanisms that 1) allow the brain to determine new movement sequences by deploying prior knowledge, and 2) drive flexible modification of multi- step motor plans. These findings coupled with my flexible behavior and large-scale electrophysiology platform will launch my independent career, where my initial work will focus on 1) discovering the causal link between neural population activity and movement sequencing, and 2) establishing electrophysiological mechanisms of action for commonly prescribed psychoactive drugs. This project will facilitate my training as an independent scientist through new experience with ultra-large- scale muti-region electrophysiology and training in state-of-the-art statistical and neural network modeling methods. This project will involve collaborations between experimental neurophysiologists (Dr. Mark Churchland), theoretical neuroscientists (Dr. Ashok Litwin-Kumar), and physician-scientists (Dr. Mike Shadlen) at Columbia University. This award will help me achieve my long-term career goal to lead an independent neuroscience laboratory that 1) elucidates causal neural mechanisms underlying deductive reasoning and motor control, and 2) uses those insights to test and develop targeted neuromodulation therapeutics for cognitive-motor disorders. The aims of this proposal will also contribute to a core goal of NINDS: acquiring fundamental knowledge about movement control as well as elucidating currently unknown mechanisms of action of prescription drugs used by hundreds of millions of people for cognitive-motor disorders.
