Neural reactivations during sleep and memory consolidation
Distributed control of skill (recovery after injury)
Closed-loop neuromodulation
Consolidated neuroprosthetic control
"The motor network consists of interconnected cortical and subcortical areas. Large scale recordings suggest frameworks for processing such as oscillatory dynamics and cross-area filtering. We aim to delineate the network dynamics of learning and to develop physiologically-inspired neurotechnology to enhance recovery and function. Goal 1. Understand how distributed network activity permits learning and skill consolidation. We are interested in how animals learn new complex and flexible skills. We specifically consider neural processing across awake and sleep in cortex and the basal ganglia. For example, how are awake experiences (task activity) processed during sleep to allow consolidation of a nascent skill (e.g. Gulati et al., Nature Neuro, 2017; Kim et al., Cell 2019)? How does this change with injury (e.g. Kim et al., Cell Reports, 2022)? Goal 2. Neural interfaces to restore neural circuit dynamics. We use principles of network plasticity to integrate bidirectional neural interfaces ("read and write"') into injured brains. We thus aim to restore neural processing and improve function (e.g., Ramanathan et al, Nature Medicine 2018; Khanna et al., Cell, 2021). Goal 3. Translate to patients. In addition to discovering fundamental principles, we are translating our research into clinical neurotechnology (Silversmith et al., Nature Biotechnology, 2021). We co-lead a pilot trial of Brain-Computer Interfaces (BCI) in human subjects with severe motor disability [BRAVO Trial, ClinicalTrials@UCSF]. “
Kim J et al., Impaired sleep-dependent consolidation after stroke – interaction of slow waves, rehabilitation and GABA Cell Reports
Kondapavulur S, Lemke S, Darevsky D, Guo L, Khanna P, Ganguly K. Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration. Nature Communications.