# Untangling the influence of distinct sources of somatosensory feedback on the neural dynamics of dexterous movement control > **NIH NIH DP2** · UNIVERSITY OF CALIFORNIA BERKELEY · 2024 · $1,255,340 ## Abstract PROJECT SUMMARY To move successfully, we must be able to sense our bodies and our environment. This is no more evident than when participants attempt to strike a match to light a candle after their hand’s somatosensation has been numbed. Despite being able to see well, participants fumble with the match and clumsily attempt to accomplish the task. Further, somatosensory-motor integration is notably impaired in many types of neurological movement disorders including Parkinson’s disease, stroke, essential tremor, and dystonia. Developing rehabilitation or therapeutic strategies to improve somatosensory-motor integration faces a central challenge: while the theoretical importance of somatosensory-motor integration (SMI) is clear, how the brain actually processes afferent signals to enable excellent movement control remains unclear. In this proposal, we seek to use a population neural dynamics framework to understand how the brain implements SMI computations. Specifically, we will leverage a novel feedback-dependent dexterous manipulation task, high-density multi-area recordings, and an innovative type of electrical stimulation that can be used to modulate inter-area communication in the macaque monkey. These combined experiments and analysis are designed to uncover how SMI computations, long known to be critical for movement control, are implemented in population neural activity patterns in brain. Further, they will pave the way for developing approaches for restoring damaged SMI in the brain after brain injury or neurodegenerative disease. The main experimental approach of this proposal includes simultaneous high-density, high channel-count (Neuropixel) electrophysiological recordings from the primary motor cortex (M1), primary somatosensory cortex (S1), and cerebellar-receiving motor thalamus (mThal) in non-human primates that are learning and executing a dexterous manipulation task. The main analytical approach includes modeling the timeseries of motor cortical population activity as a combination of intrinsic motor cortical dynamics and inputs from S1 and mThal. The hypothesis of this proposal is that S1 and mThal exert different influences on M1 population dynamics throughout the learning and execution process. Specifically, we hypothesize that S1 provides specific sensory updates that drive M1 population activity, and mThal modulates the temporal dynamics of M1 population activity. We will further develop evidence for or against this hypothesis by leveraging a novel neuromodulation approach that can boost or interrupt communication between distant brain regions. Completion of this proposal will constitute an understanding of how SMI computations, that have long been thought to be essential for movement, are actually implemented in the circuitry and population dynamics of the macaque sensorimotor system. This advance would improve our understanding of how to target somatosensory nodes to improve control of movement following motor impairment... ## Key facts - **NIH application ID:** 10909709 - **Project number:** 1DP2NS142717-01 - **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY - **Principal Investigator:** Preeya Khanna - **Activity code:** DP2 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $1,255,340 - **Award type:** 1 - **Project period:** 2024-09-13 → 2027-08-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10909709 ## Citation > US National Institutes of Health, RePORTER application 10909709, Untangling the influence of distinct sources of somatosensory feedback on the neural dynamics of dexterous movement control (1DP2NS142717-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10909709. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*