# Synaptic and circuit mechanisms of learned motor sequences > **NIH NIH R01** · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · 2024 · $638,617 ## Abstract Project Summary/Abstract This project aims to investigate the neural mechanisms that lead to complex behavioral sequences, such as hitting a tennis forehand or playing the piano. To accomplish these behaviors, the brain must stitch together each component movement into a coherent act. Both local and long-range synaptic inputs can play a major role in generating the underlying premotor commands that drive these actions, but their respective influences can often be difficult to distinguish. We investigate this issue by examining the neural circuit dynamics underlying the courtship song of the zebra finch. Birdsong is a complex behavior that consists of precisely executed vocal elements mediated by a dedicated set of anatomically distinct brain regions. We recently found that thalamic drive engages a specific subpopulation of premotor neurons within the zebra finch song nucleus HVC (proper name) and that these inputs are critical for the progression between song elements. Here we investigate how such long-range inputs interact with local circuit properties to advance our understanding of the neural processes governing skilled movements across species. In Aim 1, we will test the relative impact of local and long-range excitatory input on singing. To accomplish this, we will measure the behavioral consequences of optogenetic silencing of two primary afferent streams to HVC. We will then use in vivo voltage clamp recordings and glutamate imaging to test the related hypotheses that long-range inputs have specific temporal and spatial patterns at the level of individual postsynaptic neurons. Finally, we will test the hypothesis that intrinsic excitability may affect network function by relating cellular properties of individual neurons to their role in singing behavior. In Aim 2, we will examine the contribution of local circuit inhibitory interneurons to HVC network dynamics. We first identify functionally defined categories of interneurons with distinct behavioral roles. We will then determine whether each inhibitory subpopulation exhibits distinct connectivity patterns within the network, and we will use a novel hybrid intra-/extracellular approach to examine their influence onto premotor neurons. Finally, we will leverage a newly developed family of viral tools to test the hypothesis that these functionally defined interneuron groups are mediated by molecularly distinct cell classes. Taken together, our proposal will examine how local and long-range inputs direct cortical dynamics in the context of an ethologically relevant behavioral sequence. Our findings will have clear implications for the understanding of mammalian behaviors in health and disease. ## Key facts - **NIH application ID:** 10981171 - **Project number:** 2R01NS075044-10A1 - **Recipient organization:** NEW YORK UNIVERSITY SCHOOL OF MEDICINE - **Principal Investigator:** MICHAEL A LONG - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $638,617 - **Award type:** 2 - **Project period:** 2011-09-30 → 2029-05-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10981171 ## Citation > US National Institutes of Health, RePORTER application 10981171, Synaptic and circuit mechanisms of learned motor sequences (2R01NS075044-10A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10981171. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*