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Network Mechanisms Underlying Stable Motor Actions

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William Liberti, Ph.D.
Department of Electrical Engineering & Computer Science
University of California, Berkeley

Abstract
Precise motor skills are acquired and maintained through practice; a process of exploratory trial-and-error learning where evaluation mechanisms can differentially reinforce network patterns that produce more desired outcomes and weaken or punish patterns of activity that produce worse outcomes. However, the neural underpinnings of how practice may evaluate, maintain and sharpen the stereotypy of a precise motor action are not well understood. The zebra finch songbird offers a chance to explore the mechanisms of motor maintenance in a  particularly well defined setting: song is a constrained behavior that naturally converges around a set point, and is actively maintained and stabilized in light of external feedback and environmental challenges. While song is primarily a courtship ritual to attract females, finches will also sing in isolation, otherwise known as ‘undirected’ song,  and these songs have comparatively lower stereotypy.  Undirected song could serve as an opportunity for premotor networks to explore potentially better configurations to optimize motor output, since the performance outcome is less critical. We developed custom carbon fiber microelectrodes, cell-type specific genetic tools, and ultra-light head-mounted miniscopes to investigate the mechanistic basis of long-term motor stability of the premotor area HVC. We find that during undirected practice, some neurons are active more probabilistically, and less robustly, and trial to trial variability is not highly correlated across cells. In contrast, when song is directed to a female, this exploration is largely diminished.  In addition, while the timing of projection neurons is extremely stereotyped and precise within a day, neurons can ‘dropout’ and new neurons can ‘drop-in’  across days-  largely over intervals of sleep. In spite of these shifts at the single neuron level, local ensembles and inhibitory interneurons produce reliable patterns of activity over month-long timescales. These observations suggest that state-dependent variations could contribute to the long-term stability of the motor network, and that stereotyped motor skills can be supported by stable ensemble dynamics that persist in spite of single neuron instability.

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Status

  • Workflow Status:Published
  • Created By:Jasmine Martin
  • Created:03/19/2018
  • Modified By:Jasmine Martin
  • Modified:03/19/2018