Date of Graduation

5-2018

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Physics (PhD)

Degree Level

Graduate

Department

Physics

Advisor

Woodrow Shew

Committee Member

Paul Thibado

Second Committee Member

Nathan Parks

Keywords

Behavioral Neuroscience, Excitation, Inhibition, Motor Coding, Population Coupling

Abstract

The complexities of an organism’s experience of- and interaction with the world are emergent phenomena produced by large populations of neurons within the cerebral cortex and other brain regions. The network dynamics of these populations have been shown to be sometimes synchronous, with many neurons firing together, and sometimes asynchronous, with neurons firing more independently, leading to a decades-old debate within the neuroscience community. This discrepancy comes from viewing the system at two different scales; at the single cell level, the spiking activity of two neurons within cortex tend to be rather independent, but when the average activity of a global population is measured (e.g. during EEG, LFP measurements), large scale oscillations are typically observed. Both modes confer certain benefits and drawbacks in regard to information processing. Synchronous networks display more robust signal propagation at the expense of lower information capacity and higher signal-to-noise while more asynchronous networks exhibit higher information capacity but lack strong signal throughput. Do either of these scenarios prevail within motor cortex or do the two regimes work simultaneously to produce behavior? Here we measure neuron-to-population and neuron-to-body coupling of neurons within primary motor cortex of awake, freely behaving rats. We found that neurons with high and low population coupling coexist within cortex and population coupling was tunable via modulation of inhibitory signaling. Thus, our results show that both high and low synchrony neurons coexist. We also found that neurons with high and low population coupling serve different functional roles; neurons with low values of population coupling were more strongly coupled to the activity of the body, while neurons which were more engaged with the population tended to be less responsible in commanding body movement. These findings suggest a possible optimization strategy- the neurons that are most responsible for body movements are balanced between synchronous and asynchronous network activity, making a compromise between the various benefits and disadvantages of either extreme synchrony or extreme asynchrony.

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