School of Electrical, Computer and Energy Engineering
PhD Final Oral Defense
Exploring the Neural Code in Rat’s Agranular Medial and Agranular Lateral Cortices
during Learning of a Directional Choice Task
by
Hongwei Mao
April 10, 2014
2:00 PM
GWC 353
Committee:
Dr. Jennie Si (chair)
Dr. Marco Santello
Dr. Christopher Buneo
Dr. Yu Cao
Abstract
Animals learn to choose a proper action among alternatives according to the
circumstance. Through trial-and-error, animals improve their odds by making correct
association between their behavioral choices and external stimuli. While there has been
an extensive literature and several schools of thoughts on the theory of learning, it is still
unclear how individual neurons and a neural network adapt as learning progresses.
In this dissertation, the activity of single units in the medial and lateral agranular
(AGm and AGl, respectively) areas of rats was monitored as rats learned a directional
choice task. The task required the rat to make a left/right side lever press if a light cue
appeared on the left/right side of the interface panel.
Behavior analysis showed that the rat’s movement parameters during the
performance of directional choice became stereotyped very quickly (2-3 days) while
learning to solve the directional choice problem took weeks to occur. The entire learning
process was further broken down to 3 stages, each having similar number of recording
sessions (days). Single unit based mean firing rate analysis revealed that 1) neural
modulation by direction of choice was observed in both cortical areas; 2) the neuron
averaged mean rate each day did not change significantly among the three learning
stages; 3) the difference in mean rates between left and right trials did not change
significantly. Besides, for either the left side trials or the right side trials, the trial-to-trial
variability in neural firing rates each day did not show any trend with learning among the
three learning stages. As a means to explore the spatiotemporal pattern of recorded neural
ensemble, support vector machines (SVMs) were constructed each day to decode the
direction of choice in single trials. Improved classification accuracy indicated enhanced
discriminability between neural patterns of left and right choices as learning progressed.
When using a restricted Boltzmann machine (RBM) model to extract features in neural
activity patterns, results further supported the idea that neural firing patterns adapted over
days during the three learning stages to facilitate direction readout.
Put together, the results suggest a spatiotemporal neural coding scheme in a rat
AGl and AGm neural ensemble that may be responsible for and contributing to learning
the directional choice task.