Date of Graduation


Document Type

Dissertation (PhD)

Program Affiliation


Degree Name

Doctor of Philosophy (PhD)

Advisor/Committee Chair

Valentin Dragoi

Committee Member

Harel Shouval

Committee Member

Syed Hashmi

Committee Member

Ruth Heidelberger

Committee Member

Daniel Felleman

Committee Member

Caleb Kemere


The brain is never truly silent – up to 80% of its energy budget is expended during ongoing activity in the absence of sensory input. Previous research has shown that sensory neurons are not exclusively influenced by external stimuli but rather reflect interactions between sensory inputs and the ongoing activity of the brain. Yet, whether fluctuations in the state of cortical networks influence sensory coding in neural circuits and the behavior of the animal are unknown. To shed light on this issue, we conducted multi-unit electrophysiology experiments in visual areas V1 and V4 of behaving monkeys. First, we studied the impact of neural population spiking before stimulus presentation on orientation discrimination in the primary visual cortex. We found that when neuronal populations are in a low firing state, they have a higher capacity to discriminate stimulus features despite an overall reduction in evoked responses. Importantly, behavioral performance was significantly improved in the low firing network state. Next, we conducted recordings in the visual cortical area V4 while animals participated in a natural image orientation discrimination task to determine whether fluctuations in local population synchrony during wakefulness play any role in modulating network and behavioral performance. We found that populations of cells exhibit rapid fluctuations in synchrony of ongoing activity ranging from desynchronized responses, indicative of high alertness, to more synchronized responses, indicative of drowsiness. These state fluctuations control the variability in the accuracy of population coding and behavioral performance across trials in a visual discrimination task. When the local population activity is desynchronized, the correlated variability between neurons is reduced, and network and behavioral performance are improved. Lastly, we controlled the state of cortical networks by manipulating the animal’s behavioral state from wakefulness to rest. Thus, we analyzed population recordings from area V4 while the animals participated in an orientation discrimination task, which was immediately followed by a brief resting period of 20-30 minutes, and lastly, by a second task period (Task – Rest – Task). We found that cortical networks were desynchronized after rest such that behavioral performance was improved relative to the pre-rest condition. Altogether, the findings in this thesis demonstrate that the variability in spontaneous cortical activity is not simply noise but rather contains a dynamic structure which controls how incoming sensory information is optimally integrated with ongoing processes to guide network coding and behavior.


Cortical state, Synchrony, Neural Synchrony, Neural Coding, Resting state, brain state, primate, visual cortex



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