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Behavioral State Modulates Primary Visual Cortex Responsiveness in Mice


The brain is constantly bombarded with sensory stimuli. In order to process and perceive such diverse information streams simultaneously, the brain prioritizes information relevant to an animal’s current behavioral needs. In this thesis, I investigate the neural mechanisms that enable the brain to increase or decrease visual signals depending on an animal’s behavioral state. In chapter 1, I illustrate a novel mechanism, 3-5 Hz membrane potential (Vm) oscillations, that decreases the responsiveness of neurons in the primary visual cortex (V1) of mice. Using 2-photon guided whole-cell recordings as mice passive viewed and actively engaged drifting sine-wave gratings, I discovered that these visually-evoked phenomena were not influenced by changes in arousal or animal movement, but their timing was influenced by an animal’s behavioral state. In addition to uncovering a novel mechanism for reducing the responsiveness of neurons in the brain, this chapter substantially furthers the field’s knowledge of how behavior and arousal affect the membrane potential of neurons in the cerebral cortex. In chapter 2, I develop a method to train animals how to perform a visual attention task. I describe the hardware and software tools used to actuate the task and the method used to train the animals. Using the method outlined in this chapter, I was able to routinely train animals to perform a multimodal attention task with approximately one month of training. In chapter 3, I employed this new attention model and, using 2-photon guided whole-cell recordings in behaving animals, I discovered that attention boosts the depolarization associated with visual stimulation in layer 2/3 V1 neurons, illustrating a potential mechanism that causes neurons to be more responsive to visual cues during attention. Finally, using 128 channel silicon nanoprobes chronically implanted in V1, I verified that the attention task increased the responsiveness of V1 neurons and desynchronized the local network in mice, replicating results previously obtained in non-human primate models and setting the groundwork for future study. As a result, my thesis details novel neural mechanisms for enhancing or dampening visual signals and expands our knowledge of how the brain prioritizes information according to an animal’s behavioral context.

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