Surround Integration During Active Sensation in the Mouse Barrel Cortex

• Main Author: Lyall, Evan Harrison
• Language: EN
• Published: University of California, Berkeley 2019
• Subjects: Neurosciences|Physiology
• Online Access: http://pqdtopen.proquest.com/#viewpdf?dispub=13422798

<p>Organisms scan their sensors around their environment to build an internal representation of that environment in a process known as active sensation. The integration of information across time and space is critical to providing context as to what is the organism is perceiving. However, the neural circuits that encode and underlie the integration of incoming sensory information have predominantly been studied in the context of passive sensation. Studying these circuits in the context of active sensation is imperative to generating a better understanding of how the brain naturally encodes sensation. This would have profound impacts on understanding the mechanisms of a number of neural disorders, including autism and attention-deficit/hyperactivity disorder, as well as how to improve the acuity of artificial sensation implanted into disabled individuals. To better understand how the mammalian brain encodes and integrates information during active sensation, my collaborators and I developed several novel paradigms to study surround integration in the mouse barrel cortex during active whisking. In Chapter 1 I establish why this is an important problem, and briefly summarize what is already known about sensory coding in the mouse whisker system. In Chapter 2 my collaborators and I probe how mice represent the location of an object within its whisking field, and how the integration of information across surround whiskers affects this representation. In doing so we discover a novel thalamocortical transformation where surround integration in the cortex suppresses activity in layer 4 of the cortex, ultimately generating a smooth map of scanned space in cortical layer 2/3. In Chapter 3 I utilize a novel tactile display to better understand the logic of multi-whisker integration in two cortical layers. In this unpublished work, I show that contrary to the previous literature in anesthetized mice, cortical neurons in awake, whisking mice powerfully summate specific whisker combinations supralinearly, generating a sparse code representing the entire combinatoric space of whisker touch. In Chapter 4, I conclude with some closing thoughts and propose some future lines of inquiry to further this research.