The goal of this dissertation is to advance our understanding of perceptual decisions. A perceptual decision is a decision that is based on sensory evidence. For example, a monkey must choose whether to eat a food item based on sensory information such as its color, texture or odor. Previous research has identified regions of the brain involved in the encoding of sensory information as well as areas involved in transforming encoded representations of stimuli into signals useful for forming decisions about those stimuli. Researchers carried out much of this work by painstakingly observing the firing of single neurons or small groups of neurons while a subject performs a task, and used this information to propose and evaluate models of the decision process. However, previous studies have also shown that sensory stimuli are encoded in a distributed fashion across populations of neurons rather than in individual or small groups of neurons. Thus it is likely that populations of neurons, rather than individual neurons, are responsible for the formation of a decision. Here I directly address the question of how decisions are formed through the collective activity of populations of cortical neurons. I used voltage-sensitive dye imaging, a technique that allowed me to simultaneously monitor millions of neurons in sensory cortex, while primates performed a simple yet challenging binary decision task. I also used psychophysical techniques and computational modeling to address fundamental questions about the nature of perceptual decisions. Here I provide new evidence that choice-related neural activity is distributed across a broad population of neurons, and that most of the decision-related neural activity occurs as early as primary sensory cortex. I propose a physiological and computational mechanism for the subject’s decision process in our task, and demonstrate that this process is likely sub-optimal due to intrinsic uncertainty about sensory stimuli. Overall, I conclude that in our task, perceptual decisions are likely to be limited primarily by the quality of evidence that resides in populations of neurons in sensory cortex, secondarily by sub-optimal decoding of these sensory signals, and to a much lesser extent by additional downstream neural variability. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-12-6861 |
| Date | 31 January 2013 |
| Creators | Michelson, Charles Andrew |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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