Date of Award

12-2014

Embargo Period

3-9-2020

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Biological Sciences

Advisor(s)

Alison Barth

Abstract

Despite living in noisy sensory environments, humans and non-human primates have the ability to learn regularities and patterns in the environment solely on the basis of passive exposure. This ability to learn what is statistically likely and predictable in the environment is called statistical learning. Visual statistical learning of image sequences has been demonstrated at the level of single neurons in the rhesus macaque (monkey) inferotemporal cortex (IT). Upon subjecting monkeys to extensive exposure to pairs of images presented sequentially such that the display of one image always predicted the subsequent display of another image, IT neurons showed suppressed responses to images that occurred in a predicted context, but not when the same effect, called prediction suppression, more thoroughly, we discovered that this effect depends on the conditional probability between the images presented sequentially. Further, the effect generalizes across time and space, it is domain specific, and it can be induced by training monkeys on longer sequences. These effects are long-lasting and robust: they persist at least for 20 months after initial training with no exposure to the stimuli in the interim. We have preliminary evidence for the existence of neurophysiological markers of statistical learning in areas upstream of IT in the ventral visual stream, suggesting that learning statistical regularities may be a fundamental function of sensory cortex. images occurred in an unpredicted context (Meyer & Olson, 2011). Upon investigating this effect, called prediction suppression, more thoroughly, we discovered that this effect depends on the conditional probability between the images presented sequentially. Further, the effect generalizes across time and space, it is domain specific, and it can be induced by training monkeys on longer sequences. These effects are long-lasting and robust: they persist at least for 20 months after initial training with no exposure to the stimuli in the interim. We have preliminary evidence for the existence of neurophysiological markers of statistical learning in areas upstream of IT in the ventral visual stream, suggesting that learning statistical regularities may be a fundamental function of sensory cortex.

Available for download on Monday, March 09, 2020

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