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Neural processes for learning and mo...

Noyce, Abigail LaBombard.

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Neural processes for learning and monitoring sequential regularities in changeable environments.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural processes for learning and monitoring sequential regularities in changeable environments./
Author:	Noyce, Abigail LaBombard.
Description:	108 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Contained By:	Dissertation Abstracts International75-06B(E).
Subject:	Cognitive psychology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3611649
ISBN:	9781303725449

Neural processes for learning and monitoring sequential regularities in changeable environments.
Noyce, Abigail LaBombard.

Neural processes for learning and monitoring sequential regularities in changeable environments. - 108 p.

Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.

Thesis (Ph.D.)--Brandeis University, 2014.

This item is not available from ProQuest Dissertations & Theses.

The world is largely stable and predictable. Humans and other organisms are sensi- tive to that stability, and use it to support cognitive processes. This work consists of a series of studies that explore how humans learn about such stability, use that infor- mation to generate predictions about forthcoming sensory input, and detect when such predictions are inadequate. First, I present a modeling study that quantified the distributions of errors that people make on a complex, visuomotor sequence learning task, and examine the serial position dynamics of several parameters describing short-term visual memory. Both precision and capacity for these sequences increases with familiarity, and the worst-represented items show the largest increases. Next, I present an experiment that used the same task to understand the effects of deviant items within familiar sequences. By measuring ERPs to new, familiar, and deviant items, I dissociate the neural activity associated with detecting a deviant from that associated with encoding task-relevant stimulus characteristics. Finally, I present an experiment investigating the role of prediction in a task that is stochastic, rather than sequential, and in which deviant events occurred among the distractors rather than among the task-relevant stimuli. Unexpected events among the distractors seem to obligatorily attract attention, enhancing or impairing performance. Further, I show that the individual differences in the neural response to such unexpected events is predicted by temperament. Together, these studies illuminate how the brain learns about predictability in a range of settings, and leverages such predictability to facilitate cognition.

ISBN: 9781303725449Subjects--Topical Terms:

523881
Cognitive psychology.

Neural processes for learning and monitoring sequential regularities in changeable environments.
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100 1 $a Noyce, Abigail LaBombard. $3 3191707
245 1 0 $a Neural processes for learning and monitoring sequential regularities in changeable environments.
300 $a 108 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
500 $a Adviser: Robert Sekuler.
502 $a Thesis (Ph.D.)--Brandeis University, 2014.
506 $a This item is not available from ProQuest Dissertations & Theses.
520 $a The world is largely stable and predictable. Humans and other organisms are sensi- tive to that stability, and use it to support cognitive processes. This work consists of a series of studies that explore how humans learn about such stability, use that infor- mation to generate predictions about forthcoming sensory input, and detect when such predictions are inadequate. First, I present a modeling study that quantified the distributions of errors that people make on a complex, visuomotor sequence learning task, and examine the serial position dynamics of several parameters describing short-term visual memory. Both precision and capacity for these sequences increases with familiarity, and the worst-represented items show the largest increases. Next, I present an experiment that used the same task to understand the effects of deviant items within familiar sequences. By measuring ERPs to new, familiar, and deviant items, I dissociate the neural activity associated with detecting a deviant from that associated with encoding task-relevant stimulus characteristics. Finally, I present an experiment investigating the role of prediction in a task that is stochastic, rather than sequential, and in which deviant events occurred among the distractors rather than among the task-relevant stimuli. Unexpected events among the distractors seem to obligatorily attract attention, enhancing or impairing performance. Further, I show that the individual differences in the neural response to such unexpected events is predicted by temperament. Together, these studies illuminate how the brain learns about predictability in a range of settings, and leverages such predictability to facilitate cognition.
590 $a School code: 0021.
650 4 $a Cognitive psychology. $3 523881
650 4 $a Neurosciences. $3 588700
650 4 $a Psychobiology. $3 555678
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710 2 $a Brandeis University. $b Psychology. $3 1033658
773 0 $t Dissertation Abstracts International $g 75-06B(E).
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791 $a Ph.D.
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3611649