ERP Markers of Implicit Sequence Learning

URI / Handle

Few studies investigate the within-trial temporal dynamics of neural processes related to implicit probabilistic sequence learning (IPSL). Those that do often use the electroencephalogram to measure and analyze event-related potentials (ERPs) linked to implicit learning. Presently, there is much debate about which ERP components capture processes related to IPSL. This is largely due to a lack of consensus concerning how to define ERPs using traditional methods. To address these concerns, the present dissertation examined the within-trial temporal dynamics of implicit learning using both a traditional and a new data-driven analysis (i.e. nonparametric cluster-based permutation tests) to analyze ERPs related to IPSL in a Triplets Learning Task (TLT). Results from the traditional analysis determined that cue-based expectancies learned via implicit associations during the TLT are distinguishable by differences in N400 amplitude. This finding was confirmed by the cluster-based analysis, which returned a significant late-occurring cluster that overlapped in time and space with the N400. This Late Cluster occurred after the average response-time and appeared to capture processes reflecting conflict resolution related to target predictability. The cluster-based analysis also returned an early-occurring cluster that was sensitive to target predictability but was not captured by the traditional analysis. This Early Cluster occurred before the onset of the average response-time and likely reflects response inhibition. Both Clusters demonstrated significant effects early in learning that diminish with practice on the TLT. This finding suggests that although early on participants react to unexpected events, with practice, participants learn to expect unlikely target events to occur occasionally. Taken together, the findings from the present dissertation demonstrate the temporal dynamics of within-trial processes during IPSL and implicate ERP markers of response inhibition and conflict resolution during the TLT. Additionally, these findings highlight discrepancies between the cluster-based and the traditional analysis, calling attention to the need to incorporate data-driven methods when investigating ERPs.
Details
Title

ERP Markers of Implicit Sequence Learning

Contributors

Howard, Jr., James H. (Advisor); Kiser, Seth Adam (Author); Fuller, Rebecca L. (Other); Howard, Darlene H. (Other); Adleman, Nancy (Other)

Degree Information

Degree awarded: Ph.D. Psychology. The Catholic University of America

Extent

80 p.

URI / Handle

http://hdl.handle.net/1961/cuislandora:28260

Advisor

Howard, Jr., James H.

URI / Handle

http://hdl.handle.net/1961/cuislandora:28260

Other

Fuller, Rebecca L.; Howard, Darlene H.; Adleman, Nancy

Subject

Psychology; Cognitive psychology; Physiological psychology; ERP; Implicit Learning; Nonparametric

Created

2015-01-01T00:00:00Z

Abstract

Few studies investigate the within-trial temporal dynamics of neural processes related to implicit probabilistic sequence learning (IPSL). Those that do often use the electroencephalogram to measure and analyze event-related potentials (ERPs) linked to implicit learning. Presently, there is much debate about which ERP components capture processes related to IPSL. This is largely due to a lack of consensus concerning how to define ERPs using traditional methods. To address these concerns, the present dissertation examined the within-trial temporal dynamics of implicit learning using both a traditional and a new data-driven analysis (i.e. nonparametric cluster-based permutation tests) to analyze ERPs related to IPSL in a Triplets Learning Task (TLT). Results from the traditional analysis determined that cue-based expectancies learned via implicit associations during the TLT are distinguishable by differences in N400 amplitude. This finding was confirmed by the cluster-based analysis, which returned a significant late-occurring cluster that overlapped in time and space with the N400. This Late Cluster occurred after the average response-time and appeared to capture processes reflecting conflict resolution related to target predictability. The cluster-based analysis also returned an early-occurring cluster that was sensitive to target predictability but was not captured by the traditional analysis. This Early Cluster occurred before the onset of the average response-time and likely reflects response inhibition. Both Clusters demonstrated significant effects early in learning that diminish with practice on the TLT. This finding suggests that although early on participants react to unexpected events, with practice, participants learn to expect unlikely target events to occur occasionally. Taken together, the findings from the present dissertation demonstrate the temporal dynamics of within-trial processes during IPSL and implicate ERP markers of response inhibition and conflict resolution during the TLT. Additionally, these findings highlight discrepancies between the cluster-based and the traditional analysis, calling attention to the need to incorporate data-driven methods when investigating ERPs.

Type

Text; Dissertation

Local

Kiser_cua_0043A_10554

Publisher

The Catholic University of America

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