Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12169
Title: Intact action segmentation in Parkinson's disease: Hypothesis testing using a novel computational approach
Authors: Schiffer, A-M
Nevado-Holgado, AJ
Johnen, A
Schoenberger, AR
Fink, GR
Schubotz, RI
Keywords: Parkinson's diseas;Predictive perception;Computational classifier;Action segmentation;Episodic memory;Action represntation;Temporal prediction
Issue Date: 2015
Publisher: Elsevier
Citation: Neuropsychologia, 78, pp. 29 - 40, (2015)
Abstract: Action observation is known to trigger predictions of the ongoing course of action and thus considered a hallmark example for predictive perception. A related task, which explicitly taps into the ability to predict actions based on their internal representations, is action segmentation; the task requires participants to demarcate where one action step is completed and another one begins. It thus benefits from a temporally precise prediction of the current action. Formation and exploitation of these temporal predictions of external events is now closely associated with a network including the basal ganglia and prefrontal cortex. Because decline of dopaminergic innervation leads to impaired function of the basal ganglia and prefrontal cortex in Parkinson's disease (PD), we hypothesised that PD patients would show increased temporal variability in the action segmentation task, especially under medication withdrawal (hypothesis 1). Another crucial aspect of action segmentation is its reliance on a semantic representation of actions. There is no evidence to suggest that action representations are substantially altered, or cannot be accessed, in non-demented PD patients. We therefore expected action segmentation judgments to follow the same overall patterns in PD patients and healthy controls (hypothesis 2), resulting in comparable segmentation profiles. Both hypotheses were tested with a novel classification approach. We present evidence for both hypotheses in the present study: classifier performance was slightly decreased when it was tested for its ability to predict the identity of movies segmented by PD patients, and a measure of normativity of response behaviour was decreased when patients segmented movies under medication-withdrawal without access to an episodic memory of the sequence. This pattern of results is consistent with hypothesis 1. However, the classifier analysis also revealed that responses given by patients and controls create very similar action-specific patterns, thus delivering evidence in favour hypothesis 2. In terms of methodology, the use of classifiers in the present study allowed us to establish similarity of behaviour across groups (hypothesis 2). The approach opens up a new avenue that standard statistical methods often fail to provide and is discussed in terms of its merits to measure hypothesised similarities across study populations.
URI: http://www.sciencedirect.com/science/article/pii/S0028393215301779
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000365053800004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=f12c8c83318cf2733e615e54d9ed7ad5
http://bura.brunel.ac.uk/handle/2438/12169
DOI: http://dx.doi.org/10.1016/j.neuropsychologia.2015.09.034
ISSN: 0028-3932
Appears in Collections:Dept of Life Sciences Research Papers

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