Intact action segmentation in Parkinson's disease: Hypothesis testing using a novel computational approach

Neuropsychologia. 2015 Nov:78:29-40. doi: 10.1016/j.neuropsychologia.2015.09.034. Epub 2015 Sep 30.


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.

Keywords: Action representation; Action segmentation; Computational classifier; Episodic memory; Parkinson's disease; Predictive perception; Temporal prediction.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Antiparkinson Agents / therapeutic use
  • Basal Ganglia / physiopathology
  • Computer Simulation
  • Dopamine Agonists / therapeutic use
  • Humans
  • Judgment / physiology
  • Memory* / drug effects
  • Memory* / physiology
  • Middle Aged
  • Models, Neurological
  • Models, Psychological*
  • Motion Perception* / drug effects
  • Motion Perception* / physiology
  • Motor Skills / drug effects
  • Motor Skills / physiology
  • Neuropsychological Tests
  • Parkinson Disease / drug therapy
  • Parkinson Disease / physiopathology
  • Parkinson Disease / psychology*
  • Photic Stimulation
  • Semantics


  • Antiparkinson Agents
  • Dopamine Agonists