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Front Hum Neurosci. 2015 Nov 25;9:634. doi: 10.3389/fnhum.2015.00634. eCollection 2015.

Detection of Motor Changes in Huntington's Disease Using Dynamic Causal Modeling.

Author information

1
Department of Psychiatry and Psychotherapy, University Medical Center Freiburg Freiburg, Germany ; Freiburg Brain Imaging Center, University Medical Center Freiburg Freiburg, Germany ; Laboratory for Biological and Personality Psychology, Department of Psychology, University of Freiburg Freiburg, Germany.
2
Department of Psychiatry and Psychotherapy, University Medical Center Freiburg Freiburg, Germany ; Freiburg Brain Imaging Center, University Medical Center Freiburg Freiburg, Germany.
3
Freiburg Brain Imaging Center, University Medical Center Freiburg Freiburg, Germany ; Department of Computer Science, University of Freiburg Freiburg, Germany.
4
Freiburg Brain Imaging Center, University Medical Center Freiburg Freiburg, Germany ; Department of Neurology, University Medical Center Freiburg Freiburg, Germany ; BrainLinks-BrainTools Cluster of Excellence, University of Freiburg Freiburg, Germany.
5
Department of Neurology, Leiden University Medical Centre Leiden, Netherlands.
6
Department of Genetics and Cytogenetics, Pitié-Salpêtrière University Hospital Paris, France.
7
Centre for Molecular Medicine and Therapeutics, Department of Medical Genetics, University of British Columbia Vancouver, Canada.
8
Department of Neurodegenerative Disease, Institute of Neurology, University College London London, UK.
9
Department of Psychiatry and Psychotherapy, University Medical Center Freiburg Freiburg, Germany ; Freiburg Brain Imaging Center, University Medical Center Freiburg Freiburg, Germany ; Department of Neurology, University Medical Center Freiburg Freiburg, Germany.

Abstract

Deficits in motor functioning are one of the hallmarks of Huntington's disease (HD), a genetically caused neurodegenerative disorder. We applied functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess changes that occur with disease progression in the neural circuitry of key areas associated with executive and cognitive aspects of motor control. Seventy-seven healthy controls, 62 pre-symptomatic HD gene carriers (preHD), and 16 patients with manifest HD symptoms (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. DCM was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area (SMA), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among HD gene carriers, DCM parameters were entered into a hierarchical cluster analysis using Ward's method and squared Euclidian distance as a measure of similarity. After applying Bonferroni correction for the number of tests, DCM analysis revealed a group difference that was not present in the conventional fMRI analysis. We found an inhibitory effect of complexity on the connection from parietal to premotor areas in preHD, which became excitatory in earlyHD and correlated with putamen atrophy. While speed of finger movements did not modulate the connection from caudal to pre-SMA in controls and preHD, this connection became strongly negative in earlyHD. This second effect did not survive correction for multiple comparisons. Hierarchical clustering separated the gene mutation carriers into three clusters that also differed significantly between these two connections and thereby confirmed their relevance. DCM proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

KEYWORDS:

DCM; Huntington's disease; cluster analysis; fMRI; motor network; sequential finger tapping

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