UNASSIGNED: Deficits in motor functioning are one of the hallmarks of @entity2033 ( @entity2033 ), a genetically caused @entity179 . We applied functional magnetic resonance imaging (fMRI) and @entity3628 ( @entity3628 ) 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 @entity2033 gene carriers (preHD), and 16 @entity1 with @entity2033 (earlyHD) performed a motor finger-tapping fMRI task with systematically varying speed and complexity. @entity3628 was used to assess the causal interactions among seven pre-defined regions of interest, comprising primary motor cortex, supplementary motor area ( @entity11280 ), dorsal premotor cortex, and superior parietal cortex. To capture heterogeneity among @entity2033 gene carriers, @entity3628 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, @entity3628 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 @entity194 . While speed of finger movements did not modulate the connection from caudal to pre- @entity11280 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. @entity3628 proved useful in identifying group differences that would have remained undetected by standard analyses and may aid in the investigation of between-subject heterogeneity.

Detection of Motor Changes in XXXX Using Dynamic Causal Modeling.

@entity1 :: ('9606', 'Species') :: ['patients'] @entity3628 :: ('MESH:D004195', 'Disease') :: ['DCM', 'dynamic causal modeling'] @entity2033 :: ('MESH:D006816', 'Disease') :: ['manifest HD symptoms', "Huntington's disease", 'HD'] @entity179 :: ('MESH:D019636', 'Disease') :: ['neurodegenerative disorder'] @entity194 :: ('MESH:D001284', 'Disease') :: ['atrophy'] @entity11280 :: ('6606', 'Gene') :: ['SMA']
@entity2033 :: (MESH:D006816,Disease) :: ['Huntington's Disease']
