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CANONICAL CEREBELLAR GRAPHWAVELETS AND THEIR APPLICATION TO FMRI ACTIVATION MAPPING
"... Wavelet-based statistical parametric mapping (WSPM) is an extension of the classical approach in fMRI activation mapping that combines wavelet processing with voxel-wise statistical testing. We recently showed how WSPM, using graph wavelets tailored to the full gray-matter (GM) structure of each ind ..."
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Wavelet-based statistical parametric mapping (WSPM) is an extension of the classical approach in fMRI activation mapping that combines wavelet processing with voxel-wise statistical testing. We recently showed how WSPM, using graph wavelets tailored to the full gray-matter (GM) structure of each individual’s brain, can improve brain activity detection compared to using the classical wavelets that are only suited for the Euclidian grid. However, in order to perform analysis on a subject-invariant graph, canonical graph wavelets should be designed in normalized brain space. We here introduce an approach to define a fixed template graph of the cerebellum, an essential component of the brain, using the SUIT cerebellar template. We construct a corresponding set of canonical cerebellar graph wavelets, and adopt them in the analysis of both synthetic and real data. Compared to classical SPM, WSPM using cerebellar graph wavelets shows superior type-I error control, an empirical higher sensitivity on real data, as well as the potential to capture subtle patterns of cerebellar activity. Index Terms — Statistical testing, functional MRI, cerebellum, spectral graph theory, graph wavelet transform, wavelet thresholding
unknown title
, 2011
"... and visuomotor perturbation Cerebellar regions involved in adaptation to force field You might find this additional info useful... for this article can be found at:Supplemental material ..."
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and visuomotor perturbation Cerebellar regions involved in adaptation to force field You might find this additional info useful... for this article can be found at:Supplemental material
SENSITIVITY TO MOTOR ERROR IN CHILDREN WITH AUTISM
, 2014
"... ii When making a movement, the brain receives sensory feedback about the consequences of that action. If sensory feedback differs from predicted, the brain experiences an error, driving adaptation and improving subsequent movements. How much the brain adapts to error is governed by its sensitivity. ..."
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ii When making a movement, the brain receives sensory feedback about the consequences of that action. If sensory feedback differs from predicted, the brain experiences an error, driving adaptation and improving subsequent movements. How much the brain adapts to error is governed by its sensitivity. Computationally, sensitivity is a scaling factor, specifying the relative amount of adaptation that occurs, while theoretically it is a quantification of the error’s value. In children with autism spectrum disorder (ASD), the response to sensory feedback appears abnormal. In particular, they are hyperresponsive to proprioceptive feedback and hyporesponsive to visual feedback. Here, we hypothesized that these sensory abnormalities would be manifested as an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error. Further, we hypothesized that this pattern of error sensitivity would be related to anatomical abnormalities in the cerebellum, known to be a neural substrate of motor learning.
Behavioural and neural basis of anomalous motor learning in children with autism
"... Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to ..."
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Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8–12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in
