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Articles, Behavioral/Cognitive

Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement

Deborah A. Barany, Valeria Della-Maggiore, Shivakumar Viswanathan, Matthew Cieslak and Scott T. Grafton
Journal of Neuroscience 14 May 2014, 34 (20) 6860-6873; DOI: https://doi.org/10.1523/JNEUROSCI.5173-13.2014
Deborah A. Barany
1Brain Imaging Center, Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, and
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Valeria Della-Maggiore
2Department of Physiology and Biophysics, School of Medicine, University of Buenos Aires, C1121ABG Buenos Aires, Argentina
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Shivakumar Viswanathan
1Brain Imaging Center, Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, and
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Matthew Cieslak
1Brain Imaging Center, Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, and
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Scott T. Grafton
1Brain Imaging Center, Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106, and
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Abstract

Neurophysiology and neuroimaging evidence shows that the brain represents multiple environmental and body-related features to compute transformations from sensory input to motor output. However, it is unclear how these features interact during goal-directed movement. To investigate this issue, we examined the representations of sensory and motor features of human hand movements within the left-hemisphere motor network. In a rapid event-related fMRI design, we measured cortical activity as participants performed right-handed movements at the wrist, with either of two postures and two amplitudes, to move a cursor to targets at different locations. Using a multivoxel analysis technique with rigorous generalization tests, we reliably distinguished representations of task-related features (primarily target location, movement direction, and posture) in multiple regions. In particular, we identified an interaction between target location and movement direction in the superior parietal lobule, which may underlie a transformation from the location of the target in space to a movement vector. In addition, we found an influence of posture on primary motor, premotor, and parietal regions. Together, these results reveal the complex interactions between different sensory and motor features that drive the computation of sensorimotor transformations.

  • fMRI
  • MVPA
  • sensorimotor transformations
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The Journal of Neuroscience: 34 (20)
Journal of Neuroscience
Vol. 34, Issue 20
14 May 2014
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Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement
Deborah A. Barany, Valeria Della-Maggiore, Shivakumar Viswanathan, Matthew Cieslak, Scott T. Grafton
Journal of Neuroscience 14 May 2014, 34 (20) 6860-6873; DOI: 10.1523/JNEUROSCI.5173-13.2014

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Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement
Deborah A. Barany, Valeria Della-Maggiore, Shivakumar Viswanathan, Matthew Cieslak, Scott T. Grafton
Journal of Neuroscience 14 May 2014, 34 (20) 6860-6873; DOI: 10.1523/JNEUROSCI.5173-13.2014
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Keywords

  • fMRI
  • MVPA
  • sensorimotor transformations

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