Decoding action intentions from preparatory brain activity in human parieto-frontal networks

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How and where in the human brain high-level sensorimotor processes such as intentions and decisions are coded remain important yet essentially unanswered questions. This is in part because, to date, decoding intended actions from brain signals has been primarily constrained to invasive neural recordings in nonhuman primates. Here we demonstrate using functional MRI (fMRI) pattern recognition techniques that we can also decode movement intentions from human brain signals, specifically object-directed grasp and reach movements, moments before their initiation. Subjects performed an event-related delayed movement task toward a single centrally located object (consisting of a small cube attached atop a larger cube). For each trial, after visual presentation of the object, one of three hand movements was instructed: grasp the top cube, grasp the bottom cube, or reach to touch the side of the object (without preshaping the hand). We found that, despite an absence of fMRI signal amplitude differences between the planned movements, the spatial activity patterns in multiple parietal and premotor brain areas accurately predicted upcoming grasp and reach movements. Furthermore, the patterns of activity in a subset of these areas additionally predicted which of the two cubes were to be grasped. These findings offer new insights into the detailed movement information contained in human preparatory brain activity and advance our present understanding of sensorimotor planning processes through a unique description of parieto-frontal regions according to the specific types of hand movements they can predict.

Keywords

  • Adult, Brain Mapping, Female, Frontal Lobe, Hand, Humans, Image Processing, Computer-Assisted, Intention, Magnetic Resonance Imaging, Male, Motor Activity, Movement, Nerve Net, Parietal Lobe, Photic Stimulation, Journal Article, Research Support, Non-U.S. Gov't
Original languageEnglish
Pages (from-to)9599-9610
Number of pages12
JournalJournal of Neuroscience
Volume31
Issue number26
DOIs
Publication statusPublished - 29 Jun 2011
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