Minimax-optimal decoding of movement goals from local field potentials using complex spectral features
نویسندگان
چکیده
منابع مشابه
Optimizing the decoding of movement goals from local field potentials in macaque cortex.
The successful development of motor neuroprosthetic devices hinges on the ability to accurately and reliably decode signals from the brain. Motor neuroprostheses are widely investigated in behaving non-human primates, but technical constraints have limited progress in optimizing performance. In particular, the organization of movement-related neuronal activity across cortical layers remains poo...
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OBJECTIVE Correlating electrical activity within the human brain to movement is essential for developing and refining interventions (e.g. deep brain stimulation (DBS)) to treat central nervous system disorders. It also serves as a basis for next generation brain-machine interfaces (BMIs). This study highlights a new decoding strategy for capturing movement and its corresponding laterality from ...
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Local field potentials (LFPs) in primary motor cortex include significant information about reach target location and upper limb movement kinematics. Some evidence suggests that they may be a more robust, longer-lasting signal than action potentials (spikes). Here we assess whether LFPs can also be used to decode upper limb muscle activity, a complex movement-related signal. We record electromy...
متن کاملDecoding Movement Goals from the Fronto-Parietal Reach Network
During reach planning, fronto-parietal brain areas need to transform sensory information into a motor code. It is debated whether these areas maintain a sensory representation of the visual cue or a motor representation of the upcoming movement goal. Here, we present results from a delayed pro-/anti-reach task which allowed for dissociating the position of the visual cue from the reach goal. In...
متن کاملRole of local field potentials in encoding hand movement kinematics.
How the brain orchestrates the musculoskeletal system to produce complex three-dimensional movements is still poorly understood. Despite first promising results in brain-machine interfaces that translate cortical activity to control output, there is an ongoing debate about which brain signals provide richest information related to movement planning and execution. Novel results by Bansal and col...
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ژورنال
عنوان ژورنال: Journal of Neural Engineering
سال: 2019
ISSN: 1741-2560,1741-2552
DOI: 10.1088/1741-2552/ab1a1f