Representation and decoding of bilateral arm motor imagery using unilateral cerebral LFP signals.

Introduction: In the field of upper limb brain computer interfaces (BCIs), the research focusing on bilateral decoding mostly based on the neural signals from two cerebral hemispheres. In addition, most studies used spikes for decoding. Here we examined the representation and decoding of different laterality and regions arm motor imagery in unilateral motor cortex based on local field potentials (LFPs).

Neuronal representation of bimanual arm motor imagery in the motor cortex of a tetraplegia human, a pilot study.

Introduction: How the human brain coordinates bimanual movements is not well-established.

Methods: Here, we recorded neural signals from a paralyzed individual's left motor cortex during both unimanual and bimanual motor imagery tasks and quantified the representational interaction between arms by analyzing the tuning parameters of each neuron.

Results: We found a similar proportion of neurons preferring each arm during unimanual movements, however, when switching to bimanual movements, the proportion of contralateral preference increased to 71.