Dynamic structure of motor cortical neuron co-activity carries behaviorally relevant information

(This is the dataset used in Dynamic Structure Of Motor Cortical Neuron
Co-Activity Carries Behaviorally Relevant Information, Abstract below)
Skillful, voluntary movements are underpinned by computations performed by
networks of interconnected neurons in the primary motor cortex (M1).
Computations are reflected by patterns of co-activity between neurons.
Using pairwise spike time statistics, co-activity can be summarized as a
functional network (FN). Here, we show that the structure of FNs
constructed from an instructed-delay reach task in non-human primates are
behaviorally specific: low dimensional embedding and graph alignment
scores show that FNs constructed from closer target reach directions are
also closer in network space. Using short intervals across a trial we
constructed temporal FNs and found that temporal FNs traverse a
low-dimensional subspace in a reach-specific trajectory. Alignment scores
show that FNs become separable and correspondingly decodable shortly after
the instruction cue. Finally, we observe that reciprocal connections in
FNs transiently decrease following the instruction cue consistent with the
hypothesis that information external to the recorded population
temporarily alters the structure of the network at this moment.