Decoding 3 - D reach and grasp from hybrid signals 1 in motor and premotor cortices : spikes , multiunit 2 activity and local field potentials

21 Neural activity in motor cortex during reach and grasp movements shows modulations in 22 a broad range of signals from single-neuron spiking activity (SA) to various frequency 23 bands in broadband local field potentials (LFPs). In particular, spatiotemporal patterns in 24 multiband LFPs are thought to reflect dendritic integration of local and inter-areal 25 synaptic inputs, attentional and preparatory processes, and multiunit activity (MUA) 26 related to movement representation in the local motor area. Nevertheless, the relationship 27 between multiband LFPs and SA, as well as their relationship to movement parameters 28 and their relative value as brain-computer interface (BCI) control signals, remain poorly 29 understood. In addition, even as this broad range of signals may provide complementary 30 information channels in primary (MI) and ventral pre-motor (PMv) areas, areal 31 differences in information have not been systematically examined. Here, for the first 32 time, the amount of information in SA and multiband LFPs was compared for MI and 33 PMv by recording from dual 96-multielectrode arrays while monkeys made naturalistic 34 reach and grasp actions. Information was assessed as decoding accuracy for 3-D arm35 endpoint and grip-aperture kinematics based on SA or LFPs in MI and PMv, or 36 combinations of signal types across areas. In contrast with previous studies with ≤16 37 simultaneous electrodes, here ensembles of >16 units (on average) carried more 38 information than multiband, multichannel LFPs. Further, reach and grasp information 39 added by various LFP frequency bands was not independent from that in SA ensembles, 40 but rather typically less than and primarily contained within the latter. Notably, MI and 41 PMv did not show a particular bias towards reach or grasp for this task or for a broad 42 range of signal types. For BCIs, our results indicate that neuronal ensemble spiking is the 43 preferred signal for decoding, while LFPs and combined signals from PMv and MI can 44 add robustness to BCI control. 45