Instant neural control of a movement signal

Abstract

The activity of motor cortex (MI) neurons conveys movement intent sufficiently well to be used as a control signal to operate artificial devices, but until now this has called for extensive training or has been confined to a limited movement repertoire. Here we show how activity from a few (7-30) MI neurons can be decoded into a signal that a monkey is able to use immediately to move a computer cursor to any new position in its workspace (14 degrees x 14 degrees visual angle). Our results, which are based on recordings made by an electrode array that is suitable for human use, indicate that neurally based control of movement may eventually be feasible in paralysed humans.

A mixed filter algorithm for cognitive state estimation from simultaneously recorded continuous and binary measures of performance

“…state-space estimation procedures, by extending the current algorithm to construct mixed filter algorithms for continuous observations and point processes (continuous time binary processes) in either discrete or continuous time (Eden et al 2004;Snyder and Miller 1991). Second, the mixed filter algorithm may make it possible to use simultaneously recorded ensemble neural spiking activity and local field potentials to control neural prosthetic devices and brain machine interfaces (Musallam et al 2004;Serruya et al 2002;Taylor et al 2002;Wessberg et al 2005). Finally, the mixed filter algorithms may also suggest a new approach to analyzing cardiovascular and autonomic control from simultaneously recorded cardiovascular, respiratory and R − R interval measurements (Barbieri et al 1996(Barbieri et al , 1997(Barbieri et al , 2002 as well as for studying the dynamics of seismic events (Granat et al 2003).…”

Techniques for extracting single-trial activity patterns from large-scale neural recordings

“…An implicit form of dimensionality reduction is often performed in the context of neural prosthetic systems, when the trajectory of the arm is 'decoded' from simultaneously-recorded neurons [62][63][64]. High (~100) dimensional neural data is collapsed into a low (e.g., 3) dimensional arm trajectory estimate.…”

“…The decoded trajectory is thus a concise 'explanation' or summary of the high-dimensional neural data. Decoding techniques include linear filters [63,64], the population vector [62,65,66], and recursive Bayesian decoding using state-space models [67][68][69]. Most of these approaches attempt to infer something that can be directly observed/inferred on most trials (e.g., actual or expected arm trajectory), yet in some ways this is an advantage, as it allows evaluation of the performance of different decoding techniques.…”

Techniques and devices to restore cognition

“…Furthermore, the information encoded in the ensemble activity of multiple, simultaneously recorded individual neurons, can be decoded in real-time and be used in behaviorally useful manner [137]. A central goal of neurocognitive prosthetic development will be the determination of how to apply the realtime decoding techniques developed in neuromotor prosthetics to the growing body of data on how ensembles of neurons throughout cortex and subcortical structures represent cognitive features, such as spatial position in the environment [41,82,136].…”