Single-Neuron Stability during Repeated Reaching in Macaque Premotor Cortex

Abstract

Some movements that animals and humans make are highly stereotyped, repeated with little variation. The patterns of neural activity associated with repeats of a movement may be highly similar, or the same movement may arise from different patterns of neural activity, if the brain exploits redundancies in the neural projections to muscles. We examined the stability of the relationship between neural activity and behavior. We asked whether the variability in neural activity that we observed during repeated reaching was consistent with a noisy but stable relationship, or with a changing relationship, between neural activity and behavior. Monkeys performed highly similar reaches under tight behavioral control, while many neurons in the dorsal aspect of premotor cortex and the primary motor cortex were simultaneously monitored for several hours. Neural activity was predominantly stable over time in all measured properties: firing rate, directional tuning, and contribution to a decoding model that predicted kinematics from neural activity. The small changes in neural activity that we did observe could be accounted for primarily by subtle changes in behavior. We conclude that the relationship between neural activity and practiced behavior is reasonably stable, at least on timescales of minutes up to 48 h. This finding has significant implications for the design of neural prosthetic systems because it suggests that device recalibration need not be overly frequent, It also has implications for studies of neural plasticity because a stable baseline permits identification of nonstationary shifts.

Face-selective neurons maintain consistent visual responses across months

“…Some evidence from longitudinal recordings from primary visual and somatosensory cortices supports this idea (26,38). Results from the motor cortex are more variable, with some groups reporting consistent relations between behavior and the preferred direction of single neurons (39)(40)(41) and others finding some degree of change across days (5,42) or even within the course of a single session (6). Because activity outside of the primary sensory and motor cortical areas is less tightly coupled to action in the periphery, we might expect to see more change over time in higher level association areas.…”

Neural prosthetic systems: Current problems and future directions

“…We trained a rhesus monkey (Macaca mulatta), monkey L, in a standard reaching paradigm that has been extensively reported elsewhere [25], [28], [29]. We give a short overview here.…”

“…After a brief hold time, a peripheral target appears, indicating the goal of his reach. Restrictions on reaction time ensure that the monkey will reach quickly and accurately to the peripheral target, then receiving a juice reward [28]. This experiment was performed on 39 days over a period of 7 weeks.…”

“…To do this, we use the popular linear decoder (LD), which assumes that movement is a linear combination of recorded neural activity. Using least squares, the movement can be decoded from neural activity, and common metrics such as root-mean-squared-error (RMS) or correlation coefficient can be used to determine the quality of decode [28], [29]. A third common approach is the Kalman filter [31], which stipulates a linear relationship between physical behavior over time and between neural activity and physical behavior [14], [29].…”

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

“…Furthermore, isolations are typically stable for hours, in some cases days. Thus, the desire to collect a good deal of data quickly from stable isolations can provide sufficient motivation [e.g., 12], particularly if neural plasticity is the topic of study [e.g., 13,14]. Still, the strongest motivations relate to the simultaneous nature of array recordings, and the need to know how the activity of different neurons varies together across not-quite-identical trials [15].…”