High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) applied to motor cortex is recognized as a useful and informative method for corticomotor mapping by evoking natural-appearing movements of the limb to consistent stable end-point positions. An important feature of these movements is that stimulation of a specific site in motor cortex evokes movement to the same spatial end point regardless of the starting position of the limb. The goal of this study was to delineate effective stimulus parameters for evoking forelimb movements to stable spatial end points from HFLD-ICMS applied to primary motor cortex (M1) in awake monkeys. We investigated stimulation of M1 as combinations of frequency (30-400 Hz), amplitude (30-200 μA), and duration (0.5-2 s) while concurrently recording electromyographic (EMG) activity from 24 forelimb muscles and movement kinematics with a motion capture system. Our results suggest a range of parameters (80-140 Hz, 80-140 μA, and 1,000-ms train duration) that are effective and safe for evoking forelimb translocation with subsequent stabilization at a spatial end point. The mean time for stimulation to elicit successful movement of the forelimb to a stable spatial end point was 475.8 ± 170.9 ms. Median successful frequency and amplitude were 110 Hz and 110 μA, respectively. Attenuated parameters resulted in inconsistent, truncated, or undetectable movements, while intensified parameters yielded no change to movement end points and increased potential for large-scale physiological spread and adverse focal motor effects. Establishing cortical stimulation parameters yielding consistent forelimb movements to stable spatial end points forms the basis for a systematic and comprehensive mapping of M1 in terms of evoked movements and associated muscle synergies. Additionally, the results increase our understanding of how the central nervous system may encode movement.

Intracortical microstimulation can be used successfully to modulate neuronal activity. Activity-dependent stimulation (ADS), in which action potentials recorded extracellularly from a single neuron are used to trigger stimulation at another cortical location (closed-loop), is an effective treatment for behavioral recovery after brain lesion, but the related neurophysiological changes are still not clear. Here, we investigated the ability of ADS and random stimulation (RS) to alter firing patterns of distant cortical locations. We recorded 591 neuronal units from 23 Long-Evan healthy anesthetized rats. Stimulation was delivered to either forelimb or barrel field somatosensory cortex, using either RS or ADS triggered from spikes recorded in the rostral forelimb area (RFA). Both RS and ADS stimulation protocols rapidly altered spike firing within RFA compared with no stimulation. We observed increase in firing rates and change of spike patterns. ADS was more effective than RS in increasing evoked spikes during the stimulation periods, by producing a reliable, progressive increase in stimulus-related activity over time and an increased coupling of the trigger channel with the network. These results are critical for understanding the efficacy of closed-loop electrical microstimulation protocols in altering activity patterns in interconnected brain networks, thus modulating cortical state and functional connectivity.

High-frequency, long-duration intracortical microstimulation (HFLD-ICMS) is increasingly being used to deduce how the brain encodes coordinated muscle activity and movement. However, the full movement repertoire that can be elicited from the forelimb representation of primary motor cortex (M1) using this method has not been systematically determined. Our goal was to acquire a comprehensive M1 forelimb representational map of movement endpoints elicited with HFLD-ICMS, using stimulus parameters optimal for evoking stable forelimb spatial endpoints. The data reveal a 3D forelimb movement endpoint workspace that is represented in a patchwork fashion on the 2D M1 cortical surface. Although cortical maps of movement endpoints appear quite disorderly with respect to movement space, we show that the endpoint locations in the workspace evoked with HFLD-ICMS of two adjacent cortical points are closer together than would be expected if the organization were random. Although there were few obvious consistencies in the endpoint maps across the two monkeys tested, one notable exception was endpoints bringing the hand to the mouth, which was located at the boundary between the hand and face representation. Endpoints at the extremes of the monkey's workspace and locations above the head were largely absent. Our movement endpoints are best explained as resulting from coactivation of agonist and antagonist muscles driving the joints toward equilibrium positions determined by the length-tension relationships of the muscles.

Electrical stimulation of the brain was one of the first experimental methods applied to understanding brain organization and function and it continues as a highly useful method both in research and clinical applications. Intracortical microstimulation (ICMS) involves applying electrical stimuli through a microelectrode suitable for recording the action potentials of single neurons. ICMS can be categorized into single pulse stimulation, high frequency, short duration stimulation and high frequency, long duration stimulation. For clinical and experimental reasons, considerable interest focuses on the mechanism of neural activation by electrical stimuli. In this paper, we discuss recent results suggesting that action potentials evoked in cortical neurons by high frequency electrical stimulation do not sum with the natural, behaviorally related background activity; rather, high frequency stimulation eliminates and replaces natural activity. We refer to this as neural hijacking. We propose that a major component of the mechanism underlying neural hijacking is excitation of axons by ICMS and elimination of natural spikes by antidromic collision with stimulus driven spikes evoked at high frequency. Evidence also supports neural hijacking as an important mechanism underlying the action of deep brain stimulation (DBS) in the subthalamic nucleus and its therapeutic effect in treating Parkinson’s disease.

Neuromuscular control of voluntary movement may be simplified using muscle synergies similar to those found using non-negative matrix factorization. We recently identified synergies in electromyography (EMG) recordings associated with both voluntary movement and movement evoked by high-frequency long-duration intracortical microstimulation applied to the forelimb representation of the primary motor cortex (M1). The goal of this study was to use stimulus-triggered averaging (StTA) of EMG activity to investigate the synergy profiles and weighting coefficients associated with poststimulus facilitation, as synergies may be hard-wired into elemental cortical output modules and revealed by StTA. We applied StTA at low (LOW, ∼15 μA) and high intensities (HIGH, ∼110 μA) to 247 cortical locations of the M1 forelimb region in two male rhesus macaques while recording the EMG of 24 forelimb muscles. Our results show that 10-11 synergies accounted for 90% of the variation in poststimulus EMG facilitation peaks from the LOW-intensity StTA dataset while only 4-5 synergies were needed for the HIGH-intensity dataset. Synergies were similar across monkeys and current intensities. Most synergy profiles strongly activated only one or two muscles; all joints were represented and most, but not all, joint directions of motion were represented. Cortical maps of the synergy weighting coefficients suggest only a weak organization. StTA of M1 resulted in highly diverse muscle activations, suggestive of the limiting condition of requiring a synergy for each muscle to account for the patterns observed. Coordination of muscle activity and the neural origin of potential muscle synergies remains a fundamental question of neuroscience. We previously demonstrated that high-frequency long-duration intracortical microstimulation-evoked synergies were unrelated to voluntary movement synergies and were not clearly organized in the cortex. Here we present stimulus-triggered averaging facilitation-related muscle synergies, suggesting that when fundamental cortical output modules are activated, synergies approach the limit of single-muscle control. Thus, we conclude that if the CNS controls movement via linear synergies, those synergies are unlikely to be called from M1. This information is critical for understanding neural control of movement and the development of brain-machine interfaces.