Eberhard E. Fetz

Harnessing neuroplasticity for clinical applications

Neuroplasticity can be defined as the ability of the nervous system to respond to intrinsic or extrinsic stimuli by reorganizing its structure, function and connections. Major advances in the understanding of neuroplasticity have to date yielded few established interventions. To advance the translation of neuroplasticity research towards clinical applications, the National Institutes of Health Blueprint for Neuroscience Research sponsored a workshop in 2009. Basic and clinical researchers in disciplines from central nervous system injury/stroke, mental/addictive disorders, paediatric/developmental disorders and neurodegeneration/ageing identified cardinal examples of neuroplasticity, underlying mechanisms, therapeutic implications and common denominators. Promising therapies that may enhance training-induced cognitive and motor learning, such as brain stimulation and neuropharmacological interventions, were identified, along with questions of how best to use this body of information to reduce human disability. Improved understanding of adaptive mechanisms at every level, from molecules to synapses, to networks, to behaviour, can be gained from iterative collaborations between basic and clinical researchers. Lessons can be gleaned from studying fields related to plasticity, such as development, critical periods, learning and response to disease. Improved means of assessing neuroplasticity in humans, including biomarkers for predicting and monitoring treatment response, are needed. Neuroplasticity occurs with many variations, in many forms, and in many contexts. However, common themes in plasticity that emerge across diverse central nervous system conditions include experience dependence, time sensitivity and the importance of motivation and attention. Integration of information across disciplines should enhance opportunities for the translation of neuroplasticity and circuit retraining research into effective clinical therapies.

Direct control of paralysed muscles by cortical neurons.

A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury by artificial connections. Such signals could then control electrical stimulation of muscles, thereby restoring volitional movement to paralysed limbs. In previously separate experiments, activity of motor cortex neurons related to actual or imagined movements has been used to control computer cursors and robotic arms, and paralysed muscles have been activated by functional electrical stimulation. Here we show that Macaca nemestrina monkeys can directly control stimulation of muscles using the activity of neurons in the motor cortex, thereby restoring goal-directed movements to a transiently paralysed arm. Moreover, neurons could control functional stimulation equally well regardless of any previous association to movement, a finding that considerably expands the source of control signals for brain-machine interfaces. Monkeys learned to use these artificial connections from cortical cells to muscles to generate bidirectional wrist torques, and controlled multiple neuron–muscle pairs simultaneously. Such direct transforms from cortical activity to muscle stimulation could be implemented by autonomous electronic circuitry, creating a relatively natural neuroprosthesis. These results are the first demonstration that direct artificial connections between cortical cells and muscles can compensate for interrupted physiological pathways and restore volitional control of movement to paralysed limbs.

Operant Conditioning of Cortical Unit Activity

The activity of single neurons in precentral cortex of unanesthetized monkeys (Macaca mulatta) was conditioned by reinforcing high rates of neuronal discharge with delivery of a food pellet. Auditory or visual feedback of unit firing rates was usually provided in addition to food reinforcement. After several training sessions, monkeys could increase the activity of newly isolated cells by 50 to 500 percent above rates before reinforcement.

Long-term motor cortex plasticity induced by an electronic neural implant

It has been proposed that the efficacy of neuronal connections is strengthened when there is a persistent causal relationship between presynaptic and postsynaptic activity. Such activity-dependent plasticity may underlie the reorganization of cortical representations during learning, although direct in vivo evidence is lacking. Here we show that stable reorganization of motor output can be induced by an artificial connection between two sites in the motor cortex of freely behaving primates. An autonomously operating electronic implant used action potentials recorded on one electrode to trigger electrical stimuli delivered at another location. Over one or more days of continuous operation, the output evoked from the recording site shifted to resemble the output from the corresponding stimulation site, in a manner consistent with the potentiation of synaptic connections between the artificially synchronized populations of neurons. Changes persisted in some cases for more than one week, whereas the output from sites not incorporated in the connection was unaffected. This method for inducing functional reorganization in vivo by using physiologically derived stimulus trains may have practical application in neurorehabilitation after injury.

Corticomotoneuronal cells contribute to long-latency stretch reflexes in the rhesus monkey.

To test the hypothesis that a transcortical reflex contributes to the stretch‐evoked long‐latency electromyographic (e.m.g.) response we documented the responses of identified corticomotoneuronal (c.m.) cells and their target muscles to perturbations of active wrist movements. Macaque monkeys performed ramp‐and‐hold wrist movements against elastic loads, alternating between flexion and extension zones; brief (25 ms) torque pulses were intermittently applied during the hold period. C.m. cells were identified by a clear post‐spike facilitation in spike‐triggered averages of forelimb muscle e.m.g. activity. Activity of c.m. cells and twelve wrist and digit flexor and extensor muscles was recorded during: (a) active ramp‐and‐hold wrist movements, (b) passive ramp‐and‐hold wrist movements, and (c) torque perturbations applied during the hold phase of active flexion and extension which either lengthened or shortened the c.m. cells target muscles. Muscle‐lengthening perturbations evoked a reproducible pattern of average e.m.g. activity in the stretched muscles, consisting of two peaks: the first response (M1) had an onset latency of 11.2 +/‐ 2.1 ms (mean +/‐ S.D.), and the second (M2) began at 27.9 +/‐ 5.1 ms. Torque perturbations which shortened the active muscles also evoked a characteristic e.m.g. response consisting of an initial cessation of activity at 13.5 +/‐ 3.4 ms followed by a peak beginning at 33.9 +/‐ 3.0 ms. The responses of twenty‐one c.m. cells which facilitated wrist muscles were documented with torque pulse perturbations applied during active muscle contraction. Twenty of twenty‐one c.m. cells responded at short latency (23.4 +/‐ 8.8 ms) to torque perturbations which stretched their target muscles. For each c.m. cell‐target muscle pair, transcortical loop time was calculated as the sum of the onset latency of the c.m. cells response to lengthening perturbations (afferent time) and the onset latency of post‐spike facilitation (efferent time). The mean transcortical loop time was 30.4 +/‐ 10.2 ms, comparable to the mean onset latency of the M2 peak (27.9 +/‐ 5.1). The duration of a c.m. cells response to torque perturbations provides a further measure of the extent of its potential contribution to the M2 muscle response. In all cases but two, the c.m. cell response, delayed by the latency of the post‐spike facilitation, overlapped the M2 e.m.g. peak.

Cortical activity during motor execution, motor imagery, and imagery-based online feedback

Imagery of motor movement plays an important role in learning of complex motor skills, from learning to serve in tennis to perfecting a pirouette in ballet. What and where are the neural substrates that underlie motor imagery-based learning? We measured electrocorticographic cortical surface potentials in eight human subjects during overt action and kinesthetic imagery of the same movement, focusing on power in “high frequency” (76–100 Hz) and “low frequency” (8–32 Hz) ranges. We quantitatively establish that the spatial distribution of local neuronal population activity during motor imagery mimics the spatial distribution of activity during actual motor movement. By comparing responses to electrocortical stimulation with imagery-induced cortical surface activity, we demonstrate the role of primary motor areas in movement imagery. The magnitude of imagery-induced cortical activity change was ∼25% of that associated with actual movement. However, when subjects learned to use this imagery to control a computer cursor in a simple feedback task, the imagery-induced activity change was significantly augmented, even exceeding that of overt movement.

Decoupling the Cortical Power Spectrum Reveals Real-Time Representation of Individual Finger Movements in Humans

During active movement the electric potentials measured from the surface of the motor cortex exhibit consistent modulation, revealing two distinguishable processes in the power spectrum. At frequencies <40 Hz, narrow-band power decreases occur with movement over widely distributed cortical areas, while at higher frequencies there are spatially more focal power increases. These high-frequency changes have commonly been assumed to reflect synchronous rhythms, analogous to lower-frequency phenomena, but it has recently been proposed that they reflect a broad-band spectral change across the entire spectrum, which could be obscured by synchronous rhythms at low frequencies. In 10 human subjects performing a finger movement task, we demonstrate that a principal component type of decomposition can naively separate low-frequency narrow-band rhythms from an asynchronous, broad-spectral, change at all frequencies between 5 and 200 Hz. This broad-spectral change exhibited spatially discrete representation for individual fingers and reproduced the temporal movement trajectories of different individual fingers.

Advanced Neurotechnologies for Chronic Neural Interfaces: New Horizons and Clinical Opportunities

### Introduction Technological advances in neural interfaces are providing increasingly more powerful “toolkits” of designs, materials, components, and integrated devices for establishing high-fidelity chronic neural interfaces. For a broad class of neuroscience studies, the primary

Sensory input to primate spinal cord is presynaptically inhibited during voluntary movement

During normal voluntary movements, re-afferent sensory input continuously converges on the spinal circuits that are activated by descending motor commands. This time-varying input must either be synergistically combined with the motor commands or be appropriately suppressed to minimize interference. The earliest suppression could be produced by presynaptic inhibition, which effectively reduces synaptic transmission at the initial synapse. Here we report evidence from awake, behaving monkeys that presynaptic inhibition decreases the ability of afferent impulses to affect postsynaptic neurons in a behaviorally dependent manner. Evidence indicates that cutaneous afferent input to spinal cord interneurons is inhibited presynaptically during active wrist movement, and this inhibition is effectively produced by descending commands. Our results further suggest that this presynaptic inhibition has appropriate functional consequences for movement generation and may underlie increases in perceptual thresholds during active movement.

Primate spinal interneurons show pre-movement instructed delay activity

Preparatory changes in neural activity before the execution of a movement have been documented in tasks that involve an instructed delay period (an interval between a transient instruction cue and a subsequently triggered movement). Such preparatory activity occurs in many motor centres in the brain, including the primary motor cortex, premotor cortex, supplementary motor area and basal ganglia. Activity during the instructed delay period reflects movement planning, as it correlates with parameters of the cue and the subsequent movement (such as direction and extent), although it occurs well before muscle activity. How such delay-period activity shapes the ensuing motor action remains unknown. Here we show that spinal interneurons also exhibit early pre-movement delay activity that often differs from their responses during the subsequent muscle activity. This delay activity resembles the set-related activity found in various supraspinal areas, indicating that movement preparation may occur simultaneously over widely distributed regions, including spinal levels. Our results also suggest that two processes occur in the spinal circuitry during this delay period: the motor network is primed with rate changes in the same direction as subsequent movement-related activity; and a superimposed global inhibition suppresses the expression of this activity in muscles.