Synchronization in monkey motor cortex during a precision grip task. I. Task-dependent modulation in single-unit synchrony

Task difficulty of visually guided gait modifications involves differences in central drive to spinal motor neurons

Walking in natural environments requires visually guided modifications, which can be more challenging when involving sideways steps rather than longer steps. This exploratory study investigated whether these two types of modifications involve different changes in the central drive to spinal motor neurons of leg muscles. Fifteen adults [age: 36 ± 6 (SD) years] walked on a treadmill (4 km/h) while observing a screen displaying the real-time position of their toes. At the beginning of the swing phase, a visual target appeared in front (forward) or medial-lateral (sideways) of the ground contact in random step cycles (approximately every third step). We measured three-dimensional kinematics and electromyographic activity from leg muscles bilaterally. Intermuscular coherence was calculated in the alpha (5-15 Hz), beta (15-30 Hz), and gamma bands (30-45 Hz) approximately 230 ms before and after ground contact in control and target steps. Results showed that adjustments toward sideways targets were associated with significantly higher error, lower foot lift, and higher cocontraction between antagonist ankle muscles. Movements toward sideways targets were associated with larger beta-band soleus (SOL): medial gastrocnemius (MG) coherence and a more narrow and larger peak of synchronization in the cumulant density before ground contact. In contrast, movements toward forward targets showed no significant differences in coherence or synchronization compared with control steps. Larger SOL:MG beta-band coherence and short-term synchronization were observed during sideways, but not forward, gait modifications. This suggests that visually guided gait modifications may involve differences in the central drive to spinal ankle motor neurons dependent on the level of task difficulty.NEW & NOTEWORTHY This exploratory study suggests a specific and temporally restricted increase of central (likely corticospinal) drive to ankle muscles in relation to visually guided gait modifications. The findings indicate that a high level of visual attention to control the position of the ankle joint precisely before ground contact may involve increased central drive to ankle muscles. These findings are important for understanding the neural mechanisms underlying visually guided gait and may help develop rehabilitation interventions.

Standard intensities of transcranial alternating current stimulation over the motor cortex do not entrain corticospinal inputs to motor neurons

Transcranial alternating current stimulation (TACS) is commonly used to synchronize a cortical area and its outputs to the stimulus waveform, but gathering evidence for this based on brain recordings in humans is challenging. The corticospinal tract transmits beta oscillations (∼21 Hz) from the motor cortex to tonically contracted limb muscles linearly. Therefore, muscle activity may be used to measure the level of beta entrainment in the corticospinal tract due to TACS over the motor cortex. Here, we assessed whether TACS is able to modulate the neural inputs to muscles, which would provide indirect evidence for TACS-driven neural entrainment. In the first part of the study, we ran simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results suggest that MNs are highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N = 10) in which TACS (at 1 mA) was delivered over the motor cortex at 21 Hz (beta stimulation), or at 7 Hz or 40 Hz (control conditions) while the abductor digiti minimi or the tibialis anterior muscle were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the activity of pools of motor units innervating the muscles. By analysing motor unit pool activity, we observed that none of the TACS conditions could consistently alter the spectral contents of the common neural inputs received by the muscles. These results suggest that 1 mA TACS over the motor cortex given at beta frequencies does not entrain corticospinal activity. KEY POINTS: Transcranial alternating current stimulation (TACS) is commonly used to entrain the communication between brain regions. It is challenging to find direct evidence supporting TACS-driven neural entrainment due to the technical difficulties in recording brain activity during stimulation. Computational simulations of motor neuron pools receiving common inputs in the beta (∼21 Hz) band indicate that motor neurons are highly sensitive to corticospinal beta entrainment. Motor unit activity from human muscles does not support TACS-driven corticospinal entrainment.

Bayesian prediction of psychophysical detection responses from spike activity in the rat sensorimotor cortex

Decoding of sensorimotor information is essential for brain-computer interfaces (BCIs) as well as in normal functioning organisms. In this study, Bayesian models were developed for the prediction of binary decisions of 10 awake freely-moving male/female rats based on neural activity in a vibrotactile yes/no detection task. The vibrotactile stimuli were 40-Hz sinusoidal displacements (amplitude: 200 µm, duration: 0.5 s) applied on the glabrous skin. The task was to depress the right lever for stimulus detection and left lever for stimulus-off condition. Spike activity was recorded from 16-channel microwire arrays implanted in the hindlimb representation of primary somatosensory cortex (S1), overlapping also with the associated representation in the primary motor cortex (M1). Single-/multi-unit average spike rate (R_d) within the stimulus analysis window was used as the predictor of the stimulus state and the behavioral response at each trial based on a Bayesian network model. Due to high neural and psychophysical response variability for each rat and also across subjects, mean R_d was not correlated with hit and false alarm rates. Despite the fluctuations in the neural data, the Bayesian model for each rat generated moderately good accuracy (0.60-0.90) and good class prediction scores (recall, precision, F1) and was also tested with subsets of data (e.g. regular vs. fast spike groups). It was generally observed that the models were better for rats with lower psychophysical performance (lower sensitivity index A'). This suggests that Bayesian inference and similar machine learning techniques may be especially helpful during the training phase of BCIs or for rehabilitation with neuroprostheses.

Deconvolution improves the detection and quantification of spike transmission gain from spike trains

Accurate detection and quantification of spike transmission between neurons is essential for determining neural network mechanisms that govern cognitive functions. Using point process and conductance-based simulations, we found that existing methods for determining neuronal connectivity from spike times are highly affected by burst spiking activity, resulting in over- or underestimation of spike transmission. To improve performance, we developed a mathematical framework for decomposing the cross-correlation between two spike trains. We then devised a deconvolution-based algorithm for removing effects of second-order spike train statistics. Deconvolution removed the effect of burst spiking, improving the estimation of neuronal connectivity yielded by state-of-the-art methods. Application of deconvolution to neuronal data recorded from hippocampal region CA1 of freely-moving mice produced higher estimates of spike transmission, in particular when spike trains exhibited bursts. Deconvolution facilitates the precise construction of complex connectivity maps, opening the door to enhanced understanding of the neural mechanisms underlying brain function.

Stimulus transformation into motor action: Dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

Cognitive performance slows down with increasing age. This includes cognitive processes that are essential for the performance of a motor act, such as the slowing down in response to an external stimulus. The objective of this study was to identify aging-associated functional changes in the brain networks that are involved in the transformation of external stimuli into motor action. To investigate this topic, we employed dynamic graphs based on phase-locking of Electroencephalography signals recorded from healthy younger and older subjects while performing a simple visually-cued finger-tapping task. The network analysis yielded specific age-related network structures varying in time in the low frequencies (2-7 Hz), which are closely connected to stimulus processing, movement initiation and execution in both age groups. The networks in older subjects, however, contained several additional, particularly interhemispheric, connections and showed an overall increased coupling density. Cluster analyses revealed reduced variability of the subnetworks in older subjects, particularly during movement preparation. In younger subjects, occipital, parietal, sensorimotor and central regions were-temporally arranged in this order-heavily involved in hub nodes. Whereas in older subjects, a hub in frontal regions preceded the noticeably delayed occurrence of sensorimotor hubs, indicating different neural information processing in older subjects. All observed changes in brain network organization, which are based on neural synchronization in the low frequencies, provide a possible neural mechanism underlying previous fMRI data, which report an overactivation, especially in the prefrontal and pre-motor areas, associated with a loss of hemispheric lateralization in older subjects.

Reversible Block of Cerebellar Outflow Reveals Cortical Circuitry for Motor Coordination

Coordinated movements are achieved by well-timed activation of selected muscles. This process relies on intact cerebellar circuitry, as demonstrated by motor impairments following cerebellar lesions. Based on anatomical connectivity and symptoms observed in cerebellar patients, we hypothesized that cerebellar dysfunction should disrupt the temporal patterns of motor cortical activity, but not the selected motor plan. To test this hypothesis, we reversibly blocked cerebellar outflow in primates while monitoring motor behavior and neural activity. This manipulation replicated the impaired motor timing and coordination characteristic of cerebellar ataxia. We found extensive changes in motor cortical activity, including loss of response transients at movement onset and decoupling of task-related activity. Nonetheless, the spatial tuning of cells was unaffected, and their early preparatory activity was mostly intact. These results indicate that the timing of actions, but not the selection of muscles, is regulated through cerebellar control of motor cortical activity.

Dissociation between Temporal and Spatial Anticipation in the Neural Dynamics of Goal-directed Movement Preparation

It is well documented that providing advanced information regarding the spatial location of a target stimulus (i.e., spatial anticipation) or its timing of occurrence (i.e., temporal anticipation) influences reach preparation, reducing RTs. Yet, it remains unknown whether the RT gains attributable to temporal and spatial anticipation are subtended by similar preparatory dynamics. Here, this issue is addressed in humans by investigating EEG beta-band activity during reach preparation. Participants performed a reach RT task in which they initiated a movement as fast as possible toward visual targets following their appearance. Temporal anticipation was manipulated by having the target appear after a constant or variable delay period, whereas spatial anticipation was manipulated by precueing participants about the upcoming target location in advance or not. Results revealed that temporal and spatial anticipation both reduced reach RTs, with no interaction. Interestingly, temporal and spatial anticipation were associated with fundamentally different patterns of beta-band modulations. Temporal anticipation was associated with beta-band desynchronization over contralateral sensorimotor regions specifically around the expected moment of target onset, the magnitude of which was correlated with RT modulations across participants. In contrast, spatial anticipation did not influence sensorimotor activity but rather led to increased beta-band power over bilateral parieto-occipital regions during the entire delay period. These results argue for distinct states of preparation incurred by temporal and spatial anticipation. In particular, sensorimotor beta-band desynchronization may reflect the timely disinhibition of movement-related neuronal ensembles at the expected time of movement initiation, without reflecting its spatial parameters per se.

Review: Methods of firing rate estimation

Neuronal firing rate is traditionally defined as the number of spikes per time window. The concept is essential for the rate coding hypothesis, which is still the most commonly investigated scenario in neuronal activity analysis. The estimation of dynamically changing firing rate from neural data can be challenging due to the variability of spike times, even under identical external conditions; hence a wide range of statistical measures have been employed to solve this particular problem. In this paper, we review established firing rate estimation methods, briefly summarize the technical aspects of each approach and discuss their practical applications.

Sequential Neural Activity in Primary Motor Cortex during Sleep

Sequential firing of neurons during sleep is thought to play a role in the consolidation of learning. However, direct evidence for such sequence replay is limited to only a few brain areas and sleep states mainly in rodents. Using a custom-designed wearable neural data logger and chronically implanted electrodes, we made long-term recordings of neural activity in the primary motor cortex of two female nonhuman primates during free behavior and natural sleep. We used the local field potential (LFP) spectrogram to characterize sleep cycles, and examined firing rates, correlations, and sequential firing of neurons at different frequency bands through the cycle. Slow-wave sleep (SWS) was characterized by low neural firing rates and high synchrony, reflecting slow oscillations between cortical down and up states. However, the order in which neurons entered up states was similar to the sequence of neural activity observed at low frequencies during waking behavior. In addition, we found evidence of brief bursts of theta oscillation, associated with non-SWS states, during which neurons fired in strikingly regular sequential order phase-locked to the LFP. Theta sequences were preserved between waking and sleep, but appeared not to resemble the order of neural activity observed at lower frequencies. The sequential firing of neurons during slow oscillations and theta bursts may contribute to the consolidation of procedural memories during sleep.SIGNIFICANCE STATEMENT Replay of sequential neural activity during sleep is believed to support consolidation of daytime learning. Despite a wealth of studies investigating sequential replay in association with episodic and spatial memory, it is unknown whether similar sequences occur in motor areas during sleep. Within long-term neural recordings from monkey motor cortex, we found two distinct patterns of sequential activity during different phases of the natural sleep cycle. Slow-wave sleep was associated with delta-band sequences that resembled low-frequency activity during movement, while occasional brief bursts of theta oscillation were associated with a different order of sequential firing. Our results are the first report of sequential sleep replay in the motor cortex, which may play an important role in consolidation of procedural learning.

Dynamical ventral tegmental area circuit mechanisms of alcohol-dependent dopamine release

A large body of data has identified numerous molecular targets through which ethanol (EtOH) acts on brain circuits. Yet how these multiple mechanisms interact to result in dysregulated dopamine (DA) release under the influence of alcohol in vivo remains unclear. In this manuscript, we delineate potential circuit-level mechanisms responsible for EtOH-dependent dysregulation of DA release from the ventral tegmental area (VTA) into its projection areas. For this purpose, we constructed a circuit model of the VTA that integrates realistic Glutamatergic (Glu) inputs and reproduces DA release observed experimentally. We modelled the concentration-dependent effects of EtOH on its principal VTA targets. We calibrated the model to reproduce the inverted U-shape dose dependence of DA neuron activity on EtOH concentration. The model suggests a primary role of EtOH-induced boost in the I_h and AMPA currents in the DA firing-rate/bursting increase. This is counteracted by potentiated GABA transmission that decreases DA neuron activity at higher EtOH concentrations. Thus, the model connects well-established in vitro pharmacological EtOH targets with its in vivo influence on neuronal activity. Furthermore, we predict that increases in VTA activity produced by moderate EtOH doses require partial synchrony and relatively low rates of the Glu afferents. We propose that the increased frequency of transient (phasic) DA peaks evoked by EtOH results from synchronous population bursts in VTA DA neurons. Our model predicts that the impact of acute ETOH on dopamine release is critically shaped by the structure of the cortical inputs to the VTA.

In vitro characterization of intrinsic properties and local synaptic inputs to pyramidal neurons in macaque primary motor cortex

Primates (including humans) have a highly developed corticospinal tract, and specialized motor cortical areas which differ in key ways from rodents. Much work on motor cortex has therefore used macaque monkeys as a good animal model for human motor control. However, there is a paucity of data describing the fundamental functional architecture of primate primary motor cortex, which is best addressed with in vitro approaches. In this study we examined the cellular properties and the micro-circuitry of the adult macaque primary motor cortex by carrying out in-vitro intracellular recordings. We aimed to characterize the basic properties of the cortical circuitry by studying the intrinsic properties of its pyramidal neurons and their physiological interconnectivity. We studied the passive and active electrophysiological properties of pyramidal neurons in both superficial and deep cortical layers. Both superficial and deep pyramidal neurons exhibited bursting behaviour that could act as powerful excitation for downstream targets. Synaptic connections were lamina specific. Neurons in the deep layers had convergent excitatory inputs from all cortical layers whereas superficial neurons had only significant inputs from superficial layers. This sheds light on the functional architecture of the primate primary motor cortex and how its output is shaped. We also took the unique opportunity in our recording technique to characterize the relationship between intracellular and extracellular spike waveforms, with implications for cell-type identification in studies in awake behaving monkey. Our results will aid the interpretation of primate studies into motor control involving extracellular spike recordings and electrical stimulation in primary motor cortex.

Modeling task-specific neuronal ensembles improves decoding of grasp

OBJECTIVE

Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed.

APPROACH

In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed.

MAIN RESULTS

Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p  <  0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units.

SIGNIFICANCE

These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more reliable and accurate neural prosthesis.

Physiological tremor increases when skeletal muscle is shortened: implications for fusimotor control

KEY POINTS

In tonic, isometric, plantarflexion contractions, physiological tremor increases as the ankle joint becomes plantarflexed. Modulation of physiological tremor as a function of muscle stretch differs from that of the stretch reflex amplitude. Amplitude of physiological tremor may be altered as a function of reflex pathway gains. Healthy humans likely increase their γ-static fusimotor drive when muscles shorten. Quantification of physiological tremor by manipulation of joint angle may be a useful experimental probe of afferent gains and/or the integrity of automatic fusimotor control.

ABSTRACT

The involuntary force fluctuations associated with physiological (as distinct from pathological) tremor are an unavoidable component of human motor control. While the origins of physiological tremor are known to depend on muscle afferentation, it is possible that the mechanical properties of muscle-tendon systems also affect its generation, amplification and maintenance. In this paper, we investigated the dependence of physiological tremor on muscle length in healthy individuals. We measured physiological tremor during tonic, isometric plantarflexion torque at 30% of maximum at three ankle angles. The amplitude of physiological tremor increased as calf muscles shortened in contrast to the stretch reflex whose amplitude decreases as muscle shortens. We used a published closed-loop simulation model of afferented muscle to explore the mechanisms responsible for this behaviour. We demonstrate that changing muscle lengths does not suffice to explain our experimental findings. Rather, the model consistently required the modulation of  γ-static fusimotor drive to produce increases in physiological tremor with muscle shortening - while successfully replicating the concomitant reduction in stretch reflex amplitude. This need to control γ-static fusimotor drive explicitly as a function of muscle length has important implications. First, it permits the amplitudes of physiological tremor and stretch reflex to be decoupled. Second, it postulates neuromechanical interactions that require length-dependent γ drive modulation to be independent from α drive to the parent muscle. Lastly, it suggests that physiological tremor can be used as a simple, non-invasive measure of the afferent mechanisms underlying healthy motor function, and their disruption in neurological conditions.

Frequency and function in the basal ganglia: the origins of beta and gamma band activity

KEY POINTS

Neuronal oscillations in the basal ganglia have been observed to correlate with behaviours, although the causal mechanisms and functional significance of these oscillations remain unknown. We present a novel computational model of the healthy basal ganglia, constrained by single unit recordings from non-human primates. When the model is run using inputs that might be expected during performance of a motor task, the network shows emergent phenomena: it functions as a selection mechanism and shows spectral properties that match those seen in vivo. Beta frequency oscillations are shown to require pallido-striatal feedback, and occur with behaviourally relevant cortical input. Gamma oscillations arise in the subthalamic-globus pallidus feedback loop, and occur during movement. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the basal ganglia and lays the foundation for an integrated approach to study basal ganglia pathologies such as Parkinson's disease in silico.

ABSTRACT

Neural oscillations in the basal ganglia (BG) are well studied yet remain poorly understood. Behavioural correlates of spectral activity are well described, yet a quantitative hypothesis linking time domain dynamics and spectral properties to BG function has been lacking. We show, for the first time, that a unified description is possible by interpreting previously ignored structure in data describing globus pallidus interna responses to cortical stimulation. These data were used to expose a pair of distinctive neuronal responses to the stimulation. This observation formed the basis for a new mathematical model of the BG, quantitatively fitted to the data, which describes the dynamics in the data, and is validated against other stimulus protocol experiments. A key new result is that when the model is run using inputs hypothesised to occur during the performance of a motor task, beta and gamma frequency oscillations emerge naturally during static-force and movement, respectively, consistent with experimental local field potentials. This new model predicts that the pallido-striatum connection has a key role in the generation of beta band activity, and that the gamma band activity associated with motor task performance has its origins in the pallido-subthalamic feedback loop. The network's functionality as a selection mechanism also occurs as an emergent property, and closer fits to the data gave better selection properties. The model provides a coherent framework for the study of spectral, temporal and functional analyses of the BG and therefore lays the foundation for an integrated approach to study BG pathologies such as Parkinson's disease in silico.

Nonlinear Frequency-Domain Analysis of the Transformation of Cortical Inputs by a Motoneuron Pool-Muscle Complex

Corticomotor coherence in the beta and/or gamma bands has been described in different motor tasks, but the role of descending brain oscillations on force control has been elusive. Large-scale computational models of a motoneuron pool and the muscle it innervates have been used as tools to advance the knowledge of how neural elements may influence force control. Here, we present a frequency domain analysis of a NARX model fitted to a large-scale neuromuscular model by the means of generalized frequency response functions (GFRF). The results of such procedures indicated that the computational neuromuscular model was capable of transforming an oscillatory synaptic input (e.g., at 20 Hz) into a constant mean muscle force output. The nonlinearity uncovered by the GFRFs of the NARX model was responsible for the demodulation of an oscillatory input (e.g., a beta band oscillation coming from the brain and forming the input to the motoneuron pool). This suggests a manner by which brain rhythms descending as command signals to the spinal cord and acting on a motoneuron pool can regulate a maintained muscle force. In addition to the scientific aspects of these results, they provide new interpretations that may further neural engineering applications associated with quantitative neurological diagnoses and robotic systems for artificial limbs.

Dissociation between sustained single-neuron spiking and transient β-LFP oscillations in primate motor cortex

Determining the relationship between single-neuron spiking and transient (20 Hz) β-local field potential (β-LFP) oscillations is an important step for understanding the role of these oscillations in motor cortex. We show that whereas motor cortex firing rates and beta spiking rhythmicity remain sustained during steady-state movement preparation periods, β-LFP oscillations emerge, in contrast, as short transient events. Single-neuron mean firing rates within and outside transient β-LFP events showed no differences, and no consistent correlation was found between the beta oscillation amplitude and firing rates, as was the case for movement- and visual cue-related β-LFP suppression. Importantly, well-isolated single units featuring beta-rhythmic spiking (43%, 125/292) showed no apparent or only weak phase coupling with the transient β-LFP oscillations. Similar results were obtained for the population spiking. These findings were common in triple microelectrode array recordings from primary motor (M1), ventral (PMv), and dorsal premotor (PMd) cortices in nonhuman primates during movement preparation. Although beta spiking rhythmicity indicates strong membrane potential fluctuations in the beta band, it does not imply strong phase coupling with β-LFP oscillations. The observed dissociation points to two different sources of variation in motor cortex β-LFPs: one that impacts single-neuron spiking dynamics and another related to the generation of mesoscopic β-LFP signals. Furthermore, our findings indicate that rhythmic spiking and diverse neuronal firing rates, which encode planned actions during movement preparation, may naturally limit the ability of different neuronal populations to strongly phase-couple to a single dominant oscillation frequency, leading to the observed spiking and β-LFP dissociation.NEW & NOTEWORTHY We show that whereas motor cortex spiking rates and beta (~20 Hz) spiking rhythmicity remain sustained during steady-state movement preparation periods, β-local field potential (β-LFP) oscillations emerge, in contrast, as transient events. Furthermore, the β-LFP phase at which neurons spike drifts: phase coupling is typically weak or absent. This dissociation points to two sources of variation in the level of motor cortex beta: one that impacts single-neuron spiking and another related to the generation of measured mesoscopic β-LFPs.

Corticospinal Inputs to Primate Motoneurons Innervating the Forelimb from Two Divisions of Primary Motor Cortex and Area 3a

Previous anatomical work in primates has suggested that only corticospinal axons originating in caudal primary motor cortex ("new M1") and area 3a make monosynaptic cortico-motoneuronal connections with limb motoneurons. By contrast, the more rostral "old M1" is proposed to control motoneurons disynaptically via spinal interneurons. In six macaque monkeys, we examined the effects from focal stimulation within old and new M1 and area 3a on 135 antidromically identified motoneurons projecting to the upper limb. EPSPs with segmental latency shorter than 1.2 ms were classified as definitively monosynaptic; these were seen only after stimulation within new M1 or at the new M1/3a border (incidence 6.6% and 1.3%, respectively; total n = 27). However, most responses had longer latencies. Using measures of the response facilitation after a second stimulus compared with the first, and the reduction in response latency after a third stimulus compared with the first, we classified these late responses as likely mediated by either long-latency monosynaptic (n = 108) or non-monosynaptic linkages (n = 108). Both old and new M1 generated putative long-latency monosynaptic and non-monosynaptic effects; the majority of responses from area 3a were non-monosynaptic. Both types of responses from new M1 had significantly greater amplitude than those from old M1. We suggest that slowly conducting corticospinal fibers from old M1 generate weak late monosynaptic effects in motoneurons. These may represent a stage in control of primate motoneurons by the cortex intermediate between disynaptic output via an interposed interneuron seen in nonprimates and the fast direct monosynaptic connections present in new M1.

SIGNIFICANCE STATEMENT

The corticospinal tract in Old World primates makes monosynaptic connections to motoneurons; previous anatomical work suggests that these connections come only from corticospinal tract (CST) neurons in the subdivision of primary motor cortex within the central sulcus ("new M1") and area 3a. Here, we show using electrophysiology that cortico-motoneuronal connections from fast conducting CST fibers are indeed made exclusively from new M1 and its border with 3a. However, we also show that all parts of M1 and 3a have cortico-motoneuronal connections over more slowly conducting CST axons, as well as exert disynaptic effects on motoneurons via interposed interneurons. Differences between old and new M1 are thus more subtle than previously thought.

Modulation of synchronous sympathetic firing behaviors by endogenous GABA(A) and glycine receptor-mediated activities in the neonatal rat spinal cord in vitro

Delivering effective commands in the nervous systems require a temporal integration of neural activities such as synchronous firing. Although sympathetic nerve discharges are characterized by synchronous firing, its temporal structures and how it is modulated are largely unknown. This study used a collagenase-dissociated splanchnic sympathetic nerve-thoracic spinal cord preparation of neonatal rats in vitro as an experimental model. Several single-fiber activities were recorded simultaneously and verified by rigorous computational algorithms. Among 3763 fiber pairs that had spontaneous fiber activities, 382 fiber pairs had firing positively correlated. Their temporal relationship was quantitatively evaluated by cross-correlogram. On average, correlated firing in a fiber pair occurred in scales of ∼40ms lasting for ∼11ms. The relative frequency distribution curves of correlogram parametrical values pertinent to the temporal features were best described by trimodal Gaussians, suggesting a correlated firing originated from three or less sources. Applications of bicuculline or gabazine (noncompetitive or competitive GABA(A) receptor antagonist) and/or strychnine (noncompetitive glycine receptor antagonist) increased, decreased, or did not change individual fiber activities. Antagonist-induced enhancement and attenuation of correlated firing were demonstrated by a respective increase and decrease of the peak probability of the cross-correlograms. Heterogeneity in antagonistic responses suggests that the inhibitory neurotransmission mediated by GABA(A) and glycine receptors is not essential for but can serve as a neural substrate to modulate synchronous firing behaviors. Plausible neural mechanisms were proposed to explain the temporal structures of correlated firing between sympathetic fibers.

Fast Oscillatory Commands from the Motor Cortex Can Be Decoded by the Spinal Cord for Force Control

Oscillations in the beta and gamma bands (13-30 Hz; 35-70 Hz) have often been observed in motor cortical outputs that reach the spinal cord, acting on motoneurons and interneurons. However, the frequencies of these oscillations are above the muscle force frequency range. A current view is that the transformation of the motoneuron pool inputs into force is linear. For this reason possible roles for these oscillations are unclear, since if this transformation is linear, the high frequencies in the motoneuron inputs (e.g., 20 Hz from pyramidal tract neurons) would be filtered out by the muscle and have no effect on force control. A biologically inspired mathematical model of the neuromuscular system was used to investigate the impact of high-frequency cortical oscillatory activity on force control. The model simulation results evidenced that a typical motoneuron pool has a nonlinear behavior that enables the decoding of a high-frequency oscillatory input. An input at a single frequency (e.g., beta band) leads to an increase in the steady-state force generated by the muscle. When the input oscillation was amplitude modulated at a given low frequency, the force oscillated at this frequency. In both cases, the mechanism relies on the recruitment and derecruitment of motor units in response to the oscillatory descending drive. Therefore, the results from this study suggest a potential role in force control for cortical oscillations at frequencies at or above the beta band, despite the low-pass behavior of the muscles.

SIGNIFICANCE STATEMENT

The role of cortical oscillations in motor control has been a long-standing question, one view being that they are an epiphenomenon. Fast oscillations are known to reach the spinal cord, and hence they have been thought to affect muscle behavior. However, experimental limitations have hampered further advances to explain how they could influence muscle force. An approach for such a challenge was adopted in the present research: to study the problem through computer simulations of an advanced biologically compatible mathematical model. Using such a model, we found that the well-known mechanism of recruitment and derecruitment of the spinal cord motoneurons can allow the muscle to respond to cortical oscillations, suggesting that these oscillations are not epiphenomena in motor control.

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (<100 ms) spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters.

Alpha- and beta-band oscillations subserve different processes in reactive control of limb movements

The capacity to rapidly suppress a behavioral act in response to sudden instruction to stop is a key cognitive function. This function, called reactive control, is tested in experimental settings using the stop signal task, which requires subjects to generate a movement in response to a go signal or suppress it when a stop signal appears. The ability to inhibit this movement fluctuates over time: sometimes, subjects can stop their response, and at other times, they can not. To determine the neural basis of this fluctuation, we recorded local field potentials (LFPs) in the alpha (6–12 Hz) and beta (13–35 Hz) bands from the dorsal premotor cortex of two nonhuman primates that were performing the task. The ability to countermand a movement after a stop signal was predicted by the activity of both bands, each purportedly representing a distinct neural process. The beta band represents the level of movement preparation; higher beta power corresponds to a lower level of movement preparation, whereas the alpha band supports a proper phasic, reactive inhibitory response: movements are inhibited when alpha band power increases immediately after a stop signal. Our findings support the function of LFP bands in generating the signatures of various neural computations that are multiplexed in the brain.

Motor unit firing pattern, synchrony and coherence in a deafferented patient

The firing of spinal motoneurons (MNs) is controlled continuously by inputs from muscle, joint and skin receptors. Besides altering MN synaptic drive, the removal of these inputs is liable to alter the synaptic noise and, thus, the variability of their tonic activity. Sensory afferents, which are a major source of common and/or synchronized inputs shared by several MNs, may also contribute to the coupling in the time and frequency domains (synchrony and coherence, respectively) observed when cross-correlation and coherence analyses are applied to the discharges of MN pairs. Surprisingly, no consistent changes in firing frequency, nor in synchrony and coherence were reported to affect the activity of 3 pairs of motor units (MUs) tested in a case of sensory polyradiculoneuropathy (SPRNP), leading to an irreversible loss of large diameter sensory afferents (Farmer et al., 1993). Such a limited sample, however, precludes a definite conclusion about the actual impact that a chronic loss of muscle and cutaneous afferents may have on the firing properties of human MUs. To address this issue, the firing pattern of 92 MU pairs was analyzed at low contraction force in a case of SPRNP leading similarly to a permanent loss of proprioceptive inputs. Compared with 8 control subjects, MNs in this patient tended to discharge with slightly shorter inter-spike intervals but with greater variability. Synchronous firing tended to occur more frequently with a tighter coupling in the patient. There was no consistent change in coherence in the 15–30 Hz frequency range attributed to the MN corticospinal drive, but a greater coherence was observed below 5 Hz and between 30 and 60 Hz in the patient. The possible origins of the greater irregularity in MN tonic discharges, the tighter coupling of the synchronous firing and the changes in coherence observed in the absence of proprioceptive inputs are discussed.

Information theoretic analysis of proprioceptive encoding during finger flexion in the monkey sensorimotor system

There is considerable debate over whether the brain codes information using neural firing rate or the fine-grained structure of spike timing. We investigated this issue in spike discharge recorded from single units in the sensorimotor cortex, deep cerebellar nuclei, and dorsal root ganglia in macaque monkeys trained to perform a finger flexion task. The task required flexion to four different displacements against two opposing torques; the eight possible conditions were randomly interleaved. We used information theory to assess coding of task condition in spike rate, discharge irregularity, and spectral power in the 15- to 25-Hz band during the period of steady holding. All three measures coded task information in all areas tested. Information coding was most often independent between irregularity and 15-25 Hz power (60% of units), moderately redundant between spike rate and irregularity (56% of units redundant), and highly redundant between spike rate and power (93%). Most simultaneously recorded unit pairs coded using the same measure independently (86%). Knowledge of two measures often provided extra information about task, compared with knowledge of only one alone. We conclude that sensorimotor systems use both rate and temporal codes to represent information about a finger movement task. As well as offering insights into neural coding, this work suggests that incorporating spike irregularity into algorithms used for brain-machine interfaces could improve decoding accuracy.

Spatial computation with gamma oscillations

Gamma oscillations in cortex have been extensively studied with relation to behavior in both humans and animal models; however, their computational role in the processing of behaviorally relevant signals is still not clear. One oft-overlooked characteristic of gamma oscillations is their spatial distribution over the cortical space and the computational consequences of such an organization. Here, we advance the proposal that the spatial organization of gamma oscillations is of major importance for their function. The interaction of specific spatial distributions of oscillations with the functional topography of cortex enables select amplification of neuronal signals, which supports perceptual and cognitive processing.

Markers of criticality in phase synchronization

The concept of the brain as a critical dynamical system is very attractive because systems close to criticality are thought to maximize their dynamic range of information processing and communication. To date, there have been two key experimental observations in support of this hypothesis: (i) neuronal avalanches with power law distribution of size and (ii) long-range temporal correlations (LRTCs) in the amplitude of neural oscillations. The case for how these maximize dynamic range of information processing and communication is still being made and because a significant substrate for information coding and transmission is neural synchrony it is of interest to link synchronization measures with those of criticality. We propose a framework for characterizing criticality in synchronization based on an analysis of the moment-to-moment fluctuations of phase synchrony in terms of the presence of LRTCs. This framework relies on an estimation of the rate of change of phase difference and a set of methods we have developed to detect LRTCs. We test this framework against two classical models of criticality (Ising and Kuramoto) and recently described variants of these models aimed to more closely represent human brain dynamics. From these simulations we determine the parameters at which these systems show evidence of LRTCs in phase synchronization. We demonstrate proof of principle by analysing pairs of human simultaneous EEG and EMG time series, suggesting that LRTCs of corticomuscular phase synchronization can be detected in the resting state and experimentally manipulated. The existence of LRTCs in fluctuations of phase synchronization suggests that these fluctuations are governed by non-local behavior, with all scales contributing to system behavior. This has important implications regarding the conditions under which one should expect to see LRTCs in phase synchronization. Specifically, brain resting states may exhibit LRTCs reflecting a state of readiness facilitating rapid task-dependent shifts toward and away from synchronous states that abolish LRTCs.

Modulation dynamics in the orofacial sensorimotor cortex during motor skill acquisition

The orofacial sensorimotor cortex is known to play a role in motor learning. However, how motor learning changes the dynamics of neuronal activity and whether these changes differ between orofacial primary motor (MIo) and somatosensory (SIo) cortices remain unknown. To address these questions, we used chronically implanted microelectrode arrays to track learning-induced changes in the activity of simultaneously recorded neurons in MIo and SIo as two naive monkeys (Macaca mulatta) were trained in a novel tongue-protrusion task. Over a period of 8-12 d, the monkeys showed behavioral improvements in task performance that were accompanied by rapid and long-lasting changes in neuronal responses in MIo and SIo occurring in parallel: (1) increases in the proportion of task-modulated neurons, (2) increases in the mutual information between tongue-protrusive force and spiking activity, (3) reductions in the across-trial firing rate variability, and (4) transient increases in coherent firing of neuronal pairs. More importantly, the time-resolved mutual information in MIo and SIo exhibited temporal alignment. While showing parallel changes, MIo neurons exhibited a bimodal distribution of peak correlation lag times between spiking activity and force, whereas SIo neurons showed a unimodal distribution. Moreover, coherent activity between pairs of MIo neurons was higher and centered around force onset compared with pairwise coherence of SIo neurons. Overall, the results suggest that the neuroplasticity in MIo and SIo occurring in parallel serves as a substrate for linking sensation and movement during sensorimotor learning, whereas the differing dynamic organizations reflect specific ways to control movement parameters as learning progresses.

Axon diameters and conduction velocities in the macaque pyramidal tract

Small axons far outnumber larger fibers in the corticospinal tract, but the function of these small axons remains poorly understood. This is because they are difficult to identify, and therefore their physiology remains obscure. To assess the extent of the mismatch between anatomic and physiological measures, we compared conduction time and velocity in a large number of macaque corticospinal neurons with the distribution of axon diameters at the level of the medullary pyramid, using both light and electron microscopy. At the electron microscopic level, a total of 4,172 axons were sampled from 2 adult male macaque monkeys. We confirmed that there were virtually no unmyelinated fibers in the pyramidal tract. About 14% of pyramidal tract axons had a diameter smaller than 0.50 μm (including myelin sheath), most of these remaining undetected using light microscopy, and 52% were smaller than 1 μm. In the electrophysiological study, we determined the distribution of antidromic latencies of pyramidal tract neurons, recorded in primary motor cortex, ventral premotor cortex, and supplementary motor area and identified by pyramidal tract stimulation (799 pyramidal tract neurons, 7 adult awake macaques) or orthodromically from corticospinal axons recorded at the mid-cervical spinal level (192 axons, 5 adult anesthetized macaques). The distribution of antidromic and orthodromic latencies of corticospinal neurons was strongly biased toward those with large, fast-conducting axons. Axons smaller than 3 μm and with a conduction velocity below 18 m/s were grossly underrepresented in our electrophysiological recordings, and those below 1 μm (6 m/s) were probably not represented at all. The identity, location, and function of the majority of corticospinal neurons with small, slowly conducting axons remains unknown.

Analog and digital codes in the brain

It has long been debated whether information in the brain is coded at the rate of neuronal spiking or at the precise timing of single spikes. Although this issue is essential to the understanding of neural signal processing, it is not easily resolved because the two mechanisms are not mutually exclusive. We suggest revising this coding issue so that one hypothesis is uniquely selected for a given spike train. To this end, we decide whether the spike train is likely to transmit a continuously varying analog signal or switching between active and inactive states. The coding hypothesis is selected by comparing the likelihood estimates yielded by empirical Bayes and hidden Markov models on individual data. The analysis method is applicable to generic event sequences, such as earthquakes, machine noises, and human communications, and enhances the gain in decoding signals and infers underlying activities.

Motor unit

Movement is accomplished by the controlled activation of motor unit populations. Our understanding of motor unit physiology has been derived from experimental work on the properties of single motor units and from computational studies that have integrated the experimental observations into the function of motor unit populations. The article provides brief descriptions of motor unit anatomy and muscle unit properties, with more substantial reviews of motoneuron properties, motor unit recruitment and rate modulation when humans perform voluntary contractions, and the function of an entire motor unit pool. The article emphasizes the advances in knowledge on the cellular and molecular mechanisms underlying the neuromodulation of motoneuron activity and attempts to explain the discharge characteristics of human motor units in terms of these principles. A major finding from this work has been the critical role of descending pathways from the brainstem in modulating the properties and activity of spinal motoneurons. Progress has been substantial, but significant gaps in knowledge remain.

Motor thalamus integration of cortical, cerebellar and basal ganglia information: implications for normal and parkinsonian conditions

Motor thalamus (Mthal) is implicated in the control of movement because it is strategically located between motor areas of the cerebral cortex and motor-related subcortical structures, such as the cerebellum and basal ganglia (BG). The role of BG and cerebellum in motor control has been extensively studied but how Mthal processes inputs from these two networks is unclear. Specifically, there is considerable debate about the role of BG inputs on Mthal activity. This review summarizes anatomical and physiological knowledge of the Mthal and its afferents and reviews current theories of Mthal function by discussing the impact of cortical, BG and cerebellar inputs on Mthal activity. One view is that Mthal activity in BG and cerebellar-receiving territories is primarily "driven" by glutamatergic inputs from the cortex or cerebellum, respectively, whereas BG inputs are modulatory and do not strongly determine Mthal activity. This theory is steeped in the assumption that the Mthal processes information in the same way as sensory thalamus, through interactions of modulatory inputs with a single driver input. Another view, from BG models, is that BG exert primary control on the BG-receiving Mthal so it effectively relays information from BG to cortex. We propose a new "super-integrator" theory where each Mthal territory processes multiple driver or driver-like inputs (cortex and BG, cortex and cerebellum), which are the result of considerable integrative processing. Thus, BG and cerebellar Mthal territories assimilate motivational and proprioceptive motor information previously integrated in cortico-BG and cortico-cerebellar networks, respectively, to develop sophisticated motor signals that are transmitted in parallel pathways to cortical areas for optimal generation of motor programmes. Finally, we briefly review the pathophysiological changes that occur in the BG in parkinsonism and generate testable hypotheses about how these may affect processing of inputs in the Mthal.

The potential of multilateral analyses of neuronal activities in future brain-machine interface research

Current brain-machine interfaces are based on the implicit assumption that information encoded by neuronal activities does not change despite some recent physiological studies indicating that information encoded by neuronal activities changes. Here, we highlight the necessity for advanced decoding of neuronal activities. Especially, we discuss the advantages of multilateral analyses of neuronal activities, including synchronization and variability.

Common excitatory synaptic inputs to electrically connected cortical fast-spiking cell networks

Cortical fast-spiking (FS) interneurons are electrically interconnected through gap junctions and form dendritic net structures extending over different functional columns. Here we investigated how pyramidal cells regulate FS cell network activity. Using paired recordings and glutamate puff stimulations, we found that FS cell pairs connected by electrical synapses shared common inputs from surrounding pyramidal cells more frequently than those unconnected or connected only by chemical synapses. Experimental and simulation results suggest that activity spread evoked by common inputs to electrically connected FS cells depends on network state. When cells were in the depolarized state, common inputs to electrically connected cells enhanced spike induction and induced inhibitory effects in surrounding FS cells. By contrast, in the hyperpolarized state, either sub- or suprathreshold inputs produced depolarizing potentials in nearby cells. Our results suggest that globally connected FS cell networks are locally regulated by pyramidal cells in an electrical connection- and network state-dependent manner.

Oscillations and the basal ganglia: motor control and beyond

Oscillations form a ubiquitous feature of the central nervous system. Evidence is accruing from cortical and sub-cortical recordings that these rhythms may be functionally important, although the precise details of their roles remain unclear. The basal ganglia share this predilection for rhythmic activity which, as we see in Parkinson's disease, becomes further enhanced in the dopamine depleted state. While certain cortical rhythms appear to penetrate the basal ganglia, others are transformed or blocked. Here, we discuss the functional association of oscillations in the basal ganglia and their relationship with cortical activity. We further explore the neural underpinnings of such oscillatory activity, including the important balance to be struck between facilitating information transmission and limiting information coding capacity. Finally, we introduce the notion that synchronised oscillatory activity can be broadly categorised as immutability promoting rhythms that reinforce incumbent processes, and mutability promoting rhythms that favour novel processing.

On the functional organization and operational principles of the motor cortex

Recent studies on the functional organization and operational principles of the motor cortex (MCx), taken together, strongly support the notion that the MCx controls the muscle synergies subserving movements in an integrated manner. For example, during pointing the shoulder, elbow and wrist muscles appear to be controlled as a coupled functional system, rather than singly and separately. The recurrent pattern of intrinsic synaptic connections between motor cortical points is likely part of the explanation for this operational principle. So too is the reduplicated, non-contiguous and intermingled representation of muscles in the MCx. A key question addressed in this article is whether the selection of movement related muscle synergies is a dynamic process involving the moment to moment functional linking of a variety of motor cortical points, or rather the selection of fixed patterns embedded in the MCx circuitry. It will be suggested that both operational principles are probably involved. We also discuss the neural mechanisms by which cortical points may be dynamically linked to synthesize movement related muscle synergies. Separate corticospinal outputs sum linearly and lead to a blending of the movements evoked by activation of each point on its own. This operational principle may simplify the synthesis of motor commands. We will discuss two possible mechanisms that may explain linear summation of outputs. We have observed that the final posture of the arm when pointing to a given spatial location is relatively independent of its starting posture. From this observation and the recurrent nature of the MCx intrinsic connectivity we hypothesize that the basic mode of operation of the MCx is to associate spatial location to final arm posture. We explain how the recurrent network connectivity operates to generate the muscle activation patterns (synergies) required to move the arm and hold it in its final position.

Six networks on a universal neuromorphic computing substrate

In this study, we present a highly configurable neuromorphic computing substrate and use it for emulating several types of neural networks. At the heart of this system lies a mixed-signal chip, with analog implementations of neurons and synapses and digital transmission of action potentials. Major advantages of this emulation device, which has been explicitly designed as a universal neural network emulator, are its inherent parallelism and high acceleration factor compared to conventional computers. Its configurability allows the realization of almost arbitrary network topologies and the use of widely varied neuronal and synaptic parameters. Fixed-pattern noise inherent to analog circuitry is reduced by calibration routines. An integrated development environment allows neuroscientists to operate the device without any prior knowledge of neuromorphic circuit design. As a showcase for the capabilities of the system, we describe the successful emulation of six different neural networks which cover a broad spectrum of both structure and functionality.

Synchrony and neural coding in cerebellar circuits

The cerebellum regulates complex movements and is also implicated in cognitive tasks, and cerebellar dysfunction is consequently associated not only with movement disorders, but also with conditions like autism and dyslexia. How information is encoded by specific cerebellar firing patterns remains debated, however. A central question is how the cerebellar cortex transmits its integrated output to the cerebellar nuclei via GABAergic synapses from Purkinje neurons. Possible answers come from accumulating evidence that subsets of Purkinje cells synchronize their firing during behaviors that require the cerebellum. Consistent with models predicting that coherent activity of inhibitory networks has the capacity to dictate firing patterns of target neurons, recent experimental work supports the idea that inhibitory synchrony may regulate the response of cerebellar nuclear cells to Purkinje inputs, owing to the interplay between unusually fast inhibitory synaptic responses and high rates of intrinsic activity. Data from multiple laboratories lead to a working hypothesis that synchronous inhibitory input from Purkinje cells can set the timing and rate of action potentials produced by cerebellar nuclear cells, thereby relaying information out of the cerebellum. If so, then changing spatiotemporal patterns of Purkinje activity would allow different subsets of inhibitory neurons to control cerebellar output at different times. Here we explore the evidence for and against the idea that a synchrony code defines, at least in part, the input–output function between the cerebellar cortex and nuclei. We consider the literature on the existence of simple spike synchrony, convergence of Purkinje neurons onto nuclear neurons, and intrinsic properties of nuclear neurons that contribute to responses to inhibition. Finally, we discuss factors that may disrupt or modulate a synchrony code and describe the potential contributions of inhibitory synchrony to other motor circuits.

The activity of primary motor cortex corticospinal neurons during tool use by macaque monkeys

It has been suggested that the distinctive capacity of some nonhuman primates to use tools may reflect a well-developed corticospinal system and, in particular, direct cortico-motoneuronal (CM) connections to hand muscles. We investigated the activity of corticospinal neurons in the primary motor cortex hand area during the use of a tool by two adult macaque monkeys. They used a light rake to retrieve food rewards placed in their extrapersonal space. An analysis of EMG activity showed that the rake task involved a complex interaction of muscles acting on the digits, hand, and arm. Sixty-nine corticospinal neurons were identified antidromically as pyramidal tract neurons (PTNs). When tested on the rake task, most (64 of 69; 93%) showed a significant modulation of their discharge during at least one of three task periods: grasping the rake, projecting it beyond the food reward, and then pulling it back to retrieve the reward. Discharge patterns were heterogeneous, and many PTNs showed significant suppression of discharge during raking. Seventeen of the 69 PTNs recorded during the rake task were further identified as CM cells, exerting clear postspike facilitation on digit muscles, demonstrating that the CM system contributes to the skilled use of tools. We compared the activity of each PTN on the rake task with that during precision grip. Most PTNs (90%) modulated their activity significantly for both tasks, demonstrating that PTNs activated by a task involving fractionated movements of the digits are also recruited during rake use, although there were often contrasting patterns of PTN recruitment and muscle activity for the two tasks.

Neural synchrony within the motor system: what have we learned so far?

Synchronization of neural activity is considered essential for information processing in the nervous system. Both local and inter-regional synchronization are omnipresent in different frequency regimes and relate to a variety of behavioral and cognitive functions. Over the years, many studies have sought to elucidate the question how alpha/mu, beta, and gamma synchronization contribute to motor control. Here, we review these studies with the purpose to delineate what they have added to our understanding of the neural control of movement. We highlight important findings regarding oscillations in primary motor cortex, synchronization between cortex and spinal cord, synchronization between cortical regions, as well as abnormal synchronization patterns in a selection of motor dysfunctions. The interpretation of synchronization patterns benefits from combining results of invasive and non-invasive recordings, different data analysis tools, and modeling work. Importantly, although synchronization is deemed to play a vital role, it is not the only mechanism for neural communication. Spike timing and rate coding act together during motor control and should therefore both be accounted for when interpreting movement-related activity.

Differential modulations of ipsilateral and contralateral beta (de)synchronization during unimanual force production

Unilateral movement is usually accompanied by ipsilateral activity in the primary motor cortex (M1). It is still largely unclear whether this activity reflects interhemispheric 'cross-talk' of contralateral M1 that facilitates movement, or results from processes that inhibit motor output. We investigated the role of beta power in ipsilateral M1 during unimanual force production. Significant ipsilateral beta desynchronization occurred during continuous dynamic but not during static force production. Moreover, event-related time-frequency analysis revealed bilateral desynchronization patterns, whereas post-movement synchronization was confined to the contralateral hemisphere. Our findings indicate that ipsilateral activation is not merely the result of interhemispheric cross-talk but involves additional processes. Given observations of differential blood oxygen level-dependent responses in ipsilateral and contralateral M1, and the correlation between beta desynchronization and the firing rate of pyramidal tract neurons in contralateral M1 during movement, we speculate that beta desynchronization in contra- and ipsilateral M1 arises from distinct neural activation patterns.

Sensitivity of EMG-EMG coherence to detect the common oscillatory drive to hand muscles in young and older adults

Multichannel surface electromyograms (EMGs) were used to examine the sensitivity of EMG-EMG coherence to infer changes in common oscillatory drive to hand muscles in young and older adults. Previous research has shown that measures of coherence calculated from different neurophysiological signals are influenced by the age of the subject, the visual feedback provided to the subject, and the task being performed. The change in the magnitude of EMG-EMG coherence across experimental conditions is often interpreted as a change in the oscillatory drive to motoneuron pools of a pair of muscles. However, signal processing (e.g., full-wave rectification) and electrode location are also reported to influence EMG-EMG coherence, which could decrease the sensitivity of EMG-EMG coherence to infer a change in common oscillatory drive to motoneurons. In this study, multichannel EMGs were used to compare EMG-EMG coherence in young (n = 11) and older (n = 10) adults during index finger abduction and pinch grip tasks performed at 2 and 3.5 N with a low and a high visual feedback gain. We found that, across all conditions, EMG-EMG coherence was influenced by electrode location (P < 0.001) but not by subject age, visual feedback gain, task, or signal processing. These results suggest that EMG-EMG coherence is most sensitive to electrode location. The results are discussed in terms of the potential issues related to inferring a common oscillatory drive to hand muscles with surface EMGs.

Detecting synfire chains in parallel spike data

The synfire chain model of brain organization has received much theoretical attention since its introduction (Abeles, 1982, 1991). However there has been no convincing experimental demonstration of synfire chains due partly to limitations of recording technology but also due to lack of appropriate analytic methods for large scale recordings of parallel spike trains. We have previously published one such method based on intersection of the neural populations active at two different times (Schrader et al., 2008). In the present paper we extend this analysis to deal with higher firing rates and noise levels, and develop two additional tools based on properties of repeating firing patterns. All three measures show characteristic signatures if synfire chains underlie the recorded data. However we demonstrate that the detection of repeating firing patterns alone (as used in several papers) is not enough to infer the presence of synfire chains. Positive results from all three measures are needed.

Asynchronous decoding of finger position and of EMG during precision grip using CM cell activity: application to robot control

Recent brain-machine interfaces (BMI) have demonstrated the use of intracortical signals for the kinematic control of robotic arms. However, for potential restoration of manual dexterity, two issues remain to be addressed: (1) Can hand and digit movements for dexterous manipulation be controlled in a similar way to arm movements? (2) Can the potentially large signal space for decoding of the many degrees of freedom (dof) of hand and digit movements be minimized? The first question addresses BMI control of dexterous prosthetic devices, while the second addresses the problem of whether few, but identified, neurons might provide adequate decoding. Asynchronous decoding of precision grip finger movement kinematics from identified corticomotoneuronal (CM) cell activity was performed with an artificial neural network (ANN). After training over a given session, the ANNs successfully decoded trial-by-trial movement kinematics. Average accuracy over sessions was in the order of 80% and 50% for data sets of two monkeys respectively. Decoding accuracy increased as a function of (1) number of simultaneously recorded CM cells used for prediction, and (2) size of the sliding input window. Subsequently, a robot digit actuated by pneumatic artificial muscles, fed with the predicted trajectory, mimicked the recorded movement offline. Furthermore, CM cell signals were used for decoding of time-varying hand muscle EMG activity. The performance of EMG prediction tended to increase if CM cells that facilitated this particular muscle (compared to CM cells that facilitated other muscles) were used. These results provide evidence that an anthropomorphic robot finger can be controlled offline by spike trains recorded from identified corticospinal neurons. This represents a step towards neuroprosthetic devices for dexterous hand movements.

Synthesizing complex movement fragment representations from motor cortical ensembles

We have previously shown that the responses of primary motor cortical neurons are more accurately predicted if one assumes that individual neurons encode temporally-extensive movement fragments or preferred trajectories instead of static movement parameters (Hatsopoulos et al., 2007). Building on these findings, we examine here how these preferred trajectories can be combined to generate a rich variety of preferred movement trajectories when neurons fire simultaneously. Specifically, we used a generalized linear model to fit each neuron's spike rate to an exponential function of the inner product between the actual movement trajectory and the preferred trajectory; then, assuming conditional independence, when two neurons fire simultaneously their spiking probabilities multiply implying that their preferred trajectories add. We used a similar exponential model to fit the probability of simultaneous firing and found that the majority of neuron pairs did combine their preferred trajectories using a simple additive rule. Moreover, a minority of neuron pairs that engaged in significant synchronization combined their preferred trajectories through a small scaling adjustment to the additive rule in the exponent, while preserving the shape of the predicted trajectory representation from the additive rule. These results suggest that complex movement representations can be synthesized in simultaneously firing neuronal ensembles by adding the trajectory representations of the constituents in the ensemble.

Selective movement preparation is subserved by selective increases in corticomuscular gamma-band coherence

Local groups of neurons engaged in a cognitive task often exhibit rhythmically synchronized activity in the gamma band, a phenomenon that likely enhances their impact on downstream areas. The efficacy of neuronal interactions may be enhanced further by interareal synchronization of these local rhythms, establishing mutually well timed fluctuations in neuronal excitability. This notion suggests that long-range synchronization is enhanced selectively for connections that are behaviorally relevant. We tested this prediction in the human motor system, assessing activity from bilateral motor cortices with magnetoencephalography and corresponding spinal activity through electromyography of bilateral hand muscles. A bimanual isometric wrist extension task engaged the two motor cortices simultaneously into interactions and coherence with their respective corresponding contralateral hand muscles. One of the hands was cued before each trial as the response hand and had to be extended further to report an unpredictable visual go cue. We found that, during the isometric hold phase, corticomuscular coherence was enhanced, spatially selective for the corticospinal connection that was effectuating the subsequent motor response. This effect was spectrally selective in the low gamma-frequency band (40-47 Hz) and was observed in the absence of changes in motor output or changes in local cortical gamma-band synchronization. These findings indicate that, in the anatomical connections between the cortex and the spinal cord, gamma-band synchronization is a mechanism that may facilitate behaviorally relevant interactions between these distant neuronal groups.

Primary motor cortex of the parkinsonian monkey: differential effects on the spontaneous activity of pyramidal tract-type neurons

Dysfunction of primary motor cortex (M1) is thought to contribute to the pathophysiology of parkinsonism. What specific aspects of M1 function are abnormal remains uncertain, however. Moreover, few models consider the possibility that distinct cortical neuron subtypes may be affected differently. Those questions were addressed by studying the resting activity of intratelencephalic-type corticostriatal neurons (CSNs) and distant-projecting lamina 5b pyramidal-tract type neurons (PTNs) in the macaque M1 before and after the induction of parkinsonism by administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Contrary to previous reports, the general population of M1 neurons (i.e., PTNs, CSNs, and unidentified neurons) showed reduced baseline firing rates following MPTP, attributable largely to a marked decrease in PTN firing rates. CSN firing rates were unmodified. Although burstiness and firing patterns remained constant in M1 neurons as a whole and CSNs in particular, PTNs became more bursty post-MPTP and less likely to fire in a regular-spiking pattern. Rhythmic spiking (found in PTNs predominantly) occurred at beta frequencies (14-32 Hz) more frequently following MPTP. These results indicate that MPTP intoxication induced distinct modifications in the activity of different M1 neuronal subtypes. The particular susceptibility of PTNs suggests that PTN dysfunction may be an important contributor to the pathophysiology of parkinsonian motor signs.

Submillisecond firing synchrony between different subtypes of cortical interneurons connected chemically but not electrically

Synchronous firing is commonly observed in the brain, but its underlying mechanisms and neurobiological meaning remain debated. Most commonly, synchrony is attributed either to electrical coupling by gap junctions or to shared excitatory inputs. In the cerebral cortex and hippocampus, fast-spiking (FS) or somatostatin-containing (SOM) inhibitory interneurons are electrically coupled to same-type neighbors, and each subtype-specific network tends to fire in synchrony. Electrical coupling across subtypes is weak or absent, but SOM-FS and FS-FS pairs are often connected by inhibitory synapses. Theoretical studies suggest that purely inhibitory coupling can also promote synchrony; however, this has not been confirmed experimentally. We recorded from 74 pairs of electrically noncoupled layer 4 interneurons in mouse somatosensory cortex in vitro, and found that tonically depolarized FS-FS and SOM-FS pairs connected by unidirectional or bidirectional inhibitory synapses often fired within 1 ms of each other. Using a novel, jitter-based measure of synchrony, we found that synchrony correlated with inhibitory coupling strength. Importantly, synchrony was resistant to ionotropic glutamate receptors antagonists but was strongly reduced when GABA(A) receptors were blocked, confirming that in our experimental system IPSPs were both necessary and sufficient for synchrony. Submillisecond firing lags emerged in a computer simulation of pairs of spiking neurons, in which the only assumed interaction between neurons was by inhibitory synapses. We conclude that cortical interneurons are capable of synchronizing both within and across subtypes, and that submillisecond coordination of firing can arise by mutual synaptic inhibition alone, with neither shared inputs nor electrical coupling.

High-frequency EEG covaries with spike burst patterns detected in cortical neurons

Invasive microelectrode recordings measure neuronal spikes, which are commonly considered inaccessible through standard surface electroencephalogram (EEG). Yet high-frequency EEG potentials (hf-EEG, f > 400 Hz) found in somatosensory evoked potentials of primates may reflect the mean population spike responses of coactivated cortical neurons. Since cortical responses to electrical nerve stimulation vary strongly from trial to trial, we investigated whether the hf-EEG signal can also echo single-trial variability observed at the single-unit level. We recorded extracellular single-unit activity in the primary somatosensory cortex of behaving macaque monkeys and identified variable spike burst responses following peripheral stimulation. Each of these responses was classified according to the timing of its spike constituents, conforming to one of a discrete set of spike patterns. We here show that these spike patterns are accompanied by variations in the concomitant epidural hf-EEG. These variations cannot be explained by fluctuating stimulus efficacy, suggesting that they were generated within the thalamocortical network. As high-frequency EEG signals can also be reliably recorded from the scalp of human subjects, they may provide a noninvasive window on fluctuating cortical spike activity in humans.