Intramuscular coherence enables robust assessment of modulated supra-spinal input in human gait: an inter-dependence study of visual task and walking speed.

Intramuscular high-frequency coherence is increased during visually guided treadmill walking as a consequence of increased supra-spinal input. The influence of walking speed on intramuscular coherence and its inter-trial reproducibility need to be established before adoption as a functional gait assessment tool in clinical settings. Here, fifteen healthy controls performed a normal and a target walking task on a treadmill at various speeds (0.3 m/s, 0.5 m/s, 0.9 m/s, and preferred) during two sessions. Intramuscular coherence was calculated between two surface EMG recordings sites of the Tibialis anterior muscle during the swing phase of walking. The results were averaged across low-frequency (5-14 Hz) and high-frequency (15-55 Hz) bands. The effect of speed, task, and time on mean coherence was assessed using three-way repeated measures ANOVA. Reliability and agreement were calculated with the intra-class correlation coefficient and Bland-Altman method, respectively. Intramuscular coherence during target walking was significantly higher than during normal walking across all walking speeds in the high-frequency band as obtained by the three-way repeated measures ANOVA. Interaction effects between task and speed were found for the low- and high-frequency bands, suggesting that task-dependent differences increase at higher walking speeds. Reliability of intramuscular coherence was moderate to excellent for most normal and target walking tasks in all frequency bands. This study confirms previous reports of increased intramuscular coherence during target walking, while providing first evidence for reproducibility and robustness of this measure as a requirement to investigate supra-spinal input.Trial registration Registry number/ClinicalTrials.gov Identifier: NCT03343132, date of registration 2017/11/17.

Mind your step: Target walking task reveals gait disturbance in individuals with incomplete spinal cord injury.

BACKGROUND: Walking over obstacles requires precise foot placement while maintaining balance control of the center of mass (CoM) and the flexibility to adapt the gait patterns. Most individuals with incomplete spinal cord injury (iSCI) are capable of overground walking on level ground; however, gait stability and adaptation may be compromised. CoM control was investigated during a challenging target walking (TW) task in individuals with iSCI compared to healthy controls. The hypothesis was that individuals with iSCI, when challenged with TW, show a lack of gait pattern adaptability which is reflected by an impaired adaptation of CoM movement compared to healthy controls. METHODS: A single-center controlled diagnostic clinical trial with thirteen participants with iSCI (0.3-24 years post injury; one subacute and twelve chronic) and twelve healthy controls was conducted where foot and pelvis kinematics were acquired during two conditions: normal treadmill walking (NW) and visually guided target walking (TW) with handrail support, during which participants stepped onto projected virtual targets synchronized with the moving treadmill surface. Approximated CoM was calculated from pelvis markers and used to calculate CoM trajectory length and mean CoM Euclidean distance TW-NW (primary outcome). Nonparametric statistics, including spearman rank correlations, were performed to evaluate the relationship between clinical parameter, outdoor mobility score, performance, and CoM parameters (secondary outcome). RESULTS: Healthy controls adapted to TW by decreasing anterior-posterior and vertical CoM trajectory length (p < 0.001), whereas participants with iSCI reduced CoM trajectory length only in the vertical direction (p = 0.002). Mean CoM Euclidean distance TW-NW correlated with participants' neurological level of injury (R = 0.76, p = 0.002) and CoM trajectory length (during TW) correlated with outdoor mobility score (R = - 0.64, p = 0.026). CONCLUSIONS: This study demonstrated that reduction of CoM movement is a common strategy to cope with TW challenge in controls, but it is impaired in individuals with iSCI. In the iSCI group, the ability to cope with gait challenges worsened the more rostral the level of injury. Thus, the TW task could be used as a gait challenge paradigm in ambulatory iSCI individuals. Trial registration Registry number/ ClinicalTrials.gov Identifier: NCT03343132, date of registration 2017/11/17.

Intermuscular coherence analysis in older adults reveals that gait-related arm swing drives lower limb muscles via subcortical and cortical pathways.

KEY POINTS: Gait-related arm swing in humans supports efficient lower limb muscle activation, indicating a neural coupling between the upper and lower limbs during gait. Intermuscular coherence analyses of gait-related electromyography from upper and lower limbs in 20 healthy participants identified significant coherence in alpha and beta/gamma bands indicating that upper and lower limbs share common subcortical and cortical drivers that coordinate the rhythmic four-limb gait pattern. Additional directed connectivity analyses revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. The results provide a neural underpinning that arm swing may serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases. ABSTRACT: Human gait benefits from arm swing, as it enhances efficient lower limb muscle activation in healthy participants as well as patients suffering from neurological impairment. The underlying neuronal mechanisms of such coupling between upper and lower limbs remain poorly understood. The aim of the present study was to examine this coupling by intermuscular coherence analysis during gait. Additionally, directed connectivity analysis of this coupling enabled assessment of whether gait-related arm swing indeed drives lower limb muscles. To that end, electromyography recordings were obtained from four lower limb muscles and two upper limb muscles bilaterally, during gait, of 20 healthy participants (mean (SD) age 67 (6.8) years). Intermuscular coherence analysis revealed functional coupling between upper and lower limb muscles in the alpha and beta/gamma band during muscle specific periods of the gait cycle. These effects in the alpha and beta/gamma bands indicate involvement of subcortical and cortical sources, respectively, that commonly drive the rhythmic four-limb gait pattern in an efficiently coordinated fashion. Directed connectivity analysis revealed that upper limb muscles drive and shape lower limb muscle activity during gait via subcortical and cortical pathways and to a lesser extent vice versa. This indicates that gait-related arm swing reflects the recruitment of neuronal support for optimizing the cyclic movement pattern of the lower limbs. These findings thus provide a neural underpinning for arm swing to potentially serve as an effective rehabilitation therapy concerning impaired gait in neurological diseases.

Measuring directed functional connectivity using non-parametric directionality analysis: Validation and comparison with non-parametric Granger Causality.

BACKGROUND: 'Non-parametric directionality' (NPD) is a novel method for estimation of directed functional connectivity (dFC) in neural data. The method has previously been verified in its ability to recover causal interactions in simulated spiking networks in Halliday et al. (2015). METHODS: This work presents a validation of NPD in continuous neural recordings (e.g. local field potentials). Specifically, we use autoregressive models to simulate time delayed correlations between neural signals. We then test for the accurate recovery of networks in the face of several confounds typically encountered in empirical data. We examine the effects of NPD under varying: a) signal-to-noise ratios, b) asymmetries in signal strength, c) instantaneous mixing, d) common drive, e) data length, and f) parallel/convergent signal routing. We also apply NPD to data from a patient who underwent simultaneous magnetoencephalography and deep brain recording. RESULTS: We demonstrate that NPD can accurately recover directed functional connectivity from simulations with known patterns of connectivity. The performance of the NPD measure is compared with non-parametric estimators of Granger causality (NPG), a well-established methodology for model-free estimation of dFC. A series of simulations investigating synthetically imposed confounds demonstrate that NPD provides estimates of connectivity that are equivalent to NPG, albeit with an increased sensitivity to data length. However, we provide evidence that: i) NPD is less sensitive than NPG to degradation by noise; ii) NPD is more robust to the generation of false positive identification of connectivity resulting from SNR asymmetries; iii) NPD is more robust to corruption via moderate amounts of instantaneous signal mixing. CONCLUSIONS: The results in this paper highlight that to be practically applied to neural data, connectivity metrics should not only be accurate in their recovery of causal networks but also resistant to the confounding effects often encountered in experimental recordings of multimodal data. Taken together, these findings position NPD at the state-of-the-art with respect to the estimation of directed functional connectivity in neuroimaging.

The development of functional and directed corticomuscular connectivity during tonic ankle muscle contraction across childhood and adolescence.

In adults, oscillatory activity in the sensorimotor cortex is coherent with contralateral muscle activity at beta frequencies (15-35 Hz) during tonic contraction. This functional coupling reflects the involvement of the sensorimotor cortex, the corticospinal pathway, and likely also ascending sensory feedback in the task at hand. However, little is known about the developmental trajectory of task-related corticomuscular connectivity relating to the voluntary control of the ankle muscles. To address this, we recorded electroencephalography (EEG) from the vertex (Cz) and electromyography (EMG) from ankle muscles (proximal and distal anterior tibial, TA; soleus, SOL; gastrocnemius medialis, GM) in 33 participants aged 7-23 yr during tonic dorsi- and plantar flexion requiring precise maintenance of a submaximal torque level. Coherence was calculated for Cz-TA, Cz-SOL, TA-TA, and SOL-GM signal pairs. We found strong, positive associations between age and beta band coherence for Cz-TA, Cz-SOL, and TA-TA, suggesting that oscillatory corticomuscular connectivity is strengthened during childhood development and adolescence. Directionality analysis indicated that the primary interaction underlying this age-related increase was in the descending direction. In addition, performance during dorsi- and plantar flexion tasks was positively associated with age, indicating more precise control of the ankle joint in older participants. Performance was also positively associated with beta band coherence, suggesting that participants with greater coherence also exhibited greater precision. We propose that these results indicate an age-related increase in oscillatory corticospinal input to the ankle muscle motoneuron pools during childhood development and adolescence, with possible implications for maturation of precision force control. Within the theoretical framework of predictive coding, we suggest that our results may reflect an age-related increase in reliance on feedforward control as the developing nervous system becomes better at predicting the sensory consequences of movement. These findings may contribute to the development of novel intervention strategies targeting improved sensorimotor control in children and adolescents with central motor disorders.

Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat.

Much of the motor impairment associated with Parkinson's disease is thought to arise from pathological activity in the networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in parkinsonism, we investigated changes to the directed connectivity in BG networks following dopamine depletion. We recorded local field potentials (LFPs) in the cortex and basal ganglia of rats rendered parkinsonian by injection of 6-hydroxydopamine (6-OHDA) and in dopamine-intact controls. We performed systematic analyses of the networks using a novel tool for estimation of directed interactions (nonparametric directionality, NPD). We used a "conditioned" version of the NPD analysis that reveals the dependence of the correlation between two signals on a third reference signal. We find evidence of the dopamine dependency of both low-beta (14-20 Hz) and high-beta/low-gamma (20-40 Hz) directed network interactions. Notably, 6-OHDA lesions were associated with enhancement of the cortical "hyperdirect" connection to the subthalamic nucleus (STN) and its feedback to the cortex and striatum. We find that pathological beta synchronization resulting from 6-OHDA lesioning is widely distributed across the network and cannot be located to any individual structure. Furthermore, we provide evidence that high-beta/gamma oscillations propagate through the striatum in a pathway that is independent of STN. Rhythms at high beta/gamma show susceptibility to conditioning that indicates a hierarchical organization compared with those at low beta. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in parkinsonism. NEW & NOTEWORTHY We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson's disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a "short-circuiting" of the network that gives rise to the conditions from which pathological synchronization may arise.

Sex differences in learned fear expression and extinction involve altered gamma oscillations in medial prefrontal cortex.

Sex differences in learned fear expression and extinction involve the medial prefrontal cortex (mPFC). We recently demonstrated that enhanced learned fear expression during auditory fear extinction and its recall is linked to persistent theta activation in the prelimbic (PL) but not infralimbic (IL) cortex of female rats. Emerging evidence indicates that gamma oscillations in mPFC are also implicated in the expression and extinction of learned fear. Therefore we re-examined our in vivo electrophysiology data and found that females showed persistent PL gamma activation during extinction and a failure of IL gamma activation during extinction recall. Altered prefrontal gamma oscillations thus accompany sex differences in learned fear expression and its extinction. These findings are relevant for understanding the neural basis of post-traumatic stress disorder, which is more prevalent in women and involves impaired extinction and mPFC dysfunction.

Nonparametric directionality measures for time series and point process data.

The need to determine the directionality of interactions between neural signals is a key requirement for analysis of multichannel recordings. Approaches most commonly used are parametric, typically relying on autoregressive models. A number of concerns have been expressed regarding parametric approaches, thus there is a need to consider alternatives. We present an alternative nonparametric approach for construction of directionality measures for bivariate random processes. The method combines time and frequency domain representations of bivariate data to decompose the correlation by direction. Our framework generates two sets of complementary measures, a set of scalar measures, which decompose the total product moment correlation coefficient summatively into three terms by direction and a set of functions which decompose the coherence summatively at each frequency into three terms by direction: forward direction, reverse direction and instantaneous interaction. It can be undertaken as an addition to a standard bivariate spectral and coherence analysis, and applied to either time series or point-process (spike train) data or mixtures of the two (hybrid data). In this paper, we demonstrate application to spike train data using simulated cortical neurone networks and application to experimental data from isolated muscle spindle sensory endings subject to random efferent stimulation.

Persistent prelimbic cortex activity contributes to enhanced learned fear expression in females.

Anxiety disorders, such as post-traumatic stress, are more prevalent in women and are characterized by impaired inhibition of learned fear and medial prefrontal cortex (mPFC) dysfunction. Here we examined sex differences in fear extinction and mPFC activity in rats. Females showed more learned fear expression during extinction and its recall, but not fear conditioning. They also showed more spontaneous fear recovery and more contextual fear before extinction and its recall. Moreover, enhanced learned fear expression in females was associated with sustained prelimbic (PL) cortex activity. These results suggest that sex differences in learned fear expression may involve persistent PL activation.

Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band.

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15-32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

Dopamine D1-like receptors modulate synchronized oscillations in the hippocampal-prefrontal-amygdala circuit in contextual fear.

Contextual fear conditioning (CFC) is mediated by a neural circuit that includes the hippocampus, prefrontal cortex, and amygdala, but the neurophysiological mechanisms underlying the regulation of CFC by neuromodulators remain unclear. Dopamine D1-like receptors (D1Rs) in this circuit regulate CFC and local synaptic plasticity, which is facilitated by synchronized oscillations between these areas. In rats, we determined the effects of systemic D1R blockade on CFC and oscillatory synchrony between dorsal hippocampus (DH), prelimbic (PL) cortex, basolateral amygdala (BLA), and ventral hippocampus (VH), which sends hippocampal projections to PL and BLA. D1R blockade altered DH-VH and reduced VH-PL and VH-BLA synchrony during CFC, as inferred from theta and gamma coherence and theta-gamma coupling. D1R blockade also impaired CFC, as indicated by decreased freezing at retrieval, which was characterized by altered DH-VH and reduced VH-PL, VH-BLA, and PL-BLA synchrony. This reduction in VH-PL-BLA synchrony was not fully accounted for by non-specific locomotor effects, as revealed by comparing between epochs of movement and freezing in the controls. These results suggest that D1Rs regulate CFC by modulating synchronized oscillations within the hippocampus-prefrontal-amygdala circuit. They also add to growing evidence indicating that this circuit synchrony at retrieval reflects a neural signature of learned fear.

Time-dependent directional intermuscular coherence analysis reveals that forward and backward arm swing equally drive the upper leg muscles during gait initiation.

BACKGROUND: Human bipedal gait benefits from arm swing, as it drives and shapes lower limb muscle activity in healthy participants as well as patients suffering from neurological impairment. Also during gait initiation, arm swing instructions were found to facilitate leg muscle recruitment. RESEARCH QUESTION: The aim of the present study is to exploit the directional decomposition of coherence to examine to what extent forward and backward arm swing contribute to leg muscle recruitment during gait initiation. METHODS: Ambulant electromyography (EMG) from shoulder muscles (deltoideus anterior and posterior) and upper leg muscles (biceps femoris and rectus femoris) was analysed during gait initiation in nineteen healthy participants (median age of 67 ± 12 (IQR) years). To assess to what extent either deltoideus anterior or posterior muscles were able to drive upper leg muscle activity during distinct stages of the gait initiation process, time dependent intermuscular coherence was decomposed into directional components based on their time lag (i.e. forward, reverse and zero-lag). RESULTS: Coherence from the forward directed components, representing shoulder muscle signals leading leg muscle signals, revealed that deltoideus anterior (i.e. forward arm swing) and deltoideus posterior (i.e. backward arm swing) equally drive upper leg muscle activity during the gait initiation process. SIGNIFICANCE: The presently demonstrated time dependent directional intermuscular coherence analysis could be of use for future studies examining directional coupling between muscles or brain areas relative to certain gait (or other time) events. In the present study, this analysis provided neural underpinning that both forward and backward arm swing can provide neuronal support for leg muscle recruitment during gait initiation and can therefore both serve as an effective gait rehabilitation method in patients with gait initiation difficulties.

Intramuscular coherence during challenging walking in incomplete spinal cord injury: Reduced high-frequency coherence reflects impaired supra-spinal control.

Individuals regaining reliable day-to-day walking function after incomplete spinal cord injury (iSCI) report persisting unsteadiness when confronted with walking challenges. However, quantifiable measures of walking capacity lack the sensitivity to reveal underlying impairments of supra-spinal locomotor control. This study investigates the relationship between intramuscular coherence and corticospinal dynamic balance control during a visually guided Target walking treadmill task. In thirteen individuals with iSCI and 24 controls, intramuscular coherence and cumulant densities were estimated from pairs of Tibialis anterior surface EMG recordings during normal treadmill walking and a Target walking task. The approximate center of mass was calculated from pelvis markers. Spearman rank correlations were performed to evaluate the relationship between intramuscular coherence, clinical parameters, and center of mass parameters. In controls, we found that the Target walking task results in increased high-frequency (21-44 Hz) intramuscular coherence, which negatively related to changes in the center of mass movement, whereas this modulation was largely reduced in individuals with iSCI. The impaired modulation of high-frequency intramuscular coherence during the Target walking task correlated with neurophysiological and functional readouts, such as motor-evoked potential amplitude and outdoor mobility score, as well as center of mass trajectory length. The Target walking effect, the difference between Target and Normal walking intramuscular coherence, was significantly higher in controls than in individuals with iSCI [F(1.0,35.0) = 13.042, p < 0.001]. Intramuscular coherence obtained during challenging walking in individuals with iSCI may provide information on corticospinal gait control. The relationships between biomechanics, clinical scores, and neurophysiology suggest that intramuscular coherence assessed during challenging tasks may be meaningful for understanding impaired supra-spinal control in individuals with iSCI.

Evolution of cartesian genetic programs for development of learning neural architecture.

Although artificial neural networks have taken their inspiration from natural neurological systems, they have largely ignored the genetic basis of neural functions. Indeed, evolutionary approaches have mainly assumed that neural learning is associated with the adjustment of synaptic weights. The goal of this paper is to use evolutionary approaches to find suitable computational functions that are analogous to natural sub-components of biological neurons and demonstrate that intelligent behavior can be produced as a result of this additional biological plausibility. Our model allows neurons, dendrites, and axon branches to grow or die so that synaptic morphology can change and affect information processing while solving a computational problem. The compartmental model of a neuron consists of a collection of seven chromosomes encoding distinct computational functions inside the neuron. Since the equivalent computational functions of neural components are very complex and in some cases unknown, we have used a form of genetic programming known as Cartesian genetic programming (CGP) to obtain these functions. We start with a small random network of soma, dendrites, and neurites that develops during problem solving by repeatedly executing the seven chromosomal programs that have been found by evolution. We have evaluated the learning potential of this system in the context of a well-known single agent learning problem, known as Wumpus World. We also examined the harder problem of learning in a competitive environment for two antagonistic agents, in which both agents are controlled by independent CGP computational networks (CGPCN). Our results show that the agents exhibit interesting learning capabilities.

Improved functional connectivity network estimation for brain networks using multivariate partial coherence.

OBJECTIVE: Graphical networks and network metrics are widely used to understand and characterise brain networks and brain function. These methods can be applied to a range of electrophysiological data including electroencephalography, local field potential and single unit recordings. Functional networks are often constructed using pair-wise correlation between variables. The objective of this study is to demonstrate that functional networks can be more accurately estimated using partial correlation than with pair-wise correlation. APPROACH: We compared network metrics derived from unconditional and conditional graphical networks, obtained using coherence and multivariate partial coherence (MVPC), respectively. Graphical networks were constructed using coherence and MVPC estimates, and binary and weighted network metrics derived from these: node degree, path length, clustering coefficients and small-world index. MAIN RESULTS: Network metrics were applied to simulated and experimental single unit spike train data. Simulated data used a 10x10 grid of simulated cortical neurons with centre-surround connectivity. Conditional network metrics gave a more accurate representation of the known connectivity: Numbers of excitatory connections had range 3-11, unconditional binary node degree had range 6-80, conditional node degree had range 2-13. Experimental data used multi-electrode array recording with 19 single-units from left and right hippocampal brain areas in a rat model for epilepsy. Conditional network analysis showed similar trends to simulated data, with lower binary node degree and longer binary path lengths compared to unconditional networks. SIGNIFICANCE: We conclude that conditional networks, where common dependencies are removed through partial coherence analysis, give a more accurate representation of the interactions in a graphical network model. These results have important implications for graphical network analyses of brain networks and suggest that functional networks should be derived using partial correlation, based on MVPC estimates, as opposed to the common approach of pair-wise correlation.

Sex differences in auditory fear discrimination are associated with altered medial prefrontal cortex function.

The increased prevalence of post-traumatic stress disorder (PTSD) that is observed in women may involve sex differences in learned fear inhibition and medial prefrontal cortex (mPFC) function. PTSD is characterized by fear overgeneralization involving impaired fear regulation by safety signals. We recently found that males show fear discrimination and females show fear generalization involving reduced safety signalling after extended fear discrimination training. Here we determined if these sex differences involve altered mPFC function. Male and female rats underwent three days of auditory fear discrimination training, where one tone (CS+) was paired with footshock and another tone (CS-) was presented alone. Local field potentials were recorded from prelimbic (PL) and infralimbic (IL) mPFC during retrieval. We found that males discriminated and females generalized based on cue-induced freezing at retrieval. This was accompanied by sex differences in basal theta and gamma oscillations in PL and IL. Importantly, males also showed PL/IL theta activation during safety signalling by the CS- and IL gamma activation in response to the threat-related CS+, both of which were absent in females. These results add to growing evidence indicating that sex differences in learned fear inhibition are associated with altered mPFC function.

Optimal spectral tracking--with application to speed dependent neural modulation of tibialis anterior during human treadmill walking.

A novel method of optimal spectral tracking is presented which permits the characterisation of trial-varying parameters. Many experimental studies suffer from the limitations of available analysis methodologies, which often impose a condition of stationarity. This severely limits our ability to track slow varying or dynamic responses with any statistical certainty. Presented is a complete framework for the non-stationary analysis of trial-varying data. Theory is introduced and developed in the characterisation of speed dependent neural modulation of the locomotor drive to tibialis anterior (TA) during healthy treadmill locomotion. The approach adopts adaptive filter theory while retaining a spectral focus, thus remaining compatible with much of the current literature. Spectral tracking procedures are evaluated using both surrogate and neurophysiological time-series. Confidence intervals are derived in both empiric and numerical form. Analysis of the pre-synaptic drive to TA under the modulation of treadmill belt speed follows, with results demonstrating clear speed dependent influences on the spectral content of TA, suggesting dynamic neural modulation of the locomotor drive. Findings include speed-modulated components at 7-12Hz (early swing) and 15-20Hz (pre-stance). Speed invariant components were identified at 8-15 and 15-20Hz during early and late swing, in agreement with previous studies. Modification to the method permits a sub-optimal alternative, encouraging the exploration of short epoched data.

Using Corticomuscular and Intermuscular Coherence to Assess Cortical Contribution to Ankle Plantar Flexor Activity During Gait.

The present study used coherence and directionality analyses to explore whether the motor cortex contributes to plantar flexor muscle activity during the stance phase and push-off phase during gait. Subjects walked on a treadmill, while EEG over the leg motorcortex area and EMG from the medial gastrocnemius and soleus muscles was recorded. Corticomuscular and intermuscular coherence were calculated from pair-wise recordings. Significant EEG-EMG and EMG-EMG coherence in the beta and gamma frequency bands was found throughout the stance phase with the largest coherence towards push-off. Analysis of directionality revealed that EEG activity preceded EMG activity throughout the stance phase until the time of push-off. These findings suggest that the motor cortex contributes to ankle plantar flexor muscle activity and forward propulsion during gait.

Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network.

It is now known that astrocytes modulate the activity at the tripartite synapses where indirect signaling via the retrograde messengers, endocannabinoids, leads to a localized self-repairing capability. In this paper, a self-repairing spiking astrocyte neural network (SANN) is proposed to demonstrate a distributed self-repairing capability at the network level. The SANN uses a novel learning rule that combines the spike-timing-dependent plasticity (STDP) and Bienenstock, Cooper, and Munro (BCM) learning rules (hereafter referred to as the BSTDP rule). In this learning rule, the synaptic weight potentiation is not only driven by the temporal difference between the presynaptic and postsynaptic neuron firing times but also by the postsynaptic neuron activity. We will show in this paper that the BSTDP modulates the height of the plasticity window to establish an input-output mapping (in the learning phase) and also maintains this mapping (via self-repair) if synaptic pathways become dysfunctional. It is the functional dependence of postsynaptic neuron firing activity on the height of the plasticity window that underpins how the proposed SANN self-repairs on the fly. The SANN also uses the coupling between the tripartite synapses and γ -GABAergic interneurons. This interaction gives rise to a presynaptic neuron frequency filtering capability that serves to route information, represented as spike trains, to different neurons in the subsequent layers of the SANN. The proposed SANN follows a feedforward architecture with multiple interneuron pathways and astrocytes modulate synaptic activity at the hidden and output neuronal layers. The self-repairing capability will be demonstrated in a robotic obstacle avoidance application, and the simulation results will show that the SANN can maintain learned maneuvers at synaptic fault densities of up to 80% regardless of the fault locations.