The motor cortex drives the muscles during walking in human subjects.

Indirect evidence that the motor cortex and the corticospinal tract contribute to the control of walking in human subjects has been provided in previous studies. In the present study we used coherence analysis of the coupling between EEG and EMG from active leg muscles during human walking to address if activity arising in the motor cortex contributes to the muscle activity during gait. Nine healthy human subjects walked on a treadmill at a speed of 3.5­4 km h(-1). Seven of the subjects in addition walked at a speed of 1 km h(-1). Significant coupling between EEG recordings over the leg motor area and EMG from the anterior tibial muscle was found in the frequency band 24­40 Hz prior to heel strike during the swing phase of walking. This signifies that rhythmic cortical activity in the 24­40 Hz frequency band is transmitted via the corticospinal tract to the active muscles during walking. These findings demonstrate that the motor cortex and corticospinal tract contribute directly to the muscle activity observed in steady-state treadmill walking.

Kinematic modelling of a robotic gait device for early rehabilitation of walking.

Rehabilitation of walking is an essential element in the treatment of incomplete spinal cord injured (SCI) patients. During the early post injury period, patients find it challenging to practice upright walking. Simulating stepping movements in a supine posture may be easier and promote earlier rehabilitation. A robotic orthotic device for early intervention in spinal cord injury that does not require the patient to be in an upright posture has been modelled. The model comprises a two-bar mechanical system that is configured and powered to provide limb kinematics that approximate normal overground walking. The modelling work has been based on gait analysis performed on healthy subjects walking at 50 per cent, 75 per cent, and 100 per cent of normal cadence. Simulated angles of hip, knee, and ankle joints show a comparable range of motion (ROM) to the experimental walking data measured in healthy subjects. The model provides operating parameters for a prospective recumbent gait orthosis that could be used in early walking rehabilitation of incomplete SCI patients.

Enhancement of a virtual reality wheelchair simulator to include qualitative and quantitative performance metrics.

The increasing importance of inclusive design and in particular accessibility guidelines established in the U.K. 1996 Disability Discrimination Act (DDA) has been a prime motivation for the work on wheelchair access, a subset of the DDA guidelines, described in this article. The development of these guidelines mirrors the long-standing provisions developed in the U.S. In order to raise awareness of these guidelines and in particular to give architects, building designers, and users a physical sensation of how a planned development could be experienced, a wheelchair virtual reality system was developed. This compares with conventional methods of measuring against drawings and comparing dimensions against building regulations, established in the U.K. under British standards. Features of this approach include the marriage of an electromechanical force-feedback system with high-quality immersive graphics as well as the potential ability to generate a physiological rating of buildings that do not yet exist. The provision of this sense of "feel" augments immersion within the virtual reality environment and also provides the basis from which both qualitative and quantitative measures of a building's access performance can be gained.

Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% { 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1 - 250 spikes/sec). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multi electrode array data is briefly discussed.

Evaluation of Different Signal Processing Methods in Time and Frequency Domain for Brain-Computer Interface Applications.

Brain-computer interface (BCI) has been widely introduced in many medical applications. One of the main challenges in BCI is to run the signal processing algorithms in real-time which is challenging and usually comes with high processing unit costs. BCIs based on motor imagery task are introduced for severe neurological diseases especially locked-in patients. A common concept is to detect one's movement intention and use it to control external devices such as wheelchair or rehabilitation devices. In real-time BCI, running the signal processing algorithms might not always be possible due to the complexity of the algorithms. Moreover, the speed of the affordable computational units is not usually enough for those applications. This study evaluated a range of feature extraction methods which are commonly used for such real-time BCI applications. Electroencephalogram (EEG) and Electrooculogram (EOG) data available through IEEE Brain Initiative repository was used to investigate the performance of different feature extraction methods including template matching, statistical moments, selective bandpower, and fast Fourier transform (FFT) power spectrum. The support vector machine (SVM) was used for classification. The result indicates that there is not a significant difference when utilizing different feature extraction methods in terms of movement prediction although there is a vast difference in the computational time needed to extract these features. The results suggest that computational time could be considered as the primary parameter when choosing the feature extraction methods as there is no significant difference between the results when different features extraction methods are used.

Neural spike train synchronization indices: definitions, interpretations, and applications.

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second-order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second-order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% to 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1-250 spikes/s). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multielectrode array data is briefly discussed.

Muscle co-activity tuning in Parkinsonian hand movement: disease-specific changes at behavioral and cerebral level.

We investigated simple directional hand movements based on different degrees of muscle co-activity, at behavioral and cerebral level in healthy subjects and Parkinson's disease (PD) patients. We compared "singular" movements, dominated by the activity of one agonist muscle, to "composite" movements, requiring conjoint activity of multiple muscles, in a center-out (right hand) step-tracking task. Behavioral parameters were obtained by EMG and kinematic recordings. fMRI was used to investigate differences in underlying brain activations between PD patients (N = 12) and healthy (age-matched) subjects (N = 18). In healthy subjects, composite movements recruited the striatum and cortical areas comprising bilaterally the supplementary motor area and premotor cortex, contralateral medial prefrontal cortex, primary motor cortex, primary visual cortex, and ipsilateral superior parietal cortex. Contrarily, the ipsilateral cerebellum was more involved in singular movements. This striking dichotomy between striatal and cortical recruitment vs. cerebellar involvement was considered to reflect the complementary roles of these areas in motor control, in which the basal ganglia are involved in movement selection and the cerebellum in movement optimization. Compared to healthy subjects, PD patients showed decreased activation of the striatum and cortical areas in composite movement, while performing worse at behavioral level. This implies that PD patients are especially impaired on tasks requiring highly tuned muscle co-activity. Singular movement, on the other hand, was characterized by a combination of increased activation of the ipsilateral parietal cortex and left cerebellum. As singular movement performance was only slightly compromised, we interpret this as a reflection of increased visuospatial processing, possibly as a compensational mechanism.

Usefulness of intermuscular coherence and cumulant analysis in the diagnosis of postural tremor.

OBJECTIVE: To investigate the potential value of two advanced EMG measures as additional diagnostic measures in the polymyographic assessment of postural upper-limb tremor. METHODS: We investigated coherence as a measure of dependency between two EMG signals, and cumulant analysis to reveal patterns of synchronicity in EMG activity in muscle pairs. Eighty datasets were analyzed retrospectively, obtained from four groups: essential tremor (ET), Parkinson's disease (PD), enhanced physiological tremor (EPT), and functional tremor (FT). RESULTS: Intermuscular coherence was highest in the PD group (0.58), intermediate in FT (0.43) and ET (0.40), and weakest in EPT (0.16) (p=0.002). EPT patients could be distinguished by low coherence: coherence <0.18 in the wrist+elbow extensors differentiates EPT in this sample with a sensitivity of 86% and specificity of 84%. Cumulant analysis showed predominantly alternating activity between wrist and elbow extensor in ET patients, while a more synchronous pattern was predominant in PD, EPT and FT (p=0.008). EMG activity in wrist and elbow flexors tended to be more synchronous in PD (p=0.059). CONCLUSION: Our results suggest that coherence and cumulant analysis may be of additional value in the diagnostic work-up of postural tremor. SIGNIFICANCE: These additional measures may be helpful in diagnosing difficult tremor cases.

The influence of central neuropathic pain in paraplegic patients on performance of a motor imagery based Brain Computer Interface.

OBJECTIVE: The aim of this study was to test how the presence of central neuropathic pain (CNP) influences the performance of a motor imagery based Brain Computer Interface (BCI). METHODS: In this electroencephalography (EEG) based study, we tested BCI classification accuracy and analysed event related desynchronisation (ERD) in 3 groups of volunteers during imagined movements of their arms and legs. The groups comprised of nine able-bodied people, ten paraplegic patients with CNP (lower abdomen and legs) and nine paraplegic patients without CNP. We tested two types of classifiers: a 3 channel bipolar montage and classifiers based on common spatial patterns (CSPs), with varying number of channels and CSPs. RESULTS: Paraplegic patients with CNP achieved higher classification accuracy and had stronger ERD than paraplegic patients with no pain for all classifier configurations. Highest 2-class classification accuracy was achieved for CSP classifier covering wider cortical area: 82±7% for patients with CNP, 82±4% for able-bodied and 78±5% for patients with no pain. CONCLUSION: Presence of CNP improves BCI classification accuracy due to stronger and more distinct ERD. SIGNIFICANCE: Results of the study show that CNP is an important confounding factor influencing the performance of motor imagery based BCI based on ERD.

A framework for the analysis of neuronal networks.

The object of this work is to consider the application of some methods of spike train analysis that are not widely known, and are concerned with the description of the interaction between spike trains and the determination of causal connections between them. The notation and terminology follow conventions established in the statistical literature. The examples given are based on in-continuity recordings of the spontaneous activity of single Ia afferents from the soleus muscle and single motor units from the same muscle. Cumulant densities are shown to be simple extensions of the traditional cross-correlation methods, and are useful in characterizing the pattern of activity in one spike train that influences that in another, and to reveal interactions between spike trains that would not be apparent from the correlation histogram alone. Parameters based on the Fourier transforms of the spike trains are shown to be useful in determining timing relations between them, and in inferring patterns of connectivity not possible by correlation methods alone.

How do we approach the locomotor network in the mammalian spinal cord?

For a large number of vertebrate species it is now indisputable that spinal networks have the capability of generating the basic locomotor rhythm. However, because of technical difficulties, the rate of progress in defining the intrinsic properties of mammalian locomotor rhythm generators has been slow in comparison to that made in the study of such networks in lower vertebrates. Investigations on afferent and descending control of locomotor activity in mammals have demonstrated that many of these pathways interact with the rhythm generator. In this review we discuss how these interactions (resetting) can be used for outlining relevant spinal circuits as a basis for a future identification of individual neurons of the spinal locomotor networks. In this overview we have given particular emphasis to selected afferent systems to illustrate the possibilities and problems with this approach.

Identification of patterns of neuronal connectivity--partial spectra, partial coherence, and neuronal interactions.

The cross-correlation histogram has provided the primary tool for inferring the structure of common inputs to pairs of neurones. While this technique has produced useful results it not clear how it may be extended to complex networks. In this report we introduce a linear model for point process systems. The finite Fourier transform of this model leads to a regression type analysis of the relations between spike trains. An advantage of this approach is that the full range of techniques for multivariate regression analyses becomes available for spike train analysis. The two main parameters used for the identification of neural networks are the coherence and partial coherences. The coherence defines a bounded measure of association between two spike trains and plays the role of a squared correlation coefficient defined at each frequency lambda. The partial coherences, analogous to the partial correlations of multiple regression analysis, allow an assessment of how any number of putative input processes may influence the relation between any two output processes. In many cases analytic solutions may be found for coherences and partial coherences for simple neural networks, and in combination with simulations may be used to test hypotheses concerning proposed networks inferred from spike train analyses.

A review of recent applications of cross-correlation methodologies to human motor unit recording.

This article reviews some recent applications of time and frequency domain cross-correlation techniques to human motor unit recording. These techniques may be used to examine the pre-synaptic mechanisms involved in control of motoneuron activity during on-going motor tasks in man without the need for imposed and artificial perturbations of the system. In this review we examine, through several examples, areas in which insights have been gained into the basic neurophysiological processes that bring about motoneuron firing in man and illustrate how these processes are affected by central nervous system pathology. We will demonstrate that synchronization and coherence may be revealed between human motor unit discharges and give examples that support the hypothesis that these phenomena are generated by activity in a focused common corticospinal input to spinal motoneurons. Disruption of central motor pathways due to diseases of the nervous system leads to pathophysiological alterations in the activity of these pre-synaptic motoneuron inputs that can be revealed by cross-correlation analysis of motor unit discharges. The significance of these studies and outstanding questions in this field are discussed.

An extended difference of coherence test for comparing and combining several independent coherence estimates: theory and application to the study of motor units and physiological tremor.

Recently there has been an increase in the use of spectral methods for the analysis of experimental data. These analytical methods allow the study of interactions between simultaneously recorded signals and are particularly suited to the study of systems displaying rhythmic behaviour. A useful parameter in this context is the coherence function which provides a bounded measure of linear association between two signals. In this report we introduce two new techniques for dealing with an arbitrary number of independent coherence estimates. The first technique provides a test to compare the coherence estimates for statistically significant differences. The second allows the original coherence estimates to be combined, or 'pooled' into a single representative estimate. These two measures, taken together, provide a powerful tool for characterising and summarising the correlations within data sets. Applications of the techniques are illustrated by analysing the interactions between single motor unit discharges and finger tremor, and between pairs of motor unit discharges in human subjects.

The participation of forelimb flexors in labyrinth and neck reflexes in the decerebrate cat.

The reflex behaviour of triceps and biceps brachii was assessed by EMG recordings during natural labyrinth or neck stimulation. Labyrinth reflexes resulting from changes in head position are antagonistic to those resulting from changes in neck position. Reflexes recorded from biceps were reciprocal to those recorded in ipsilateral triceps and symmetrical to those from contralateral triceps. A scheme of labyrinth and neck reflexes involving forelimb flexors is presented.

Conditioning of crossed extensor reflex pathways by independent natural stimulation of labyrinth, neck and elbow joint afferents.

The present experiments demonstrated that labyrinth, neck and elbow joint afferents interact to influence the excitability of crossed extensor reflex pathways projecting to triceps brachii in decerebrate cats. Reflex excitability was dependent on head, neck and elbow position such that it was increased when the elbow was held at full flexion and either the head maintained side down or the neck rotated side up. Such interaction between these afferents is likely to be important in postural control.

Modulation of soleus H-reflex following ipsilateral mechanical loading of the sole of the foot in normal and complete spinal cord injured humans.

The modulation of the soleus H-reflex in response to tonic mechanical loading applied to the plantar aspect of the foot sole was examined in nine normal subjects and five patients with a clinically defined complete spinal cord injury (SCI). With the subjects seated, tonic pressure applied to the metatarsal region of the ipsilateral foot sole significantly depressed soleus H-reflex excitability in all subjects. The demonstration of a decrease in H-reflex excitability in both subject groups as a result of applied pressure to the foot suggests that the change in reflex excitability is the result of a common spinal mechanism. The results highlight the modulatory effects that natural stimulation of cutaneous afferents can have on reflex excitability and may have practical application in gait rehabilitation and in the management of disorders of muscle tone following SCI.

Spinal locomotor activity in acutely spinalized cats induced by intrathecal application of noradrenaline.

In this study we present a method of intrathecal drug administration in the acute spinal cat. A thin tube introduced into the subarachnoid space below the spinal cord was used for local drug administration. Noradrenaline reduced short-latency and provoked long-latency reflexes following high threshold afferent stimulation. Topical application of noradrenaline to the spinal cord was also able to induce and maintain locomotion. Our results strengthen the notion that noradrenergic systems play an important role in motor control. In addition, the present report introduces a protocol in the acute spinal cat, which combine the benefits associated with direct application of drugs as used in vitro experiments with the advantages of using the well investigated in vivo cat spinal cord preparation.

Using electroencephalography to study functional coupling between cortical activity and electromyograms during voluntary contractions in humans.

Previous studies of neuronal oscillations in sensorimotor cortex in humans and primates have observed rhythmic 15-30 Hz activity, which is correlated with motor output. In humans, this work has been limited to magnetic recordings. In the present study we investigate if similar results can be obtained using electroencephalography (EEG). EEG recordings were made from over the sensorimotor cortex of five adult subjects who performed repeated periods of maintained wrist extension and flexion. Coherence analysis between EEG and electromyogram (EMG) recordings from these muscles revealed correlation in the 15-30 Hz range, with a synchronous correlation structure which matches that previously observed in humans and in paired cortical recordings from primates. We conclude that EEG is equally efficient at investigating functional aspects of these cortical rhythms during voluntary movement in humans.

In vitro effects of dihydrotestosterone on granulosa cell production of estrogen and progesterone.

To investigate the direct effects of androgens on follicle development, intact, immature female rats were given 8 IU PMSG (0 hour) and four injections of either vehicle or dihydrotestosterone (DHT), 1 mg/kg body weight, at 0, 12, 24, and 36 hours after PMSG. Granulosa cells from small (less than 200 microns), medium (200 to 400 microns), and large (greater than 400 microns) follicles were isolated and cultured in the presence or absence of 0.5 microM DHT in vitro for 48 hours, and the medium was assayed for progesterone and estrogen. Results show that DHT caused an increase in progesterone accumulation in all granulosa cells, regardless of follicle size. However, DHT inhibited estrogen accumulation in granulosa cells from different-size follicles and the inhibition varied depending on the duration of androgen exposure in vivo. The inhibition of estrogen accumulation was seen in granulosa cells from small follicles without prior exposure to DHT in vivo, while an inhibition of estrogen accumulation was seen in granulosa cells from medium and large follicles exposed to DHT treatment in vivo. Taken together, the results of experiments with in vivo and/or in vitro DHT treatment show that the androgen increases granulosa cell progesterone synthesis regardless of follicle size. However, the estrogen accumulation by granulosa cell is dependent on follicle size and duration of DHT exposure.