Extracting synergies in gait: using EMG variability to evaluate control strategies

There has been extensive debate as to whether muscle synergies in motor tasks reflect underlying neural organization or simply correlations in muscle activity that are imposed by the task. One possible means of distinguishing these two alternatives is through the analysis of variability in the electromyogram (EMG). Here, we simulated EMG in eight lower-limb muscles and introduced hypothetical neural coupling between specific muscle groups. Neural coupling was simulated by introducing correlations in the neural activation commands to different muscles (positive, negative, or zero coupling). When the entire EMG signal was used for analysis, the extracted synergies reflected only simultaneous muscle activity, regardless of the neural coupling between the muscles. On the other hand, examining the variability in the EMG after subtracting the ensemble average was successful in identifying the simulated neural coupling. The extracted synergies from these two methods were also different when we analyzed data from participants during treadmill walking. The results emphasize the importance of examining EMG variability to understand the neural basis of muscle synergies.     

基于非线性互依赖性的癫痫致痫区识别方法研究

致痫区的准确识别是治疗癫痫并减少副作用的基础,但传统视觉识别的方法在很多情况并不能令人满意。信号处理方法可以获得一些视觉观察不能发现的信息来作为传统方法的补充。致痫区识别可以看作一个驱动方识别问题,为了解决这个问题提出一种非线性互依赖性测度来作为致痫区(驱动方)的标识。非线性互依赖性可以检测EEG信号之间耦合的强度和方向信息,特别是耦合的方向信息可用以揭示癫痫发作传播的方向。对于不同的应用,以k和a这两个参数调节非线性互依赖性的灵敏度和完备性。在神经群模型构建的平台上对所提出致痫区识别的方法进行仿真。仿真结果显示,对于兴奋程度不同的致痫区,在没有突触延迟的情况下可以取得98.84%的总识别率,在有突触延迟的情况下可以取得与无突触延迟情况相近的识别率,说明基于非线性互依赖性的致痫区识别可以适用于不同的致痫区类型。     

海马区神经电信号相位同步化的初步研究

大脑各个区域的神经电活动存在各种不同频率的振荡,而theta节律振荡(5～10 Hz)是海马区神经活动具有代表性的特征.本文用海马区theta节律显著性检测和theta节律相位同步化的方法来分析多电极记录的神经元放电及其局部场电位信号,验证了theta节律成分的显著性和动物行为之间的关系,并首次研究了小鼠在不同行为状态下左右海马神经电活动之间的相位同步化的差异.     

Shoulder abduction-induced reductions in reaching work area following hemiparetic stroke: neuroscientific implications

A stroke-related loss of corticospinal and corticobulbar pathways is postulated to result in an increased use of remaining neural substrates such as bulbospinal pathways as individuals with stroke are required to generate greater volitional shoulder abduction torques. The effect of shoulder abduction on upper extremity reaching range of motion (work area) was measured in 18 individuals with stroke using the Arm Coordination Training 3-D (ACT^3D) device. This robotic system is capable of quantifying movement kinematics when a subject attempts to reach while simultaneously generating various levels of active shoulder abduction torque. We have provided data demonstrating an incremental increase of abnormal coupling of elbow flexion for greater levels of shoulder abduction in the paretic limb that results in a reduction in available work area as a function of active limb support. The progressive increase in the expression of abnormal shoulder/elbow coupling can be explained by a progressive reliance on the indirect cortico-bulbospinal connections that remain in individuals following a stroke-induced brain injury.     

Foetal ECG recovery using dynamic neural networks

Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coefficient) and statistical (analysis of variance, ANOVA) measures allows us to select the best recovery model. Finally, finite impulse response (FIR) and gamma neural networks are included in the adaptive noise cancellation (ANC) scheme in order to provide highly non-linear, dynamic capabilities to the recovery model. Neural networks are benchmarked with classical adaptive methods such as the least mean squares (LMS) and the normalized LMS (NLMS) algorithms in simulated and real registers and some conclusions are drawn. For synthetic registers, the most determinant factor in the identification of the models is the foetal-maternal signal-to-noise ratio (SNR). In addition, as the electromyogram contribution becomes more relevant, neural networks clearly outperform the LMS-based algorithm. From the ANOVA test, we found statistical differences between LMS-based models and neural models when complex situations (high foetal-maternal and foetal-noise SNRs) were present. These conclusions were confirmed after doing robustness tests on synthetic registers, visual inspection of the recovered signals and calculation of the recognition rates of foetal R-peaks for real situations. Finally, the best compromise between model complexity and outcomes was provided by the FIR neural network. Both the methodology for selecting a model and the introduction of advanced neural models are the main contributions of this paper.     

Frontal brain oscillations and social anxiety: A cross-frequency spectral analysis during baseline and speech anticipation

Increasing evidence suggests that cross-frequency spectral coupling between slow (SW) and fast (FW) wave activity in the EEG supports information exchange between separate and functionally distinct neural systems. Further, evidence suggests that states of uncertainty, anticipation and anxious apprehension involve a high degree of SW-FW coupling. We examined whether adults pre-selected for high and low social anxiety showed distinct patterns of frontal brain oscillatory coupling during resting baseline and the anticipation of a self-presentation task. As predicted, the high socially anxious group showed significantly greater SW-FW coupling than the low socially anxious group, in the right, but not left, frontal electrode sites while anticipating a public speaking task. Additionally, the low socially anxious group showed a decrease in delta power from baseline to speech anticipation, suggesting that they found the same task potentially rewarding. Exploratory analyses indicated no effects of delta-gamma coupling. However, EEG gamma band power increased during the speech anticipation condition, in the parietal electrode sites. Our results are discussed in the context of previous studies on cross-frequency EEG coupling in relation to individual differences in motivation and emotion and future directions for studying the neural correlates of anxiety.     

Synchronised oscillations of the human sensorimotor cortex

Oscillations are a prominent feature of macroscopic human sensorimotor cortical activity as recorded non-invasively with electroencephalography (EEG) and magnetoencephalography (MEG). The advent of whole-scalp MEG systems allowing rapid non-invasive recording from the entire cortex and accurate localisation of neural sources, and the development of refined signal analysis methods are important factors that led to an increasing interest in studies of sensorimotor oscillations during the last 10 years. Investigations on healthy subjects revealed frequency-specific localisation and modality-specific reactivity of 10 Hz and 20 Hz sensorimotor oscillations. Task-specific coherence between motor cortical and electromyographic oscillations, reflecting cortico-motoneuronal coupling, point towards a functional role of precentral oscillations in the cortical control of voluntary movements. Furthermore, abnormal cortico-motoneuronal coupling may underlie clinical symptoms of motor disorders, such as tremor. Thus, investigation of oscillatory sensorimotor activity proceeds from phenomenology to function and provides an interesting approach to address questions in human motor physiology and pathophysiology.     

Neural remodeling may partly contribute to the abnormality of excitation-contraction coupling in heart failure

Heart failure (HF) is a major and growing public health problem in the world. About 50% of deaths in HF occur suddenly due to malignant arrhythmia. Therefore, exploring the further mechanisms of chronic HF and finding new therapy targets are essential for the progression of HF treatment. Recently, some published papers suggested that myocardial neural remodeling and abnormal excitation-contraction (EC) coupling might partly contribute to the development of HF and sudden cardiac death. Even though a few studies have demonstrated that the sympathetic nerve system (SNS) may have significant impact on the functional states of myocardial EC coupling through the beta-adrenergic signaling pathway, so far, it still remains unknown that whether neural remodeling affects the EC coupling. Studies from Marks' group demonstrated that 70% of cardiac ryanodine receptors (RyR2), which located on the sarcoplasmic reculum (SR) controlling intracellular Ca(2+) release and muscle contraction in the heart, from failing hearts were abnormal and only 15% exhibited the most severe defects. In addition, Litwin et al. observed that temporal and spatial heterogeneities in local Ca(2+) release events in a rabbit model of HF after myocardial infarction. Because some studies have demonstrated that chronic SNS hyperactivity in HF led to protein kinase A (PKA) hyperphosphorylation of RyR2 in the heart, and the myocardial sympathetic nerve distribution become heterogeneous in the setting of HF. Thus, it is reasonable for us to propose the hypothesis that neural remodeling may partly account for the abnormality of EC coupling in HF.     

The use of functional neuroimaging to evaluate psychological and other non-pharmacological treatments for clinical pain

A large number of studies have provided evidence for the efficacy of psychological and other non-pharmacological interventions in the treatment of chronic pain. While these methods are increasingly used to treat pain, remarkably few studies focused on the exploration of their neural correlates. The aim of this article was to review the findings from neuroimaging studies that evaluated the neural response to distraction-based techniques, cognitive behavioral therapy (CBT), clinical hypnosis, mental imagery, physical therapy/exercise, biofeedback, and mirror therapy. To date, the results from studies that used neuroimaging to evaluate these methods have not been conclusive and the experimental methods have been suboptimal for assessing clinical pain. Still, several different psychological and non-pharmacological treatment modalities were associated with increased pain-related activations of executive cognitive brain regions, such as the ventral- and dorsolateral prefrontal cortex. There was also evidence for decreased pain-related activations in afferent pain regions and limbic structures. If future studies will address the technical and methodological challenges of today's experiments, neuroimaging might have the potential of segregating the neural mechanisms of different treatment interventions and elucidate predictive and mediating factors for successful treatment outcomes. Evaluations of treatment-related brain changes (functional and structural) might also allow for sub-grouping of patients and help to develop individualized treatments.     

Controlled E-field gradient coils for MRI

Peripheral neural stimulation is a major problem in current gradient coil designs. Induced current problems in patients relate directly to gradient strength and modulation frequency. Present designs of gradient coil tend to limit ultra-high-speed imaging methods such as echo-planar imaging (EPI) and echo-volumar imaging (EVI) because of the effect of induced currents in the patient which produce neural stimulation resulting in tingling sensations and involuntary muscle twitch. Neural stimulation could also trigger epileptic fits and/or cardiac fibrillation. For reduction of induced currents, an important aspect is the coil geometry. It is desirable to design the gradient coil in such a way as to prevent closed loop circulating currents within the body. Preliminary results using a four-sector gradient coil with a rectangular geometry, operating in a low mutual coupling mode and using passive E-field control, indicate significant reduction of the E-field within the subject volume of the coil, leading to a reduction of induced currents in a patient. Such a reduction allows safer operation using higher magnetic gradient strengths together with faster scans. Currently very fast scans are prohibited by virtue of the neural stimulation effects produced in present standard coil geometries.     

Comparative evaluation of methods for quantification of neural activity

Electrograms of single- and few-fibre baro- and chemoreceptor preparations from the carotid sinus nerve of rabbits were recorded monophasically at different levels of activation, as well as complete absence of potentials during temporary cold block of the preparation. The neural activity of every neurogram was determined by a PDP-12 computer using three different methods: (i) Determining all maxima and minima in the electrogram and distinguishing action potentials by comparing the amplitude changes to discriminator values derived from previous analysis of noise; (ii) counting transitions of the electrogram across a constant-voltage threshold just above the baseline noise; (iii) integrating the electrogram with or without rectification with reference to the electrical zero level. The results provided evidence that, in single- as in few-fibre preparations if methods (ii) in part, and (iii) generally, yield erroneous values and, consequently, distorted activity response curves due to measurement of baseline or superimposed noise, loss of summated potentials, baseline shifts and/or the presence of different types of potentials in the recording. Most satisfactory results were obtained by method (i). However, since even the latter becomes incorrect if the neural frequency exceeds several hundred to about 1000 impulses/s, none of these methods can be considered for exact quantification of neural activity in multi-fibre preparations or whole nerves.     

Modeling methology for nonlinear physiological systems

A general modeling approach for a broad class of nonlinear systems is presented that uses the concept of principal dynamic modes (PDMs). These PDMs constitute a filter bank whose outputs feed into a multi-input static nonlinearity of multinomial (polynomia) form to yield a general model for the broad class of Volterra systems. Because the practically obtainable models (from stimulus-response data) are of arbitrary order of nonlinearity, this approach is applicable to many nonlinear physiological systems heretofore beyond our methodological means. Two specific methods are proposed for the estimation of these PDMs and the associated nonlinearities from stimulus-response data. Method I uses eigendecomposition of a properly constructed matrix using the first two kernel estimates (obtained by existing methods). Method II uses a particular class of feedforward artificial neural networks with polynomial activation functions. The efficacy of these two methods is demonstrated with computer-simulated examples, and their relative performance is discussed. The advent of this approach promises a practicable solution to the vexing problem of modeling highly nonlinear physiological systems, provided that experimental data be available for reliable estimation of the requisite PDMs.     

Network recruitment to coherent oscillations in a hippocampal computer model

Coherent neural oscillations represent transient synchronization of local neuronal populations in both normal and pathological brain activity. These oscillations occur at or above gamma frequencies (>30 Hz) and often are propagated to neighboring tissue under circumstances that are both normal and abnormal, such as gamma binding or seizures. The mechanisms that generate and propagate these oscillations are poorly understood. In the present study we demonstrate, via a detailed computational model, a mechanism whereby physiological noise and coupling initiate oscillations and then recruit neighboring tissue, in a manner well described by a combination of stochastic resonance and coherence resonance. We develop a novel statistical method to quantify recruitment using several measures of network synchrony. This measurement demonstrates that oscillations spread via preexisting network connections such as interneuronal connections, recurrent synapses, and gap junctions, provided that neighboring cells also receive sufficient inputs in the form of random synaptic noise. "Epileptic" high-frequency oscillations (HFOs), produced by pathologies such as increased synaptic activity and recurrent connections, were superior at recruiting neighboring tissue. "Normal" HFOs, associated with fast firing of inhibitory cells and sparse pyramidal cell firing, tended to suppress surrounding cells and showed very limited ability to recruit. These findings point to synaptic noise and physiological coupling as important targets for understanding the generation and propagation of both normal and pathological HFOs, suggesting potential new diagnostic and therapeutic approaches to human disorders such as epilepsy.     

Association of orofacial with laryngeal and respiratory motor output during speech

Speech motor coordination most likely involves synaptic coupling among neural systems that innervate orofacial, laryngeal, and respiratory muscles. The nature and strength of coupling of the orofacial with the respiratory and laryngeal systems was studied indirectly by correlating orofacial speeds with fundamental frequency, vocal intensity, and inspiratory volume during speech. Fourteen adult subjects repeated a simple test utterance at varying rates and vocal intensities while recordings were obtained of the acoustic signal and movements of the upper lip, lower lip, tongue, jaw, rib cage, and abdomen. Across subjects and orofacial speed measures (14 subjects x 4 structures), significant correlations were obtained for fundamental frequency in 42 of 56 cases, for intensity in 35 of 56 cases, and for inspiratory volume in 14 of 56 cases. These results suggest that during speech production there is significant neural coupling of orofacial muscle systems with the laryngeal and respiratory systems as they are involved in vocalization. Comparisons across the four orofacial structures revealed higher correlations for the jaw relative to other orofacial structures. This suggests stronger connectivity between neural systems linking the jaw with the laryngeal and respiratory systems. This finding may be relevant to the frame/content theory of speech production, which suggests that the neural circuitry involved in jaw motor control for speech has evolved to form relatively strong linkages with systems involved in vocalization.     

A reevaluation of intervestibular nuclear coupling: its role in vestibular compensation

Recent experimental observations indicate that pathways interconnecting the bilateral vestibular nuclei (VN) may provide positive-feedback loops for signals across the midline. The implications of such positive feedback are considered in the context of vestibular compensation. A simple conceptual model of the interconnected VN is studied analytically, based on the hypothesis that the restoration of central symmetry is achieved via changes of neural gain in closed commissural loops. A wide variety of experimental conditions related to vestibular compensation are investigated. Analytic model predictions are compared to behavioral and neurophysiological findings in the literature. The results show that organized control over commissural gains in closed loops coupling the bilateral VN is fully compatible with all phenomena cited in the article. In particular, such a mechanism for vestibular compensation can reconcile observations such as the fact that Bechterew phenomena and decompensation can both be elicited from the compensated state. Placing the site of vestibular compensation in pathways linking the VN has many implications. Other forms of central neural plasticity (e.g., vestibuloocular reflex (VOR) gain plasticity) may rely on a similar principle, since modulation of transmidline coupling can be a very powerful means of altering responses in a bilateral nervous system.     

Model-free functional MRI analysis based on unsupervised clustering

Conventional model-based or statistical analysis methods for functional MRI (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms. However, they are not applicable in situations in which patterns of neural response are complicated and when fMRI response is unknown. In this paper the "neural gas" network is adapted and rigourosly studied for analyzing fMRI data. The algorithm supports spatial connectivity aiding in the identification of activation sites in functional brain imaging. A comparison of this new method with Kohonen's self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative evaluations. The most important findings in this paper are: (1) both "neural gas" and the fuzzy clustering technique outperform Kohonen's map in terms of identifying signal components with high correlation to the fMRI stimulus, (2) the "neural gas" outperforms the two other methods with respect to the quantization error, and (3) Kohonen's map outperforms the two other methods in terms of computational expense. The applicability of the new algorithm is demonstrated on experimental data.     

Spontaneous slow oscillation—slow spindle features predict induced overnight memory retention

Study ObjectivesSynchronization of neural activity within local networks and between brain regions is a major contributor to rhythmic field potentials such as the EEG. On the other hand, dynamic changes in microstructure and activity are reflected in the EEG, for instance slow oscillation (SO) slope can reflect synaptic strength. SO-spindle coupling is a measure for neural communication. It was previously associated with memory consolidation, but also shown to reveal strong interindividual differences. In studies, weak electric current stimulation has modulated brain rhythms and memory retention. Here, we investigate whether SO-spindle coupling and SO slope during baseline sleep are associated with (predictive of) stimulation efficacy on retention performance.MethodsTwenty-five healthy subjects participated in three experimental sessions. Sleep-associated memory consolidation was measured in two sessions, in one anodal transcranial direct current stimulation oscillating at subjects individual SO frequency (so-tDCS) was applied during nocturnal sleep. The third session was without a learning task (baseline sleep). The dependence on SO-spindle coupling and SO-slope during baseline sleep of so-tDCS efficacy on retention performance were investigated.ResultsStimulation efficacy on overnight retention of declarative memories was associated with nesting of slow spindles to SO trough in deep nonrapid eye movement baseline sleep. Steepness and direction of SO slope in baseline sleep were features indicative for stimulation efficacy.ConclusionsFindings underscore a functional relevance of activity during the SO up-to-down state transition for memory consolidation and provide support for distinct consolidation mechanisms for types of declarative memories.     

Evaluation of methods for chemically coupling foot-and-mouth disease virus to sheep red blood cells for immunological assays

Six methods of chemically coupling proteins to red blood cells were evaluated for their effectiveness in coupling foot-and-mouth disease virus (FMDV) to sheep red blood cells. The coupling agents tested were potassium periodate, 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide hydrochloride (ECDI), chromium chloride, glutaraldehyde, bis-diazotized benzidine (BDB) and N-succinimidyl 3-(2-pyridyldithio) propionate (SPDP). Of these, only the coupling methods using BDB and SPDP resulted in virus-red cell complexes that reacted with FMDV antiserum in passive hemagglutination and passive immune hemolysis assays. The BDB and SPDP methods were studied further to determine optimal coupling conditions, the kinetics of coupling and the effects of chemical couplers on viral integrity. Only the FMDV-red cell complexes formed with SPDP were suitable targets for detecting FMDV antibody producing lymphocytes in a hemolytic plaque assay.