Multi-frequency phase locking in human somatosensory cortex

Tactile-Sensing Technologies: Trends, Challenges and Outlook in Agri-Food Manipulation

Tactile sensing plays a pivotal role in achieving precise physical manipulation tasks and extracting vital physical features. This comprehensive review paper presents an in-depth overview of the growing research on tactile-sensing technologies, encompassing state-of-the-art techniques, future prospects, and current limitations. The paper focuses on tactile hardware, algorithmic complexities, and the distinct features offered by each sensor. This paper has a special emphasis on agri-food manipulation and relevant tactile-sensing technologies. It highlights key areas in agri-food manipulation, including robotic harvesting, food item manipulation, and feature evaluation, such as fruit ripeness assessment, along with the emerging field of kitchen robotics. Through this interdisciplinary exploration, we aim to inspire researchers, engineers, and practitioners to harness the power of tactile-sensing technology for transformative advancements in agri-food robotics. By providing a comprehensive understanding of the current landscape and future prospects, this review paper serves as a valuable resource for driving progress in the field of tactile sensing and its application in agri-food systems.

Vibrotactile stimulation at gamma frequency mitigates pathology related to neurodegeneration and improves motor function

The risk for neurodegenerative diseases increases with aging, with various pathological conditions and functional deficits accompanying these diseases. We have previously demonstrated that non-invasive visual stimulation using 40 Hz light flicker ameliorated pathology and modified cognitive function in mouse models of neurodegeneration, but whether 40 Hz stimulation using another sensory modality can impact neurodegeneration and motor function has not been studied. Here, we show that whole-body vibrotactile stimulation at 40 Hz leads to increased neural activity in the primary somatosensory cortex (SSp) and primary motor cortex (MOp). In two different mouse models of neurodegeneration, Tau P301S and CK-p25 mice, daily exposure to 40 Hz vibrotactile stimulation across multiple weeks also led to decreased brain pathology in SSp and MOp. Furthermore, both Tau P301S and CK-p25 mice showed improved motor performance after multiple weeks of daily 40 Hz vibrotactile stimulation. Vibrotactile stimulation at 40 Hz may thus be considered as a promising therapeutic strategy for neurodegenerative diseases with motor deficits.

Random Tactile Noise Stimulation Reveals Beta-Rhythmic Impulse Response Function of the Somatosensory System

Both passive tactile stimulation and motor actions result in dynamic changes in beta band (15-30 Hz Hz) oscillations over somatosensory cortex. Similar to alpha band (8-12 Hz) power decrease in the visual system, beta band power also decreases following stimulation of the somatosensory system. This relative suppression of α and β oscillations is generally interpreted as an increase in cortical excitability. Here, next to traditional single-pulse stimuli, we used a random intensity continuous right index finger tactile stimulation (white noise), which enabled us to uncover an impulse response function of the somatosensory system. Contrary to previous findings, we demonstrate a burst-like initial increase rather than decrease of beta activity following white noise stimulation (human participants, N = 18, 8 female). These β bursts, on average, lasted for 3 cycles, and their frequency was correlated with resonant frequency of somatosensory cortex, as measured by a multifrequency steady-state somatosensory evoked potential paradigm. Furthermore, beta band bursts shared spectro-temporal characteristics with evoked and resting-state β oscillations. Together, our findings not only reveal a novel oscillatory signature of somatosensory processing that mimics the previously reported visual impulse response functions, but also point to a common oscillatory generator underlying spontaneous β bursts in the absence of tactile stimulation and phase-locked β bursts following stimulation, the frequency of which is determined by the resonance properties of the somatosensory system.SIGNIFICANCE STATEMENT The investigation of the transient nature of oscillations has gained great popularity in recent years. The findings of bursting activity, rather than sustained oscillations in the beta band, have provided important insights into its role in movement planning, working memory, inhibition, and reactivation of neural ensembles. In this study, we show that also in response to tactile stimulation the somatosensory system responds with ∼3 cycle oscillatory beta band bursts, whose spectro-temporal characteristics are shared with evoked and resting-state beta band oscillatory signatures of the somatosensory system. As similar bursts have been observed in the visual domain, these oscillatory signatures might reflect an important supramodal mechanism in sensory processing.

Multi-phase locking value: A generalized method for determining instantaneous multi-frequency phase coupling

BACKGROUND

Many physical, biological and neural systems behave as coupled oscillators, with characteristic phase coupling across different frequencies. Methods such as n : m phase locking value (where two coupling frequencies are linked as: mf ₁ = nf ₂) and bi-phase locking value have previously been proposed to quantify phase coupling between two resonant frequencies (e.g. f, 2f/3) and across three frequencies (e.g. f ₁, f ₂, f ₁ + f ₂), respectively. However, the existing phase coupling metrics have their limitations and limited applications. They cannot be used to detect or quantify phase coupling across multiple frequencies (e.g. f ₁, f ₂, f ₃, f ₄, f ₁ + f ₂ + f ₃ - f ₄), or coupling that involves non-integer multiples of the frequencies (e.g. f ₁, f ₂, 2f ₁/3 + f ₂/3).

NEW METHODS

To address the gap, this paper proposes a generalized approach, named multi-phase locking value (M-PLV), for the quantification of various types of instantaneous multi-frequency phase coupling. Different from most instantaneous phase coupling metrics that measure the simultaneous phase coupling, the proposed M-PLV method also allows the detection of delayed phase coupling and the associated time lag between coupled oscillators.

RESULTS

The M-PLV has been tested on cases where synthetic coupled signals are generated using white Gaussian signals, and a system comprised of multiple coupled Rössler oscillators, as well as a human subject dataset. Results indicate that the M-PLV can provide a reliable estimation of the time window and frequency combination where the phase coupling is significant, as well as a precise determination of time lag in the case of delayed coupling. This method has the potential to become a powerful new tool for exploring phase coupling in complex nonlinear dynamic systems.

Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum

Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG). Specifically, source estimation results showed differences between AS and neurotypically developing (NTD) subjects in the brain response to 25-Hz vibrotactile stimulation of the right fingertips, with lower inter-trial coherence (ITC) observed in the AS group. Here, we examined whether these group differences can be detected without source estimation using scalp electroencephalography (EEG), which is more commonly available in clinical settings than MEG, and therefore offers a greater potential for clinical translation. To that end, we recorded simultaneous whole-head MEG and EEG in 14 AS and 10 NTD subjects (age 15-28 years) using the same vibrotactile paradigm. Based on the scalp topographies, small sets of left hemisphere MEG and EEG sensors showing the maximum overall ITC were selected for group comparisons. Significant differences between the AS and NTD groups in ITC at 25 Hz as well as at 50 Hz were recorded in both MEG and EEG sensor data. For each measure, the mean ITC was lower in the AS than in the NTD group. EEG ITC values correlated with behaviorally assessed somatosensory sensation avoiding scores. The results show that information about ITC from MEG and EEG signals have substantial overlap, and thus EEG sensor-based ITC measures of the AS somatosensory processing biomarker previously identified using source localized MEG data have a potential to be developed into clinical use in AS, thanks to the higher accessibility to EEG in clinical settings.

Neural Coding of Vibration Intensity

Vibrotactile feedback technology has become widely used in human-computer interaction due to its low cost, wearability, and expressiveness. Although neuroimaging studies have investigated neural processes associated with different types of vibrotactile feedback, encoding vibration intensity in the brain remains largely unknown. The aim of this study is to investigate neural processes associated with vibration intensity using electroencephalography. Twenty-nine healthy participants (aged 18-40 years, nine females) experienced vibrotactile feedback at the distal phalanx of the left index finger with three vibration intensity conditions: no vibration, low-intensity vibration (1.56 g), and high-intensity vibration (2.26 g). The alpha and beta band event-related desynchronization (ERD) as well as P2 and P3 event-related potential components for each of the three vibration intensity conditions are obtained. Results demonstrate that the ERD in the alpha band in the contralateral somatosensory and motor cortex areas is significantly associated with the vibration intensity. The average power spectral density (PSD) of the peak period of the ERD (400-600 ms) is significantly stronger for the high- and low-vibration intensity conditions compared to the no vibration condition. Furthermore, the average PSD of the ERD rebound (700-2,000 ms) is significantly maintained for the high-vibration intensity compared to low-intensity and no vibration conditions. Beta ERD signals the presence of vibration. These findings inform the development of quantitative measurements for vibration intensities based on neural signals.

Allophonic perception of VOT contrasts in Spanish children with dyslexia

INTRODUCTION

Previous studies have evidenced a different mode of speech perception in dyslexia, characterized by the use of allophonic rather than phonemic units. People with dyslexia perceive phonemic features (such as voicing) less accurately than typical readers, but they perceive allophonic features (i.e., language-independent differences between speech sounds) more accurately.

METHOD

In this study, we investigated the perception of voicing contrasts in a sample of 204 Spanish children with or without dyslexia. Identification and discrimination data were collected for synthetic sounds varying along three different voice onset time (VOT) continua (ba/pa, de/te, and di/ti). Empirical data will be contrasted with a mathematical model of allophonic perception building up from neural oscillations and auditory temporal processing.

RESULTS

Children with dyslexia exhibited a general deficit in categorical precision; that is, they discriminated among phonemically contrastive pairs (around 0-ms VOT) less accurately than did chronological age controls, irrespective of the stimulus continuum. Children with dyslexia also exhibited a higher sensitivity in the discrimination of allophonic features (around ±30-ms VOT), but only for the stimulus continuum that was based on a nonlexical contrast (ba/pa).

CONCLUSION

Fitting the neural network model to the data collected for this continuum suggests that allophonic perception is due to a deficit in "subharmonic coupling" between high-frequency oscillations. Relationships with "temporal sampling framework" theory are discussed.

Spatiotemporal features of β-γ phase-amplitude coupling in Parkinson's disease derived from scalp EEG

Abnormal phase-amplitude coupling between β and broadband-γ activities has been identified in recordings from the cortex or scalp of patients with Parkinson's disease. While enhanced phase-amplitude coupling has been proposed as a biomarker of Parkinson's disease, the neuronal mechanisms underlying the abnormal coupling and its relationship to motor impairments in Parkinson's disease remain unclear. To address these issues, we performed an in-depth analysis of high-density EEG recordings at rest in 19 patients with Parkinson's disease and 20 age- and sex-matched healthy control subjects. EEG signals were projected onto the individual cortical surfaces using source reconstruction techniques and separated into spatiotemporal components using independent component analysis. Compared to healthy controls, phase-amplitude coupling of Parkinson's disease patients was enhanced in dorsolateral prefrontal cortex, premotor cortex, primary motor cortex and somatosensory cortex, the difference being statistically significant in the hemisphere contralateral to the clinically more affected side. β and γ signals involved in generating abnormal phase-amplitude coupling were not strictly phase-phase coupled, ruling out that phase-amplitude coupling merely reflects the abnormal activity of a single oscillator in a recurrent network. We found important differences for couplings between the β and γ signals from identical components as opposed to those from different components (originating from distinct spatial locations). While both couplings were abnormally enhanced in patients, only the latter were correlated with clinical motor severity as indexed by part III of the Movement Disorder Society Unified Parkinson's Disease Rating Scale. Correlations with parkinsonian motor symptoms of such inter-component couplings were found in premotor, primary motor and somatosensory cortex, but not in dorsolateral prefrontal cortex, suggesting motor domain specificity. The topography of phase-amplitude coupling demonstrated profound differences in patients compared to controls. These findings suggest, first, that enhanced phase-amplitude coupling in Parkinson's disease patients originates from the coupling between distinct neural networks in several brain regions involved in motor control. Because these regions included the somatosensory cortex, abnormal phase-amplitude coupling is not exclusively tied to the hyperdirect tract connecting cortical regions monosynaptically with the subthalamic nucleus. Second, only the coupling between β and γ signals from different components appears to have pathophysiological significance, suggesting that therapeutic approaches breaking the abnormal lateral coupling between neuronal circuits may be more promising than targeting phase-amplitude coupling per se.

Nonlinear System Identification of Neural Systems from Neurophysiological Signals

The human nervous system is one of the most complicated systems in nature. Complex nonlinear behaviours have been shown from the single neuron level to the system level. For decades, linear connectivity analysis methods, such as correlation, coherence and Granger causality, have been extensively used to assess the neural connectivities and input-output interconnections in neural systems. Recent studies indicate that these linear methods can only capture a certain amount of neural activities and functional relationships, and therefore cannot describe neural behaviours in a precise or complete way. In this review, we highlight recent advances in nonlinear system identification of neural systems, corresponding time and frequency domain analysis, and novel neural connectivity measures based on nonlinear system identification techniques. We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively. These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions. These nonlinear approaches also have the potential to produce sensitive biomarkers to facilitate the development of precision diagnostic tools for evaluating neurological disorders and the effects of targeted intervention.

Nonlinear Modeling of Cortical Responses to Mechanical Wrist Perturbations Using the NARMAX Method

OBJECTIVE

Nonlinear modeling of cortical responses (EEG) to wrist perturbations allows for the quantification of cortical sensorimotor function in healthy and neurologically impaired individuals. A common model structure reflecting key characteristics shared across healthy individuals may provide a reference for future clinical studies investigating abnormal cortical responses associated with sensorimotor impairments. Thus, the goal of our study is to identify this common model structure and therefore to build a nonlinear dynamic model of cortical responses, using nonlinear autoregressive-moving-average model with exogenous inputs (NARMAX).

METHODS

EEG was recorded from ten participants when receiving continuous wrist perturbations. A common model structure detection method was developed for identifying a common NARMAX model structure across all participants, with individualized parameter values. The results were compared to conventional subject-specific models.

RESULTS

The proposed method achieved 93.91% variance accounted for (VAF) when implementing a one-step-ahead prediction and around 50% VAF for a k-step ahead prediction (k = 3), without a substantial drop of VAF as compare to subject-specific models. The estimated common structure suggests that the measured cortical response is a mixed outcome of the nonlinear transformation of external inputs and local neuronal interactions or inherent neuronal dynamics at the cortex.

CONCLUSION

The proposed method well determined the common characteristics across subjects in the cortical responses to wrist perturbations.

SIGNIFICANCE

It provides new insights into the human sensorimotor nervous system in response to somatosensory inputs and paves the way for future translational studies on assessments of sensorimotor impairments using our modeling approach.

Quantifying the Nonlinear Interaction in the Nervous System Based on Phase-Locked Amplitude Relationship

OBJECTIVE

This paper introduces the Cross-frequency Amplitude Transfer Function (CATF), a model-free method for quantifying nonlinear stimulus-response interaction based on phase-locked amplitude relationship.

METHOD

The CATF estimates the amplitude transfer from input frequencies at stimulation signal to their harmonics/intermodulation at the response signal. We first verified the performance of CATF in simulation tests with systems containing a static nonlinear function and a linear dynamic, i.e., Hammerstein and Wiener systems. We then applied the CATF to investigate the second-order nonlinear amplitude transfer in the human proprioceptive system from the periphery to the cortex.

RESULT

The simulation demonstrated that the CATF is a general method, which can well quantify nonlinear stimulus-response amplitude transfer for different orders of nonlinearity in Wiener or Hammerstein system configurations. Applied to the human proprioceptive system, we found a complicated nonlinear system behavior with substantial amplitude transfer from the periphery stimulation to cortical response signals in the alpha band. This complicated system behavior may be associated with the nonlinear behavior of the muscle spindle and the dynamic interaction in the thalamocortical radiation.

CONCLUSION

This paper provides a new tool to identify nonlinear interaction in the nervous system.

SIGNIFICANCE

The results provide novel insight of nonlinear dynamics in the human proprioceptive system.

New Horizons in Early Dementia Diagnosis: Can Cerebellar Stimulation Untangle the Knot?

Differentiating Mild Cognitive Impairment (MCI) from dementia and estimating the risk of MCI-to-dementia conversion (MDC) are challenging tasks. Thus, objective tools are mandatory to get early diagnosis and prognosis. About that, there is a growing interest on the role of cerebellum-cerebrum connectivity (CCC). The aim of this study was to differentiate patients with an early diagnosis of dementia and MCI depending on the effects of a transcranial magnetic stimulation protocol (intermittent theta-burst stimulation -iTBS) delivered on the cerebellum able to modify cortico-cortical connectivity. Indeed, the risk of MDC is related to the response to iTBS, being higher in non-responder individuals. All patients with MCI, but eight (labelled as MCI-), showed preserved iTBS aftereffect. Contrariwise, none of the patients with dementia showed iTBS aftereffects. None of the patients showed EEG aftereffects following a sham TBS protocol. Five among the MCI- patients converted to dementia at 6-month follow-up. Our data suggest that cerebellar stimulation by means of iTBS may support the differential diagnosis between MCI and dementia and potentially identify the individuals with MCI who may be at risk of MDC. These findings may help clinicians to adopt a better prevention/follow-up strategy in such patients.

Imaging human cortical responses to intraneural microstimulation using magnetoencephalography

The sensation of touch in the glabrous skin of the human hand is conveyed by thousands of fast-conducting mechanoreceptive afferents, which can be categorised into four distinct types. The spiking properties of these afferents in the periphery in response to varied tactile stimuli are well-characterised, but relatively little is known about the spatiotemporal properties of the neural representations of these different receptor types in the human cortex. Here, we use the novel methodological combination of single-unit intraneural microstimulation (INMS) with magnetoencephalography (MEG) to localise cortical representations of individual touch afferents in humans, by measuring the extracranial magnetic fields from neural currents. We found that by assessing the modulation of the beta (13-30 Hz) rhythm during single-unit INMS, significant changes in oscillatory amplitude occur in the contralateral primary somatosensory cortex within and across a group of fast adapting type I mechanoreceptive afferents, which corresponded well to the induced response from matched vibrotactile stimulation. Combining the spatiotemporal specificity of MEG with the selective single-unit stimulation of INMS enables the interrogation of the central representations of different aspects of tactile afferent signalling within the human cortices. The fundamental finding that single-unit INMS ERD responses are robust and consistent with natural somatosensory stimuli will permit us to more dynamically probe the central nervous system responses in humans, to address questions about the processing of touch from the different classes of mechanoreceptive afferents and the effects of varying the stimulus frequency and patterning.

A Novel Approach for Modeling Neural Responses to Joint Perturbations Using the NARMAX Method and a Hierarchical Neural Network

The human nervous system is an ensemble of connected neuronal networks. Modeling and system identification of the human nervous system helps us understand how the brain processes sensory input and controls responses at the systems level. This study aims to propose an advanced approach based on a hierarchical neural network and non-linear system identification method to model neural activity in the nervous system in response to an external somatosensory input. The proposed approach incorporates basic concepts of Non-linear AutoRegressive Moving Average Model with eXogenous input (NARMAX) and neural network to acknowledge non-linear closed-loop neural interactions. Different from the commonly used polynomial NARMAX method, the proposed approach replaced the polynomial non-linear terms with a hierarchical neural network. The hierarchical neural network is built based on known neuroanatomical connections and corresponding transmission delays in neural pathways. The proposed method is applied to an experimental dataset, where cortical activities from ten young able-bodied individuals are extracted from electroencephalographic signals while applying mechanical perturbations to their wrist joint. The results yielded by the proposed method were compared with those obtained by the polynomial NARMAX and Volterra methods, evaluated by the variance accounted for (VAF). Both the proposed and polynomial NARMAX methods yielded much better modeling results than the Volterra model. Furthermore, the proposed method modeled cortical responded with a mean VAF of 69.35% for a three-step ahead prediction, which is significantly better than the VAF from a polynomial NARMAX model (mean VAF 47.09%). This study provides a novel approach for precise modeling of cortical responses to sensory input. The results indicate that the incorporation of knowledge of neuroanatomical connections in building a realistic model greatly improves the performance of system identification of the human nervous system.

Enhanced perceptual processing of self-generated motion: Evidence from steady-state visual evoked potentials

The sense of agency emerges when our voluntary actions produce anticipated or predictable outcomes in the external world. It remains unclear how the sense of control also influences our perception of the external world. The present study examined perceptual processing of self-generated motion versus non-self-generated motion using steady-state visual evoked potentials (SSVEPs). Participants continuously moved their finger on a touchpad to trigger the movements of two shapes (Experiment 1) or two groups of dots (Experiment 2) on a monitor. Degree of control was manipulated by varying the spatial relation between finger movement and stimulus trajectory across conditions. However, the velocity, onset time, and offset time of visual stimuli always corresponded to participants' finger movement. Stimuli flickered at a frequency of either 7.5 Hz or 10 Hz, thus SSVEPs of these frequencies and their harmonics provided a frequency-tagged measurement of perceptual processing. Participants triggered the motion of all stimuli simultaneously, but had greater levels of control over some stimuli than over others. Their task was to detect a brief colour change on the border(s) of one shape (Experiment 1) or of one group of dots (Experiment 2). Although control over shapes/dots was irrelevant to the visual detection task, we found stronger SSVEPs for stimuli that were under a high level of control, compared with the stimuli that were under a low level of control. Our results suggest that the spatial regularity between self-generated movements and visual input boosted the neural responses underlying perceptual processing. Our results support the preactivation account of sensory attenuation, suggesting that perceptual processing of self-generated events is enhanced rather than inhibited.

Steady-State EEG and Psychophysical Measures of Multisensory Integration to Cross-Modally Synchronous and Asynchronous Acoustic and Vibrotactile Amplitude Modulation Rate

According to thetemporal principleof multisensory integration, cross-modal synchronisation of stimulus onset facilitates multisensory integration. This is typically observed as a greater response to multisensory stimulation relative to the sum of the constituent unisensory responses (i.e.,superadditivity). The aim of the present study was to examine whether the temporal principle extends to the cross-modal synchrony of amplitude-modulation (AM) rate. It is well established that psychophysical sensitivity to AM stimulation is strongly influenced by AM rate where the optimum rate differs according to sensory modality. This rate-dependent sensitivity is also apparent from EEG steady-state response (SSR) activity, which becomes entrained to the stimulation rate and is thought to reflect neural processing of the temporal characteristics of AM stimulation. In this study we investigated whether cross-modal congruence of AM rate reveals both psychophysical and EEG evidence of enhanced multisensory integration. To achieve this, EEG SSR and psychophysical sensitivity to simultaneous acoustic and/or vibrotactile AM stimuli were measured at cross-modally congruent and incongruent AM rates. While the results provided no evidence of superadditive multisensory SSR activity or psychophysical sensitivity, the complex pattern of results did reveal a consistent correspondence between SSR activity and psychophysical sensitivity to AM stimulation. This indicates that entrained EEG activity may provide a direct measure of cortical activity underlying multisensory integration. Consistent with the temporal principle of multisensory integration, increased vibrotactile SSR responses and psychophysical sensitivity were found for cross-modally congruent relative to incongruent AM rate. However, no corresponding increase in auditory SSR or psychophysical sensitivity was observed for cross-modally congruent AM rates. This complex pattern of results can be understood in terms of the likely influence of theprinciple of inverse effectivenesswhere the temporal principle of multisensory integration was only evident in the context of reduced perceptual sensitivity for the vibrotactile but not the auditory modality.

Unveiling neural coupling within the sensorimotor system: directionality and nonlinearity

Neural coupling between the central nervous system and the periphery is essential for the neural control of movement. Corticomuscular coherence is a popular linear technique to assess synchronised oscillatory activity in the sensorimotor system. This oscillatory coupling originates from ascending somatosensory feedback and descending motor commands. However, corticomuscular coherence cannot separate this bidirectionality. Furthermore, the sensorimotor system is nonlinear, resulting in cross‐frequency coupling. Cross‐frequency oscillations cannot be assessed nor exploited by linear measures. Here, we emphasise the need of novel coupling measures, which provide directionality and acknowledge nonlinearity, to unveil neural coupling in the sensorimotor system. We highlight recent advances in the field and argue that assessing directionality and nonlinearity of neural coupling will break new ground in the study of the control of movement in healthy and neurologically impaired individuals.

Integrated trimodal SSEP experimental setup for visual, auditory and tactile stimulation

OBJECTIVE

Steady-state evoked potentials (SSEPs), the brain responses to repetitive stimulation, are commonly used in both clinical practice and scientific research. Particular brain mechanisms underlying SSEPs in different modalities (i.e. visual, auditory and tactile) are very complex and still not completely understood. Each response has distinct resonant frequencies and exhibits a particular brain topography. Moreover, the topography can be frequency-dependent, as in case of auditory potentials. However, to study each modality separately and also to investigate multisensory interactions through multimodal experiments, a proper experimental setup appears to be of critical importance. The aim of this study was to design and evaluate a novel SSEP experimental setup providing a repetitive stimulation in three different modalities (visual, tactile and auditory) with a precise control of stimuli parameters. Results from a pilot study with a stimulation in a particular modality and in two modalities simultaneously prove the feasibility of the device to study SSEP phenomenon.

APPROACH

We developed a setup of three separate stimulators that allows for a precise generation of repetitive stimuli. Besides sequential stimulation in a particular modality, parallel stimulation in up to three different modalities can be delivered. Stimulus in each modality is characterized by a stimulation frequency and a waveform (sine or square wave). We also present a novel methodology for the analysis of SSEPs.

MAIN RESULTS

Apart from constructing the experimental setup, we conducted a pilot study with both sequential and simultaneous stimulation paradigms. EEG signals recorded during this study were analyzed with advanced methodology based on spatial filtering and adaptive approximation, followed by statistical evaluation.

SIGNIFICANCE

We developed a novel experimental setup for performing SSEP experiments. In this sense our study continues the ongoing research in this field. On the other hand, the described setup along with the presented methodology is a considerable improvement and an extension of methods constituting the state-of-the-art in the related field. Device flexibility both with developed analysis methodology can lead to further development of diagnostic methods and provide deeper insight into information processing in the human brain.

Decoding the orientation of contrast edges from MEG evoked and induced responses

Visual gamma oscillations have been proposed to subserve perceptual binding, but their strong modulation by diverse stimulus features confounds interpretations of their precise functional role. Overcoming this challenge necessitates a comprehensive account of the relationship between gamma responses and stimulus features. Here we used multivariate pattern analyses on human MEG data to characterize the relationships between gamma responses and one basic stimulus feature, the orientation of contrast edges. Our findings confirmed we could decode orientation information from induced responses in two dominant frequency bands at 24-32 Hz and 50-58 Hz. Decoding was higher for cardinal than oblique orientations, with similar results also obtained for evoked MEG responses. In contrast to multivariate analyses, orientation information was mostly absent in univariate signals: evoked and induced responses in early visual cortex were similar in all orientations, with only exception an inverse oblique effect observed in induced responses, such that cardinal orientations produced weaker oscillatory signals than oblique orientations. Taken together, our results showed multivariate methods are well suited for the analysis of gamma oscillations, with multivariate patterns robustly encoding orientation information and predominantly discriminating cardinal from oblique stimuli.

Oscillatory Correlates of Visual Consciousness

Conscious experiences are linked to activity in our brain: the neural correlates of consciousness (NCC). Empirical research on these NCCs covers a wide range of brain activity signals, measures, and methodologies. In this paper, we focus on spontaneous brain oscillations; rhythmic fluctuations of neuronal (population) activity which can be characterized by a range of parameters, such as frequency, amplitude (power), and phase. We provide an overview of oscillatory measures that appear to correlate with conscious perception. We also discuss how increasingly sophisticated techniques allow us to study the causal role of oscillatory activity in conscious perception (i.e., ‘entrainment’). This review of oscillatory correlates of consciousness suggests that, for example, activity in the alpha-band (7–13 Hz) may index, or even causally support, conscious perception. But such results also showcase an increasingly acknowledged difficulty in NCC research; the challenge of separating neural activity necessary for conscious experience to arise (prerequisites) from neural activity underlying the conscious experience itself (substrates) or its results (consequences).

Quantification of task-dependent cortical activation evoked by robotic continuous wrist joint manipulation in chronic hemiparetic stroke

Background

Cortical damage after stroke can drastically impair sensory and motor function of the upper limb, affecting the execution of activities of daily living and quality of life. Motor impairment after stroke has been thoroughly studied, however sensory impairment and its relation to movement control has received less attention. Integrity of the somatosensory system is essential for feedback control of human movement, and compromised integrity due to stroke has been linked to sensory impairment.

Methods

The goal of this study is to assess the integrity of the somatosensory system in individuals with chronic hemiparetic stroke with different levels of sensory impairment, through a combination of robotic joint manipulation and high-density electroencephalogram (EEG). A robotic wrist manipulator applied continuous periodic disturbances to the affected limb, providing somatosensory (proprioceptive and tactile) stimulation while challenging task execution. The integrity of the somatosensory system was evaluated during passive and active tasks, defined as ‘relaxed wrist’ and ‘maintaining 20% maximum wrist flexion’, respectively. The evoked cortical responses in the EEG were quantified using the power in the averaged responses and their signal-to-noise ratio.

Results

Thirty individuals with chronic hemiparetic stroke and ten unimpaired individuals without stroke participated in this study. Participants with stroke were classified as having severe, mild, or no sensory impairment, based on the Erasmus modification of the Nottingham Sensory Assessment. Under passive conditions, wrist manipulation resulted in contralateral cortical responses in unimpaired and chronic stroke participants with mild and no sensory impairment. In participants with severe sensory impairment the cortical responses were strongly reduced in amplitude, which related to anatomical damage. Under active conditions, participants with mild sensory impairment showed reduced responses compared to the passive condition, whereas unimpaired and chronic stroke participants without sensory impairment did not show this reduction.

Conclusions

Robotic continuous joint manipulation allows studying somatosensory cortical evoked responses during the execution of meaningful upper limb control tasks. Using such an approach it is possible to quantitatively assess the integrity of sensory pathways; in the context of movement control this provides additional information required to develop more effective neurorehabilitation therapies.

Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion

Coupling between cortical oscillations and muscle activity facilitates neuronal communication during motor control. The linear part of this coupling, known as corticomuscular coherence, has received substantial attention, even though neuronal communication underlying motor control has been demonstrated to be highly nonlinear. A full assessment of corticomuscular coupling, including the nonlinear part, is essential to understand the neuronal communication within the sensorimotor system. In this study, we applied the recently developed n:m coherence method to assess nonlinear corticomuscular coupling during isotonic wrist flexion. The n:m coherence is a generalized metric for quantifying nonlinear cross-frequency coupling as well as linear iso-frequency coupling. By using independent component analysis (ICA) and equivalent current dipole source localization, we identify four sensorimotor related brain areas based on the locations of the dipoles, i.e., the contralateral primary sensorimotor areas, supplementary motor area (SMA), prefrontal area (PFA) and posterior parietal cortex (PPC). For all these areas, linear coupling between electroencephalogram (EEG) and electromyogram (EMG) is present with peaks in the beta band (15–35 Hz), while nonlinear coupling is detected with both integer (1:2, 1:3, 1:4) and non-integer (2:3) harmonics. Significant differences between brain areas is shown in linear coupling with stronger coherence for the primary sensorimotor areas and motor association cortices (SMA, PFA) compared to the sensory association area (PPC); but not for the nonlinear coupling. Moreover, the detected nonlinear coupling is similar to previously reported nonlinear coupling of cortical activity to somatosensory stimuli. We suggest that the descending motor pathways mainly contribute to linear corticomuscular coupling, while nonlinear coupling likely originates from sensory feedback.

Nonlinear Connectivity in the Human Stretch Reflex Assessed by Cross-Frequency Phase Coupling

Communication between neuronal populations is facilitated by synchronization of their oscillatory activity. Although nonlinearity has been observed in the sensorimotor system, its nonlinear connectivity has not been widely investigated yet. This study investigates nonlinear connectivity during the human stretch reflex based on neuronal synchronization. Healthy participants generated isotonic wrist flexion while receiving a periodic mechanical perturbation to the wrist. Using a novel cross-frequency phase coupling metric, we estimate directional nonlinear connectivity, including time delay, from the perturbation to brain and to muscle, as well as from brain to muscle. Nonlinear phase coupling is significantly stronger from the perturbation to the muscle than to the brain, with a shorter time delay. The time delay from the perturbation to the muscle is 33 ms, similar to the reported latency of the spinal stretch reflex at the wrist. Source localization of nonlinear phase coupling from the brain to the muscle suggests activity originating from the motor cortex, although its effect on the stretch reflex is weak. As such nonlinear phase coupling between the perturbation and muscle activity is dominated by the spinal reflex loop. This study provides new evidence of nonlinear neuronal synchronization in the stretch reflex at the wrist joint with respect to spinal and transcortical loops.

Sensory Entrainment Mechanisms in Auditory Perception: Neural Synchronization Cortico-Striatal Activation

The auditory system displays modulations in sensitivity that can align with the temporal structure of the acoustic environment. This sensory entrainment can facilitate sensory perception and is particularly relevant for audition. Systems neuroscience is slowly uncovering the neural mechanisms underlying the behaviorally observed sensory entrainment effects in the human sensory system. The present article summarizes the prominent behavioral effects of sensory entrainment and reviews our current understanding of the neural basis of sensory entrainment, such as synchronized neural oscillations, and potentially, neural activation in the cortico-striatal system.

Quantifying Nonlinear Contributions to Cortical Responses Evoked by Continuous Wrist Manipulation

Cortical responses to continuous stimuli as recorded using either magneto- or electroencephalography (EEG) have shown power at harmonics of the stimulated frequency, indicating nonlinear behavior. Even though the selection of analysis techniques depends on the linearity of the system under study, the importance of nonlinear contributions to cortical responses has not been formally addressed. The goal of this paper is to quantify the nonlinear contributions to the cortical response obtained from continuous sensory stimulation. EEG was used to record the cortical response evoked by continuous movement of the wrist joint of healthy subjects applied with a robotic manipulator. Multisine stimulus signals (i.e., the sum of several sinusoids) elicit a periodic cortical response and allow to assess the nonlinear contributions to the response. Wrist dynamics (relation between joint angle and torque) were successfully linearized, explaining 99% of the response. In contrast, the cortical response revealed a highly nonlinear relation; where most power (  ∼ 80 %) occurred at non-stimulated frequencies. Moreover, only 10% of the response could be explained using a nonparametric linear model. These results indicate that the recorded evoked cortical responses are governed by nonlinearities and that linear methods do not suffice when describing the relation between mechanical stimulus and cortical response.

Change in Mean Frequency of Resting-State Electroencephalography after Transcranial Direct Current Stimulation

Transcranial direct current stimulation (tDCS) is proposed as a tool to investigate cognitive functioning in healthy people and as a treatment for various neuropathological disorders. However, the underlying cortical mechanisms remain poorly understood. We aim to investigate whether resting-state electroencephalography (EEG) can be used to monitor the effects of tDCS on cortical activity. To this end we tested whether the spectral content of ongoing EEG activity is significantly different after a single session of active tDCS compared to sham stimulation. Twenty participants were tested in a sham-controlled, randomized, crossover design. Resting-state EEG was acquired before, during and after active tDCS to the left dorsolateral prefrontal cortex (15 min of 2 mA tDCS) and sham stimulation. Electrodes with a diameter of 3.14 cm² were used for EEG and tDCS. Partial least squares (PLS) analysis was used to examine differences in power spectral density (PSD) and the EEG mean frequency to quantify the slowing of EEG activity after stimulation. PLS revealed a significant increase in spectral power at frequencies below 15 Hz and a decrease at frequencies above 15 Hz after active tDCS (P = 0.001). The EEG mean frequency was significantly reduced after both active tDCS (P < 0.0005) and sham tDCS (P = 0.001), though the decrease in mean frequency was smaller after sham tDCS than after active tDCS (P = 0.073). Anodal tDCS of the left DLPFC using a high current density bi-frontal electrode montage resulted in general slowing of resting-state EEG. The similar findings observed following sham stimulation question whether the standard sham protocol is an appropriate control condition for tDCS.

EEG frequency tagging to explore the cortical activity related to the tactile exploration of natural textures

When sliding our fingertip against a textured surface, complex vibrations are produced in the skin. It is increasingly recognised that the neural transduction and processing of these vibrations plays an important role in the dynamic tactile perception of textures. The aim of the present study was to develop a novel means to tag the cortical activity related to the processing of these vibrations, by periodically modulating the amplitude of texture exploration-induced vibrations such as to record a steady-state evoked potential (SS-EP). The EEG was recorded while the right index fingertip was scanned against four different textures using a constant exploration velocity. Amplitude modulation of the elicited vibrations was achieved by periodically modulating the force applied against the finger. Frequency analysis of the recorded EEG signals showed that modulation of the vibrations induced by the fingertip-texture interactions elicited an SS-EP at the frequency of modulation (3 Hz) as well as its second harmonic (6 Hz), maximal over parietal regions contralateral to the stimulated side. Textures generating stronger vibrations also generated SS-EPs of greater magnitude. Our results suggest that frequency tagging using SS-EPs can be used to isolate and explore the brain activity related to the tactile exploration of natural textures.

A General Approach for Quantifying Nonlinear Connectivity in the Nervous System Based on Phase Coupling

Interaction between distant neuronal populations is essential for communication within the nervous system and can occur as a highly nonlinear process. To better understand the functional role of neural interactions, it is important to quantify the nonlinear connectivity in the nervous system. We introduce a general approach to measure nonlinear connectivity through phase coupling: the multi-spectral phase coherence (MSPC). Using simulated data, we compare MSPC with existing phase coupling measures, namely n : m synchronization index and bi-phase locking value. MSPC provides a system description, including (i) the order of the nonlinearity, (ii) the direction of interaction, (iii) the time delay in the system, and both (iv) harmonic and (v) intermodulation coupling beyond the second order; which are only partly revealed by other methods. We apply MSPC to analyze data from a motor control experiment, where subjects performed isotonic wrist flexions while receiving movement perturbations. MSPC between the perturbation, EEG and EMG was calculated. Our results reveal directional nonlinear connectivity in the afferent and efferent pathways, as well as the time delay (43 ± 8 ms) between the perturbation and the brain response. In conclusion, MSPC is a novel approach capable to assess high-order nonlinear interaction and timing in the nervous system.

Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously--elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding 'feeder' cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale

Functional connectivity is abnormal in autism, but the nature of these abnormalities remains elusive. Different studies, mostly using functional magnetic resonance imaging, have found increased, decreased, or even mixed pattern functional connectivity abnormalities in autism, but no unifying framework has emerged to date. We measured functional connectivity in individuals with autism and in controls using magnetoencephalography, which allowed us to resolve both the directionality (feedforward versus feedback) and spatial scale (local or long-range) of functional connectivity. Specifically, we measured the cortical response and functional connectivity during a passive 25-Hz vibrotactile stimulation in the somatosensory cortex of 20 typically developing individuals and 15 individuals with autism, all males and right-handed, aged 8-18, and the mu-rhythm during resting state in a subset of these participants (12 per group, same age range). Two major significant group differences emerged in the response to the vibrotactile stimulus. First, the 50-Hz phase locking component of the cortical response, generated locally in the primary (S1) and secondary (S2) somatosensory cortex, was reduced in the autism group (P < 0.003, corrected). Second, feedforward functional connectivity between S1 and S2 was increased in the autism group (P < 0.004, corrected). During resting state, there was no group difference in the mu-α rhythm. In contrast, the mu-β rhythm, which has been associated with feedback connectivity, was significantly reduced in the autism group (P < 0.04, corrected). Furthermore, the strength of the mu-β was correlated to the relative strength of 50 Hz component of the response to the vibrotactile stimulus (r = 0.78, P < 0.00005), indicating a shared aetiology for these seemingly unrelated abnormalities. These magnetoencephalography-derived measures were correlated with two different behavioural sensory processing scores (P < 0.01 and P < 0.02 for the autism group, P < 0.01 and P < 0.0001 for the typical group), with autism severity (P < 0.03), and with diagnosis (89% accuracy). A biophysically realistic computational model using data driven feedforward and feedback parameters replicated the magnetoencephalography data faithfully. The direct observation of both abnormally increased and abnormally decreased functional connectivity in autism occurring simultaneously in different functional connectivity streams, offers a potential unifying framework for the unexplained discrepancies in current findings. Given that cortical feedback, whether local or long-range, is intrinsically non-linear, while cortical feedforward is generally linear relative to the stimulus, the present results suggest decreased non-linearity alongside an increased veridical component of the cortical response in autism.

Neuromagnetic beta and gamma oscillations in the somatosensory cortex after music training in healthy older adults and a chronic stroke patient

OBJECTIVE

Extensive rehabilitation training can lead to functional improvement even years after a stroke. Although neuronal plasticity is considered as a main origin of such ameliorations, specific subtending mechanisms need further investigation. Our aim was to obtain objective neuromagnetic measures sensitive to brain reorganizations induced by a music-supported training.

METHODS

We applied 20-Hz vibrotactile stimuli to the index finger and the ring finger, recorded somatosensory steady-state responses with magnetoencephalography, and analyzed the cortical sources displaying oscillations synchronized with the external stimuli in two groups of healthy older adults before and after musical training or without training. In addition, we applied the same analysis for an anecdotic report of a single chronic stroke patient with hemiparetic arm and hand problems, who received music-supported therapy (MST).

RESULTS

Healthy older adults showed significant finger separation within the primary somatotopic map. Beta dipole sources were more anterior located compared to gamma sources. An anterior shift of sources and increases in synchrony between the stimuli and beta and gamma oscillations were observed selectively after music training. In the stroke patient a normalization of somatotopic organization was observed after MST, with digit separation recovered after training and stimulus induced gamma synchrony increased.

CONCLUSIONS

The proposed stimulation paradigm captures the integrity of primary somatosensory hand representation. Source position and synchronization between the stimuli and gamma activity are indices, sensitive to music-supported training. Responsiveness was also observed in a chronic stroke patient, encouraging for the music-supported therapy. Notably, changes in somatosensory responses were observed, even though the therapy did not involve specific sensory discrimination training.

SIGNIFICANCE

The proposed protocol can be used for monitoring changes in neuronal organization during training and will improve the understanding of the brain mechanisms underlying rehabilitation.

Concurrent visual and tactile steady-state evoked potentials index allocation of inter-modal attention: a frequency-tagging study

We investigated effects of inter-modal attention on concurrent visual and tactile stimulus processing by means of stimulus-driven oscillatory brain responses, so-called steady-state evoked potentials (SSEPs). To this end, we frequency-tagged a visual (7.5Hz) and a tactile stimulus (20Hz) and participants were cued, on a trial-by-trial basis, to attend to either vision or touch to perform a detection task in the cued modality. SSEPs driven by the stimulation comprised stimulus frequency-following (i.e. fundamental frequency) as well as frequency-doubling (i.e. second harmonic) responses. We observed that inter-modal attention to vision increased amplitude and phase synchrony of the fundamental frequency component of the visual SSEP while the second harmonic component showed an increase in phase synchrony, only. In contrast, inter-modal attention to touch increased SSEP amplitude of the second harmonic but not of the fundamental frequency, while leaving phase synchrony unaffected in both responses. Our results show that inter-modal attention generally influences concurrent stimulus processing in vision and touch, thus, extending earlier audio-visual findings to a visuo-tactile stimulus situation. The pattern of results, however, suggests differences in the neural implementation of inter-modal attentional influences on visual vs. tactile stimulus processing.

Dissociation of psychophysical and EEG steady-state response measures of cross-modal temporal correspondence for amplitude modulated acoustic and vibrotactile stimulation

Research examining multisensory integration suggests that the correspondence of stimulus characteristics across modalities (cross-modal correspondence) can have a dramatic influence on both neurophysiological and perceptual responses to multimodal stimulation. The current study extends prior research by examining the cross-modal correspondence of amplitude modulation rate for simultaneous acoustic and vibrotactile stimulation using EEG and perceptual measures of sensitivity to amplitude modulation. To achieve this, psychophysical thresholds and steady-state responses (SSRs) were measured for acoustic and vibrotactile amplitude modulated (AM) stimulation for 21 and 40 Hz AM rates as a function of the cross-modal correspondence. The study design included three primary conditions to determine whether the changes in the SSR and psychophysical thresholds were due to the cross-modal temporal correspondence of amplitude modulated stimuli: NONE (AM in one modality only), SAME (the same AM rate for each modality) and DIFF (different AM rates for each modality). The results of the psychophysical analysis showed that AM detection thresholds for the simultaneous AM conditions (i.e., SAME and DIFF) were significantly higher (i.e., lower sensitivity) than AM detection thresholds for the stimulation of a single modality (i.e., NONE). SSR results showed significant effects of SAME and DIFF conditions on SSR activity. The different pattern of results for perceptual and SSR measures of cross-modal correspondence of AM rate indicates a dissociation between entrained cortical activity (i.e., SSR) and perception.

Quantifying connectivity via efferent and afferent pathways in motor control using coherence measures and joint position perturbations

The applicability of corticomuscular coherence (CMC) as a connectivity measure is limited since only 40-50 % of the healthy population presents significant CMC. In this study, we applied continuous joint position perturbations to obtain a more reliable measure of connectivity in motor control. We evaluated the coherence between joint position perturbations and EEG (position-cortical coherence, PCC) and CMC. Healthy subjects performed two isotonic force tasks against the handle of a wrist manipulator. The baseline task was isometric; in the perturbed task, the handle moved continuously with small amplitude. The position perturbation signal covered frequencies between 5 and 29 Hz. In the perturbed task, all subjects had significant PCC and 86 % of the subjects had significant CMC, on both stimulus and non-stimulus frequencies. In the baseline task, CMC was present in only 45 % of the subjects, mostly on beta-band frequencies. The position perturbations during an isotonic force task elicited PCC in all subjects and elicited CMC in most subjects on both stimulus and non-stimulus frequencies. Perturbed CMC possibly arises by two separate processes: an intrinsic process, similar to the process in an unperturbed task, involving both efferent and afferent pathways; and a process related to the excitation of the afferent and efferent pathways by the perturbation. These processes cannot be separated. PCC, however, reflects connectivity via the afferent pathways only. As PCC was present in all healthy subjects, we propose this coherence as a reliable measure for connectivity in motor control via the afferent pathways.

Effects of mnemonic load on cortical activity during visual working memory: linking ongoing brain activity with evoked responses

The mechanisms generating task-locked changes in cortical potentials remain poorly understood, despite a wealth of research. It has recently been proposed that ongoing brain oscillations are not symmetric, so that task-related amplitude modulations generate a baseline shift that does not average out, leading to slow event-related potentials. We test this hypothesis using multivariate methods to formally assess the co-variation between task-related evoked potentials and spectral changes in scalp EEG during a visual working memory task, which is known to elicit both evoked and sustained cortical activities across broadly distributed cortical regions. 64-channel EEG data were acquired from eight healthy human subjects who completed a visuo-spatial associative working memory task as memory load was parametrically increased from easy to hard. As anticipated, evoked activity showed a complex but robust spatio-temporal waveform maximally expressed bilaterally in the parieto-occipital and anterior midline regions, showing robust effects of memory load that were specific to the stage of the working memory trial. Similarly, memory load was associated with robust spectral changes in the theta and alpha range, throughout encoding in posterior regions and through maintenance and retrieval in anterior regions, consistent with the additional resources required for decision making in prefrontal cortex. Analysis of the relationship between event-related changes in slow potentials and cortical rhythms, using partial least squares, is indeed consistent with the notion that the former make a causal contribution to the latter.

Phase-locked cluster oscillations in periodically forced integrate-and-fire-or-burst neuronal populations

The minimal integrate-and-fire-or-burst neuron model succinctly describes both tonic firing and postinhibitory rebound bursting of thalamocortical cells in the sensory relay. Networks of integrate-and-fire-or-burst (IFB) neurons with slow inhibitory synaptic interactions have been shown to support stable rhythmic states, including globally synchronous and cluster oscillations, in which network-mediated inhibition cyclically generates bursting in coherent subgroups of neurons. In this paper, we introduce a reduced IFB neuronal population model to study synchronization of inhibition-mediated oscillatory bursting states to periodic excitatory input. Using numeric methods, we demonstrate the existence and stability of 1:1 phase-locked bursting oscillations in the sinusoidally forced IFB neuronal population model. Phase locking is shown to arise when periodic excitation is sufficient to pace the onset of bursting in an IFB cluster without counteracting the inhibitory interactions necessary for burst generation. Phase-locked bursting states are thus found to destabilize when periodic excitation increases in strength or frequency. Further study of the IFB neuronal population model with pulse-like periodic excitatory input illustrates that this synchronization mechanism generalizes to a broad range of n:m phase-locked bursting states across both globally synchronous and clustered oscillatory regimes.

Synchronization of β and γ oscillations in the somatosensory evoked neuromagnetic steady-state response

The sensory evoked neuromagnetic response consists of superimposition of an immediately stimulus-driven component and induced changes in the autonomous brain activity, each having distinct functional relevance. Commonly, the strength of phase locking in neural activities has been used to differentiate the different responses. The steady-state response is a strong oscillatory neural activity, which is evoked with rhythmic stimulation, and provides an effective tool to investigate oscillatory brain networks. In this case, both the sensory response and intrinsic activity, representing higher order processes, are highly synchronized to the stimulus. In this study we hypothesized that temporal dynamics of oscillatory activities would characterize the differences between the two types of activities and that beta and gamma oscillations are differently involved in this distinction. We used magnetoencephalography (MEG) for studying how ongoing steady-state responses elicited by a 20-Hz vibro-tactile stimulus to the right index finger were affected by a concurrent isolated touch stimulus to the same hand ring finger. SI source activity showed oscillations at multiples of 20 Hz with characteristic differences in the beta band and the gamma band. The response amplitudes were largest at 20 Hz (beta) and significantly reduced at 40 Hz and 60 Hz (gamma), although synchronization strength, indicated by inter-trial coherence (ITC), did not substantially differ between 20 Hz and 40 Hz. Moreover, the beta oscillations showed a fast onset, whereas the amplitude of gamma oscillations increased slowly and reached the steady state 400 ms after onset of the vibration stimulus. Most importantly, the pulse stimuli interacted only with gamma oscillations in a way that gamma oscillations decreased immediately after the concurrent stimulus onset and recovered slowly, resembling the initial slope. Such time course of gamma oscillations is similar to our previous observations in the auditory system. The time constant is in line with the time required for conscious perception of the sensory stimulus. Based on the observed different spectro-temporal dynamics, we propose that while beta activities likely relate to independent representation of the sensory input, gamma oscillation likely relates to binding of sensory information for higher order processing.

A canonical model of multistability and scale-invariance in biological systems

Multistability and scale-invariant fluctuations occur in a wide variety of biological organisms from bacteria to humans as well as financial, chemical and complex physical systems. Multistability refers to noise driven switches between multiple weakly stable states. Scale-invariant fluctuations arise when there is an approximately constant ratio between the mean and standard deviation of a system's fluctuations. Both are an important property of human perception, movement, decision making and computation and they occur together in the human alpha rhythm, imparting it with complex dynamical behavior. Here, we elucidate their fundamental dynamical mechanisms in a canonical model of nonlinear bifurcations under stochastic fluctuations. We find that the co-occurrence of multistability and scale-invariant fluctuations mandates two important dynamical properties: Multistability arises in the presence of a subcritical Hopf bifurcation, which generates co-existing attractors, whilst the introduction of multiplicative (state-dependent) noise ensures that as the system jumps between these attractors, fluctuations remain in constant proportion to their mean and their temporal statistics become long-tailed. The simple algebraic construction of this model affords a systematic analysis of the contribution of stochastic and nonlinear processes to cortical rhythms, complementing a recently proposed biophysical model. Similar dynamics also occur in a kinetic model of gene regulation, suggesting universality across a broad class of biological phenomena.

Biological systems are able to adapt to rapidly and widely changing environments. Many biological organisms employ two distinct mechanisms that improve their survival in these circumstances: Firstly they exhibit rapid, qualitative changes in their internal dynamics; secondly they possess the ability to respond to change that is not absolute, but scales in proportion to the underlying intensity of the environment. In this paper, we study a simple class of noisy, dynamical systems that mathematically represent a very broad range of more complex models. We hence show how a combination of nonlinear instabilities and state-dependent noise in this model is able to unify these two apparently distinct biological phenomena. To illustrate its unifying potential, this simple model is applied to two very distinct biological processes – the spontaneous activity of the human cortex (i.e. when subjects are at rest), and genetic regulation in a bacteriophage. We also provide proof of principle that our model can be inverted from empirical data, allowing estimation of the parameters that express the nonlinear and stochastic influences at play in the underlying system.

Temporal dynamics of primary motor cortex γ oscillation amplitude and piper corticomuscular coherence changes during motor control

In recent years, the use of non-invasive techniques (EEG/MEG) to measure the ~80 Hz ("gamma") oscillations generated by the primary motor cortex during motor control has been well validated. However, primary motor cortex gamma oscillations have yet to be systematically compared with lower frequency (30-50 Hz, 'piper') corticomuscular coherence in the same tasks. In this paper, primary cortex gamma oscillations and piper corticomuscular coherence are compared for three types of movements: simple abductions of the index finger, repetitive abductions of the index finger of different extents and frequencies and static abduction of the index finger at two different force levels. For simple movements, piper coherence and gamma amplitude followed very similar time courses with coherence appearing at approximately half the frequency of cortical gamma oscillations. No evidence of 2:1 phase-phase coupling was observed. A similar pattern of results was observed for repetitive movements varying in size and frequency; however, during the production of static force, the time courses became dissociated. During these movements, EMG piper amplitude was sustained for the entire contraction; gamma power showed a burst at onset but no piper corticomuscular coherence was observed. For these data, this dissociation suggests that while primary motor cortex gamma oscillations and piper corticomuscular coherence may often co-occur during the production of dynamic movements, they probably reflect different functional processes in motor control.

BrainModes: the role of neuronal oscillations in health and disease

The core idea of complexity science--namely how macroscopic phenomena emerge from the interactions between microscopic quantities--is particularly relevant to the study of the human brain. It is in this context that the term "BrainModes" was adopted to explore how cooperative phenomena (or 'modes' of activity) occurring at one spatial or temporal scale give rise to coherent structures at other scales. This Special Issue reports the 2009 BrainModes Workshop, held in Bristol (December 2009) which focussed on the fusion of theoretical, computational, experimental and clinical methods for enhancing our understanding of the role played by neuronal oscillations in healthy and diseased brain states.