Steady-state vibration somatosensory evoked potentials: physiological characteristics and tuning function

Road safety: The influence of vibration frequency on driver drowsiness, reaction time, and driving performance

Driver drowsiness is a factor in at least 20% of serious motor vehicle accidents. Although research has shown that Whole-Body Vibration (WBV) can induce drowsiness in drivers, it is unknown whether particular frequencies are more problematic. The present study systematically investigated the influence of WBV frequency on driver drowsiness. Fifteen participants each undertook six 1-h sessions of simulated driving while being subjected to WBV of either 0 Hz (no vibration), 1-4 Hz, 4-8 Hz, 8-16 Hz, 16-32 Hz or 32-64 Hz. Subjective sleepiness, as measured by the Karolinska Sleepiness Scale (KSS), confirmed that drivers felt drowsier when exposed to the two lowest frequency ranges (1-4 Hz and 4-8 Hz). Reaction time, which measures attention and alertness, was significantly impaired by the two lowest frequency ranges. Objective driving performance measures (Standard Deviation of Lane Position (SDLP), Standard Deviation of (SD) Steering Angle, Time in Unsafe Zone) also showed significant degradation due to exposure to the two lowest frequency ranges. Exposure to 1-4 Hz or 4-8 Hz vibration caused attention to become significantly impaired within 15-20 min and driving performance to be significantly impaired by 30-35 min. The other frequency ranges had little or no effect. These findings point to a need to develop equivalent vibration-induced drowsiness contours that can be adopted as transportation safety standards.

Somatosensory input in the context of transcranial magnetic stimulation coupled with electroencephalography: An evidence-based overview

The transcranial evoked potential (TEP) is a powerful technique to investigate brain dynamics, but some methodological issues limit its interpretation. A possible contamination of the TEP by electroencephalographic (EEG) responses evoked by the somatosensory input generated by transcranial magnetic stimulation (TMS) has been postulated; nonetheless, a characterization of these responses is lacking. The aim of this work was to review current evidence about possible somatosensory evoked potentials (SEP) induced by sources of somatosensory input in the craniofacial region. Among these, only contraction of craniofacial muscle and stimulation of free cutaneous nerve endings may be able to induce EEG responses, but direct evidence is lacking due to experimental difficulties in isolating these inputs. Notably, EEG evoked activity in this context is represented by a N100/P200 complex, reflecting a saliency-related multimodal response, rather than specific activation of the primary somatosensory cortex. Strategies to minimize or remove these responses by EEG processing still yield uncertain results; therefore, data inspection is of paramount importance to judge a possible contamination of the TEP by multimodal potentials caused by somatosensory input.

Bayesian analysis of phase data in EEG and MEG

Electroencephalography and magnetoencephalography recordings are non-invasive and temporally precise, making them invaluable tools in the investigation of neural responses in humans. However, these recordings are noisy, both because the neuronal electrodynamics involved produces a muffled signal and because the neuronal processes of interest compete with numerous other processes, from blinking to day-dreaming. One fruitful response to this noisiness has been to use stimuli with a specific frequency and to look for the signal of interest in the response at that frequency. Typically this signal involves measuring the coherence of response phase: here, a Bayesian approach to measuring phase coherence is described. This Bayesian approach is illustrated using two examples from neurolinguistics and its properties are explored using simulated data. We suggest that the Bayesian approach is more descriptive than traditional statistical approaches because it provides an explicit, interpretable generative model of how the data arises. It is also more data-efficient: it detects stimulus-related differences for smaller participant numbers than the standard approach.

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.

Novel electrotactile brain-computer interface with somatosensory event-related potential based control

Objective

A brain computer interface (BCI) allows users to control external devices using non-invasive brain recordings, such as electroencephalography (EEG). We developed and tested a novel electrotactile BCI prototype based on somatosensory event-related potentials (sERP) as control signals, paired with a tactile attention task as a control paradigm.

Approach

A novel electrotactile BCI comprises commercial EEG device, an electrical stimulator and custom software for EEG recordings, electrical stimulation control, synchronization between devices, signal processing, feature extraction, selection, and classification. We tested a novel BCI control paradigm based on tactile attention on a sensation at a target stimulation location on the forearm. Tactile stimuli were electrical pulses delivered at two proximal locations on the user's forearm for stimulating branches of radial and median nerves, with equal probability of the target and distractor stimuli occurrence, unlike in any other ERP-based BCI design. We proposed a compact electrical stimulation electrodes configuration for delivering electrotactile stimuli (target and distractor) using 2 stimulation channels and 3 stimulation electrodes. We tested the feasibility of a single EEG channel BCI control, to determine pseudo-online BCI performance, in ten healthy subjects. For optimizing the BCI performance we compared the results for two classifiers, sERP averaging approaches, and novel dedicated feature extraction/selection methods via cross-validation procedures.

Main results

We achieved a single EEG channel BCI classification accuracy in the range of 75.1 to 88.1% for all subjects. We have established an optimal combination of: single trial averaging to obtain sERP, feature extraction/selection methods and classification approach.

Significance

The obtained results demonstrate that a novel electrotactile BCI paradigm with equal probability of attended (target) and unattended (distractor) stimuli and proximal stimulation sites is feasible. This method may be used to drive restorative BCIs for sensory retraining in stroke or brain injury, or assistive BCIs for communication in severely disabled users.

Reducing the Calibration Time in Somatosensory BCI by Using Tactile ERD

OBJECTIVE

We propose a tactile-induced-oscillation approach to reduce the calibration time in somatosensory brain-computer interfaces (BCI).

METHODS

Based on the similarity between tactile induced event-related desynchronization (ERD) and imagined sensation induced ERD activation, we extensively evaluated BCI performance when using a conventional and a novel calibration strategy. In the conventional calibration, the tactile imagined data was used, while in the sensory calibration model sensory stimulation data was used. Subjects were required to sense the tactile stimulus when real tactile was applied to the left or right wrist and were required to perform imagined sensation tasks in the somatosensory BCI paradigm.

RESULTS

The sensory calibration led to a significantly better performance than the conventional calibration when tested on the same imagined sensation dataset ( [Formula: see text]=10.89, P=0.0038), with an average 5.1% improvement in accuracy. Moreover, the sensory calibration was 39.3% faster in reaching a performance level of above 70% accuracy.

CONCLUSION

The proposed approach of using tactile ERD from the sensory cortex provides an effective way of reducing the calibration time in a somatosensory BCI system.

SIGNIFICANCE

The tactile stimulation would be specifically useful before BCI usage, avoiding excessive fatigue when the mental task is difficult to perform. The tactile ERD approach may find BCI applications for patients or users with preserved afferent pathways.

Developmental experiences alter the temporal processing characteristics of the visual cortex: Evidence from deaf and hearing native signers

To date, the extent to which early experience shapes the functional characteristics of neural circuits is still a matter of debate. In the present study, we tested whether congenital deafness and/or the acquisition of a sign language alter the temporal processing characteristics of the visual system. Moreover, we investigated whether, assuming cross-modal plasticity in deaf individuals, the temporal processing characteristics of possibly reorganised auditory areas resemble those of the visual cortex. Steady-state visual evoked potentials (SSVEPs) were recorded in congenitally deaf native signers, hearing native signers, and hearing nonsigners. The luminance of the visual stimuli was periodically modulated at 12, 21, and 40 Hz. For hearing nonsigners, the optimal driving rate was 12 Hz. By contrast, for the group of hearing signers the optimal driving rate was 12 and 21 Hz, whereas for the group of deaf signers the optimal driving rate was 21 Hz. We did not observe evidence for cross-modal recruitment of auditory cortex in the group of deaf signers. These results suggest a higher preferred neural processing rate as a consequence of the acquisition of a sign language.

Individual Optimal Attentional Strategy in Motor Learning Tasks Characterized by Steady-State Somatosensory and Visual Evoked Potentials

Focus of attention is one of the most influential factors facilitating motor performance. Previous evidence supports that the external focus (EF) strategy, which directs attention to movement outcomes, is associated with better motor performance than the internal focus (IF) strategy, which directs attention to body movements. However, recent studies have reported that the EF strategy is not effective for some individuals. Furthermore, neuroimaging studies have demonstrated that the frontal and parietal areas characterize individual optimal attentional strategies for motor tasks. However, whether the sensory cortices are also functionally related to individual optimal attentional strategy remains unclear. Therefore, the present study examined whether an individual’s sensory processing ability would reflect the optimal attentional strategy. To address this point, we explored the relationship between responses in the early sensory cortex and individuals’ optimal attentional strategy by recording steady-state somatosensory evoked potentials (SSSEP) and steady-state visual evoked potentials (SSVEP). Twenty-six healthy young participants first performed a motor learning task with reaching movements under IF and EF conditions. Of the total sample, 12 individuals showed higher after-effects under the IF condition than the EF condition (IF-dominant group), whereas the remaining individuals showed the opposite trend (EF-dominant group). Subsequently, we measured SSSEP from bilateral primary somatosensory cortices while presenting vibrotactile stimuli and measured SSVEP from bilateral primary visual cortices while presenting checkerboard visual stimuli. The degree of increasing SSSEP response when the individuals in the IF-dominant group directed attention to vibrotactile stimuli was significantly more potent than those in the EF-dominant individuals. By contrast, the individuals in the EF-dominant group showed a significantly larger SSVEP increase while they directed attention to visual stimuli compared with the IF-dominant individuals. Furthermore, a significant correlation was observed such that individuals with more robust IF dominance showed more pronounced SSSEP attention modulation. These results suggest that the early sensory areas have crucial brain dynamics to characterize an individual’s optimal attentional strategy during motor tasks. The response characteristics may reflect the individual sensory processing ability, such as control of priority to the sensory inputs. Considering individual cognitive traits based on the suitable attentional strategy could enhance adaptability in motor tasks.

A modality-specific somatosensory evoked potential test protocol for clinical evaluation: A feasibility study

OBJECTIVE

We aimed to establish an objective neurophysiological test protocol that can be used to assess the somatosensory nervous system.

METHODS

In order to assess most fiber subtypes of the somatosensory nervous system, repetitive stimuli of seven different modalities (touch, vibration, pinprick, cold, contact heat, laser, and warmth) were synchronized with the electroencephalogram (EEG) and applied on the cheek and dorsum of the hand and dorsum of the foot in 21 healthy subjects and three polyneuropathy (PNP) patients. Latencies and amplitudes of the modalities were assessed and compared. Patients received quantitative sensory testing (QST) as reference.

RESULTS

We found reproducible evoked potentials recordings for touch, vibration, pinprick, contact-heat, and laser stimuli. The recording of warm-evoked potentials was challenging in young healthy subjects and not applicable in patients. Latencies were shortest within Aβ-fiber-mediated signals and longest within C-fibers. The test protocol detected function loss within the Aβ-fiber and Aδ-fiber-range in PNP patients. This function loss corresponded with QST findings.

CONCLUSION

In this pilot study, we developed a neurophysiological test protocol that can specifically assess most of the somatosensory modalities. Despite technical challenges, initial patient data appear promising regarding a possible future clinical application.

SIGNIFICANCE

Established and custom-made stimulators were combined to assess different fiber subtypes of the somatosensory nervous system using modality-specific evoked potentials.

EEG-based brain-computer interfaces exploiting steady-state somatosensory-evoked potentials: a literature review

A brain-computer interface (BCI) aims to derive commands from the user's brain activity in order to relay them to an external device. To do so, it can either detect a spontaneous change in the mental state, in the so-called 'active' BCIs, or a transient or sustained change in the brain response to an external stimulation, in 'reactive' BCIs. In the latter, external stimuli are perceived by the user through a sensory channel, usually sight or hearing. When the stimulation is sustained and periodical, the brain response reaches an oscillatory steady-state that can be detected rather easily. We focus our attention on electroencephalography-based BCIs (EEG-based BCI) in which a periodical signal, either mechanical or electrical, stimulates the user skin. This type of stimulus elicits a steady-state response of the somatosensory system that can be detected in the recorded EEG. The oscillatory and phase-locked voltage component characterising this response is called a steady-state somatosensory-evoked potential (SSSEP). It has been shown that the amplitude of the SSSEP is modulated by specific mental tasks, for instance when the user focuses their attention or not to the somatosensory stimulation, allowing the translation of this variation into a command. Actually, SSSEP-based BCIs may benefit from straightforward analysis techniques of EEG signals, like reactive BCIs, while allowing self-paced interaction, like active BCIs. In this paper, we present a survey of scientific literature related to EEG-based BCI exploiting SSSEP. Firstly, we endeavour to describe the main characteristics of SSSEPs and the calibration techniques that allow the tuning of stimulation in order to maximise their amplitude. Secondly, we present the signal processing and data classification algorithms implemented by authors in order to elaborate commands in their SSSEP-based BCIs, as well as the classification performance that they evaluated on user experiments.

Behavioral and Neural Dynamics of Interpersonal Synchrony Between Performing Musicians: A Wireless EEG Hyperscanning Study

Interpersonal synchrony refers to the temporal coordination of actions between individuals and is a common feature of social behaviors, from team sport to ensemble music performance. Interpersonal synchrony of many rhythmic (periodic) behaviors displays dynamics of coupled biological oscillators. The current study addresses oscillatory dynamics on the levels of brain and behavior between music duet partners performing at spontaneous (uncued) rates. Wireless EEG was measured from N = 20 pairs of pianists as they performed a melody first in Solo performance (at their spontaneous rate of performance), and then in Duet performances at each partner's spontaneous rate. Influences of partners' spontaneous rates on interpersonal synchrony were assessed by correlating differences in partners' spontaneous rates of Solo performance with Duet tone onset asynchronies. Coupling between partners' neural oscillations was assessed by correlating amplitude envelope fluctuations of cortical oscillations at the Duet performance frequency between observed partners and between surrogate (re-paired) partners, who performed the same melody but at different times. Duet synchronization was influenced by partners' spontaneous rates in Solo performance. The size and direction of the difference in partners' spontaneous rates were mirrored in the size and direction of the Duet asynchronies. Moreover, observed Duet partners showed greater inter-brain correlations of oscillatory amplitude fluctuations than did surrogate partners, suggesting that performing in synchrony with a musical partner is reflected in coupled cortical dynamics at the performance frequency. The current study provides evidence that dynamics of oscillator coupling are reflected in both behavioral and neural measures of temporal coordination during musical joint action.

Reducing False Triggering Caused by Irrelevant Mental Activities in Brain-Computer Interface Based on Motor Imagery

In recent years, the brain-computer interface (BCI) based on motor imagery (MI) has been considered as a potential post-stroke rehabilitation technology. However, the recognition of MI relies on the event-related desynchronization (ERD) feature, which has poor task specificity. Further, there is the problem of false triggering (irrelevant mental activities recognized as the MI of the target limb). In this paper, we discuss the feasibility of reducing the false triggering rate using a novel paradigm, in which the steady-state somatosensory evoked potential (SSSEP) is combined with the MI (MI-SSSEP). Data from the target (right hand MI) and nontarget task (rest) were used to establish the recognition model, and three kinds of interference tasks were used to test the false triggering performance. In the MI-SSSEP paradigm, ERD and SSSEP features modulated by MI could be used for recognition, while in the MI paradigm, only ERD features could be used. The results showed that the false triggering rate of interference tasks with SSSEP features was reduced to 29.3%, which was far lower than the 55.5% seen under the MI paradigm with ERD features. Moreover, in the MI-SSSEP paradigm, the recognition rate of the target and nontarget task was also significantly improved. Further analysis showed that the specificity of SSSEP was significantly higher than that of ERD (p < 0.05), but the sensitivity was not significantly different. These results indicated that SSSEP modulated by MI could more specifically decode the target task MI, and thereby may have potential in achieving more accurate rehabilitation training.

Neuronal correlates of the subjective experience of attention

The effect of top–down attention on stimulus‐evoked responses and alpha oscillations and the association between arousal and pupil diameter are well established. However, the relationship between these indices, and their contribution to the subjective experience of attention, remains largely unknown. Participants performed a sustained (10–30 s) attention task in which rare (10%) targets were detected within continuous tactile stimulation (16 Hz). Trials were followed by attention ratings on an 8‐point visual scale. Attention ratings correlated negatively with contralateral somatosensory alpha power and positively with pupil diameter. The effect of pupil diameter on attention ratings extended into the following trial, reflecting a sustained aspect of attention related to vigilance. The effect of alpha power did not carry over to the next trial and furthermore mediated the association between pupil diameter and attention ratings. Variations in steady‐state amplitude reflected stimulus processing under the influence of alpha oscillations but were only weakly related to subjective ratings of attention. Together, our results show that both alpha power and pupil diameter are reflected in the subjective experience of attention, albeit on different time spans, while continuous stimulus processing might not contribute to the experience of attention.

Inter-stimulus phase coherence in steady-state somatosensory evoked potentials and its application in improving the performance of single-channel MI-BCI

Objective. With the development of clinical applications of motor imagery-based brain-computer interfaces (MI-BCIs), a single-channel MI-BCI system that can be easily assembled is an attractive goal. However, due to the low quality of the spectral power features in the traditional MI-BCI paradigm, the recognition performance of current single-channel systems is far lower than that of multi-channel systems, impeding their use in clinical applications.Approach.In this study, the subjects' right and left hands were stimulated simultaneously at different frequencies to induce steady-state somatosensory evoked potentials (SSSEP). Subjects then performed motor imagery (MI) tasks. A new electroencephalography (EEG) index, inter-stimulus phase coherence (ISPC), was built to measure phase desynchronization of SSSEP caused by MI. Then, ISPC is introduced as a feature into left-hand and right-hand MI recognition.Main results.ISPC analysis found that left-handed MI can cause a significant decrease in phase synchronization in contralateral sensorimotor SSSEP, while right-handed MI has little effect on it, and vice versa. Combining ISPC features with traditional spectral power features, the single-channel left-hand versus right-hand MI recognition accuracy reaches 81.0%, which is much higher than that observed with traditional MI paradigms (about 60%).Significance.This work shows that the hybrid MI-SSSEP paradigm can provide more sensitive EEG features to decode motor intentions, demonstrating its potential for clinical applications.

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.

Vibration Alert to the Brain: Evoked and Induced MEG Responses to High-Frequency Vibrotactile Stimuli on the Index Finger of Dominant and Non-dominant Hand

Background: In recent years, vibrotactile haptic feedback technology has been widely used for user interfaces in the mobile devices. Although functional neuroimaging studies have investigated human brain responses to different types of tactile inputs, the neural mechanisms underlying high-frequency vibrotactile perception are still relatively unknown. Our aim was to investigate neuromagnetic brain responses to high-frequency vibrotactile stimulation, using magnetoencephalography (MEG).

Methods: We measured 152-channel whole-head MEG in 30 healthy, right-handed volunteers (aged 20–28 years, 15 females). A total of 300 vibrotactile stimuli were presented at the tip of either the left index finger or the right index finger in two separate sessions. Sinusoidal vibrations at 150 Hz for 200 ms were generated with random inter-stimulus intervals between 1.6 and 2.4 s. Both time-locked analysis and time-frequency analysis were performed to identify peak responses and oscillatory modulations elicited by high-frequency vibrations. The significance of the evoked and induced responses for dominant and non-dominant hand stimulation conditions was statistically tested, respectively. The difference in responses between stimulation conditions was also statistically evaluated.

Results: Prominent peak responses were observed at 56 ms (M50) and at 100 ms (M100) for both stimulation conditions. The M50 response revealed clear dipolar field patterns in the contralateral side with significant cortical activations in the contralateral primary sensorimotor area, whereas the M100 response was not as prominent as the M50. Vibrotactile stimulation induced significant suppression of both alpha (8–12 Hz) and beta (20–30 Hz) band activity during the mid-latency period (0.2–0.4 s), primarily in sensorimotor areas contralateral to the stimulation side. In addition, a significant alpha enhancement effect in posterior regions was accompanied with alpha suppressions in sensorimotor regions. The alpha suppression was observed in a broader distribution of cortical areas for the non-dominant hand stimulation.

Conclusion: Our data demonstrate that high-frequency tactile vibrations, which is known to primarily activate Pacinian corpuscles, elicit somatosensory M50 and M100 responses in the evoked fields and induce modulations of alpha and beta band oscillations during mid-latency periods. Our study is also consistent with that the primary sensorimotor area is significantly involved in the processing of high-frequency vibrotactile information with contralateral dominance.

GABA Modulates Frequency-Dependent Plasticity in Humans

Frequency-dependent reorganization of the primary somatosensory cortex, together with perceptual changes, arises following repetitive sensory stimulation. Here, we investigate the role of GABA in this process. We co-stimulated two finger tips and measured GABA and Glx using magnetic resonance (MR) spectroscopy at the beginning and end of the stimulation. Participants performed a perceptual learning task before and after stimulation. There were 2 sessions with stimulation frequency either at or above the resonance frequency of the primary somatosensory cortex (23 and 39 Hz, respectively). Perceptual learning occurred following above resonance stimulation only, while GABA reduced during this condition. Lower levels of early GABA were associated with greater perceptual learning. One possible mechanism underlying this finding is that cortical disinhibition “unmasks” lateral connections within the cortex to permit adaptation to the sensory environment. These results provide evidence in humans for a frequency-dependent inhibitory mechanism underlying learning and suggest a mechanism-based approach for optimizing neurostimulation frequency.

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In the context of repetitive sensory stimulation, GABA release is frequency dependent

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Stimulating above the resonance frequency of the somatosensory cortex reduces GABA

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Perceptual learning is associated with a reduction in GABA

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Early GABA reduction opens a window for plasticity and learning

Cross-frequency and iso-frequency estimation of functional corticomuscular coupling after stroke

Functional corticomuscular coupling (FCMC) between the brain and muscles has been used for motor function assessment after stroke. Two types, iso-frequency coupling (IFC) and cross-frequency coupling (CFC), are existed in sensory-motor system for healthy people. However, in stroke, only a few studies focused on IFC between electroencephalogram (EEG) and electromyogram (EMG) signals, and no CFC studies have been found. Considering the intrinsic complexity and rhythmicity of the biological system, we first used the wavelet package transformation (WPT) to decompose the EEG and EMG signals into several subsignals with different frequency bands, and then applied transfer entropy (TE) to analyze the IFC and CFC relationship between each pair-wise subsignal. In this study, eight stroke patients and eight healthy people were enrolled. Results showed that both IFC and CFC still existed in stroke patients (EEG → EMG: 1:1, 3:2, 2:1; EMG → EEG: 1:1, 2:1, 2:3, 3:1). Compared with the stroke-unaffected side and healthy controls, the stroke-affected side yielded lower alpha, beta and gamma synchronization (IFC: beta; CFC: alpha, beta and gamma). Further analysis indicated that stroke patients yielded no significant difference of the FCMC between EEG → EMG and EMG → EEG directions. Our study indicated that alpha and beta bands were essential to concentrating and maintaining the motor capacities, and provided a new insight in understanding the propagation and function in the sensory-motor system.

20 Hz Steady-State Response in Somatosensory Cortex During Induction of Tactile Perceptual Learning Through LTP-Like Sensory Stimulation

The induction of synaptic plasticity requires the presence of temporally patterned neural activity. Numerous cellular studies in animals and brain slices have demonstrated that long-term potentiation (LTP) enhances synaptic transmission, which can be evoked by high-frequency intermittent stimulation. In humans, plasticity processes underlying perceptual learning can be reliably induced by repetitive, LTP-like sensory stimulation. These protocols lead to improvement of perceptual abilities parallel to widespread remodeling of cortical processing. However, whether maintained rhythmic cortical activation induced by the LTP-like stimulation is also present during human perceptual learning experiments, remains elusive. To address this question, we here applied a 20 Hz intermittent stimulation protocol for 40 min to the index-, middle- and ring-fingers of the right hand, while continuously recording EEG over the hand representation in primary somatosensory cortex in young adult participants. We find that each train of stimulation initiates a transient series of sensory-evoked potentials which accumulate after about 500 ms into a 20 Hz steady-state response persisting over the entire period of the 2-s-train. During the inter-train interval, no consistent evoked activity can be detected. This response behavior is maintained over the whole 40 min of stimulation without any indication of habituation. However, the early stimulation evoked potentials (SEPs) and the event-related desynchronization (ERD) during the steady-state response change over the 40 min of stimulation. In a second experiment, we demonstrate in a separate cohort of participants that the here-applied pneumatic type of stimulation results in improvement of tactile acuity as typically observed for electrically applied 20 Hz intermittent stimulation. Our data demonstrate that repetitive stimulation using a 20 Hz protocol drives rhythmic activation in the hand representation of somatosensory cortex, which is sustained during the entire stimulation period. At the same time, cortical excitability increases as indicated by altered ERD and SEP amplitudes. Our results, together with previous data underlining the dependence of repetitive sensory stimulation effects on NMDA-receptor activation, support the view that repetitive sensory stimulation elicits LTP-like processes in the cortex, thereby facilitating perceptual learning processes.

Secondary somatosensory area is involved in vibrotactile temporal-structure processing: MEG analysis of slow cortical potential shifts in humans

Purpose: Temporal-structure discrimination is an essential dimension of tactile processing. Exploring object surface by touch generates vibrotactile input with various temporal dynamics, which gives diversity to tactile percepts. Here, we examined whether slow cortical potential shifts (SCPs) (<1 Hz) evoked by long vibrotactile stimuli can reflect active temporal-structure processing.Materials and methods: Vibrotactile-evoked magnetic brain responses were recorded in 10 right-handed healthy volunteers using a piezoelectric-based stimulator and whole-head magnetoencephalography. A series of vibrotactile train stimuli with various temporal structures were delivered to the right index finger. While all trains consisted of identical number (15) of stimuli delivered within a fixed duration (1500 ms), temporal structures were varied by modulating inter-stimulus intervals (ISIs). Participants judged regularity/irregularity of ISI for each train in the active condition, whereas they ignored the stimuli while performing a visual distraction task in the passive condition. We analysed the spatiotemporal features of SCPs and their behaviour using the minimum norm estimates with the dynamic statistical parametric mapping.Results: SCPs were localized to contralateral primary somatosensory area (S1), contralateral superior temporal gyrus, and contralateral as well as ipsilateral secondary somatosensory areas (S2). A significant enhancement of SCPs was observed in the ipsilateral S2 (S2i) in the active condition, whereas such effects were absent in the other regions. We also found a significant larger amplitude difference between the regular- and irregular-stimulus evoked S2i responses during the active condition than during the passive condition.Conclusions: This study suggests that S2 subserves the temporal dimension of vibrotactile processing.

40-Hz Binaural beats enhance training to mitigate the attentional blink

This study investigated whether binaural beat stimulation could accelerate the training outcome in an attentional blink (AB) task. The AB refers to the lapse in detecting a target T2 in rapid serial visual presentation (RSVP) after the identification of a preceding target T1. Binaural beats (BB) are assumed to entrain neural oscillations and support cognitive function. Participants were assigned into two groups and presented with BB sounds while performing the AB task on three subsequent days in a cross-over design. Group A was presented with 40-Hz BB during the first day and 16 Hz during the second day, while the order of beat frequencies was reversed in Group B. No sound was presented on the third day. MEG recordings confirmed a strong entrainment of gamma oscillations during 40-Hz BB stimulation and smaller gamma entrainment with 16-Hz BB. The rhythm of the visual stimulation elicited 10-Hz oscillations in occipital MEG sensors which were of similar magnitude for both BB frequencies. The AB performance did not increase within a session. However, participants improved between sessions, with overall improvement equal in both groups. Group A improved more after the first day than the second day. In contrast, group B gained more from the 40 Hz stimulation on the second day than from 16-Hz stimulation on the first day. Taken together, 40-Hz BB stimulation during training accelerates the training outcome. The improvement becomes evident not immediately, but after consolidation during sleep. Therefore, auditory beats stimulation is a promising method of non-invasive brain stimulation for enhancing training and learning which is well-suited to rehabilitation training.

Electrical stimulation-induced SSSEP as an objective index to evaluate the difference of tactile acuity between the left and right hand

OBJECTIVE

The objective of this study is to propose an objective index to evaluate the difference of tactile acuity between the left and right hand based on steady-state somatosensory evoked potential (SSSEP).

APPROACH

Two kinds of tactile sensations (vibration and pressure) with three levels of intensities (low/medium/high) were evoked on two finger areas of the left or right hand (thumb and index for healthy hands, thumb and index-projected areas for disabled hands) via transcutaneous electrical nerve stimulation (TENS). Three forearm amputees and 13 able-bodied subjects were recruited to discriminate the specific level and area of the applied stimulation. Electroencephalography was adopted to simultaneously record the somatosensory cortex response to TENS. We assessed the discrimination performance (discrimination accuracy rate (AR) and response time (RT)) to quantify the tactile acuity, while the evoked SSSEP was synchronously analyzed. Linear regression analyses were performed between the difference of SSSEP amplitudes and the difference of discrimination performance for the left and right hand stimulation.

MAIN RESULTS

Frequency domain analysis revealed that SSSEP amplitude increased with the increase of the stimulation intensity. There were positive correlations between the difference of SSSEP amplitudes and the difference of ARs for the left and right hand stimulation in the sensations of vibration (R ²  =  0.6389 for able-bodied subjects, R ²  =  0.5328 for amputees) and pressure (R ²  =  0.6102 for able-bodied subjects, R ²  =  0.5452 for amputees), respectively. Significance The SSSEP amplitude could be used as an objective index to evaluate the difference of the tactile acuity between the left and right hand and has the potential to be applied in sensory rehabilitation for amputees or stroke patients.

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.

Centro-parietal EEG potentials index subjective evidence and confidence during perceptual decision making

Recent studies suggest that a centro-parietal positivity (CPP) in the EEG signal tracks the absolute (unsigned) strength of accumulated evidence for choices that require the integration of noisy sensory input. Here, we investigated whether the CPP might also reflect the evidence for decisions based on a quantitative comparison between two sequentially presented stimuli (a signed quantity). We recorded EEG while participants decided whether the latter of two vibrotactile frequencies was higher or lower than the former in six variants of this task (n = 116). To account for biases in sequential comparisons, we applied a behavioral model based on Bayesian inference that estimated subjectively perceived frequency differences. Immediately after the second stimulus, parietal ERPs reflected the signed value of subjectively perceived differences and afterwards their absolute value. Strikingly, the modulation by signed difference was evident in trials without any objective evidence for either choice and correlated with choice-selective premotor beta band amplitudes. Modulations by the absolute strength of subjectively perceived evidence - a direct indicator of task difficulty - exhibited all features of statistical decision confidence. Together, our data suggest that parietal EEG signals first index subjective evidence, and later include a measure of confidence in the context of perceptual decision making.

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.

Performance of Brain-Computer Interfacing Based on Tactile Selective Sensation and Motor Imagery

A large proportion of users do not achieve adequate control using current non-invasive brain-computer interfaces (BCIs). This issue has being coined "BCI-Illiteracy" and is observed among different BCI modalities. Here, we compare the performance and the BCI-illiteracy rate of a tactile selective sensation (SS) and motor imagery (MI) BCI, for a large subject samples. We analyzed 80 experimental sessions from 57 subjects with two-class SS protocols. For SS, the group average performance was 79.8 ± 10.6%, with 43 out of the 57 subjects (75.4%) exceeding the 70% BCI-illiteracy threshold for left- and right-hand SS discrimination. When compared with previous results, this tactile BCI outperformed all other tactile BCIs currently available. We also analyzed 63 experimental sessions from 43 subjects with two-class MI BCI protocols, where the group average performance was 77.2 ± 13.3%, with 69.7% of the subjects exceeding the 70% performance threshold for left- and right-hand MI. For within-subject comparison, the 24 subjects who participated to both the SS and MI experiments, the BCI performance was superior with SS than MI especially in beta frequency band (p < 0.05), with enhanced R² discriminative information in the somatosensory cortex for the SS modality. Both SS and MI showed a functional dissociation between lower alpha ([8 10] Hz) and upper alpha ([10 13] Hz) bands, with BCI performance significantly better in the upper alpha than the lower alpha (p < 0.05) band. In summary, we demonstrated that SS is a promising BCI modality with low BCI illiteracy issue and has great potential in practical applications reaching large population.

tACS motor system effects can be caused by transcutaneous stimulation of peripheral nerves

Transcranial alternating current stimulation (tACS) is a noninvasive neuromodulation method which has been shown to modulate hearing, motor, cognitive and memory function. However, the mechanisms underpinning these findings are controversial, as studies show that the current reaching the cortex may not be strong enough to entrain neural activity. Here, we propose a new hypothesis to reconcile these opposing results: tACS effects are caused by transcutaneous stimulation of peripheral nerves in the skin and not transcranial stimulation of cortical neurons. Rhythmic activity from peripheral nerves then entrains cortical neurons. A series of experiments in rats and humans isolated the transcranial and transcutaneous mechanisms and showed that the reported effects of tACS on the motor system can be caused by transcutaneous stimulation of peripheral nerves. Whether or not the transcutaneous mechanism will generalize to tACS effects on other systems is debatable but should be investigated.

Transcranial alternating current stimulation (tACS) uses weak electrical currents, applied to the head, to modulate brain activity. Here, the authors show that contrary to previous assumptions, the effects of tACS on the brain may be mediated by its effect on peripheral nerves in the skin, not direct.

Oscillatory EEG signatures of postponed somatosensory decisions

In recent electroencephalography (EEG) studies, the vibrotactile frequency comparison task has been used to study oscillatory signatures of perceptual decision making in humans, revealing a choice-selective modulation of premotor upper beta band power shortly before decisions were reported. Importantly, these studies focused on decisions that were (1) indicated immediately after stimulus presentation, and (2) for which a direct motor mapping was provided. Here, we investigated whether the putative beta band choice signal also extends to postponed decisions, and how such a decision signal might be influenced by a response mapping that is dissociated from a specific motor command. We recorded EEG data in two separate experiments, both employing the vibrotactile frequency comparison task with delayed decision reports. In the first experiment, delayed choices were associated with a fixed motor mapping, whereas in the second experiment, choices were mapped onto a color code concealing a specific motor response until the end of the delay phase. In between stimulus presentations, as well as after the second stimulus, prefrontal beta band power indexed stimulus information held in working memory. Beta band power also encoded choices during the response delay, notably, in different cortical areas depending on the provided response mapping. In particular, when decisions were associated with a specific motor mapping, choices were represented in premotor cortices, whereas the color mapping resulted in a choice-selective modulation of beta band power in parietal cortices. Together, our findings imply that how a choice is expressed (i.e., the decision consequence) determines where in the cortical sensorimotor hierarchy an according decision signal is processed.

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.

Rhythmic facilitation of sensory processing: A critical review

Here we review the role of brain oscillations in sensory processing. We examine the idea that neural entrainment of intrinsic oscillations underlies the processing of rhythmic stimuli in the context of simple isochronous rhythms as well as in music and speech. This has been a topic of growing interest over recent years; however, many issues remain highly controversial: how do fluctuations of intrinsic neural oscillations-both spontaneous and entrained to external stimuli-affect perception, and does this occur automatically or can it be actively controlled by top-down factors? Some of the controversy in the literature stems from confounding use of terminology. Moreover, it is not straightforward how theories and findings regarding isochronous rhythms generalize to more complex, naturalistic stimuli, such as speech and music. Here we aim to clarify terminology, and distinguish between different phenomena that are often lumped together as reflecting "neural entrainment" but may actually vary in their mechanistic underpinnings. Furthermore, we discuss specific caveats and confounds related to making inferences about oscillatory mechanisms from human electrophysiological data.

Gamma and Beta Oscillations in Human MEG Encode the Contents of Vibrotactile Working Memory

Ample evidence suggests that oscillations in the beta band represent quantitative information about somatosensory features during stimulus retention. Visual and auditory working memory (WM) research, on the other hand, has indicated a predominant role of gamma oscillations for active WM processing. Here we reconciled these findings by recording whole-head magnetoencephalography during a vibrotactile frequency comparison task. A Braille stimulator presented healthy subjects with a vibration to the left fingertip that was retained in WM for comparison with a second stimulus presented after a short delay. During this retention interval spectral power in the beta band from the right intraparietal sulcus and inferior frontal gyrus (IFG) monotonically increased with the to-be-remembered vibrotactile frequency. In contrast, induced gamma power showed the inverse of this pattern and decreased with higher stimulus frequency in the right IFG. Together, these results expand the previously established role of beta oscillations for somatosensory WM to the gamma band and give further evidence that quantitative information may be processed in a fronto-parietal network.

Effect of sensory attenuation on cortical movement-related oscillations

This study examined the impact of induced sensory deficits on cortical, movement-related oscillations measured using electroencephalography (EEG). We hypothesized that EEG patterns in healthy subjects with induced sensory reduction would be comparable to EEG found after chronic loss of sensory feedback. EEG signals from 64 scalp locations were measured from 10 healthy subjects. Participants dorsiflexed their ankle after prolonged vibration of the tibialis anterior (TA). Beta band time frequency decompositions were calculated using wavelets and compared across conditions. Changes in patterns of movement-related brain activity were observed following attenuation of sensory feedback. A significant decrease in beta power of event-related synchronization was associated with simple ankle dorsiflexion after prolonged vibration of the TA. Attenuation of sensory feedback in young, healthy subjects led to a corresponding decrease in beta band synchronization. This temporary change in beta oscillations suggests that these modulations are a mechanism for sensorimotor integration. The loss of sensory feedback found in spinal cord injury patients contributes to changes in EEG signals underlying motor commands. Similar alterations in cortical signals in healthy subjects with reduced sensory feedback implies these changes reflect normal sensorimotor integration after reduced sensory input rather than brain plasticity. NEW & NOTEWORTHY Transient attenuation of sensory afferents in young, healthy adults led to similar changes in brain activity found previously in volunteers with incomplete spinal cord injury. Beta band power associated with ankle movement in these controls was attenuated after prolonged vibration of the tibialis anterior. Evoked potential measurements suggest that prolonged vibration reduces phasing across trials as the mechanism behind this attenuation of cortical activity.

Decoding Covert Somatosensory Attention by a BCI System Calibrated With Tactile Sensation

OBJECTIVE

We propose a novel calibration strategy to facilitate the decoding of covert somatosensory attention by exploring the oscillatory dynamics induced by tactile sensation.

METHODS

It was hypothesized that the similarity of the oscillatory pattern between stimulation sensation (SS, real sensation) and somatosensory attentional orientation (SAO) provides a way to decode covert somatic attention. Subjects were instructed to sense the tactile stimulation, which was applied to the left (SS-L) or the right (SS-R) wrist. The brain-computer interface (BCI) system was calibrated with the sensation data and then applied for online SAO decoding.

RESULTS

Both SS and SAO showed oscillatory activation concentrated on the contralateral somatosensory hemisphere. Offline analysis showed that the proposed calibration method led to a greater accuracy than the traditional calibration method based on SAO only. This is confirmed by online experiments, where the online accuracy on 15 subjects was 78.8 ± 13.1%, with 12 subjects >70% and 4 subject >90%.

CONCLUSION

By integrating the stimulus-induced oscillatory dynamics from sensory cortex, covert somatosensory attention can be reliably decoded by a BCI system calibrated with tactile sensation.

SIGNIFICANCE

Indeed, real tactile sensation is more consistent during calibration than SAO. This brain-computer interfacing approach may find application for stroke and completely locked-in patients with preserved somatic sensation.

Evidence for frequency-dependent cortical plasticity in the human brain

Frequency-dependent plasticity (FDP) describes adaptation at the synapse in response to stimulation at different frequencies. Its consequence on the structure and function of cortical networks is unknown. We tested whether cortical "resonance," favorable stimulation frequencies at which the sensory cortices respond maximally, influenced the impact of FDP on perception, functional topography, and connectivity of the primary somatosensory cortex using psychophysics and functional imaging (fMRI). We costimulated two digits on the hand synchronously at, above, or below the resonance frequency of the somatosensory cortex, and tested subjects' accuracy and speed on tactile localization before and after costimulation. More errors and slower response times followed costimulation at above- or below-resonance, respectively. Response times were faster after at-resonance costimulation. In the fMRI, the cortical representations of the two digits costimulated above-resonance shifted closer, potentially accounting for the poorer performance. Costimulation at-resonance did not shift the digit regions, but increased the functional coupling between them, potentially accounting for the improved response time. To relate these results to synaptic plasticity, we simulated a network of oscillators incorporating Hebbian learning. Two neighboring patches embedded in a cortical sheet, mimicking the two digit regions, were costimulated at different frequencies. Network activation outside the stimulated patches was greatest at above-resonance frequencies, reproducing the spread of digit representations seen with fMRI. Connection strengths within the patches increased following at-resonance costimulation, reproducing the increased fMRI connectivity. We show that FDP extends to the cortical level and is influenced by cortical resonance.

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.

A Multi-Class Tactile Brain-Computer Interface Based on Stimulus-Induced Oscillatory Dynamics

We proposed a multi-class tactile brain-computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory attention can modulate tactile-induced oscillation changes, which can decode different sensation attention tasks. Subjects performed four tactile attention tasks, prompted by cues presented in random order and while both wrists were simultaneously stimulated: 1) selective sensation on left hand (SS-L); 2) selective sensation on right hand (SS-R); 3) bilateral selective sensation; and 4) selective sensation suppressed or idle state (SS-S). The classification accuracy between SS-L and SS-R (79.9 ± 8.7%) was comparable with that of a previous tactile BCI system based on selective sensation. Moreover, the accuracy could be improved to an average of 90.3 ± 4.9% by optimal class-pair and frequency-band selection. Three-class discrimination had an accuracy of 75.2 ± 8.3%, with the best discrimination reached for the classes SS-L, SS-R, and SS-S. Finally, four classes were classified with an accuracy of 59.4 ± 7.3%. These results show that the proposed system is a promising new paradigm for multi-class BCI.

Cortical oscillatory dynamics of tactile selective sensation - for a novel type of somatosensory Brain-computer Interface

In this study, cortical oscillatory dynamics with respect to tactile selective sensation tasks were investigated. Subjects were required to perform three tactile attention tasks, prompted by cues presented in random order and while both wrists were simultaneously stimulated: 1) selective sensation of the left hand (SS-L), 2) selective sensation of the right hand (SS-R), 3) bilateral selective sensation (SS-B). Even-related (de)synchronization (ERD/ERS) analysis revealed a clear contralateral activation of somatosensory cortex during the SS-L and SS-R tasks, and a bilateral activation during SS-B tasks. Additionally, we found a clear ERS in occipital region of the brain during all the SS tasks. Diverse activation pattern among SS-L, SS-R and SS-B offers novel brain signals for somatosensory Brain-computer Interfaces.

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.

Response-Modality-Specific Encoding of Human Choices in Upper Beta Band Oscillations during Vibrotactile Comparisons

Perceptual decisions based on the comparison of two vibrotactile frequencies have been extensively studied in non-human primates. Recently, we obtained corresponding findings from human oscillatory electroencephalography (EEG) activity in the form of choice-selective modulations of upper beta band amplitude in medial premotor areas. However, the research in non-human primates as well as its human counterpart was so far limited to decisions reported by button presses. Thus, here we investigated whether the observed human beta band modulation is specific to the response modality. We recorded EEG activity from participants who compared two sequentially presented vibrotactile frequencies (f1 and f2), and decided whether f2 > f1 or f2 < f1, by performing a horizontal saccade to either side of a computer screen. Contrasting time-frequency transformed EEG data between both choices revealed that upper beta band amplitude (∼24–32 Hz) was modulated by participants’ choices before actual responses were given. In particular, “f2 > f1” choices were always associated with higher beta band amplitude than “f2 < f1” choices, irrespective of whether the choice was correct or not, and independent of the specific association between saccade direction and choice. The observed pattern of beta band modulation was virtually identical to our previous results when participants responded with button presses. In line with an intentional framework of decision making, the most likely sources of the beta band modulation were now, however, located in lateral as compared to medial premotor areas including the frontal eye fields. Hence, we could show that the choice-selective modulation of upper beta band amplitude is on the one hand consistent across different response modalities (i.e., same modulation pattern in similar frequency band), and on the other hand effector specific (i.e., modulation originating from areas involved in planning and executing saccades).

Validation of periodic fMRI signals in response to wearable tactile stimulation

To map cortical representations of the body, we recently developed a wearable technology for automatic tactile stimulation in human functional magnetic resonance imaging (fMRI) experiments. In a two-condition block design experiment, air puffs were delivered to the face and hands periodically. Surface-based regions of interest (S-ROIs) were initially identified by thresholding a linear statistical measure of signal-to-noise ratio of periodic response. Across subjects, S-ROIs were found in the frontal, primary sensorimotor, posterior parietal, insular, temporal, cingulate, and occipital cortices. To validate and differentiate these S-ROIs, we develop a measure of temporal stability of response based on the assumption that a periodic stimulation evokes stable (low-variance) periodic fMRI signals throughout the entire scan. Toward this end, we apply time-frequency analysis to fMRI time series and use circular statistics to characterize the distribution of phase angles for data selection. We then assess the temporal variability of a periodic signal by measuring the path length of its trajectory in the complex plane. Both within and outside the primary sensorimotor cortex, S-ROIs with high temporal variability and deviant phase angles are rejected. A surface-based probabilistic group-average map is constructed for spatial screening of S-ROIs with low to moderate temporal variability in non-sensorimotor regions. Areas commonly activated across subjects are also summarized in the group-average map. In summary, this study demonstrates that analyzing temporal characteristics of the entire fMRI time series is essential for second-level selection and interpretation of S-ROIs initially defined by an overall linear statistical measure.

Enhancing performance of a motor imagery based brain-computer interface by incorporating electrical stimulation-induced SSSEP

OBJECTIVE

We proposed a novel simultaneous hybrid brain-computer interface (BCI) by incorporating electrical stimulation into a motor imagery (MI) based BCI system. The goal of this study was to enhance the overall performance of an MI-based BCI. In addition, the brain oscillatory pattern in the hybrid task was also investigated.

APPROACH

64-channel electroencephalographic (EEG) data were recorded during MI, selective attention (SA) and hybrid tasks in fourteen healthy subjects. In the hybrid task, subjects performed MI with electrical stimulation which was applied to bilateral median nerve on wrists simultaneously.

MAIN RESULTS

The hybrid task clearly presented additional steady-state somatosensory evoked potential (SSSEP) induced by electrical stimulation with MI-induced event-related desynchronization (ERD). By combining ERD and SSSEP features, the performance in the hybrid task was significantly better than in both MI and SA tasks, achieving a ~14% improvement in total relative to the MI task alone and reaching ~89% in mean classification accuracy. On the contrary, there was no significant enhancement obtained in performance while separate ERD feature was utilized in the hybrid task. In terms of the hybrid task, the performance using combined feature was significantly better than using separate ERD or SSSEP feature.

SIGNIFICANCE

The results in this work validate the feasibility of our proposed approach to form a novel MI-SSSEP hybrid BCI outperforming a conventional MI-based BCI through combing MI with electrical stimulation.

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.

A hybrid three-class brain-computer interface system utilizing SSSEPs and transient ERPs

OBJECTIVE

This paper investigates the fusion of steady-state somatosensory evoked potentials (SSSEPs) and transient event-related potentials (tERPs), evoked through tactile simulation on the left and right-hand fingertips, in a three-class EEG based hybrid brain-computer interface. It was hypothesized, that fusing the input signals leads to higher classification rates than classifying tERP and SSSEP individually.

APPROACH

Fourteen subjects participated in the studies, consisting of a screening paradigm to determine person dependent resonance-like frequencies and a subsequent online paradigm. The whole setup of the BCI system was based on open interfaces, following suggestions for a common implementation platform. During the online experiment, subjects were instructed to focus their attention on the stimulated fingertips as indicated by a visual cue. The recorded data were classified during runtime using a multi-class shrinkage LDA classifier and the outputs were fused together applying a posterior probability based fusion. Data were further analyzed offline, involving a combined classification of SSSEP and tERP features as a second fusion principle. The final results were tested for statistical significance applying a repeated measures ANOVA.

MAIN RESULTS

A significant classification increase was achieved when fusing the results with a combined classification compared to performing an individual classification. Furthermore, the SSSEP classifier was significantly better in detecting a non-control state, whereas the tERP classifier was significantly better in detecting control states. Subjects who had a higher relative band power increase during the screening session also achieved significantly higher classification results than subjects with lower relative band power increase.

SIGNIFICANCE

It could be shown that utilizing SSSEP and tERP for hBCIs increases the classification accuracy and also that tERP and SSSEP are not classifying control- and non-control states with the same level of accuracy.

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.