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Neurofeedback of self-regulated brain activity in circumscribed cortical regions is used as a novel strategy to facilitate functional restoration following stroke. Basic knowledge about its impact on motor system oscillations and functional connectivity is however scarce. Specifically, a direct comparison between different feedback modalities and their neural signatures is missing. We assessed a neurofeedback training intervention of modulating β-activity in circumscribed sensorimotor regions by kinesthetic motor imagery (MI). Right-handed healthy participants received two different feedback modalities contingent to their MI-associated brain activity in a cross-over design: (I) visual feedback with a brain–computer interface (BCI) and (II) proprioceptive feedback with a brain–robot interface (BRI) orthosis attached to the right hand. High-density electroencephalography was used to examine the reactivity of the cortical motor system during the training session of each task by studying both local oscillatory power entrainment and distributed functional connectivity. Both feedback modalities activated a distributed functional connectivity network of coherent oscillations. A significantly higher skill and lower variability of self-controlled sensorimotor β-band modulation could, however, be achieved in the BRI condition. This gain in controlling regional motor oscillations was accompanied by functional coupling of remote β-band and θ-band activity in bilateral fronto-central regions and left parieto-occipital regions, respectively. The functional coupling of coherent θ-band oscillations correlated moreover with the skill of regional β-modulation thus revealing a motor learning related network. Our findings indicate that proprioceptive feedback is more suitable than visual feedback to entrain the motor network architecture during the interplay between motor imagery and feedback processing thus resulting in better volitional control of regional brain activity. [Display omitted] •Proprioceptive input is superior to visual input to entrain the motor network during neurofeedback.•Proprioceptive feedback increases self-control of regional β-band modulation.•Proprioceptive feedback entrains motor functional connectivity in the θ- and β-band.•Large-scale functional connectivity in θ-band correlates with regional β-band control.

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.

According to electrophysiological studies motor imagery and motor execution are associated with perturbations of brain oscillations over spatially similar cortical areas. By contrast, neuroimaging and lesion studies suggest that at least partially distinct cortical networks are involved in motor imagery and execution. We sought to further disentangle this relationship by studying the role of brain-robot interfaces in the context of motor imagery and motor execution networks. Twenty right-handed subjects performed several behavioral tasks as indicators for imagery and execution of movements of the left hand, i.e. kinesthetic imagery, visual imagery, visuomotor integration and tonic contraction. In addition, subjects performed motor imagery supported by haptic/proprioceptive feedback from a brain–robot-interface. Principal component analysis was applied to assess the relationship of these indicators. The respective cortical resting state networks in the α-range were investigated by electroencephalography using the phase slope index. We detected two distinct abilities and cortical networks underlying motor control: a motor imagery network connecting the left parietal and motor areas with the right prefrontal cortex and a motor execution network characterized by transmission from the left to right motor areas. We found that a brain–robot-interface might offer a way to bridge the gap between these networks, opening thereby a backdoor to the motor execution system. This knowledge might promote patient screening and may lead to novel treatment strategies, e.g. for the rehabilitation of hemiparesis after stroke. Panel A shows the component coefficients for the visual and the kinesthetic imagery scale (VIS & KIS), for performances in the brain-robotic-interface (BRI), in the tonic contraction task (EMG) and in the task based on visuomotor integration (VMI). The gap between motor imagery (VIS & KIS) and motor execution (EMG, VMI) is bridged by the BRI. Panel B shows the connections with the strongest prediction for motor imagery (blue arrows) and motor execution (red arrows). [Display omitted] •The abilities of motor imagery and motor execution are uncorrelated.•They can be predicted with high specificity from resting state connectivity.•Motor imagery is linked to a parieto-centro-frontal network.•Motor execution is linked to a bilateral motor network.•A brain–robot interface can form a bridge between these abilities and networks.

Since thoroughly validated naturalistic affective German speech stimulus databases are rare, we present here a novel validated database of speech sequences assembled with the purpose of emotion induction. The database comprises 37 audio speech sequences with a total duration of 92 minutes for the induction of positive, neutral, and negative emotion: comedian shows intending to elicit humorous and amusing feelings, weather forecasts, and arguments between couples and relatives from movies or television series. Multiple continuous and discrete ratings are used to validate the database to capture the time course and variabilities of valence and arousal. We analyse and quantify how well the audio sequences fulfil quality criteria of differentiation, salience/strength, and generalizability across participants. Hence, we provide a validated speech database of naturalistic scenarios suitable to investigate emotion processing and its time course with German-speaking participants. Information on using the stimulus database for research purposes can be found at the OSF project repository GAUDIE: https://osf.io/xyr6j/ .

Volitional modulation and neurofeedback of sensorimotor oscillatory activity is currently being evaluated as a strategy to facilitate motor restoration following stroke. Knowledge on the interplay between this regional brain self-regulation, distributed network entrainment and handedness is, however, limited. In a randomized cross-over design, twenty-one healthy subjects (twelve right-handers [RH], nine left-handers [LH]) performed kinesthetic motor imagery of left (48 trials) and right finger extension (48 trials). A brain-machine interface turned event-related desynchronization in the beta frequency-band (16–22 Hz) during motor imagery into passive hand opening by a robotic orthosis. Thereby, every participant subsequently activated either the dominant (DH) or non-dominant hemisphere (NDH) to control contralateral hand opening. The task-related cortical networks were studied with electroencephalography. The magnitude of the induced oscillatory modulation range in the sensorimotor cortex was independent of both handedness (RH, LH) and hemispheric specialization (DH, NDH). However, the regional beta-band modulation was associated with different alpha-band networks in RH and LH: RH presented a stronger inter-hemispheric connectivity, while LH revealed a stronger intra-hemispheric interaction. Notably, these distinct network entrainments were independent of hemispheric specialization. In healthy subjects, sensorimotor beta-band activity can be robustly modulated by motor imagery and proprioceptive feedback in both hemispheres independent of handedness. However, right and left handers show different oscillatory entrainment of cortical alpha-band networks during neurofeedback. This finding may inform neurofeedback interventions in future to align them more precisely with the underlying physiology.

Sensorimotor rhythms (SMRs) are oscillatory brain activities in the α- and β-bands across the sensorimotor regions of the brain. Each frequency band has its own specific function. The α-band oscillations are closely related to intrinsic cortical networks, whereas oscillations in the β-band are relevant for the information transfer between the cortex and periphery, as well as for visual and proprioceptive feedback. This study aimed to investigate the interaction between these two frequency bands, under the premise that the regional modulation of β-band power is linked to a cortical network in the α-band. We therefore designed a procedure to maximize the modulation of β-band activity over the sensorimotor cortex by combining kinesthetic motor-imagery with closed-loop haptic feedback. The cortical network activity during this procedure was estimated via the phase slope index in electroencephalographic recordings. Analysis of effective connectivity within the α-band network revealed an information flow between the precentral (premotor and primary motor), postcentral (primary somatosensory) and parietal cortical areas. The range of β-modulation was connected to a reduction of an ipsilateral sensorimotor and parietal α-network and, consequently, to a lateralization of this network to the contralateral side. These results showed that regional sensorimotor oscillatory activity in the β-band was regulated by cortical coupling of distant areas in the α-band. PSIsum/PSI: Cortical information flow [arrows indicate significant connections, p<0.05 (corrected for multiple comparison)] and net cortical information flow [topoplot, p-values (corrected for multiple comparison) on a logarithmic scale] showing significant α-band activation patterns of subjects with a high range of β-modulation (left), and subjects with a low range of β-modulation (right). The red color indicates net drivers and the blue color indicates net recipients. [Display omitted] •Cortical α-networks became stable during sensorimotor β-modulation.•Information flow was present between the precentral, postcentral and parietal areas.•Increasing β-modulation range was connected to lateralized α-network.

While robot-assisted arm and hand training after stroke allows for intensive task-oriented practice, it has provided only limited additional benefit over dose-matched physiotherapy up to now. These rehabilitation devices are possibly too supportive during the exercises. Neurophysiological signals might be one way of avoiding slacking and providing robotic support only when the brain is particularly responsive to peripheral input. We tested the feasibility of three-dimensional robotic assistance for reaching movements with a multi-joint exoskeleton during motor imagery (MI)-related desynchronization of sensorimotor oscillations in the β-band. We also registered task-related network changes of cortical functional connectivity by electroencephalography via the imaginary part of the coherence function. Healthy subjects and stroke survivors showed similar patterns-but different aptitudes-of controlling the robotic movement. All participants in this pilot study with nine healthy subjects and two stroke patients achieved their maximum performance during the early stages of the task. Robotic control was significantly higher and less variable when proprioceptive feedback was provided in addition to visual feedback, i.e., when the orthosis was actually attached to the subject's arm during the task. A distributed cortical network of task-related coherent activity in the θ-band showed significant differences between healthy subjects and stroke patients as well as between early and late periods of the task. Brain-robot interfaces (BRIs) may successfully link three-dimensional robotic training to the participants' efforts and allow for task-oriented practice of activities of daily living with a physiologically controlled multi-joint exoskeleton. Changes of cortical physiology during the task might also help to make subject-specific adjustments of task difficulty and guide adjunct interventions to facilitate motor learning for functional restoration, a proposal that warrants further investigation in a larger cohort of stroke patients.

Response inhibition, a core component of executive functioning, has been studied extensively in autism, though results depend substantially on task choice and design. This study investigated whether autistic and non-autistic adults differ in behavioral and neurophysiological responses during a visuospatial go/no-go task (GNGT) implemented in virtual reality (VR). Participants (22 autistic, 10 non-autistic) completed a blocked go/no-go task in a VR environment, where stimuli appeared in varied spatial locations. Prefrontal hemodynamic responses were recorded using functional near-infrared spectroscopy (fNIRS), along with reaction times (RTs) and error rates. Both groups demonstrated slower RTs and fewer errors in no-go blocks compared to go blocks, with no significant group differences in behavioral performance. fNIRS analyses revealed significant right-lateralized increases in oxygenated hemoglobin concentration in the dorsolateral prefrontal cortex (dlPFC) during no-go blocks in non-autistic adults only. Autistic adults showed no significant task-related modulation of prefrontal cortex activity. While behavioral performance was comparable across groups, only non-autistic participants showed task-related modulation of dlPFC activity. These findings highlight differential neural engagement during inhibition and illustrate the potential of fNIRS paradigms for examining the executive functioning of autistic individuals in VR.

Affect monitoring is being discussed as a novel strategy to make adaptive systems more user-oriented. Basic knowledge about oscillatory processes and functional connectivity underlying affect during naturalistic human–computer interactions (HCI) is, however, scarce. This study assessed local oscillatory power entrainment and distributed functional connectivity in a close-to-naturalistic HCI-paradigm. Sixteen participants interacted with a simulated assistance system which deliberately evoked positive (supporting goal-achievement) and negative (impeding goal-achievement) affective reactions. Electroencephalography (EEG) was used to examine the reactivity of the cortical system during the interaction by studying both event-related (de-)synchronization (ERD/ERS) and event-related functional coupling of cortical networks towards system-initiated assistance. Significantly higher α-band and β-band ERD in centro-parietal and parieto-occipital regions and β-band ERD in bi-lateral fronto-central regions were observed during impeding system behavior. Supportive system behavior activated significantly higher γ-band ERS in bi-hemispheric parietal-occipital regions. This was accompanied by functional coupling of remote β-band and γ-band activity in the medial frontal, left fronto-central and parietal regions, respectively. Our findings identify oscillatory signatures of positive and negative affective processes as reactions to system-initiated assistance. The findings contribute to the development of EEG-based neuroadaptive assistance loops by suggesting a non-obtrusive method for monitoring affect in HCI.