Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials

The strength of anticipated distractors shapes EEG alpha and theta oscillations in a Working Memory task

Working Memory (WM) requires maintenance of task-relevant information and suppression of task-irrelevant/distracting information. Alpha and theta oscillations have been extensively investigated in relation to WM. However, studies that examine both theta and alpha bands in relation to distractors, encompassing not only power modulation but also connectivity modulation, remain scarce. Here, we depicted, at the EEG-source level, the increase in power and connectivity in theta and alpha bands induced by strong relative to weak distractors during a visual Sternberg-like WM task involving the encoding of verbal items. During retention, a strong or weak distractor was presented, predictable in time and nature. Analysis focused on the encoding and retention phases before distractor presentation. Theta and alpha power were computed in cortical regions of interest, and connectivity networks estimated via spectral Granger causality and synthetized using in/out degree indices. The following modulations were observed for strong vs. weak distractors. In theta band during encoding, the power in frontal regions increased, together with frontal-to-frontal and bottom-up occipital-to-temporal-to-frontal connectivity; even during retention, bottom-up theta connectivity increased. In alpha band during retention, but not during encoding, the power in temporal-occipital regions increased, together with top-down frontal-to-occipital and temporal-to-occipital connectivity. From our results, we postulate a proactive cooperation between theta and alpha mechanisms: the first would mediate enhancement of target representation both during encoding and retention, and the second would mediate increased inhibition of sensory areas during retention only, to suppress the processing of imminent distractor without interfering with the processing of ongoing target stimulus during encoding.

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS-EEG responses

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS-EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS-EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS-EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS-EEG physiology, providing insights for its application in physiological and clinical research.

Heartbeat-related spectral perturbation of electroencephalogram reflects dynamic interoceptive attention states in the trial-by-trial classification analysis

Attending to heartbeats for interoceptive awareness initiates distinct electrophysiological responses synchronized with the R-peaks of an electrocardiogram (ECG), such as the heartbeat-evoked potential (HEP). Beyond HEP, this study proposes heartbeat-related spectral perturbation (HRSP), a time-frequency map of the R-peak locked electroencephalogram (EEG), and explores its characteristics in identifying interoceptive attention states using a classification approach. HRSPs of EEG brain components specified by independent component analysis (ICA) were used for the offline and online classification of interoceptive states. A convolutional neural network (CNN) designed specifically for HRSP was applied to publicly available data from a binary-state experiment (attending to self-heartbeats and white noise) and data from our four-state classification experiment (attending to self-heartbeats, white noise, time passage, and toe) with diverse input feature conditions of HRSP. From the dynamic state perspective, we evaluated the primary frequency bands of HRSP and the minimal number of averaging epochs required to reflect changing interoceptive attention states without compromising accuracy. We also assessed the utility of group ICA and models for classifying HRSP in new participants. The CNN for trial-by-trial HRSP with actual R-peaks demonstrated significantly higher classification accuracy than HRSP with sham, i.e., randomly positioned, R-peaks. Gradient-weighted class activation mapping highlighted the prominent role of theta and alpha bands between 200-600 ms post-R-peak-features absent in classifications using sham HRSPs. Online classification benefits from employing a group ICA and classification model, ensuring reliable accuracy without individual EEG precollection. These results suggest HRSP's potential to reflect interoceptive attention states, proposing transformative implications for clinical applications.

Visual selective attention in individuals with age-related hearing loss

Evidence from epidemiological studies suggests that hearing loss is associated with an accelerated decline in cognitive function, but the underlying pathophysiological mechanism remains poorly understood. Studies using auditory tasks have suggested that degraded auditory input increases the cognitive load for auditory perceptual processing and thereby reduces the resources available for other cognitive tasks. Attention-related networks are among the systems overrecruited to support degraded auditory perception, but it is unclear how they function when no excessive recruitment of cognitive resources for auditory processing is needed. Here, we implemented an EEG study using a nonauditory visual attentional selection task in 30 individuals with age-related hearing loss (ARHLs, 60-73 years) and compared them with aged (N = 30, 60-70 years) and young (N = 35, 22-29 years) normal-hearing controls. Compared with their normal-hearing peers, ARHLs demonstrated a significant amplitude reduction for the posterior contralateral N2 component, which is a well-validated index of the allocation of selective visual attention, despite the comparable behavioral performance. Furthermore, the amplitudes were observed to correlate significantly with hearing acuities (pure tone audiometry thresholds) and higher-order hearing abilities (speech-in-noise thresholds) in aged individuals. The target-elicited alpha lateralization, another mechanism of visuospatial attention, demonstrated in control groups was not observed in ARHLs. Although behavioral performance is comparable, the significant decrease in N2pc amplitude in ARHLs provides neurophysiologic evidence that may suggest a visual attentional deficit in ARHLs even without extra-recruitment of cognitive resources by auditory processing. It supports the hypothesis that constant degraded auditory input in ARHLs has an adverse impact on the function of cognitive control systems, which is a possible mechanism mediating the relationship between hearing loss and cognitive decline.

Brain and grammar: revealing electrophysiological basic structures with competing statistical models

Acoustic, lexical, and syntactic information are simultaneously processed in the brain requiring complex strategies to distinguish their electrophysiological activity. Capitalizing on previous works that factor out acoustic information, we could concentrate on the lexical and syntactic contribution to language processing by testing competing statistical models. We exploited electroencephalographic recordings and compared different surprisal models selectively involving lexical information, part of speech, or syntactic structures in various combinations. Electroencephalographic responses were recorded in 32 participants during listening to affirmative active declarative sentences. We compared the activation corresponding to basic syntactic structures, such as noun phrases vs. verb phrases. Lexical and syntactic processing activates different frequency bands, partially different time windows, and different networks. Moreover, surprisal models based on part of speech inventory only do not explain well the electrophysiological data, while those including syntactic information do. By disentangling acoustic, lexical, and syntactic information, we demonstrated differential brain sensitivity to syntactic information. These results confirm and extend previous measures obtained with intracranial recordings, supporting our hypothesis that syntactic structures are crucial in neural language processing. This study provides a detailed understanding of how the brain processes syntactic information, highlighting the importance of syntactic surprisal in shaping neural responses during language comprehension.

Data processing techniques impact quantification of cortico-cortical evoked potentials

BACKGROUND

Cortico-cortical evoked potentials (CCEPs) are a common tool for probing effective connectivity in intracranial human electrophysiology. As with all human electrophysiology data, CCEP data are highly susceptible to noise. To address noise, filters and re-referencing are often applied to CCEP data, but different processing strategies are used from study to study.

NEW METHOD

We systematically compare how common average re-referencing and filtering CCEP data impacts quantification.

RESULTS

We show that common average re-referencing and filters, particularly filters that cut out more frequencies, can significantly impact the quantification of CCEP magnitude and morphology. We identify that high cutoff high pass filters (> 0.5 Hz), low cutoff low pass filters (< 200 Hz), and common average re-referencing impact quantification across subjects. However, we also demonstrate that the presence of noise may impact CCEP quantification, and preprocessing is necessary to mitigate this. We show that filtering is more effective than re-referencing or averaging across trials for reducing most common types of noise.

COMPARISON WITH EXISTING METHODS

These results suggest that existing CCEP processing methods must be applied with care to maximize noise reduction and minimize changes to the data. We do not test every available processing strategy; rather we demonstrate that processing can influence the results of CCEP studies. We emphasize the importance of reporting all processing methods, particularly re-referencing methods.

CONCLUSIONS

We propose a general framework for choosing an appropriate processing pipeline for CCEP data, taking into consideration the noise levels of a specific dataset. We suggest that minimal gentle filtering is preferable.

Alpha and theta oscillations on a visual strategic processing task in age-related hearing loss

Introduction

Emerging evidence suggests changes in several cognitive control processes in individuals with age-related hearing loss (ARHL). However, value-directed strategic processing, which involves selectively processing salient information based on high value, has been relatively unexplored in ARHL. Our previous work has shown behavioral changes in strategic processing in individuals with ARHL. The current study examined event-related alpha and theta oscillations linked to a visual, value-directed strategic processing task in 19 individuals with mild untreated ARHL and 17 normal hearing controls of comparable age and education.

Methods

Five unique word lists were presented where words were assigned high- or low-value based on the letter case, and electroencephalography (EEG) data was recorded during task performance.

Results

The main effect of the group was observed in early time periods. Specifically, greater theta synchronization was seen in the ARHL group relative to the control group. Interaction between group and value was observed at later time points, with greater theta synchronization for high- versus low-value information in those with ARHL.

Discussion

Our findings provide evidence for oscillatory changes tied to a visual task of value-directed strategic processing in individuals with mild untreated ARHL. This points towards modality-independent neurophysiological changes in cognitive control in individuals with mild degrees of ARHL and adds to the rapidly growing literature on the cognitive consequences of ARHL.

Commit to your putting stroke: exploring the impact of quiet eye duration and neural activity on golf putting performance

Introduction

There is a growing interest in characterizing the cognitive-motor processes that underlie superior performance in highly skilled athletes. The aim of this study was to explore neural markers of putting performance in highly skilled golfers by recording mobile EEG (electroencephalogram) during the pre-shot period.

Methods

Twenty-eight right-handed participants (20 males) with a mean age of 24.2 years (± 6.4) and an average handicap of +1.7 (± 6.4) completed a testing session. Following the warm-up, participants completed 140 putts from a distance of 8ft (2.4m), with putts taken from 5 different positions. While putting, participants wore an eye tracker and a gel-based EEG system with 32 electrodes. Time and frequency domain features of the EEG signals were extracted to characterize Movement-Related Cortical Potentials (MRCP) and rhythmic modulations of neural activity in theta, alpha, sensorimotor and beta frequency bands associated with putting performance.

Results

Eye-tracking data demonstrate that mean Quiet Eye durations are not a reliable marker of expertise as the same duration was found for both successful and unsuccessful putts. Following rigorous data processing data from 12 participants (8 males, mean age 21.6 years ± 5.4, average handicap +1.5 ± 4.4) were included in the EEG analysis. MRCP analysis revealed performance-based differences, with unsuccessful putts having a greater negative amplitude in comparison to successful putts. Time frequency analysis of the EEG data revealed that successful putts exhibit distinct neural activity profiles compared to unsuccessful ones. For successful putts, greater suppression of beta was present in the central region prior to the putt. By contrast, increased frontal theta power was present for unsuccessful putts immediately before the putt (consistent with hesitation and the need for motor plan adjustments prior to execution).

Discussion

We propose that neural activity may provide plausible insights into the mechanisms behind why identical QE durations can lead to both success and failure. From an applied perspective, this study highlights the merits of a multi-measure approach to gain further insights into performance differences within highly skilled golfers. We discuss considerations for future research and solutions to address the challenges related to the complexities of collecting clean EEG signals within naturalistic sporting contexts.

Instrumentation for TMS‐EEG Experiment: ArTGen and a Custom EEG Interface

In transcranial magnetic stimulation (TMS) and electroencephalography (EEG) experiments, two researchers typically collaborate in the lab. This study addresses the challenge a single researcher faces in managing the TMS experiment's timing while operating the TMS coil. It introduces the Arduino Trigger Generator (ArTGen) to remotely control the timing of TMS experiments using a footswitch pedal. Moreover, a bespoke printed circuit board (PCB) is designed to interface the eegoMylab amplifier with off‐the‐shelf EEG caps. The ArTGen facilitates accurate timing of the TMS stimulator's inter‐pulse intervals (IPIs) through a footswitch pedal, enhancing researchers' control over TMS‐EEG experiments. The PCB interface provides a cost‐effective tool to extend the functionality of the eegoMylab amplifier. The integration of our PCB interface has been validated in a custom TMS‐EEG setup by analyzing TMS‐evoked potentials (TEPs), global mean field power (GMFP), butterfly plots, and event‐related spectral potentials (ERSPs). The PCB reliably preserved EEG signal integrity, ensuring accurate data acquisition. Thorough channel‐wise consistency checks across components confirmed data accuracy. ArTGen's portability and footswitch feature streamline experimental control, aiding TMS‐EEG research and clinical applications. Moreover, our PCB resolves compatibility between the eegoMylab amplifier and the Waveguard EEG cap by extending the amplifier to connect to off‐the‐shelf EEG caps. The ArTGen serves as a robust remote control tool for TMS stimulators, while our PCB interface presents a solution for integrating a customized TMS‐EEG setup. This study addresses the gap in existing TMS‐EEG research by introducing innovative technological enhancements that not only augment experimental flexibility but also streamline procedural workflows.

Behavioral and neural measures of semantic conflict monitoring: Findings from a novel picture-word interference task

Conflict monitoring has been studied extensively using experimental paradigms that manipulate perceptual dimensions of stimuli and responses. The picture-word interference (PWI) task has historically been used to examine semantic conflict, but primarily for the purpose of examining lexical retrieval. In this study, we utilized two novel PWI tasks to assess conflict monitoring in the context of semantic conflict. Participants included nineteen young adults (14F, age = 20.79 ± 3.14) who completed two tasks: Animals and Objects. Task and conflict effects were assessed by examining behavioral (reaction time and accuracy) and neurophysiological (oscillations in theta, alpha, and beta band) measures. Results revealed conflict effects within both tasks, but the pattern of findings differed across the two semantic categories. Participants were slower to respond to unmatched versus matched trials on the Objects task only and were less accurate responding to matched versus unmatched trials in the Animals task only. We also observed task differences, with participants responding more accurately on conflict trials for Animals compared to Objects. Differences in neural oscillations were observed, including between-task differences in low beta oscillations and within-task differences in theta, alpha, and low beta. We also observed significant correlations between task performance and standard measures of cognitive control. This work provides new insights into conflict monitoring, highlighting the importance of examining conflict across different semantic categories, especially in the context of animacy. The findings serve as a benchmark to assess conflict monitoring using PWI tasks across populations of varying cognitive ability.

Exploring Electrocortical Signatures of Gait Adaptation: Differential Neural Dynamics in Slow and Fast Gait Adapters

Individuals exhibit significant variability in their ability to adapt locomotor skills, with some adapting quickly and others more slowly. Differences in brain activity likely contribute to this variability, but direct neural evidence is lacking. We investigated individual differences in electrocortical activity that led to faster locomotor adaptation rates. We recorded high-density electroencephalography while young, neurotypical adults adapted their walking on a split-belt treadmill and grouped them based on how quickly they restored their gait symmetry. Results revealed unique spectral signatures within the posterior parietal, bilateral sensorimotor, and right visual cortices that differ between fast and slow adapters. Specifically, fast adapters exhibited lower alpha power in the posterior parietal and right visual cortices during early adaptation, associated with quicker attainment of steady-state step length symmetry. Decreased posterior parietal alpha may reflect enhanced spatial attention, sensory integration, and movement planning to facilitate faster locomotor adaptation. Conversely, slow adapters displayed greater alpha and beta power in the right visual cortex during late adaptation, suggesting potential differences in visuospatial processing. Additionally, fast adapters demonstrated reduced spectral power in the bilateral sensorimotor cortices compared with slow adapters, particularly in the theta band, which may suggest variations in perception of the split-belt perturbation. These findings suggest that alpha and beta oscillations in the posterior parietal and visual cortices and theta oscillations in the sensorimotor cortex are related to the rate of gait adaptation.

Electrocortical theta activity may reflect sensory prediction errors during adaptation to a gradual gait perturbation

Locomotor adaptation to abrupt and gradual perturbations are likely driven by fundamentally different neural processes. The aim of this study was to quantify brain dynamics associated with gait adaptation to a gradually introduced gait perturbation, which typically results in smaller behavioral errors relative to an abrupt perturbation. Loss of balance during standing and walking elicits transient increases in midfrontal theta oscillations that have been shown to scale with perturbation intensity. We hypothesized there would be no significant change in anterior cingulate theta power (4-7 Hz) with respect to pre-adaptation when a gait perturbation is introduced gradually because the gradual perturbation acceleration and stepping kinematic errors are small relative to an abrupt perturbation. Using mobile electroencephalography (EEG), we measured gait-related spectral changes near the anterior cingulate, posterior cingulate, sensorimotor, and posterior parietal cortices as young, neurotypical adults (n = 30) adapted their gait to an incremental split-belt treadmill perturbation. Most cortical clusters we examined (>70%) did not exhibit changes in electrocortical activity between 2-50 Hz. However, we did observe gait-related theta synchronization near the left anterior cingulate cortex during strides with the largest errors, as measured by step length asymmetry. These results suggest gradual adaptation with small gait asymmetry and perturbation magnitude may not require significant cortical resources beyond normal treadmill walking. Nevertheless, the anterior cingulate may remain actively engaged in error monitoring, transmitting sensory prediction error information via theta oscillations.

[Formula: see text]-[Formula: see text]: A Nonparametric Model for Neural Power Spectra Decomposition

The power spectra estimated from the brain recordings are the mixed representation of aperiodic transient activity and periodic oscillations, i.e., aperiodic component (AC) and periodic component (PC). Quantitative neurophysiology requires precise decomposition preceding parameterizing each component. However, the shape, statistical distribution, scale, and mixing mechanism of AC and PCs are unclear, challenging the effectiveness of current popular parametric models such as FOOOF, IRASA, BOSC, etc. Here, ξ- π was proposed to decompose the neural spectra by embedding the nonparametric spectra estimation with penalized Whittle likelihood and the shape language modeling into the expectation maximization framework. ξ- π was validated on the synthesized spectra with loss statistics and on the sleep EEG and the large sample iEEG with evaluation metrics and neurophysiological evidence. Compared to FOOOF, both the simulation presenting shape irregularities and the batch simulation with multiple isolated peaks indicated that ξ- π improved the fit of AC and PCs with less loss and higher F1-score in recognizing the centering frequencies and the number of peaks; the sleep EEG revealed that ξ- π produced more distinguishable AC exponents and improved the sleep state classification accuracy; the iEEG showed that ξ- π approached the clinical findings in peak discovery. Overall, ξ- π offered good performance in the spectra decomposition, which allows flexible parameterization using descriptive statistics or kernel functions. ξ- π is a seminal tool for brain signal decoding in fields such as cognitive neuroscience, brain-computer interface, neurofeedback, and brain diseases.

The effect of EEG microstate on the characteristics of TMS-EEG

OBJECTIVE

Differences in neural states at the time of transcranial magnetic stimulation (TMS) can lead to variations in the effectiveness of TMS stimulation. Strategies that aim to lock neural activity states and improve the precision of stimulation timing in TMS optimization should gradually receive attention. One feasible approach is to utilize microstate locking for TMS stimulation, and understanding the impact of microstates at the time of stimulation on TMS response forms the foundation of this approach.

APPROACH

TMS-EEG data were extracted from 21 healthy subjects through experiments. Based on the different microstates at the time of stimulation, the trials were classified into four datasets. TMS-evoked potential (TEP), topographical distribution, and natural frequency, were computed for each dataset to explore the differences in TMS-EEG characteristics across different microstates.

MAIN RESULTS

The N100 component of microstate C group (-2.376 μV) was significantly higher (p = 0.003) than of microstate D group (-1.739 μV), and the P180 component of microstate D group (2.482 μV) was significantly higher (p = 0.024) than of microstate B group (1.766 μV) and slightly higher (p = 0.058) than of microstate C group (1.863 μV) by calculating the ROI. The topographical distribution of TEP components during microstate C and microstate D still retained the template characteristics of the microstate at the time of stimulation, and the natural frequencies did not differ among the four classical microstates.

SIGNIFICANCE

This study showed the potential for future closed-loop TMS based on microstates and would guiding the development of microstate-based closed-loop TMS techniques.

Episodic long-term memory formation during slow-wave sleep

We are unresponsive during slow-wave sleep but continue monitoring external events for survival. Our brain wakens us when danger is imminent. If events are non-threatening, our brain might store them for later consideration to improve decision-making. To test this hypothesis, we examined whether novel vocabulary consisting of simultaneously played pseudowords and translation words are encoded/stored during sleep, and which neural-electrical events facilitate encoding/storage. An algorithm for brain-state-dependent stimulation selectively targeted word pairs to slow-wave peaks or troughs. Retrieval tests were given 12 and 36 hr later. These tests required decisions regarding the semantic category of previously sleep-played pseudowords. The sleep-played vocabulary influenced awake decision-making 36 hr later, if targeted to troughs. The words' linguistic processing raised neural complexity. The words' semantic-associative encoding was supported by increased theta power during the ensuing peak. Fast-spindle power ramped up during a second peak likely aiding consolidation. Hence, new vocabulary played during slow-wave sleep was stored and influenced decision-making days later.

Sensorimotor Oscillations in Human Infants during an Innate Rhythmic Movement

The relationship between cerebral rhythms and early sensorimotor development is not clear. In recent decades, evidence revealed a rhythmic modulation involving sensorimotor processing. A widely corroborated functional role of oscillatory activity is to coordinate the information flow across sensorimotor networks. Their activity is coordinated by event-related synchronisation and desynchronisation in different sensorimotor rhythms, which indicate parallel processes may be occurring in the neuronal network during movement. To date, the dynamics of these brain oscillations and early sensorimotor development are unexplored. Our study investigates the relationship between the cerebral rhythms using EEG and a typical rhythmic movement of infants, the non-nutritive sucking (NNS) behaviour. NNS is an endogenous behaviour that originates from the suck central pattern generator in the brainstem. We find, in 17 infants, that sucking frequency correlates with beta synchronisation within the sensorimotor area in two phases: one strongly anticipating (~3 s) and the other encompassing the start of the motion. These findings suggest that a beta synchronisation of the sensorimotor cortex may influence the sensorimotor dynamics of NNS activity. Our results reveal the importance of rapid brain oscillations in infants and the role of beta synchronisation and their possible role in the communication between cortical and deep generators.

Event-related desynchronization and synchronization in multiple sclerosis

BACKGROUND

Motor preparation and execution can be impaired in patients with multiple sclerosis (pwMS). These neural processes can be assessed using electroencephalography (EEG). During a self-paced movement, EEG signal amplitude decreases before movement (event-related desynchronization, ERD) and increases after movement (event-related synchronization, ERS).

OBJECTIVE

To reappraise ERD/ERS changes in pwMS compared to healthy controls (HC).

METHODS

This single-center study included 13 pwMS and 10 sex/age-matched HC. 60-channel EEG was recorded during two self-paced movements of the right hand: a simple index finger extension task and a more complex finger tapping task. Clinical variables included MS type, sex, age, disease duration, disability, grip strength, fatigue and attentional performance. EEG variables included ERD and ERS onset latency, duration, and amplitude determined using two methods of signal analyses (based on visual or automated determination) in the alpha and beta frequency bands in five cortical regions: right and left frontocentral and centroparietal regions and a midline region. Neuroimaging variables included the volumes of four deep brain structures (thalamus, putamen, pallidum and caudate nucleus) and the relative lesion load.

RESULTS

ERD/ERS changes in pwMS compared to HC were observed only in the beta band. In pwMS, beta-ERD had a delayed onset in the midline and right parietocentral regions and a shortened duration or increased amplitude in the parietocentral region; beta-ERS had a shorter duration, delayed onset, or reduced amplitude in the left parieto/frontocentral region. In addition, pwMS with a more delayed beta-ERD in the midline region had less impaired executive functions but increased caudate nuclei volume, while pwMS with a more delayed beta-ERS in the parietocentral region contralateral to the movement had less fatigue but increased thalami volume.

CONCLUSION

This study confirms an alteration of movement preparation and execution in pwMS, mainly characterized by a delayed cortical activation (ERD) and a delayed and reduced post-movement inhibition (ERS) in the beta band. Compensatory mechanisms could be involved in these changes, associating more preserved clinical performance and overactivation of deep brain structures.

Training-related changes in neural beta oscillations associated with implicit and explicit motor sequence learning

Many motor actions we perform have a sequential nature while learning a motor sequence involves both implicit and explicit processes. In this work, we developed a task design where participants concurrently learn an implicit and an explicit motor sequence across five training sessions, with EEG recordings at sessions 1 and 5. This intra-subject approach allowed us to study training-induced behavioral and neural changes specific to the explicit and implicit components. Based on previous reports of beta power modulations in sensorimotor networks related to sequence learning, we focused our analysis on beta oscillations at motor-cortical sites. On a behavioral level, substantial performance gains were evident early in learning in the explicit condition, plus slower performance gains across training sessions in both explicit and implicit sequence learning. Consistent with the behavioral trends, we observed a training-related increase in beta power in both sequence learning conditions, while the explicit condition displayed stronger beta power suppression during early learning. The initially stronger beta suppression and subsequent increase in beta power specific to the explicit component, correlated with enhanced behavioral performance, possibly reflecting higher cortical excitability. Our study suggests an involvement of motor-cortical beta oscillations in the explicit component of motor sequence learning.

Comparison of Immediate Neuromodulatory Effects between Focal Vibratory and Electrical Sensory Stimulations after Stroke

Focal vibratory stimulation (FVS) and neuromuscular electrical stimulation (NMES) are promising technologies for sensory rehabilitation after stroke. However, the differences between these techniques in immediate neuromodulatory effects on the poststroke cortex are not yet fully understood. In this research, cortical responses in persons with chronic stroke (n = 15) and unimpaired controls (n = 15) were measured by whole-brain electroencephalography (EEG) when FVS and NMES at different intensities were applied transcutaneously to the forearm muscles. Both FVS and sensory-level NMES induced alpha and beta oscillations in the sensorimotor cortex after stroke, significantly exceeding baseline levels (p < 0.05). These oscillations exhibited bilateral sensory deficiency, early adaptation, and contralesional compensation compared to the control group. FVS resulted in a significantly faster P300 response (p < 0.05) and higher theta oscillation (p < 0.05) compared to NMES. The beta desynchronization over the contralesional frontal-parietal area remained during NMES (p > 0.05), but it was significantly weakened during FVS (p < 0.05) after stroke. The results indicated that both FVS and NMES effectively activated the sensorimotor cortex after stroke. However, FVS was particularly effective in eliciting transient involuntary attention, while NMES primarily fostered the cortical responses of the targeted muscles in the contralesional motor cortex.

A study on EEG differences between active counting and focused breathing tasks for more sensitive detection of consciousness

Introduction

In studies on consciousness detection for patients with disorders of consciousness, difference comparison of EEG responses based on active and passive task modes is difficult to sensitively detect patients' consciousness, while a single potential analysis of EEG responses cannot comprehensively and accurately determine patients' consciousness status. Therefore, in this paper, we designed a new consciousness detection paradigm based on a multi-stage cognitive task that could induce a series of event-related potentials and ERD/ERS phenomena reflecting different consciousness contents. A simple and direct task of paying attention to breathing was designed, and a comprehensive evaluation of consciousness level was conducted using multi-feature joint analysis.

Methods

We recorded the EEG responses of 20 healthy subjects in three modes and reported the consciousness-related mean event-related potential amplitude, ERD/ERS phenomena, and the classification accuracy, sensitivity, and specificity of the EEG responses under different conditions.

Results

The results showed that the EEG responses of the subjects under different conditions were significantly different in the time domain and time-frequency domain. Compared with the passive mode, the amplitudes of the event-related potentials in the breathing mode were further reduced, and the theta-ERS and alpha-ERD phenomena in the frontal region were further weakened. The breathing mode showed greater distinguishability from the active mode in machine learning-based classification.

Discussion

By analyzing multiple features of EEG responses in different modes and stimuli, it is expected to achieve more sensitive and accurate consciousness detection. This study can provide a new idea for the design of consciousness detection methods.

Auditory stimulation during REM sleep modulates REM electrophysiology and cognitive performance

REM sleep is critical for memory, emotion, and cognition. Manipulating brain activity during REM could improve our understanding of its function and benefits. Earlier studies have suggested that auditory stimulation in REM might modulate REM time and reduce rapid eye movement density. Building on this, we studied the cognitive effects and electroencephalographic responses related to such stimulation. We used acoustic stimulation locked to eye movements during REM and compared two overnight conditions (stimulation and no-stimulation). We evaluated the impact of this stimulation on REM sleep duration and electrophysiology, as well as two REM-sensitive memory tasks: visual discrimination and mirror tracing. Our results show that this auditory stimulation in REM decreases the rapid eye movements that characterize REM sleep and improves performance on the visual task but is detrimental to the mirror tracing task. We also observed increased beta-band activity and decreased theta-band activity following stimulation. Interestingly, these spectral changes were associated with changes in behavioural performance. These results show that acoustic stimulation can modulate REM sleep and suggest that different memory processes underpin its divergent impacts on cognitive performance.

Transcranial Direct Current Stimulation Decreases P3 Amplitude and Inherent Delta Activity during a Waiting Impulsivity Paradigm: Crossover Study

The inability to wait for a target before initiating an action (i.e., waiting impulsivity) is one of the main features of addictive behaviors. Current interventions for addiction, such as transcranial Direct Current Stimulation (tDCS), have been suggested to improve this inability. Nonetheless, the effects of tDCS on waiting impulsivity and underlying electrophysiological (EEG) markers are still not clear. Therefore, this study aimed to evaluate the effects of neuromodulation over the right inferior frontal gyrus (rIFG) on the behavior and EEG markers of reward anticipation (i.e., cue and target-P3 and underlying delta/theta power) during a premature responding task. For that, forty healthy subjects participated in two experimental sessions, where they received active and sham tDCS over the rIFG combined with EEG recording during the task. To evaluate transfer effects, participants also performed two control tasks to assess delay discounting and motor inhibition. The active tDCS decreased the cue-P3 and target-P3 amplitudes, as well as delta power during target-P3. While no tDCS effects were found for motor inhibition, active tDCS increased the discounting of future rewards when compared to sham. These findings suggest a tDCS-induced modulation of the P3 component and underlying oscillatory activity during waiting impulsivity and the discounting of future rewards.

Blindness affects the developmental trajectory of the sleeping brain

Sleep plays a crucial role in brain development, sensory information processing, and consolidation. Sleep spindles are markers of these mechanisms as they mirror the activity of the thalamocortical circuits. Spindles can be subdivided into two groups, slow (10-13 Hz) and fast (13-16 Hz), which are each associated with different functions. Specifically, fast spindles oscillate in the high-sigma band and are associated with sensorimotor processing, which is affected by visual deprivation. However, how blindness influences spindle development has not yet been investigated. We recorded nap video-EEG of 50 blind/severely visually impaired (BSI) and 64 sighted children aged 5 months to 6 years old. We considered aspects of both macro- and micro-structural spindles. The BSI children lacked the evolution of developmental spindles within the central area. Specifically, young BSI children presented low central high-sigma and high-beta (25-30 Hz) event-related spectral perturbation and showed no signs of maturational decrease. High-sigma and high-beta activity in the BSI group correlated with clinical indices predicting perceptual and motor disorders. Our findings suggest that fast spindles are pivotal biomarkers for identifying an early developmental deviation in BSI children. These findings are critical for initial therapeutic intervention.

Finding tau rhythms in EEG: An independent component analysis approach

Tau rhythms are largely defined by sound responsive alpha band (~8-13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial recording because of tau's elusiveness in the electroencephalogram. Here, we demonstrate that independent component analysis (ICA) decomposition can be an effective way to identify tau sources and study tau source activities in EEG recordings. Subjects (N = 18) were passively exposed to complex acoustic stimuli while the EEG was recorded from 68 electrodes across the scalp. Subjects' data were split into 60 parallel processing pipelines entailing use of five levels of high-pass filtering (passbands of 0.1, 0.5, 1, 2, and 4 Hz), three levels of low-pass filtering (25, 50, and 100 Hz), and four different ICA algorithms (fastICA, infomax, adaptive mixture ICA [AMICA], and multi-model AMICA [mAMICA]). Tau-related independent component (IC) processes were identified from this data as being localized near the superior temporal gyri with a spectral peak in the 8-13 Hz alpha band. These "tau ICs" showed alpha suppression during sound presentations that was not seen for other commonly observed IC clusters with spectral peaks in the alpha range (e.g., those associated with somatomotor mu, and parietal or occipital alpha). The choice of analysis parameters impacted the likelihood of obtaining tau ICs from an ICA decomposition. Lower cutoff frequencies for high-pass filtering resulted in significantly fewer subjects showing a tau IC than more aggressive high-pass filtering. Decomposition using the fastICA algorithm performed the poorest in this regard, while mAMICA performed best. The best combination of filters and ICA model choice was able to identify at least one tau IC in the data of ~94% of the sample. Altogether, the data reveal close similarities between tau EEG IC dynamics and tau dynamics observed in MEG and intracranial data. Use of relatively aggressive high-pass filters and mAMICA decomposition should allow researchers to identify and characterize tau rhythms in a majority of their subjects. We believe adopting the ICA decomposition approach to EEG analysis can increase the rate and range of discoveries related to auditory responsive tau rhythms.

Electroencephalography-Based Effects of Acute Alcohol Intake on the Pain Matrix

The effects of acute and chronic intakes of high doses of alcohol on pain perception are well known, ranging from short-term analgesic effects to long-term sensitization and polyneuropathies. The short-term analgesic effects of ethanol consumption on subjective pain perception have been well studied in the literature. Recent advances in neuroimaging allow for an insight into pain-related structures in the brain, fostering the mechanistic understanding of the processing of nociceptive input and pain. We aimed to utilize EEG, combined with standardized noxious mechanical/thermal stimulation and subjective pain testing, to research the effects of acute alcohol intake on nociceptive processing and pain perception. We recruited 12 healthy subjects in an unblinded cross-over study design and aimed at achieving a blood alcohol level of 0.1%. Our data revealed a significant reduction in subjective pain ratings to noxious thermal and mechanical stimuli after alcohol ingestion. Our EEG data revealed suppressing effects on the cortical structures responsible for processing pain, the "pain matrix". We conclude that in addition to its analgesic effects, as expressed by the reduction in subjective pain, alcohol has a further impact on the "pain matrix" and directly affects the salience to a nociceptive stimulus.

Impaired proactive cognitive control in Parkinson's disease

Adaptive control has been studied in Parkinson's disease mainly in the context of proactive control and with mixed results. We compared reactive- and proactive control in 30 participants with Parkinson's disease to 30 age matched healthy control participants. The electroencephalographic activity of the participants was recorded over 128 channels while they performed a numerical Stroop task, in which we controlled for confounding stimulus-response learning. We assessed effects of reactive- and proactive control on reaction time-, accuracy- and electroencephalographic time-frequency data. Behavioural results show distinct impairments of proactive- and reactive control in participants with Parkinson's disease, when tested on their usual medication. Compared to healthy control participants, participants with Parkinson's disease were impaired in their ability to adapt cognitive control proactively and were less effective to resolve conflict using reactive control. Successful reactive and proactive control in the healthy control group was accompanied by a reduced conflict effect between congruent and incongruent items in midline-frontal theta power. Our findings provide evidence for a general impairment of proactive control in Parkinson's disease and highlight the importance of controlling for the effects of S-R learning when studying adaptive control. Evidence concerning reactive control was inconclusive, but we found that participants with Parkinson's disease were less effective than healthy control participants in resolving conflict during the reactive control task.

Electrophysiological population dynamics reveal context dependencies during decision making in human frontal cortex

Evidence from monkeys and humans suggests that the orbitofrontal cortex (OFC) encodes the subjective value of options under consideration during choice. Data from non-human primates suggests that these value signals are context-dependent, representing subjective value in a way influenced by the decision makers' recent experience. Using electrodes distributed throughout cortical and subcortical structures, human epilepsy patients performed an auction task where they repeatedly reported the subjective values they placed on snack food items. High-gamma activity in many cortical and subcortical sites including the OFC positively correlated with subjective value. Other OFC sites showed signals contextually modulated by the subjective value of previously offered goods-a context dependency predicted by theory but not previously observed in humans. These results suggest that value and value-context signals are simultaneously present but separately represented in human frontal cortical activity.

Inferring individual evaluation criteria for reaching trajectories with obstacle avoidance from EEG signals

During reaching actions, the human central nerve system (CNS) generates the trajectories that optimize effort and time. When there is an obstacle in the path, we make sure that our arm passes the obstacle with a sufficient margin. This comfort margin varies between individuals. When passing a fragile object, risk-averse individuals may adopt a larger margin by following the longer path than risk-prone people do. However, it is not known whether this variation is associated with a personalized cost function used for the individual optimal control policies and how it is represented in our brain activity. This study investigates whether such individual variations in evaluation criteria during reaching results from differentiated weighting given to energy minimization versus comfort, and monitors brain error-related potentials (ErrPs) evoked when subjects observe a robot moving dangerously close to a fragile object. Seventeen healthy participants monitored a robot performing safe, daring and unsafe trajectories around a wine glass. Each participant displayed distinct evaluation criteria on the energy efficiency and comfort of robot trajectories. The ErrP-BCI outputs successfully inferred such individual variation. This study suggests that ErrPs could be used in conjunction with an optimal control approach to identify the personalized cost used by CNS. It further opens new avenues for the use of brain-evoked potential to train assistive robotic devices through the use of neuroprosthetic interfaces.

EEG error-related potentials encode magnitude of errors and individual perceptual thresholds

Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks.

Nociception in Chicken Embryos, Part II: Embryonal Development of Electroencephalic Neuronal Activity In Ovo as a Prerequisite for Nociception

Chicken culling has been forbidden in Germany since 2022; male/female selection and male elimination must be brought to an embryonic status prior to the onset of nociception. The present study evaluated the ontogenetic point at which noxious stimuli could potentially be perceived/processed in the brain in ovo. EEG recordings from randomized hyperpallial brain sites were recorded in ovo and noxious stimuli were applied. Temporal and spectral analyses of the EEG were performed. The onset of physiological neuronal signals could be determined at developmental day 13. ERP/ERSP/ITC analysis did not reveal phase-locked nociceptive responses. Although no central nociceptive responses were documented, adequate EEG responses to noxious stimuli from other brain areas cannot be excluded. The extreme stress impact on the embryo during the recording may overwrite the perception of noniceptive stimuli. The results suggest developmental day 13 as the earliest embryonal stage being able to receive and process nociceptive stimuli.

Strategy-based motor learning decreases the post-movement β power

Motor learning depends on the joint contribution of several processes including cognitive strategies aiming at goal achievement and prediction error-driven implicit adaptation. Understanding this functional interplay and its clinical implications requires insight into the individual learning processes, including at a neural level. Here, we set out to examine the impact of learning a cognitive strategy, over and above implicit adaptation, on the oscillatory post-movement β rebound (PMBR), which typically decreases in power following (visuo)motor perturbations. Healthy participants performed reaching movements towards a target, with online visual feedback replacing the view of their moving hand. The feedback was sometimes rotated, either relative to their movements (visuomotor rotation) or invariant to their movements (and relative to the target; clamped feedback), always for two consecutive trials interspersed between non-rotated trials. In both conditions, the first trial with a rotation was unpredictable. On the second trial, the task was either to re-aim, and thereby compensate for the rotation experienced in the first trial (visuomotor rotation; Compensate condition), or to ignore the rotation and keep on aiming at the target (clamped feedback; Ignore condition). After-effects did not differ between conditions, indicating that the amount of implicit learning was similar, while large differences in movement direction in the second rotated trial between conditions indicated that participants successfully acquired re-aiming strategies. Importantly, PMBR power following the first rotated trial was modulated differently in the two conditions. Specifically, it decreased in both conditions, but this effect was larger when participants had to acquire a cognitive strategy and prepare to re-aim. Our results therefore suggest that the PMBR is modulated by cognitive demands of motor learning, possibly reflecting the evaluation of a behaviourally significant goal achievement error.

Tactile estimation of hedonic and sensory properties during active touch: An electroencephalography study

Perceptual judgements about our physical environment are informed by somatosensory information. In real-world exploration, this often involves dynamic hand movements to contact surfaces, termed active touch. The current study investigated cortical oscillatory changes during active exploration to inform the estimation of surface properties and hedonic preferences of two textured stimuli: smooth silk and rough hessian. A purpose-built touch sensor quantified active touch, and oscillatory brain activity was recorded from 129-channel electroencephalography. By fusing these data streams at a single trial level, oscillatory changes within the brain were examined while controlling for objective touch parameters (i.e., friction). Time-frequency analysis was used to quantify changes in cortical oscillatory activity in alpha (8-12 Hz) and beta (16-24 Hz) frequency bands. Results reproduce findings from our lab, whereby active exploration of rough textures increased alpha-band event-related desynchronisation in contralateral sensorimotor areas. Hedonic processing of less preferred textures resulted in an increase in temporoparietal beta-band and frontal alpha-band event-related desynchronisation relative to most preferred textures, suggesting that higher order brain regions are involved in the hedonic processing of texture. Overall, the current study provides novel insight into the neural mechanisms underlying texture perception during active touch and how this process is influenced by cognitive tasks.

Long-term practice of intuitive inquiry meditation modulates EEG dynamics during self-schema processing

Objective

Intuitive inquiry meditation is a unique form of Buddhist Zen/Chan practice in which individuals actively and intuitively utilize the cognitive functions to cultivate doubt and explore the concept of the self. This event-related potential (ERP) study aimed to investigate the neural correlates by which long-term practice of intuitive inquiry meditation induces flexibility in self-schema processing, highlighting the role of doubt and belief processes in this exploration.

Methods

Twenty experienced and eighteen beginner meditators in intuitive inquiry meditation were recruited for this ERP study. The interactions of doubt and belief processes with concepts of the self and Buddha were investigated. A 128-channel electroencephalography (EEG) system was used to collect EEG data. The ERP data were processed and analyzed using EEGLAB.

Results

The data showed a double dissociation between beginners and experienced meditators (monks) in the concepts of the self and Buddha: intuitive inquiry meditation reduced the brain activity of beginners when viewing Buddha image but not when viewing a picture of themselves. However, in experienced meditators, intuitive inquiry meditation reduced brain activity when they viewed images of themselves but not when they viewed Buddha image. Further event-related spectral perturbation (ERSP) analysis revealed that experienced meditators had a greater theta spectral power and higher intertrial coherence (ITC), indicating that they could more flexibly modulate ongoing cognitive processes than beginner meditators.

Conclusion

Intuitive inquiry meditation could help beginner meditators detach from the concept of Buddha but not from that of the self. However, in experienced meditators, the opposite was true. ERSP analysis showed that only experienced meditators exhibited significant alterations in brain activity dynamics during intuitive inquiry meditation, which might enable these practitioners to become spontaneously detached from the concept of the self. These findings revealed the neural mechanism by which long-term practice of intuitive inquiry meditation can influence the doubting process and its effect on self-schema processing.

Electrocortical activity correlated with locomotor adaptation during split-belt treadmill walking

Locomotor adaptation is crucial for daily gait adjustments to changing environmental demands and obstacle avoidance. Mobile brain imaging with high-density electroencephalography (EEG) now permits quantification of electrocortical dynamics during human locomotion. To determine the brain areas involved in human locomotor adaptation, we recorded high-density EEG from healthy, young adults during split-belt treadmill walking. We incorporated a dual-electrode EEG system and neck electromyography to decrease motion and muscle artefacts. Voluntary movement preparation and execution have been linked to alpha (8-13 Hz) and beta band (13-30 Hz) desynchronizations in the sensorimotor and posterior parietal cortices, whereas theta band (4-7 Hz) modulations in the anterior cingulate have been correlated with movement error monitoring. We hypothesized that relative to normal walking, split-belt walking would elicit: (1) decreases in alpha and beta band power in sensorimotor and posterior parietal cortices, reflecting enhanced motor flexibility; and (2) increases in theta band power in anterior cingulate cortex, reflecting instability and balance errors that will diminish with practice. We found electrocortical activity in multiple regions that was associated with stages of gait adaptation. Data indicated that sensorimotor and posterior parietal cortices had decreased alpha and beta band spectral power during early adaptation to split-belt treadmill walking that gradually returned to pre-adaptation levels by the end of the adaptation period. Our findings emphasize that multiple brain areas are involved in adjusting gait under changing environmental demands during human walking. Future studies could use these findings on healthy, young participants to identify dysfunctional supraspinal mechanisms that may be impairing gait adaptation. KEY POINTS: Identifying the location and time course of electrical changes in the brain correlating with gait adaptation increases our understanding of brain function and provides targets for brain stimulation interventions. Using high-density EEG in combination with 3D biomechanics, we found changes in neural oscillations localized near the sensorimotor, posterior parietal and cingulate cortices during split-belt treadmill adaptation. These findings suggest that multiple cortical mechanisms may be associated with locomotor adaptation, and their temporal dynamics can be quantified using mobile EEG. Results from this study can serve as a reference model to examine brain dynamics in individuals with movement disorders that cause gait asymmetry and reduced gait adaptation.

Eye movements during phasic versus tonic rapid eye movement sleep are biomarkers of dissociable electroencephalogram processes for the consolidation of novel problem-solving skills

The hallmark eye movement (EM) bursts that occur during rapid eye movement (REM) sleep are markers of consolidation for procedural memory involving novel cognitive strategies and problem-solving skills. Examination of the brain activity associated with EMs during REM sleep might elucidate the processes involved in memory consolidation, and may uncover the functional significance of REM sleep and EMs themselves. Participants performed a REM-dependent, novel procedural problem-solving task (i.e. the Tower of Hanoi; ToH) before and after intervals of either overnight sleep (n = 20) or a daytime 8-hour wake period (n = 20). In addition, event-related spectral perturbation of the electroencephalogram (EEG) time-locked to EMs occurring either in bursts (i.e. phasic REM), or in isolation (i.e. tonic REM), were compared to sleep on a non-learning control night. ToH improvement was greater following sleep compared to wakefulness. During sleep, prefrontal theta (~2-8 Hz) and central-parietal-occipital sensorimotor rhythm (SMR) activity (~8-16 Hz) time-locked to EMs, were greater on the ToH night versus control night, and during phasic REM sleep, were both positively correlated with overnight memory improvements. Furthermore, SMR power during tonic REM increased significantly from the control night to ToH night, but was relatively stable from night to night during phasic REM. These results suggest that EMs are markers of learning-related increases in theta and SMR during phasic and tonic REM sleep. Phasic and tonic REM sleep may be functionally distinct in terms of their contribution to procedural memory consolidation.

Event-Related Spectral Perturbation, Inter Trial Coherence, and Functional Connectivity in motor execution: A comparative EEG study of old and young subjects

INTRODUCTION

The motor-related bioelectric brain activity of healthy young and old subjects was studied to understand the effect of aging on motor execution. A visually cued finger tapping movement paradigm and high-density EEG were used to examine the time and frequency characteristics.

METHODS

Twenty-two young and 22 healthy elderly adults participated in the study. Repeated trials of left and right index finger movements were recorded with a 128-channel EEG. Event-Related Spectral Perturbation (ERSP), Inter Trial Coherence (ITC), and Functional Connectivity were computed and compared between the age groups.

RESULTS

An age-dependent theta and alpha band ERSP decrease was observed over the frontal-midline area. Decrease of beta band ERSP was found over the ipsilateral central-parietal regions. Significant ITC differences were found in the delta and theta bands between old and young subjects over the contralateral parietal-occipital areas. The spatial extent of increased ITC values was larger in old subjects. The movement execution of older subjects showed higher global efficiency in the delta and theta bands, and higher local efficiency and node strengths in the delta, theta, alpha, and beta bands.

CONCLUSION

As functional compensation of aging, elderly motor networks involve more nonmotor, parietal-occipital, and frontal areas, with higher global and local efficiency, node strength. ERSP and ITC changes seem to be sensitive and complementary biomarkers of age-related motor execution.

Differences in electroencephalography oscillations between normal aging and mild cognitive impairment during semantic memory retrieval

Semantic memory remains relatively stable with normal cognitive aging and declines in early stages of neurodegenerative disease. We measured electroencephalography (EEG) oscillatory correlates of semantic memory retrieval to examine the effects of normal and pathological aging. Twenty-nine cognitively healthy young adults (YA), 22 cognitively healthy aging adults (HA) and 20 patients with mild cognitive impairment (MCI) completed a semantic memory retrieval task with concurrent EEG recording in which they judged whether two words (features of objects) led to retrieval of an object (retrieval) or not (non-retrieval). Event-related power changes contrasting the two conditions (retrieval vs. non-retrieval) within theta, alpha, low-beta and high-beta EEG frequency bands were examined for normal aging (YA vs. HA) and pathological aging effects (HA vs. MCI). With no behavioural differences between the two normal age groups, we found later theta and alpha event-related power differences between conditions only in YA and a high-beta event-related power difference only in HA. For pathological aging effects, with reduced accuracy in MCI, we found different EEG patterns of early event-related beta power differences between conditions in MCI compared with HA and an event-related low-beta power difference only in HA. Beta oscillations were correlated with behavioural performance only in HA. We conclude that the aging brain relies on faster (beta) oscillations during the semantic memory task. With pathological aging, retrieval accuracy declines and pattern of beta oscillation changes. The findings provide insights about age-related neural mechanisms underlying semantic memory and have implications for early detection of pathological aging.

Tensor Decomposition Analysis of Longitudinal EEG Signals Reveals Differential Oscillatory Dynamics in Eyes-Closed and Eyes-Open Motor Imagery BCI: A Case Report

Functional dissociation of brain neural activity induced by opening or closing the eyes has been well established. However, how the temporal dynamics of the underlying neuronal modulations differ between these eye conditions during movement-related behaviours is less known. Using a robotic-assisted motor imagery brain-computer interface (MI BCI), we measured neural activity over the motor regions with electroencephalography (EEG) in a stroke survivor during his longitudinal rehabilitation training. We investigated lateralized oscillatory sensorimotor rhythm modulations while the patient imagined moving his hemiplegic hand with closed and open eyes to control an external robotic splint. In order to precisely identify the main profiles of neural activation affected by MI with eyes-open (MIEO) and eyes-closed (MIEC), a data-driven approach based on parallel factor analysis (PARAFAC) tensor decomposition was employed. Using the proposed framework, a set of narrow-band, subject-specific sensorimotor rhythms was identified; each of them had its own spatial and time signature. When MIEC trials were compared with MIEO trials, three key narrow-band rhythms whose peak frequencies centred at ∼8.0 Hz, ∼11.5 Hz, and ∼15.5 Hz, were identified with differently modulated oscillatory dynamics during movement preparation, initiation, and completion time frames. Furthermore, we observed that lower and higher sensorimotor oscillations represent different functional mechanisms within the MI paradigm, reinforcing the hypothesis that rhythmic activity in the human sensorimotor system is dissociated. Leveraging PARAFAC, this study achieves remarkable precision in estimating latent sensorimotor neural substrates, aiding the investigation of the specific functional mechanisms involved in the MI process.

Instant Effects of Semantic Information on Visual Perception

Does our perception of an object change once we discover what function it serves? We showed human participants (n = 48, 31 females and 17 males) pictures of unfamiliar objects either together with keywords matching their function, leading to semantically informed perception, or together with nonmatching keywords, resulting in uninformed perception. We measured event-related potentials to investigate at which stages in the visual processing hierarchy these two types of object perception differed from one another. We found that semantically informed compared with uninformed perception was associated with larger amplitudes in the N170 component (150-200 ms), reduced amplitudes in the N400 component (400-700 ms), and a late decrease in alpha/beta band power. When the same objects were presented once more without any information, the N400 and event-related power effects persisted, and we also observed enlarged amplitudes in the P1 component (100-150 ms) in response to objects for which semantically informed perception had taken place. Consistent with previous work, this suggests that obtaining semantic information about previously unfamiliar objects alters aspects of their lower-level visual perception (P1 component), higher-level visual perception (N170 component), and semantic processing (N400 component, event-related power). Our study is the first to show that such effects occur instantly after semantic information has been provided for the first time, without requiring extensive learning.SIGNIFICANCE STATEMENT There has been a long-standing debate about whether or not higher-level cognitive capacities, such as semantic knowledge, can influence lower-level perceptual processing in a top-down fashion. Here we could show, for the first time, that information about the function of previously unfamiliar objects immediately influences cortical processing within less than 200 ms. Of note, this influence does not require training or experience with the objects and related semantic information. Therefore, our study is the first to show effects of cognition on perception while ruling out the possibility that prior knowledge merely acts by preactivating or altering stored visual representations. Instead, this knowledge seems to alter perception online, thus providing a compelling case against the impenetrability of perception by cognition.

Rule Abstraction Is Facilitated by Auditory Cuing in REM Sleep

Sleep facilitates abstraction, but the exact mechanisms underpinning this are unknown. Here, we aimed to determine whether triggering reactivation in sleep could facilitate this process. We paired abstraction problems with sounds, then replayed these during either slow-wave sleep (SWS) or rapid eye movement (REM) sleep to trigger memory reactivation in 27 human participants (19 female). This revealed performance improvements on abstraction problems that were cued in REM, but not problems cued in SWS. Interestingly, the cue-related improvement was not significant until a follow-up retest 1 week after the manipulation, suggesting that REM may initiate a sequence of plasticity events that requires more time to be implemented. Furthermore, memory-linked trigger sounds evoked distinct neural responses in REM, but not SWS. Overall, our findings suggest that targeted memory reactivation in REM can facilitate visual rule abstraction, although this effect takes time to unfold.SIGNIFICANCE STATEMENT The ability to abstract rules from a corpus of experiences is a building block of human reasoning. Sleep is known to facilitate rule abstraction, but it remains unclear whether we can manipulate this process actively and which stage of sleep is most important. Targeted memory reactivation (TMR) is a technique that uses re-exposure to learning-related sensory cues during sleep to enhance memory consolidation. Here, we show that TMR, when applied during REM sleep, can facilitate the complex recombining of information needed for rule abstraction. Furthermore, we show that this qualitative REM-related benefit emerges over the course of a week after learning, suggesting that memory integration may require a slower form of plasticity.

Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements

Planning goal-directed movements towards different targets is at the basis of common daily activities (e.g., reaching), involving visual, visuomotor, and sensorimotor brain areas. Alpha (8-13 Hz) and beta (13-30 Hz) oscillations are modulated during movement preparation and are implicated in correct motor functioning. However, how brain regions activate and interact during reaching tasks and how brain rhythms are functionally involved in these interactions is still limitedly explored. Here, alpha and beta brain activity and connectivity during reaching preparation are investigated at EEG-source level, considering a network of task-related cortical areas. Sixty-channel EEG was recorded from 20 healthy participants during a delayed center-out reaching task and projected to the cortex to extract the activity of 8 cortical regions per hemisphere (2 occipital, 2 parietal, 3 peri-central, 1 frontal). Then, we analyzed event-related spectral perturbations and directed connectivity, computed via spectral Granger causality and summarized using graph theory centrality indices (in degree, out degree). Results suggest that alpha and beta oscillations are functionally involved in the preparation of reaching in different ways, with the former mediating the inhibition of the ipsilateral sensorimotor areas and disinhibition of visual areas, and the latter coordinating disinhibition of the contralateral sensorimotor and visuomotor areas.

Cross-modal interactions at the audiovisual cocktail-party revealed by behavior, ERPs, and neural oscillations

Theories of attention argue that objects are the units of attentional selection. In real-word environments such objects can contain visual and auditory features. To understand how mechanisms of selective attention operate in multisensory environments, in this pre-registered study, we created an audiovisual cocktail-party situation, in which two speakers (left and right of fixation) simultaneously articulated brief numerals. In three separate blocks, informative auditory speech was presented (a) alone or paired with (b) congruent or (c) uninformative visual speech. In all blocks, subjects localized a pre-defined numeral. While audiovisual-congruent and uninformative speech improved response times and speed of information uptake according to diffusion modeling, an ERP analysis revealed that this did not coincide with enhanced attentional engagement. Yet, consistent with object-based attentional selection, the deployment of auditory spatial attention (N2ac) was accompanied by visuo-spatial attentional orienting (N2pc) irrespective of the informational content of visual speech. Notably, an N2pc component was absent in the auditory-only condition, demonstrating that a sound-induced shift of visuo-spatial attention relies on the availability of audio-visual features evolving coherently in time. Additional exploratory analyses revealed cross-modal interactions in working memory and modulations of cognitive control.

Pre-stimulus beta power varies as a function of auditory-motor synchronization and temporal predictability

Introduction

Auditory-motor interactions can support the preparation for expected sensory input. We investigated the periodic modulation of beta activity in the electroencephalogram to assess the role of active auditory-motor synchronization. Pre-stimulus beta activity (13–30 Hz) has been interpreted as a neural signature of the preparation for expected sensory input.

Methods

In the current study, participants silently counted frequency deviants in sequences of pure tones either during a physically inactive control condition or while pedaling on a cycling ergometer. Tones were presented either rhythmically (at 1 Hz) or arrhythmically with variable intervals. In addition to the pedaling conditions with rhythmic (auditory-motor synchronization, AMS) or arrhythmic stimulation, a self-generated stimulus condition was used in which tones were presented in sync with the participants’ spontaneous pedaling. This condition served to explore whether sensory predictions are driven primarily by the auditory or by the motor system.

Results

Pre-stimulus beta power increased for rhythmic compared to arrhythmic stimulus presentation in both sitting and pedaling conditions but was strongest in the AMS condition. Furthermore, beta power in the AMS condition correlated with motor performance, i.e., the better participants synchronized with the rhythmic stimulus sequence, the higher was pre-stimulus beta power. Additionally, beta power was increased for the self-generated stimulus condition compared with arrhythmic pedaling, but there was no difference between the self-generated and the AMS condition.

Discussion

The current data pattern indicates that pre-stimulus beta power is not limited to neuronal entrainment (i.e., periodic stimulus presentation) but represents a more general correlate of temporal anticipation. Its association with the precision of AMS supports the role of active behavior for auditory predictions.

EEG responses to standardised noxious stimulation during clinical anaesthesia: a pilot study

Background

During clinical anaesthesia, the administration of analgesics mostly relies on empirical knowledge and observation of the patient's reactions to noxious stimuli. Previous studies in healthy volunteers under controlled conditions revealed EEG activity in response to standardised nociceptive stimuli even at high doses of remifentanil and propofol. This pilot study aims to investigate the feasibility of using these standardised nociceptive stimuli in routine clinical practice.

Methods

We studied 17 patients undergoing orthopaedic trauma surgery under general anaesthesia. We evaluated if the EEG could track standardised noxious phase-locked electrical stimulation and tetanic stimulation, a time-locked surrogate for incisional pain, before, during, and after the induction of general anaesthesia. Subsequently, we analysed the effect of tetanic stimulation on the surgical pleth index as a peripheral, vegetative, nociceptive marker.

Results

We found that the phase-locked evoked potentials after noxious electrical stimulation vanished after the administration of propofol, but not at low concentrations of remifentanil. After noxious tetanic stimulation under general anaesthesia, there were no consistent spectral changes in the EEG, but the vegetative response in the surgical pleth index was statistically significant (Hedges' g effect size 0.32 [95% confidence interval 0.12-0.77], P=0.035).

Conclusion

Our standardised nociceptive stimuli are not optimised for obtaining consistent EEG responses in patients during clinical anaesthesia. To validate and sufficiently reproduce EEG-based standardised stimulation as a marker for nociception in clinical anaesthesia, other pain models or stimulation settings might be required to transfer preclinical studies into clinical practice.

Clinical trial registration

DRKS00017829.

Musical tempo affects EEG spectral dynamics during subsequent time estimation

The perception of time depends on the rhythmicity of internal and external synchronizers. One external synchronizer that affects time estimation is music. This study aimed to analyze the effects of musical tempi on EEG spectral dynamics during subsequent time estimation. Participants performed a time production task after (i) silence and (ii) listening to music at different tempi -90, 120, and 150 bpm- while EEG activity was recorded. While listening, there was an increase in alpha power at all tempi compared to the resting state and an increase of beta at the fastest tempo. The beta increase persisted during the subsequent time estimations, with higher beta power during the task after listening to music at the fastest tempo than task performance without music. Spectral dynamics in frontal regions showed lower alpha activity in the final stages of time estimations after listening to music at 90- and 120-bpm than in the silence condition and higher beta in the early stages at 150 bpm. Behaviorally, the 120 bpm musical tempo produced slight improvements. Listening to music modified tonic EEG activity that subsequently affected EEG dynamics during time production. Music at a more optimal rate could have benefited temporal expectation and anticipation. The fastest musical tempo may have generated an over-activated state that affected subsequent time estimations. These results emphasize the importance of music as an external stimulus that can affect brain functional organization during time perception even after listening.

EEG-based sensory testing reveals altered nociceptive processing in elite endurance athletes

Increased exercise loads, as observed in elite athletes, seem to modulate the subjective pain perception in healthy subjects. The combination of electroencephalography (EEG) and standardized noxious stimulation can contribute to an objective assessment of the somatosensory stimulus processing. We assessed the subjective pain ratings and the electroencephalogram (EEG)-based response after standardized noxious mechanical and thermal stimuli as well as during conditioned pain modulation (CPM) in 26 elite endurance athletes and compared them to 26 recreationally active controls. Elite endurance athletes had consistently stronger somatosensory responses in the EEG to both mechanical and thermal noxious stimuli than the control group. We observed no significant group differences in the subjective pain ratings, which may have been influenced by our statistics and choice of stimuli. The CPM testing revealed that our conditioning stimulus modulated the subjective pain perception only in the control group, whereas the EEG indicated a modulatory effect of the conditioning stimulus on the spectral response only in the athletes group. We conclude that a higher activation in the cortical regions that process nociceptive information may either be an indicator for central sensitization or an altered stimulus salience in the elite endurance athletes' group. Our findings from our CPM testing were limited by our methodology. Further longitudinal studies are needed to examine if exercise-induced changes in the somatosensory system might have a critical impact on the long-term health of athletes.

Agency affects pain inference through prior shift as opposed to likelihood precision modulation in a Bayesian pain model

Agency and expectations play a crucial role in pain perception and treatment. In the Bayesian pain model, somatosensation (likelihood) and expectations (prior) are weighted by their precision and integrated to form a pain percept (posterior). Combining pain treatment with stimulus-related expectations allows the mechanistic assessment of whether agency enters this model as a shift of the prior or a relaxation of the likelihood precision. In two experiments, heat pain was sham treated either externally or by the subject, while a predictive cue was utilized to create high or low treatment expectations. Both experiments revealed additive effects and greater pain relief under self-treatment and high treatment expectations. Formal model comparisons favored a prior shift rather than a modulation of likelihood precision. Electroencephalography revealed a theta-to-alpha effect, temporally associated with expectations, which was correlated with trial-by-trial pain ratings, further supporting a prior shift through which agency exerts its influence in the Bayesian pain model.

High precision magnetoencephalography reveals increased right-inferior frontal gyrus beta power during response conflict

Flexibility of behavior and the ability to rapidly switch actions is critical for adaptive living in humans. It is well established that the right-inferior frontal gyrus (R-IFG) is recruited during outright action-stopping, relating to increased beta (12-30 Hz) power. It has also been posited that inhibiting incorrect response tendencies and switching is central to motor flexibility. However, it is not known if the commonly reported R-IFG beta signature of response inhibition in action-stopping is also recruited during response conflict, which would suggest overlapping networks for stopping and switching. In the current study, we analyzed high precision magnetoencephalography (hpMEG) data recorded with multiple within subject recording sessions (trials n > 10,000) from 8 subjects during different levels of response conflict. We hypothesized that a R-IFG-triggered network for response inhibition is domain general and therefore also involved in mediating response conflict. We tested whether R-IFG showed increased beta power dependent on the level of response conflict. Using event-related spectral perturbations and linear mixed modeling, we found that R-IFG beta power increased for response conflict trials. The R-IFG beta increase was specific to trials with strong response conflict, and increased R-IFG beta power related to less error. This supports a more generalized role for R-IFG beta, beyond simple stopping behavior towards response switching.

Virtual accident curb risk habituation in workers by restoring sensory responses to real-world warning

In high-risk work environments, workers become habituated to hazards they frequently encounter, subsequently underestimating risk and engaging in unsafe behaviors. This phenomenon has been termed "risk habituation" and identified as a vital root cause of fatalities and injuries at workplaces. Providing an effective intervention that curbs workers' risk habituation is critical in preventing occupational injuries and fatalities. However, there exists no empirically supported intervention for curbing risk habituation. To this end, here we investigated how experiencing an accident in a virtual reality (VR) environment affects workers' risk habituation toward repeatedly exposed workplace hazards. We examined an underlying mechanism of risk habituation at the sensory level and evaluated the effect of the accident intervention through electroencephalography (EEG). The results of pre- and posttreatment analyses indicate experiencing the virtual accident effectively curbs risk habituation at both the behavioral and sensory level. The findings open new vistas for occupational safety training.