Spherical splines for scalp potential and current density mapping

Brain oscillatory processes related to sequence memory in healthy older adults

Sequence memory is subject to age-related decline, but the underlying processes are not yet fully understood. We analyzed electroencephalography (EEG) in 21 healthy older (60-80 years) and 26 young participants (20-30 years) and compared time-frequency spectra and theta-gamma phase-amplitude-coupling (PAC) during encoding of the order of visually presented items. In older adults, desynchronization in theta (4-8 Hz) and synchronization in gamma (30-45 Hz) power did not distinguish between subsequently correctly and incorrectly remembered trials, while there was a subsequent memory effect for young adults. Theta-gamma PAC was modulated by item position within a sequence for older but not young adults. Specifically, position within a sequence was coded by higher gamma amplitude for successive theta phases for later correctly remembered trials. Thus, deficient differentiation in theta desynchronization and gamma oscillations during sequence encoding in older adults may reflect neurophysiological correlates of age-related memory decline. Furthermore, our results indicate that sequences are coded by theta-gamma PAC in older adults, but that this mechanism might lose precision in aging.

Neural representations of statistical and rule-based predictions in Gilles de la Tourette syndrome

Gilles de la Tourette syndrome (GTS) is a disorder characterised by motor and vocal tics, which may represent habitual actions as a result of enhanced learning of associations between stimuli and responses (S-R). In this study, we investigated how adults with GTS and healthy controls (HC) learn two types of regularities in a sequence: statistics (non-adjacent probabilities) and rules (predefined order). Participants completed a visuomotor sequence learning task while EEG was recorded. To understand the neurophysiological underpinnings of these regularities in GTS, multivariate pattern analyses on the temporally decomposed EEG signal as well as sLORETA source localisation method were conducted. We found that people with GTS showed superior statistical learning but comparable rule-based learning compared to HC participants. Adults with GTS had different neural representations for both statistics and rules than HC adults; specifically, adults with GTS maintained the regularity representations longer and had more overlap between them than HCs. Moreover, over different time scales, distinct fronto-parietal structures contribute to statistical learning in the GTS and HC groups. We propose that hyper-learning in GTS is a consequence of the altered sensitivity to encode complex statistics, which might lead to habitual actions.

Analysis of modulations of mental fatigue on intra-individual variability from single-trial event related potentials

BACKGROUND

Intra-individual variability (IIV), a measure of variance within an individual's performance, has been demonstrated as metrics of brain responses for neural functionality. However, how mental fatigue modulates IIV remains unclear. Consequently, the development of robust mental fatigue detection methods at the single-trial level is challenging.

NEW METHODS

Based on a long-duration flanker task EEG dataset, the modulations of mental fatigue on IIV were explored in terms of response time (RT) and trial-to-trial latency variations of event-related potentials (ERPs). Specifically, latency variations were quantified using residue iteration decomposition (RIDE) to reconstruct latency-corrected ERPs. We compared reconstructed ERPs with raw ERPs by means of temporal principal component analysis (PCA). Furthermore, a single-trial classification pipeline was developed to detect the changes of mental fatigue levels.

RESULTS

We found an increased IIV in the RT metric in the fatigue state compared to the alert state. The same sequence of ERPs (N1, P2, N2, P3a, P3b, and slow wave, or SW) was separated from both raw and reconstructed ERPs using PCA, whereas differences between raw and reconstructed ERPs in explained variances for separated ERPs were found owing to IIV. Particularly, a stronger N2 was detected in the fatigue than alert state after RIDE. The single-trial fatigue detection pipeline yielded an acceptable accuracy of 73.3%.

COMPARISON WITH EXISTING METHODS

The IIV has been linked to aging and brain disorders, and as an extension, our finding demonstrates IIV as an efficient indicator of mental fatigue.

CONCLUSIONS

This study reveals significant modulations of mental fatigue on IIV at the behavioral and neural levels and establishes a robust mental fatigue detection pipeline.

Frontal alpha asymmetry during emotion regulation in adults with lifetime major depression

Emotion regulation (ER) often is impaired in current or remitted major depression (MD), although the extent of the deficits is not fully understood. Recent studies suggest that frontal alpha asymmetry (FAA) could be a promising electrophysiological measure to investigate ER. The purpose of this study was to investigate ER differences between participants with lifetime major depression (lifetime MD) and healthy controls (HC) for the first time in an experimental task by using FAA. We compared lifetime MD (n = 34) and HC (n = 25) participants aged 18-24 years in (a) an active ER condition, in which participants were instructed to reappraise negative images and (b) a condition in which they attended to the images while an EEG was recorded. We also report FAA results from an independent sample of adolescents with current MD (n = 36) and HC adolescents (n = 38). In the main sample, both groups were able to decrease self-reported negative affect in response to negative images through ER, without significant group differences. We found no differences between groups or conditions in FAA, which was replicated within the independent adolescent sample. The lifetime MD group also reported less adaptive ER in daily life and higher difficulty of ER during the task. The lack of differences between in self-reported affect and FAA between lifetime MD and HC groups in the active ER task indicates that lifetime MD participants show no impairments when instructed to apply an adaptive ER strategy. Implications for interventional aspects are discussed.

Electrophysiological responses of audiovisual integration from infancy to adulthood

Our ability to merge information from different senses into a unified percept is a crucial perceptual process for efficient interaction with our multisensory environment. Yet, the developmental process underlying how the brain implements multisensory integration (MSI) remains poorly known. This cross-sectional study aims to characterize the developmental patterns of audiovisual events in 131 individuals aged from 3 months to 30 years. Electroencephalography (EEG) was recorded during a passive task, including simple auditory, visual, and audiovisual stimuli. In addition to examining age-related variations in MSI responses, we investigated Event-Related Potentials (ERPs) linked with auditory and visual stimulation alone. This was done to depict the typical developmental trajectory of unisensory processing from infancy to adulthood within our sample and to contextualize the maturation effects of MSI in relation to unisensory development. Comparing the neural response to audiovisual stimuli to the sum of the unisensory responses revealed signs of MSI in the ERPs, more specifically between the P2 and N2 components (P2 effect). Furthermore, adult-like MSI responses emerge relatively late in the development, around 8 years old. The automatic integration of simple audiovisual stimuli is a long developmental process that emerges during childhood and continues to mature during adolescence with ERP latencies decreasing with age.

Asynchronous behavioral and neurophysiological changes in word production in the adult lifespan

Behavioral and brain-related changes in word production have been claimed to predominantly occur after 70 years of age. Most studies investigating age-related changes in adulthood only compared young to older adults, failing to determine whether neural processes underlying word production change at an earlier age than observed in behavior. This study aims to fill this gap by investigating whether changes in neurophysiological processes underlying word production are aligned with behavioral changes. Behavior and the electrophysiological event-related potential patterns of word production were assessed during a picture naming task in 95 participants across five adult lifespan age groups (ranging from 16 to 80 years old). While behavioral performance decreased starting from 70 years of age, significant neurophysiological changes were present at the age of 40 years old, in a time window (between 150 and 220 ms) likely associated with lexical-semantic processes underlying referential word production. These results show that neurophysiological modifications precede the behavioral changes in language production; they can be interpreted in line with the suggestion that the lexical-semantic reorganization in mid-adulthood influences the maintenance of language skills longer than for other cognitive functions.

Cardiorespiratory rhythm-contingent trace eyeblink conditioning in elderly adults

Learning outcome is modified by the degree to which the subject responds and pays attention to specific stimuli. Our recent research suggests that presenting stimuli in contingency with a specific phase of the cardiorespiratory rhythm might expedite learning. Specifically, expiration-diastole (EXP-DIA) is beneficial for learning trace eyeblink conditioning (TEBC) compared with inspiration-systole (INS-SYS) in healthy young adults. The aim of this study was to investigate whether the same holds true in healthy elderly adults (n = 50, aged >70 yr). Participants were instructed to watch a silent nature film while TEBC trials were presented at either INS-SYS or EXP-DIA (separate groups). Learned responses were determined as eyeblinks occurring after the tone conditioned stimulus (CS), immediately preceding the air puff unconditioned stimulus (US). Participants were classified as learners if they made at least five conditioned responses (CRs). Brain responses to the stimuli were measured by electroencephalogram (EEG). Memory for the film and awareness of the CS-US contingency were evaluated with a questionnaire. As a result, participants showed robust brain responses to the CS, acquired CRs, and reported awareness of the CS-US relationship to a variable degree. There was no difference between the INS-SYS and EXP-DIA groups in any of the above. However, when only participants who learned were considered, those trained at EXP-DIA (n = 11) made more CRs than those trained at INS-SYS (n = 13). Thus, learned performance could be facilitated in those elderly who learned. However, training at a specific phase of cardiorespiratory rhythm did not increase the proportion of participants who learned.NEW & NOTEWORTHY We trained healthy elderly individuals in trace eyeblink conditioning, either at inspiration-systole or at expiration-diastole. Those who learned exhibited more conditioned responses when trained at expiration-diastole rather than inspiration-systole. However, there was no difference between the experimental groups in the proportion of individuals who learned or did not learn.

Electrophysiological Measures of Listening-in-Noise With and Without Remote Microphone System Use in Autistic and Non-Autistic Youth

OBJECTIVES

This study examined the neural mechanisms by which remote microphone (RM) systems might lead to improved behavioral performance on listening-in-noise tasks in autistic and non-autistic youth.

DESIGN

Cortical auditory evoked potentials (CAEPs) were recorded in autistic (n = 25) and non-autistic (n = 22) youth who were matched at the group level on chronological age ( M = 14.21 ± 3.39 years) and biological sex. Potentials were recorded during an active syllable identification task completed in quiet and in multi-talker babble noise with and without the use of an RM system. The effects of noise and RM system use on speech-sound-evoked P1-N1-P2 responses and the associations between the cortical responses and behavioral performance on syllable identification were examined.

RESULTS

No group differences were observed for behavioral or CAEP measures of speech processing in quiet or in noise. In the combined sample, syllable identification in noise was less accurate and slower than in the quiet condition. The addition of the RM system to the noise condition restored accuracy, but not the response speed, to the levels observed in quiet. The CAEP analyses noted amplitude reductions and latency delays in the noise compared with the quiet condition. The RM system use increased the N1 amplitude as well as reduced and delayed the P2 response relative to the quiet and noise conditions. Exploratory brain-behavior correlations revealed that larger N1 amplitudes in the RM condition were associated with greater behavioral accuracy of syllable identification. Reduced N1 amplitude and accelerated P2 response were associated with shorter syllable identification response times when listening with the RM system.

CONCLUSIONS

Findings suggest that although listening-in-noise with an RM system might remain effortful, the improved signal to noise ratio facilitates attention to the sensory features of the stimuli and increases speech sound identification accuracy.

Topographical Features of Pediatric Electroencephalography during High Initial Concentration Sevoflurane for Inhalational Induction of Anesthesia

BACKGROUND

High-density electroencephalographic (EEG) monitoring remains underutilized in clinical anesthesia, despite its obvious utility in unraveling the profound physiologic impact of these agents on central nervous system functioning. In school-aged children, the routine practice of rapid induction with high concentrations of inspiratory sevoflurane is commonplace, given its favorable efficacy and tolerance profile. However, few studies investigate topographic EEG during the critical timepoint coinciding with loss of responsiveness-a key moment for anesthesiologists in their everyday practice. The authors hypothesized that high initial sevoflurane inhalation would better precipitate changes in brain regions due to inhomogeneities in maturation across three different age groups compared with gradual stepwise paradigms utilized by other investigators. Knowledge of these changes may inform strategies for agent titration in everyday clinical settings.

METHODS

A total of 37 healthy children aged 5 to 10 yr underwent induction with 4% or greater sevoflurane in high-flow oxygen. Perturbations in anesthetic state were investigated in 23 of these children using 64-channel EEG with the Hjorth Laplacian referencing scheme. Topographical maps illustrated absolute, relative, and total band power across three age groups: 5 to 6 yr (n = 7), 7 to 8 yr (n = 8), and 9 to 10 yr (n = 8).

RESULTS

Spectral analysis revealed a large shift in total power driven by increased delta oscillations. Well-described topographic patterns of anesthesia, e.g., frontal predominance, paradoxical beta excitation, and increased slow activity, were evident in the topographic maps. However, there were no statistically significant age-related changes in spectral power observed in a midline electrode subset between the groups when responsiveness was lost compared to the resting state.

CONCLUSIONS

High initial concentration sevoflurane induction causes large-scale topographic effects on the pediatric EEG. Within the minute after unresponsiveness, this dosage may perturb EEG activity in children to an extent where age-related differences are not discernible.

EDITOR’S PERSPECTIVE

The Impact of Spectral and Temporal Degradation on Vocoded Speech Recognition in Early-Blind Individuals

This study compared the impact of spectral and temporal degradation on vocoded speech recognition between early-blind and sighted subjects. The participants included 25 early-blind subjects (30.32 ± 4.88 years; male:female, 14:11) and 25 age- and sex-matched sighted subjects. Tests included monosyllable recognition in noise at various signal-to-noise ratios (-18 to -4 dB), matrix sentence-in-noise recognition, and vocoded speech recognition with different numbers of channels (4, 8, 16, and 32) and temporal envelope cutoff frequencies (50 vs 500 Hz). Cortical-evoked potentials (N2 and P3b) were measured in response to spectrally and temporally degraded stimuli. The early-blind subjects displayed superior monosyllable and sentence recognition than sighted subjects (all p < 0.01). In the vocoded speech recognition test, a three-way repeated-measure analysis of variance (two groups × four channels × two cutoff frequencies) revealed significant main effects of group, channel, and cutoff frequency (all p < 0.001). Early-blind subjects showed increased sensitivity to spectral degradation for speech recognition, evident in the significant interaction between group and channel (p = 0.007). N2 responses in early-blind subjects exhibited shorter latency and greater amplitude in the 8-channel (p = 0.022 and 0.034, respectively) and shorter latency in the 16-channel (p = 0.049) compared with sighted subjects. In conclusion, early-blind subjects demonstrated speech recognition advantages over sighted subjects, even in the presence of spectral and temporal degradation. Spectral degradation had a greater impact on speech recognition in early-blind subjects, while the effect of temporal degradation was similar in both groups.

Electroencephalography Microstate Class D is a Brain Marker of Subjective Sleep Quality for College Students with High Habitual Sleep Efficiency

Subjective sleep quality is an individual's subjective sleep feeling, and its effective evaluation is the premise of improving sleep quality. However, people with autism or mental disorders often experience difficulties in verbally expressing their subjective sleep quality. To solve the above problem, this study provides a non-verbal and convenient brain feature to assess subjective sleep quality. Reportedly, microstates are often used to characterize the patterns of functional brain activity in humans. The occurrence frequency of microstate class D is an important feature in the insomnia population. We therefore hypothesize that the occurrence frequency of microstate class D is a physiological indicator of subjective sleep quality. To test this hypothesis, we recruited college students from China as participants [N = 61, mean age = 20.84 years]. The Chinese version of the Pittsburgh Sleep Quality Index scale was used to measure subjective sleep quality and habitual sleep efficiency, and the state characteristics of the brain at this time were assessed using closed eyes resting-state brain microstate class D. The occurrence frequency of EEG microstate class D was positively associated with subjective sleep quality (r = 0.32, p < 0.05). Further analysis of the moderating effect showed that the occurrence frequency of microstate class D was significantly and positively correlated with subjective sleep quality in the high habitual sleep efficiency group. However, the relationship was not significant in the low sleep efficiency group (βsimple = 0.63, p < 0.001). This study shows that the occurrence frequency of microstate class D is a physiological indicator of assessing subjective sleep quality levels in the high sleep efficiency group. This study provides brain features for assessing subjective sleep quality of people with autism and mental disorders who cannot effectively describe their subjective feelings.

Electrophysiological correlates of inhibitory control in children: Relations with prenatal maternal risk factors and child psychopathology

Inhibitory control plays an important role in children's cognitive and socioemotional development, including their psychopathology. It has been established that contextual factors such as socioeconomic status (SES) and parents' psychopathology are associated with children's inhibitory control. However, the relations between the neural correlates of inhibitory control and contextual factors have been rarely examined in longitudinal studies. In the present study, we used both event-related potential (ERP) components and time-frequency measures of inhibitory control to evaluate the neural pathways between contextual factors, including prenatal SES and maternal psychopathology, and children's behavioral and emotional problems in a large sample of children (N = 560; 51.75% females; Mage = 7.13 years; Rangeage = 4-11 years). Results showed that theta power, which was positively predicted by prenatal SES and was negatively related to children's externalizing problems, mediated the longitudinal and negative relation between them. ERP amplitudes and latencies did not mediate the longitudinal association between prenatal risk factors (i.e., prenatal SES and maternal psychopathology) and children's internalizing and externalizing problems. Our findings increase our understanding of the neural pathways linking early risk factors to children's psychopathology.

The time course of feature-selective attention inside and outside the focus of spatial attention

Research on attentional selection of stimulus features has yielded seemingly contradictory results. On the one hand, many experiments in humans and animals have observed a "global" facilitation of attended features across the entire visual field, even when spatial attention is focused on a single location. On the other hand, several event-related potential studies in humans reported that attended features are enhanced at the attended location only. The present experiment demonstrates that these conflicting results can be explained by differences in the timing of attentional allocation inside and outside the spatial focus of attention. Participants attended to fields of either red or blue randomly moving dots on either the left or right side of fixation with the task of detecting brief coherent motion targets. Recordings of steady-state visual evoked potentials elicited by the flickering stimuli allowed concurrent measurement of the time course of feature-selective attention in visual cortex on both the attended and the unattended sides. The onset of feature-selective attentional modulation on the attended side occurred around 150 ms earlier than on the unattended side. This finding that feature-selective attention is not spatially global from the outset but extends to unattended locations after a temporal delay resolves previous contradictions between studies finding global versus hierarchical selection of features and provides insight into the fundamental relationship between feature-based and location-based (spatial) attention mechanisms.

Effect of spectral degradation on speech intelligibility and cortical representation

Noise-vocoded speech has long been used to investigate how acoustic cues affect speech understanding. Studies indicate that reducing the number of spectral channel bands diminishes speech intelligibility. Despite previous studies examining the channel band effect using earlier event-related potential (ERP) components, such as P1, N1, and P2, a clear consensus or understanding remains elusive. Given our hypothesis that spectral degradation affects higher-order processing of speech understanding beyond mere perception, we aimed to objectively measure differences in higher-order abilities to discriminate or interpret meaning. Using an oddball paradigm with speech stimuli, we examined how neural signals correlate with the evaluation of speech stimuli based on the number of channel bands measuring N2 and P3b components. In 20 young participants with normal hearing, we measured speech intelligibility and N2 and P3b responses using a one-syllable task paradigm with animal and non-animal stimuli across four vocoder conditions with 4, 8, 16, or 32 channel bands. Behavioral data from word repetition clearly affected the number of channel bands, and all pairs were significantly different (p < 0.001). We also observed significant effects of the number of channels on the peak amplitude [F(2.006, 38.117) = 9.077, p < 0.001] and peak latency [F(3, 57) = 26.642, p < 0.001] of the N2 component. Similarly, the P3b component showed significant main effects of the number of channel bands on the peak amplitude [F(2.231, 42.391) = 13.045, p < 0.001] and peak latency [F(3, 57) = 2.968, p = 0.039]. In summary, our findings provide compelling evidence that spectral channel bands profoundly influence cortical speech processing, as reflected in the N2 and P3b components, a higher-order cognitive process. We conclude that spectrally degraded one-syllable speech primarily affects cortical responses during semantic integration.

Why is there an error negativity on correct trials? A reappraisal

In healthy subjects, the Error Negativity (Ne) was initially reported on errors and on partial errors, only. Later on, application of the Laplacian transformation to EEG data unmasked a Ne-like wave (Nc) that shares a main generator with the Ne, suggesting that the Nc is just a small Ne. However, the reason why a small Ne would persist on correct responses remains unclear. Now, sometimes, subthreshold EMG activations in the muscles corresponding to correct responses (not strong enough to reach the response threshold) can precede full-blown correct responses. These "partially correct" activities seem to correspond to (force) execution errors, as they evoke a sizeable Ne. Within the frames of the Reward Value and Prediction Model or of the Predicted Response-Outcome model we propose that the action monitoring system evokes a Ne/Nc on correct responses because, even when a correct choice has been made, the accuracy of response (force) execution cannot be fully predicted. If this interpretation is correct, it can be assumed that, once these execution errors have been corrected, the correctness of the (full-blown) correcting response is highly predictable. Consequently, they should evoke a smaller Nc/Ne than "pure" correct responses. We show, that for the response thresholds set in the present experiment, the correcting response of the trials containing a partially correct activation evoke no identifiable Nc at all. Therefore it seems that there usually is an Error Negativity on correct trials because the correctness of response (force) execution cannot be fully predicted.

A distributed theta network of error generation and processing in aging

Based on previous concepts that a distributed theta network with a central "hub" in the medial frontal cortex is critically involved in movement regulation, monitoring, and control, the present study explored the involvement of this network in error processing with advancing age in humans. For that aim, the oscillatory neurodynamics of motor theta oscillations was analyzed at multiple cortical regions during correct and error responses in a sample of older adults. Response-related potentials (RRPs) of correct and incorrect reactions were recorded in a four-choice reaction task. RRPs were decomposed in the time-frequency domain to extract oscillatory theta activity. Motor theta oscillations at extended motor regions were analyzed with respect to power, temporal synchronization, and functional connectivity. Major results demonstrated that errors had pronounced effects on motor theta oscillations at cortical regions beyond the medial frontal cortex by being associated with (1) theta power increase in the hemisphere contra-lateral to the movement, (2) suppressed spatial and temporal synchronization at pre-motor areas contra-lateral to the responding hand, (2) inhibited connections between the medial frontal cortex and sensorimotor areas, and (3) suppressed connectivity and temporal phase-synchronization of motor theta networks in the posterior left hemisphere, irrespective of the hand, left, or right, with which the error was made. The distributed effects of errors on motor theta oscillations demonstrate that theta networks support performance monitoring. The reorganization of these networks with aging implies that in older individuals, performance monitoring is associated with a disengagement of the medial frontal region and difficulties in controlling the focus of motor attention and response selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-10018-4.

High-density electroencephalographic functional networks in genetic generalized epilepsy: Preserved whole-brain topology hides local reorganization

OBJECTIVE

Genetic generalized epilepsy (GGE) accounts for approximately 20% of adult epilepsy cases and is considered a disorder of large brain networks, involving both hemispheres. Most studies have not shown any difference in functional whole-brain network topology when compared to healthy controls. Our objective was to examine whether this preserved global network topology could hide local reorganizations that balance out at the global network level.

METHODS

We recorded high-density electroencephalograms from 20 patients and 20 controls, and reconstructed the activity of 118 regions. We computed functional connectivity in windows free of interictal epileptiform discharges in broad, delta, theta, alpha, and beta frequency bands, characterized the network topology, and used the Hub Disruption Index (HDI) to quantify the topological reorganization. We examined the generalizability of our results by reproducing a 25-electrode clinical system.

RESULTS

Our study did not reveal any significant change in whole-brain network topology among GGE patients. However, the HDI was significantly different between patients and controls in all frequency bands except alpha (p < .01, false discovery rate [FDR] corrected, d < -1), and accompanied by an increase in connectivity in the prefrontal regions and default mode network. This reorganization suggests that regions that are important in transferring the information in controls were less so in patients. Inversely, the crucial regions in patients are less so in controls. These findings were also found in delta and theta frequency bands when using 25 electrodes (p < .001, FDR corrected, d < -1).

SIGNIFICANCE

In GGE patients, the overall network topology is similar to that of healthy controls but presents a balanced local topological reorganization. This reorganization causes the prefrontal areas and default mode network to be more integrated and segregated, which may explain executive impairment associated with GGE. Additionally, the reorganization distinguishes patients from controls even when using 25 electrodes, suggesting its potential use as a diagnostic tool.

Monitoring Changes in TMS-Evoked EEG and EMG Activity During 1 Hz rTMS of the Healthy Motor Cortex

Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique capable of inducing neuroplasticity as measured by changes in peripheral muscle electromyography (EMG) or electroencephalography (EEG) from pre-to-post stimulation. However, temporal courses of neuromodulation during ongoing rTMS are unclear. Monitoring cortical dynamics via TMS-evoked responses using EMG (motor-evoked potentials; MEPs) and EEG (transcranial-evoked potentials; TEPs) during rTMS might provide further essential insights into its mode of action - temporal course of potential modulations. The objective of this study was to first evaluate the validity of online rTMS-EEG and rTMS-EMG analyses, and second to scrutinize the temporal changes of TEPs and MEPs during rTMS. As rTMS is subject to high inter-individual effect variability, we aimed for single-subject analyses of EEG changes during rTMS. Ten healthy human participants were stimulated with 1,000 pulses of 1 Hz rTMS over the motor cortex, while EEG and EMG were recorded continuously. Validity of MEPs and TEPs measured during rTMS was assessed in sensor and source space. Electrophysiological changes during rTMS were evaluated with model fitting approaches on a group- and single-subject level. TEPs and MEPs appearance during rTMS was consistent with past findings of single pulse experiments. Heterogeneous temporal progressions, fluctuations or saturation effects of brain activity were observed during rTMS depending on the TEP component. Overall, global brain activity increased over the course of stimulation. Single-subject analysis revealed inter-individual temporal courses of global brain activity. The present findings are in favor of dose-response considerations and attempts in personalization of rTMS protocols.

Motor oscillations reveal new correlates of error processing in the human brain

It has been demonstrated that during motor responses, the activation of the motor cortical regions emerges in close association with the activation of the medial frontal cortex implicated with performance monitoring and cognitive control. The present study explored the oscillatory neurodynamics of response-related potentials during correct and error responses to test the hypothesis that such continuous communication would modify the characteristics of motor potentials during performance errors. Electroencephalogram (EEG) was recorded at 64 electrodes in a four-choice reaction task and response-related potentials (RRPs) of correct and error responses were analysed. Oscillatory RRP components at extended motor areas were analysed in the theta (3.5-7 Hz) and delta (1-3 Hz) frequency bands with respect to power, temporal synchronization (phase-locking factor, PLF), and spatial synchronization (phase-locking value, PLV). Major results demonstrated that motor oscillations differed between correct and error responses. Error-related changes (1) were frequency-specific, engaging delta and theta frequency bands, (2) emerged already before response production, and (3) had specific regional topographies at posterior sensorimotor and anterior (premotor and medial frontal) areas. Specifically, the connectedness of motor and sensorimotor areas contra-lateral to the response supported by delta networks was substantially reduced during errors. Also, there was an error-related suppression of the phase stability of delta and theta oscillations at these areas. This synchronization reduction was accompanied by increased temporal synchronization of motor theta oscillations at bi-lateral premotor regions and by two distinctive error-related effects at medial frontal regions: (1) a focused fronto-central enhancement of theta power and (2) a separable enhancement of the temporal synchronization of delta oscillations with a localized medial frontal focus. Together, these observations indicate that the electrophysiological signatures of performance errors are not limited to the medial frontal signals, but they also involve the dynamics of oscillatory motor networks at extended cortical regions generating the movement. Also, they provide a more detailed picture of the medial frontal processes activated in relation to error processing.

EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.

Coherent activity within and between hemispheres: cortico-cortical connectivity revealed by rTMS of the right posterior parietal cortex

Introduction

Low frequency (1 Hz) repetitive transcranial stimulation (rTMS) applied over right posterior parietal cortex (rPPC) has been shown to reduce cortical excitability both of the stimulated area and of the interconnected contralateral homologous areas. In the present study, we investigated the whole pattern of intra- and inter-hemispheric cortico-cortical connectivity changes induced by rTMS over rPPC.

Methods

To do so, 14 healthy participants underwent resting state EEG recording before and after 30 min of rTMS at 1 Hz or sham stimulation over the rPPC (electrode position P6). Real stimulation was applied at 90% of motor threshold. Coherence values were computed on the electrodes nearby the stimulated site (i.e., P4, P8, and CP6) considering all possible inter- and intra-hemispheric combinations for the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-50 Hz).

Results and discussion

Results revealed a significant increase in coherence in delta, theta, alpha and beta frequency bands between rPPC and the contralateral homologous sites. Moreover, an increase in coherence in theta, alpha, beta and gamma frequency bands was found between rPPC and right frontal sites, reflecting the activation of the fronto-parietal network within the right hemisphere. Summarizing, subthreshold rTMS over rPPC revealed cortico-cortical inter- and intra-hemispheric connectivity as measured by the increase in coherence among these areas. Moreover, the present results further confirm previous evidence indicating that the increase of coherence values is related to intra- and inter-hemispheric inhibitory effects of rTMS. These results can have implications for devising evidence-based rehabilitation protocols after stroke.

Electrophysiological correlates of temporal numerosity adaptation

Introduction

Much research has revealed the human visual system is capable to estimate numerical quantities, rapidly and reliably, in both the spatial and the temporal domain. This ability is highly susceptible to short-term plastic phenomena related to previous exposure to visual numerical information (i.e., adaptation). However, while determinants of spatial numerosity adaptation have been widely investigated, little is known about the neural underpinnings of short-term plastic phenomena related to the encoding of temporal numerical information. In the present study we investigated the electrophysiological correlates of temporal numerosity adaptation.

Methods

Participants were asked to estimate the numerosity of a test sequence of flashes after being exposed to either a high or low numerous adapting sequence. Behavioral results confirmed the expected underestimation of test stimulus when this was preceded by a high numerous sequence as compared to when preceded by a low numerous sequence.

Results

Electrophysiological data revealed that this behavior was tightly linked to the amplitude of the steady-state visual evoked (ssVEP) response elicited by the test stimulus. When preceded by a high numerous sequence, the test stimulus elicited larger ssVEP responses as compared to when preceded by a low numerous sequence with this pattern being robustly correlated with behavior. Finally, topographical maps showed that this difference was mostly evident across two antero-posterior distributed clusters of electrodes and correlated with changes in functional connectivity.

Discussion

Taken together, our results suggest that visual plastic phenomena related to the encoding of temporal numerosity information reflect changes in rhythmic evoked activity that are likely related to long range communications between distinct brain regions.

Global Functional Connectivity is Associated with Mind Wandering Domain of Comfort

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. To assess the relationship between brain activity and subjective experiences, various questionnaires are used. Previous studies using Amsterdam Resting State Questionnaire were focusing on fMRI functional connectivity or EEG microstates and spectral aspect. Here, we utilized Global Field Synchronization as the parameter to estimate global functional connectivity. By re-analyzing the resting-state data from 226 young healthy participants we showed a strong evidence of relationship between ARSQ domain of Comfort and GFS values in the alpha range (r = 0.210, BF10 = 12.338) and substantial evidence for positive relationship between ARSQ domain of Comfort and GFS in the beta frequency range (r = 196, BF10 = 6.307). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the individual intrinsic electrical brain activity.

EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies

Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by "eyeballing" of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings.

Identifying ADHD and subtypes through microstates analysis and complex networks

The diagnosis of attention-deficit hyperactivity disorder (ADHD) is based on the health history and on the evaluation of questionnaires to identify symptoms. This evaluation can be subjective and lengthy, especially in children. Therefore, a biomarker would be of great value to assist mental health professionals in the process of diagnosing ADHD. Event-related potential (ERP) is one of the most informative and dynamic methods of monitoring cognitive processes. Previous works suggested that specific sets of ERP-microstates are selectively affected by ADHD. This paper proposes a new methodology for the ERP-microstate analysis and identification of ADHD patients based on complex networks to model the microstate topographic maps. The analysis of global and local features of ERP-microstate networks revealed topological differences between ADHD and healthy control. The classification using a neural network with a single hidden layer resulted in an average accuracy of 99.72% in binary classification and 99.31% in the classification of ADHD subtypes. The results were compared to the power band spectral densities and the energy of wavelet coefficients. The temporal features of ERP-microstates, such as frequency of occurrence, duration, coverage, and transition probabilities, were also evaluated for comparison proposes. Overall, the selected topological features of ERP-microstate networks derived from the proposed method performed significantly better classification results. The results suggest that topological features of ERP-microstate networks are promising to identify ADHD and its subtypes with a neural network model compared to power band spectrum density, wavelet transform, and temporal features of ERP-microstates.

The topology of interpersonal neural network in weak social ties

The strategies for social interaction between strangers differ from those between acquaintances, whereas the differences in neural basis of social interaction have not been fully elucidated. In this study, we examined the geometrical properties of interpersonal neural networks in pairs of strangers and acquaintances during antiphase joint tapping. Dual electroencephalogram (EEG) of 29 channels per participant was measured from 14 strangers and 13 acquaintance pairs.Intra-brain synchronizations were calculated using the weighted phase lag index (wPLI) for intra-brain electrode combinations, and inter-brain synchronizations were calculated using the phase locking value (PLV) for inter-brain electrode combinations in the theta, alpha, and beta frequency bands. For each participant pair, electrode combinations with larger wPLI/PLV than their surrogates were defined as the edges of the neural networks. We calculated global efficiency, local efficiency, and modularity derived from graph theory for the combined intra- and inter-brain networks of each pair. In the theta band networks, stranger pairs showed larger local efficiency than acquaintance pairs, indicating that the two brains of stranger pairs were more densely connected. Hence, weak social ties require extensive social interactions and result in high efficiency of information transfer between neighbors in neural network.

A phase-shifting anterior-posterior network organizes global phase relations

Prior research has identified a variety of task-dependent networks that form through inter-regional phase-locking of oscillatory activity that are neural correlates of specific behaviors. Despite ample knowledge of task-specific functional networks, general rules governing global phase relations have not been investigated. To discover such general rules, we focused on phase modularity, measured as the degree to which global phase relations in EEG comprised distinct synchronized clusters interacting with one another at large phase lags. Synchronized clusters were detected with a standard community-detection algorithm, and the degree of phase modularity was quantified by the index q. Notably, we found that the mechanism controlling phase modularity is remarkably simple. A network comprising anterior-posterior long-distance connectivity coherently shifted phase relations from low-angles (|Δθ| < π/4) in low-modularity states (bottom 5% in q) to high-angles (|Δθ| > 3π/4) in high-modularity states (top 5% in q), accounting for fluctuations in phase modularity. This anterior-posterior network may play a fundamental functional role as (1) it controls phase modularity across a broad range of frequencies (3-50 Hz examined) in different behavioral conditions (resting with the eyes closed or watching a silent nature video) and (2) neural interactions (measured as power correlations) in beta-to-gamma bands were consistently elevated in high-modularity states. These results may motivate future investigations into the functional roles of phase modularity as well as the anterior-posterior network that controls it.

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.

Improving the detection of sleep slow oscillations in electroencephalographic data

Study objectives

We aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate the performance of traditional sleep SO detection algorithms on such a manually labeled data set. We sought to develop improved methods for SO detection.

Method

SOs in polysomnographic recordings acquired during nap time from ten older adults were manually labeled using a custom built graphical user interface tool. Three automatic SO detection algorithms previously used in the literature were evaluated on this data set. Additional machine learning and deep learning algorithms were trained on the manually labeled data set.

Results

Our custom built tool significantly decreased the time needed for manual labeling, allowing us to manually inspect 96,277 potential SO events. The three automatic SO detection algorithms showed relatively low accuracy (max. 61.08%), but results were qualitatively similar, with SO density and amplitude increasing with sleep depth. The machine learning and deep learning algorithms showed higher accuracy (best: 99.20%) while maintaining a low prediction time.

Conclusions

Accurate detection of SO events is important for investigating their role in memory consolidation. In this context, our tool and proposed methods can provide significant help in identifying these events.

Event Related Potentials to Native Speech Contrasts Predicts Word Reading Abilities in Early School-Aged Children

Speech perception skills have been implicated in the development of phoneme-grapheme correspondence, yet the exact nature of speech perception and word reading ability remains unknown. We investigate phonological sensitivity to native (English) and nonnative (Spanish) speech syllables within an auditory oddball paradigm using event related potentials (ERPs) collected from lateral temporal electrode sites in 33 monolingual English-speaking children aged 6-8 years (N=33). We further explore the relationship between ERPs to English word reading abilities for this group. Results revealed that language stimuli (English, Spanish), ERP condition (standard, deviant), and hemisphere (left, right) all influenced the lateral N1 component. ERPs recorded from deviant English stimuli were significantly more negative within the left hemisphere compared to all other recorded ERPs. Mean amplitude differences within the N1 in left lateral electrode sites recorded in response to English phoneme contrasts significantly predicted English word reading abilities within this sample. Results indicate that speech perception of native contrasts recorded in left temporal electrode sites for the N1 component are linked to English word reading abilities in early school-aged children.

Agreeableness modulates mental state decoding: Electrophysiological evidence

Agreeableness is one of the five personality traits which is associated with theory of mind (ToM) abilities. One of the critical processes involved in ToM is the decoding of emotional cues. In the present study, we investigated whether this process is modulated by agreeableness using electroencephalography (EEG) while taking into account task complexity and sex differences that are expected to moderate the relationship between emotional decoding and agreeableness. This approach allowed us to identify at which stage of the neural processing agreeableness kicks in, in order to distinguish the impact on early, perceptual processes from slower, inferential processing. Two tasks were employed and submitted to 62 participants during EEG recording: the reading the mind in the eyes (RME) task, requiring the decoding of complex mental states from eye expressions, and the biological (e)motion task, involving the perception of basic emotional actions through point-light body stimuli. Event-related potential (ERP) results showed a significant correlation between agreeableness and the contrast for emotional and non-emotional trials in a late time window only during the RME task. Specifically, higher levels of agreeableness were associated with a deeper neural processing of emotional versus non-emotional trials within the whole and male samples. In contrast, the modulation in females was negligible. The source analysis highlighted that this ERP-agreeableness association engages the ventromedial prefrontal cortex. Our findings expand previous research on personality and social processing and confirm that sex modulates this relationship.

Aging alters functional connectivity of motor theta networks during sensorimotor reactions

OBJECTIVE

Both cognitive and primary motor networks alter with advancing age in humans. The networks activated in response to external environmental stimuli supported by theta oscillations remain less well explored. The present study aimed to characterize the effects of aging on the functional connectivity of response-related theta networks during sensorimotor tasks.

METHODS

Electroencephalographic signals were recorded in young and middle-to-older age adults during three tasks performed in two modalities, auditory and visual: a simple reaction task, a Go-NoGo task, and a choice-reaction task. Response-related theta oscillations were computed. The phase-locking value (PLV) was used to analyze the spatial synchronization of primary motor and motor control theta networks.

RESULTS

Performance was overall preserved in older adults. Independently of the task, aging was associated with reorganized connectivity of the contra-lateral primary motor cortex. In younger adults, it was synchronized with motor control regions (intra-hemispheric premotor/frontal and medial frontal). In older adults, it was only synchronized with intra-hemispheric sensorimotor regions.

CONCLUSIONS

Motor theta networks of older adults manifest a functional decoupling between the response-generating motor cortex and motor control regions, which was not modulated by task variables. The overall preserved performance in older adults suggests that the increased connectivity within the sensorimotor network is associated with an excessive reliance on sensorimotor feedback during movement execution compensating for a deficient cognitive regulation of motor regions during sensorimotor reactions.

SIGNIFICANCE

New evidence is provided for the reorganization of motor networks during sensorimotor reactions already at the transition from middle to old age.

"Neural Noise" in Auditory Responses in Young Autistic and Neurotypical Children

Elevated "neural noise" has been advanced as an explanation of autism and autistic sensory experiences. However, functional neuroimaging measures of neural noise may be vulnerable to contamination by recording noise. This study explored variability of electrophysiological responses to tones of different intensities in 127 autistic and 79 typically-developing children aged 2-5 years old. A rigorous data processing pipeline, including advanced visualizations of different signal sources that were maximally independent across different time lags, was used to identify and eliminate putative recording noise. Inter-trial variability was measured using median absolute deviations (MADs) of EEG amplitudes across trials and inter-trial phase coherence (ITPC). ITPC was elevated in autism in the 50 and 60 dB intensity conditions, suggesting diminished (rather than elevated) neural noise in autism, although reduced ITPC to soft 50 dB sounds was associated with increased loudness discomfort. Autistic and non-autistic participants did not differ in MADs, and indeed, the vast majority of the statistical tests examined in this study yielded no significant effects. These results appear inconsistent with the neural noise account.

Loosely controlled experimental EEG datasets for higher-order cognitions in design and creativity tasks

Understanding neural mechanisms in design and creativity processes remains a challenging endeavor. To address this gap, we present two electroencephalography (EEG) datasets recorded in design and creativity experiments. We have discussed the details, similarities, differences, and corresponding cognitive tasks of the two datasets in the following sections. The design dataset (Dataset A) comprises EEG recordings of 27 participants during loosely controlled design creation experiments. Each experiment included six design problems. In each design problem, participants performed five cognitive tasks, including problem understanding, idea generation, rating idea generation, idea evaluation, and rating idea evaluation. The NASA Task Load Index was used in rating tasks. The creativity dataset (Dataset B) includes EEG signals recorded from 28 participants in creativity experiments which were based on a modified variant of the Torrance Test of Creative Thinking (TTCT-F). Participants were presented with three incomplete sketches and were asked to perform three creativity tasks for each sketch: idea generation, idea evolution, and idea evaluation. In both datasets, we structured the experiments into predefined steps, primarily to ensure participants' comfort and task clarity. This was the only control applied to the experiments. All the tasks were loosely controlled: open-ended (up to 3 min) and self-paced. 64-channel EEG signals were recorded at 500 Hz based on the international 10-10 system by the Brain Vision EEG recording system while the participants were performing their assigned tasks. EEG channels were pre-processed and finally referenced to the Cz channel to remove artifacts. EEGs were pre-processed using popular pipelines widely used in previous studies. Preprocessed EEG signals were finally segmented according to the tasks to facilitate future analyses. The EEG signals are stored in the .mat format. While the present paper mainly addresses pre-processed datasets, it also cites raw EEG recordings in the following sections. We aim to promote research and facilitate the development of experimental protocols and methodologies in design and creativity cognition by sharing these resources. There exist important points regarding the datasets which are worth mentioning. These datasets represent a novel contribution to the field, offering insights into design and creativity neurocognition. To our knowledge, publicly accessible datasets of this nature are scarce, and, to the best of our knowledge, our datasets are the first publicly available ones in design and creativity. Researchers can utilize these datasets directly or draw upon the considerations and technical insights provided to inform their studies. Furthermore, we introduce the concept of loosely controlled cognitive experiments in design and creativity cognition. These experiments strike a balance between flexibility and control, allowing participants to incubate creative ideas over extended response times while maintaining structured experimental sections. Such an approach fosters more natural data recording procedures and holds the potential to enhance the accuracy and reliability of future studies. The loosely controlled approach can be employed in future cognitive studies. This paper also conducts a comparative analysis of the two datasets, offering a holistic view of design and creativity tasks. By exploring various aspects of these cognitive processes, we provide an understanding for future researchers.

AS, Hatlestad-Hall C, Yazidi A, Hammer HL, Hebold Haraldsen IRJ. Introducing Region Based Pooling for handling a varied number of EEG channels for deep learning models

Introduction

A challenge when applying an artificial intelligence (AI) deep learning (DL) approach to novel electroencephalography (EEG) data, is the DL architecture's lack of adaptability to changing numbers of EEG channels. That is, the number of channels cannot vary neither in the training data, nor upon deployment. Such highly specific hardware constraints put major limitations on the clinical usability and scalability of the DL models.

Methods

In this work, we propose a technique for handling such varied numbers of EEG channels by splitting the EEG montages into distinct regions and merge the channels within the same region to a region representation. The solution is termed Region Based Pooling (RBP). The procedure of splitting the montage into regions is performed repeatedly with different region configurations, to minimize potential loss of information. As RBP maps a varied number of EEG channels to a fixed number of region representations, both current and future DL architectures may apply RBP with ease. To demonstrate and evaluate the adequacy of RBP to handle a varied number of EEG channels, sex classification based solely on EEG was used as a test example. The DL models were trained on 129 channels, and tested on 32, 65, and 129-channels versions of the data using the same channel positions scheme. The baselines for comparison were zero-filling the missing channels and applying spherical spline interpolation. The performances were estimated using 5-fold cross validation.

Results

For the 32-channel system version, the mean AUC values across the folds were: RBP (93.34%), spherical spline interpolation (93.36%), and zero-filling (76.82%). Similarly, on the 65-channel system version, the performances were: RBP (93.66%), spherical spline interpolation (93.50%), and zero-filling (85.58%). Finally, the 129-channel system version produced the following results: RBP (94.68%), spherical spline interpolation (93.86%), and zero-filling (91.92%).

Conclusion

In conclusion, RBP obtained similar results to spherical spline interpolation, and superior results to zero-filling. We encourage further research and development of DL models in the cross-dataset setting, including the use of methods such as RBP and spherical spline interpolation to handle a varied number of EEG channels.

Sex Differences in Low-Level Multisensory Integration in Developmental Dyslexia

Reading acquisition involves the integration of auditory and visual stimuli. Thus, low-level audiovisual multisensory integration might contribute to disrupted reading in developmental dyslexia. Although dyslexia is more frequently diagnosed in males and emerging evidence indicates that the neural basis of dyslexia might differ between sexes, previous studies examining multisensory integration did not evaluate potential sex differences nor tested its neural correlates. In the current study on 88 adolescents and young adults, we found that only males with dyslexia showed a deficit in multisensory integration of simple nonlinguistic stimuli. At the neural level, both females and males with dyslexia presented smaller differences in response to multisensory compared to those in response to unisensory conditions in the N1 and N2 components (early components of event-related potentials associated with sensory processing) than the control group. Additionally, in a subsample of 80 participants matched for nonverbal IQ, only males with dyslexia exhibited smaller differences in the left hemisphere in response to multisensory compared to those in response to unisensory conditions in the N1 component. Our study indicates that deficits of multisensory integration seem to be more severe in males than females with dyslexia. This provides important insights into sex-modulated cognitive processes that might confer vulnerability to reading difficulties.

Response to experimental cold-induced pain discloses a resistant category among endurance athletes, with a distinct profile of pain-related behavior and GABAergic EEG markers: a case-control preliminary study

Pain is a major public health problem worldwide, with a high rate of treatment failure. Among promising non-pharmacological therapies, physical exercise is an attractive, cheap, accessible and innocuous method; beyond other health benefits. However, its highly variable therapeutic effect and incompletely understood underlying mechanisms (plausibly involving the GABAergic neurotransmission) require further research. This case-control study aimed to investigate the impact of long-lasting intensive endurance sport practice (≥7 h/week for the last 6 months at the time of the experiment) on the response to experimental cold-induced pain (as a suitable chronic pain model), assuming that highly trained individual would better resist to pain, develop advantageous pain-copying strategies and enhance their GABAergic signaling. For this purpose, clinical pain-related data, response to a cold-pressor test and high-density EEG high (Hβ) and low beta (Lβ) oscillations were documented. Among 27 athletes and 27 age-adjusted non-trained controls (right-handed males), a category of highly pain-resistant participants (mostly athletes, 48.1%) was identified, displaying lower fear of pain, compared to non-resistant non-athletes. Furthermore, they tolerated longer cold-water immersion and perceived lower maximal sensory pain. However, while having similar Hβ and Lβ powers at baseline, they exhibited a reduction between cold and pain perceptions and between pain threshold and tolerance (respectively -60% and - 6.6%; -179.5% and - 5.9%; normalized differences), in contrast to the increase noticed in non-resistant non-athletes (+21% and + 14%; +23.3% and + 13.6% respectively). Our results suggest a beneficial effect of long-lasting physical exercise on resistance to pain and pain-related behaviors, and a modification in brain GABAergic signaling. In light of the current knowledge, we propose that the GABAergic neurotransmission could display multifaceted changes to be differently interpreted, depending on the training profile and on the homeostatic setting (e.g., in pain-free versus chronic pain conditions). Despite limitations related to the sample size and to absence of direct observations under acute physical exercise, this precursory study brings into light the unique profile of resistant individuals (probably favored by training) allowing highly informative observation on physical exercise-induced analgesia and paving the way for future clinical translation. Further characterizing pain-resistant individuals would open avenues for a targeted and physiologically informed pain management.

Brain-behavior analysis of transcranial direct current stimulation effects on a complex surgical motor task

Transcranial Direct Current Stimulation (tDCS) has demonstrated its potential in enhancing surgical training and performance compared to sham tDCS. However, optimizing its efficacy requires the selection of appropriate brain targets informed by neuroimaging and mechanistic understanding. Previous studies have established the feasibility of using portable brain imaging, combining functional near-infrared spectroscopy (fNIRS) with tDCS during Fundamentals of Laparoscopic Surgery (FLS) tasks. This allows concurrent monitoring of cortical activations. Building on these foundations, our study aimed to explore the multi-modal imaging of the brain response using fNIRS and electroencephalogram (EEG) to tDCS targeting the right cerebellar (CER) and left ventrolateral prefrontal cortex (PFC) during a challenging FLS suturing with intracorporeal knot tying task. Involving twelve novices with a medical/premedical background (age: 22-28 years, two males, 10 females with one female with left-hand dominance), our investigation sought mechanistic insights into tDCS effects on brain areas related to error-based learning, a fundamental skill acquisition mechanism. The results revealed that right CER tDCS applied to the posterior lobe elicited a statistically significant (q < 0.05) brain response in bilateral prefrontal areas at the onset of the FLS task, surpassing the response seen with sham tDCS. Additionally, right CER tDCS led to a significant (p < 0.05) improvement in FLS scores compared to sham tDCS. Conversely, the left PFC tDCS did not yield a statistically significant brain response or improvement in FLS performance. In conclusion, right CER tDCS demonstrated the activation of bilateral prefrontal brain areas, providing valuable mechanistic insights into the effects of CER tDCS on FLS peformance. These insights motivate future investigations into the effects of CER tDCS on error-related perception-action coupling through directed functional connectivity studies.

Effect of a single session of sensorimotor rhythm neurofeedback training on the putting performance of professional golfers

Sensorimotor rhythm (SMR) activity has been associated with automaticity and flow in motor execution. Studies have revealed that neurofeedback training (NFT) of the SMR can improve sports performance; however, few studies have adequately explored the effects of a single session of such NFT or examined the possible mechanisms underlying these effects on sports performance. This study recruited 44 professional golfers to address these gaps in the literature. A crossover design was employed to determine the order of the participation in the NFT and no-training control conditions. The participants were asked to perform 60 10-foot putts while electroencephalograms (EEGs) were recorded before and after the tasks. In pre-and post-tests, visual analog scales were used to assess the psychological states associated with SMR activities including the levels of attention engagement, conscious motor control, and physical relaxation. The results revealed that a single NFT session effectively increased SMR power and improved putting performance compared with the control condition. The subjective assessments also revealed that the participants reported lower attention engagement, less conscious control of the motor details and were more relaxed in the putting task, suggesting that SMR NFT promoted effortless and quiescent mental states during motor preparation for a putting task. This study aligns with theoretical hypotheses and extends current knowledge by revealing that a single session of SMR NFT can effectively enhance SMR power and improve putting performance in professional golfers. It also provides preliminary evidence of the possible underlying mechanisms that drive the effect of SMR NFT on putting performances.

Attentional Modulation in Early Visual Cortex: A Focused Reanalysis of Steady-state Visual Evoked Potential Studies

Steady-state visual evoked potentials (SSVEPs) are a powerful tool for investigating selective attention. Here, we conducted a combined reanalysis of multiple studies employing this technique in a variety of attentional experiments to, first, establish benchmark effect sizes of attention on amplitude and phase of SSVEPs and, second, harness the power of a large data set to test more specific hypotheses. Data of eight published SSVEP studies were combined, in which human participants (n = 135 in total) attended to flickering random dot stimuli based on their defining features (e.g., location, color, luminance, or orientation) or feature conjunctions. The reanalysis established that, in all the studies, attention reliably enhanced amplitudes, with color-based attention providing the strongest effect. In addition, the latency of SSVEPs elicited by attended stimuli was reduced by ∼4 msec. Next, we investigated the modulation of SSVEP amplitudes in a subset of studies where two different features were attended concurrently. Although most models assume that attentional effects of multiple features are combined additively, our results suggest that neuronal enhancement provided by concurrent attention is better described by multiplicative integration. Finally, we used the combined data set to demonstrate that the increase in trial-averaged SSVEP amplitudes with attention cannot be explained by increased synchronization of single-trial phases. Contrary to the prediction of the phase-locking account, the variance across trials of complex Fourier coefficients increases with attention, which is more consistent with boosting of a largely phase-locked signal embedded in non-phase-locked noise.

Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity

Studying the development of brain network disruptions in epilepsy is challenged by the paucity of data before epilepsy onset. Here, we used the unilateral, kainate mouse model of hippocampal epilepsy to investigate brain network changes before and after epilepsy onset and their stability across time. Using 32 epicranial electrodes distributed over the mouse hemispheres, we analyzed EEG epochs free from epileptic activity in 15 animals before and 28 days after hippocampal injection (group 1) and in 20 animals on two consecutive days (d28 and d29, group 2). Statistical dependencies between electrodes were characterized with the debiased-weighted phase lag index. We analyzed: a) graph metric changes from baseline to chronic stage (d28) in group 1; b) their reliability across d28 and d29, in group 2; c) their correlation with epileptic activity (EA: seizure, spike and fast-ripple rates), averaged over d28 and d29, in group 2. During the chronic stage, intra-hemispheric connections of the non-injected hemisphere strengthened, yielding an asymmetrical network in low (4-8 Hz) and high theta (8-12 Hz) bands. The contralateral hemisphere also became more integrated and segregated within the high theta band. Both network topology and EEG markers of EA were stable over consecutive days but not correlated with each other. Altogether, we show reproducible large-scale network modifications after the development of focal epilepsy. These modifications are mostly specific to the non-injected hemisphere. The absence of correlation with epileptic activity does not allow to specifically ascribe these network changes to mechanisms supporting EA or rather compensatory inhibition but supports the notion that epilepsy extends beyond the sole repetition of EA and impacts network that might not be involved in EA generation.

Afferents to Action: Cortical Proprioceptive Processing Assessed with Corticokinematic Coherence Specifically Relates to Gross Motor Skills

Voluntary motor control is thought to be predicated on the ability to efficiently integrate and process somatosensory afferent information. However, current approaches in the field of motor control have not factored in objective markers of how the brain tracks incoming somatosensory information. Here, we asked whether motor performance relates to such markers obtained with an analysis of the coupling between peripheral kinematics and cortical oscillations during continuous movements, best known as corticokinematic coherence (CKC). Motor performance was evaluated by measuring both gross and fine motor skills using the Box and Blocks Test (BBT) and the Purdue Pegboard Test (PPT), respectively, and with a biomechanics measure of coordination. A total of 61 participants completed the BBT, while equipped with electroencephalography and electromyography, and the PPT. We evaluated CKC, from the signals collected during the BBT, as the coherence between movement rhythmicity and brain activity, and coordination as the cross-correlation between muscle activity. CKC at movements' first harmonic was positively associated with BBT scores (r = 0.41, p = 0.001), and alone showed no relationship with PPT scores (r = 0.07, p = 0.60), but in synergy with BBT scores, participants with lower PPT scores had higher CKC than expected based on their BBT score. Coordination was not associated with motor performance or CKC (p > 0.05). These findings demonstrate that cortical somatosensory processing in the form of strengthened brain-peripheral coupling is specifically associated with better gross motor skills and thus may be considered as a valuable addition to classical tests of proprioception acuity.

Sexual Orientation Affects Neural Responses to Subtle Social Aggression Signals

The current series of studies are the first to examine brain responses to social aggression signals as a function of male and female sexual orientation. For the first set of studies (1a, 1b), axillary sweat had been collected from 17 heterosexual men and 17 heterosexual women aggressively responding to frustrating opponents (aggression condition) and while playing a construction game (control condition). Sweat samples were pooled according to sex and condition, and presented via a constant flow olfactometer to 17 gay and 23 heterosexual men (Study 1a), and 19 lesbian and 25 heterosexual women (Study 1b). Ongoing EEG was recorded from 61 scalp locations, chemosensory event-related potentials (CSERPs; P2, P3-1, P3-2) were analyzed, and neuronal sources calculated (low resolution electromagnetic tomography). Within the second set of studies (2a, 2b), pictures of males' and females' weak angry and neutral facial expressions were presented to 21 gay and 23 heterosexual men (Study 2a), and 19 lesbian and 26 heterosexual women (Study 2b), and ERPs (N170, P3) were analyzed. Gay men showed larger P3-1 amplitudes than heterosexual men upon presentation of male aggression sweat, accompanied by activation of the right inferior frontal gyrus (IFG, BA 10). Gay men also displayed longer N170 latencies in response to men's compared to women's angry facial expressions, while heterosexual men did not. In women, sexual orientation did not affect the processing of aggression sweat or anger expressions. Gay men showed preferential processing of chemosensory aggression signals (P3-1 amplitudes), indicating fine-tuned socioemotional sensitivity, related to activation of brain areas involved in emotion regulation (IFG). They further process the relative relevance of visual aggression signals (N170 latency). These results were in line with theories proposing a common evolutionary pathway for same-sex attraction and traits easing social integration.

Cortical effects of wrist tendon vibration during an arm tracking task in chronic stroke survivors: An EEG study

The purpose of this study was to characterize changes in cortical activity and connectivity in stroke survivors when vibration is applied to the wrist flexor tendons during a visuomotor tracking task. Data were collected from 10 chronic stroke participants and 10 neurologically-intact controls while tracking a target through a figure-8 pattern in the horizontal plane. Electroencephalography (EEG) was used to measure cortical activity (beta band desynchronization) and connectivity (beta band task-based coherence) with movement kinematics and performance error also being recorded during the task. All participants came into our lab on two separate days and performed three blocks (16 trials each, 48 total trials) of tracking, with the middle block including vibration or sham applied at the wrist flexor tendons. The order of the sessions (Vibe vs. Sham) was counterbalanced across participants to prevent ordering effects. During the Sham session, cortical activity increased as the tracking task progressed (over blocks). This effect was reduced when vibration was applied to controls. In contrast, vibration increased cortical activity during the vibration period in participants with stroke. Cortical connectivity increased during vibration, with larger effect sizes in participants with stroke. Changes in tracking performance, standard deviation of hand speed, were observed in both control and stroke groups. Overall, EEG measures of brain activity and connectivity provided insight into effects of vibration on brain control of a visuomotor task. The increases in cortical activity and connectivity with vibration improved patterns of activity in people with stroke. These findings suggest that reactivation of normal cortical networks via tendon vibration may be useful during physical rehabilitation of stroke patients.

Acute hypoxia alters visuospatial attention orienting: an electrical neuroimaging study

Our study investigated the effects of hypoxia on visuospatial attention processing during preparation for a single/double-choice motor response. ERPs were recorded in two sessions in which participants breathed either ambient-air or oxygen-impoverished air. During each session, participants performed four cue-target attention orienting and/or alerting tasks. Replicating the classic findings of valid visuospatial attentional orienting modulation, ERPs to pre-target cues elicited both an Anterior directing attention negativity (ADAN)/CNV and a posterior Late directing attention positivity (LDAP)/TP, which in ambient air were larger for attention orienting than for alerting. Hypoxia increased the amplitude of both these potentials in the spatial orienting conditions for the upper visual hemifield, while, for the lower hemifield, it increased ADAN/CNV, but decreased LDAP/TP for the same attention conditions. To these ERP changes corresponded compensatory enhanced activation of right anterior cingulate cortex, left superior parietal lobule and frontal gyrus, as well as detrimental effects of hypoxia on behavioral overt performance. Together, these findings reveal for the first time, to our knowledge, that (1) these reversed alterations of the activation patterns during the time between cue and target occur at a larger extent in hypoxia than in air, and (2) acute normobaric hypoxia alters visuospatial attention orienting shifting in space.

Altered spread of waves of activities at large scale is influenced by cortical thickness organization in temporal lobe epilepsy: a magnetic resonance imaging-high-density electroencephalography study

Temporal lobe epilepsy is a brain network disorder characterized by alterations at both the structural and the functional levels. It remains unclear how structure and function are related and whether this has any clinical relevance. In the present work, we adopted a novel methodological approach investigating how network structural features influence the large-scale dynamics. The functional network was defined by the spatio-temporal spreading of aperiodic bursts of activations (neuronal avalanches), as observed utilizing high-density electroencephalography in patients with temporal lobe epilepsy. The structural network was modelled as the region-based thickness covariance. Loosely speaking, we quantified the similarity of the cortical thickness of any two brain regions, both across groups and at the individual level, the latter utilizing a novel approach to define the subject-wise structural covariance network. In order to compare the structural and functional networks (at the nodal level), we studied the correlation between the probability that a wave of activity would propagate from a source to a target region and the similarity of the source region thickness as compared with other target brain regions. Building on the recent evidence that large-waves of activities pathologically spread through the epileptogenic network in temporal lobe epilepsy, also during resting state, we hypothesize that the structural cortical organization might influence such altered spatio-temporal dynamics. We observed a stable cluster of structure-function correlation in the bilateral limbic areas across subjects, highlighting group-specific features for left, right and bilateral temporal epilepsy. The involvement of contralateral areas was observed in unilateral temporal lobe epilepsy. We showed that in temporal lobe epilepsy, alterations of structural and functional networks pair in the regions where seizures propagate and are linked to disease severity. In this study, we leveraged on a well-defined model of neurological disease and pushed forward personalization approaches potentially useful in clinical practice. Finally, the methods developed here could be exploited to investigate the relationship between structure-function networks at subject level in other neurological conditions.

An Accumulating Neural Signal Underlying Binocular Rivalry Dynamics

During binocular rivalry, conflicting images are presented one to each eye and perception alternates stochastically between them. Despite stable percepts between alternations, modeling suggests that neural signals representing the two images change gradually, and that the duration of stable percepts are determined by the time required for these signals to reach a threshold that triggers an alternation. However, direct physiological evidence for such signals has been lacking. Here, we identify a neural signal in the human visual cortex that shows these predicted properties. We measured steady-state visual evoked potentials (SSVEPs) in 84 human participants (62 females, 22 males) who were presented with orthogonal gratings, one to each eye, flickering at different frequencies. Participants indicated their percept while EEG data were collected. The time courses of the SSVEP amplitudes at the two frequencies were then compared across different percept durations, within participants. For all durations, the amplitude of signals corresponding to the suppressed stimulus increased and the amplitude corresponding to the dominant stimulus decreased throughout the percept. Critically, longer percepts were characterized by more gradual increases in the suppressed signal and more gradual decreases of the dominant signal. Changes in signals were similar and rapid at the end of all percepts, presumably reflecting perceptual transitions. These features of the SSVEP time courses are well predicted by a model in which perceptual transitions are produced by the accumulation of noisy signals. Identification of this signal underlying binocular rivalry should allow strong tests of neural models of rivalry, bistable perception, and neural suppression.SIGNIFICANCE STATEMENT During binocular rivalry, two conflicting images are presented to the two eyes and perception alternates between them, with switches occurring at seemingly random times. Rivalry is an important and longstanding model system in neuroscience, used for understanding neural suppression, intrinsic neural dynamics, and even the neural correlates of consciousness. All models of rivalry propose that it depends on gradually changing neural activity that on reaching some threshold triggers the perceptual switches. This manuscript reports the first physiological measurement of neural signals with that set of properties in human participants. The signals, measured with EEG in human observers, closely match the predictions of recent models of rivalry, and should pave the way for much future work.

Distinguishing Laparoscopic Surgery Experts from Novices Using EEG Topographic Features

The study aimed to differentiate experts from novices in laparoscopic surgery tasks using electroencephalogram (EEG) topographic features. A microstate-based common spatial pattern (CSP) analysis with linear discriminant analysis (LDA) was compared to a topography-preserving convolutional neural network (CNN) approach. Expert surgeons (N = 10) and novice medical residents (N = 13) performed laparoscopic suturing tasks, and EEG data from 8 experts and 13 novices were analysed. Microstate-based CSP with LDA revealed distinct spatial patterns in the frontal and parietal cortices for experts, while novices showed frontal cortex involvement. The 3D CNN model (ESNet) demonstrated a superior classification performance (accuracy > 98%, sensitivity 99.30%, specificity 99.70%, F1 score 98.51%, MCC 97.56%) compared to the microstate based CSP analysis with LDA (accuracy ~90%). Combining spatial and temporal information in the 3D CNN model enhanced classifier accuracy and highlighted the importance of the parietal-temporal-occipital association region in differentiating experts and novices.

Ten-month-old infants' neural tracking of naturalistic speech is not facilitated by the speaker's eye gaze

Eye gaze is a powerful ostensive cue in infant-caregiver interactions, with demonstrable effects on language acquisition. While the link between gaze following and later vocabulary is well-established, the effects of eye gaze on other aspects of language, such as speech processing, are less clear. In this EEG study, we examined the effects of the speaker's eye gaze on ten-month-old infants' neural tracking of naturalistic audiovisual speech, a marker for successful speech processing. Infants watched videos of a speaker telling stories, addressing the infant with direct or averted eye gaze. We assessed infants' speech-brain coherence at stress (1-1.75 Hz) and syllable (2.5-3.5 Hz) rates, tested for differences in attention by comparing looking times and EEG theta power in the two conditions, and investigated whether neural tracking predicts later vocabulary. Our results showed that infants' brains tracked the speech rhythm both at the stress and syllable rates, and that infants' neural tracking at the syllable rate predicted later vocabulary. However, speech-brain coherence did not significantly differ between direct and averted gaze conditions and infants did not show greater attention to direct gaze. Overall, our results suggest significant neural tracking at ten months, related to vocabulary development, but not modulated by speaker's gaze.