European Journal of Neuroscience

Previous studies show that there are differences in native and foreign speech processing (Lev-Ari, 2018) while mixed evidence has been found regarding differences between dialectal and foreign accent processing (see: Adank et al., 2009; Floccia et al. 2006 but see also: Floccia et al., 2009; Girard et al., 2008). Within this field, two theories have been proposed. The Perceptual Distance Hypothesis states that the mechanisms underlying dialectal accent processing are attenuated versions of those of foreign (Clarke & Garrett, 2004). While, the Different Processes Hypothesis argues that the mechanisms of foreign and dialectal accent processing are qualitatively different (Floccia et al, 2009). A recent study looking at single-word EEG data, suggested that there may be flexibility in processing mechanisms (Thomas et al., 2022). The present study deepens this investigation by addressing in which frequency bands native, dialectal and foreign accent processing differ when listening to extended speech. Electroencephalographic data was recorded from 30 participants who listened to dialogues of approximately six minutes spoken in native, dialectal and foreign accents. Power spectral density estimation (1-35 hz) was performed. Linear mixed models were done in frequency windows of particular relevance to discourse processing. Frequency bands associated with phoneme [gamma], syllable [theta], and prosody [delta] were considered along with those of general cognitive mechanisms [alpha and beta]. Results show power differences in the Gamma frequency range. While in higher frequency ranges foreign accent processing is differentiated from power amplitudes of native and dialectal accent processing, in low frequencies we do not see any accent-related power amplitude modulations. This suggests that there may be a difference in phoneme processing for native accent types and foreign accent, while we speculate that top-down mechanisms during discourse processing may mitigate the effects observed with short units of speech.

The stop-signal task is often used to study inhibitory control. When combined with electrophysiological recordings, the N2 and P3 event-related potentials (ERPs) are regularly observed. Numerous studies link both amplitude and latency differences of the N2 and P3 to failed versus successful stopping. A slower N2-P3 complex when stopping fails has repeatedly been reported across many studies and found to correlate moderately with behavioral stopping speed. However, most studies rely on averaging across trials, thereby limiting the examination of trial-by-trial dynamics. In the present study, we employed different machine learning-approaches to classify successful from failed stop trials based on time-frequency single-trial EEG data. We also tested whether attenuating the slowing effect would alter classification performance. To preserve interpretability, we first identified five group-level EEG components time-locked to stopping and then used the time-frequency representation as features in different models. Our findings suggest that regularized logistic regression can reliably classify successful from failed stopping with an AUC = 0.72. Correcting for ERP latency differences did not markedly reduce overall classification (i.e., AUC = 0.71), but the model had to compensate by leveraging subtler, broadly distributed time-frequency features. Our feature importance measure indicated that a component closely resembling the N2-P3 complex contributed largely to the classification performance, producing a sparse model. Once the slowing effect was attenuated in the data, the model still retained predictive performance but had to rely on 15 times as many time-frequency features across the five components. Thus, it is likely that multiple overlapping processes unfold during stopping that influence response inhibition in addition to the N2-P3 complex. While the N2-P3 complex is consistently evoked during stopping and carry large discriminative ability, considering additional auxiliary processes might further our understanding into mechanisms underlying response inhibition.

Tourette disorder (TD) is characterized by tics, which are sudden repetitive involuntary movements or vocalizations. Deficits in inhibitory control in TD patients remain inconclusive from the traditional method of estimating the ability to stop an impending action, which requires careful interpretation of a parameter derived from race model. One possible explanation for these inconsistencies is that race models assumptions are often violated. Here, we used a pair of metrics derived from a recent alternative model to address why stopping performance in TD patients is unaffected by impairments in neural circuitry. These new metrics distinguish between proactive and reactive inhibitory control and estimate them separately. When these metrics were contrasted with healthy controls (HC), we identified robust deficits in reactive control in TD patients, but not in proactive control. The patient population exhibited difficulty in slowing down the speed of movement planning, which they compensated by their intact ability of procrastination. TEASERTourette disorder patients inhibit action by means of strategic postponement to compensate impaired slowness in preparation.

A core challenge of cognitive neuroscience is to understand how cognition changes over time within the same individual. For example, the tendency for behavioural responses in a range of cognitive domains to oscillate over time has been studied extensively. Recently, however, the phenomenon of behavioural oscillations has been called into question by indications that past findings might reflect aperiodic temporal structure rather than true oscillations. Brookshire (2022) proposed methods to control for aperiodic temporal structure while examining oscillations in behavioural time-courses and found no evidence of behavioural oscillations in reanalyses of four published datasets. However, Brookshires (2022) method has been criticised for having low sensitivity to detect effects of realistic magnitude, so it is currently unclear whether these findings suggest that behavioural oscillations are not present in these and perhaps many other datasets, or whether they are false negatives. Here, we present a modification of Brookshires (2022) AR-surrogate method with increased sensitivity to detect effects of realistic magnitude, adequate control of false positives, and other desirable properties such as the ability to increase statistical power by adding more participants. Using this method, we reanalyse the same publicly available datasets and show significant behavioural oscillations in each of them, suggesting oscillations in behaviour are a robust phenomenon upon which to draw theoretical inferences. The participant-level AR-surrogate method is currently the most sensitive method available for analysing behavioural oscillations while controlling for the contribution of aperiodic data fluctuations.

Interruptions (secondary tasks) have been frequently investigated in behavioral studies leading to a deterioration of working memory performance. Yet, the underlying attentional control processes are not sufficiently understood. A lateralized working memory task was frequently interrupted by either a high- or low-demanding arithmetic task and a subsequent retroactive cue indicated the working memory item required for later report. We examined the role of frontal theta (4-7 Hz) and posterior alpha power (8-14 Hz) as correlates for retroactive attentional switches between working memory representations. In particular, highly demanding interruptions decreased primary task performance compared to a control condition without interruption. This was also reflected in decreased frontal theta power and higher posterior alpha power after retro-cue presentation, suggesting decreased attentional control resources. Moreover, reduced alpha lateralization indicated an impaired refocusing on primary task information following the interruption. These results highlight oscillatory mechanisms required for successfully handling the detrimental effects of interruptions.

The subjective experience of an attraction in time of an action, and the event caused by the action, is known as the intentional binding phenomenon. Intentional binding is a robust phenomenon and has previously been associated with subjective sense of agency, but recent studies have shown that binding can take place in the absence of action intentions. In this study, we tested possible electrophysiological equivalents to the intentional binding phenomenon under a simple action-effect task, where pressing of a button caused tones to occur at different pitches or delays with different probabilities. Changing the probabilities of the effect of an action has in some previous studies shown to influence the intentional binding phenomenon. We tested whether changes in action-effect probability gave rise to differences in movement related cortical potentials (MRCP) slopes, peak latency and auditory event related potential (aERP) changes of amplitude or latency of the N1, P2, P3 and N4 components of the central aERP, of which some has been related to sense of agency or intentional binding. We also tested differences in MRCP across the whole scalp prior to movements, and to differences in aERP across the whole scalp after the tone is played. We found no electrophysiological indications of intentional binding when action-effect contingencies were changed in accordance with conditions that have given rise to intentional binding in previous experiments. Our results are in line with several recent studies that have questioned whether intentional binding follows all voluntary actions and can be related to sense of agency at all.

Paediatric autoimmune encephalitis (e.g., acute disseminated encephalomyelitis, N-methyl-D-aspartate receptor antibody encephalitis) is an inflammatory brain disease that causes cognitive deficits, psychiatric symptoms, seizures, MRI, and EEG abnormalities. Patients can continue to experience residual cognitive difficulties months to years after the acute illness. Magnetoencephalography (MEG) can examine neural changes in the absence of frank structural abnormalities and may help identify factors predicting children at risk of long-term cognitive deficits. We predicted that theta and delta brain functional connectivity networks would be associated with processing speed and working memory in children with autoimmune encephalitis. Participants were children diagnosed with autoimmune encephalitis at least 18 months before testing and typically developing children. All completed MEG recording (Elekta Neuromag Triux) at rest, eyes open with a fixation cross during six minutes; T1 MRI scans; and cognitive evaluation using the primary subtests of the Weschler Intelligence Scale for Children, fifth edition. Brain connectivity, specifically in delta and theta brain activity, was estimated with amplitude envelope correlation, and network efficiency was measured using graph measures (global efficiency, local efficiency, modularity). The measures were compared across the two groups with permutation correction for multiple thresholds. Finally, statistical associations with processing speed and working memory scores were tested in the autoimmune encephalitis group. Age and sex-matched cohorts of 12 children with AE (11.2{+/-}3.5y, IQR 9y; 5M:7F) and 12 typically developing controls (10.6{+/-}3.2y, IQR 7y; 8M:4F) participated in this study. On average, children with autoimmune encephalitis did not differ from controls in working memory (t(21)= 1.449; p = .162; d = 0.605) but had a significantly lower processing speed (t(21) = 2.463; p = .023; Cohens d = 1.028). The groups did not differ in theta network topology measures but the autoimmune encephalitis group had a significantly lower delta local efficiency across all thresholds tested (d = -1.60 at network threshold 14%). Theta modularity was associated with lower working memory ({beta} = -.781; t(8) = -2.588, p = .032) but this effect did not survive correction for multiple comparisons (p(corr) = .224). No other graph measure was significantly associated with psychometric scores in the autoimmune encephalitis group. MEG was able to capture network alterations in paediatric autoimmune encephalitis patients, specifically in the topological organisation of delta brain activity. This preliminary study demonstrates that MEG is an appropriate tool for assessing children with autoimmune encephalitis; future studies should focus on confirming which functional networks can predict cognitive performance.

Mind wandering during ongoing tasks can impede task performance and increase the risk of failure in laboratory as well as in daily-life tasks and work environments. Neurocognitive measures like the electroencephalography (EEG) offer the opportunity to assess mind wandering non-invasively without interfering with the primary task. However, the literature on electrophysiological correlates of mind wandering is rather inconsistent. The present study aims towards clarifying this picture by breaking down the temporal dynamics of mind-wandering encounters using a cluster-based permutation approach. Participants performed a switching task during which mind wandering was occasionally assessed via thought probes applied after trial completion at random time points. In line with previous studies, response accuracy was reduced during mind wandering. Moreover, alpha power during the inter-trial interval was significantly increased on those trials on which participants reported that they had been mind-wandering. This spatially widely distributed effect is theoretically well in line with recent findings linking an increased alpha power to an internally oriented state of attention. Measurements of alpha power may therefore be used to detect mind wandering online during critical tasks in traffic and industry in order to prevent failures.

Motor coordination to an isochronous beat improves when it is subdivided into equal intervals. Here, we study if this subdivision benefit (i) varies with the kind of subdivision, (ii) is enhanced in individuals with formal musical training, and (iii), is an inherent property of neural oscillations. We recorded electroencephalograms of musicians and non-musicians during: (a) listening to an isochronous beat, (b) listening to one of 4 different subdivisions, (c) listening to the beat again, and (d) listening and tapping the beat with the same subdivisions as in (b). We found that tapping consistency and neural entrainment in condition (d) was enhanced in non-musicians for duplets (1:2) compared to the other types of subdivisions. Musicians showed overall better tapping performance and were equally good at tapping together with duplets, triplets (1:3) and quadruplets (1:4), but not with quintuplets (1:5). This group difference was reflected in enhanced neural responses in the triplet and quadruplet conditions. Importantly, for all participants, the neural entrainment to the beat and its first harmonic (i.e. the duplet frequency) increased after listening to each of the subdivisions (c compared to a). Since these subdivisions are harmonics of the beat frequency, the observed preference of the brain to enhance the simplest subdivision level (duplets) may be an inherent property of neural oscillations. In sum, a tapping advantage for simple binary subdivisions is reflected in neural oscillations to harmonics of the beat, and formal training in music can enhance it. Highlights- The neural entrainment to periodic sounds only differs between musicians and non-musicians when they perform a predictive sensorimotor synchronization task. - After listening to a subdivided beat, the frequencies related to the beat and its first harmonic are enhanced in the EEG, likely stabilizing the perception of the beat. - There is a natural advantage for binary structures in sensorimotor synchronization, observed in the tapping of duplets by non-musicians, which can be extended to other subdivisions after extensive musical training.

The relationship between symbolic thinking and language abilities is a topic of intense debate. We have recently discovered three distinct phenotypes of language comprehension, which we defined as command, modifier and syntactic phenotypes (Vyshedskiy et al., 2024). Individuals in the command phenotype were limited to comprehension of simple commands, while those in the modifier phenotype showed additional comprehension of color, size, and number modifiers. Finally, individuals in the most-advanced syntactic phenotype added comprehension of spatial prepositions, verb tenses, flexible syntax, possessive pronouns, complex explanations, and fairytales. In this report we analyzed how these three language phenotypes differed in their symbolic thinking as exhibited through their drawing abilities. In a cohort of 39,654 autistic individuals 4- to 21-years-of-age, parents reported that drawing, coloring and art was manifested by 36.0% of participants. Among these individuals, representational drawing was manifested by 54.1% of individuals with syntactic-, 27.7% of those with modifier-, and 10.1% of those with command-phenotype (all pairwise differences between the phenotypes were statistically significant, p < 0.0001). The ability to draw a novel image per parents description (e.g. a three-headed horse) was reported by 34.6% of individuals with syntactic-, 7.9% of those with modifier-, and 1.9% of individuals with command-phenotype (all pairwise differences between the phenotypes were statistically significant, p < 0.0001). These results show strong association between the representational drawing ability and the syntactic-language-comprehension-phenotype, suggesting a potential benefit of drawing interventions in language therapy.

Smoking is a severe addictive health risk behavior and notorious for the high likelihood of relapse after attempted cessation. Such an addictive pattern in smoking has been associated with neurobiological changes in the brain. However, little is known whether the neural changes associated with chronic smoking persist after a long period of successful abstinence. To address this question, we examined resting state EEG (rsEEG) in heavy smokers who have been smoking for 20 years or more, past-smokers who have been successfully abstaining for 20 years or more, and non-smokers. Compared with chronic current- or past-smokers, non-smokers showed higher relative power in theta frequency band, showcasing long-lasting effects of smoking on the brain. A few rsEEG features in alpha frequency band also revealed reversible impacts of smoking, such that only current-smokers, but not past-smokers, showed distinctively higher patterns than non-smokers in their relative power, EEG reactivity--power changes between eyes-closed and eyes-open conditions--, and coherence between channels. Furthermore, rsEEG feature differences between current- and past-smokers were accounted for by individuals self-reported smoking history and nicotine dependence. These data suggest long-lasting impacts of chronic smoking on the brain that are dissociable from the neural changes reversible with long-term abstinence.

Excitatory glutamatergic synapses in the brain are remarkably plastic. Two forms of plasticity have received the most attention: long-term potentiation (LTP) and synaptic homeostasis. While LTP requires the activation of NMDA receptors, synaptic homeostasis does not. However, both phenomena are mediated by the recruitment of postsynaptic AMPA receptors to the synapses. Recently a new form of plasticity has been described referred to as presynaptic homeostatic plasticity (PHP) (Chipman et al., 2022; Chipman et al., 2025). Pharmacological inhibition of AMPA synaptic responses in CA1 hippocampal pyramidal cells initiates a rapid homeostatic response that results in the recovery of the AMPA responses to normal values in the continued presence of the inhibitor. Accompanying this recovery is a doubling of the NMDA response which is interpreted as an increase in the release of glutamate. This is provocative since it is the first report claiming that a reduction in AMPA responses triggers an enhancement in NMDA responses. Using three different protocols to monitor synaptic responses we fail to observe any recovery of synaptic responses in the presence of an AMPA inhibitor. Furthermore, there was no enhancement in NMDA responses. Thus, we find no evidence for the presence of PHP at CA1 hippocampal synapses.

Accumulating evidence indicates transient beta bursts play an important role in the representation of temporal information and prediction. However, the role of beta bursts in sensorimotor synchronization (SMS) involving active interactions between motor and sensory systems to synchronize predictive movements to periodic events remains unclear. To answer this question, 15 participants were invited to complete a finger-tapping task whilst high-density EEG (128 channels) was recorded. Participants tapped with their right index finger in synchrony with 1 Hz and 0.5 Hz tone trains. In line with previous findings, we found a negative mean asynchrony between tone and tap time, i.e., taps preceded tones for both tone frequencies (1 and 0.5 Hz). In the EEG data, beta bursts were detected and their timing in relationship with tapping and auditory tracking was examined. Results revealed that beta bursts tracked tapping and were modulated by the low frequency phase of the tone frequency (i.e., 1 Hz or 0.5 Hz). Importantly, the locking of beta bursts to the phase of auditory tracking correlated with the behavioural variance on a single trial level that occurred while tapping to the tones. These results demonstrate a critical role for an interplay between beta bursts and low frequency phase in coordinating rhythmic behaviour.

Reaction time (RT) is important in evaluating delayed latency in behavior. Unlike that of humans, the RT of animals, in which the stimulus-response relationship is not one-to-one due to repeated responses per trial, may exhibit two peaks of the fastest and densest responses in a distribution of responses. We determined whether the two peak latencies are aligned for a single RT by controlling stimulus duration. In delay conditioning with mice using sound cues of 10, 5, and 2s, the 2s group exhibited the strongest positive correlations between the two peaks, as well as responses number and accuracy rate, suggesting coupling of the fastest and densest responses, and a one-to-one relationship between stimulus and response, respectively. We propose the use of harmonization of the two peaks, elicited by stimuli that induce minimal responses, as a criterion for designing animal experiments to mimic humanlike RT.

Mindfulness-based cognitive training exhibits great propensity for improving cognitive performance across a range of contexts. However, the neurophysiological basis of these cognitive enhancements has remained relatively unclear. Previous studies have widely examined EEG during mindfulness practice - or made comparisons with long-term meditators and controls - but have failed to capture how EEG dynamics in subsequent cognitive testing scenarios might be altered as a function of mindfulness-based interventions. The current study therefore aimed to assess a variety of EEG dynamics (oscillatory, aperiodic, and event-related) during engagement in a dynamic and complex cognitive task, following a mindfulness-based cognitive training regime. Participants (n = 40, age range = 18 - 38) attended the lab on two separate occasions (pre- and post-a web-based one-week mindfulness intervention), where EEG was recorded during engagement in the Target Motion Analyst (TMA) task. Previous analysis of the same participants demonstrated that greater adherence to the mindfulness-based cognitive training was associated with improved performance on the TMA task (Dziego, Bornkessel-Schlesewsky, Schlesewsky et al., 2024). Here, we capitalise on these previous findings to assess whether adherence is paralleled by measurable differences in on-task EEG dynamics. Linear mixed-effects modelling demonstrated that, while main effects were observed across session, adherence to cognitive training was not directly associated with alpha power, theta power or 1/f parameters. Challenges also arose when computing event-related potentials (ERPs), illustrating the difficulties of using this technique in more complex testing environments. While these results are challenging to place within the context of previous EEG studies on meditation and cognitive performance, our findings highlight the complexities in understanding the cognitive benefits of mindfulness-based training interventions through EEG dynamics observed during subsequent cognitive testing.

A recent article (Delorme, A., 2023, EEG is better left alone. Scientific Reports, 13, 2372. https://doi.org/10.1038/s41598-023-27528-0) proposed a metric to determine the benefit of applying pre-processing methods to EEG data. Using that metric, it concluded that most pre-processing methods do not improve data quality. The question is revisited in this short paper, using a sample of the same data as used by that paper. It is argued that the metric is of limited applicability, and that in some situations pre-processing might be critical to make good use of the data. Note: This paper was submitted to Scientific Reports as a commentary to the paper cited and rejected without review.

People who report experiencing alcohol-related blackouts (ARBs) are at increased risk of alcohol-related injury and even death. Blackout susceptibility is heritable and blackouts are not experienced by all who engage in hazardous drinking. Blackout is defined by anterograde amnesia, but a person in the blackout state also maintains consciousness and motor control at high levels of intoxication, which is behaviorally similar to episodes seen in individuals with a history of sleepwalking or related parasomnias. Spectral analysis of resting-state electroencephalograms (EEG) can provide insight into individual differences in baseline neurophysiology which may predict blackout susceptibility in otherwise healthy individuals. The current study investigated potential neurophysiological phenotypes present in the resting-state EEG spectra of individuals with a history of blackout, sleepwalking, or related parasomnias. In Experiment 1, adult females with a history of alcohol-related blackout had reduced resting-state alpha peak power over the primary motor cortex compared to those with no such history, while aperiodic slope over the right primary motor cortex was negatively correlated with lifetime blackout score in males. In Experiment 2, increased frequency of parasomnia episodes was associated with reduced resting-state alpha peak power across males and females. Together, these findings provide the first support for the existence of common neurophysiological phenotypes between specific parasomnias and alcohol-related blackout. New & NoteworthyResearch on blackout often focuses on hippocampal suppression by alcohol because anterograde amnesia is a salient and definitional aspect of alcohol-related blackout. We focused here instead on the resilience of motor function to suppression by alcohol during the blackout state. We identified a sex-specific EEG marker associated with blackout history, and then found that the same marker was related to the frequency of episodes of certain non-REM parasomnias in both sexes. These findings suggest that these pathological states may share underlying dysfunction of motor inhibition, allowing for coordinated motor activity to persist during intoxication or sleep.

Bae & Luck (2018) reported a study of visual working memory in which the orientation being held in memory was decoded from the scalp distribution of sustained ERP activity and alpha-band EEG oscillations. Decoding accuracy was compared to chance at each point during the delay interval, and a correction for multiple comparisons was applied to find clusters of consecutive above-chance time points that were stronger than would be expected by chance. However, the correction used in that study did not account for the autocorrelation of the noise and may have been overly liberal. Here, we describe a more appropriate correction procedure and apply it to the data from Bae & Luck (2018). We find that the major clusters of time points that were significantly above chance with the original correction procedure remained above chance with the updated correction procedure. However, some minor clusters that were significant with the original procedure were no longer significant with the updated procedure. We recommend that future studies use the updated correction procedure.

Response inhibition is among the core constructs of cognitive control. It is notoriously difficult to quantify from overt behavior, since the outcome of successful inhibition is the lack of a behavioral response. Currently, the most common measure of action stopping, and by proxy response inhibition, is the model-based stop signal reaction time (SSRT) derived from the stop signal task. Recently, partial response electromyography (prEMG) has been introduced as a complementary physiological measure to capture individual stopping latencies. PrEMG refers to muscle activity initiated by the go signal that plummets after the stop signal before its accumulation to a full response. Whereas neither the SSRT nor the prEMG is an unambiguous marker for neural processes underlying response inhibition, our analysis indicates that the prEMG peak latency is better suited to investigate brain mechanisms of action stopping. This study is a methodological resource with a comprehensive overview of the psychometric properties of the prEMG in a stop signal task, and further provides practical tips for data collection and analysis.

Sustained attention allows concentration on a task over long periods of time. This ability fluctuates, with periods of effective focus ( in-the-zone) and periods of increased performance variability and susceptibility to errors ( out-of-the-zone). Little is known about the neural dynamics underlying these states and their fluctuations during sustained attention tasks. To address this, we had thirty young adults perform the gradual onset continuous performance task (gradCPT), during which their EEG and responses were recorded. States of sustained attention (out-vs. in-the-zone) were identified based on the variance time course of participants RT. Out-of-the-zone states were associated with increased errors of commission and reduced perceptual sensitivity compared to in-the-zone states, as expected. Importantly, a significant decline in theta oscillations at mid-prefrontal regions was found during out-of-the-zone (vs. in-the-zone) states over a [~]400 ms period around the transition point between stimuli, and the extent of this decline predicted commission errors and response bias. In addition, individual differences in the variability of midfrontal theta along the task were associated with RT variability. Finally, participants exhibiting greater theta variability showed a more pronounced decline in perceptual sensitivity when being out-of-the-zone and less stable RTs compared to those with lower variability. Our results suggest that states of diminished sustained attention, even during short lapses, are characterized by a reduction in midfrontal theta activity, and that fluctuations in this rhythm covary with fluctuations in attentional control.