Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review

Action Planning Renders Objects in Working Memory More Attentionally Salient

A rapidly growing body of work suggests that visual working memory (VWM) is fundamentally action oriented. Consistent with this, we recently showed that attention is more strongly biased by VWM representations of objects when we plan to act on those objects in the future. Using EEG and eye tracking, here, we investigated neurophysiological correlates of the interactions between VWM and action. Participants (n = 36) memorized a shape for a subsequent VWM test. At test, a probe was presented along with a secondary object. In the action condition, participants gripped the actual probe if it matched the memorized shape, whereas in the control condition, they gripped the secondary object. Crucially, during the VWM delay, participants engaged in a visual selection task, in which they located a target as fast as possible. The memorized shape could either encircle the target (congruent trials) or a distractor (incongruent trials). Replicating previous findings, we found that eye gaze was biased toward the VWM-matching shape and, importantly, more so when the shape was directly associated with an action plan. Moreover, the ERP results revealed that during the selection task, future action-relevant VWM-matching shapes elicited (1) a stronger Ppc (posterior positivity contralateral), signaling greater attentional saliency; (2) an earlier PD (distractor positivity) component, suggesting faster suppression; (3) a larger inverse (i.e., positive) sustained posterior contralateral negativity in incongruent trials, consistent with stronger suppression of action-associated distractors; and (4) an enhanced response-locked positivity over left motor regions, possibly indicating enhanced inhibition of the response associated with the memorized item during the interim task. Overall, these results suggest that action planning renders objects in VWM more attentionally salient, supporting the notion of selection-for-action in working memory.

Altered Cortical Activity during a Finger Tap in People with Stroke

This study describes electroencephalography (EEG) measurements during a simple finger movement in people with stroke to understand how temporal patterns of cortical activation and network connectivity align with prolonged muscle contraction at the end of a task. We investigated changes in the EEG temporal patterns in the beta band (13-26 Hz) of people with chronic stroke (N = 10, 7 F/3 M) and controls (N = 10, 7 F/3 M), during and after a cued movement of the index finger. We quantified the change in beta band EEG power relative to baseline as activation at each electrode and the change in task-based phase-locking value (tbPLV) and beta band task-based coherence (tbCoh) relative to baseline coherence as connectivity between EEG electrodes. Finger movements were associated with a decrease in beta power (event related desynchronization (ERD)) followed by an increase in beta power (event related resynchronization (ERS)). The ERS in the post task period was lower in the stroke group (7%), compared to controls (44%) (p < 0.001) and the transition from ERD to ERS was delayed in the stroke group (1.43 s) compared to controls (0.90 s) in the C3 electrode (p = 0.007). In the same post movement period, the stroke group maintained a heightened tbPLV (p = 0.030 for time to baseline of the C3:Fz electrode pair) and did not show the decrease in connectivity in electrode pair C3:Fz that was observed in controls (tbPLV: p = 0.006; tbCoh: p = 0.023). Our results suggest that delays in cortical deactivation patterns following movement coupled with changes in the time course of connectivity between the sensorimotor and frontal cortices in the stroke group might explain clinical observations of prolonged muscle activation in people with stroke. This prolonged activation might be attributed to the combination of cortical reorganization and changes to sensory feedback post-stroke.

Asymmetries in event-related potentials part 1: A systematic review of face processing studies

The human brain shows distinct lateralized activation patterns for a range of cognitive processes. One such function, which is thought to be lateralized to the right hemisphere (RH), is human face processing. Its importance for social communication and interaction has led to a plethora of studies investigating face processing in health and disease. Temporally highly resolved methods, like event-related potentials (ERPs), allow for a detailed characterization of different processing stages and their specific lateralization patterns. This systematic review aimed at disentangling some of the contradictory findings regarding the RH specialization in face processing focusing on ERP research in healthy participants. Two databases were searched for studies that investigated left and right electrodes while participants viewed (mostly neutral) facial stimuli. The included studies used a variety of different tasks, which ranged from passive viewing to memorizing faces. The final data selection highlights, that strongest lateralization to the RH was found for the N170, especially for right-handed young male participants. Left-handed, female, and older participants showed less consistent lateralization patterns. Other ERP components like the P1, P2, N2, P3, and the N400 were overall less clearly lateralized. The current review highlights that many of the assumed lateralization patterns are less clear than previously thought and that the variety of stimuli, tasks, and EEG setups used, might contribute to the ambiguous findings.

Bayesian estimation of group event-related potential components (BEGEP): testing a model for synthetic and real datasets

Objective.The spatial resolution of event-related potentials (ERPs) recorded on the head surface is quite low, since the sensors located on the scalp register mixtures of signals from several cortical sources. Bayesian models for multi-channel ERPs obtained from a group of subjects under multiple task conditions can aid in recovering signals from these sources.Approach.This study introduces a novel model that captures several important characteristics of ERP, including person-to-person variability in the magnitude and latency of source signals. Furthermore, the model takes into account that ERP noise, the main source of which is the background electroencephalogram, has the following properties: it is spatially correlated, spatially heterogeneous, and varies over time and from person to person. Bayesian inference algorithms have been developed to estimate the parameters of this model, and their performance has been evaluated through extensive experiments using synthetic data and real ERPs records in a large number of subjects (N= 351).Main results.The signal estimates obtained using these algorithms were compared with the results of the analysis of ERPs by conventional methods. This comparison showed that the use of this model is suitable for the analysis of ERPs and helps to reveal some features of source signals that are difficult to observe in their mixture signals recorded on the scalp.Significance.This study shown that the proposed method is a potentially useful tool for analyzing ERPs collected from groups of subjects in various cognitive neuroscience experiments.

Exploring the neural underpinnings of chord prediction uncertainty: an electroencephalography (EEG) study

Predictive processing in the brain, involving interaction between interoceptive (bodily signal) and exteroceptive (sensory) processing, is essential for understanding music as it encompasses musical temporality dynamics and affective responses. This study explores the relationship between neural correlates and subjective certainty of chord prediction, focusing on the alignment between predicted and actual chord progressions in both musically appropriate chord sequences and random chord sequences. Participants were asked to predict the final chord in sequences while their brain activity was measured using electroencephalography (EEG). We found that the stimulus preceding negativity (SPN), an EEG component associated with predictive processing of sensory stimuli, was larger for non-harmonic chord sequences than for harmonic chord progressions. Additionally, the heartbeat evoked potential (HEP), an EEG component related to interoceptive processing, was larger for random chord sequences and correlated with prediction certainty ratings. HEP also correlated with the N5 component, found while listening to the final chord. Our findings suggest that HEP more directly reflects the subjective prediction certainty than SPN. These findings offer new insights into the neural mechanisms underlying music perception and prediction, emphasizing the importance of considering auditory prediction certainty when examining the neural basis of music cognition.

Feedback negativity and feedback-related P3 in individuals at risk for depression: Comparing surface potentials and current source densities

Blunted responses to reward feedback have been linked to major depressive disorder (MDD) and depression risk. Using a monetary incentive delay task (win, loss, break-even), we investigated the impact of family risk for depression and lifetime history of MDD and anxiety disorder with 72-channel electroencephalograms (EEG) recorded from 29 high-risk and 32 low-risk individuals (15-58 years, 30 male). Linked-mastoid surface potentials (ERPs) and their corresponding reference-free current source densities (CSDs) were quantified by temporal principal components analysis (PCA). Each PCA solution revealed a midfrontal feedback negativity (FN; peak around 310 ms) and a posterior feedback-P3 (fb-P3; 380 ms) as two distinct reward processing stages. Unbiased permutation tests and multilevel modeling of component scores revealed greater FN to loss than win and neutral for all stratification groups, confirming FN sensitivity to valence. Likewise, all groups had greater fb-P3 to win and loss than neutral, confirming that fb-P3 indexes motivational salience and allocation of attention. By contrast, group effects were subtle, dependent on data transformation (ERP, CSD), and did not confirm reduced FN or fb-P3 for at-risk individuals. Instead, CSD-based fb-P3 was overall reduced in individuals with than without MDD history, whereas ERP-based fb-P3 was greater for high-risk individuals than for low-risk individuals for monetary, but not neutral outcomes. While the present findings do not support blunted reward processing in depression and depression risk, our side-by-side comparison underscores how the EEG reference choice affects the characterization of subtle group differences, strongly advocating the use of reference-free techniques.

Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG

BACKGROUND

Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency.

METHODS

Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score.

RESULTS

The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%.

CONCLUSION

The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.

Rhythmically Modulating Neural Entrainment during Exposure to Regularities Influences Statistical Learning

The ability to discover regularities in the environment, such as syllable patterns in speech, is known as statistical learning. Previous studies have shown that statistical learning is accompanied by neural entrainment, in which neural activity temporally aligns with repeating patterns over time. However, it is unclear whether these rhythmic neural dynamics play a functional role in statistical learning or whether they largely reflect the downstream consequences of learning, such as the enhanced perception of learned words in speech. To better understand this issue, we manipulated participants' neural entrainment during statistical learning using continuous rhythmic visual stimulation. Participants were exposed to a speech stream of repeating nonsense words while viewing either (1) a visual stimulus with a "congruent" rhythm that aligned with the word structure, (2) a visual stimulus with an incongruent rhythm, or (3) a static visual stimulus. Statistical learning was subsequently measured using both an explicit and implicit test. Participants in the congruent condition showed a significant increase in neural entrainment over auditory regions at the relevant word frequency, over and above effects of passive volume conduction, indicating that visual stimulation successfully altered neural entrainment within relevant neural substrates. Critically, during the subsequent implicit test, participants in the congruent condition showed an enhanced ability to predict upcoming syllables and stronger neural phase synchronization to component words, suggesting that they had gained greater sensitivity to the statistical structure of the speech stream relative to the incongruent and static groups. This learning benefit could not be attributed to strategic processes, as participants were largely unaware of the contingencies between the visual stimulation and embedded words. These results indicate that manipulating neural entrainment during exposure to regularities influences statistical learning outcomes, suggesting that neural entrainment may functionally contribute to statistical learning. Our findings encourage future studies using non-invasive brain stimulation methods to further understand the role of entrainment in statistical learning.

Skill and experience impact neural activity during global and local biological motion processing

During biological motion perception, individuals with perceptual experience learn to use more global processing, simultaneously extracting information from multiple body segments. Less experienced observers may use more local processing of individual body segments. The parietal lobe (e.g., alpha and beta power) has been shown to be critical to global and local static stimulus perception. Therefore, in this paper, we examined how skill impacts motion processing by assessing behavioral and neural responses to degrading global or local motion information for soccer penalty kicks. Skilled (N = 21) and less skilled (N = 19) soccer players anticipated temporally occluded videos of penalty kicks under normal, blurred (degraded local information), or spatially occluded (hips-only; degraded global information) viewing conditions. EEG was used to measure parietal alpha and beta power. Skilled players outperformed less skilled players, albeit both skill groups were less accurate in the blurred and hips-only conditions. Skilled performers showed significant decreases in bilateral parietal beta power in the hips-only condition, suggesting a greater reliance on global motion information under normal viewing conditions. Additionally, the hips-only condition elicited significantly greater beta relative to alpha power (beta - alpha), lower beta power, and lower alpha power than the control condition for both skill groups, suggesting spatial occlusion elicited a shift towards more local processing. Our novel findings demonstrate that skill and experience impact how motion is processed.

Impaired proactive cognitive control in Parkinson's disease

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

Parietal cortical alpha/beta suppression during prospective memory retrieval

Prospective memory (PM) impairment is among the most frequent memory complaints, yet little is known about the underlying neural mechanisms. PM for a planned intention may be achieved through strategic monitoring of the environment for cues, involving ongoing attentional processes, or through spontaneous retrieval. We hypothesized that parietal spectral power modulation accompanies prospectively encoded intention retrieval, irrespective of PM retrieval approach. A cognitively engaging arithmetic-based ongoing task (OGT) was employed to encourage spontaneous retrieval, with a focal, internally generated PM cue to eliminate OGT/PM trial differentiation based on perceptual or conceptual PM cue features. Two PM repetition frequencies were used to vary the extent of strategic monitoring. We observed a transient parietal alpha/beta spectral power reduction directly preceding the response, which was distinguishable on a single trial basis, as revealed by an OGT/PM trial classification rate exceeding 70% using linear discriminant analysis. The alpha/beta idling rhythm reflects cortical inhibition. A disengagement of task-relevant neural assemblies from this rhythm, reflected in alpha/beta power reduction, is deemed to increase information content, facilitate information integration, and enable engagement of neural assemblies in task-related cortical networks. The observed power reduction is consistent with the Dual Pathways model, where PM strategies converge at the PM retrieval stage.

N1-P2 event-related potentials and perceived intensity are associated: The effects of a weak pre-stimulus and attentional load on processing of a subsequent intense stimulus

A weak stimulus presented immediately before a more intense one reduces both the N1-P2 cortical response and the perceived intensity of the intense stimulus. The former effect is referred to as cortical prepulse inhibition (PPI), the latter as prepulse inhibition of perceived stimulus intensity (PPIPSI). Both phenomena are used to study sensory gating in clinical and non-clinical populations, however little is known about their relationship. Here, we investigated 1) the possibility that cortical PPI and PPIPSI are associated, and 2) how they are affected by attentional load. Participants were tasked with comparing the intensity of an electric pulse presented alone versus one preceded 200 ms by a weaker electric prepulse (Experiment 1), or an acoustic pulse presented alone with one preceded 170 ms by a weaker acoustic prepulse (Experiment 2). A counting task (easy vs. hard) manipulating attentional load was included in Experiment 2. In both experiments, we observed a relationship between N1-P2 amplitude and perceived intensity, where greater cortical PPI was associated with a higher probability of perceiving the 'pulse with prepulse' as less intense. Moreover, higher attentional load decreased observations of PPIPSI but had no effect on N1-P2 amplitude. Based on the findings we propose that PPIPSI partially relies on the allocation of attentional resources towards monitoring cortical channels that process stimulus intensity characteristics such as the N1-P2 complex.

Auditory Evoked P300 Potential in Patients With Parkinson's Disease

BACKGROUND

 Parkinson's disease (PD) is the second most common neurodegenerative disorder. Though the cardinal features of PD are motor symptoms, it is also associated with many non-motor symptoms, such as cognitive impairment, autonomic dysfunction, sleep disorders, and depression, which could affect the quality of life. Early identification of PD's non-motor signs can aid in the diagnosis of PD. The current research aimed to assess the neurophysiological changes in PD patients using auditory evoked P300 potential and to determine the possible correlation between P300 wave components and cognitive impairment.

MATERIALS AND METHODS

 This cross-sectional research involved 32 idiopathic PD patients. The neurophysiological changes in PD patients were studied using auditory evoked P300 potential and the obtained data were compared with normative data. The patient's cognitive status was scored using the Montreal Cognitive Assessment (MoCA) questionnaire and they were divided into two groups: the patients with normal cognition and the patients with impaired cognition.

RESULTS

 The participants showed a significant decrease in P300 amplitude (p = 0.000) but no change in P300 latency when compared to normative data using the Wilcoxon rank sum test. Also, there was a positive correlation between the MoCA score and P300 amplitude (p < 0.05), indicating that if cognition is impaired, P300 amplitude would also be reduced. There was a significant difference between PD patients with impaired cognition and patients with normal cognition in the P300 amplitude at Cz (p = 0.001) and Fz (p = 0.003) when the Mann-Whitney U test was used. These findings indicate that it is possible to notice changes in the P300 wave components among PD patients when their cognition is impaired.

CONCLUSION

 Auditory evoked P300 potentials can be used to objectively evaluate cognition in PD patients and by starting supportive therapy, the quality of life for PD patients can be improved.

Healthy ageing and cognitive impairment alter EEG functional connectivity in distinct frequency bands

Functional connectivity (FC) indicates the interdependencies between brain signals recorded from spatially distinct locations in different frequency bands, which is modulated by cognitive tasks and is known to change with ageing and cognitive disorders. Recently, the power of narrow-band gamma oscillations induced by visual gratings have been shown to reduce with both healthy ageing and in subjects with mild cognitive impairment (MCI). However, the impact of ageing/MCI on stimulus-induced gamma FC has not been well studied. We recorded electroencephalogram (EEG) from a large cohort (N = 229) of elderly subjects (>49 years) while they viewed large cartesian gratings to induce gamma oscillations and studied changes in alpha and gamma FC with healthy ageing (N = 218) and MCI (N = 11). Surprisingly, we found distinct differences across age and MCI groups in power and FC. With healthy ageing, alpha power did not change but FC decreased significantly. MCI reduced gamma but not alpha FC significantly compared with age and gender matched controls, even when power was matched between the two groups. Overall, our results suggest distinct effects of ageing and disease on EEG power and FC, suggesting different mechanisms underlying ageing and cognitive disorders.

Laplacian reference is optimal for steady-state visual-evoked potentials

Steady-state visual-evoked potentials (SSVEPs) are widely used in human neuroscience studies and applications such as brain-computer interfaces (BCIs). Surprisingly, no previous study has systematically evaluated different reference methods for SSVEP analysis, despite that signal reference is crucial for the proper assessment of neural activities. In the present study, using four datasets from our previous SSVEP studies (Chen J, Valsecchi M, Gegenfurtner KR. J Neurophysiol 118: 749-754, 2017; Chen J, Valsecchi M, Gegenfurtner KR. Neuropsychologia 102: 206-216, 2017; Chen J, McManus M, Valsecchi M, Harris LR, Gegenfurtner KR. J Vis 19: 8, 2019) and three public datasets from other studies (Baker DH, Vilidaite G, Wade AR. PLoS Comput Biol 17: e1009507, 2021; Lygo FA, Richard B, Wade AR, Morland AB, Baker DH. NeuroImage 230: 117780, 2021; Vilidaite G, Norcia AM, West RJH, Elliott CJH, Pei F, Wade AR, Baker DH. Proc R Soc B 285: 20182255, 2018), we compared four reference methods: monopolar reference, common average reference, averaged-mastoids reference, and Laplacian reference. The quality of the resulting SSVEP signals was compared in terms of both signal-to-noise ratios (SNRs) and reliability. The results showed that Laplacian reference, which uses signals at the maximally activated electrode after subtracting the average of the nearby electrodes to reduce common noise, gave rise to the highest SNRs. Furthermore, the Laplacian reference resulted in SSVEP signals that were highly reliable across recording sessions or trials. These results suggest that Laplacian reference is optimal for SSVEP studies and applications. Laplacian reference is especially advantageous for SSVEP experiments where short preparation time is preferred as it requires only data from the maximally activated electrode and a few surrounding electrodes.NEW & NOTEWORTHY The present study provides a comprehensive evaluation of the use of different reference methods for steady-state visual-evoked potentials (SSVEPs) and has found that Laplacian reference increases signal-to-noise ratios (SNRs) and enhances reliabilities of SSVEP signals. Thus, the results suggest that Laplacian reference is optimal for SSVEP analysis.

Motor Cortical Correlates of Paired Associative Stimulation Induced Plasticity: A TMS-EEG Study

Paired associative stimulation (PAS) is a non-invasive brain stimulation technique that modulates synaptic plasticity in the human motor cortex (M1). Since previous studies have primarily used motor-evoked potentials (MEPs) as outcome measure, cortical correlates of PAS-induced plasticity remain unknown. Therefore, the aim of this observational study was to investigate cortical correlates of a standard PAS induced plasticity in the primary motor cortex by using a combined TMS-EEG approach in a cohort of eighteen healthy subjects. In addition to the expected long-lasting facilitatory modulation of MEPs amplitude, PAS intervention also induced a significant increase in transcranial magnetic stimulation-evoked potentials (TEPs) P30 and P60 amplitude. No significant correlation between the magnitude of PAS-induced changes in TEP components and MEP amplitude were observed. However, the linear regression analysis revealed that the combined changes in P30 and P60 component amplitudes significantly predicted the MEP facilitation after PAS. The findings of our study offer novel insight into the neurophysiological changes associated with PAS-induced plasticity at M1 cortical level and suggest a complex relationship between TEPs and MEPs changes following PAS.

Enhanced temporal resolution of vision in action video game players

Video game play has been suggested to improve visual and attention processing. Nevertheless, while action video game play is highly dynamic, there is scarce research on how information is temporally discriminated at the millisecond level. This cross-sectional study investigates whether temporal discrimination at the millisecond level in vision varies across action video game players (VGPs; N = 23) and non-video game players (NVGPs; N = 23). Participants discriminated synchronous from asynchronous onsets of two visual targets in virtual reality, while their EEG and oculomotor movements were recorded. Results show an increased sensitivity to short asynchronies (11, 33 and 66 ms) in VGPs compared with NVGPs, which was especially marked at the start of the task, suggesting better temporal discrimination abilities. Pre-targets oculomotor freezing - the inhibition of small fixational saccades - was associated with correct temporal discrimination, probably revealing attentional preparation. However, this parameter did not differ between groups. EEG and reconstruction analyses suggest that the enhancement of temporal discrimination in VGPs during temporal discrimination is related to parieto-occipital processing, and a reduction of alpha-band (8-14 Hz) power and inter-trial phase coherence. Overall, the study reveals an enhanced ability in action video game players to discriminate in time visual events in close temporal proximity combined with reduced alpha-band oscillatory activities. Consequently, playing action video games is associated with an improved temporal resolution of vision.

Tool use acquisition induces a multifunctional interference effect during object processing: evidence from the sensorimotor mu rhythm

A fundamental characteristic of human development is acquiring and accumulating tool use knowledge through observation and sensorimotor experience. Recent studies showed that, in children and adults, different action possibilities to grasp-to-move and grasp-to-use objects generate a conflict that extinguishes neural motor resonance phenomena during visual object processing. In this study, a training protocol coupled with EEG recordings was administered in virtual reality to healthy adults to evaluate whether a similar conflict occurs between novel tool use knowledge. Participants perceived and manipulated two novel 3D tools trained beforehand with either single or double-usage. A weaker reduction of mu-band (10-13 Hz) power, accompanied by a reduced inter-trial phase coherence, was recorded during the perception of the tool associated with the double-usage. These effects started within the first 200 ms of visual object processing and were predominantly recorded over the left motor system. Furthermore, interacting with the double usage tool delayed grasp-to-reach movements. The results highlight a multifunctional interference effect, such as tool use acquisition reduces the neural motor resonance phenomenon and inhibits the activation of the motor system during subsequent object recognition. These results imply that learned tool use information guides sensorimotor processes of objects.

Resting-state frontal, frontlateral, and parietal alpha asymmetry:A pilot study examining relations with depressive disorder type and severity

Introduction

The search for biomarkers has been central to efforts of improving clinical diagnosis and prognosis in psychopathology in the last decades. The main approach has been to validate biomarkers that could accurately discriminate between clinical diagnoses of very prevalent forms of psychopathology. One of the most popular electrophysiological markers proposed for discrimination in depressive disorders is the electroencephalography (EEG)-derived frontal alpha asymmetry. However, the validity, reliability and predictive value of this biomarker have been questioned in recent years, mainly due to conceptual and methodological heterogeneity.

Methods

In the current non-experimental, correlational study we investigated relationship of resting-state EEG alpha asymmetry from multiple sites (frontal, frontolateral, and parietal) with different forms of depressive disorders (varying in type or severity), in a clinical sample.

Results

Results showed that alpha asymmetry in the parietal (P3-P4) was significantly higher than in the frontal (F3-F4) and frontolateral sites (F7-F8). However, we did not find significant relations between alpha asymmetry indices and our depressive disorder measures, except for a moderate positive association between frontolateral alpha asymmetry (eyes-closed only) and depressive disorder severity (determined through clinical structured interview). We also found no significant differences in alpha asymmetry between participants, depending on their depression type.

Discussion

Based on results, we propose the parietal and frontolateral asymmetry indices to form hypotheses that should not be abandoned in the depression markers research, but worth for further experimental research. Methodological and clinical implications of the current findings are discussed.

Evolving changes in cortical and subcortical excitability during movement preparation: A study of brain potentials and eye-blink reflexes during loud acoustic stimulation

During preparation for action, the presentation of loud acoustic stimuli (LAS) can trigger movements at very short latencies in a phenomenon called the StartReact effect. It was initially proposed that a special, separate subcortical mechanism that bypasses slower cortical areas could be involved. We sought to examine the evidence for a separate mechanism against the alternative that responses to LAS can be explained by a combination of stimulus intensity effects and preparatory states. To investigate whether cortically mediated preparatory processes are involved in mediating reactions to LAS, we used an auditory reaction task where we manipulated the preparation level within each trial by altering the conditional probability of the imperative stimulus. We contrasted responses to non-intense tones and LAS and examined whether cortical activation and subcortical excitability and motor responses were influenced by preparation levels. Increases in preparation levels were marked by gradual reductions in reaction time (RT) coupled with increases in cortical activation and subcortical excitability - at both condition and trial levels. Interestingly, changes in cortical activation influenced motor and auditory but not visual areas - highlighting the widespread yet selective nature of preparation. RTs were shorter to LAS than tones, but the overall pattern of preparation level effects was the same for both stimuli. Collectively, the results demonstrate that LAS responses are indeed shaped by cortically mediated preparatory processes. The concurrent changes observed in brain and behavior with increasing preparation reinforce the notion that preparation is marked by evolving brain states which shape the motor system for action.

Mild Cognitive Impairment in African Americans Is Associated with Differences in EEG Theta/Beta Ratio

BACKGROUND

Identification of older individuals with increased risk for cognitive decline can contribute not only to personal benefits (e.g., early treatment, evaluation of treatment), but could also benefit clinical trials (e.g., patient selection). We propose that baseline resting-state electroencephalography (rsEEG) could provide markers for early identification of cognitive decline.

OBJECTIVE

To determine whether rsEEG theta/beta ratio (TBR) differed between mild cognitively impaired (MCI) and healthy older adults.

METHODS

We analyzed rsEEG from a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling older African Americans (58 cognitively typical and 41 MCI). Eyes closed rsEEGs were acquired before and after participants engaged in a visual motion direction discrimination task. rsEEG TBR was calculated for four midline locations and assessed for differences as a function of MCI status. Hemispheric asymmetry of TBR was also analyzed at equidistant lateral electrode sites.

RESULTS

Results showed that MCI participants had a higher TBR than controls (p = 0.04), and that TBR significantly differed across vertex location (p < 0.001) with the highest TBR at parietal site. MCI and cognitively normal controls also differed in hemispheric asymmetries, such that MCI show higher TBR at frontal sites, with TBR greater over right frontal electrodes in the MCI group (p = 0.003) and no asymmetries found in the cognitively normal group. Lastly, we found a significant task aftereffect (post-task compared to pre-task measures) with higher TBR at posterior locations (Oz p = 0.002, Pz p = 0.057).

CONCLUSION

TBR and TBR asymmetries differ between MCI and cognitively normal older adults and may reflect neurodegenerative processes underlying MCI symptoms.

Spatial proximity to others induces plastic changes in the neural representation of the peripersonal space

Peripersonal space (PPS) is a highly plastic "invisible bubble" surrounding the body whose boundaries are mapped through multisensory integration. Yet, it is unclear how the spatial proximity to others alters PPS boundaries. Across five experiments (N = 80), by recording behavioral and electrophysiological responses to visuo-tactile stimuli, we demonstrate that the proximity to others induces plastic changes in the neural PPS representation. The spatial proximity to someone else's hand shrinks the portion of space within which multisensory responses occur, thus reducing the PPS boundaries. This suggests that PPS representation, built from bodily and multisensory signals, plastically adapts to the presence of conspecifics to define the self-other boundaries, so that what is usually coded as "my space" is recoded as "your space". When the space is shared with conspecifics, it seems adaptive to move the other-space away from the self-space to discriminate whether external events pertain to the self-body or to other-bodies.

P3b Amplitude and Latency in Tic Disorders: A Meta-Analysis

P3b is an event-related potential (ERP) that may be abnormal in patients with tic disorders (TD), but evidence has been inconsistent. Given the possible association between P3b and TD and the need for biomarkers for TD, the primary objective of this meta-analysis was to characterize P3b in patients with TD in comparison to healthy controls (HCs).

METHODS

By searching PubMed, Embase, Web of Science, SCOPUS, Medline, and Google Scholar, we identified studies that compared P3b between TD patients and HCs. The amplitude and latency of P3b were then analyzed. Subgroup analyses were conducted to investigate the influence of different experimental factors on P3b indices.

RESULT

Overall, 19 articles involving 388 cases and 414 controls were evaluated. There were no significant abnormalities in P3b amplitude and latency in TD patients. The P3b amplitude of the TD patients was significantly decreased during the oddball task, and the P3b amplitude of the adult TD patients was also significantly decreased.

CONCLUSION

TD patients may have an abnormal P3b compared to HCs under specified conditions.

Intelligence and Visual Mismatch Negativity: Is Pre-Attentive Visual Discrimination Related to General Cognitive Ability?

EEG has been used for decades to identify neurocognitive processes related to intelligence. Evidence is accumulating for associations with neural markers of higher-order cognitive processes (e.g., working memory); however, whether associations are specific to complex processes or also relate to earlier processing stages remains unclear. Addressing these issues has implications for improving our understanding of intelligence and its neural correlates. The MMN is an ERP that is elicited when, within a series of frequent standard stimuli, rare deviant stimuli are presented. As stimuli are typically presented outside the focus of attention, the MMN is suggested to capture automatic pre-attentive discrimination processes. However, the MMN and its relation to intelligence has largely only been studied in the auditory domain, thus preventing conclusions about the involvement of automatic discrimination processes in humans' dominant sensory modality-vision. EEG was recorded from 50 healthy participants during a passive visual oddball task that presented simple sequence violations and deviations within a more complex hidden pattern. Signed area amplitudes and fractional area latencies of the visual MMN were calculated with and without Laplacian transformation. Correlations between visual MMN and intelligence (Raven's Advanced Progressive Matrices) were of negligible to small effect sizes, differed critically between measurement approaches, and Bayes Factors provided anecdotal to substantial evidence for the absence of an association. We discuss differences between the auditory and visual MMN, the implications of different measurement approaches, and offer recommendations for further research in this evolving field.

The novel frontal alpha asymmetry factor and its association with depression, anxiety, and personality traits

Frontal alpha asymmetry (FAA) is widely examined in EEG research, yet a procedural consensus on its assessment is lacking. In this study, we tested a latent factorial approach to measure FAA. We assessed resting-state FAA at broad, low, and high alpha bands (8-13; 8-10.5; and 11-13 Hz) using mastoids as reference electrodes and Current Source Density (CSD) transformation (N = 139 non-clinical participants). From mastoid-referenced data, we extracted a frontal alpha asymmetry factor (FAAf) and a parietal factor (PAAf) subjecting all asymmetry indices to a varimax-rotated, principal component analysis. We explored split-half reliability and discriminant validity of the mastoid factors and the mastoid and CSD raw asymmetry indices (F3/4, F7/8, P3/4, and P7/8). Both factor and raw scores reached an excellent split-half reliability (>.99), but only the FAAf reached the maximum discriminant validity from parietal scores. Next, we explored the correlations of latent factor and raw FAA scores with symptoms of depression, anxiety, and personality traits to determine which associations were driven by FAA after variance from parietal activity was removed. After correcting for false discovery rate, only FAAf at the low alpha band was negatively associated with depression symptoms (a latent CES-D factor) and significantly diverged from PAAf's association with depression symptoms. With respect to personality traits, only CSD-transformed F7/8 was positively correlated with Conscientiousness and significantly diverged from the correlations between Conscientiousness and P3/4 and P7/8. Overall, the latent factor approach shows promise for isolating functionally distinct resting-state EEG signatures, although further research is needed to examine construct validity.

Large-scale frontoparietal theta, alpha, and beta phase synchronization: A set of EEG differential characteristics for freezing of gait in Parkinson's disease?

Freezing of gait (FOG) is a complex gait disturbance in Parkinson's disease (PD), during which the patient is not able to effectively initiate gait or continue walking. The mystery of the FOG phenomenon is still unsolved. Recent studies have revealed abnormalities in cortical activities associated with FOG, which highlights the importance of cortical and cortical-subcortical network dysfunction in PD patients with FOG. In this paper, phase-locking value (PLV) of eight frequency sub-bands between 0.05 Hz and 35 Hz over frontal, motor, and parietal areas [during an ankle dorsiflexion (ADF) task] is used to investigate EEG phase synchronization. PLV was investigated over both superficial and deeper networks by analyzing EEG signals preprocessed with and without Surface Laplacian (SL) spatial filter. Four groups of participants were included: PD patients with severe FOG (N = 5, 5 males), PD patients with mild FOG (N = 7, 6 males), PD patients without FOG (N = 14, 13 males), and healthy age-matched controls (N = 13, 10 males). Fifteen trials were recorded from each participant. At superficial layers, frontoparietal theta phase synchrony was a unique feature present in PD with FOG groups. At deeper networks, significant dominance of interhemispheric frontoparietal alpha phase synchrony in PD with FOG, in contrast to beta phase synchrony in PD without FOG, was identified. Alpha phase synchrony was more distributed in PD with severe FOG, with higher levels of frontoparietal alpha phase synchrony. In addition to FOG-related abnormalities in PLV analysis, phase-amplitude coupling (PAC) analysis was also performed on frequency bands with PLV abnormalities. PAC analysis revealed abnormal coupling between theta and low beta frequency bands in PD with severe FOG at the superficial layers over frontal areas. At deeper networks, theta and alpha frequency bands show high PAC over parietal areas in PD with severe FOG. Alpha and low beta also presented PAC over frontal areas in PD groups with FOG. The results introduced significant phase synchrony differences between PD with and without FOG and provided important insight into a possible unified underlying mechanism for FOG. These results thus suggest that PLV and PAC can potentially be used as EEG-based biomarkers for FOG.

A systematic data-driven approach to analyze sensor-level EEG connectivity: Identifying robust phase-synchronized network components using surface Laplacian with spectral-spatial PCA

Although conventional averaging across predefined frequency bands reduces the complexity of EEG functional connectivity (FC), it obscures the identification of resting-state brain networks (RSN) and impedes accurate estimation of FC reliability. Extending prior work, we combined scalp current source density (CSD; spherical spline surface Laplacian) and spectral-spatial PCA to identify FC components. Phase-based FC was estimated via debiased-weighted phase-locking index from CSD-transformed resting EEGs (71 sensors, 8 min, eyes open/closed, 35 healthy adults, 1-week retest). Spectral PCA extracted six robust alpha and theta components (86.6% variance). Subsequent spatial PCA for each spectral component revealed seven robust regionally focused (posterior, central, and frontal) and long-range (posterior-anterior) alpha components (peaks at 8, 10, and 13 Hz) and a midfrontal theta (6 Hz) component, accounting for 37.0% of FC variance. These spatial FC components were consistent with well-known networks (e.g., default mode, visual, and sensorimotor), and four were sensitive to eyes open/closed conditions. Most FC components had good-to-excellent internal consistency (odd/even epochs, eyes open/closed) and test-retest reliability (ICCs ≥ .8). Moreover, the FC component structure was generally present in subsamples (session × odd/even epoch, or smaller subgroups [n = 7-10]), as indicated by high similarity of component loadings across PCA solutions. Apart from systematically reducing FC dimensionality, our approach avoids arbitrary thresholds and allows quantification of meaningful and reliable network components that may prove to be of high relevance for basic and clinical research applications.

Shifting Baselines: Longitudinal Reductions in EEG Beta Band Power Characterize Resting Brain Activity with Intensive Meditation

Objectives

A core assumption of meditation training is that cognitive capacities developed during formal practice will transfer to other contexts or activities as expertise develops over time. This implies that meditation training might influence domain-general neurocognitive systems, the spontaneous activity of which should be reflected in the dynamics of the resting brain. Previous research has demonstrated that 3 months of meditation training led to reductions in EEG beta band power during mindfulness of breathing practice. The current study extends these findings to ask whether concomitant shifts in power are observed during 2 min of eyes closed rest, when participants are not explicitly engaged in formal meditation.

Methods

Experienced meditation practitioners were randomly assigned to practice 3 months of focused attention meditation in a residential retreat, or to serve as waitlist controls. The waitlist controls later completed their own 3-month retreat. Permutation-based cluster analysis of 88-channel resting EEG data was used to test for spectral changes in spontaneous brain activity over the course of the retreats.

Results

Longitudinal reductions in EEG power in the beta frequency range were identified and replicated across the two independent training periods. Less robust reductions were also observed in the high alpha frequency range, and in individual peak alpha frequency. These changes closely mirror those previously observed during formal mindfulness of breathing meditation practice.

Conclusions

These findings suggest that the neurocognitive effects of meditation training can extend beyond the bounds of formal practice, influencing the spontaneous activity of the resting brain. Rather than serving as an invariant baseline, resting states might carry meaningful training-related effects, blurring the line between state and trait change.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12671-022-01974-9.

Multisensory integration and interactions across vision, hearing, and somatosensation in autism spectrum development and typical development

Most prior studies of multisensory integration (MSI) in autism have measured MSI in only a single combination of modalities - typically audiovisual integration. The present study used onset reaction times (RTs) and 125-channel electroencephalography (EEG) to examine different forms of bimodal and trimodal MSI based on combinations of auditory (noise burst), somatosensory (finger tap), and visual (flash) stimuli presented in a spatially-aligned manner using a custom desktop apparatus. A total of 36 autistic and 19 non-autistic adolescents between the ages of 11-14 participated. Significant RT multisensory facilitation relative to summed unisensory RT was observed in both groups, as were significant differences between summed unisensory and multisensory ERPs. Although the present study's statistical approach was not intended to test effect latencies, these interactions may have begun as early as ∼45 ms, constituting "early" (<100 ms) MSI. RT and ERP measurements of MSI appeared independent of one another. Groups did not significantly differ in multisensory RT facilitation, but we found exploratory evidence of group differences in the magnitude of audiovisual interactions in ERPs. Future research should make greater efforts to explore MSI in under-represented populations, especially autistic people with intellectual disabilities and nonspeaking/minimally-verbal autistic people.

µ-rhythm phase from somatosensory but not motor cortex correlates with corticospinal excitability in EEG-triggered TMS

BACKGROUND

Sensorimotor µ-rhythm phase is correlated with corticospinal excitability. Transcranial magnetic stimulation (TMS) of motor cortex results in larger motor evoked potentials (MEPs) during the negative peak of the EEG oscillation as extracted with a surface Laplacian. However, the anatomical source of the relevant oscillation is not clear and demonstration of the relationship is sensitive to the choice of EEG montage.

OBJECTIVE/HYPOTHESIS

Here, we compared two EEG montages preferentially sensitive to oscillations originating from the crown of precentral gyrus (dorsal premotor cortex) vs. postcentral gyrus (secondary somatosensory cortex). We hypothesized that the EEG signal from precentral gyrus would correlate more strongly with MEP amplitude, given that the corticospinal neurons are located in the anterior wall of the sulcus and the corticospinal tract has input from premotor cortex.

NEW METHOD

Real-time EEG-triggered TMS of motor cortex was applied in 6 different conditions in randomly interleaved order, 3 phase conditions (positive peak, negative peak, random phase of the ongoing µ-oscillation), and each phase condition for 2 different EEG montages corresponding to oscillations preferentially originating in precentral gyrus (premotor cortex) vs. postcentral gyrus (somatosensory cortex), extracted using FCC3h vs. C3 centered EEG montages.

RESULTS

The negative vs. positive peak of sensorimotor µ-rhythm as extracted from the C3 montage (postcentral gyrus, somatosensory cortex) correlated with states of high vs. low corticospinal excitability (p < 0.001), replicating previous findings. However, no significant correlation was found for sensorimotor µ-rhythm as extracted from the neighboring FCC3 montage (precentral gyrus, premotor cortex). This implies that EEG-signals from the somatosensory cortex are better predictors of corticospinal excitability than EEG-signals from the motor areas.

CONCLUSIONS

The extraction of a brain oscillation whose phase corresponds to corticospinal excitability is highly sensitive to the selected EEG montage and the location of the EEG sensors on the scalp. Here, the cortical source of EEG oscillations predicting response amplitude does not correspond to the cortical target of the stimulation, indicating that even in this simple case, a specific neuronal pathway from somatosensory cortex to primary motor cortex is involved.

EEG asymmetry and cognitive testing in MCI identification

BACKGROUND

Finding the baseline resting-state EEG markers for early identification of cognitive decline can contribute to the identification of individuals at risk of further change. Potential applications include identifying participants for clinical trials, early treatment, and evaluation of treatment, accessible even from a community setting.

METHODS

Analyses were completed on a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling African Americans (58 cognitively typical/HC, and 41 mildly cognitively impaired/MCI), who were recruited from the Michigan Alzheimer's Disease Research Center (MADRC) and the Wayne State University Institute of Gerontology. In addition to neuropsychological testing with CogState and Toolbox computerized batteries, resting-state EEGs (rsEEG, eyes closed) were acquired before and after participants were engaged in a visual motion direction discrimination task. rsEEG frontal alpha asymmetry (FAA) and frontal beta asymmetry (FBA) were calculated.

RESULTS

FAA showed no difference across groups for the pre-task resting state. FBA was significantly different between groups, with more asymmetric frontal beta in MCI. Both physiological indices, however, along with computerized neuropsychological tests were significant predictors in logistic regression classification of MCI vs. control participants.

CONCLUSION

rsEEG asymmetries can contribute significantly to successful discrimination of older persons with MCI from those without, over and above cognitive testing, alone.

Still Wanting to Win: Reward System Stability in Healthy Aging

Healthy aging is accompanied by multi-faceted changes. Especially within the brain, healthy aging exerts substantial impetus on core parts of cognitive and motivational networks. Rewards comprise basic needs, such as food, sleep, and social contact. Thus, a functionally intact reward system remains indispensable for elderly people to cope with everyday life and adapt to their changing environment. Research shows that reward system function is better preserved in the elderly than most cognitive functions. To investigate the compensatory mechanisms providing reward system stability in aging, we employed a well-established reward paradigm (Monetary Incentive Delay Task) in groups of young and old participants while undergoing EEG measurement. As a new approach, we applied EEG connectivity analyses to assess cortical reward-related network connectivity. At the behavioral level, our results confirm that the function of the reward system is preserved in old age. The mechanisms identified for maintaining reward system function in old age do not fit into previously described models of cognitive aging. Overall, older adults exhibit lower reward-related connectivity modulation, higher reliance on posterior and right-lateralized brain areas than younger adults, and connectivity modulation in the opposite direction than younger adults, with usually greater connectivity during non-reward compared to reward conditions. We believe that the reward system has unique compensatory mechanisms distinct from other cognitive functions, probably due to its etymologically very early origin. In summary, this study provides important new insights into cortical reward network connectivity in healthy aging.

A tutorial on the use of temporal principal component analysis in developmental ERP research - Opportunities and challenges

Developmental researchers are often interested in event-related potentials (ERPs). Data-analytic approaches based on the observed ERP suffer from major problems such as arbitrary definition of analysis time windows and regions of interest and the observed ERP being a mixture of latent underlying components. Temporal principal component analysis (PCA) can reduce these problems. However, its application in developmental research comes with the unique challenge that the component structure differs between age groups (so-called measurement non-invariance). Separate PCAs for the groups can cope with this challenge. We demonstrate how to make results from separate PCAs accessible for inferential statistics by re-scaling to original units. This tutorial enables readers with a focus on developmental research to conduct a PCA-based ERP analysis of amplitude differences. We explain the benefits of a PCA-based approach, introduce the PCA model and demonstrate its application to a developmental research question using real-data from a child and an adult group (code and data openly available). Finally, we discuss how to cope with typical challenges during the analysis and name potential limitations such as suboptimal decomposition results, data-driven analysis decisions and latency shifts.

Neural correlates of familiar and unfamiliar action in infancy

Behavioral evidence shows that experience with an action shapes action perception. Neural mirroring has been suggested as a mechanism underlying this behavioral phenomenon. Suppression of electroencephalogram (EEG) power in the mu frequency band, an index of motor activation, typically reflects neural mirroring. However, contradictory findings exist regarding the association between mu suppression and motor familiarity in infant EEG studies. In this study, we investigated the neural underpinnings reflecting the role of familiarity in action perception. We measured neural processing of familiar (grasp) and novel (tool-use) actions in 9- and 12-month-old infants. Specifically, we measured infants' distinct motor/visual activity and explored functional connectivity associated with these processes. Mu suppression was stronger for grasping than for tool use, whereas significant mu and occipital alpha (indexing visual activity) suppression were evident for both actions. Interestingly, selective motor-visual functional connectivity was found during observation of familiar action, a pattern not observed for novel action. Thus, the neural correlates of perception of familiar actions may be best understood in terms of a functional neural network rather than isolated regional activity. Our findings provide novel insights on analytic approaches for identifying motor-specific neural activity while also considering neural networks involved in observing motorically familiar versus unfamiliar actions.

Predictive value of P300 event-related potential component in early cognitive impairment in patients with uncomplicated newly diagnosed hepatitis C virus

Background

Cognitive impairment in patients with hepatitis C virus (HCV) is reported in the early onset of HCV infection without hepatic cirrhosis or marked liver impairment. Methods currently available to identify the risk for early cognitive impairment in hepatitis C virus (HCV) infection do not combine enough sensitivity and specificity. The present study aimed to evaluate the P 300 components of event-related potential (ERP) abnormalities as valid biomarkers for prediction and diagnosis of the cognitive impairment in newly diagnosed hepatitis C virus infection. This study is a case–control involved fifty patients newly diagnosed HCV and fifty age and sex-matched healthy controls. Assessments of cognitive functions were carried out by the Mini-mental State Examination, Wechsler Memory Scale Revised short form, and The Wechsler Adult Intelligence Scale, in addition to estimation of the amplitude and the latency of the P300 by the event-related potentials.

Results

Neuropsychological scales suggested the early incidence of cognitive impairment among hepatitis C virus patients. The electrophysiological study showed significant prolongation of P300 latency and decreased amplitude in HCV patients group compared with the control group. A binary logistic regression detected that P 300 latency ≥ 369 ms was significantly accompanied by a threefold increased risk of impaired cognition (OR 3.09, 95% CI 1.59–5.72, P < 0.01), while P 300 amplitude ≤ 8.2 μv was significantly accompanied by a twofold increased risk of impaired cognition (OR 2.18, 95% 1.43–4.05, P < 0.01).

Conclusion

This study concluded that the P300 event-related potentials components are valid biomarker as easy, noninvasive assessment and cost-effective method of early cognitive impairment in patients with uncomplicated newly diagnosed hepatitis C virus.

Registration of Clinical Trial Research

ClinicalTrials.gov ID: NCT04389268. https://clinicaltrials.gov/ct2/show/NCT04389268

A comparison and classification of oscillatory characteristics in speech perception and covert speech

Covert speech, the mental imagery of speaking, has been studied increasingly to understand and decode thoughts in the context of brain-computer interfaces. In studies of speech comprehension, neural oscillations are thought to play a key role in the temporal encoding of speech. However, little is known about the role of oscillations in covert speech. In this study, we investigated the oscillatory involvements in covert speech and speech perception. Data were collected from 10 participants with 64 channel EEG. Participants heard the words, 'blue' and 'orange', and subsequently mentally rehearsed them. First, continuous wavelet transform was performed on epoched signals and subsequently two-tailed t-tests between two classes were conducted to determine statistical differences in frequency and time (t-CWT). Features were also extracted using t-CWT and subsequently classified using a support vector machine. θ and γ phase amplitude coupling (PAC) was also assessed within and between tasks. All binary classifications produced accuracies significantly greater (80-90%) than chance level, supporting the use of t-CWT in determining relative oscillatory involvements. While the perception task dynamically invoked all frequencies with more prominent θ and α activity, the covert task favoured higher frequencies with significantly higher γ activity than perception. Moreover, the perception condition produced significant θ-γ PAC, corroborating a reported linkage between syllabic and phonemic sampling. Although this coupling was found to be suppressed in the covert condition, we found significant cross-task coupling between perception θ and covert speech γ. Covert speech processing appears to be largely associated with higher frequencies of EEG. Importantly, the significant cross-task coupling between speech perception and covert speech, in the absence of within-task covert speech PAC, supports the notion that the γ- and θ-bands subserve, respectively, shared and unique encoding processes across tasks.

Resting State Functional Connectivity Analysis During General Anesthesia: A High-Density EEG Study

The depth of anesthesia monitoring is helpful to guide administrations of general anesthetics during surgical procedures,however, the conventional 2-4 channels electroencephalogram (EEG) derived monitors have their limitations in monitoring conscious states due to low spatial resolution and suboptimal algorithm. In this study, 256-channel high-density EEG signals in 24 subjects receiving three types of general anesthetics (propofol, sevoflurane and ketamine) respectively were recorded both before and after anesthesia. The raw EEG signals were preprocessed by EEGLAB 14.0. Functional connectivity (FC) analysis by traditional coherence analysis (CA) method and a novel sparse representation (SR) method. And the network parameters, average clustering coefficient (ACC) and average shortest path length (ASPL) before and after anesthesia were calculated. The results show SR method find more significant FC differences in frontal and occipital cortices, and whole brain network (p<0.05). In contrast, CA can hardly obtain consistent ASPL in the whole brain network (p>0.05). Further, ASPL calculated by SR for whole brain connections in all of three anesthesia groups increased, which can be a unified EEG biomarker of general anesthetics-induced loss of consciousness (LOC). Therefore FC analysis based on SR analysis has better performance in distinguishing anesthetic-induced LOC from awake state.

Midfrontal theta oscillations and conflict monitoring in children and adults

Conflict monitoring is central in cognitive control, as detection of conflict serves as a signal for the need to engage control. This study examined whether (1) midfrontal theta oscillations similarly support conflict monitoring in children and adults, and (2) performance monitoring difficulty influences conflict monitoring and resolution. Children (n = 25) and adults (n = 24) completed a flanker task with fair or rigged response feedback. Relative to adults, children showed a smaller congruency effect on midfrontal theta power, overall lower midfrontal theta power and coherence, and (unlike adults) no correlation between midfrontal theta power and N2 amplitude, suggesting that reduced neural communication efficiency contributes to less efficient conflict monitoring in children than adults. In both age groups, response feedback fairness affected response times and the P3, but neither midfrontal theta oscillations nor the N2, indicating that performance monitoring difficulty influenced conflict resolution but not conflict monitoring.

Cortical network modularity changes along the course of frontotemporal and Alzheimer's dementing diseases

Cortical network modularity underpins cognitive functions, so we hypothesized its progressive derangement along the course of frontotemporal (FTD) and Alzheimer's (AD) dementing diseases. EEG was recorded in 18 FTD, 18 AD, and 20 healthy controls (HC). In the FTD and AD patients, the EEG recordings were performed at the prodromal stage of dementia, at the onset of dementia, and three years after the onset of dementia. HC underwent three EEG recordings at 2-3-year time interval. Information flows underlying EEG activity recorded at electrode pairs were estimated by means of Mutual Information (MI) analysis. The functional organization of the cortical network was modelled by means of the Graph theory analysis on MI adjacency matrices. Graph theory analysis showed that the main hub of HC (Parietal area) was lost in FTD patients at onset of dementia, substituted by provincial hubs in frontal leads. No changes in global network organization were found in AD. Despite a progressive cognitive impairment during the FTD and AD progression, only the FTD patients showed a derangement in the cortical network modularity, possibly due to dysfunctions in frontal functional connectivity.

Learning spatial filters from EEG signals with Graph Signal Processing methods

In this paper, we propose to learn a spatial filter directly from Electroencephalography (EEG) signals using graph signal processing tools. We combine a graph learning algorithm with a high-pass graph filter to remove spatially large signals from the raw data. This approach increases topographical localization, and attenuates volume-conducted features. We empirically show that our method gives similar results that the surface Laplacian in the noiseless case while being more robust to noise or defective electrodes.Clinical relevance- The proposed method is an alternative to the surface Laplacian filter that is commonly used for processing EEG signals. It could be used in cases where this standard approach does not provide satisfying results (low signal-to-noise ratios due to a low number of epochs, defective electrodes). This could be particularly interesting in case of an electrode defect, as it can happen in clinical practice.

The relationship between internalizing problems and acute exercise duration in children with attention-deficit/hyperactivity disorder: The role of frontal alpha asymmetry

BACKGROUND

Frontal alpha asymmetry (FAA) has been associated with the regulation of certain types of internalizing psychopathologies, and is affected by acute aerobic exercise (AE). However, no previous studies have examined the association between FAA and internalizing problems or the effects of acute exercise on FAA in children with ADHD.

AIMS

This study had two objectives. First, it aimed to examine the relationship between FAA and internalizing behaviors in children with ADHD. Second, it sought to investigate the differential effects of acute AE (30 and 50 min) on FAA.

METHOD

Participants were assigned to one of the following three groups: 50 min of AE, 30 min of AE, and a control group. Resting electroencephalogram (EEG) data were recorded before and after their respective treatments. EEG data from 43 participants were analyzed to investigate the association between pre-test FAA and internalizing problems as assessed by Child Behavior Checklist scores. Additionally, EEG data from 46 participants were analyzed to examine the effects of acute AE on post-test FAA while controlling for pre-test FAA.

RESULTS

Pre-test FAA was found to be significantly negatively associated with internalizing problems, with both hemispheres contributing to this association. Regarding the effects of acute exercise, the 50-minute AE group had highest post-test FAA, reflected by the increased relative left-side frontal activity.

CONCLUSIONS

These findings suggest that FAA is a biological marker of internalizing symptoms in children with ADHD, and a 50-minute session of AE can effectively modulate FAA.

Classification of alcoholic EEG signals using wavelet scattering transform-based features

Following the research question and the relevant dataset, feature extraction is the most important component of machine learning and data science pipelines. The wavelet scattering transform (WST) is a recently developed knowledge-based feature extraction technique and is structurally like a convolutional neural network (CNN). It preserves information in high-frequency, is insensitive to signal deformations, and generates low variance features of real-valued signals generally required in classification tasks. With data from a publicly-available UCI database, we investigated the ability of WST-based features extracted from multichannel electroencephalogram (EEG) signals to discriminate 1.0-s EEG records of 20 male subjects with alcoholism and 20 male healthy subjects. Using record-wise 10-fold cross-validation, we found that WST-based features, inputted to a support vector machine (SVM) classifier, were able to correctly classify all alcoholic and normal EEG records. Similar performances were achieved with 1D CNN. In contrast, the highest independent-subject-wise mean 10-fold cross-validation performance was achieved with WST-based features fed to a linear discriminant (LDA) classifier. The results achieved with two 10-fold cross-validation approaches suggest that the WST together with a conventional classifier is an alternative to CNN for classification of alcoholic and normal EEGs. WST-based features from occipital and parietal regions were the most informative at discriminating between alcoholic and normal EEG records.

Cortical mechanisms underlying variability in intermittent theta-burst stimulation-induced plasticity: A TMS-EEG study

OBJECTIVE

To test the hypothesis that intermittent theta burst stimulation (iTBS) variability depends on the ability to engage specific neurons in the primary motor cortex (M1).

METHODS

In a sham-controlled interventional study on 31 healthy volunteers, we used concomitant transcranial magnetic stimulation (TMS) and electroencephalography (EEG). We compared baseline motor evoked potentials (MEPs), M1 iTBS-evoked EEG oscillations, and resting-state EEG (rsEEG) between subjects who did and did not show MEP facilitation following iTBS. We also investigated whether baseline MEP and iTBS-evoked EEG oscillations could explain inter and intraindividual variability in iTBS aftereffects.

RESULTS

The facilitation group had smaller baseline MEPs than the no-facilitation group and showed more iTBS-evoked EEG oscillation synchronization in the alpha and beta frequency bands. Resting-state EEG power was similar between groups and iTBS had a similar non-significant effect on rsEEG in both groups. Baseline MEP amplitude and beta iTBS-evoked EEG oscillation power explained both inter and intraindividual variability in MEP modulation following iTBS.

CONCLUSIONS

The results show that variability in iTBS-associated plasticity depends on baseline corticospinal excitability and on the ability of iTBS to engage M1 beta oscillations.

SIGNIFICANCE

These observations can be used to optimize iTBS investigational and therapeutic applications.

Rhythmic Modulation of Visual Perception by Continuous Rhythmic Auditory Stimulation

At any given moment our sensory systems receive multiple, often rhythmic, inputs from the environment. Processing of temporally structured events in one sensory modality can guide both behavioral and neural processing of events in other sensory modalities, but whether this occurs remains unclear. Here, we used human electroencephalography (EEG) to test the cross-modal influences of a continuous auditory frequency-modulated (FM) sound on visual perception and visual cortical activity. We report systematic fluctuations in perceptual discrimination of brief visual stimuli in line with the phase of the FM-sound. We further show that this rhythmic modulation in visual perception is related to an accompanying rhythmic modulation of neural activity recorded over visual areas. Importantly, in our task, perceptual and neural visual modulations occurred without any abrupt and salient onsets in the energy of the auditory stimulation and without any rhythmic structure in the visual stimulus. As such, the results provide a critical validation for the existence and functional role of cross-modal entrainment and demonstrates its utility for organizing the perception of multisensory stimulation in the natural environment.SIGNIFICANCE STATEMENT Our sensory environment is filled with rhythmic structures that are often multi-sensory in nature. Here, we show that the alignment of neural activity to the phase of an auditory frequency-modulated (FM) sound has cross-modal consequences for vision: yielding systematic fluctuations in perceptual discrimination of brief visual stimuli that are mediated by accompanying rhythmic modulation of neural activity recorded over visual areas. These cross-modal effects on visual neural activity and perception occurred without any abrupt and salient onsets in the energy of the auditory stimulation and without any rhythmic structure in the visual stimulus. The current work shows that continuous auditory fluctuations in the natural environment can provide a pacing signal for neural activity and perception across the senses.

The interplay between domain-general and domain-specific mechanisms during the time-course of verbal associative learning: An event-related potential study

Humans continuously learn new information. Here, we examined the temporal brain dynamics of explicit verbal associative learning between unfamiliar items. In the first experiment, 25 adults learned object-pseudoword associations during a 5-day training program allowing us to track the N400 dynamics across learning blocks within and across days. Successful learning was accompanied by an initial frontal N400 that decreased in amplitude across blocks during the first day and shifted to parietal sites during the last training day. In Experiment 2, we replicated our findings with 38 new participants randomly assigned to a consistent learning or an inconsistent learning group. The N400 amplitude modulations that we found, both within and between learning sessions, are taken to reflect the emergence of novel lexical traces even when learning concerns items for which no semantic information is provided. The shift in N400 topography suggests that different N400 neural generators may contribute to specific word learning steps through a balance between domain-general and language-specific mechanisms.

Tool use and function knowledge shape visual object processing

Perceiving the environment automatically informs how we can interact with it through affordance mechanisms. However, it remains unknown how our knowledge about the environment shapes how it is perceived. In this training study, we evaluated whether motor and function knowledge about novel objects affects visual object processing. Forty-three participants associated a usage or function to a novel object in interactive virtual reality while their EEG was recorded. Both usage and function influenced the mu-band (8-12 Hz) rhythms, suggesting that motor and function object information influence motor processing during object recognition. Learning the usage also prevented the reduction of the theta-band (4-8 Hz) rhythms recorded over the posterior cortical areas, suggesting a predominant top-down influence of tool use information on visuo-motor pathways. The modulation being specifically induced by learning an object usage, the results support further the embodied cognition approach rather than the reasoning-based approach of object processing.