Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction.

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

A comprehensive characterization of cognitive performance, clinical symptoms, and cortical activity following mild traumatic brain injury (mTBI).

OBJECTIVE: The objective of this study was to investigate clinical symptoms, cognitive performance and cortical activity following mild traumatic brain injury (mTBI). METHODS: We recruited 30 individuals in the sub-acute phase post mTBI and 28 healthy controls with no history of head injury and compared these groups on clinical, cognitive and cortical activity measures. Measures of cortical activity included; resting state electroencephalography (EEG), task related EEG and combined transcranial magnetic stimulation with electroencephalography (TMS-EEG). Primary analyses investigated clinical, cognitive and cortical activity differences between groups. Exploratory analyses investigated the relationships between these measures. RESULTS: At 4 weeks' post injury, mTBI participants exhibited significantly greater post concussive and clinical symptoms compared to controls; as well as reduced cognitive performance on verbal learning and working memory measures. mTBI participants demonstrated alterations in cortical activity while at rest and in response to stimulation with TMS. CONCLUSIONS: The present study comprehensively characterized the multidimensional effect of mTBI in the sub-acute phase post injury, showing a broad range of differences compared to non-mTBI participants. Further research is needed to explore the relationship between these pathophysiologies and clinical/cognitive symptoms in mTBI.

EEG microstates in early-to-middle childhood show associations with age, biological sex, and alpha power.

Electroencephalographic (EEG) microstates can provide a unique window into the temporal dynamics of large-scale brain networks across brief (millisecond) timescales. Here, we analysed fundamental temporal features of microstates extracted from the broadband EEG signal in a large (N = 139) cohort of children spanning early-to-middle childhood (4-12 years of age). Linear regression models were used to examine if participants' age and biological sex could predict the temporal parameters GEV, duration, coverage, and occurrence, for five microstate classes (A-E) across both eyes-closed and eyes-open resting-state recordings. We further explored associations between these microstate parameters and posterior alpha power after removal of the 1/f-like aperiodic signal. The microstates obtained from our neurodevelopmental EEG recordings broadly replicated the four canonical microstate classes (A to D) frequently reported in adults, with the addition of the more recently established microstate class E. Biological sex served as a significant predictor in the regression models for four of the five microstate classes (A, C, D, and E). In addition, duration and occurrence for microstate E were both found to be positively associated with age for the eyes-open recordings, while the temporal parameters of microstates C and E both exhibited associations with alpha band spectral power. Together, these findings highlight the influence of age and sex on large-scale functional brain networks during early-to-middle childhood, extending understanding of neural dynamics across this important period for brain development.

Gamma connectivity predicts response to intermittent theta burst stimulation in Alzheimer's disease: a randomized controlled trial.

There is growing evidence that neural network dysfunction is a likely proximate cause of cognitive impairment in Alzheimer's disease and may represent a promising therapeutic target. Here, we investigated whether a course of intermittent theta burst stimulation (iTBS) could modulate functional connectivity and cognition in mild to moderate Alzheimer's. In a double-blind parallel randomized sham-controlled trial, 58 participants were randomized to either active or sham iTBS. Stimulation was applied to the left dorsolateral prefrontal cortex, right dorsolateral prefrontal cortex, left posterior parietal cortex, and right posterior parietal cortex in every treatment session. Neurobiological (electroencephalography), cognitive, and behavioral functional assessments were undertaken at baseline and end of treatment. Cognitive and functional assessments were also conducted at 3 (blinded) and 6 month (active group only) follow-ups. Active iTBS increased resting-state gamma connectivity and improved delayed recall on an episodic memory task. Both baseline gamma connectivity and change in gamma connectivity predicted improved delayed recall following active treatment. These findings support future research into iTBS for Alzheimer's focusing on protocol optimization.

Neurophysiological correlates of non-motor symptoms in late premanifest and early-stage manifest huntington's disease.

OBJECTIVE: To find sensitive neurophysiological correlates of non-motor symptoms in Huntington's disease (HD), which are essential for the development and assessment of novel treatments. METHODS: We used resting state EEG to examine differences in oscillatory activity (analysing the isolated periodic as well as the complete EEG signal) and functional connectivity in 22 late premanifest and early stage people with HD and 20 neurotypical controls. We then assessed the correlations between these neurophysiological markers and clinical measures of apathy and processing speed. RESULTS: Significantly lower theta and greater delta resting state power was seen in the HD group, as well as significantly greater delta connectivity. There was a significant positive correlation between theta power and processing speed, however there were no associations between the neurophysiological and apathy measures. CONCLUSIONS: We speculate that these changes in oscillatory power and connectivity reflect ongoing, frontally concentrated degenerative and compensatory processes associated with HD. SIGNIFICANCE: Our findings support the potential utility of quantitative EEG as a proximate marker of processing speed, but not apathy in HD.

Obsessive-compulsive disorder (OCD) is associated with increased electroencephalographic (EEG) delta and theta oscillatory power but reduced delta connectivity.

Obsessive-Compulsive Disorder (OCD) is a mental health condition causing significant decline in the quality of life of sufferers and the limited knowledge on the pathophysiology hinders successful treatment. The aim of the current study was to examine electroencephalographic (EEG) findings of OCD to broaden our understanding of the disease. Resting-state eyes-closed EEG data was recorded from 25 individuals with OCD and 27 healthy controls (HC). The 1/f arrhythmic activity was removed prior to computing oscillatory powers of all frequency bands (delta, theta, alpha, beta, gamma). Cluster-based permutation was used for between-group statistical analyses, and comparisons were performed for the 1/f slope and intercept parameters. Functional connectivity (FC) was measured using coherence and debiased weighted phase lag index (d-wPLI), and statistically analyzed using the Network Based Statistic method. Compared to HC, the OCD group showed increased oscillatory power in the delta and theta bands in the fronto-temporal and parietal brain regions. However, there were no significant between-group findings in other bands or 1/f parameters. The coherence measure showed significantly reduced FC in the delta band in OCD compared to HC but the d-wPLI analysis showed no significant differences. OCD is associated with raised oscillatory power in slow frequency bands in the fronto-temporal brain regions, which agrees with the previous literature and therefore is a potential biomarker. Although delta coherence was found to be lower in OCD, due to inconsistencies found between measures and the previous literature, further research is required to ascertain definitive conclusions.

Recovery of clinical, cognitive and cortical activity measures following mild traumatic brain injury (mTBI): A longitudinal investigation.

The mechanisms that underpin recovery following mild traumatic brain injury (mTBI) remain poorly understood. Identifying neurophysiological markers and their functional significance is necessary to develop diagnostic and prognostic indicators of recovery. The current study assessed 30 participants in the subacute phase of mTBI (10-31 days post-injury) and 28 demographically matched controls. Participants also completed 3 month (mTBI: N = 21, control: N = 25) and 6 month (mTBI: N = 15, control: N = 25) follow up sessions to track recovery. At each time point, a battery of clinical, cognitive, and neurophysiological assessments was completed. Neurophysiological measures included resting-state electroencephalography (EEG) and transcranial magnetic stimulation combined with EEG (TMS-EEG). Outcome measures were analysed using mixed linear models (MLM). Group differences in mood, post-concussion symptoms and resting-state EEG resolved by 3 months, and recovery was maintained at 6 months. On TMS-EEG derived neurophysiological measures of cortical reactivity, group differences ameliorated at 3 months but re-emerged at 6 months, while on measures of fatigue, group differences persisted across all time points. Persistent neurophysiological changes and greater fatigue in the absence of measurable cognitive impairment may suggest the impact of mTBI on neuronal communication may leads to increased neural effort to maintain efficient function. Neurophysiological measures to track recovery may help identify both temporally optimal windows and therapeutic targets for the development of new treatments in mTBI.

Obsessive-compulsive disorder (OCD) is associated with increased engagement of frontal brain regions across multiple event-related potentials.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a psychiatric condition leading to significant distress and poor quality of life. Successful treatment of OCD is restricted by the limited knowledge about its pathophysiology. This study aimed to investigate the pathophysiology of OCD using electroencephalographic (EEG) event-related potentials (ERPs), elicited from multiple tasks to characterise disorder-related differences in underlying brain activity across multiple neural processes. METHODS: ERP data were obtained from 25 OCD patients and 27 age- and sex-matched healthy controls (HCs) by recording EEG during flanker and go/nogo tasks. Error-related negativity (ERN) was elicited by the flanker task, while N200 and P300 were generated using the go/nogo task. Primary comparisons of the neural response amplitudes and the topographical distribution of neural activity were conducted using scalp field differences across all time points and electrodes. RESULTS: Compared to HCs, the OCD group showed altered ERP distributions. Contrasting with the previous literature on ERN and N200 topographies in OCD where fronto-central negative voltages were reported, we detected positive voltages. Additionally, the P300 was found to be less negative in the frontal regions. None of these ERP findings were associated with OCD symptom severity. CONCLUSIONS: These results indicate that individuals with OCD show altered frontal neural activity across multiple executive function-related processes, supporting the frontal dysfunction theory of OCD. Furthermore, due to the lack of association between altered ERPs and OCD symptom severity, they may be considered potential candidate endophenotypes for OCD.

Medial prefrontal transcranial alternating current stimulation for apathy in Huntington's disease.

We investigated the effects of transcranial alternating current stimulation (tACS) targeted to the bilateral medial prefrontal cortex (mPFC) and administered at either delta or alpha frequencies, on brain activity and apathy in people with Huntington's disease (HD) (n = 17). Given the novelty of the protocol, neurotypical controls (n = 20) were also recruited. All participants underwent three 20-min sessions of tACS; one session at alpha frequency (Individualised Alpha Frequency (IAF), or 10 Hz when an IAF was not detected); one session at delta frequency (2 Hz); and a session of sham tACS. Participants completed the Monetary Incentive Delay (MID) task with simultaneous recording of EEG immediately before and after each tACS condition. The MID task presents participants with cues signalling potential monetary gains or losses that increase activity in key regions of the cortico-basal ganglia-thalamocortical networks, with dysfunction of the latter network being implicated in the pathophysiology of apathy. We used the P300 and Contingent Negative Variation (CNV) event-related potentials elicited during the MID task as markers of mPFC engagement. HD participants' CNV amplitude significantly increased in response to alpha-tACS, but not delta-tACS or sham. Neurotypical controls' P300 and CNV were not modulated by any of the tACS conditions, but they did demonstrate a significant decrease in post-target response times following alpha-tACS. We present this as preliminary evidence of the ability of alpha-tACS to modulate brain activity associated with apathy in HD.

Effects of medial prefrontal transcranial alternating current stimulation on neural activity and connectivity in people with Huntington's disease and neurotypical controls.

We investigated the effects of transcranial alternating current stimulation (tACS) targeted to the medial prefrontal cortex (mPFC) on resting electroencephalographic (EEG) indices of oscillatory power, aperiodic exponent and offset, and functional connectivity in 22 late premanifest and early manifest stage individuals with HD and 20 neurotypical controls. Participants underwent three 20-minute sessions of tACS at least 72 hours apart; one session at alpha frequency (either each participant's Individualised Alpha Frequency (IAF), or 10 Hz when an IAF was not detected); one session at delta frequency (2 Hz); and a session of sham tACS. Session order was randomised and counterbalanced across participants. EEG recordings revealed a reduction of the spectral exponent ('flattening' of the 1/f slope) of the eyes-open aperiodic signal in participants with HD following alpha-tACS, suggestive of an enhancement in excitatory tone. Contrary to expectation, there were no changes in oscillatory power or functional connectivity in response to any of the tACS conditions in the participants with HD. By contrast, alpha-tACS increased delta power in neurotypical controls, who further demonstrated significant increases in theta power and theta functional connectivity in response to delta-tACS. This study contributes to the rapidly growing literature on the potential experimental and therapeutic applications of tACS by examining neurophysiological outcome measures in people with HD as well as neurotypical controls.

Alterations in EEG functional connectivity in individuals with depression: A systematic review.

The brain works as an organised, network-like structure of functionally interconnected regions. Disruptions to interconnectivity in certain networks have been linked to symptoms of depression and impairments in cognition. Electroencephalography (EEG) is a low-burden tool by which differences in functional connectivity (FC) can be assessed. This systematic review aims to provide a synthesis of evidence relating to EEG FC in depression. A comprehensive electronic literature search for terms relating to depression, EEG, and FC was conducted on studies published before the end of November 2021, according to PRISMA guidelines. Studies comparing EEG measures of FC of individuals with depression to that of healthy control groups were included. Data was extracted by two independent reviewers, and the quality of EEG FC methods was assessed. Fifty-two studies assessing EEG FC in depression were identified: 36 assessed resting-state FC, and 16 assessed task-related or other (i.e., sleep) FC. Somewhat consistent findings in resting-state studies suggest for no differences between depression and control groups in EEG FC in the delta and gamma frequencies. However, while most resting-state studies noted a difference in alpha, theta, and beta, no clear conclusions could be drawn about the direction of the difference, due to considerable inconsistencies between study design and methodology. This was also true for task-related and other EEG FC. More robust research is needed to understand the true differences in EEG FC in depression. Given that the FC between brain regions drives behaviour, cognition, and emotion, characterising how FC differs in depression is essential for understanding the aetiology of depression.

Investigation of neurobiological responses to theta burst stimulation during recovery from mild traumatic brain injury (mTBI).

OBJECTIVE: The ability of the brain to recover following neurological insult is of interest for mild traumatic brain injury (mTBI) populations. Investigating whether non-invasive brain stimulation (NIBS) can modulate neurophysiology and cognition may lead to the development of therapeutic interventions post injury. The purpose of this study was to investigate neurobiological effects of one session of intermittent theta burst stimulation (iTBS) to the dorsolateral prefrontal cortex (DLPFC) in participants recovering from mTBI. METHOD: Changes to neurophysiology were assessed with electroencephalography (EEG) and transcranial magnetic stimulation combined with EEG (TMS-EEG). Digit span working memory accuracy assessed cognitive performance. 30 patients were assessed within one-month of sustaining a mTBI and 26 demographically matched controls were assessed. Participants were also assessed at 3-months (mTBI: N = 21, control: N = 26) and 6-months (mTBI: N = 15, control: N = 24). RESULTS: Analyses demonstrated iTBS did not reliably modulate neurophysiological activity, and no differences in cognitive performance were produced by iTBS at any assessment time-point. CONCLUSIONS: Factors responsible for our null results are unclear. Possible limitations to our experimental design are discussed. SIGNIFICANCE: Our findings suggest additional research is required to establish the effects of iTBS on plasticity following mTBI, prior to therapeutic application. DATA AND CODE AVAILABILITY STATEMENT: We do not have ethical approval to make this data publicly available, as our approval predated our inclusion of such approvals (which we now do routinely).

Electroencephalographic Connectivity: A Fundamental Guide and Checklist for Optimal Study Design and Evaluation.

Brain connectivity can be estimated through many analyses applied to electroencephalography (EEG) data. However, substantial heterogeneity in the implementation of connectivity methods exists. Heterogeneity in conceptualization of connectivity measures, data collection, or data preprocessing may be associated with variability in robustness of measurement. While it is difficult to compare the results of studies using different EEG connectivity measures, standardization of processing and reporting may facilitate the task. We discuss how factors such as referencing, epoch length and number, controls for volume conduction, artifact removal, and statistical control of multiple comparisons influence the EEG connectivity estimate for connectivity measures, and what can be done to control for potential confounds associated with these factors. Based on the results reported in previous literature, this article presents recommendations and a novel checklist developed for quality assessment of EEG connectivity studies. This checklist and its recommendations are made in an effort to draw attention to factors that may influence connectivity estimates and factors that need to be improved in future research. Standardization of procedures and reporting in EEG connectivity may lead to EEG connectivity studies being made more synthesizable and comparable despite variations in the methodology underlying connectivity estimates.

Investigating Neurophysiological Markers of Symptom Severity in Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is characterized by a progressive decline in cognitive functioning for which there is a stark lack of effective treatments. Investigating the neurophysiological markers of symptom severity in AD may aid in the identification of alternative treatment targets. OBJECTIVE: In the current study we used a multimodal approach to investigate the association between functional connectivity (specifically between scalp electrodes placed over frontal and parietal regions) and symptom severity in AD, and to explore the relationship between connectivity and cortical excitability. METHODS: 40 people with AD (25 mild severity, 15 moderate severity) underwent neurobiological assessment (resting state electroencephalography (EEG) and prefrontal transcranial magnetic stimulation (TMS) with EEG) and cognitive assessment. Neurobiological outcomes were resting state functional connectivity and TMS-evoked potentials. Cognitive outcomes were scores on the Alzheimer's Disease Assessment Scale-Cognitive Subscale, Mini-Mental Status Examination, and a measure of episodic verbal learning. RESULTS: Greater contralateral functional theta connectivity between frontal scalp electrodes and parietal scalp electrodes was associated with poorer cognitive performance. In addition, significant correlations were seen between the contralateral theta connectivity and the N100 and P60 TMS-evoked potentials measured from electrodes over the left dorsolateral prefrontal cortex. CONCLUSION: Together these findings provide initial support for the use of multimodal neurophysiological approaches to investigate potential therapeutic targets in AD. Suggestions for future research are discussed.

Investigating neurophysiological markers of impaired cognition in schizophrenia.

Cognitive impairment is highly prevalent in schizophrenia and treatment options are severely limited. A greater understanding of the pathophysiology of impaired cognition would have broad implications, including for the development of effective treatments. In the current study we used a multimodal approach to identify neurophysiological markers of cognitive impairment in schizophrenia. Fifty-seven participants (30 schizophrenia, 27 controls) underwent neurobiological assessment (electroencephalography [EEG] and Transcranial Magnetic Stimulation combined with EEG [TMS-EEG]) and assessment of cognitive functioning using an n-back task and the MATRICS Consensus Cognitive Battery. Neurobiological outcome measures included oscillatory power during a 2-back task, TMS-related oscillations and TMS-evoked potentials (TEPs). Cognitive outcome measures were d prime and accurate reaction time on the 2-back and MATRICS domain scores. Compared to healthy controls, participants with schizophrenia showed significantly reduced theta oscillations in response to TMS, and trend level decreases in task-related theta and cortical reactivity (i.e. reduced N100 and N40 TEPs). Participants with schizophrenia also showed significantly impaired cognitive performance across all measures. Correlational analysis identified significant associations between cortical reactivity and TMS-related oscillations in both groups; and trend level associations between task-related oscillations and impaired cognition in schizophrenia. The current study provides experimental support for possible neurophysiological markers of cognitive impairment in schizophrenia. The potential implications of these findings, including for treatment development, are discussed.

Repetitive Transcranial Magnetic Stimulation for Obsessive-Compulsive Disorder: A Meta-analysis of Randomized, Sham-Controlled Trials.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a chronic, disabling mental health condition with limited treatment options available to date. Numerous randomized controlled trials have explored the efficacy of repetitive transcranial magnetic stimulation (rTMS) in OCD. This meta-analysis synthesized data from selected randomized controlled trials and examined the impact of different treatment parameters to generate hypotheses that would direct future randomized controlled trials. METHODS: A database search was performed to identify studies published in English up to October 2020. Randomized, sham-controlled studies that used rTMS to treat OCD were included. Effect sizes were calculated using Hedges' g for pre- to post-treatment Yale-Brown Obsessive Compulsive Scale scores. Subgroup analyses were conducted to assess the effects of variations in rTMS treatment parameters. RESULTS: A total of 26 studies with 781 participants were included. Overall, rTMS demonstrated a modest effect on reduction of Yale-Brown Obsessive Compulsive Scale scores (Hedges' g = 0.64, 95% confidence interval = 0.39-0.89; p < .0001). The largest significant effect size was obtained by targeting the bilateral dorsolateral prefrontal cortex. High- and low-frequency rTMS showed comparable effects. Studies with follow-up data suggested that the effects of active rTMS remain significantly superior to those of sham 4 weeks after treatment. CONCLUSIONS: The therapeutic effects of rTMS are superior to those of sham in the treatment of OCD. Targeting the bilateral dorsolateral prefrontal cortex was the most favorable approach in administering rTMS. Further research is required to determine the optimal frequency, total pulses per session, and duration of treatment with rTMS for OCD.

Resting EEG theta connectivity and alpha power to predict repetitive transcranial magnetic stimulation response in depression: A non-replication from the ICON-DB consortium.

OBJECTIVE: Our previous research showed high predictive accuracy at differentiating responders from non-responders to repetitive transcranial magnetic stimulation (rTMS) for depression using resting electroencephalography (EEG) and clinical data from baseline and one-week following treatment onset using a machine learning algorithm. In particular, theta (4-8 Hz) connectivity and alpha power (8-13 Hz) significantly differed between responders and non-responders. Independent replication is a necessary step before the application of potential predictors in clinical practice. This study attempted to replicate the results in an independent dataset. METHODS: We submitted baseline resting EEG data from an independent sample of participants who underwent rTMS treatment for depression (N = 193, 128 responders) (Krepel et al., 2018) to the same between group comparisons as our previous research (Bailey et al., 2019). RESULTS: Our previous results were not replicated, with no difference between responders and non-responders in theta connectivity (p = 0.250, Cohen's d = 0.1786) nor alpha power (p = 0.357, ηp2 = 0.005). CONCLUSIONS: These results suggest that baseline resting EEG theta connectivity or alpha power are unlikely to be generalisable predictors of response to rTMS treatment for depression. SIGNIFICANCE: These results highlight the importance of independent replication, data sharing and using large datasets in the prediction of response research.

Individual alpha frequency proximity associated with repetitive transcranial magnetic stimulation outcome: An independent replication study from the ICON-DB consortium.

OBJECTIVE: The aim of the current study was to attempt to replicate the finding that the individual alpha frequency (IAF) as well as the absolute difference between IAF and 10 Hz stimulation frequency (IAF-prox) is related to treatment outcome. METHODS: Correlations were performed to investigate the relationship between IAF-prox and percentage symptom improvement in a sample of 153 patients with major depressive disorder treated with 10 Hz (N = 59) to the left dorsolateral prefrontal cortex (DLPFC) or 1 Hz (N = 94) to the right DLPFC repetitive Transcranial Magnetic Stimulation (rTMS). RESULTS: There was a significant negative correlation between IAF-prox and the percentage of symptom improvement only for the 10 Hz group. Curve fitting models revealed that there was a quadratic association between IAF and treatment response in the 10 Hz group, with a peak at 10 Hz IAF. CONCLUSION: The main result of Corlier and colleagues was replicated, and the findings suggest that the distance between 10 Hz stimulation frequency and the IAF may influence clinical outcome in a non-linear manner. SIGNIFICANCE: rTMS is often administered at a frequency of 10 Hz, which is the center of the EEG alpha frequency band. The results can make a significant contribution to optimizing the clinical application of rTMS.

Mindfulness meditation alters neural activity underpinning working memory during tactile distraction.

Evidence suggests that mindfulness meditation (MM) improves selective attention and reduces distractibility by enhancing top-down neural modulation. Altered P300 and alpha neural activity from MM have been identified and may reflect the neural changes that underpin these improvements. Given the proposed role of alpha activity in supressing processing of task-irrelevant information, it is theorised that altered alpha activity may underlie increased availability of neural resources in meditators. The present study investigated attentional function in meditators using a cross-modal study design, examining the P300 during working memory (WM) and alpha activity during concurrent distracting tactile stimuli. Thirty-three meditators and 27 healthy controls participated in the study. Meditators showed a more frontal distribution of P300 neural activity following WM stimuli (p = 0.005, η2 = 0.060) and more modulation of alpha activity at parietal-occipital regions between single (tactile stimulation only) and dual task demands (tactile stimulation plus WM task) (p < 0.001, η2 = 0.065). Additionally, meditators performed more accurately than controls (p = 0.038, η2 = 0.067). The altered distribution of neural activity concurrent with improved WM performance suggests greater attentional resources dedicated to task related functions, such as WM in meditators. Thus, meditation-related neural changes are likely multifaceted, involving both altered distribution and also amplitudes of brain activity, thereby enhancing attentional processes depending on task requirements.