Dopaminergic hypo-activity and reduced theta-band power in autism spectrum disorder: A resting-state EEG study

Clinical and neuropsychological correlates of theta-band functional excitation-inhibition ratio in autism: An EEG study

OBJECTIVE

How abnormal brain signaling impacts cognition in autism spectrum disorder (ASD) remained elusive. This study aimed to investigate the local and global brain signaling in ASD indicated by theta-band functional excitation-inhibition (fE/I) ratio and explored psychophysiological relationships between fE/I, cognitive deficits, and ASD symptomatology.

METHODS

A total of 83 ASD and typically developing (TD) individuals participated in this study. Participants' interference control and set-shifting abilities were assessed. Resting-state electroencephalography (EEG) was used for estimating theta-band fE/I ratio.

RESULTS

ASD individuals (n = 31 without visual EEG abnormality; n = 22 with visual EEG abnormality) generally performed slower in a cognitive task tapping interference control and set-maintenance abilities, but only ASD individuals with visually abnormal EEG performed significantly slower than their TD counterparts (Bonferroni-corrected ps < .001). Heightened theta-band fE/I ratios at the whole-head level, left and right hemispheres were observed in the ASD subgroup without visual EEG abnormality only (Bonferroni-corrected ps < .001), which remained highly significant when only data from medication-naïve participants were analyzed. In addition, higher left hemispheric fE/I ratios in ASD individuals without visual EEG abnormality were significantly correlated with faster interference control task performance, in turn faster reaction time was significantly associated with less severe restricted, repetitive behavior (Bonferroni-corrected ps ≤ .0017).

CONCLUSIONS

Differential theta-band fE/I within the ASD population. Heightened theta-band fE/I in ASD without visual EEG abnormality may be associated with more efficient filtering of distractors and a less severe ASD symptom manifestation.

SIGNIFICANCE

Brain signaling, indicated by theta-band fE/I, was different in ASD subgroups. Only ASD with visually-normal EEG showed heightened theta-band fE/I, which was associated with faster processing of visual distractors during a cognitive task. More efficient distractor filtering was associated with less restricted, repetitive behaviors.

Resting-state EEG power differences in autism spectrum disorder: a systematic review and meta-analysis

Narrative reviews have described various resting-state EEG power differences in autism across all five canonical frequency bands, with increased power for low and high frequencies and reduced power for middle frequencies. However, these differences have yet to be quantified using effect sizes and probed robustly for consistency, which are critical next steps for clinical translation. Following PRISMA guidelines, we conducted a systematic review of published and gray literature on resting-state EEG power in autism. We performed 10 meta-analyses to synthesize and quantify differences in absolute and relative resting-state delta, theta, alpha, beta, and gamma EEG power in autism. We also conducted moderator analyses to determine whether demographic characteristics, methodological details, and risk-of-bias indicators might account for heterogeneous study effect sizes. Our literature search and study selection processes yielded 41 studies involving 1,246 autistic and 1,455 neurotypical individuals. Meta-analytic models of 135 effect sizes demonstrated that autistic individuals exhibited reduced relative alpha (g = -0.35) and increased gamma (absolute: g = 0.37, relative: g = 1.06) power, but similar delta (absolute: g = 0.06, relative: g = 0.10), theta (absolute: g = -0.03, relative: g = -0.15), absolute alpha (g = -0.17), and beta (absolute: g = 0.01, relative: g = 0.08) power. Substantial heterogeneity in effect sizes was observed across all absolute (I2: 36.1-81.9%) and relative (I2: 64.6-84.4%) frequency bands. Moderator analyses revealed that age, biological sex, IQ, referencing scheme, epoch duration, and use of gold-standard autism diagnostic instruments did not moderate study effect sizes. In contrast, resting-state paradigm type (eyes-closed versus eyes-open) moderated absolute beta, relative delta, and relative alpha power effect sizes, and resting-state recording duration moderated relative alpha power effect sizes. These findings support further investigation of resting-state alpha and gamma power as potential biomarkers for autism.

Effects of multisession cathodal transcranial direct current stimulation with cognitive training on sociocognitive functioning and brain dynamics in autism: A double-blind, sham-controlled, randomized EEG study

BACKGROUND

Few treatment options are available for targeting core symptoms of autism spectrum disorder (ASD). The development of treatments that target common neural circuit dysfunctions caused by known genetic defects, namely, disruption of the excitation/inhibition (E/I) balance, is promising. Transcranial direct current stimulation (tDCS) is capable of modulating the E/I balance in healthy individuals, yet its clinical and neurobiological effects in ASD remain elusive.

OBJECTIVE

This double-blind, randomized, sham-controlled trial investigated the effects of multisession cathodal prefrontal tDCS coupled with online cognitive remediation on social functioning, information processing efficiency and the E/I balance in ASD patients aged 14-21 years.

METHODS

Sixty individuals were randomly assigned to receive either active or sham tDCS (10 sessions in total, 20 min/session, stimulation intensity: 1.5 mA, cathode: F3, anode: Fp2, size of electrodes: 25 cm2) combined with 20 min of online cognitive remediation. Social functioning, information processing efficiency during cognitive tasks, and theta- and gamma-band E/I balance were measured one day before and after the treatment.

RESULTS

Compared to sham tDCS, active cathodal tDCS was effective in enhancing overall social functioning [F(1, 58) = 6.79, p = .012, ηp2 = 0.105, 90% CI: (0.013, 0.234)] and information processing efficiency during cognitive tasks [F(1, 58) = 10.07, p = .002, ηp2 = 0.148, 90% CI: (0.034, 0.284)] in these individuals. Electroencephalography data showed that this cathodal tDCS protocol was effective in reducing the theta-band E/I ratio of the cortical midline structures [F(1, 58) = 4.65, p = .035, ηp2 = 0.074, 90% CI: (0.010, 0.150)] and that this reduction significantly predicted information processing efficiency enhancement (b = -2.546, 95% BCa CI: [-4.979, -0.113], p = .041).

CONCLUSION

Our results support the use of multisession cathodal tDCS over the left dorsolateral prefrontal cortex combined with online cognitive remediation for reducing the elevated theta-band E/I ratio in sociocognitive information processing circuits in ASD patients, resulting in more adaptive regulation of global brain dynamics that is associated with enhanced information processing efficiency after the intervention.

Look into my eyes: What can eye-based measures tell us about the relationship between physical activity and cognitive performance?

BACKGROUND

There is a growing interest to understand the neurobiological mechanisms that drive the positive associations of physical activity and fitness with measures of cognitive performance. To better understand those mechanisms, several studies have employed eye-based measures (e.g., eye movement measures such as saccades, pupillary measures such as pupil dilation, and vascular measures such as retinal vessel diameter) deemed to be proxies for specific neurobiological mechanisms. However, there is currently no systematic review providing a comprehensive overview of these studies in the field of exercise-cognition science. Thus, this review aimed to address that gap in the literature.

METHODS

To identify eligible studies, we searched 5 electronic databases on October 23, 2022. Two researchers independently extracted data and assessed the risk of bias using a modified version of the Tool for the assEssment of Study qualiTy and reporting in EXercise (TESTEX scale, for interventional studies) and the critical appraisal tool from the Joanna Briggs Institute (for cross-sectional studies).

RESULTS

Our systematic review (n = 35 studies) offers the following main findings: (a) there is insufficient evidence available to draw solid conclusions concerning gaze-fixation-based measures; (b) the evidence that pupillometric measures, which are a proxy for the noradrenergic system, can explain the positive effect of acute exercise and cardiorespiratory fitness on cognitive performance is mixed; (c) physical training- or fitness-related changes of the cerebrovascular system (operationalized via changes in retinal vasculature) are, in general, positively associated with cognitive performance improvements; (d) acute and chronic physical exercises show a positive effect based on an oculomotor-based measure of executive function (operationalized via antisaccade tasks); and (e) the positive association between cardiorespiratory fitness and cognitive performance is partly mediated by the dopaminergic system (operationalized via spontaneous eye-blink rate).

CONCLUSION

This systematic review offers confirmation that eye-based measures can provide valuable insight into the neurobiological mechanisms that may drive positive associations between physical activity and fitness and measures of cognitive performance. However, due to the limited number of studies utilizing specific methods for obtaining eye-based measures (e.g., pupillometry, retinal vessel analysis, spontaneous eye blink rate) or investigating a possible dose-response relationship, further research is necessary before more nuanced conclusions can be drawn. Given that eye-based measures are economical and non-invasive, we hope this review will foster the future application of eye-based measures in the field of exercise-cognition science.

Blink rate and facial orientation reveal distinctive patterns of attentional engagement in autistic toddlers: a digital phenotyping approach

Differences in social attention are well-documented in autistic individuals, representing one of the earliest signs of autism. Spontaneous blink rate has been used to index attentional engagement, with lower blink rates reflecting increased engagement. We evaluated novel methods using computer vision analysis (CVA) for automatically quantifying patterns of attentional engagement in young autistic children, based on facial orientation and blink rate, which were captured via mobile devices. Participants were 474 children (17-36 months old), 43 of whom were diagnosed with autism. Movies containing social or nonsocial content were presented via an iPad app, and simultaneously, the device's camera recorded the children's behavior while they watched the movies. CVA was used to extract the duration of time the child oriented towards the screen and their blink rate as indices of attentional engagement. Overall, autistic children spent less time facing the screen and had a higher mean blink rate compared to neurotypical children. Neurotypical children faced the screen more often and blinked at a lower rate during the social movies compared to the nonsocial movies. In contrast, autistic children faced the screen less often during social movies than during nonsocial movies and showed no differential blink rate to social versus nonsocial movies.

Neuropsychiatric feature-based subgrouping reveals neural sensory processing spectrum in female FMR1 premutation carriers: A pilot study

Introduction

Fragile X Syndrome (FXS) is rare genetic condition characterized by a repeat expansion (CGG) in the Fragile X messenger ribonucleoprotein 1 (FMR1) gene where individuals with greater than 200 repeats are defined as full mutation. FXS clinical presentation often includes intellectual disability, and autism-like symptoms, including anxiety and sensory hypersensitivities. Individuals with 55 to <200 CGG repeats are said to have the FMR1 premutation, which is not associated with primary characteristics of the full mutation, but with an increased risk for anxiety, depression, and other affective conditions, as well as and impaired cognitive processing differences that vary in severity. Defining subgroups of premutation carriers based on distinct biological features may identify subgroups with varying levels of psychiatric, cognitive, and behavioral alterations.

Methods

The current pilot study utilized 3 cluster subgroupings defined by previous k means cluster analysis on neuropsychiatric, cognitive, and resting EEG variables in order to examine basic sensory auditory chirp task-based EEG parameters from 33 females with the FMR1 premutation (ages 17-78).

Results

Based on the predefined, neuropsychiatric three-cluster solution, premutation carriers with increased neuropsychiatric features and higher CGG repeat counts (cluster 1) showed decreased stimulus onset response, similar to previous ERP findings across a number of psychiatric disorders but opposite to findings in individuals with full mutation FXS. Premutation carriers with increased executive dysfunction and resting gamma power (cluster 2) exhibited decreased gamma phase locking to a chirp stimulus, similar to individuals with full mutation FXS. Cluster 3 members, who were relatively unaffected by psychiatric or cognitive symptoms, showed the most normative task-based EEG metrics.

Discussion

Our findings suggest a spectrum of sensory processing characteristics present in subgroups of premutation carriers that have been previously understudied due to lack of overall group differences. Our findings also further validate the pre-defined clinical subgroups by supporting links between disturbances in well-defined neural pathways and behavioral alterations that may be informative for identifying the mechanisms supporting specific risk factors and divergent therapeutic needs in individuals with the FMR1 premutation.

fMRI BOLD and MEG theta power reflect complementary aspects of activity during lexicosemantic decision in adolescents with ASD

Neuroimaging studies of autism spectrum disorder (ASD) have been predominantly unimodal. While many fMRI studies have reported atypical activity patterns for diverse tasks, the MEG literature in ASD remains comparatively small. Our group recently reported atypically increased event-related theta power in individuals with ASD during lexicosemantic processing. The current multimodal study examined the relationship between fMRI BOLD signal and anatomically-constrained MEG (aMEG) theta power. Thirty-three adolescents with ASD and 23 typically developing (TD) peers took part in both fMRI and MEG scans, during which they distinguished between standard words (SW), animal words (AW), and pseudowords (PW). Regions-of-interest (ROIs) were derived based on task effects detected in BOLD signal and aMEG theta power. BOLD signal and theta power were extracted for each ROI and word condition. Compared to TD participants, increased theta power in the ASD group was found across several time windows and regions including left fusiform and inferior frontal, as well as right angular and anterior cingulate gyri, whereas BOLD signal was significantly increased in the ASD group only in right anterior cingulate gyrus. No significant correlations were observed between BOLD signal and theta power. Findings suggest that the common interpretation of increases in BOLD signal and theta power as 'activation' require careful differentiation, as these reflect largely distinct aspects of regional brain activity. Some group differences in dynamic neural processing detected with aMEG that are likely relevant for lexical processing may be obscured by the hemodynamic signal source and low temporal resolution of fMRI.

Intellectually able adults with autism spectrum disorder show typical resting-state EEG activity

There is broad interest in discovering quantifiable physiological biomarkers for psychiatric disorders to aid diagnostic assessment. However, finding biomarkers for autism spectrum disorder (ASD) has proven particularly difficult, partly due to high heterogeneity. Here, we recorded five minutes eyes-closed rest electroencephalography (EEG) from 186 adults (51% with ASD and 49% without ASD) and investigated the potential of EEG biomarkers to classify ASD using three conventional machine learning models with two-layer cross-validation. Comprehensive characterization of spectral, temporal and spatial dimensions of source-modelled EEG resulted in 3443 biomarkers per recording. We found no significant group-mean or group-variance differences for any of the EEG features. Interestingly, we obtained validation accuracies above 80%; however, the best machine learning model merely distinguished ASD from the non-autistic comparison group with a mean balanced test accuracy of 56% on the entirely unseen test set. The large drop in model performance between validation and testing, stress the importance of rigorous model evaluation, and further highlights the high heterogeneity in ASD. Overall, the lack of significant differences and weak classification indicates that, at the group level, intellectually able adults with ASD show remarkably typical resting-state EEG.

A new feature selection approach for driving fatigue EEG detection with a modified machine learning algorithm

This study aims to identify new electroencephalography (EEG) features for the detection of driving fatigue. The most common EEG feature in driving fatigue detection is the power spectral density (PSD) of five frequency bands, i.e., alpha, beta, gamma, delta, and theta bands. PSD has proved to be useful, however its flaw is that it covers much implicit information of the time domain. In this study we propose a new approach, which combines ensemble empirical mode decomposition (EEMD) and PSD, to explore new EEG features for driving fatigue detection. Through EEMD we get a series of intrinsic mode function (IMF) components, from which we can extract PSD features. We used six features to compare with the proposed features, including the PSD of five frequency bands, PSD of empirical mode decomposition (EMD)-IMF components, PSD, permutation entropy (PE), sample entropy (SE), and fuzzy entropy (FE) of EEMD-IMF components, and common spatial pattern. Feature overlap ratio and multiple machine learning methods were applied to evaluate these feature extraction approaches. The results show that the classification accuracy and overlap ratio of experiments based on IMF's energy spectrum is far superior to other features. Through channel optimization and a comparison of accuracy, we conclude that our new feature selection approach has a better performance based on the modified hierarchical extreme learning machine algorithm with Particle Swarm Optimization (PSO-H-ELM) classifier, which has the highest average accuracy of 97.53%.

Right Anterior Theta Hypersynchrony as a Quantitative Measure Associated with Autistic Traits and K-Cl Cotransporter KCC2 Polymorphism

Our aim was to use theta coherence as a quantitative trait to investigate the relation of the polymorphisms in NKCC1 (rs3087889) and KCC2 (rs9074) channel protein genes to autistic traits (AQ) in neurotypicals. Coherence values for candidate connection regions were calculated from eyes-closed resting EEGs in two independent groups. Hypersynchrony within the right anterior region was related to AQ in both groups (p < 0.05), and variability in this hypersynchrony was related to the rs9074 polymorphism in the total group (p < 0.05). In conclusion, theta hypersynchrony within the right anterior region during eyes-closed rest can be considered a quantitative measure for autistic traits. Replicating our findings in two independent populations with different backgrounds strengthens the validity of the current study.

The effects of monophasic anodal transcranial pulsed current stimulation on corticospinal excitability and motor performance in healthy young adults: A randomized double-blind sham-controlled study

INTRODUCTION

Transcranial pulsed current stimulation (tPCS) could be used to deliver electrical pulses at different frequencies to entrain the cortical neurons of the brain. Frequency dependence of these pulses in the induction of changes in corticospinal excitability (CSE) has not been reported.

OBJECTIVE

We aimed to assess the effect of anodal tPCS (a-tPCS) at theta (4 Hz), and gamma (75 Hz) frequencies on CSE as assessed by the peak-to-peak amplitude of transcranial magnetic stimulation (TMS) induced motor evoked potentials (MEPs) and motor performance.

METHOD

In a randomized double-blinded sham-controlled cross over design study, seventeen healthy participants attended three experimental sessions and received either a-tPCS at 4 Hz, 75 Hz, or sham a-tPCS with 1.5 mA for 15 min. The amplitude of TMS induced resting MEPs and time for completion of the grooved pegboard test were recorded at baseline, immediately after, and 30-min after a-tPCS.

RESULTS

Both a-tPCS at 75 Hz and 4 Hz showed significantly increased CSE compared to sham. The a-tPCS at 75 Hz induced significantly higher CSE changes compared to 4 Hz. There was a significant increase in intracortical facilitation and a significant reduction in short-interval intra-cortical inhibition with both 4 and 75 Hz stimulation. However, the inhibition and facilitation did not correlate with CSE. Motor performance was unaffected by the interventions.

CONCLUSION

The high CSE changes in M1 in a-tPCS at 75 Hz provides an initial understanding of the frequency-specific effect of a-tPCS. More research is needed to establish this concept and to assess its behavioural relevance.

Subjective and Electroencephalographic Sleep Parameters in Children and Adolescents with Autism Spectrum Disorder: A Systematic Review

Background: Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical and etiological components. These disorders are associated with functional impairment, and provoke significant physical and mental affliction. The purpose of this study is to update the existing literature about objective and subjective sleep parameters in children and adolescents with ASD, extrapolating information from polysomnography or sleep electroencephalography, and sleep related questionnaires. Methods: We have conducted a systematic review of case-control studies on this topic, performing a web-based search on PubMed, Scopus and the Web of Science databases according to the Preferred Reporting items for Systematic Review and Meta-analyses (PRISMA) guidelines. Results: Data collected from 20 survey result reports showed that children and adolescents with ASD experienced a higher rate of sleep abnormalities than in typically developing children. The macrostructural sleep parameters that were consistent with subjective parent reported measures unveil a greater percentage of nighttime signs of insomnia. Sleep microstructure patterns, in addition, pointed towards the bidirectional relationship between brain dysfunctions and sleep problems in children with ASD. Conclusions: Today’s literature acknowledges that objective and subjective sleep difficulties are more often recognized in individuals with ASD, so clinicians should assess sleep quality in the ASD clinical population, taking into consideration the potential implications on treatment strategies. It would be worthwhile in future studies to examine how factors, such as age, cognitive level or ASD severity could be related to ASD sleep abnormalities. Future research should directly assess whether sleep alterations could represent a specific marker for atypical brain development in ASD.