Alpha oscillations during visual selective attention are aberrant in youth and adults with cerebral palsy.

Our understanding of the neurobiology underlying cognitive dysfunction in persons with cerebral palsy is very limited, especially in the neurocognitive domain of visual selective attention. This investigation utilized magnetoencephalography and an Eriksen arrow-based flanker task to quantify the dynamics underlying selective attention in a cohort of youth and adults with cerebral palsy (n = 31; age range = 9 to 47 yr) and neurotypical controls (n = 38; age range = 11 to 49 yr). The magnetoencephalography data were transformed into the time-frequency domain to identify neural oscillatory responses and imaged using a beamforming approach. The behavioral results indicated that all participants exhibited a flanker effect (greater response time for the incongruent compared to congruent condition) and that individuals with cerebral palsy were slower and less accurate during task performance. We computed interference maps to focus on the attentional component and found aberrant alpha (8 to 14 Hz) oscillations in the right primary visual cortices in the group with cerebral palsy. Alpha and theta (4 to 7 Hz) oscillations were also seen in the left and right insula, and these oscillations varied with age across all participants. Overall, persons with cerebral palsy exhibit deficiencies in the cortical dynamics serving visual selective attention, but these aberrations do not appear to be uniquely affected by age.

An Explainable Unified Framework of Spatio-Temporal Coupling Learning with Application to Dynamic Brain Functional Connectivity Analysis.

Time-series data such as fMRI and MEG carry a wealth of inherent spatio-temporal coupling relationship, and their modeling via deep learning is essential for uncovering biological mechanisms. However, current machine learning models for mining spatio-temporal information usually overlook this intrinsic coupling association, in addition to poor explainability. In this paper, we present an explainable learning framework for spatio-temporal coupling. Specifically, this framework constructs a deep learning network based on spatio-temporal correlation, which can well integrate the time-varying coupled relationships between node representation and inter-node connectivity. Furthermore, it explores spatio-temporal evolution at each time step, providing a better explainability of the analysis results. Finally, we apply the proposed framework to brain dynamic functional connectivity (dFC) analysis. Experimental results demonstrate that it can effectively capture the variations in dFC during brain development and the evolution of spatio-temporal information at the resting state. Two distinct developmental functional connectivity (FC) patterns are identified. Specifically, the connectivity among regions related to emotional regulation decreases, while the connectivity associated with cognitive activities increases. In addition, children and young adults display notable cyclic fluctuations in resting-state brain dFC.

Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development.

Modeling dynamic interactions among network components is crucial to uncovering the evolution mechanisms of complex networks. Recently, spatio-temporal graph learning methods have achieved noteworthy results in characterizing the dynamic changes of inter-node relations (INRs). However, challenges remain: The spatial neighborhood of an INR is underexploited, and the spatio-temporal dependencies in INRs' dynamic changes are overlooked, ignoring the influence of historical states and local information. In addition, the model's explainability has been understudied. To address these issues, we propose an explainable spatio-temporal graph evolution learning (ESTGEL) model to model the dynamic evolution of INRs. Specifically, an edge attention module is proposed to utilize the spatial neighborhood of an INR at multi-level, i.e., a hierarchy of nested subgraphs derived from decomposing the initial node-relation graph. Subsequently, a dynamic relation learning module is proposed to capture the spatio-temporal dependencies of INRs. The INRs are then used as adjacent information to improve the node representation, resulting in comprehensive delineation of dynamic evolution of the network. Finally, the approach is validated with real data on brain development study. Experimental results on dynamic brain networks analysis reveal that brain functional networks transition from dispersed to more convergent and modular structures throughout development. Significant changes are observed in the dynamic functional connectivity (dFC) associated with functions including emotional control, decision-making, and language processing.

High-definition transcranial direct current stimulation of the parietal cortices modulates the neural dynamics underlying verbal working memory.

Verbal working memory (vWM) is an essential limited-capacity cognitive system that spans the fronto-parietal network and utilizes the subprocesses of encoding, maintenance, and retrieval. With the recent widespread use of noninvasive brain stimulation techniques, multiple recent studies have examined whether such stimulation may enhance cognitive abilities such as vWM, but the findings to date remain unclear in terms of both behavior and critical brain regions. In the current study, we applied high-definition direct current stimulation to the left and right parietal cortices of 39 healthy adults in three separate sessions (left anodal, right anodal, and sham). Following stimulation, participants completed a vWM task during high-density magnetoencephalography (MEG). Significant neural responses at the sensor-level were imaged using a beamformer and whole-brain ANOVAs were used to identify the specific neuromodulatory effects of the stimulation conditions on neural responses serving distinct phases of vWM. We found that right stimulation had a faciliatory effect relative to left stimulation and sham on theta oscillations during encoding in the right inferior frontal, while the opposite pattern was observed for left supramarginal regions. Stimulation also had a faciliatory effect on theta in occipital regions and alpha in temporal regions regardless of the laterality of stimulation. In summary, our data suggest that parietal HD-tDCS both facilitates and interferes with neural responses underlying both the encoding and maintenance phases of vWM. Future studies are warranted to determine whether specific tDCS parameters can be tuned to accentuate the facilitation responses and attenuate the interfering aspects.

Chronic Cannabis users exhibit altered oscillatory dynamics and functional connectivity serving visuospatial processing.

BACKGROUND: Cannabis is the most widely used psychoactive drug in the United States. While multiple studies have associated acute cannabis consumption with alterations in cognitive function (e.g., visual and spatial attention), far less is known regarding the effects of chronic consumption on the neural dynamics supporting these cognitive functions. METHODS: We used magnetoencephalography (MEG) and an established visuospatial processing task to elicit multi-spectral neuronal responses in 44 regular cannabis users and 53 demographically matched non-user controls. To examine the effects of chronic cannabis use on the oscillatory dynamics underlying visuospatial processing, neural responses were imaged using a time-frequency resolved beamformer and compared across groups. RESULTS: Neuronal oscillations serving visuospatial processing were identified in the theta (4-8 Hz), alpha (8-14 Hz), and gamma range (56-76 Hz), and these were imaged and examined for group differences. Our key results indicated that users exhibited weaker theta oscillations in occipital and cerebellar regions and weaker gamma responses in the left temporal cortices compared to non-users. Lastly, alpha oscillations did not differ, but alpha connectivity among higher-order attention areas was weaker in cannabis users relative to non-users and correlated with performance. CONCLUSIONS: Overall, these results suggest that chronic cannabis users have alterations in the oscillatory dynamics and neural connectivity serving visuospatial attention. Such alterations were observed across multiple cortical areas critical for higher-order processing and may reflect compensatory activity and/or the initial emergence of aberrant dynamics. Future work is needed to fully understand the implications of altered multispectral oscillations and neural connectivity in cannabis users.

Regular cannabis use modulates gamma activity in brain regions serving motor control.

BACKGROUND: People who regularly use cannabis exhibit altered brain dynamics during cognitive control tasks, though the impact of regular cannabis use on the neural dynamics serving motor control remains less understood. AIMS: We sought to investigate how regular cannabis use modulates the neural dynamics serving motor control. METHODS: Thirty-four people who regularly use cannabis (cannabis+) and 33 nonusers (cannabis-) underwent structured interviews about their substance use history and performed the Eriksen flanker task to map the neural dynamics serving motor control during high-density magnetoencephalography (MEG). The resulting neural data were transformed into the time-frequency domain to examine oscillatory activity and were imaged using a beamforming approach. RESULTS: MEG sensor-level analyses revealed robust beta (16-24 Hz) and gamma oscillations (66-74 Hz) during motor planning and execution, which were imaged using a beamformer. Both responses peaked in the left primary motor cortex and voxel time series were extracted to evaluate the spontaneous and oscillatory dynamics. Our key findings indicated that the cannabis+ group exhibited weaker spontaneous gamma activity in the left primary motor cortex relative to the cannabis- group, which scaled with cannabis use and behavioral metrics. Interestingly, regular cannabis use was not associated with differences in oscillatory beta and gamma activity, and there were no group differences in spontaneous beta activity. CONCLUSIONS: Our findings suggest that regular cannabis use is associated with suppressed spontaneous gamma activity in the left primary motor cortex, which scales with the degree of cannabis use disorder symptomatology and is coupled to behavioral task performance.

A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity during Brain Development.

OBJECTIVE: Brain dynamic effective connectivity (dEC), characterizes the information transmission patterns between brain regions that change over time, which provides insight into the biological mechanism underlying brain development. However, most existing methods predominantly capture fixed or temporally invariant EC, leaving dEC largely unexplored. METHODS: Herein we propose a deep dynamic causal learning model specifically designed to capture dEC. It includes a dynamic causal learner to detect time-varying causal relationships from spatio-temporal data, and a dynamic causal discriminator to validate these findings by comparing original and reconstructed data. RESULTS: Our model outperforms established baselines in the accuracy of identifying dynamic causalities when tested on the simulated data. When applied to the Philadelphia Neurodevelopmental Cohort, the model uncovers distinct patterns in dEC networks across different age groups. Specifically, the evolution process of brain dEC networks in young adults is more stable than in children, and significant differences in information transfer patterns exist between them. CONCLUSION: This study highlights the brain's developmental trajectory, where networks transition from undifferentiated to specialized structures with age, in accordance with the improvement of an individual's cognitive and information processing capability. SIGNIFICANCE: The proposed model consists of the identification and verification of dynamic causality, utilizing the spatio-temporal fusing information from fMRI. As a result, it can accurately detect dEC and characterize its evolution over age.

Effects of endogenous testosterone on oscillatory activity during verbal working memory in youth.

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6-14 years-old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole-brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone-related effects in theta (4-7 Hz) and alpha (8-14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left-lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex-specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age.

Chronic cannabis use alters the spontaneous and oscillatory gamma dynamics serving cognitive control.

Regular cannabis use is associated with cortex-wide changes in spontaneous and oscillatory activity, although the functional significance of such changes remains unclear. We hypothesized that regular cannabis use would suppress spontaneous gamma activity in regions serving cognitive control and scale with task performance. Participants (34 cannabis users, 33 nonusers) underwent an interview regarding their substance use history and completed the Eriksen flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain and virtual sensors were extracted from the peak voxels of the grand-averaged oscillatory interference maps to quantify spontaneous gamma activity during the pre-stimulus baseline period. We then assessed group-level differences in spontaneous and oscillatory gamma activity, and their relationship with task performance and cannabis use metrics. Both groups exhibited a significant behavioral flanker interference effect, with slower responses during incongruent relative to congruent trials. Mixed-model ANOVAs indicated significant gamma-frequency neural interference effects in the left frontal eye fields (FEF) and left temporoparietal junction (TPJ). Further, a group-by-condition interaction was detected in the left FEF, with nonusers exhibiting stronger gamma oscillations during incongruent relative to congruent trials and cannabis users showing no difference. In addition, spontaneous gamma activity was sharply suppressed in cannabis users relative to nonusers in the left FEF and TPJ. Finally, spontaneous gamma activity in the left FEF and TPJ was associated with task performance across all participants, and greater cannabis use was associated with weaker spontaneous gamma activity in the left TPJ of the cannabis users. Regular cannabis use was associated with weaker spontaneous gamma in the TPJ and FEF. Further, the degree of use may be proportionally related to the degree of suppression in spontaneous activity in the left TPJ.

Neurochemical organization of cortical proteinopathy and neurophysiology along the Alzheimer's disease continuum.

INTRODUCTION: Despite parallel research indicating amyloid-ß accumulation, alterations in cortical neurophysiological signaling, and multi-system neurotransmitter disruptions in Alzheimer's disease (AD), the relationships between these phenomena remains unclear. METHODS: Using magnetoencephalography, positron emission tomography, and an atlas of 19 neurotransmitters, we studied the alignment between neurophysiological alterations, amyloid-ß deposition, and the neurochemical gradients of the cortex. RESULTS: In patients with mild cognitive impairment and AD, changes in cortical rhythms were topographically aligned with cholinergic, serotonergic, and dopaminergic systems. These alignments correlated with the severity of clinical impairments. Additionally, cortical amyloid-ß plaques were preferentially deposited along neurochemical boundaries, influencing how neurophysiological alterations align with muscarinic acetylcholine receptors. Most of the amyloid-ß-neurochemical and alpha-band neuro-physio-chemical alignments replicated in an independent dataset of individuals with asymptomatic amyloid-ß accumulation. DISCUSSION: Our findings demonstrate that AD pathology aligns topographically with the cortical distribution of chemical neuromodulator systems and scales with clinical severity, with implications for potential pharmacotherapeutic pathways. HIGHLIGHTS: Changes in cortical rhythms in Alzheimer's are organized along neurochemical boundaries. The strength of these alignments is related to clinical symptom severity. Deposition of amyloid-ß (Aß) is aligned with similar neurotransmitter systems. Aß deposition mediates the alignment of beta rhythms with cholinergic systems. Most alignments replicate in participants with pre-clinical Alzheimer's pathology.

Spontaneous cortical activity is altered in persons with HIV and related to domain-specific cognitive function.

Whilst the average lifespan of persons with HIV now approximates that of the general population, these individuals are at a much higher risk of developing cognitive impairment with ∼35-70% experiencing at least subtle cognitive deficits. Previous works suggest that HIV impacts both low-level primary sensory regions and higher-level association cortices. Notably, multiple neuroHIV studies have reported elevated levels of spontaneous cortical activity during the pre-stimulus baseline period of task-based experiments, but only a few have examined such activity during resting-state conditions. In the current study, we examined such spontaneous cortical activity using magnetoencephalography in 79 persons with HIV and 83 demographically matched seronegative controls and related this neural activity to performance on neuropsychological assessments of cognitive function. Consistent with previous works, persons with HIV exhibited stronger spontaneous gamma activity, particularly in inferior parietal, prefrontal and superior temporal cortices. In addition, serostatus moderated the relationship between spontaneous beta activity and attention, motor and processing speed scores, with controls but not persons with HIV showing stronger beta activity with better performance. The current results suggest that HIV predominantly impacts spontaneous activity in association cortices, consistent with alterations in higher-order brain function, and may be attributable to deficient GABAergic signalling, given its known role in the generation of gamma and beta oscillations. Overall, these effects align with previous studies showing aberrant spontaneous activity in persons with HIV and provide a critical new linkage to domain-specific cognitive dysfunction.

Optimal gamma-band entrainment of visual cortex.

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14-16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma-band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma-band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma-band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high-density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma-band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. PRACTITIONER POINTS: Gamma-band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown. We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma-band frequencies. These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions.

Anterior pituitary gland volume mediates associations between pubertal hormones and changes in transdiagnostic symptoms in youth.

The pituitary gland (PG) plays a central role in the production and secretion of pubertal hormones, with documented links to the emergence and increase in mental health symptoms known to occur during adolescence. Although much of the literature has focused on examining whole PG volume, recent findings suggest that there are associations among pubertal hormone levels, including dehydroepiandrosterone (DHEA), subregions of the PG, and elevated mental health symptoms (e.g., internalizing symptoms) during adolescence. Surprisingly, studies have not yet examined associations among these factors and increasing transdiagnostic symptomology, despite DHEA being a primary output of the anterior PG. Therefore, the current study sought to fill this gap by examining whether anterior PG volume specifically mediates associations between DHEA levels and changes in dysregulation symptoms in an adolescent sample ( N = 114, 9 - 17 years, M age = 12.87, SD = 1.88). Following manual tracing of the anterior and posterior PG, structural equation modeling revealed that greater anterior, not posterior, PG volume mediated the association between greater DHEA levels and increasing dysregulation symptoms across time, controlling for baseline dysregulation symptom levels. These results suggest specificity in the role of the anterior PG in adrenarcheal processes that may confer risk for psychopathology during adolescence. This work not only highlights the importance of separately tracing the anterior and posterior PG, but also suggests that transdiagnostic factors like dysregulation are useful in parsing hormone-related increases in mental health symptoms in youth.

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds.

Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging. Methods: We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevel-opmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP). Results: We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity. Conclusion: Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics. Significance: Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.

Everyday home radon exposure is associated with altered structural brain morphology in youths.

The refinement of brain morphology extends across childhood, and exposure to environmental toxins during this period may alter typical trends. Radon is a highly common radiologic toxin with a well-established role in cancer among adults. However, effects on developmental populations are understudied in comparison. This study investigated whether home radon exposure is associated with altered brain morphology in youths. Fifty-four participants (6-14 yrs, M=10.52 yrs, 48.15% male, 89% White) completed a T1-weighted MRI and home measures of radon. We observed a significant multivariate effect of home radon concentrations, which was driven by effects on GMV. Specifically, higher home radon was associated with smaller GMV (F=6.800, p=.012, ηp2=.13). Conversely, there was a trending radon-by-age interaction on WMV, which reached significance when accounting for the chronicity of radon exposure (F=4.12, p=.049, ηp2=.09). We found that youths with above-average radon exposure showed no change in WMV with age, whereas low radon was linked with normative, age-related WMV increases. These results suggest that everyday home radon exposure may alter sensitive structural brain development, impacting developmental trajectories in both gray and white matter.

A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds.

Objective: fMRI and derived measures such as functional connectivity (FC) have been used to predict brain age, general fluid intelligence, psychiatric disease status, and preclinical neurodegenerative disease. However, it is not always clear that all demographic confounds, such as age, sex, and race, have been removed from fMRI data. Additionally, many fMRI datasets are restricted to authorized researchers, making dissemination of these valuable data sources challenging. Methods: We create a variational autoencoder (VAE)-based model, DemoVAE, to decorrelate fMRI features from demographics and generate high-quality synthetic fMRI data based on user-supplied demographics. We train and validate our model using two large, widely used datasets, the Philadelphia Neurodevelopmental Cohort (PNC) and Bipolar and Schizophrenia Network for Intermediate Phenotypes (BSNIP). Results: We find that DemoVAE recapitulates group differences in fMRI data while capturing the full breadth of individual variations. Significantly, we also find that most clinical and computerized battery fields that are correlated with fMRI data are not correlated with DemoVAE latents. An exception are several fields related to schizophrenia medication and symptom severity. Conclusion: Our model generates fMRI data that captures the full distribution of FC better than traditional VAE or GAN models. We also find that most prediction using fMRI data is dependent on correlation with, and prediction of, demographics. Significance: Our DemoVAE model allows for generation of high quality synthetic data conditioned on subject demographics as well as the removal of the confounding effects of demographics. We identify that FC-based prediction tasks are highly influenced by demographic confounds.

Hypertension Impacts the Oscillatory Dynamics Serving the Encoding Phase of Verbal Working Memory.

BACKGROUND: Chronic hypertension is known to be a major contributor to cognitive decline, with executive function and working memory being among the domains most commonly affected. Despite the growing literature on such dysfunction in patients with hypertension, the underlying neural processes are poorly understood. METHODS: In this cross-sectional study, we examine these neural processes by having participants with controlled hypertension, uncontrolled hypertension, and healthy controls perform a verbal working memory task during magnetoencephalography. Neural oscillations associated with the encoding and maintenance components of the working memory task were imaged and statistically evaluated among the 3 groups. RESULTS: Differences related to hypertension emerged during the encoding phase, where the hypertension groups exhibited weaker α-ß oscillatory responses compared with controls in the left parietal cortices, whereas such oscillatory activity differed between the 2 hypertension groups in the right prefrontal regions. Importantly, these neural responses in the prefrontal and parietal cortices during encoding were also significantly associated with behavioral performance across all participants. CONCLUSIONS: Overall, our data suggest that hypertension is associated with neurophysiological abnormalities during working memory encoding, whereas the neural processes serving maintenance seem to be preserved. The right hemispheric neural responses likely reflected compensatory processing, which patients with controlled hypertension may use to achieve verbal working memory function at the level of controls, as opposed to the uncontrolled hypertension group where diminished resources may have limited such additional recruitment.

MRI morphometry of the anterior and posterior cerebellar vermis and its relationship to sensorimotor and cognitive functions in children.

INTRODUCTION: The human cerebellum emerges as a posterior brain structure integrating neural networks for sensorimotor, cognitive, and emotional processing across the lifespan. Developmental studies of the cerebellar anatomy and function are scant. We examine age-dependent MRI morphometry of the anterior cerebellar vermis, lobules I-V and posterior neocortical lobules VI-VII and their relationship to sensorimotor and cognitive functions. METHODS: Typically developing children (TDC; n=38; age 9-15) and healthy adults (HAC; n=31; 18-40) participated in high-resolution MRI. Rigorous anatomically informed morphometry of the vermis lobules I-V and VI-VII and total brain volume (TBV) employed manual segmentation computer-assisted FreeSurfer Image Analysis Program [http://surfer.nmr.mgh.harvard.edu]. The neuropsychological scores (WASI-II) were normalized and related to volumes of anterior, posterior vermis, and TBV. RESULTS: TBVs were age independent. Volumes of I-V and VI-VII were significantly reduced in TDC. The ratio of VI-VII to I-V (∼60%) was stable across age-groups; I-V correlated with visual-spatial-motor skills; VI-VII with verbal, visual-abstract and FSIQ. CONCLUSIONS: In TDC neither anterior I-V nor posterior VI-VII vermis attained adult volumes. The "inverted U" developmental trajectory of gray matter peaking in adolescence does not explain this finding. The hypothesis of protracted development of oligodendrocyte/myelination is suggested as a contributor to TDC's lower cerebellar vermis volumes.

Neuromodulatory effects of parietal high-definition transcranial direct-current stimulation on network-level activity serving fluid intelligence.

Fluid intelligence (Gf) involves rational thinking skills and requires the integration of information from different cortical regions to resolve novel complex problems. The effects of non-invasive brain stimulation on Gf have been studied in attempts to improve Gf, but such studies are rare and the few existing have reached conflicting conclusions. The parieto-frontal integration theory of intelligence (P-FIT) postulates that the parietal and frontal lobes play a critical role in Gf. To investigate the suggested role of parietal cortices, we applied high-definition transcranial direct current stimulation (HD-tDCS) to the left and right parietal cortices of 39 healthy adults (age 19-33 years) for 20 min in three separate sessions (left active, right active and sham). After completing the stimulation session, the participants completed a logical reasoning task based on Raven's Progressive Matrices during magnetoencephalography. Significant neural responses at the sensor level across all stimulation conditions were imaged using a beamformer. Whole-brain, spectrally constrained functional connectivity was then computed to examine the network-level activity. Behaviourally, we found that participants were significantly more accurate following left compared to right parietal stimulation. Regarding neural findings, we found significant HD-tDCS montage-related effects in brain networks thought to be critical for P-FIT, including parieto-occipital, fronto-occipital, fronto-parietal and occipito-cerebellar connectivity during task performance. In conclusion, our findings showed that left parietal stimulation improved abstract reasoning abilities relative to right parietal stimulation and support both P-FIT and the neural efficiency hypothesis. KEY POINTS: Abstract reasoning is a critical component of fluid intelligence and is known to be served by multispectral oscillatory activity in the fronto-parietal cortices. Recent studies have aimed to improve abstract reasoning abilities and fluid intelligence overall through behavioural training, but the results have been mixed. High-definition transcranial direct-current stimulation (HD-tDCS) applied to the parietal cortices modulated task performance and neural oscillations during abstract reasoning. Left parietal stimulation resulted in increased accuracy and decreased functional connectivity between occipital regions and frontal, parietal, and cerebellar regions. Future studies should investigate whether HD-tDCS alters abstract reasoning abilities in those who exhibit declines in performance, such as healthy ageing populations.

Adults with cerebral palsy exhibit uncharacteristic cortical oscillations during an adaptive sensorimotor control task.

Prior research has shown that the sensorimotor cortical oscillations are uncharacteristic in persons with cerebral palsy (CP); however, it is unknown if these altered cortical oscillations have an impact on adaptive sensorimotor control. This investigation evaluated the cortical dynamics when the motor action needs to be changed "on-the-fly". Adults with CP and neurotypical controls completed a sensorimotor task that required either proactive or reactive control while undergoing magnetoencephalography (MEG). When compared with the controls, the adults with CP had a weaker beta (18-24 Hz) event-related desynchronization (ERD), post-movement beta rebound (PMBR, 16-20 Hz) and theta (4-6 Hz) event-related synchronization (ERS) in the sensorimotor cortices. In agreement with normative work, the controls exhibited differences in the strength of the sensorimotor gamma (66-84 Hz) ERS during proactive compared to reactive trials, but similar condition-wise changes were not seen in adults with CP. Lastly, the adults with CP who had a stronger theta ERS tended to have better hand dexterity, as indicated by the Box and Blocks Test and Purdue Pegboard Test. These results may suggest that alterations in the theta and gamma cortical oscillations play a role in the altered hand dexterity and uncharacteristic adaptive sensorimotor control noted in adults with CP.