Biology subjects

Bellgrove, M. A.

Publications and source records attributed to Bellgrove, M. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Genetic and environmental factors associated with DNA methylation across childhood and adolescence in individuals with and without attention-deficit/hyperactivity disorder

Background: Genetic and environmental factors both contribute risk to the development of childhood Attention-deficit/hyperactivity disorder (ADHD), yet the molecular mechanisms conferring this risk remain unclear. We investigated the genetic and environmental factors influencing DNA methylation (DNAm) at sites linked to ADHD symptom trajectories. Methods: We used two overlapping subsamples from a longitudinal paediatric cohort: (1) children with genetic and epigenetic data at first wave saliva sampling (Wave 3, n=113, 9.47-11.86 years) underwent methylation quantitative trait loci (meQTL) analysis; (2) children with environmental (Waves 1-3) and one or more waves of epigenetic data (n=126, 9.5-11.9 years) were analysed using LASSO regression to identify predictors of ADHD (Remitted ADHD/Persistent ADHD/Controls) and Wave 3 DNAm. In a subset with multiple DNAm timepoints (n=75), linear mixed models tested whether environmental predictors associated with longitudinal DNAm change, and whether ADHD moderated these associations. Analyses were conducted on 12 CpGs in which we previously identified change in DNAm according to the ADHD clinical outcome. Results: Nineteen meQTLs for 5 CpGs explained up to 40% of DNAm variance. We identified 17 environmental predictors of ADHD and wave 3 DNAm. Higher household income and school quality of life (QoL) were associated with reduced DNAm at cg02208776 (household) and cg11124426 (QoL) over time. Critically, higher income in Remitted ADHD showed greater DNAm declines than Controls, with opposite patterns in Persistent ADHD. Conclusion: DNAm patterns linked to ADHD outcomes were associated with genetic and environmental factors. Notably, household income and school functioning were associated with epigenetic change, with income effects varying by ADHD trajectories - characterising higher income as protective in remittent individuals.

genomics↗

bioRxiv2026

An Integrated EEG, TMS-EEG and Behavioural Dataset for Investigating the Neural Correlates of Working Memory

Working memory is a fundamental process that underlies cognition. Accordingly, the neural mechanisms that support working memory performance are of great interest in cognitive neuroscience. We present a publicly accessible dataset comprising 123 healthy adults (mean age = 28.58 years, SD = 7.56; age range = 18-46 years; 75 females) to facilitate investigation of the neural mechanisms underlying working memory performance in humans. Across two days of assessment, participants underwent a battery of cognitive tasks assessing working memory and other cognitive domains (day 1), followed by 62-channel EEG recordings (day 2). EEG data were acquired at rest, during a visual working memory task, and following single-pulse transcranial magnetic stimulation (TMS-EEG) targeting key brain regions involved in working memory. This article provides a detailed overview of the study design, methodology, and data characteristics.

neuroscience↗

bioRxiv2026

Diminished Stimulus-Evoked Activity During Sustained Attention Without Behavioural Cost in ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is often accompanied by attentional challenges, sleep difficulties and increased reports of daytime sleepiness, indicating potential links between attention and arousal mechanisms. Electroencephalographic (EEG) studies have shown that sleep-like wake slow wave (SW) activity during wakefulness, characterised by reduced cortical activity, corresponds with periods of inattention in both ADHD and neurotypical populations. However, it remains unclear whether group differences in waking SWs are consistent across different types of sustained attention tasks or may be context-dependent. The present study compared sustained attention performance and wake SW activity between adults with and without ADHD during a continuous visual target detection task. EEG data were collected while adults with (n = 52) and without ADHD (n = 49) completed a sustained attention paradigm. The task presented a continuous stream of rotating (anti-clockwise or clockwise) black-and-white checkerboard stimuli, and participants were required to detect infrequent targets that were marginally longer in duration than non-targets. Behavioural and neural measures (power spectra, steady-state visually evoked potentials (SSVEP), event-related potentials and SW density during wake) were analysed. No significant group differences were observed for task performance and wake SW activity. However, electrophysiological analyses revealed the ADHD group showed reduced P300, elevated beta-band power, and lower SSVEPs to target stimuli compared with the neurotypical group. These neural differences in the context of comparable performance suggest compensatory cortical recruitment in ADHD. The absence of SW differences further supports this, suggesting comparable performance and maintained arousal may reflect successful neural compensation in ADHD in this cognitive task. Significance StatementIndividuals with ADHD commonly experience attention differences, but emerging evidence suggests these difficulties may depend on task context. Using clinical diagnostic interviews, medication washout, and Bayesian statistics, we found strong evidence for comparable performance between ADHD and neurotypical adults on a sustained attention task. Notably, slow wave activity during wakefulness did not differ between groups, consistent with maintained arousal. Nevertheless, differences in brain activity, including altered target processing, increased cortical activation and reduced visual entrainment, suggested compensatory neural recruitment in ADHD. This context-dependent pattern has important theoretical and clinical implications: identifying task features that challenge or support performance in ADHD can reveal how individuals compensate neurally, and guide interventions that leverage task features to support attention in ADHD.

neuroscience↗

bioRxiv2025

Sleep-like slow waves in wakefulness index post-stroke behavioural alterations

Increases in high-amplitude, low-frequency EEG oscillations during non-rapid eye movement (NREM) sleep serve as markers of neuronal silencing, which disrupts functional connectivity and is associated with a loss of awareness and responsiveness. Cortical slowing likewise occurs during wakefulness, upon sleep deprivation, and accompanies performance deterioration. Recent work has revealed similar oscillations (termed sleep-like slow waves) following stroke in brain regions close or connected to a brain lesion, offering a plausible but untested mechanism for stroke-related behavioural impairment. Here, we simultaneously recorded EEG and behavioural performance while 30 unilateral stroke patients (12 left hemisphere, 18 right hemisphere) and 27 age-matched healthy adults completed a computerised perceptual decision-making task. Sleep-like slow waves occurred more frequently in stroke patients relative to healthy controls. Furthermore, there was a significant correlation between slow wave occurrence and the accuracy and speed of perceptual reports in stroke patients, suggesting that variations in the occurrence of slow waves may contribute to cognitive heterogeneity post-stroke. Evidence that sleep-like slow waves predict deficits in perceptual decision-making following stroke indicates that stroke-induced lesions can destabilize cortical networks extending beyond the damaged regions, thereby contributing to broader cognitive impairments.

neuroscience↗

bioRxiv2025

An Evaluation of the Efficacy of Single-Echo and Multi-Echo fMRI Denoising Strategies

Resting-state functional magnetic resonance imaging (rsfMRI) is commonly used to study brain-wide patterns of inter-regional functional coupling (FC). However, the resulting signals are vulnerable to multiple sources of noise, such as those related to non-neuronal physiological fluctuations and head motion, which can alter FC estimates and influence their associations with behavioral outcomes. The best strategy for acquiring and processing rsfMRI data to mitigate noise remains an open question. In this study of 358 healthy individuals, we compared the denoising efficacy of 60 multi-echo (ME) and 30 single-echo (SE) rsfMRI preprocessing pipelines across six distinct measures of data quality. We also evaluated how each pipeline influences the effect sizes of FC-based predictive models of personality and cognitive measures estimated via cross-validated kernel ridge regression. We found that ME pipelines generally showed superior denoising efficacy to SE pipelines, but that no single pipeline was associated with both superior denoising efficacy and behavioural prediction. Using a heuristic scheme to rank pipelines across benchmark evaluations, we found that an ME acquisition combined with Automatic Removal of Motion Artifacts Independent Component Analysis (ICA-AROMA) and Regressor Interpolation at Progressive Time Delays (RIPTiDe) offered a reasonable compromise between denoising efficacy and brain-behavior predictions for both ME and SE data. In general, ME pipelines ranked more highly than SE pipelines. These findings support the use of ME acquisitions in future work but suggest that no single denoising pipeline should be considered optimal for all purposes.

neuroscience↗

bioRxiv2025

Sleep-like Slow Waves During Wakefulness Mediate Attention and Vigilance Difficulties in Adult Attention-Deficit/Hyperactivity Disorder

BackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) is characterised by behavioural variability and heightened inattention associated with increased mind wandering (MW) and mind blanking (MB). Individuals with ADHD frequently experience sleep disorders and excessive daytime sleepiness, suggesting interactions between attention and arousal systems. Research examining brain activity using electroencephalography (EEG) has demonstrated that sleep-like slow waves (SW) during wakefulness are linked to inattention in neurotypical individuals, particularly following sleep deprivation, yet their role in ADHD remains unclear. This study investigated whether individuals with ADHD present with altered waking SW distribution compared to neurotypical controls and whether SW explain attentional difficulties in ADHD. MethodsAdults with (n = 32) and without ADHD (n = 31) completed a sustained attention task while EEG recorded brain activity. Mental state probes (on-task, MW, MB) were embedded within the task. Sleep-like SW reflect a slowing of cortical activity and was detected from EEG activity. Omission/commission errors, reaction time (RT), RT variability, mental state reports and subjective sleepiness were analysed. Mediation analysis examined whether SW density explained ADHD-related performance differences. ResultsIndividuals with ADHD exhibited more commission errors, MW and MB, and higher SW density (SW/min), particularly over parieto-temporal electrodes. Increased SW density correlated with higher omission errors, slower RTs, greater RT variability, and elevated sleepiness ratings. On-task reports were negatively correlated with SW density. Mediation analysis revealed that SW density significantly accounted for ADHD-related attentional difficulties. ConclusionsWake SW may explain attentional difficulties in ADHD, providing a potential mechanistic link between sleep disturbances and attentional fluctuations.

neuroscience↗

bioRxiv2025

The role of human intraparietal sulcus in evidence accumulation revealed by EEG and model-informed fMRI

Sequential sampling models propose that the repeated sampling of sensory information is a fundamental component of perceptual decision-making. Electroencephalographic investigations in humans have demonstrated motor-independent representations of evidence accumulation, but such observations have seldom been made in neuroimaging studies exploring the neuroanatomical origins of evidence accumulation. Here, we aimed to reveal the neuroanatomical locus of sensory evidence accumulation in the human brain by regressing an electrophysiological marker of evidence accumulation (centroparietal positivity, CPP) against changes in blood oxygen level-dependent (BOLD) signal during perceptual decision-making. Our cross-modal imaging approach revealed a cluster within left intraparietal sulcus (IPS), located within putative lateral intraparietal area (region hIP3), for which BOLD signals scaled in relation to the slope of the CPP. Furthermore, the drift rate parameter of a drift diffusion model parametrically modulated BOLD activity within an overlapping region of left IPS. In contrast, parametric modulation by reaction time revealed a distributed fronto-parietal network, demonstrating the utility of our approach for isolating a discrete neuroanatomical locus of evidence accumulation. Together, our findings provide strong support for intraparietal sulcus involvement in the accumulation of sensory evidence during human perceptual decision-making.

neuroscience↗

bioRxiv2025

Geometric influences on the regional organization of the mammalian brain

The mammalian brain comprises anatomically and functionally distinct regions, yet the principles governing their organization across scales remain unclear. Efforts to map regional boundaries use expert judgement or data-driven clustering of functional, connectional, and/or architectonic properties, but these approaches are often descriptive, have limited generalizability, and do not elucidate generative mechanisms. Here, we develop a geometrically constrained framework for the hierarchical, multiscale regional organization of neocortical and non-neocortical structures. The framework yields parcels at any resolution with high internal homogeneity across hundreds of anatomical, functional, cellular, and molecular properties in humans, macaques, marmosets, and mice, and it generalizes to understudied mammalian species. Finally, we demonstrate that the framework captures the essence of a reaction-diffusion mechanism in which brain geometry shapes the spatial expression of putative patterning molecules that establish a blueprint of regional identity during development. Our findings point to a conserved, universal influence of geometry on mammalian brain organization.

neuroscience↗

bioRxiv2024

Mapping the impact of DUSP6 in an ADHD iPSC derived-dopaminergic neuronal model

Although the gene DUSP6 has been implicated as a risk gene for attention deficit hyperactivity disorder (ADHD) in recent GWAS studies, its functional role in the aetiology of the condition remains poorly understood. DUSP6 is reported to regulate dopaminergic neurotransmission by decreasing available synaptic dopamine, suggesting a potential mechanism by which DUSP6 may confer risk to ADHD. In this study, we employed CRISPR-Cas9 to generate isogenic iPSC lines from an individual with ADHD, including heterozygous and homozygous DUSP6 knockouts alongside the parental control. These iPSC lines were differentiated into dopaminergic neurons and assessed at both cellular, and transcriptomic levels. We observed significant increase in extracellular dopamine in proportion to DUSP6 gene dosage, with greater elevation in homozygous compared to heterozygous knockouts. RNA sequencing further supported this finding, showing that DUSP6-knockout increased expression of genes regulating dopamine secretion and synaptic processes critical for dopaminergic system. Beyond dopamine signalling, transcriptomic changes implicated DUSP6 in neurodevelopmental biological mechanisms, essential to the development of ADHD. Furthermore, we identified significant overlaps between DUSP6-regulated genes and those associated with major depression, bipolar disorder, and schizophrenia, suggesting shared genetic pathways potentially influenced by DUSP6. This study provides mechanistic insights into the role that DUSP6 could potentially play in the aetiology of ADHD and its broader implications across related neuropsychiatric conditions.

neuroscience↗

bioRxiv2024

Transcriptome profiling of dopaminergic neurons derived from an ADHD induced pluripotent stem cell (iPSC) model

The most recent ADHD-GWAS meta-analysis highlighted the potential role of 76 genes enriched among genes expressed in early brain development and associated with midbrain dopaminergic neurons. However, the precise functional importance of the GWAS-identified single nucleotide polymorphisms (SNPs) remain unknown. In contrast to GWAS, transcriptome analysis directly investigates gene products by assessing the transcribed RNA. This allows one to gain functional insights into gene expression paving the way for a better understanding of the molecular risk mechanisms of conditions, such as ADHD. In this study, we performed transcriptome profiling of highly homogeneous dopamine neurons developed from induced pluripotent cells (iPSCs) that were derived from an individual with ADHD and a neurotypical comparison individual. Comparative gene expression analysis between the examined lines revealed that the top differentially expressed genes (DEGs) were predominantly associated with nervous system functions related to neuronal development and dopaminergic regulation. Notably, 29 of the DEGs overlapped with those identified by ADHD-GWAS meta- analysis. These genes are overrepresented in biological processes including developmental growth regulation, axonogenesis, and nervous system development. In addition, gene set analysis revealed significant enrichment for meta categories such as ion channel activity, synaptic function and assembly, neuronal development and cell differentiation. Further, we observed significantly reduced projections in the ADHD dopamine neurons at the mid- differentiation stage (day 14 in vitro), providing preliminary support for the delayed neuronal maturation hypotheses of ADHD. This study underscores the potential of using iPSC-derived cell type-specific models that integrate genome and transcriptome analyses for biological discovery in ADHD.

neuroscience↗

bioRxiv2024

Multiscale heterogeneity of white matter morphometry in psychiatric disorders

BackgroundInter-individual variability in neurobiological and clinical characteristics in mental illness is often overlooked by classical group-mean case-control studies. Studies using normative modelling to infer person-specific deviations of grey matter volume have indicated that group means are not representative of most individuals. The extent to which this variability is present in white matter morphometry, which is integral to brain function, remains unclear. MethodsWe applied Warped Bayesian Linear Regression normative models to T1- weighted magnetic resonance imaging data and mapped inter-individual variability in person-specific white matter volume deviations in 1,294 cases (58% male) diagnosed with one of six disorders (attention-deficit/hyperactivity, autism, bipolar, major depressive, obsessive-compulsive and schizophrenia) and 1,465 matched controls (54% male) recruited across 25 scan sites. We developed a framework to characterize deviation heterogeneity at multiple spatial scales, from individual voxels, through inter- regional connections, specific brain regions, and spatially extended brain networks. ResultsThe specific locations of white matter volume deviations were highly heterogeneous across participants, affecting the same voxel in fewer than 8% of individuals with the same diagnosis. For autism and schizophrenia, negative deviations (i.e., areas where volume is lower than normative expectations) aggregated into common tracts, regions and large-scale networks in up to 35% of individuals. ConclusionsThe prevalence of white matter volume deviations was lower than previously observed in grey matter, and the specific location of these deviations was highly heterogeneous when considering voxel-wise spatial resolution. Evidence of aggregation within common pathways and networks was apparent in schizophrenia and autism but not other disorders.

neuroscience↗

bioRxiv2023

Neurophysiological mechanisms underlying post-stroke deficits in contralesional perceptual processing

Slowed responding to sensory inputs presented in contralesional space is pervasive following unilateral cerebral stroke, but the causal neurophysiological pathway by which this occurs remains unclear. To this end, here we leverage a perceptual decision-making framework to disambiguate information processing stages between sensation and action in 30 unilateral stroke patients (18 right hemisphere, 12 left hemisphere) and 27 neurologically healthy adults. By recording neural activity using electroencephalography (EEG) during task performance, we show that the relationship between strokes in either hemisphere and slowed contralesional response times is sequentially mediated by weaker target selection signals in the contralateral hemisphere (the N2c ERP), and subsequently delayed evidence accumulation signals (the centroparietal positivity). Notably, asymmetries in CPP and response times across hemispheres are associated with everyday functioning. Together, these data suggest a plausible neurophysiological pathway by which post-stroke contralesional slowing arises and highlight the utility of neurophysiological assessments for tracking clinically relevant behaviour.

neuroscience↗

bioRxiv2023

Neurophysiology of perceptual decision-making and its alterations in attention deficit hyperactivity disorder (ADHD)

Despite the prevalence of ADHD, efforts to develop a detailed understanding of the neuropsychology of this neurodevelopmental condition are complicated by the diversity of interindividual presentations and the inability of current clinical tests to distinguish between its sensory, attentional, arousal or motoric contributions. Identifying objective methods that can decompose the clinical heterogeneity of ADHD is a long-held goal that is hoped to advance our understanding of etiological processes and potentially aid the development of personalized treatment approaches. Here, we examine key neuropsychological components of ADHD within an electrophysiological (EEG) perceptual decision-making paradigm that is capable of isolating distinct neural signals of several key information processing stages necessary for sensory-guided actions from attentional selection to motor responses. We show that compared to typically developing children, children with ADHD displayed slower and less accurate performance, which was driven by the atypical dynamics of discrete electrophysiological signatures of attentional selection, the accumulation of sensory evidence, and strategic adjustments reflecting urgency of response. These findings offer an integrated account of decision-making in ADHD and establish discrete neural signals that can be used to understand the wide range of neuropsychological performance variations in individuals with ADHD. Significance StatementThe efficacy of diagnostic and therapeutic pathways in ADHD is limited by our incomplete understanding of its neurological basis. One promising avenue of research is the search for basic neural mechanisms that may contribute to the variety of cognitive challenges associated with ADHD. We developed a mechanistic account of differences in a fundamental cognitive process by integrating across neurocognitive, neurophysiological (i.e., EEG), and computational levels of analysis. We detected distinct neural changes in ADHD that explained altered performance (e.g., slowed and less accurate responses). These included changes in neural patterns of attentional selection, sensory information processing, and response preparation. These findings enhance our understanding of the neurophysiological profile of ADHD and may offer potential targets for more effective, personalized interventions.

neuroscience↗

bioRxiv2023

Characterising the contribution of auditory and somatosensory inputs to TMS-evoked potentials following stimulation of prefrontal, premotor and parietal cortex

Transcranial magnetic stimulation (TMS) results in a series of evoked potentials (TEPs) in electroencephalography (EEG) recordings. However, it remains unclear whether these responses reflect neural activity resulting from transcranial stimulation of the cortex, or from the sensory experiences of TMS. Across three experiments (total n = 135), we recorded EEG activity following TMS to the dorsolateral prefrontal cortex, premotor cortex, and parietal cortex as well as a sensory control condition (stimulation of the shoulder or electrical stimulation of the scalp with a click sound). We found that TEPs showed a stereotypical frontocentral N100/P200 complex following TMS of all cortical sites and control conditions, regardless of TMS intensity or the type of sensory control. In contrast, earlier TEPs (<60 ms) showed site-specific characteristics which were largest at the site of stimulation. Self-reported sensory experiences differed across sites, with prefrontal stimulation resulting in stronger auditory (click sound perception) and somatosensory input (scalp muscle twitch, discomfort) than premotor or parietal stimulation, a pattern that was reflected in the amplitude of later (N100/P200), but not earlier (<60 ms) TEP peak amplitudes. Later TEPs were also larger in individuals who experienced stronger click sound perception and, to a lesser extent, TMS-evoked scalp muscle twitches. Increasing click sound perception by removing auditory masking increased N100/P200 amplitudes without altering earlier peaks, an effect which was more prominent at sites with more successful masking. Together, these findings suggest that the frontocentral N100/P200 complex represents a generalised sensory response resulting from TMS-related auditory and somatosensory input. In contrast, early TEP peaks likely reflect activity resulting from transcranial stimulation of the cortex. The results have important implications for designing and interpreting TEP studies, especially when comparing TEPs between stimulation sites and participant groups showing differences in sensory experiences following TMS.

neuroscience↗

bioRxiv2023

Modelling cognitive outcomes in the UK Biobank: education, noradrenaline and frontoparietal networks

Education is often used as a surrogate measure of so called cognitive reserve (CR) benefiting cognitive functioning in later years. In line with Robertsons theory we tested here a hypothesis that education acting on the noradrenergic system strengthen the right fronto-parietal networks to facilitate CR and maintain cognition throughout the lifetime. We used machine learning and mediation analysis to model interactions between neurobiological features (genetic variants in noradrenergic signalling, structural and functional fronto-parietal connectivity) and education (proxy of CR) on cognitive outcomes (general cognitive ability score) in the UK Biobank cohort. We show that: (1) interactions between education and neurobiological variables better explain cognitive outcomes than either factor alone; (2) among the neurobiological features selected using variable importance testing, measures of right fronto-parietal connectivity are the strongest mediators of the effect of education on cognitive outcomes. Our findings offer novel insights into neurobiological basis of CR by pointing to between-networks connectivity, representing connections linking the default mode network with the right fronto-parietal network as the key facilitator of CR.

neuroscience↗

bioRxiv2023

Genetically mediated associations between chronotype and neuroimaging phenotypes in the UK Biobank: a Mendelian randomisation study

Chronotype impacts numerous physiological and disease traits, from metabolic syndrome to schizophrenia. The suprachiasmatic nucleus (SCN) maintains transcriptional-translational feedback loop (TTFL) which acts as a central chronobiological pacemaker, regulating 24-hour cycles throughout the human body. However, each tissue maintains its own peripheral clock, and both endogenous hormones and neurotransmitters and exogenous environmental cues regulate the SCNs central clock. The extent to which brain regions outside the SCN influence the core TTFL is unknown. Here, we investigated how genetic variability affecting brain regions outside the SCN may indirectly influence chronotype, using Mendelian randomization and causal inference. We performed genome wide association studies (GWAS) based on image derived phenotypes (IDPs) from neuroimaging data (grey matter volume, thickness and surface area, microstructural white matter measures; 42,062 participants), and additionally for sleep duration and morning/evening chronotype (361,739 participants). Significant, single nucleotide polymorphisms (SNPs) associating with each phenotype were entered into 2-sample Mendelian randomization performed using inverse-variance weighted methods (exposure versus outcome): 1) chronotype versus each IDP, 2) sleep versus each IDP and 3) each IDP versus chronotype. Subsequently, we investigated genes where significant instrumental SNPs were located for circadian periodic cycling, interaction with TTFL genes in common biological pathways (genetic, physical, or functional interaction), and enrichment of traits from UK Biobank and GWAS Catalogs. We found three associations with chronotype (morning/evening diurnal preference) outside the SCN based on genetically predicted (FAM76B, DENND1A, CDH11) regional differences in brain volume. Specifically, genetically predicted lower inferior temporal gyrus volume linked to morning phenotype, while lower volume of the superior parietal lobule and angular gyrus linked to evening preference. In addition, evening chronotype exposure influenced superior temporal gyrus volume, and both increased sleep duration and evening chronotype influenced thalamic volume. We conclude that genetically mediated associations between chronotype and brain regions outside SCN exist suggesting novel zeitgeber mechanisms.

neuroscience↗

bioRxiv2023

The effect of dopamine D2 receptor blockade on human motor skill learning

Rationale: Dopamine signalling supports motor skill learning in a variety of ways, including through an effect on cortical and striatal plasticity. One neuromodulator that has been consistently linked to motor skill learning is dopamine. However, the specific role of dopamine D2 receptor in the acquisition and consolidation stages of motor learning remains unclear. ObjectivesTo examine the effect of a selective D2 receptor antagonist on human motor skill acquisition and consolidation. MethodsIn this randomised, double-blind, placebo-controlled design, healthy adult men and women (N = 23) completed a sequential motor skill learning task after taking either sulpiride (800mg) or placebo. A 20-minute bout of high-intensity interval cycling exercise was included to enhance experimental effects and counteract potentially confounding sedative effects of sulpiride. ResultsSulpiride reduced performance during motor skill acquisition relative to placebo in the first session, however this difference was abolished at the subsequent retention test. Sulpiride did not reduce consolidation of learning as expected, however it led to a reduction in speed of execution relative to placebo. ConclusionsOur results demonstrate that neuromodulation at the dopamine D2 receptor is critical in the early acquisition of a novel motor skill. These results may have functional relevance in motor rehabilitation as reduced dopamine transmission can impact performance during initial learning and slow subsequent performance of the skill.

neuroscience↗

bioRxiv2022

Can hubs of the human connectome be identified consistently with diffusion MRI?

Recent years have seen a surge in the use of diffusion MRI to map connectomes in humans, paralleled by a similar increase in processing and analysis choices. Yet these different steps and their effects are rarely compared systematically. Here, in a healthy young adult population (n=294), we characterized the impact of a range of analysis pipelines on one widely studied property of the human connectome; its degree distribution. We evaluated the effects of 40 pipelines (comparing common choices of parcellation, streamline seeding, tractography algorithm, and streamline propagation constraint) and 44 group-representative connectome reconstruction schemes on highly connected hub regions. We found that hub location is highly variable between pipelines. The choice of parcellation has a major influence on hub architecture, and hub connectivity is highly correlated with regional surface area in most of the assessed pipelines ({rho}>0.70 in 69% of the pipelines), particularly when using weighted networks. Overall, our results demonstrate the need for prudent decision-making when processing diffusion MRI data, and for carefully considering how different processing choices can influence connectome organization. Author SummaryThe increasing use of diffusion MRI for mapping white matter connectivity has been matched by a similar increase in the number of ways to process the diffusion data. Here, we assess how diffusion processing affects hubs across 1760 pipeline variations. Many processing pipelines do not show a high concentration of connectivity within hubs. When present, hub location and distribution vary based on processing choices. The choice of probabilistic or deterministic tractography has a major impact on hub location and strength. Finally, node strength in weighted networks can correlate highly with node size. Overall, our results illustrate the need for prudent decision-making when processing and interpreting diffusion MRI data. Code and data availabilityAll the data used in this study is openly available on Figshare at https://doi.org/10.26180/c.6352886.v1. Scripts to analyze these data are available on GitHub at https://github.com/BMHLab/DegreeVariability. Competing InterestsThe authors declare that they have no competing interests.

neuroscience↗