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Marsh, R.

Publications and source records attributed to Marsh, R..

9 recordsLinked to original sources

Disrupted Higher-Order Topology in OCD Brain Networks Revealed by Hodge Laplacian - an ENIGMA Study

Brain disorders are increasingly understood as disorders of distributed brain circuits, yet functional connectivity (FC), the dominant framework for mapping them, treats the brain as a collection of pairwise relationships between regions and cannot represent pathology distributed across coordinated sets of connections. We introduce a Hodge-Laplacian topological framework that localizes higher-order "loop" (1-cycle) organization within functional connectome, maps each loop to specific edges and networks, and yields a subject-level measure of loop expression. Applied to resting-state fMRI from the ENIGMA-OCD consortium (1,024 patients and 1,028 controls across 28 sites), the framework identified 93 loop-level abnormalities in obsessive-compulsive disorder (OCD), concentrated in frontoparietal and somatomotor systems. The edges forming these loops largely showed no significant differences between groups, indicating that the abnormalities were invisible to conventional FC analysis. The frontoparietal and somatomotor loop clusters recurred across the clinical subgroups, suggesting convergence on a shared higher-order phenotype. Robustness analyses showed the loop signal reflected higher-order organization rather than an artifact of individual edges, the network backbone, or any single site. These results indicate that coordinated, multi-edge pathology exists and can be localized even when pairwise analyses fail to detect it, positioning higher-order topology as a generalizable axis for mapping circuit pathology across psychiatric and neurological disorders.

neuroscience↗

Generalized brain-state modeling with KenazLBM

The large-scale functional state of a human brain remains difficult to characterize, much less predict. Regardless, techniques have been engineered to electrically neuromodulate the brain to treat a subset of neurologic and psychiatric disorders with moderate efficacy. Accurate characterization of a brains instantaneous functional state has stymied the development of more effective neuromodulation paradigms. Advanced computational methods are required to address this gap and enable large-scale neuroscience. Here we define the concept of generalized brain-state modeling across humans as Large Brain-State Modeling (LBM) and present KenazLBM as the worlds first example. KenazLBM can instantaneously characterize the functional state of a persons brain with raw iEEG data, and predict future brain-states. KenazLBM was trained on over 17.9 billion unique multichannel tokens from people undergoing intracranial electroencephalography (iEEG) recordings, and has learned to interrelate brain-states between people into a common interpretable topology. Most importantly, the model generalizes to unseen subject data with significant recording channel heterogeneity from the training set. We offer KenazLBM as a first generalized brain-state model to serve as a new paradigm of basic neuroscience inquiry and potential translation into neuromodulation therapeutics.

neuroscience↗

Image quality metrics fail to accurately represent biological information in fluorescence microscopy

Image processing methods offer the potential to improve the quality of fluorescence microscopy data, allowing for image acquisition at lower, less phototoxic illumination doses. The training and evaluation of such methods is informed and driven by full-reference image quality metrics (IQMs); however, these metrics derive from applications to natural scene images, not fluorescence microscopy images. Here we investigate the response of IQMs to common properties of fluorescence microscopy data and whether IQMs are capable of reporting the biological information content of images. We find that IQM scores are biased by image content for both raw and processed microscopy data, and that improvements in IQM values reported after processing are not reliably correlated with performance in downstream analysis tasks. As common IQMs are unreliable proxies for guiding image processing developments in biological fluorescence microscopy, image processing performance should be benchmarked according to downstream analysis success.

bioinformatics↗

Investigating microbiota differences across chronic pancreatitis, influenced by lifestyle and genetic determinants

BackgroundChronic pancreatitis (CP) is a multifaceted and irreversible inflammatory condition that impacts both endocrine and exocrine pancreatic functions. Whilst there is evidence of a general intestinal microbial dysbiosis, differences across CP resulting from diverse triggers remains poorly elucidated. MethodsIn this study, we investigated how different CP triggers, namely alcohol-induced CP (AIP) and CFTR-related CP (CFRP), might undermine differences across microbiota structure and predicted function. Faecal samples from 25 CP participants were collected, alongside 9 healthy controls for microbiota analyses. Both full and short (V4) 16S rRNA sequencing was performed, including predicted functionality using PICRUSt2. Clinical metadata was integrated to investigate relationships with microbiota structure and predicted functionality with ordination-based approaches. ResultsMicrobiota diversity patterns between groups varied slightly by sequencing approach, with differences across common core and rarer satellite taxa diversity evident. Importantly, microbiota compositional profiles were shared between approaches, with control samples clustering closer than CP samples. Between groups, significant differences in microbiota composition were apparent, with the AIP group significantly different to both control and CFRP groups across various microbiota partitions (P < 0.05). Notable genera drove the observed dissimilarity, including Bifidobacterium, Faecalibacterium, and Ruminococcus, which were decreased in relative abundance across CP. Predictive functional analyses further demonstrated increased similarity of controls as compared to CP groups. Significant variation across both microbiota structure and predicted function was explained by CP subtype (P < 0.01). When compared back to controls, the relative abundance of various predicted functional pathways from both the core and satellite taxa was significantly different across groups (P < 0.05). ConclusionsOverall, we demonstrate that gut microbiota structure and predicted function differs between not only healthy controls and CP, including across CP subtypes themselves. Various taxa with important physiological roles were implicated across CP. Differences in predicted functionality of the core and satellite taxa were evident, relating to microbial processes that may have downstream consequences at the site of the GI tract. Future studies will employ larger cohorts with the incorporation of additional omics-based approaches. This will better elucidate differences in microbiota structure and functionality across CP, including relationships with pancreatic-based clinical outcomes.

microbiology↗

Characterisation and correction of polarisation effects in fluorescently labelled fibres

Many biological structures take the form of fibres and filaments, and quantitative analysis of fibre organisation is important for understanding their functions in both normal physiological conditions and disease. In order to visualise these structures, fibres can be fluorescently labelled and imaged, with specialised image analysis methods available for quantifying the degree and strength of fibre alignment. Here we show that fluorescently labelled fibres can display polarised emission, with the strength of this effect varying depending on structure and fluorophore identity. This can bias automated analysis of fibre alignment and mask the true underlying structural organisation. We present a method for quantifying and correcting these polarisation effects without requiring polarisation resolved microscopy, and demonstrate its efficacy when applied to images of fluorescently labelled collagen gels, allowing for more reliable characterisation of fibre microarchitecture.

cell biology↗

Decoding Age-specific Changes in Brain Functional Connectivity Using a Sliding-window Based Clustering Method

Functional magnetic resonance imaging (fMRI) permits detailed study of human brain function. Understanding the age-specific development of neural circuits in the typically developing brain may help us generate new hypotheses for developmental psychopathologies. Functional connectivity (FC), defined as the statistical associations between two brain regions, has been widely used in estimating functional networks from fMRI data. Previous research has shown that the evolution of FC does not follow a linear trend, particularly from childhood to young adulthood. Thus, this work aims to detect the nuanced FC changes with age from the non-linear curves and identify age-period-specific FC development patterns. We proposed a sliding-window based clustering approach to identify refined age interval of FC development. We used resting-state fMRI (rs-fMRI) data from the human connectome project-development (HCP-D), which recruited children, adolescents, and young adults aged from 5 to 21 years. Our analyses revealed different developmental patterns of resting-state FC by sex. In general, females matured earlier than males, but males had a faster development rate during age 100 -120 months. We identified four developmental phases: network construction in late childhood, segregation and integration construction in adolescence, network pruning in young adulthood, and a unique phase in males -- U-shape development. In addition, we investigated the sex effect on the slopes of FC-age correlation. Males had higher slopes during late childhood and young adulthood. These results inform trajectories of normal FC development, information that can in the future be used to pinpoint when development might go awry in neurodevelopmental disorders. HighlightO_LIPropose a novel sliding-window-based framework to identify refined age intervals of functional connectivity (FC) development. C_LIO_LIIdentify four developmental phases: network construction in late childhood, segregation and integration in adolescence, network pruning in young adulthood, and a unique phase in males -- U-shape development. C_LIO_LICharacterize the representative FC pattern for each developmental phase based on global network statistics, modular connectivity, and hub ROIs. C_LIO_LIReveal sex differences in developmental timing, rate, and patterns of resting-state FC. C_LI

neuroscience↗

White Matter Microstructure and its Relation to Clinical Features of Obsessive-Compulsive Disorder: Findings from the ENIGMA OCD Working Group

ImportanceMicrostructural alterations in cortico-subcortical connections are thought to be present in Obsessive-Compulsive Disorder (OCD). However, prior studies have yielded inconsistent findings, perhaps because small sample sizes provided insufficient power to detect subtle abnormalities. ObjectiveTo investigate microstructural white matter alterations and their relation to clinical features in the largest dataset of adult and pediatric OCD to date. Design, Setting, and ParticipantsIn this cross-sectional case-control magnetic resonance study, we investigated diffusion tensor imaging metrics from 700 adult patients and 645 adult controls, as well as 174 pediatric patients and 144 pediatric controls across 19 sites participating in the ENIGMA-OCD Working Group. Main Outcomes and MeasuresWe extracted measures of fractional anisotropy (FA) as main outcome, and mean diffusivity, radial diffusivity, and axial diffusivity as secondary outcomes for 25 white matter regions. We meta-analyzed patient-control group differences (Cohens d) across sites, after adjusting for age and sex, and investigated associations with clinical characteristics. ResultsAdult OCD patients showed significant FA reduction in the sagittal stratum (d=-0.21, z=-3.21, p=0.001) and posterior thalamic radiation (d=-0.26, z=-4.57, p<0.0001). In the sagittal stratum only, lower FA was associated with a younger age of onset (z=2.71, p=0.006), longer duration of illness (z=-2.086, p=0.036) and a higher percentage of medicated patients in the cohorts studied (z=-1.98, p=0.047). No significant association with symptom severity was found. Pediatric OCD patients did not show any detectable microstructural abnormalities compared to matched controls. Conclusions and RelevanceMicrostructural alterations in projection and association fibers to posterior brain regions were found in adult OCD, and related to disease course and medication status. Such results are relevant to models positing deficits in connectivity as a crucial mechanism in OCD. KEY POINTSO_ST_ABSQuestionC_ST_ABSDo patients with Obsessive-Compulsive Disorder (OCD) show white matter microstructural alterations, and are these alterations related to clinical features? FindingsData from 19 sites of the ENIGMA-OCD Consortium were included, involving 700 adult patients and 645 adult controls, 174 pediatric patients and 144 pediatric controls. Diffusion tensor imaging data were meta-analyzed using a harmonized data processing and analysis protocol. Adult, but not pediatric, patients showed alterations in the sagittal stratum and posterior thalamic radiation; sagittal stratum differences were associated with clinical features. MeaningMicrostructural abnormalities found in adult but not in the pediatric cohort, are related to illness duration and medication status.

neuroscience↗

The interaction of compliance and activation on the force-length operating range and force generating capacity of skeletal muscle

Muscle performance is influenced by where it operates on its force-length curve. Here we explore how activation and tendon compliance interact to influence muscle operating lengths and force-generating capacity. To study this, we built a musculoskeletal model of the lower limb of the guinea fowl and simulated the force-length operating range during fixed-end fixed-posture contractions for 39 actuators under thousands of combinations of activation and posture using three different muscle models: Muscles with non-compliant tendons, muscles with compliant tendons but no activation dependent shift in optimal fiber length (L0), and muscles with both compliant tendons and activation-dependent shifts in L0. We found that activation dependent effects altered muscle fiber lengths up to 40% and increased or decreased force capacity by up to 50% during fixed-end contractions. Typically, activation-compliance effects reduce muscle force and are dominated by the effects of tendon compliance at high activations. At low activation, however, activation-dependent shifts in L0 are equally important and can result in relative force changes for low compliance muscles of up to 60%. There are regions of the force-length curve in which muscles are most sensitive to compliance and there are troughs of influence where these factors have little effect. These regions are hard to predict, though, because the magnitude and location of these areas of high and low sensitivity shift with compliance level. Here we provide a map for when these effects will meaningfully influence force capacity and an example of their contributions to force production during a static task, namely standing.

physiology↗

Non-motor effects of subthalamic nucleus stimulation in Parkinson's patients

IntroductionThe existing white matter connectivity analyses of the subthalamic region have mainly included the motor effects of deep brain stimulation. We investigate white matter connectivity associated with the stimulation-induced non-motor acute clinical effects in three domains: mood changes, dizziness and sweating. MethodsUsing whole brain probabilistic tractography and seeding from the volumes of tissue activation, connectivity maps were generated and statistically compared across patients. The cortical voxels associated with each non-motor domain were compared with stimulation-induced motor improvements in a multivariate model. The resulting voxels maps were thresholded for false discovery (FDR q<0.05) and clustered using a multimodal atlas. To understand the role of local pathways in the subthalamic region, a group level parcellation was performed for each non-motor domain. ResultsThe non-motor effects are rarely observed during stimulation titration: from 1100 acute clinical effects, mood change was observed in 14, dizziness in 23, and sweating in 20. Distinct cortical clusters were associated with each domain, notably mood change was associated with voxels in salience network and dizziness with voxels in visual association cortex. The subthalamic parcellation yielded a medio-lateral gradient with motor parcel being lateral and the non-motor parcels being medial. We also observed an antero-posterior organization in the medial non-motor clusters with mood changes (anterior), dizziness and sweating (posterior). ConclusionWe interpret these findings based on the literature and foresee these to be useful for shaping the electrical field with the imminent use of steerable DBS electrodes.

neuroscience↗