Biology subjects

McColgan, P.

Publications and source records attributed to McColgan, P..

9 recordsLinked to original sources

bioRxiv2026

Evolution of the motor cortex microstructure and its lateralization: a comparative study of chimpanzees and humans

Human hand coordination exceeds that of other species, including great apes, and is marked by pronounced right-hand dominance. This specialization parallels an expansion of its cortical representation, forming the hand-knob in the motor cortex. In humans, this region shows high myelination on quantitative MRI (qMRI), but whether this feature is shared with great apes remains unclear. It is also unknown whether increased right-hand dominance in humans is mirrored by greater hemispheric asymmetry in cortical microstructure. Using high-resolution qMRI, we compared motor cortex subdivisions controlling the leg, hand, and face in humans and chimpanzees. We found consistently higher myelin and iron content in the hand-knob in both species, suggesting an evolutionarily conserved role. However, only humans showed enhanced rightward lateralization. These results highlight both conserved and species-specific features of the motor cortex, offering insights into the evolution of manual dexterity and handedness.

neuroscience↗

bioRxiv2023

Neuroimaging and plasma marker evidence for white matter macrostructure loss in Parkinsons disease

Parkinsons disease (PD) is the second commonest neurodegenerative disorder and over half of patients progress to postural instability, dementia or death within 10 years of diagnosis. However, onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in the underlying pathological process. Improved biomarkers of poor outcomes would be helpful for targeted treatment, but most studies to-date have been limited to a single modality or the assessment of patients with established cognitive impairment. Here, we use multimodal neuroimaging and plasma biomarkers in 98 patients with PD and 28 age-matched controls followed-up over 3 years, including: gray matter (cortical thickness), white matter (macrostructure: fibre-cross section and microstructure: fibre density) at whole-brain and tract level, structural and functional connectivity and plasma levels of neurofilament light chain (NFL) and phosphorylated tau (p-tau) 181. We show extensive reductions in fibre cross-section and structural connectivity in PD with poor outcomes, with preserved gray matter and functional connectivity. NFL, but not p-tau181 levels was increased in PD with poor outcomes and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma NFL may be useful biomarkers of poor outcomes in PD. As new targeted treatments are emerging, these biomarkers show important potential to aid patient selection for treatments and improve stratification to clinical trials.

neuroscience↗

bioRxiv2022

Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis

Quantitative MRI (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (R1), effective transverse relaxation rate (R2*), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (R2* at 3T, R1 at 7T), endothelial cells (R1 and MTsat at 3T), microglia (R1 and MTsat at 3T, R1 at 7T), and oligodendrocytes (R1 at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.

neuroscience↗

bioRxiv2021

Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

BackgroundVisual hallucinations in Parkinsons disease (PD) are transient, suggesting a change in dynamic brain states. However, the causes underlying these dynamic brain changes are not known. MethodsFocusing on fundamental network properties of integration and segregation, we used rsfMRI to examine alterations in temporal dynamics in PD patients with hallucinations (n=16) compared to those without hallucinations (n=75) and a group of normal controls (n=32). We used network control theory to examine how structural connectivity guides transitions between functional states. We then studied the brain regions most involved in these state transitions, and examined corresponding neurotransmitter density profiles and receptor gene expression in health. ResultsThere were significantly altered temporal dynamics in PD with hallucinations, with an increased proportion of time spent in the Segregated state compared to non-hallucinators and controls; less between-state transitions; and increased dwell time in the Segregated state. The energy cost needed to transition from integrated-to-segregated state was lower in PD-hallucinators compared to non-hallucinators. This was primarily driven by subcortical and transmodal cortical brain regions, including the thalamus and default mode network regions. The regional energy needed to transition from integrated-to-segregated state was significantly correlated with regional neurotransmitter density and gene expression profiles for serotoninergic (including 5HT2A), GABAergic, noradrenergic and cholinergic but not dopaminergic density profiles. ConclusionsWe describe the patterns of temporal functional dynamics in PD-hallucinations, and link these with neurotransmitter systems involved in early sensory and complex visual processing. Our findings provide mechanistic insights into visual hallucinations in PD and highlighting potential therapeutic targets.

neuroscience↗

bioRxiv2021

Timing of selective basal ganglia white matter loss in Huntington's disease

ObjectivesTo investigate the timeframe prior to symptom onset when cortico-basal ganglia white matter (WM) loss begins in premanifest Huntingtons disease (preHD), and which striatal and thalamic sub-region WM tracts are most vulnerable. MethodsWe performed fixel-based analysis, which allows resolution of crossing WM fibres at the voxel level, on diffusion tractography derived WM tracts of striatal and thalamic sub-regions in two independent cohorts; TrackON-HD, which included 72 preHD (approx. 11 years before disease onset) and 85 controls imaged at three time points over two years; and the HD young adult study (HD-YAS), which included 54 preHD (approx. 25 years before disease onset) and 53 controls, imaged at one time point. Group differences in fibre density and cross section (FDC) were investigated. ResultsWe found no significant group differences in cortico-basal ganglia sub-region FDC in preHD gene carriers 25 years before onset. In gene carriers 11 years before onset, there were reductions in striatal (limbic and caudal motor) and thalamic (premotor, motor and sensory) FDC at baseline, with no significant change over 2 years. Caudal motor-striatal, pre-motor-thalamic, and primary motor-thalamic FDC at baseline, showed significant correlations with the Unified Huntingtons disease rating scale (UHDRS) total motor score (TMS). Limbic cortico-striatal FDC and apathy were also significantly correlated. ConclusionsOur findings suggest that the initiation of disease modifying therapies 25 years before onset could protect these important brain networks from undergoing neurodegeneration and highlight selectively vulnerable sub-regions of the striatum and thalamus that may be important targets for future therapies.

neuroscience↗

bioRxiv2020

Visual dysfunction predicts cognitive impairment and white matter degeneration in Parkinson's disease

Visual dysfunction predicts dementia in Parkinsons disease (PD), but whether this translates to structural change is not known. We aimed to identify longitudinal white matter changes in patients with Parkinsons disease and low visual function and also in those who developed mild cognitive impairment (MCI). We used fixel-based analysis to examine longitudinal white matter change in PD. Diffusion MRI and clinical assessments were performed in 77 patients at baseline (22 low visual function /55 intact vision; and 13 MCI, 13 MCI converters /51 normal cognition) and 25 controls and again after 18 months. We compared micro-structural changes in fibre density, macro-structural changes in fibre bundle cross-section (FC) and combined fibre density and cross-section across white matter, adjusting for age, gender and intracranial volume. Patients with Parkinsons and visual dysfunction showed worse cognitive performance at follow up and were more likely to develop MCI compared with those with normal vision (p=0.008). Parkinsons with poor visual function showed diffuse micro-structural and macro-structural changes at baseline, whereas those with MCI showed fewer baseline changes. At follow-up, Parkinsons with low visual function showed widespread macrostructural changes, involving the fronto-occipital fasciculi, external capsules, and middle cerebellar peduncles bilaterally. No longitudinal change was seen in baseline MCI or in MCI converters, even when the two groups were combined. Parkinsons patients with poor visual function show increased white matter damage over time, providing further evidence for visual function as a marker of imminent cognitive decline.

neuroscience↗

bioRxiv2020

Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics: a framework for tracking neurodegenerative disease

Cortical layer-specific ultra-high field MRI has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease. Here we compare cortical layer-specificity for a 7T multi-parametric mapping (MPM) 500m whole brain acquisition to the von Economo and Big Brain post-mortem histology atlases. We also investigate the relationship between 7T MPMs, layer-specific gene expression and Huntingtons disease related genes, using the Allen Human Brain atlas. Finally we link MPM cortical depth measures with white matter connections using high-fidelity diffusion tractography from a 300mT/m Connectom MRI system. We show that R2* across cortical depths is highly correlated with layer-specific cell number, cell staining intensity and gene expression. Furthermore white matter connections were highly correlated with grey matter R1 and R2* across cortical depths. These findings demonstrate the potential of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease.

neuroscience↗

bioRxiv2018

Stability and sensitivity of structural connectomes: effect of thresholding and filtering and demonstration in neurodegeneration

Structural connectomes derived using diffusion tractography are increasingly used to investigate white matter connectivity in neurological diseases. However inherent biases in diffusion tractography algorithms may lead to both false negatives and false positives in connectome construction. A range of graph thresholding approaches and more recently several streamline filtering algorithms have been developed to address these issues. However there is no consensus in the literature regarding the best available approach. Using a cohort of Huntingtons disease patients and healthy controls we compared the effect of several graph thresholding strategies: proportional, absolute, consensus and consistency thresholding, with and without streamline filtering, using Spherical Deconvolution Informed Filtering of tractograms (SIFT2) algorithm. We examined the effect of thresholding strategies on the stability of graph theory metrics and the sensitivity of these measures in neurodegeneration. We show that while a number of graph thresholding procedures result in stable metrics across thresholds, the detection of group differences is highly variable. We also showed that the application of streamline filtering using SIFT2 resultes in better detection of group differences and stronger clinical correlations. We therefore conclude that the application of SIFT2 streamline filtering without graph thresholding may be sufficient for structural connectome construction.

neuroscience↗

bioRxiv2018

Assessment of Functional Connectome Construction Strategies in Neurodegeneration

Connectomics can be used to investigate functional brain networks in neurodegenerative diseases including Huntingtons disease (HD). In this developing field, different connectome construction strategies have emerged in parallel. However, there is a need to understand the influences of different strategies on subsequent analyses when constructing a connectome. This study systematically compares connectome construction strategies based on their biological relevance to functional networks in neurodegeneration.\n\nWe asked which functional connectome construction strategy was best able to discriminate HD gene carriers from healthy controls, and how such a strategy affected modular organization of the network. The major factors compared were principal component-based correction versus wavelet decomposition for physiological noise correction, the type of parcellation atlas (functional, structural and multi-modal), weighted versus binarized networks, and unthresholded versus proportionally thresholded networks. We found that principal component-based correction generated the most discriminatory connectomes, while binarization and proportional thresholding did not increase discrimination between HD gene carriers and healthy controls. When a functional parcellation atlas was used, the highest discrimination rates were obtained. We observed that the group differences in modular organization of the functional connectome were greatly affected by binarization and thresholding, showing no consistent pattern of modularity.\n\nThis study suggests that functional connectome construction strategies using principal component-based correction and weighted unthresholded connectivity matrices may outperform other strategies.

neuroscience↗