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Howells, F. M.

Publications and source records attributed to Howells, F. M..

3 recordsLinked to original sources

Structural Brain Network Alterations in Relation to Treatment and Illness Severity in Bipolar Disorder

BackgroundLarge-scale T1-weighted MRI studies have established grey-matter abnormalities in bipolar disorder (BD), with our group contributing to consensus findings. However, structural connectivity, particularly within emotion- and reward-related circuits, remains poorly understood. Diffusion-weighted MRI (dMRI) enables investigation of white-matter pathways, yet prior work is constrained by small samples, methodological heterogeneity, and unclear medication effects. We conducted the largest dMRI network analysis in BD, relating symptom burden and polypharmacy to tractography-derived connectivity and graph-theoretic metrics. MethodsCross-sectional structural and diffusion MRI scans from 449 individuals with BD (35.7{+/-}12.6 years) and 510 controls (33.3{+/-}12.6 years), aged 18-65, were analyzed across 16 ENIGMA-BD sites. Standardized segmentation/parcellation and constrained spherical deconvolution tractography generated individual structural connectivity matrices. Graph-theoretic metrics of global and subnetwork organization were related to symptom severity and medications. ResultsBD showed widespread network alterations (lower density and efficiency, longer path length, and higher betweenness centrality), altered microstructural organization in a limbic-basal ganglia circuit, and abnormal streamline counts in a default-mode/salience/fronto-limbic-basal ganglia network. Longer illness duration, later onset, and psychosis history were associated with greater abnormalities in network architecture, whereas more manic episodes were associated with greater fronto-limbic connectivity. Antidepressant (particularly SSRI), anticonvulsant, and antipsychotic use related to poorer global and fronto-limbic connectivity; no clear lithium effects emerged. ConclusionsAs the largest structural connectivity study in BD, we reveal widespread disruption in reward and emotion-regulation networks influenced by illness severity and medication use. Results show that multisite harmonization is feasible and highlight ENIGMA-BD as a scalable framework for identifying reproducible neurobiological markers.

neuroscience↗

Estimating multimodal brain variability in schizophreniaspectrum disorders: A worldwide ENIGMA study

ObjectiveSchizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia. MethodsThis meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy. ResultsWe found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region. ConclusionsHigher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

neuroscience↗

Strategic Leadership Coaching supports Young Executives decision-making

Decision-making is central to daily function for executives in any organisation. Strategic leadership coaching (SLC) is an effective way to support complex decision-making, yet empirical neuroscientific data to support is lacking. The purpose of this study was to investigate the effects of SLC on young executives cortical arousal and their neural circuitry activation during the completion of computerized tasks which require activation of decision-making circuitry. We hypothesised SLC would improve cortical arousal when engaged with decision-making tasks, specifically increased electroencephalography (EEG) relative alpha band activity and improved neural circuitry engagement, measured as increased amplitude of event-related potential wave components. This study included thirty-one young male executives, of which eighteen underwent 8 sessions of SLC over two months. EEG records were collected thrice from those who underwent SLC (prior, post, and two months post), and twice from the control group (two months apart). The EEG recording session included completion of two decision-making tasks, an Iowa gambling task and Stroop colour-word conflict task. Finding, SLC increased alpha band activity over left frontal and central electrodes, and increased right parietal N170 amplitude and left parietal P300 amplitude. These findings support our hypothesis, as SLC improved cognitive cortical resources (enhanced alpha) which in turn permitted greater efficiency within decision-making circuitry (increased wave component amplitudes). This study provides the first and necessary neurobiological evidence to support and develop this line of research in SLC, and other forms of coaching, as it adds significant value.

neuroscience↗