Biology subjects

Steele, C. J.

Publications and source records attributed to Steele, C. J..

At least 19 recordsLinked to original sources

bioRxiv2026

What EEG doesn't see: a whole-brain MEG map of sleep spindles and slow oscillations

Sleep spindles and slow oscillations (SOs) are hallmarks of non-rapid eye movement (NREM) sleep, linked to memory consolidation and restorative functions. They are usually detected in one or a few scalp electroencephalography (EEG) channels with parameters that vary across studies, and serve as the reference even in magnetoencephalography (MEG), fMRI and intracranial studies. We argue that these choices filter which neural activity is captured. Nineteen young adults took a daytime nap during simultaneous MEG and EEG. Using MEG source imaging across 416 cortical, subcortical and cerebellar regions, we mapped the amplitude and density of SOs (0.5-4 Hz, and 0.5-2 and 2-4 Hz separately) and of spindles (9-18 Hz, and slow, 9-12.9 Hz, and fast, 13-18 Hz, separately), and related each region's activity to a single scalp derivation (Cz-M1). Both rhythms were detected throughout the brain, including the thalamus, hippocampus, amygdala, basal ganglia and cerebellum. The balance between bands varied across regions: fast spindles predominated over slow spindles along the dorsal midline, around the central sulcus and in the thalamus, slow spindles predominated in occipital cortex and the cerebellar hemispheres, and 2-4 Hz SOs were relatively most prominent in occipital cortex. Amplitude and density formed reliable but distinct maps: regions with larger fast spindles also had more of them, whereas SOs, and slow spindles once source depth was controlled, were larger where they were less frequent. More SOs were detected in every region than at Cz-M1, whereas more fast spindles were detected at Cz-M1 than in any single region. Around the SO, slow-spindle activity had the same timing at the scalp and in the sources, but the up-state increase in fast-spindle activity seen at the scalp was absent from local sources. Slow spindles were the most strongly shared events, and sensorimotor sources the most scalp-like. Thus, a single scalp derivation offers a selective and partly composite view of sleep oscillations, with implications for interpreting their functional roles and for targeting them with closed-loop auditory stimulation

neuroscience↗

bioRxiv2026

Regional distribution of white matter hyperintensity burden in coronary artery disease and links with coronary revascularization procedure

IntroductionCoronary artery disease (CAD) increases the risk of cerebrovascular events, yet early brain injury in this population remains poorly characterized. White matter hyperintensities (WMHs), a biomarker of cerebrovascular lesions, are prevalent in CAD and are linked to risk of stroke. Beyond total burden, spatial distribution of WMHs carries pathological significance and is critical for understanding CAD-related injury. While clinical outcomes including coronary revascularization procedure and myocardial infarction influence CAD prognosis, their impact on WMH burden remains unclear. MethodsThis study investigated regional WMH burden in CAD and its relationship with clinical characteristics. 82 adults over 50 years participated, including 44 individuals with CAD and 38 controls. WMHs were segmented from fluid attenuated inversion recovery and T1-weighted MRI and categorized as total, periventricular, deep, and superficial regions. History of myocardial infarction and coronary revascularization (coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI)), was obtained from medical files. ResultsIndividuals with CAD exhibited higher total, periventricular, and deep WMH volumes than controls. Participants who underwent CABG had higher superficial WMH volumes than those with PCI, suggesting greater disease severity influences WMH burden. ConclusionCAD is characterized by a distinct pattern of cerebrovascular vulnerability, with revascularization procedures influencing WMH burden

neuroscience↗

bioRxiv2026

EEG-SSFormer: Towards a Robust Mamba-Based Architecture for Dementia Detection from Resting State Electroencephalography

Resting-state electroencephalography (rs-EEG) offers a cost effective and portable alternative to conventional neuroimaging for dementia screening, yet the lengthy, multichannel nature of rs-EEG makes learning robust representations challenging. Convolutional and Transformer based architectures dominate current deep learning based approaches, but often struggle with long-range dependencies and may not properly preserve channel-dependent features. In this work, we propose EEG-ChiMamba, a state space model based architecture designed for the classification of mild cognitive impairment (MCI) and dementia from normal controls using raw channel-independent rs-EEG signals. Our method decouples channel-wise representation learning from modeling cross-channel interactions and leverages Mamba layers for effective long-sequence modeling. We evaluate our method on the Chung-Ang University EEG dataset (CAUEEG) with 1,155 subjects, the largest public rs-EEG dataset for challenging MCI and dementia differential diagnosis. We achieve a 3-class accuracy of 57.65% using a strict subject-wise split, and relate task-specific features learned by our model as revealed by feature occlusion-based explainability techniques to clinical literature, highlighting that state space models can facilitate interpretable and scalable clinical rs-EEG screening tools for cognitive degeneration. The code for the study is publicly available at: https://github.com/HealthX-Lab/EEG-ChiMamba

neuroscience↗

bioRxiv2025

Patterns of Structural Disconnection Driving Proprioceptive Deficits After Stroke

BackgroundStroke is a leading cause of death and disability worldwide, with proprioceptive impairments affecting up to 64% of survivors. These impairments hinder sensorimotor function and motor recovery, significantly impacting post-stroke disability and quality of life. Proprioception depends on an integrated network of brain regions but remains underexplored due to limitations in clinical assessments, making it difficult to identify precise links between stroke- related damage and functional deficits. To address this, we combined quantitative proprioceptive measurements with Connectome-based Lesion-Symptom Mapping (CLSM) to identify white matter (WM) disconnection patterns underlying proprioceptive deficits following sensorimotor stroke. MethodsIn this observational study, we investigated the relationship between WM disconnection and proprioceptive deficits in 39 chronic stroke survivors with paretic arm function (>6 months post-stroke; 13 females; aged 35-81) using CLSM and kinematic assessments. Lesions were manually delineated from 3T MRI scans, and proprioception was quantified using the Arm Position Matching (APM) task on the KINARM Exoskeleton. Patient-specific voxel-wise WM disconnection maps were generated using the Tractography Lesion Assessment Standard (TractLAS), which quantifies disconnection relative to a healthy WM connectome. Proprioceptive scores were regressed against disconnection maps using voxel-wise linear regressions (family-wise error corrected, controlled for age and sex). ResultsOur disconnectome-based approach identified a network of regions where proprioceptive deficits were significantly associated with WM disconnection (d = 0.55-1, p < .005 FWE, t = 3.48-6.35). These included tracts previously implicated in proprioceptive function (superior longitudinal fasciculus, middle longitudinal fasciculus, and arcuate fasciculus) and beyond (medial lemniscus, spinothalamic tract, posterior thalamic radiation). ConclusionWe provide evidence that post-stroke proprioceptive impairments arise from network- wide WM disconnection in several key tracts that mediate proprioceptive function. This study highlights the benefits of using CLSM to assess stroke-related proprioceptive deficits and offers a framework for network-informed assessments of functional impairments that can be used for targeted therapies post-stroke.

neuroscience↗

bioRxiv2025

Multivariate white matter microstructure alterations in older adults with coronary artery disease

Patients with coronary artery disease (CAD) face an increased risk of cognitive impairment, dementia, and stroke. While white matter (WM) lesions are frequently reported in patients with CAD, the effects on WM microstructure alterations remain largely unknown. We aimed to identify WM microstructural alterations in individuals with CAD compared to healthy controls (HC), and to examine their relationships with cognitive performance. Forty-three (43) patients with CAD and 36 HC aged 50 and older underwent comprehensive neuropsychological testing and multi-modal 3T MRI. A novel multivariate approach - the Mahalanobis distance (D2) - was used to quantify WM abnormalities as the amount of deviation from the HC reference group. D2 integrates multiple MRI-derived diffusion-weighted imaging, R1 relaxometry, and magnetization transfer imaging metrics, while accounting for covariance between metrics. Relationships between WM D2 and cognition (executive function and processing speed) were also assessed. Compared to HCs, patients with CAD had higher D2 values in the whole WM (p=0.009) and in the territories right anterior, bilateral middle, and right posterior cerebral artery territories (p<0.05). Myelin-sensitive metrics, particularly R1 relaxation rate and MT saturation (MTsat), were the most important contributors to D2. Processing speed was positively associated with greater R1 in both the whole WM and left middle cerebral artery territory. These findings suggest that greater WM microstructural alterations observed in patients with CAD were mainly driven by differences in myelin content, as R1 and MTsat were the most important contributors. These alterations may contribute to a heightened risk of cognitive impairment.

neuroscience↗

bioRxiv2024

Sex and APOE4-specific links between cardiometabolic risk factors and white matter alterations in individuals with a family history of Alzheimer's disease

INTRODUCTIONWhite matter (WM) alterations are among the earliest changes in Alzheimers disease (AD), yet limited work has comprehensively characterized the effects of AD risk factors on WM. METHODSIn older adults with a family history of AD, we investigated the sex-specific and APOE genotype-related relationships between WM microstructure and risk factors. Multiple MRI-derived metrics were integrated using a multivariate approach based on the Mahalanobis distance (D2). The links between WM D2 and cognition were also explored. RESULTSWM D2 in several regions was associated with high systolic blood pressure, BMI, and glycated hemoglobin, and low cholesterol, in both males and females. APOE4+ displayed a distinct risk pattern, with LDL-cholesterol having a detrimental effect only in carriers, and this pattern was linked to immediate memory performance. Myelination was the main mechanism underlying WM alterations. DISCUSSIONOur findings reveal that combined exposure to multiple cardiometabolic risk factors negatively impacts microstructural health, which may subsequently affect cognition. Notably, APOE4 carriers exhibited a different risk pattern, especially in the role of LDL, suggesting distinct underlying mechanisms in this group.

neuroscience↗

bioRxiv2024

Microstructural Correlates of Cognitive and Motor Functioning Revealed via Multimodal Multivariate Analysis

Recent advances in cognitive neuroscience emphasise the importance of healthy white matter (WM) for optimal behavioural functioning. It is now widely accepted that brain connectivity via WM contributes to the emergence of behaviour. However, the association between the microstructure of WM fibres and behaviour is poorly understood due to the indirect and overlapping nature of methods used to assess microstructure. Here, we used the Mahalanobis Distance (D2) to integrate 10 metrics of WM derived from multimodal neuroimaging that have strong ties to microstructure. The D2 metric was chosen because it accounts for metrics' covariance as it measures the voxelwise distance between every subject and the average; thus providing a robust multiparametric assessment of microstructure. We used multivariate correlation to examine voxelwise WM-behaviour associations with two cognitive and two motor tasks, which allowed us to compare within and across behavioural domains. We observed that behaviour is organised in cognitive, motor, and integrative components that have widespread associations with WM, from frontal to parietal regions. Notably, the decomposition of these factors shows that tasks traditionally labelled as cognitive also contain motor components that map onto motor-related WM patterns, and that motor tasks likewise contain non-motor components linked to distinct WM microstructural features. Our results highlight the complex nature of the links between microstructure and behaviour, and support the relevance of multivariate modelling when examining brain-behaviour associations.

neuroscience↗

bioRxiv2024

MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics

Multivariate approaches have recently gained in popularity to address the physiological unspecificity of neuroimaging metrics and to better characterize the complexity of biological processes underlying behavior. However, commonly used approaches are biased by the intrinsic associations between variables, or they are computationally expensive and may be more complicated to implement than standard univariate approaches. Here, we propose using the Mahalanobis distance (D2), an individual-level measure of deviation relative to a reference distribution that accounts for covariance between metrics. To facilitate its use, we introduce an open-source python-based tool for computing D2 relative to a reference group or within a single individual: the MultiVariate Comparison (MVComp) toolbox. The toolbox allows different levels of analysis (i.e., group-or subject-level), resolutions (e.g., voxel-wise, ROI-wise) and dimensions considered (e.g., combining MRI metrics or WM tracts). Several example cases are presented to showcase the wide range of possible applications of MVComp and to demonstrate the functionality of the toolbox. The D2 framework was applied to the assessment of white matter (WM) microstructure at 1) the group-level, where D2 can be computed between a subject and a reference group to yield an individualized measure of deviation. We observed that clustering applied to D2 in the corpus callosum yields parcellations that highly resemble known topography based on neuroanatomy, suggesting that D2 provides an integrative index that meaningfully reflects the underlying microstructure. 2) At the subject level, D2 was computed between voxels to obtain a measure of (dis)similarity. The loadings of each MRI metric (i.e., its relative contribution to D2) were then extracted in voxels of interest to showcase a useful option of the MVComp toolbox. These relative contributions can provide important insights into the physiological underpinnings of differences observed. Integrative multivariate models are crucial to expand our understanding of the complex brain-behavior relationships and the multiple factors underlying disease development and progression. Our toolbox facilitates the implementation of a useful multivariate method, making it more widely accessible.

neuroscience↗

bioRxiv2024

Intrinsic structural covariation links cerebellum subregions to the cerebral cortex

The human cerebellum is increasingly recognized to be involved in non-motor and higher-order cognitive functions. Yet, its ties with the entire cerebral cortex have not been holistically studied in a whole-brain exploration with a unified analytical framework. Here, we characterized disso-ciable cortical-cerebellar structural covariation patterns across the brain in n=38,527 UK Bio-bank participants. Our results invigorate previous observations in that important shares of corti-cal-cerebellar structural covariation are described as i) a dissociation between the higher-level cognitive system and lower-level sensorimotor system, as well as ii) an anticorrelation between the visual-attention system and advanced associative networks within the cerebellum. We also discovered a novel pattern of ipsilateral, rather than contralateral, cerebral-cerebellar associations. Furthermore, phenome-wide association assays revealed key phenotypes, including cognitive phenotypes, lifestyle, physical properties, and blood assays, associated with each decomposed covariation pattern, helping to understand their real-world implications. This systems neurosci-ence view paves the way for future studies to explore the implications of these structural covaria-tions, potentially illuminating new pathways in our understanding of neurological and cognitive disorders.

neuroscience↗

bioRxiv2023

Patterns of Cerebellar-Cortical Structural Covariance Mirror Anatomical Connectivity of Sensorimotor and Cognitive Networks

The cortex and cerebellum are densely connected through reciprocal input/output projections that form segregated loop circuits. Anatomical studies in primates and imaging studies in humans show that anterior lobules of the cerebellum exhibit denser connections to sensorimotor and parietal cortical regions, while lobules Crus I and II are more heavily connected to prefrontal regions. The cerebellum and cortex develop in tandem in childhood, leading to the hypothesis that individual differences in structure should be related, especially for connected regions. To test this hypothesis we examined covariation between the volumes of anterior sensorimotor and lateral cognitive lobules of the cerebellum and measures of cortical thickness (CT) and surface surface area (SA) across the whole brain in a sample of 270 young, healthy adults drawn from the HCP dataset. We found that patterns of cerebellar-cortical covariance differed between sensorimotor and cognitive networks such that anterior motor lobules of the cerebellum showed greater covariance with sensorimotor regions of the cortex, while lobules Crus I and Crus II showed greater covariance with frontal and temporal regions. Interestingly, cerebellar volume showed predominantly negative relationships with CT and predominantly positive relationships with SA. Individual differences in SA are thought to be largely under genetic control while CT is thought to be more malleable by experience. This suggests that cerebellar-cortical covariation for SA may be a more stable feature, whereas covariation for CT may be more affected by development. Additionally, dissimilarity metrics revealed that the pattern of covariance showed a gradual transition between sensorimotor and cognitive lobules, consistent with evidence of functional gradients within the cerebellum. Taken together, these findings are consistent with known patterns of structural and functional connectivity between the cerebellum and cortex. They also shed new light on possibly differing relationships between cerebellar volume and cortical thickness and surface area. Finally, our findings are consistent with the interactive specialization framework which proposes that structurally and functionally connected brain regions develop in concert.

neuroscience↗

bioRxiv2022

Visuo-motor transformations in the intraparietal sulcus mediate the acquisition of endovascular medical skill

Performing endovascular medical interventions safely and efficiently requires a diverse set of skills that need to be practised in dedicated training sessions. Here, we used multimodal magnetic resonance (MR) imaging to determine the structural and functional plasticity and core skills associated with skill acquisition. A training group learned to perform a simulator-based endovascular procedure, while a control group performed a simplified version of the task; multimodal MR images were acquired before and after training. Using a well-controlled interaction design, we found strong, multimodal evidence for the role of the intraparietal sulcus (IPS) in endovascular skill acquisition that is in line with previous work implicating the structure in simple visuo-motor and mental rotation tasks. Our results provide a unique window into the multimodal nature of rapid structural and functional plasticity of the human brain while learning a multifaceted and complex clinical skill. Further, our results provide a detailed description of the plasticity process associated with endovascular skill acquisition and highlight specific facets of skills that could enhance current medical pedagogy and be useful to explicitly target during clinical resident training.

neuroscience↗

bioRxiv2022

Assessing Quantitative MRI Techniques using Multimodal Comparisons

The study of brain structure and change in neuroscience is commonly conducted using macroscopic morphological measures of the brain such as regional volume or cortical thickness, providing little insight into the microstructure and physiology of the brain. In contrast, quantitative MRI allows the monitoring of microscopic brain change non-invasively in-vivo, and provides normative values for comparisons between tissues, regions, and individuals. To support the development and common use of qMRI for cognitive neuroscience, we analysed a set of qMRI metrics (R1, R2*, Magnetization Transfer saturation, Proton Density saturation, Fractional Anisotropy, Mean Diffusivity) in 101 healthy young adults. Here we provide a comprehensive descriptive analysis of these metrics and their linear relationships to each other in grey and white matter to develop a more complete understanding of the relationship to tissue microstructure. Furthermore, we provide evidence that combinations of metrics may uncover informative gradients across the brain by showing that lower variance components of PCA may be used to identify cortical gradients otherwise hidden within individual metrics. We discuss these results within the context of microstructural and physiological neuroscience research.

neuroscience↗

bioRxiv2021

Mapping Pontocerebellar Connectivity with Diffusion MRI

The cerebellums involvement in cognitive, affective and motor functions is mediated by connections to different regions of the cerebral cortex. A distinctive feature of cortico-cerebellar loops that has been demonstrated in the animal work is a topographic organization that is preserved across its different components. Here we used tractography derived from diffusion imaging data to characterize the connections between the pons and the individual lobules of the cerebellum, and generate a classification of the pons based on its pattern of connectivity. We identified a rostral to caudal gradient in the pons, similar to that observed in the animal work, such that rostral regions were preferentially connected to cerebellar lobules involved in non-motor, and caudal regions with motor regions. These findings advance our fundamental understanding of the cerebellum, and the classifications we generated provide context for future research into the pontocerebellar tracts involvement in health and disease.

neuroscience↗

bioRxiv2021

Motor Sequences - Separating The Sequence From The Motor. A longitudinal rsfMRI Study

In motor learning, sequence-specificity, i.e. the learning of specific sequential associations, has predominantly been studied using task-based fMRI paradigms. However, offline changes in resting state functional connectivity after sequence-specific motor learning are less well understood. Previous research has established that plastic changes following motor learning can be divided into stages including fast learning, slow learning and retention. A description of how resting state functional connectivity after sequence-specific motor sequence learning (MSL) develops across these stages is missing. This study aimed to identify plastic alterations in whole-brain functional connectivity after learning a complex motor sequence by contrasting an active group who learned a complex sequence with a control group who performed a control task matched for motor execution. Resting state fMRI and behavioural performance were collected in both groups over the course of 5 consecutive training days and at follow-up after 12 days to encompass fast learning, slow learning, overall learning and retention. Between-group interaction analyses showed sequence-specific decreases in functional connectivity during overall learning in the right supplementary motor area (SMA). We found that connectivity changes in key regions of the motor network including the superior parietal cortex (SPC) and primary motor cortex (M1) were not a result of sequence-specific learning but were instead linked to motor execution. Our study confirms the sequence-specific role of SMAthat has previously been identified in online task-based learning studies, and extends it to resting state network changes after sequence-specific MSL.

neuroscience↗

bioRxiv2020

White matter microstructural changes in short-term learning of a continuous visuomotor sequence

Efficient neural transmission is crucial for optimal brain function, yet the plastic potential of white matter (WM) has long been overlooked. Growing evidence now shows that modifications to axons and myelin occur not only as a result of long-term learning, but also after short training periods. Motor sequence learning (MSL), a common paradigm used to study neuroplasticity, occurs in overlapping learning stages and different neural circuits are involved in each stage. However, most studies investigating short-term WM plasticity have used a pre-post design, in which the temporal dynamics of changes across learning stages cannot be assessed. In this study, we used multiple magnetic resonance imaging (MRI) scans at 7 Tesla to investigate changes in WM in a group learning a complex visuomotor sequence (LRN) and in a control group (SMP) performing a simple sequence, for 5 consecutive days. Consistent with behavioral results, where most improvements occurred between the two first days, structural changes in WM were observed only in the early phase of learning (d1-d2), and in overall learning (d1-d5). In LRNs, WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices. Moreover, our structural findings in WM were related to changes in functional connectivity, assessed with resting-state functional MRI data in the same cohort, through analyses in regions of interest (ROIs). Significant changes in WM microstructure were found in a ROI underlying the right supplementary motor area. Together, our findings provide evidence for highly dynamic WM plasticity in the sensorimotor network during short-term MSL.

neuroscience↗

bioRxiv2020

Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging

Cognitive decline occurs in healthy and pathological aging, and both may be preceded by subtle changes in the brain -- offering a basis for cognitive predictions. Previous work has largely focused on predicting a diagnostic label from structural brain imaging. Our study broadens the scope of applications to cognitive decline in healthy aging by predicting future decline as a continuous trajectory, rather than a diagnostic label. Furthermore, since brain structure as well as function changes in aging, it is reasonable to expect predictive gains when using multiple brain imaging modalities. Here, we tested whether baseline multimodal neuroimaging data improve the prediction of future cognitive decline in healthy and pathological aging. Non-brain data (including demographics and clinical and neuropsychological scores) were combined with structural and functional connectivity MRI data from the OASIS-3 project (N = 662; age = 46 - 96y). The combined input data was entered into cross-validated multi-target random forest models to predict future cognitive decline (measured by the Clinical Dementia Rating and the Mini-Mental State Examination), on average 5.8y into the future. The analysis was preregistered and all analysis code is publicly available. We found that combining non-brain with structural data improved the continuous prediction of future cognitive decline (best test-set performance: R2 = 0.42) and that cognitive performance, daily functioning, and subcortical volume drove the performance of our model. In contrast, including functional connectivity did not improve predictive accuracy. In the future, the prognosis of age-related cognitive decline may enable earlier and more effective cognitive, pharmacological, and behavioral interventions to be tailored to the individual.

neuroscience↗

bioRxiv2020

Sex moderates the relationship between aortic stiffness, cognition and cerebrovascular reactivity in healthy older adults

It is well established that sex differences exist in the manifestation of cardiovascular diseases. Arterial stiffness (AS) has been associated with changes in cerebrovascular reactivity (CVR) and cognitive decline in aging. Specifically, older adults with increased AS show a decline on executive function (EF) tasks. Interestingly, the relationship between AS and CVR is more complex, where some studies show decreased CVR with increased AS, and others demonstrate preserved CVR despite higher AS. We investigated the possible role of sex and hematocrit (HCT) on these hemodynamic relationships. Acquisitions were completed in 48 older adults. Dual-echo pCASL data were collected during a hypercapnia challenge. Aortic PWV data was acquired using cine phase contrast velocity series. A moderation model test revealed that sex moderated the relationship between PWV and CVR and PWV and EF. In addition, there was a significant effect of HCT on the sex differences observed in the moderation effect on EF. Together, our results indicate that the relationships between PWV, CVR and EF are in part mediated by sex and HCT. HighlightsO_LIThis study investigates the role of sex on cerebrovascular measures of brain health and congition C_LIO_LISex moderates the relationship between PWV, cerebrovascular reactivity and cognition C_LIO_LIHematocrit influences the sex differences observed C_LI

neuroscience↗

bioRxiv2019

Clinical, imaging genetics and deformation based morphometry study of longitudinal changes after surgery for intractable aggressive behaviour

Intractable aggressive behaviour is a devastating behavioural disorder that reach 30% of psychiatric aggressive patients. Neuromodulatory surgeries may be treatment alternatives to reduce suffering. We investigated the outcomes of bilateral amygdala radiofrequency ablation in four patients with intractable aggressive behaviour (life-threatening-self-injury and social aggression) by studying whole brain magnetic resonance imaging and clinical data. Post-surgery assessments revealed decreases in aggression and agitation and improvements in quality of life. Aggressive behaviour was positively correlated with serum testosterone levels and the testosterone/cortisol ratio in males. No clinically significant side effects were observed. Imaging analyses revealed preoperative amygdala volumes within normal range and confirmed appropriate lesion locations. Reduction in aggressiveness were accompanied by volumetric reduction in brain areas associated with aggressive behaviour (express genes related to aggressive behaviour), and increases in regions related to somatosensation. These findings further elucidates the neurocircuitry of aggression and suggests novel neuromodulation targets.

clinical trials↗