A5008079896- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Advanced MRI Techniques and Applications
- Epilepsy research and treatment
- Neuroscience and Neuropharmacology Research
- Dementia and Cognitive Impairment Research
- Advanced Neuroimaging Techniques and Applications
- Atomic and Subatomic Physics Research
- Pain Mechanisms and Treatments
- Memory and Neural Mechanisms
- Hereditary Neurological Disorders
- Gene Regulatory Network Analysis
- Sleep and Wakefulness Research
- Neuroscience and Neural Engineering
- Botulinum Toxin and Related Neurological Disorders
- Neurological disorders and treatments
- Olfactory and Sensory Function Studies
Cardiff University
2019-2025
University of Birmingham
2021-2024
University of Exeter
2016-2020
Physical Sciences (United States)
2019
Engineering and Physical Sciences Research Council
2019
Wellcome Trust
2019
Living Systems (United States)
2019
Abstract The dynamics of the resting brain exhibit transitions between a small number discrete networks, each remaining stable for tens to hundreds milliseconds. These functional microstates are thought be building blocks spontaneous consciousness. electroencephalogram (EEG) is useful tool imaging microstates, and EEG microstate analysis can potentially give insight into altered underpinning cognitive impairment in disorders such as Alzheimer’s disease (AD). Since non-invasive relatively...
Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer's disease (AD). A large body evidence shows that, compared healthy controls (HC), AD is power increases in lower EEG frequencies (delta and theta) decreases higher (alpha beta), together slowing the peak alpha frequency. However, pathophysiological processes underlying these changes remain unclear. For instance, recent studies have...
Chronic pain presents an enormous personal and economic burden there is urgent need for effective treatments. In a mouse model of chronic neuropathic pain, selective silencing key neurons in spinal signalling networks with botulinum constructs resulted reduction behaviours associated the peripheral nerve. However, to establish clinical relevance it was important know how long this period lasted. Now, we show that neuronal concomitant mechanical thermal hypersensitivity lasts up 120d...
EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition disease. A key limitation of conventional that it must be performed at the sensor level, therefore gives limited anatomical insight. Here, we generalise methodology applicable source-reconstructed electrophysiological data. Using simulations a neural-mass network model, first established validity robustness proposed method. MEG resting-state data, uncovered ten microstates with...
Abstract Noninvasive functional neuroimaging of the human brain can give crucial insight into mechanisms that underpin healthy cognition and neurological disorders. Magnetoencephalography (MEG) measures extracranial magnetic fields originating from neuronal activity with high temporal resolution, but requires source reconstruction to make neuroanatomical inferences these signals. Many algorithms are available, have been widely evaluated in context localizing task‐evoked activities. However,...
The effectiveness of intracranial electroencephalography (iEEG) to inform epilepsy surgery depends on where iEEG electrodes are implanted. This decision is informed by noninvasive recording modalities such as scalp EEG. Herein we propose a framework interrogate EEG and determine lateralization aid in electrode implantation.We use eLORETA map source activities from seizure epochs recorded consider 15 regions interest (ROIs). Functional networks then constructed using the phase-locking value...
Functional and structural disconnection of the brain is a prevailing hypothesis to explain cognitive impairment in Alzheimer's Disease (AD). We aim understand link between alterations networks using functional connectivity analysis modelling.EEG was recorded from 21 AD patients 26 controls, mapped into source space eLORETA, calculated phase locking factor. The mini-mental state exam (MMSE) used assess impairment. A computational model uncover mechanisms altered connectivity.Small-worldness...
Abstract Objective This study was undertaken to validate a set of candidate biomarkers seizure susceptibility in retrospective, multisite case–control study, and determine the robustness these derived from routinely collected electroencephalography (EEG) within large cohort (both epilepsy common alternative conditions such as nonepileptic attack disorder). Methods The database consisted 814 EEG recordings 648 subjects, eight National Health Service sites across UK. Clinically noncontributory...
Abstract Electroencephalography (EEG) has shown potential for identifying early-stage biomarkers of neurocognitive dysfunction associated with dementia due to Alzheimer’s disease (AD). A large body evidence shows that, compared healthy controls (HC), AD is power increases in lower EEG frequencies (delta and theta) decreases higher (alpha beta), together slowing the peak alpha frequency. However, pathophysiological processes underlying these changes remain unclear. For instance, recent...
People with Alzheimer's disease (AD) are 6-10 times more likely to develop seizures than the healthy aging population. Leading hypotheses largely consider hyperexcitability of local cortical tissue as primarily responsible for increased seizure prevalence in AD. However, general population people epilepsy, large-scale brain network organization additionally plays a role determining likelihood and phenotype. Here, we propose that alterations seen AD may contribute likelihood. To test this...
Abstract Non-invasive functional neuroimaging of the human brain at rest can give crucial insight into mechanisms that underpin healthy cognition and neurological disorders. Magnetoencephalography (MEG) measures extracranial magnetic fields originating from neuronal activity with very high temporal resolution, but requires source reconstruction to make neuroanatomical inferences these signals. Many algorithms for task-based MEG data are available. However, no consensus yet exists on optimum...
Abstract Individuals are different in their behavioural responses and cognitive abilities. Neural underpinnings of individual differences largely unknown. Here, by using multimodal imaging data including diffusion MRI, functional MRI MEG, we show the consistency interindividual variation connectivity across modalities. We demonstrated that regional variability structural connectomes is characterized higher association cortices lower sensory visual cortices. This pattern consistent all...
Abstract Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) multimodal connectivity. Structural is characterized by higher ISV association cortices including core multiple-demand network lower sensorimotor cortex. MEG exhibits frequency-dependent...
The entorhinal cortex is a crucial component of our memory and spatial navigation systems one the first areas to be affected in dementias featuring tau pathology, such as Alzheimer's disease frontotemporal dementia. Electrophysiological recordings from principle cells medial (layer II stellate cells, mEC-SCs) demonstrate number key identifying properties including subthreshold oscillations theta (4-12 Hz) range clustered action potential firing. These single cell are correlated with network...
Beta-frequency oscillations (20-30 Hz) are prominent in both human and rodent electroencephalogram (EEG) recordings. Discrete epochs of beta (or Beta2) prevalent the hippocampus other brain areas during exploration novel environments. However, little is known about spatial distribution temporal relationships across cortex response to novelty. To investigate this, mice fitted with 30-channel EEG-style multi-electrode arrays underwent a single recording session environment. While changes...
Abstract INTRODUCTION Elucidating and better understanding functional biomarkers of Alzheimer’s disease (AD) is crucial. By analysing a detailed longitudinal dataset, this study aimed to create model-based toolset characterise understand the conversion mild cognitive impairment (MCI) AD. METHODS EEG, MRI, neuropsychological data were collected from participants in San Marino: AD (n = 10), MCI 20), controls 11). Across two additional years, classified as converters or non-converters. RESULTS...
Abstract EEG microstate analysis is a useful approach for studying brain states - nicknamed ‘atoms of thought’ and their fast transitions in healthy cognition disease. A key limitation conventional that it must be performed at the sensor level, therefore gives limited anatomical insight into cortical mechanisms underpinning these states. In this study, we generalise methodology to applicable source-reconstructed electrophysiological data. Using simulations neural-mass network model, first...
Abstract Introduction Electroencephalogram (EEG) is a potentially useful clinical tool for aiding diagnosis of Alzheimer’s disease (AD). We hypothesized we can increase the accuracy EEG AD using microstates, which are epochs quasi-stability at millisecond scale. Methods was collected from two independent cohorts and control participants cohort mild cognitive impairment (MCI) patients with four-year follow-up. Microstates were analysed, including novel measure complexity. Results Microstate...
Abstract People with Alzheimer’s disease (AD) are 6-10 times more likely to develop seizures than the healthy aging population. Leading hypotheses largely consider increased excitability of local cortical tissue as primarily responsible for seizure prevalence in AD. However, both dynamics and large-scale brain network structure believed be crucial determining likelihood phenotype. In this study, we combine computational modelling electrophysiological data demonstrate a potential mechanism...
Abstract EEG microstate analysis is an approach to study brain states and their fast transitions in healthy cognition disease. A key limitation of conventional that it must be performed at the sensor level, therefore gives limited anatomical insight. Here, we generalise methodology applicable source-reconstructed electrophysiological data. Using simulations a neural-mass network model, first established validity robustness proposed method. MEG resting-state data, uncovered ten microstates...
Abstract +microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG literature and toolboxes by including algorithms analysis other neuroimaging modalities such as sensor-space MEG source-space data. includes codes performing individual- group-level in resting-state task-based data event-related potentials/fields. Functions are included to visualise perform statistical of sequences, novel advanced approaches microstate-segmented connectivity...