Biology subjects

Carmichael, D. W.

Publications and source records attributed to Carmichael, D. W..

4 recordsLinked to original sources

bioRxiv2026

Delineating the heartbeat-evoked potential from cardiac artefact

Introduction The heartbeat-evoked potential (HEP) is widely interpreted as an EEG/MEG marker of cortical processing of cardiac afferent signals. It is superimposed on electrical and mechanical signals generated by the heartbeat. Because the neural response and cardiac artefact share the same trigger, conventional averaging and blind-source correction lack an observable cardiac-only reference. Methods We used clinically acquired EEGs with isoelectric-appearing cerebral activity and preserved cardiac activity as a negative control for non-neural heartbeat-locked scalp signal. Thirty-nine isoelectric participants were compared with 118 heart-rate-matched participants whose clinical EEGs were reported as normal. Participant-level heartbeat averages were analysed using covariate-adjusted spatiotemporal permutation tests. We characterised interindividual cardiac-artefact morphology and tested the primary group contrast across average-reference, surface-Laplacian and cardiac-artefact-directed ICA analyses, with pseudotrial correction for heartbeat-independent EEG activity. Results Cardiac-artefact morphology varied markedly across isoelectric participants and was predominantly posterior or posterolateral. In the prespecified primary analysis, controls showed a negative frontocentral cluster persisted at 90-365 ms, p=.016, and a posterior cluster at 145-310 ms, p=.03. The topography of the first cluster aligns with the spatiotemporal characteristics of the early window of the HEP as identified in the literature. This cluster was negative in polarity at the scalp. This suggests positive voltage changes in the early HEP are in fact reductions in HEP activity. Exploratory analyses explored the effects of montage, and artefact correction with independent component analysis to remove CA. There was no significant group difference in ECG. Conclusion These findings provide an important first empirical scalp-level dissociation of the early HEP from CA using an inversion-of-ground-truth approach. A robustly observed cluster of difference, consistent with the early HEP, suggests that this part of the HEP is a distinct, frontocentral, negative cortical response.

neuroscience↗

bioRxiv2022

Widespread, depth-dependent microstructural damage in the cortex of children with drug resistant focal epilepsy: A quantitative T1 and T2 mapping study

ObjectiveTissue abnormalities in focal epilepsy may extend beyond the presumed focus. The underlying pathophysiology of these broader changes is unclear, and it is not known whether they result from ongoing disease processes, treatment-related side-effects, or whether they emerge earlier. Few studies have focused on the period of onset for most focal epilepsies, childhood. Fewer still have utilised quantitative MRI, which may provide a more sensitive and interpretable measure of tissue microstructural change. Here, we aimed to determine common spatial modes of changes in cortical architecture in children with heterogeneous drug-resistant focal epilepsy and, secondarily, whether changes were related to disease severity. MethodsTo assess cortical microstructure, quantitative T1 and T2 relaxometry (qT1 and qT2) was measured in 43 children with drug-resistant focal epilepsy [age-range=4-18 years] and 46 typically-developing children [age-range=2-18 years]. We assessed depth-dependent qT1 and qT2 values across the neocortex, as well as their gradient of change across cortical depths. We also determined whether global changes seen in group analyses were driven by focal pathologies in individual patients. Finally, as a proof-of-concept, we trained a classifier using qT1 and qT2 gradient maps from patients with radiologically-defined abnormalities (MRI-positive) and healthy controls, and tested if this could classify patients without reported radiological abnormalities (MRI-negative). ResultsWe uncovered depth-dependent qT1 and qT2 increases in widespread cortical areas in patients, likely representing microstructural alterations in myelin or gliosis. Changes did not correlate with disease severity measures, suggesting they may represent antecedent neurobiological alterations. Using a classifier trained with MRI-positive patients and controls, sensitivity was 62% at 100% specificity on held-out MRI-negative patients. SignificanceThese findings suggest the presence of a potential imaging endophenotype of focal epilepsy, detectable irrespective of radiologically-identified abnormalities, and potentially evident pre-symptomatically. Key PointsO_LIWe assessed cortical microstructure in children with focal epilepsy C_LIO_LIQuantitative T1 and T2 relaxometry (qT1 and qT2) was measured in the neocortex C_LIO_LIPatients showed extensive qT1/qT2 increases and intracortical organization changes C_LIO_LIAlterations may appear during cerebral development, prior to disease onset C_LI

neuroscience↗

bioRxiv2020

Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity

BackgroundTranscranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure. ObjectivesIn this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity. MethodsWe applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n=22) and TBI participants (n=34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure. ResultsWe find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional - in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region. ConclusionsOur results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation.

neuroscience↗

bioRxiv2017

Measurement of the mapping between intracranial EEG and fMRI recordings in the human brain

There are considerable gaps in our understanding of the relationship between human brain activity measured at different temporal and spatial scales by intracranial electroencephalography and fMRI. By comparing individual features and summary descriptions of intracranial EEG activity we determined which best predict fMRI changes in the sensorimotor cortex in two brain states: at rest and during motor performance. We also then examine the specificity of this relationship to spatial colocalisation of the two signals.\n\nWe acquired electrocorticography and fMRI simultaneously (ECoG-fMRI) in the sensorimotor cortex of 3 patients with epilepsy. During motor activity, high gamma power was the only frequency band where the electrophysiological response was colocalised with fMRI measures across all subjects. The best model of fMRI changes was its principal components, a parsimonious description of the entire ECoG spectrogram. This model performed much better than a model based on the classical frequency bands both during task and rest periods or models derived on a summary of cross spectral changes (e.g. root mean squared EEG frequency). This suggests that the region specific fMRI signal is reflected in spatially and spectrally distributed EEG activity.

neuroscience↗