Biology subjects

Hamandi, K.

Publications and source records attributed to Hamandi, K..

10 recordsLinked to original sources

bioRxiv2025

Females with epilepsy show abnormal changes to perimenstrual sensory induced long-term potentiation

IntroductionCatamenial epilepsy refers to a cyclical exacerbation of seizure frequency and/or severity linked to stages of the menstrual cycle. To investigate the contribution of underlying excitatory and inhibitory mechanisms of this exacerbation we induced and measured long-term potentiation (LTP). Oestradiol modulates primarily NMDA receptor driven excitation and would enhance visual LTP. Allopregnanolone modulates GABA receptor mediated inhibition and would suppress visual LTP. MethodA control cohort (n = 25) and a cohort with epilepsy (n = 20) were recruited. Participants took part in a visual LTP task while EEG was recorded. Three study visits were timed to capture the mid-follicular (days +5 to +8), mid-luteal (days -9 to -5) phases, as well as the hormone withdrawal in the perimenstrual phase (days -3 to +2). Blood samples confirmed session timing. Generative computational modelling of thalamocortical changes in the EEG was paired with standard evoked potential analysis. Result17 (age 26 {+/-} 9.40) participants with epilepsy, and a control cohort of 25 (age 30 {+/-} 7.06) without epilepsy completed the study. The P2 visually evoked potential (a positive-going component of the visual event related potential waveform) was significantly more enhanced by LTP induction in the mid-follicular phase than the mid-luteal or perimenstrual phases in the control cohort (F(2, 144) =11.54, p = 0.004 corrected). In contrast, in the epilepsy cohort the P2 was significantly more potentiated in the perimenstrual phase than the mid-follicular or mid-luteal phases (F(2,108) = 12.21, p = 0.005 corrected). The effect of cycle on visual LTP was robust, with only 3/17 participants with epilepsy showing highest P2 modulation in the mid-follicular phase (which is the pattern the healthy cohort showed). The computational modelling showed that in epilepsy, the perimenstrual phase was associated with a decrease in superficial pyramidal grain control as well as decreased LTP driven modulation of feed-forward superficial connections to layer 5 and layer 6 to thalamus. DiscussionOur finding of enhanced visual LTP in the luteal phase and perimenstrual phase of females with epilepsy indicates a breakthrough of glutamatergic excitation. Given the relationship between oestrogen and n-methyl-D-aspartate (NMDA) receptor dependent LTP this is plausibly NMDA receptor driven. Several thalamocortical model parameter changes observed warrant further investigation in studies stratifying participants by catamenial epilepsy type. Overall, while research into allopregnanolone and its inhibitory effects dominate perimenstrual catamenial epilepsy research, this study justifies consideration of the role of seizure exacerbating oestradiol.

neuroscience↗

bioRxiv2025

Associations between epilepsy-related polygenic risk and brain morphology in childhood

AO_SCPLOWBSTRACTC_SCPLOWTemporal lobe epilepsy with hippocampal sclerosis (TLE-HS) is associated with a complex genetic architecture, but the translation from genetic risk factors to brain vulnerability remains unclear. Here, we examined associations between epilepsy-related polygenic risk scores for HS (PRS-HS) and brain structure in a large sample of neurotypical children, and correlated these signatures with case-control findings in in multicentric cohorts of patients with TLE-HS. Imaging-genetic analyses revealed PRS-related cortical thinning in temporo-parietal and fronto-central regions, strongly anchored to distinct functional and structural network epicentres. Compared to disease-related effects derived from epilepsy case-control cohorts, structural correlates of PRS-HS mirrored atrophy and epicentre patterns in patients with TLE-HS. By identifying a potential pathway between genetic vulnerability and disease mechanisms, our findings provide new insights into the genetic underpinnings of structural alterations in TLE-HS and highlight potential imaging-genetic biomarkers for early risk stratification and personalized interventions.

neuroscience↗

bioRxiv2023

Patterns of subregional cerebellar atrophy across epilepsy syndromes: An ENIGMA-Epilepsy study

ObjectiveThe intricate neuroanatomical structure of the cerebellum is of longstanding interest in epilepsy, but has been poorly characterized within the current cortico-centric models of this disease. We quantified cross-sectional regional cerebellar lobule volumes using structural MRI in 1,602 adults with epilepsy and 1,022 healthy controls across twenty-two sites from the global ENIGMA-Epilepsy working group. MethodsA state-of-the-art deep learning-based approach was employed that parcellates the cerebellum into 28 neuroanatomical subregions. Linear mixed models compared total and regional cerebellar volume in i) all epilepsies; ii) temporal lobe epilepsy with hippocampal sclerosis (TLE-HS); iii) non-lesional temporal lobe epilepsy (TLE-NL); iv) genetic generalised epilepsy; and (v) extra-temporal focal epilepsy (ETLE). Relationships were examined for cerebellar volume versus age at seizure onset, duration of epilepsy, phenytoin treatment, and cerebral cortical thickness. ResultsAcross all epilepsies, reduced total cerebellar volume was observed (d=0.42). Maximum volume loss was observed in the corpus medullare (dmax=0.49) and posterior lobe grey matter regions, including bilateral lobules VIIB (dmax= 0.47), Crus I/II (dmax= 0.39), VIIIA (dmax=0.45) and VIIIB (dmax=0.40). Earlier age at seizure onset ({eta}{rho}2max=0.05) and longer epilepsy duration ({eta}{rho}2max=0.06) correlated with reduced volume in these regions. Findings were most pronounced in TLE-HS and ETLE with distinct neuroanatomical profiles observed in the posterior lobe. Phenytoin treatment was associated with reduced posterior lobe volume. Cerebellum volume correlated with cerebral cortical thinning more strongly in the epilepsy cohort than in controls. SignificanceWe provide robust evidence of deep cerebellar and posterior lobe subregional grey matter volume loss in patients with chronic epilepsy. Volume loss was maximal for posterior subregions implicated in non-motor functions, relative to motor regions of both the anterior and posterior lobe. Associations between cerebral and cerebellar changes, and variability of neuroanatomical profiles across epilepsy syndromes argue for more precise incorporation of cerebellum subregions into neurobiological models of epilepsy. Key pointsO_LICerebellar involvement in epilepsy is poorly understood within current cortico-centric models of this disease C_LIO_LIWe used a novel, deep learning segmentation tool to parcellate the cerebellum into 28 anatomical subunits using an international MRI dataset of 1,602 individuals with epilepsy (aged between 18 and 65 years old) including temporal lobe epilepsy with hippocampal sclerosis (TLE-HS, n=562), TLE non-lesional (TLE-NL, n=284), generalised genetic epilepsy (GGE, n=186) and extra temporal focal epilepsy (ETLE, n=251) and 1,022 controls. C_LIO_LIAcross all epilepsies (vs. controls) robust changes in the corpus medullare and posterior lobe "non-motor" regions were observed, with maximal differences in bilateral VIIB and Crus II lobules. Lower volume of these regions correlated with longer disease duration. Anterior "motor lobe" regions were relatively spared. C_LIO_LIFindings were most pronounced in TLE-HS and ETLE groups, with distinct neuroanatomical profiles observed. C_LIO_LICortical thinning was associated with pronounced cerebellar volume loss in TLE-HS epilepsy, relative to controls. C_LI ETHICAL PUBLICATION STATEMENTWe confirm that we have read the Journals position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.

neuroscience↗

bioRxiv2021

The interaction between neural populations: Additive versus diffusive coupling

Models of networks of populations of neurons commonly assume that the interactions between neural populations are via additive or diffusive coupling. When using the additive coupling, a populations activity is affected by the sum of the activities of neighbouring populations. In contrast, when using the diffusive coupling a neural population is affected by the sum of the differences between its activity and the activity of its neighbours. These two coupling functions have been used interchangeably for similar applications. Here, we show that the choice of coupling can lead to strikingly different brain network dynamics. We focus on a model of seizure transitions that has been used both with additive and diffusive coupling in the literature. We consider networks with two and three nodes, and large random and scale-free networks with 64 nodes. We further assess functional networks inferred from magnetoencephalography (MEG) from people with epilepsy and healthy controls. To characterize the seizure dynamics on these networks, we use the escape time, the brain network ictogenicity (BNI) and the node ictogenicity (NI), which are measures of the networks global and local ability to generate seizures. Our main result is that the level of ictogenicity of a network is strongly dependent on the coupling function. We find that people with epilepsy have higher additive BNI than controls, as hypothesized, while the diffusive BNI provides the opposite result. Moreover, individual nodes that are more likely to drive seizures with one type of coupling are more likely to prevent seizures with the other coupling function. Our results on the MEG networks and evidence from the literature suggest that the additive coupling may be a better modelling choice than the diffusive coupling, at least for BNI and NI studies. Thus, we highlight the need to motivate and validate the choice of coupling in future studies. Author summaryMost models of brain dynamics assume that distinct brain regions interact in either an additive or a diffusive way. With additive coupling, each brain region sums incoming signals. In contrast, with diffusive coupling, each region sums the differences between its own signal and incoming signals. Although they are different, these two couplings have been used for very similar applications, particularly within models of epilepsy. Here we assessed the effect of this choice on seizure behaviour. Using a model of seizures and both artificial and real brain networks, we showed that the coupling choice can lead to very different seizure dynamics. We found that networks that are more prone to seizures using one coupling, are less prone to them using the other. Likewise, individual brain regions that are more likely to drive seizures when using additive coupling, are more likely to prevent them when using diffusive coupling. Using real brain networks, we found that the additive coupling predicted higher seizure propensity in people with epilepsy compared to healthy controls, whereas the diffusive coupling did not. Our results highlight the need to justify the choice of coupling used and show that the additive coupling may be a better option in some applications.

neuroscience↗

bioRxiv2021

Short Association Fibre Tractography

It is estimated that in the human brain, short association fibres (SAF) represent more than half of the total white matter volume and their involvement has been implicated in a range of neurological and psychiatric conditions. This population of fibres, however, remains relatively understudied in the neuroimaging literature. Some of the challenges pertinent to the mapping of SAF include their variable anatomical course and proximity to the cortical mantle, leading to partial volume effects and potentially affecting streamline trajectory estimation. This work considers the impact of seeding and filtering strategies and choice of scanner, acquisition, data resampling to propose a whole-brain, surface-based short ([≤]30-40 mm) SAF tractography approach. The framework is shown to produce longer streamlines with a predilection for connecting gyri as well as high cortical coverage. We further demonstrate that certain areas of subcortical white matter become disproportionally underrepresented in diffusion-weighted MRI data with lower angular and spatial resolution and weaker diffusion weighting; however, collecting data with stronger gradients than are usually available clinically has minimal impact, making our framework translatable to data collected on commonly available hardware. Finally, the tractograms are examined using voxel- and surfacebased measures of consistency, demonstrating moderate reliability, low repeatability and high between-subject variability, urging caution when streamline count-based analyses of SAF are performed.

neuroscience↗

bioRxiv2020

Electrophysiological receptor mapping of GABA-A receptors

The non-invasive study of cortical oscillations provides a window onto neuronal processing. Temporal correlation of these oscillations between distinct anatomical regions is considered a marker of functional connectedness. As the most abundant inhibitory neurotransmitter in the mammalian brain, {gamma}-aminobutyric acid (GABA) is thought to play a crucial role in shaping the frequency and amplitude of oscillations, which thereby suggests a role for GABA in shaping the topography of functional activity and connectivity. This study explored the effects of pharmacologically blocking the reuptake of GABA (increasing local concentrations) through oral administration of the GABA transporter 1 (GAT1) blocker tiagabine (15 mg). We show that the spatial distribution of tiagabine-induced activity changes, across the brain, corresponds to group-average flumazenil PET maps of GABAA receptor distribution. In a placebo-controlled crossover design, we collected resting magnetoencephalography (MEG) recordings from 15 healthy male individuals prior to, and at 1-, 3- and 5- hours post, administration of tiagabine and placebo pill. Using leakage-corrected amplitude envelope correlations (AECs), we quantified the functional connectivity in discrete frequency bands across the whole brain, using the 90-region Automatic Anatomical Labelling atlas (AAL90), as well as quantifying the average oscillatory activity across the brain. Analysis of variance in connectivity using a drug-by-session (2x4) design revealed interaction effects, accompanied by main effects of drug and session. Post-hoc permutation testing of each post-drug recording against the respective pre-drug baseline revealed consistent reductions of a bilateral occipital network spanning theta, alpha and beta frequencies, and across 1- 3- and 5- hour recordings following tiagabine, but not placebo. The same analysis applied to activity, across the brain, also revealed a significant interaction, with post-hoc permutation testing demonstrating significant increases in activity across frontal regions, coupled with reductions in activity in posterior regions, across the delta, theta, alpha and beta frequency bands. Crucially, we show that the spatial distribution of tiagabine-induced changes in oscillatory activity overlap significantly with group-averaged maps of the estimated distribution of GABAA receptors, derived from scaled flumazenil volume-of-distribution (FMZ-VT) PET, hence demonstrating a possible mechanistic link between GABA availability, GABAA receptor distribution, and low-frequency network oscillations. We therefore propose that electrophysiologically-derived maps of oscillatory connectivity and activity can be used as sensitive, time-resolved, and targeted receptor-mapping tools for pharmacological imaging at the group level, providing direct measures of target engagement and pharmacodynamics.

neuroscience↗

bioRxiv2020

Network-based atrophy modelling in the common epilepsies: a worldwide ENIGMA study

Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1,021 adults with epilepsy compared to 1,564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy co-localized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Indices of progressive atrophy further revealed a strong influence of connectome architecture on disease progression in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients, and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided novel insights into the macroscale features that shape the pathophysiology of common epilepsies.

neuroscience↗

bioRxiv2019

White matter abnormalities across different epilepsy syndromes in adults: an ENIGMA Epilepsy study

The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analyzed from 1,069 non-epileptic controls and 1,249 patients: temporal lobe epilepsy with hippocampal sclerosis (N=599), temporal lobe epilepsy with normal MRI (N=275), genetic generalized epilepsy (N=182) and nonlesional extratemporal epilepsy (N=193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fiber tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at p<0.001). Across "all epilepsies" lower fractional anisotropy was observed in most fiber tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. Less robust effects were seen with mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Those with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced differences in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and in mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of microstructural abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibers in a large multicentre study of epilepsy. Overall, epilepsy patients showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding new insights into pathological substrates that may be used to guide future therapeutic and genetic studies.

neuroscience↗

bioRxiv2019

Frontoparietal network dynamics impairments in juvenile myoclonic epilepsy revealed by MEG energy landscape

Juvenile myoclonic epilepsy (JME) is a form of idiopathic generalized epilepsy affecting brain activity. It is unclear to what extent JME leads to abnormal network dynamics across functional networks. Here, we proposed a method to characterise network dynamics in MEG resting-state data, combining a pairwise maximum entropy model (pMEM) and the associated energy landscape analysis. Fifty-two JME patients and healthy controls underwent a resting-state MEG recording session. We fitted the pMEM to the oscillatory power envelopes in theta (4-7 Hz), alpha (8-13 Hz), beta (15-25 Hz) and gamma (30-60 Hz) bands in three source-localised resting-state networks: the frontoparietal network (FPN), the default mode network (DMN), and the sensorimotor network (SMN). The pMEM provided an accurate fit to the MEG oscillatory activity in both patient and control groups, and allowed estimation of the occurrence probability of each network state, with its regional activity and pairwise regional co-activation constrained by empirical data. We used energy values derived from the pMEM to depict an energy landscape of each network, with a higher energy state corresponding to a lower occurrence probability. When comparing the energy landscapes between groups, JME patients showed fewer local energy minima than controls and had elevated energy values for the FPN within the theta, beta and gamma-bands. Furthermore, numerical simulation of the fitted pMEM showed that the proportion of time the FPN was occupied within the basins of characteristic energy minima was shortened in JME patients. These network alterations were confirmed by a significant leave-one-out classification of individual participants based on a support vector machine employing the energy values of pMEM as features. Our findings suggested that JME patients had altered multi-stability in selective functional networks and frequency bands in the frontoparietal cortices.\n\nHighlightsO_LIAn energy landscape analysis characterises the dynamics of MEG oscillatory activity\nC_LIO_LIPatients with JME exhibit fewer local minima of the energy in their energy landscapes\nC_LIO_LIJME affects the network dynamics in the frontoparietal network.\nC_LIO_LIEnergy landscape measures allow good single-patient classification.\nC_LI

neuroscience↗

bioRxiv2018

Uncovering a role for the dorsal hippocampal commissure in episodic memory

The dorsal hippocampal commissure (DHC) is a white matter tract that provides inter-hemispheric connections between temporal lobe brain regions. Despite the importance of these regions for learning and memory, there is scant evidence of a role for the DHC in successful memory performance. We used diffusion-weighted MRI (DW-MRI) and white matter tractography to reconstruct the DHC across both humans (in vivo) and nonhuman primates (ex vivo). Across species, our findings demonstrate close consistency between the known anatomy and tract reconstructions of the DHC. Anterograde tract-tracer techniques also highlighted the parahippocampal origins of DHC fibers in nonhuman primates. Finally, we derived Diffusion Tensor MRI (DT-MRI) metrics from the DHC in a large sample of human subjects to investigate whether inter-individual variation in DHC microstructure is predictive of memory performance. The mean diffusivity of the DHC was correlated with performance in a standardised episodic memory task; an effect that was not reproduced in a comparison commissure tract - the anterior commissure. These findings highlight a role for the DHC in episodic memory, and our tract reconstruction approach has the potential to generate further novel insights into the role of this previously understudied white matter tract in both health and disease.

neuroscience↗