Clozapine-induced paroxysmal discharges

PhD ThesisThe atypical antipsychotic clozapine is a widely prescribed and effective treatment for the positive and negative symptoms of schizophrenia, but reports of side effects are common. In one study EEG abnormalities were observed in 53% of patients treated with clozapine, and the absence or presence of EEG abnormalities correlated with the plasma clozapine concentration. Here, epileptiform activity was present in conventional EEG recordings from a 32 year old male patient with psychiatric illness taking clozapine for 3 weeks. Brief (ca.100ms), transient epileptiform spikes occurred at a frequency of approximately 2 per h and originated primarily in parietal cortex. One month after withdrawal of clozapine, epileptiform spikes were no longer present. An in vitro model was developed using the equivalent region of association cortex, namely 2⁰ somatosensory cortex, in normal rat brain slices to probe such activity with increased spatial and temporal resolution, and to investigate mechanisms underlying its generation. Wide band in vitro recordings revealed that clozapine (10-20µM) induced regular, frequent very fast oscillations (VFO, > 70Hz) in this region. These VFO comprised short transient high frequency discharges and were maximal in patches along layer V. The atypical antipsychotic olanzapine, but not the classical antipsychotic haloperidol, also induced prominent VFO in this region. Sharp electrode intracellular recordings revealed that there was almost no correlation between the somatic activity of layer V regular spiking (RS) pyramidal cells and field VFO, but layer V intrinsically bursting (IB) cells did correlate to some extent with the local field. Interestingly, IB cell spikelets were also weakly correlated with field VFO suggesting a role for axonal hyperexcitability in this cell type in the mechanism. Clozapine-induced VFO persisted following blockade of AMPA, NMDA, and GABAA chemical synaptic receptors, and the gap junction blockers carbenoxolone and quinine also failed to significantly attenuate the power of this activity. Although octanol abolished clozapine-induced VFO, it was not clear that this effect resulted from blockade of gap junctions as this drug also blocks spikes. In addition to VFO events, clozapine (10-20µM) also induced occasional, spontaneous transient paroxysmal discharges, similar to the EEG phenomena, in 33% (11/33 slices) of slices in vitro. Sharp electrode intracellular recordings revealed that clozapine- induced full paroxysmal discharges were associated with spikes, EPSPs and IPSPs in layer V RS and IB cells, suggesting that these events were mediated via chemical synaptic transmission in both of these cell types. Multi-electrode array recordings of local field potentials and units suggested that clozapine-induced paroxysmal events started superficially in association cortex, moved deeper and then propagated horizontally along these deep layers. The onset of clozapine-induced VFO was accompanied by a significant elevation in parvalbumin immunoreactivity, particularly in layer II-IV, where there was a greater than twofold increase in the signal, and this may be relevant to the therapeutic action of the drug

Dynamics on networks: the role of local dynamics and global networks on the emergence of hypersynchronous neural activity.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tGraph theory has evolved into a useful tool for studying complex brain networks inferred from a variety of measures of neural activity, including fMRI, DTI, MEG and EEG. In the study of neurological disorders, recent work has discovered differences in the structure of graphs inferred from patient and control cohorts. However, most of these studies pursue a purely observational approach; identifying correlations between properties of graphs and the cohort which they describe, without consideration of the underlying mechanisms. To move beyond this necessitates the development of computational modeling approaches to appropriately interpret network interactions and the alterations in brain dynamics they permit, which in the field of complexity sciences is known as dynamics on networks. In this study we describe the development and application of this framework using modular networks of Kuramoto oscillators. We use this framework to understand functional networks inferred from resting state EEG recordings of a cohort of 35 adults with heterogeneous idiopathic generalized epilepsies and 40 healthy adult controls. Taking emergent synchrony across the global network as a proxy for seizures, our study finds that the critical strength of coupling required to synchronize the global network is significantly decreased for the epilepsy cohort for functional networks inferred from both theta (3-6 Hz) and low-alpha (6-9 Hz) bands. We further identify left frontal regions as a potential driver of seizure activity within these networks. We also explore the ability of our method to identify individuals with epilepsy, observing up to 80% predictive power through use of receiver operating characteristic analysis. Collectively these findings demonstrate that a computer model based analysis of routine clinical EEG provides significant additional information beyond standard clinical interpretation, which should ultimately enable a more appropriate mechanistic stratification of people with epilepsy leading to improved diagnostics and therapeutics.Funding was from Epilepsy Research UK (http://www.epilepsyresearch.org.uk) via grant number A1007 and the Medical Research Council (http://www.mrc.ac.uk) via grants (MR/K013998/1 and G0701310)

Neuronal networks in children with continuous spikes and waves during slow sleep

Epileptic encephalopathy with continuous spikes and waves during slow sleep is an age-related disorder characterized by the presence of interictal epileptiform discharges during at least >85% of sleep and cognitive deficits associated with this electroencephalography pattern. The pathophysiological mechanisms of continuous spikes and waves during slow sleep and neuropsychological deficits associated with this condition are still poorly understood. Here, we investigated the haemodynamic changes associated with epileptic activity using simultaneous acquisitions of electroencephalography and functional magnetic resonance imaging in 12 children with symptomatic and cryptogenic continuous spikes and waves during slow sleep. We compared the results of magnetic resonance to electric source analysis carried out using a distributed linear inverse solution at two time points of the averaged epileptic spike. All patients demonstrated highly significant spike-related positive (activations) and negative (deactivations) blood oxygenation-level-dependent changes (P < 0.05, family-wise error corrected). The activations involved bilateral perisylvian region and cingulate gyrus in all cases, bilateral frontal cortex in five, bilateral parietal cortex in one and thalamus in five cases. Electrical source analysis demonstrated a similar involvement of the perisylvian brain regions in all patients, independent of the area of spike generation. The spike-related deactivations were found in structures of the default mode network (precuneus, parietal cortex and medial frontal cortex) in all patients and in caudate nucleus in four. Group analyses emphasized the described individual differences. Despite aetiological heterogeneity, patients with continuous spikes and waves during slow sleep were characterized by activation of the similar neuronal network: perisylvian region, insula and cingulate gyrus. Comparison with the electrical source analysis results suggests that the activations correspond to both initiation and propagation pathways. The deactivations in structures of the default mode network are consistent with the concept of epileptiform activity impacting on normal brain function by inducing repetitive interruptions of neurophysiological functio

Dynamic brain network states in human generalized spike-wave discharges.

Generalized spike-wave discharges in idiopathic generalized epilepsy are conventionally assumed to have abrupt onset and offset. However, in rodent models, discharges emerge during a dynamic evolution of brain network states, extending several seconds before and after the discharge. In human idiopathic generalized epilepsy, simultaneous EEG and functional MRI shows cortical regions may be active before discharges, and network connectivity around discharges may not be normal. Here, in human idiopathic generalized epilepsy, we investigated whether generalized spike-wave discharges emerge during a dynamic evolution of brain network states. Using EEG-functional MRI, we studied 43 patients and 34 healthy control subjects. We obtained 95 discharges from 20 patients. We compared data from patients with discharges with data from patients without discharges and healthy controls. Changes in MRI (blood oxygenation level-dependent) signal amplitude in discharge epochs were observed only at and after EEG onset, involving a sequence of parietal and frontal cortical regions then thalamus (P < 0.01, across all regions and measurement time points). Examining MRI signal phase synchrony as a measure of functional connectivity between each pair of 90 brain regions, we found significant connections (P < 0.01, across all connections and measurement time points) involving frontal, parietal and occipital cortex during discharges, and for 20 s after EEG offset. This network prominent during discharges showed significantly low synchrony (below 99% confidence interval for synchrony in this network in non-discharge epochs in patients) from 16 s to 10 s before discharges, then ramped up steeply to a significantly high level of synchrony 2 s before discharge onset. Significant connections were seen in a sensorimotor network in the minute before discharge onset. This network also showed elevated synchrony in patients without discharges compared to healthy controls (P = 0.004). During 6 s prior to discharges, additional significant connections to this sensorimotor network were observed, involving prefrontal and precuneus regions. In healthy subjects, significant connections involved a posterior cortical network. In patients with discharges, this posterior network showed significantly low synchrony during the minute prior to discharge onset. In patients without discharges, this network showed the same level of synchrony as in healthy controls. Our findings suggest persistently high sensorimotor network synchrony, coupled with transiently (at least 1 min) low posterior network synchrony, may be a state predisposing to generalized spike-wave discharge onset. Our findings also show that EEG onset and associated MRI signal amplitude change is embedded in a considerably longer period of evolving brain network states before and after discharge events

Interictal Functional Connectivity of Human Epileptic Networks Assessed by Intracerebral EEG and BOLD Signal Fluctuations

In this study, we aimed to demonstrate whether spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal derived from resting state functional magnetic resonance imaging (fMRI) reflect spontaneous neuronal activity in pathological brain regions as well as in regions spared by epileptiform discharges. This is a crucial issue as coherent fluctuations of fMRI signals between remote brain areas are now widely used to define functional connectivity in physiology and in pathophysiology. We quantified functional connectivity using non-linear measures of cross-correlation between signals obtained from intracerebral EEG (iEEG) and resting-state functional MRI (fMRI) in 5 patients suffering from intractable temporal lobe epilepsy (TLE). Functional connectivity was quantified with both modalities in areas exhibiting different electrophysiological states (epileptic and non affected regions) during the interictal period. Functional connectivity as measured from the iEEG signal was higher in regions affected by electrical epileptiform abnormalities relative to non-affected areas, whereas an opposite pattern was found for functional connectivity measured from the BOLD signal. Significant negative correlations were found between the functional connectivities of iEEG and BOLD signal when considering all pairs of signals (theta, alpha, beta and broadband) and when considering pairs of signals in regions spared by epileptiform discharges (in broadband signal). This suggests differential effects of epileptic phenomena on electrophysiological and hemodynamic signals and/or an alteration of the neurovascular coupling secondary to pathological plasticity in TLE even in regions spared by epileptiform discharges. In addition, indices of directionality calculated from both modalities were consistent showing that the epileptogenic regions exert a significant influence onto the non epileptic areas during the interictal period. This study shows that functional connectivity measured by iEEG and BOLD signals give complementary but sometimes inconsistent information in TLE

Autism: a world changing too fast for a mis-wired brain ?

International audienceDisorders in verbal and emotional communication and imitation, social reciprocity and higher order cognition observed in individuals with autism spectrum disorders (ASD) are presented here as phenotypic expressions of temporo-spatial processing disorders (TSPDs). TSPDs include various degrees of disability in (i) processing multi-sensory dynamic stimuli online, (ii) associating them into meaningful and coherent patterns and (iii) producing real-time sensory-motor adjustments and motor outputs. In line with this theory, we found that slowing down the speed opf facial and vocal events enhanced imitative, verbal and cognitive abilities in some ASD children, particularly those with low functioning autism. We then argue that TSPDs may result from Multi-system Brain Disconnectivity-Dissynchrony (MBD), defined as an increase or decrease in functional connectivity and neuronal synchronization within/between multiple neurofunctional territories and pathways. Recent functional magnetic resonance imaging (fMRI) and electrophysiological studies supporting MBD are outlined. Finally, we review the suspected underlying neurobiological mechanisms of MBD as evidenced in neuroimaging, genetic, environmental and epigenetic studies. Overall, our TSPD/MBD approach to ASD may open new promising avenues for a better understanding of neuro-physio-psychopathology of ASD and clinical rehabilitation of people affected by these syndromes

Patterns of altered neural synchrony in the default mode network in autism spectrum disorder revealed with magnetoencephalography (MEG): Relationship to clinical symptomatology

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142922/1/aur1908.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142922/2/aur1908_am.pd

Neuroimaging of Epilepsy: EEG-fMRI in the Presurgical Evaluation of Focal Epilepsy

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