Bursts with high and low load of epileptiform spikes show context-dependent correlations in epileptic mice (original) (raw)
Related papers
PLOS Computational Biology, 2015
Drug-resistant epilepsy is traditionally characterized by pathologic cortical tissue comprised of seizure-initiating 'foci'. These 'foci' are thought to be embedded within an epileptic network whose functional architecture dynamically reorganizes during seizures through synchronous and asynchronous neurophysiologic processes. Critical to understanding these dynamics is identifying the synchronous connections that link foci to surrounding tissue and investigating how these connections facilitate seizure generation and termination. We use intracranial recordings from neocortical epilepsy patients undergoing pre-surgical evaluation to analyze functional connectivity before and during seizures. We develop and apply a novel technique to track network reconfiguration in time and to parse these reconfiguration dynamics into distinct seizure states, each characterized by unique patterns of network connections that differ in their strength and topography. Our approach suggests that seizures are generated when the synchronous relationships that isolate seizure 'foci' from the surrounding epileptic network are broken down. As seizures progress, foci reappear as isolated subnetworks, marking a shift in network state that may aid seizure termination. Collectively, our observations have important theoretical implications for understanding the spatial involvement of distributed cortical structures in the dynamics of seizure generation, propagation and termination, and have practical significance in determining which circuits to modulate with implantable devices. epileptic networks | seizure focus | network state | synchrony | graph theory | community detection | dynamic network neuroscience Abbreviations: ECoG, electrocorticography Significance Statement. Localization-related epilepsy affects ≈80% of epilepsy patients and is often resistant to medication. The challenge for treating patients is mapping dynamic connectivity between cortical structures in the epileptic network during seizures. While it is well known that whole-brain functional architecture reconfigures during tasks, we hypothesize that epileptic networks reconfigure at the meso-scale leading to seizure initiation, propagation, and termination. We develop new methods to track dynamic network reconfiguration amongst connections of different strength as seizures evolve. Our results indicate that seizure onset is primarily driven by the breakdown of strong connections that re-surge in an isolated focal sub-network as seizures transition to termination. These findings have practical implications for targeting specific connections with implantable, therapeutic devices to control seizures. Footline Author PNAS Issue Date Volume Issue Number 7 arXiv:1407.5105v1 [q-bio.NC]
Is burst activity in cortical slices a representative model for epilepsy?
Neurocomputing, 2003
Neocortical slices including sensory cortex of mouse were used to study cellular and network activity during bicuculline evoked seizure-like activity. The relationship between the activities of single cells and the network was quantiÿed using entropy measures of spike trains. The network shows a large increase in synchronous burst activity during the seizure-like phase. Surprisingly, the individual cells do not seem to follow this pattern of increased synchrony. It is hypothesized that the recruitment of silent units during the seizure onset may explain this paradoxical ÿnding. Our data agrees with recent ÿndings in experimental seizures and intra-operative recordings in humans.
Journal of Neural Engineering, 2016
Objective-Quantifying the relationship between microelectrode-recorded multi-unit activity (MUA) and local field potentials (LFPs) in distinct brain regions can provide detailed information on the extent of functional connectivity in spatially widespread networks. These methods are common in studies of cognition using non-human animal models, but are rare in humans. Here we applied a neuronal spike-triggered impulse response to electrophysiological recordings from the human epileptic brain for the first time, and we evaluate functional connectivity in relation to brain areas supporting the generation of seizures. Approach-Broadband interictal electrophysiological data were recorded from microwires adapted to clinical depth electrodes that were implanted bilaterally using stereotactic techniques in six presurgical patients with medically refractory epilepsy. MUA and LFPs were isolated in each microwire, and we calculated the impulse response between the MUA on one microwire and the LFPs on a second microwire for all possible MUA/LFP pairs. Results were compared to clinical seizure localization, including sites of seizure onset and interictal epileptiform discharges. Main results-We detected significant interictal long-range functional connections in each subject, in some cases across hemispheres. Results were consistent between two independent datasets, and the timing and location of significant impulse responses reflected anatomical connectivity. However, within individual subjects, the spatial distribution of impulse responses was unique. In two subjects with clear seizure localization and successful surgery, the epileptogenic zone was associated with significant impulse responses. Significance-The results suggest that the spike-triggered impulse response can provide valuable information about the neuronal networks that contribute to seizures using only interictal
Clinical Neurophysiology of Epileptogenic Networks
IntechOpen eBooks, 2022
Current theories and models of brain rhythm generation are based on (1) the excitability of individual neurons and whole networks, (2) the structural and functional connectivity of neuronal ensembles, (3) the dynamic interaction of excitatory and inhibitory network components, and (4) the importance of transient local and global states. From the interplay of the above, systemic network properties arise which account for activity overdrive or suppression, and critical-level synchronization. Under certain conditions or states, small-to-large scale neuronal networks can be entrained into excessive and/or hypersynchronous electrical brain activity (epileptogenesis). In this chapter we demonstrate with artificial neuronal network simulations how physiological brain oscillations (delta, theta, alpha, beta and gamma range, and transients thereof, including sleep spindles and larger sleep waves) are generated and how epileptiform phenomena can potentially emerge, as observed at a macroscopic scale on scalp and intracranial EEG recordings or manifested with focal and generalized, aware and unaware, motor and nonmotor or absence seizures in man. Fast oscillations, ripples and sharp waves, spike and slow wave discharges, sharp and rhythmical slow waves, paroxysmal depolarization and DC shifts or attenuation and electrodecremental responses seem to underlie key mechanisms of epileptogenesis across different scales of neural organization and bear clinical implications for the pharmacological and surgical treatment of the various types of epilepsy.
Epileptic high-frequency network activity in a model of non-lesional temporal lobe epilepsy
Brain, 2010
High-frequency cortical activity, particularly in the 250-600 Hz (fast ripple) band, has been implicated in playing a crucial role in epileptogenesis and seizure generation. Fast ripples are highly specific for the seizure initiation zone. However, evidence for the association of fast ripples with epileptic foci depends on animal models and human cases with substantial lesions in the form of hippocampal sclerosis, which suggests that neuronal loss may be required for fast ripples. In the present work, we tested whether cell loss is a necessary prerequisite for the generation of fast ripples, using a non-lesional model of temporal lobe epilepsy that lacks hippocampal sclerosis. The model is induced by unilateral intrahippocampal injection of tetanus toxin. Recordings from the hippocampi of freely-moving epileptic rats revealed high-frequency activity (4100 Hz), including fast ripples. High-frequency activity was present both during interictal discharges and seizure onset. Interictal fast ripples proved a significantly more reliable marker of the primary epileptogenic zone than the presence of either interictal discharges or ripples (100-250 Hz). These results suggest that fast ripple activity should be considered for its potential value in the pre-surgical workup of non-lesional temporal lobe epilepsy.
Physiology of functional and effective networks in epilepsy
Clinical Neurophysiology, 2014
The relationships between functional and structural networks provide insights into brain abnormalities that are observed in epilepsy. Functional and effective connectivity methods have been used to identify the ictal onset zone as well as to characterize the onset, spread, and termination of seizures. Studies of the dynamics of epileptic networks suggest mechanisms that may explain the sudden onset and termination of seizures.
Journal of mathematical neuroscience, 2012
We describe a phenomenological model of seizure initiation, consisting of a bistable switch between stable fixed point and stable limit-cycle attractors. We determine a quasi-analytic formula for the exit time problem for our model in the presence of noise. This formula--which we equate to seizure frequency--is then validated numerically, before we extend our study to explore the combined effects of noise and network structure on escape times. Here, we observe that weakly connected networks of 2, 3 and 4 nodes with equivalent first transitive components all have the same asymptotic escape times. We finally extend this work to larger networks, inferred from electroencephalographic recordings from 35 patients with idiopathic generalised epilepsies and 40 controls. Here, we find that network structure in patients correlates with smaller escape times relative to network structures from controls. These initial findings are suggestive that network structure may play an important role in s...
Spatiotemporal neuronal correlates of seizure generation in focal epilepsy
Epilepsia, 2012
Purpose-Focal seizures are thought to reflect simultaneous activation of a large population of neurons within a discrete region of pathological brain. Resective surgery targeting this focus is an effective treatment in carefully selected patients, but not all. While in vivo recordings of singleneuron (i.e., "unit") activity in patients with epilepsy have a long history, no studies have examined long-term firing rates leading into seizures and the spatial relationship of unit activity with respect to the seizure onset zone. Methods-Microelectrode arrays recorded action potentials from neurons in mesial temporal structures (often including contralateral mesial temporal structures) in seven patients with mesial temporal lobe epilepsy. Key Findings-Only 7.6% of microelectrode recordings showed increased firing rates prior to seizure onset and only 32.4% of microelectrodes showed any seizure-related activity changes. Surprisingly, firing rates on the majority of microelectrodes (67.6%) did not change throughout the seizure, including some microelectrodes located within the seizure onset zone. Furthermore, changes in firing rate prior to and at seizure onset were observed on microelectrodes located outside the seizure onset zone and even in contralateral mesial temporal lobe. These early changes varied from seizure to seizure, demonstrating the heterogeneity of ensemble activity underlying the generation of focal seizures. Increased neuronal synchrony was primarily observed only following seizure onset. Significance-These results suggest that cellular correlates of seizure initiation and sustained ictal discharge in mesial temporal lobe epilepsy involve a small subset of the neurons within and outside the seizure onset zone. These results further suggest that the "epileptic ensemble or network" responsible for seizure generation are more complex and heterogeneous than previously thought and that future studies may find mechanistic insights and therapeutic treatments outside the clinical seizure onset zone.
Abnormal binding and disruption in large scale networks involved in human partial seizures
There is a marked increase in the amount of electrophysiological and neuroimaging works dealing with the study of large scale brain connectivity in the epileptic brain. Our view of the epileptogenic process in the brain has largely evolved over the last twenty years from the historical concept of " epileptic focus " to a more complex description of " Epileptogenic networks " involved in the genesis and " propagation " of epileptic activities. In particular, a large number of studies have been dedicated to the analysis of intracerebral EEG signals to characterize the dynamic of interactions between brain areas during temporal lobe seizures. These studies have reported that large scale functional connectivity is dramatically altered during seizures, particularly during temporal lobe seizure genesis and development. Dramatic changes in neural synchrony provoked by epileptic rhythms are also responsible for the production of ictal symptoms or changes in patient's behaviour such as automatisms, emotional changes or consciousness alteration. Beside these studies dedicated to seizures, large-scale network connectivity during the interictal state has also been investigated not only to define biomarkers of epileptogenicity but also to better understand the cognitive impairments observed between seizures. Review Approximately 30% of focal epilepsies are resistant to antiepileptic drugs. In this situation , surgical resection of the epileptogenic zone (EZ) is the only therapeutic option able to suppress seizures. The localisation and the definition of the EZ are therefore crucial issues that can be addressed through detailed analysis of anatomo-functional data acquired in epileptic patients during pre-surgical evaluation. From a theoretical viewpoint, the EZ is a highly illustrative example of complex system exhibiting nonlinear dynamics as well as ruptures (more or less abrupt) between these dynamics (typically during the transition from interictal to ictal activity) as reflected by signals directly recorded from involved brain structures. Several reviews dealing with " neural networks " and epilepsy or with synchrony and epilepsy [1,2] are available in the literature. With regard to these reviews, our objectives were more specifically to focus on works studying functional connectivity from stereotactic EEG (SEEG) signals, to propose a general framework (" the epileptogenic