Dataset Information

Contralateral dissociation between neural activity and cerebral blood volume during recurrent acute focal neocortical seizures.

ABSTRACT:

Objective

Whether epileptic events disrupt normal neurovascular coupling mechanisms locally or remotely is unclear. We sought to investigate neurovascular coupling in an acute model of focal neocortical epilepsy, both within the seizure onset zone and in contralateral homotopic cortex.

Methods

Neurovascular coupling in both ipsilateral and contralateral vibrissal cortices of the urethane-anesthetized rat were examined during recurrent 4-aminopyridine (4-AP, 15 mm, 1 ?l) induced focal seizures. Local field potential (LFP) and multiunit spiking activity (MUA) were recorded via two bilaterally implanted 16-channel microelectrodes. Concurrent two-dimensional optical imaging spectroscopy was used to produce spatiotemporal maps of cerebral blood volume (CBV).

Results

Recurrent acute seizures in right vibrissal cortex (RVC) produced robust ipsilateral increases in LFP and MUA activity, most prominently in layer 5, that were nonlinearly correlated to local increases in CBV. In contrast, contralateral left vibrissal cortex (LVC) exhibited relatively smaller nonlaminar specific increases in neural activity coupled with a decrease in CBV, suggestive of dissociation between neural and hemodynamic responses.

Significance

These findings provide insights into the impact of epileptic events on the neurovascular unit, and have important implications both for the interpretation of perfusion-based imaging signals in the disorder and understanding the widespread effects of epilepsy. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here.

SUBMITTER: Harris S

PROVIDER: S-EPMC4336552 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Publications

Contralateral dissociation between neural activity and cerebral blood volume during recurrent acute focal neocortical seizures.

Harris Sam S Boorman Luke L Bruyns-Haylett Michael M Kennerley Aneurin A Ma Hongtao H Zhao Mingrui M Overton Paul G PG Schwartz Theodore H TH Berwick Jason J

Epilepsia 20140722 9

<h4>Objective</h4>Whether epileptic events disrupt normal neurovascular coupling mechanisms locally or remotely is unclear. We sought to investigate neurovascular coupling in an acute model of focal neocortical epilepsy, both within the seizure onset zone and in contralateral homotopic cortex.<h4>Methods</h4>Neurovascular coupling in both ipsilateral and contralateral vibrissal cortices of the urethane-anesthetized rat were examined during recurrent 4-aminopyridine (4-AP, 15 mm, 1 μl) induced fo ...[more]

PMID: 25053117

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Project description:Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4×4 mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) a newly developed stage segmentation method, applied to local field potentials (LFPs) and multiunit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~2-3 Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25-60 Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergoes complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time scale network dynamics evolving through these discrete stages.

Project description:The apparent unpredictability of epileptic seizures has a major impact in the quality of life of people with pharmacologically resistant seizures. Here, we present initial results and a proof-of-concept of how focal seizures can be predicted early in advance based on intracortical signals recorded from small neocortical patches away from identified seizure onset areas. We show that machine learning algorithms can discriminate between interictal and preictal periods based on multiunit activity (i.e. thresholded action potential counts) and multi-frequency band local field potentials recorded via 4 X 4 mm2 microelectrode arrays. Microelectrode arrays were implanted in 5 patients undergoing neuromonitoring for resective surgery. Post-implant analysis revealed arrays were outside the seizure onset areas. Preictal periods were defined as the 1-hour period leading to a seizure. A 5-minute gap between the preictal period and the putative seizure onset was enforced to account for potential errors in the determination of actual seizure onset times. We used extreme gradient boosting and long short-term memory networks for prediction. Prediction accuracy based on the area under the receiver operating characteristic curves reached 90% for at least one feature type in each patient. Importantly, successful prediction could be achieved based exclusively on multiunit activity. This result indicates that preictal activity in the recorded neocortical patches involved not only subthreshold postsynaptic potentials, perhaps driven by the distal seizure onset areas, but also neuronal spiking in distal recurrent neocortical networks. Beyond the commonly identified seizure onset areas, our findings point to the engagement of large-scale neuronal networks in the neural dynamics building up toward a seizure. Our initial results obtained on currently available human intracortical microelectrode array recordings warrant new studies on larger datasets, and open new perspectives for seizure prediction and control by emphasizing the contribution of multiscale neural signals in large-scale neuronal networks.

Dataset Information

Contralateral dissociation between neural activity and cerebral blood volume during recurrent acute focal neocortical seizures.

Objective

Methods

Results

Significance

Publications

Contralateral dissociation between neural activity and cerebral blood volume during recurrent acute focal neocortical seizures.

Similar Datasets

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