Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients.

Spatiotemporal evolution of synchrony dynamics among neuronal populations plays an important role in decoding complicated brain function in normal cognitive processing as well as during pathological conditions such as epileptic seizures. In this paper, a non-linear analytical methodology is proposed to quantitatively evaluate the phase-synchrony dynamics in epilepsy patients. A set of finite neuronal oscillators was adaptively extracted from a multi-channel electrocorticographic (ECoG) dataset utilizing noise-assisted multivariate empirical mode de-composition (NA-MEMD).

EMD-Based, Mean-Phase Coherence Analysis to Assess Instantaneous Phase-Synchrony Dynamics in Epilepsy Patients.

In this paper, an adaptive, non-linear, analytical methodology is proposed in order to quantitatively evaluate the instantaneous phase-synchrony dynamics in epilepsy patients. A group of finite neuronal oscillators is extracted from a multichannel electrocorticographic (ECoG) data, using the empirical mode decomposition (EMD). The instantaneous phases of the extracted oscillators are measured using the Hilbert transform in order to be utilized in the mean-phase coherence analysis.

Using Interictal HFOs to Improve the Identification of Epileptogenic Zones in Preparation for Epilepsy Surgery.

For the more than 15 million patients who have drug-resistant epilepsy, surgical resection of the region where seizure arise is often the only alternative therapy. However, the identification of this epileptogenic zone (EZ) is often imprecise. Generally, insufficient EZ identification and resection may cause seizures to continue and too much resection may lead to unnecessary neurological deficits.

Should stimulation parameters be individualized to stop seizures: Evidence in support of this approach.

Objective: Deep-brain electrical stimulation (DBS) is a treatment modality being explored for many neurologic diseases and is a potentially potent means of disrupting the aberrant rhythms that arise during the epileptic seizures that afflict >1% of the population. However, current DBS protocols typically employed are formulated a priori and do not reflect the electrophysiologic dynamics within the brain as seizures arise, which may underlie their limited efficacy. This study investigates how the efficacy of DBS could be improved using endogenous dynamics to inform stimulation protocols.

Rapid onset of a kainate-induced mirror focus in rat hippocampus is mediated by contralateral AMPA receptors.

The development of an epileptic "mirror" focus in an area of the brain contralateral to the primary epileptic focus typically evolves over days in the experimental setting after status epilepticus or electrical kindling of the primary focal region. In contrast, we observed the rapid development of an apparent mirror focus in the contralateral hippocampus following microinjection of kainic acid (KA) in the ipsilateral hippocampus in rats. Using multisite intracranial recordings, local field potentials were recorded in anesthetized adult male rats using electrodes implanted in the CA3 region of both hippocampi and in the anteromedial nucleus of the thalamus.

Synchrony dynamics across brain structures in limbic epilepsy vary between initiation and termination phases of seizures.

Neuronal populations in the brain achieve levels of synchronous electrophysiological activity during both normal brain function and pathological states such as epileptic seizures. Understanding how the dynamics of neuronal oscillators in the brain evolve from normal to diseased states is a critical component toward decoding such complex behaviors. In this study, we sought to develop a more in-depth understanding of multisite dynamics underlying seizure evolution in limbic epilepsy by analyzing oscillators in recordings of local field potentials from three brain structures (bilateral hippocampi and anteromedial thalamus) in a kainic acid in vivo rat model of temporal lobe epilepsy extracted using the empirical mode decomposition (EMD) technique.

A study of multi-site brain dynamics during limbic seizures.

Neuronal populations in the brain achieve levels of synchronous electrophysiological activity as a consequence of both normal brain functions as well as during pathological states such as in epileptic seizures. Understanding the nature of this synchrony and the dynamics of neuronal oscillators in the brain is a critical component towards decoding such complex behaviors. We have sought to achieve a more in-depth understanding of the dynamics underlying the evolution of seizures in limbic epilepsy by analyzing recordings of local field potentials from three subcortical nuclei that are part of the circuit of Papez in a kainic acid rat model of temporal lobe epilepsy using the empirical mode decomposition technique.