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Background:Surgical treatment of drug-resistant temporal lobe epilepsy (TLE) depends on proper identification of the seizure onset zone (SOZ) and differentiation of mesial, temporolimbic seizure onsets from temporal neocortical seizure onsets. Noninvasive source imaging using electroencephalography (EEG) and magnetoencephalography (MEG) can provide accurate information on interictal spike localization; however, EEG and MEG have low sensitivity for epileptiform activity restricted to deep temporolimbic structures. Moreover, in mesial temporal lobe epilepsy (MTLE), interictal spikes frequently arise in neocortical foci distant from the SOZ, rendering interictal spike localization potentially misleading for presurgical planning.Methods:In this study, we used two different beamformer techniques applied to the MEG signal of ictal events acquired during EEG-MEG recordings in six patients with TLE (three neocortical, three MTLE) in whom the ictal source localization results could be compared to ground truth SOZ localizations determined from intracranial EEG and/or clinical, neuroimaging, and postsurgical outcome evidence.Results:Beamformer analysis proved to be highly accurate in all cases and was able to identify focal SOZs in mesial, temporolimbic structures. In three patients, interictal spikes were absent, too complex for dipole modeling, or localized to anterolateral temporal neocortex distant to a mesial temporal SOZ, and thus unhelpful in presurgical investigation.Conclusions:MEG beamformer source reconstruction is suitable for analysis of ictal events in TLE and can complement or supersede the traditional analysis of interictal spikes. The method outlined is applicable to any type of epileptiform event, expanding the information value of MEG and broadening its utility for presurgical recording in epilepsy.

Deep brain stimulation is a treatment option for patients with drug-resistant epilepsy. The precise mechanism of neuromodulation in epilepsy is unknown, and biomarkers are needed for optimizing treatment. The aim of this study was to describe the neural network associated with deep brain stimulation targets for epilepsy and to explore its potential application as a novel biomarker for neuromodulation. Using seed-to-voxel functional connectivity maps, weighted by seizure outcomes, brain areas associated with stimulation were identified in normative resting state functional scans of 1000 individuals. To pinpoint specific regions in the normative epilepsy deep brain stimulation network, we examined overlapping areas of functional connectivity between the anterior thalamic nucleus, centromedian thalamic nucleus, hippocampus and less studied epilepsy deep brain stimulation targets. Graph network analysis was used to describe the relationship between regions in the identified network. Furthermore, we examined the associations of the epilepsy deep brain stimulation network with disease pathophysiology, canonical resting state networks and findings from a systematic review of resting state functional MRI studies in epilepsy deep brain stimulation patients. Cortical nodes identified in the normative epilepsy deep brain stimulation network were in the anterior and posterior cingulate, medial frontal and sensorimotor cortices, frontal operculum and bilateral insulae. Subcortical nodes of the network were in the basal ganglia, mesencephalon, basal forebrain and cerebellum. Anterior thalamic nucleus was identified as a central hub in the network with the highest betweenness and closeness values, while centromedian thalamic nucleus and hippocampus showed average centrality values. The caudate nucleus and mammillothalamic tract also displayed high centrality values. The anterior cingulate cortex was identified as an important cortical hub associated with the effect of deep brain stimulation in epilepsy. The neural network of deep brain stimulation targets shared hubs with known epileptic networks and brain regions involved in seizure propagation and generalization. Two cortical clusters identified in the epilepsy deep brain stimulation network included regions corresponding to resting state networks, mainly the default mode and salience networks. Our results were concordant with findings from a systematic review of resting state functional MRI studies in patients with deep brain stimulation for epilepsy. Our findings suggest that the various epilepsy deep brain stimulation targets share a common cortico-subcortical network, which might in part underpin the antiseizure effects of stimulation. Interindividual differences in this network functional connectivity could potentially be used as biomarkers in selection of patients, stimulation parameters and neuromodulation targets.

Current understanding of synaptic transmission in the human brain is based primarily by analogy with data obtained using animal model preparations with large presynaptic terminals from squid, chick, rat or mouse. While these models are excellent for the analysis of general principles of synaptic transmission they are unlikely to serve for the understanding of human-specific modifications or defects. To address this issue we have developed a human preparation based on fresh excised human brain tissue that permits the examination of synaptic vesicle recycling in identified single presynaptic terminals (synaptosomes, SSMs).A plug of middle temporal gyrus cortex, removed for hippocampal epilepsy focus surgery (Valiante), was homogenized. SSMs were isolated and purified by micro-discontinuous sucrose gradient centrifugation. The isolation of SSMs was confirmed by immunocytochemistry and biochemistry (Western blot) using a wide range of presynaptic markers. Individual SSM types could be identified by immunostaining for postsynaptic receptors since a small piece of the postsynaptic membrane typically remains attached to the presynaptic nerve terminal (See: Nath et al., Fronteirs in Cellular Neuroscience 2014). The SSMs were functional as SV turnover was demonstrated in individual terminals by Ca2+-triggered styryl-dye uptake and destaining. We also demonstrated that the SSMs could be frozen for later physiological study and loaded with intracellular test compounds using our Cryoloading method (ibid).This new method will provide a means to assess SV turnover and transmitter release in identified presynaptic nerve terminals in human brain and examine human-specific disorders such as Parkinson's and Alzheimer's diseases.

Treatment for epilepsy depends largely on seizure frequency reported by patients through their seizure diaries. However, patients may be unaware of some of their seizures, which may lead to incomplete diary data, impacting on appropriate treatment plans. The purpose of this study was to quantify awareness of seizures in patients admitted to an epilepsy monitoring unit through post event assessments by registered nurses. Results indicated that only 44.5% of complex partial and secondarily generalized tonic-clonic seizures were recognized by patients with epilepsy. Incomplete data in seizure diaries are likely a widespread problem, which may have an important impact on treatment and, thereby, on the safety and quality of life of individuals with epilepsy.