In vitro Oscillation Patterns Throughout the Hippocampal Formation in a Rodent Model of Epilepsy.

Specific oscillatory patterns are considered biomarkers of pathological neuronal network in brain diseases, such as epilepsy. However, the dynamics of underlying oscillations during the epileptogenesis throughout the hippocampal formation in the temporal lobe epilepsy is not clear. Here, we characterized in vitro oscillatory patterns within the hippocampal formation of epileptic rats, under 4-aminopyridine (4-AP)-induced hyperexcitability and during the spontaneous network activity, at two periods of epileptogenesis. First, at the beginning of epileptic chronic phase, 30 days post-pilocarpine-induced Status Epilepticus (SE). Second, at the established epilepsy, 60 days post-SE. The 4-AP-bathed slices from epileptic rats had increased susceptibility to ictogenesis in CA1 at 30 days post-SE, and in entorhinal cortex and dentate gyrus at 60 days post-SE. Higher power and phase coherence were detected mainly for gamma and/or high frequency oscillations (HFOs), in a region- and stage-specific manner. Interestingly, under spontaneous network activity, even without 4-AP-induced hyperexcitability, slices from epileptic animals already exhibited higher power of gamma and HFOs in different areas of hippocampal formation at both periods of epileptogenesis, and higher phase coherence in fast ripples at 60 days post-SE. These findings reinforce the critical role of gamma and HFOs in each one of the hippocampal formation areas during ongoing neuropathological processes, tuning the neuronal network to epilepsy.

Motor deficits and beta oscillations are dissociable in an alpha-synuclein model of Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterised by progressive motor symptoms resulting from chronic loss of dopaminergic neurons in the nigrostriatal pathway. The over expression of the protein alpha-synuclein in the substantia nigra has been used to induce progressive dopaminergic neuronal loss and to reproduce key histopathological and temporal features of PD in animal models. However, the neurophysiological aspects of the alpha-synuclein PD model have been poorly characterised. Hereby, we performed chronic in vivo electrophysiological recordings in the corticostriatal circuit of rats injected with viral vector to over express alpha-synuclein in the right substantia nigra. Our model, previously shown to exhibit mild motor deficits, presented moderate dopaminergic cell loss but did not present prominent local field potential oscillations in the beta frequency range (11-30 Hz), considered a hallmark of PD, during the 9 weeks after onset of alpha-synuclein over expression. Spinal cord stimulation, a potential PD symptomatic therapy, was applied regularly from sixth to ninth week after alpha-synuclein over expression onset and had an inhibitory effect on the firing rate of corticostriatal neurons in both control and alpha-synuclein hemispheres. Dopamine synthesis inhibition at the end of the experiment resulted in severe parkinsonian symptoms such as akinesia and increased beta and high-frequency (>90 Hz) oscillations. These results suggest that the alpha-synuclein PD model with moderate level of dopaminergic depletion does not reproduce the prominent corticostriatal beta oscillatory activity associated to parkinsonian conditions.

Automated detection of high-frequency oscillations in electrophysiological signals: Methodological advances.

In recent years, new recording technologies have advanced such that oscillations of neuronal networks can be identified from simultaneous, multisite recordings at high temporal and spatial resolutions. However, because of the deluge of multichannel data generated by these experiments, achieving the full potential of parallel neuronal recordings also depends on the development of new mathematical methods capable of extracting meaningful information related to time, frequency and space. In this review, we aim to bridge this gap by focusing on the new analysis tools developed for the automated detection of high-frequency oscillations (HFOs, >40Hz) in local field potentials. For this, we provide a revision of different aspects associated with physiological and pathological HFOs as well as the several stages involved in their automatic detection including preprocessing, selection, rejection and analysis through time-frequency processes. Beyond basic research, the automatic detection of HFOs would greatly assist diagnosis of epilepsy disorders based on the recognition of these typical pathological patterns in the electroencephalogram (EEG). Also, we emphasize how these HFO detection methods can be applied and the properties that might be inferred from neuronal signals, indicating potential future directions.

Pathologic substrates of focal epilepsy influence the generation of high-frequency oscillations.

OBJECTIVE: Although a clear correlation has been observed between high-frequency oscillations (HFOs) and the seizure-onset zone in distinct lesions, the role of the underlying pathologic substrates in the generation of HFOs is not well established. We aimed to investigate HFO correlates of different pathologic substrates in patients with drug-resistant epilepsy, and to examine the relation of HFOs with the anatomic location of the dysplastic lesion and surrounding tissue in patients with focal cortical dysplasia (FCD). METHODS: We studied consecutive patients with drug-resistant epilepsy who underwent intracranial electroencephalography (iEEG) investigations with depth electrodes at the Montreal Neurological Institute and Hospital, between November 2004 and May 2013. Inclusion criteria were the following: a focal lesion documented by magnetic resonance imaging (MRI); EEG recording at a 2,000 Hz sampling rate; and seizures starting from depth electrode contacts placed in lesion and perilesional tissue. RESULTS: Thirty-seven patients (13 FCD, 12 mesial temporal sclerosis, five cortical atrophy, three polymicrogyria, three nodular heterotopia, and one tuberous sclerosis) were included; 18 were women (median age 34). Ripples and fast ripples were found in all lesion types, except tuberous sclerosis, which showed no fast ripples. There was a significant difference in rates of ripples and fast ripples across different lesions (p < 0.001), with higher rates in FCD, mesial temporal sclerosis, and nodular heterotopia than in atrophy, polymicrogyria, and tuberous sclerosis. Regarding patients with FCD, HFOs rates differed significantly across the three types of tissue (lesional, perilesional, and nonlesional; p < 0.001), being higher within the borders of the MRI-visible dysplastic lesion, followed by the surrounding area, and rare in the remote cortex. SIGNIFICANCE: Our findings suggest that in patients who are all intractable, the HFO rates vary with different pathologies, and reflect different types of neuronal derangements. Our results also emphasize the potential usefulness of HFOs as an additional method to better define the extent of the epileptogenic dysplastic tissue in FCD.