Ventral and dorsal pathways of speech perception: An intracerebral ERP study.

Recent theory of physiology of language suggests a dual stream dorsal/ventral organization of speech perception. Using intra-cerebral Event-related potentials (ERPs) during pre-surgical assessment of twelve drug-resistant epileptic patients, we aimed to single out electrophysiological patterns during both lexical-semantic and phonological monitoring tasks involving ventral and dorsal regions respectively. Phonological information processing predominantly occurred in the left supra-marginal gyrus (dorsal stream) and lexico-semantic information occurred in anterior/middle temporal and fusiform gyri (ventral stream). Similar latencies were identified in response to phonological and lexico-semantic tasks, suggesting parallel processing. Typical ERP components were strongly left lateralized since no evoked responses were recorded in homologous right structures. Finally, ERP patterns suggested the inferior frontal gyrus as the likely final common pathway of both dorsal and ventral streams. These results brought out detailed evidence of the spatial-temporal information processing in the dual pathways involved in speech perception

Contextual modulation of hippocampal activity during picture naming

International audiencePicture naming is a standard task used to probe language processes in healthy and impaired speakers. It recruits a broad neural network of language related areas, among which the hippocampus is rarely included. However, the hippocampus could play a role during picture naming, subtending, for example, implicit learning of the links between pictured objects and their names. To test this hypothesis, we recorded hippocampal activity during plain picture naming, without memorization requirement; we further assessed whether this activity was modulated by contextual factors such as repetition priming and semantic interference. Local field potentials recorded from intracerebral electrodes implanted in the healthy hippocampi of epileptic patients revealed a specific and reliable pattern of activity, markedly modulated by repetition priming and semantic context. These results indicate that the hippocampus is recruited during picture naming, presumably in relation to implicit learning, with contextual factors promoting differential hippocampal processes, possibly subtended by different sub-circuitries. (C) 2016 Published by Elsevier Inc

An open-source toolbox for Multi-patient Intracranial EEG Analysis (MIA)

International audienceIntracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses therein recorded. In this context, we designed, implemented, and tested a userfriendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin. MIA helps analyzing event related iEEG signals while following good scientific practice recommendations, such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and timefrequency domains, and the similarity of time courses across patients or contacts can be assessed within anatomical regions. MIA allows visualizing all these results in a variety of formats at every step of the analysis. Here, we present the toolbox architecture and illustrate the different steps and features of the analysis pipeline using a group dataset collected during a language task

An open-source toolbox for Multi-patient Intracranial EEG Analysis (MIA)

Intracranial EEG (iEEG) performed during the pre-surgical evaluation of refractory epilepsy provides a great opportunity to investigate the neurophysiology of human cognitive functions with exceptional spatial and temporal precisions. A difficulty of the iEEG approach for cognitive neuroscience, however, is the potential variability across patients in the anatomical location of implantations and in the functional responses that are recorded. In this context, we designed, implemented, and tested a user-friendly and efficient open-source toolbox for Multi-Patient Intracranial data Analysis (MIA), which can be used as standalone program or as a Brainstorm plugin. MIA helps analyzing iEEG signals while following good scientific practice recommendations, such as building reproducible analysis pipelines and applying robust statistics. The signals can be analyzed in the temporal and time-frequency domains, and the similarity of time courses across patients or contacts can be assessed within anatomical regions. MIA allows visualizing all these results in a variety of formats at every step of the analysis. Here we present the toolbox architecture and illustrate the different steps and features of the analysis pipeline using a group dataset collected during a language task

Time rescaling reproduces EEG behavior during transition from propofol anesthesia-induced unconsciousness to consciousness

Abstract General anesthesia (GA) is a reversible manipulation of consciousness whose mechanism is mysterious at the level of neural networks leaving space for several competing hypotheses. We recorded electrocorticography (ECoG) signals in patients who underwent intracranial monitoring during awake surgery for the treatment of cerebral tumors in functional areas of the brain. Therefore, we recorded the transition from unconsciousness to consciousness directly on the brain surface. Using frequency resolved interferometry; we studied the intermediate ECoG frequencies (4–40 Hz). In the theoretical study, we used a computational Jansen and Rit neuron model to simulate recovery of consciousness (ROC). During ROC, we found that f increased by a factor equal to 1.62 ± 0.09, and δf varied by the same factor (1.61 ± 0.09) suggesting the existence of a scaling factor. We accelerated the time course of an unconscious EEG trace by an approximate factor 1.6 and we showed that the resulting EEG trace match the conscious state. Using the theoretical model, we successfully reproduced this behavior. We show that the recovery of consciousness corresponds to a transition in the frequency (f, δf) space, which is exactly reproduced by a simple time rescaling. These findings may perhaps be applied to other altered consciousness states

Neural networks underlying hyperkinetic seizures of "temporal lobe" origin.

International audiencePURPOSE: Hyperkinetic seizures are most often considered to originate from prefrontal cortex. Recently however, it has been suggested that hyperkinetic seizures can be found in patients with temporal lobe seizures. The objective of this study was to determine the features of temporal epilepsy with hyperkinetic seizures and the functional anatomy of involved brain networks. METHODS: We retrospectively identified patients investigated by depth electrodes (SEEG) in whom hyperkinetic manifestations were proved to be linked to initial temporal lobe involvement. Seizure organisation was determined according to the "Epileptogenicity Index" (EI), a new way to quantify rapid discharges at seizure onset. RESULTS: We found 7 patients among 130 SEEG investigations that fulfilled the inclusion criteria. Most of the patients presented with hyperkinetic occurring (or predominating) during sleep. SEEG signal analysis demonstrated a common temporo-frontal network in which the temporal pole played a central role. Major involvement of the orbito-frontal cortex and to a lesser extent the cingulate gyrus was also a particular feature of these seizures. DISCUSSION: Seizures originating in the temporal lobe must be recognized as an important cause of hyperkinetic seizures. The temporal pole and its connexions with medio-basal prefrontal cortex represent the main structures involved in epileptogenic networks

The role of sub-hippocampal versus hippocampal regions in bitemporal lobe epilepsies

International audienceObjective We aimed at better delineating the functional anatomical organization of bitemporal lobe epilepsy. Methods We studied the epileptogenic zone (EZ) by quantifying the epileptogenicity of brain structures explored by depth electrodes in patients investigated by stereoelectroencephalography (SEEG). We compared 15 patients with bilateral mesial temporal lobe epilepsy (BTLE) and 15 patients with unilateral mesial temporal lobe epilepsy (UTLE). This quantification was performed using the ‘Epileptogenicity Index’ (EI). Results Age at epilepsy onset, and epilepsy duration, were not statistically different in both groups. UTLE patients more frequently displayed maximal epileptogenicity in hippocampal structures, whereas BTLE patients had maximal values in subhippocampal areas (entorhinal cortex, temporal pole, parahippocampal cortex). Conclusions Our results suggest different organization of the EZ in the two groups. Significance BTLE was associated with more involvement of subhippocampal regions, a result in agreement with known anatomical connections between the two temporal lobes. © 2016 International Federation of Clinical Neurophysiolog

Technical solutions for simultaneous MEG and SEEG recordings: towards routine clinical use

International audienceInterictal epileptiform discharges, or "interictal spikes", are the hallmark of epilepsy. Still, there is growing evidence that oscillatory activity-whether in the gamma band (30-120 Hz) or at higher frequencies is another important marker of hyperexcitable tissues. A major difficulty arises from the fact that interictal spikes and oscillations overlap in the frequency domain. This hampers the correct delineation of the cortex producing pathological oscillations by simple filtering. Here, we propose a nonlinear technique for fitting the spike waveform in order to remove it, resulting in a "despiked" signal. This strategy was first applied to simulated data inspired from real stereo-electroencephalographic (SEEG) signals, then to real data. We show that despiking leads to a better space-time-frequency analysis of the oscillatory part of the signal. Thus, in the real SEEG signals, the spatio-temporal maps show a buildup of gamma oscillations during the preictal period in the despiked signals, whereas in the original signals this activity is masked by spikes. Despiking is thus a promising venue for a better characterization of oscillatory activity in electrophysiology of epilepsy.

Deep brain activities can be detected with magnetoencephalography

International audienceThe hippocampus and amygdala are key brain structures of the medial temporal lobe, involved in cognitive and emotional processes as well as pathological states such as epilepsy. Despite their importance, it is still unclear whether their neural activity can be recorded non-invasively. Here, using simultaneous intracerebral and magnetoencephalography (MEG) recordings in patients with focal drug-resistant epilepsy, we demonstrate a direct contribution of amygdala and hippocampal activity to surface MEG recordings. In particular, a method of blind source separation, independent component analysis, enabled activity arising from large neocortical networks to be disentangled from that of deeper structures, whose amplitude at the surface was small but significant. This finding is highly relevant for our understanding of hippocampal and amygdala brain activity as it implies that their activity could potentially be measured non-invasively