Christian G. Bénar

Single-trial analysis of oddball event-related potentials in simultaneous EEG-fMRI

There has recently been a growing interest in the use of simultaneous electroencephalography (EEG) and functional MRI (fMRI) for evoked activity in cognitive paradigms, thereby obtaining functional datasets with both high spatial and temporal resolution. The simultaneous recording permits obtaining event‐related potentials (ERPs) and MR images in the same environment, conditions of stimulation, and subject state; it also enables tracing the joint fluctuations of EEG and fMRI signals. The goal of this study was to investigate the possibility of tracking the trial‐to‐trial changes in event‐related EEG activity, and of using this information as a parameter in fMRI analysis. We used an auditory oddball paradigm and obtained single‐trial amplitude and latency features from the EEG acquired during fMRI scanning. The single‐trial P300 latency presented significant correlation with parameters external to the EEG (target‐to‐target interval and reaction time). Moreover, we obtained significant fMRI activations for the modulation by P300 amplitude and latency, both at the single‐subject and at the group level. Our results indicate that, in line with other studies, the EEG can bring a new dimension to the field of fMRI analysis by providing fine temporal information on the fluctuations in brain activity. Hum Brain Mapp, 2007.

Rostral Cingulate Zone and correct response monitoring: ICA and source localization evidences for the unicity of correct- and error-negativities

Falkenstein et al. (1991) first described a negative wave occurring just after an erroneous response in choice Reaction time tasks (Error Negativity-Ne or Error Related Negativity-ERN). Thanks to Laplacian transform of the data, Vidal et al. (2000, 2003a) described a wave on correct trials with similar topography and latency, although of smaller amplitude compared to the errors. A critical question is whether the Ne observed on errors and the negativity reported on correct trials reflect the same (modulated) activity, or whether they reflect completely different mechanisms. These two alternative possibilities were tested thanks to Independent Component Analysis (ICA) and source localization. ICA results showed that the waves recorded on errors and correct trials can be accounted for by the same independent component, corresponding to a dipolar source located within the Rostral Cingulate Zone. Source localization on the raw data also confirmed a common generator for correct and error trials. These data suggest that the waves on errors and correct trials reflect the same brain activity, whose amplitude varies as a function of the correctness of the response. The implications of this result for cognitive control are discussed.

A systematic framework for functional connectivity measures

Various methods have been proposed to characterize the functional connectivity between nodes in a network measured with different modalities (electrophysiology, functional magnetic resonance imaging etc.). Since different measures of functional connectivity yield different results for the same dataset, it is important to assess when and how they can be used. In this work, we provide a systematic framework for evaluating the performance of a large range of functional connectivity measures—based upon a comprehensive portfolio of models generating measurable responses. Specifically, we benchmarked 42 methods using 10,000 simulated datasets from 5 different types of generative models with different connectivity structures. Since all functional connectivity methods require the setting of some parameters (window size and number, model order etc.), we first optimized these parameters using performance criteria based upon (threshold free) ROC analysis. We then evaluated the performance of the methods on data simulated with different types of models. Finally, we assessed the performance of the methods against different levels of signal-to-noise ratios and network configurations. A MATLAB toolbox is provided to perform such analyses using other methods and simulated datasets.

Asymmetric Function of Theta and Gamma Activity in Syllable Processing: An Intra-Cortical Study

Low-gamma (25–45u2009Hz) and theta (4–8u2009Hz) oscillations are proposed to underpin the integration of phonemic and syllabic information, respectively. How these two scales of analysis split functions across hemispheres is unclear. We analyzed cortical responses from an epileptic patient with a rare bilateral electrode implantation (stereotactic EEG) in primary (A1/BA41 and A2/BA42) and association auditory cortices (BA22). Using time-frequency analyses, we confirmed the dominance of a 5–6u2009Hz theta activity in right and of a low-gamma (25–45u2009Hz) activity in left primary auditory cortices (A1/A2), during both resting state and syllable processing. We further detected high-theta (7–8u2009Hz) resting activity in left primary, but also associative auditory regions. In left BA22, its phase correlated with high-gamma induced power. Such a hierarchical relationship across theta and gamma frequency bands (theta/gamma phase-amplitude coupling) could index the process by which the neural code shifts from stimulus feature- to phonological-encoding, and is associated with the transition from evoked to induced power responses. These data suggest that theta and gamma activity in right and left auditory cortices bear different functions. They support a scheme where slow parsing of the acoustic information dominates in right hemisphere at a syllabic (5–6u2009Hz) rate, and left auditory cortex exhibits a more complex cascade of oscillations, reflecting the possible extraction of transient acoustic cues at a fast (~25–45u2009Hz) rate, subsequently integrated at a slower, e.g., syllabic one. Slow oscillations could functionally participate to speech processing by structuring gamma activity in left BA22, where abstract percepts emerge.

Preictal changes in cerebral haemodynamics: Review of findings and insights from intracerebral EEG

The possibility of recording changes in brain signals occurring before epileptic seizures is of considerable interest, both as markers for seizure anticipation and as a window into the mechanisms of seizure generation. Several studies have reported preictal changes on electrophysiological traces. More recently, observations have been made of changes occurring on haemodynamic signals before interictal events or before seizures, often without concurrent changes observed on electrophysiology. We present here a critical review of these findings, in optical imaging, SPECT and fMRI, followed by a discussion based on data from intracerebral EEG.

Electrophysiological study of the basal temporal language area : A convergence zone between language perception and production networks

OBJECTIVEnRegions involved in language processing have been observed in the inferior part of the left temporal lobe. Although collectively labelled the Basal Temporal Language Area (BTLA), these territories are functionally heterogeneous and are involved in language perception (i.e. reading or semantic task) or language production (speech arrest after stimulation). The objective of this study was to clarify the role of BTLA in the language network in an epileptic patient who displayed jargonaphasia.nnnMETHODSnIntracerebral evoked related potentials to verbal and non-verbal stimuli in auditory and visual modalities were recorded from BTLA. Time-frequency analysis was performed during ictal events.nnnRESULTSnEvoked potentials and induced gamma-band activity provided direct evidence that BTLA is sensitive to language stimuli in both modalities, 350 ms after stimulation. In addition, spontaneous gamma-band discharges were recorded from this region during which we observed phonological jargon.nnnCONCLUSIONnThe findings emphasize the multimodal nature of this region in speech perception. In the context of transient dysfunction, the patients lexical semantic processing network is disrupted, reducing spoken output to meaningless phoneme combinations.nnnSIGNIFICANCEnThis rare opportunity to study the BTLA in vivo demonstrates its pivotal role in lexico-semantic processing for speech production and its multimodal nature in speech perception.

Investigation of Linear Coupling Between Single-Event Blood Flow Responses and Interictal Discharges in a Model of Experimental Epilepsy

A successful outcome of epilepsy neurosurgery relies on an accurate delineation of the epileptogenic region to be resected. Functional magnetic resonance imaging (fMRI) would allow doing this noninvasively at high spatial resolution. However, a clear, quantitative description of the relationship between hemodynamic changes and the underlying epileptiform neuronal activity is still missing, thereby preventing the systematic use of fMRI for routine epilepsy surgery planning. To this aim, we used a local epilepsy model to record simultaneously cerebral blood flow (CBF) with laser Doppler (LD) and local field potentials (LFP) in rat frontal cortex. CBF responses to individual interictal-like spikes were large and robust. Their amplitude correlated linearly with spike amplitude. Moreover, the CBF response added linearly in time over a large range of spiking rates. CBF responses could thus be predicted by a linear model of the kind currently used for the interpretation of fMRI data, but including also the spikes amplitudes as additional information. Predicted and measured CBF responses matched accurately. For high spiking frequencies (above approximately 0.2 Hz), the responses saturated but could eventually recover, indicating the presence of multiple neurovascular coupling mechanisms, which might act at different spatiotemporal scales. Spatially, CBF responses peaked at the center of epileptic activity and displayed a spatial specificity at least as good as the millimeter. These results suggest that simultaneous electroencephalographic and blood flow-based fMRI recordings should be suitable for the noninvasive precise localization of hyperexcitable regions in epileptic patients candidate for neurosurgery.

Simultaneous recording of MEG, EEG and intracerebral EEG during visual stimulation: From feasibility to single-trial analysis

Electroencephalography (EEG), magnetoencephalography (MEG), and intracerebral stereotaxic EEG (SEEG) are the three neurophysiological recording techniques, which are thought to capture the same type of brain activity. Still, the relationships between non-invasive (EEG, MEG) and invasive (SEEG) signals remain to be further investigated. In early attempts at comparing SEEG with either EEG or MEG, the recordings were performed separately for each modality. However such an approach presents substantial limitations in terms of signal analysis. The goal of this technical note is to investigate the feasibility of simultaneously recording these three signal modalities (EEG, MEG and SEEG), and to provide strategies for analyzing this new kind of data. Intracerebral electrodes were implanted in a patient with intractable epilepsy for presurgical evaluation purposes. This patient was presented with a visual stimulation paradigm while the three types of signals were simultaneously recorded. The analysis started with a characterization of the MEG artifact caused by the SEEG equipment. Next, the average evoked activities were computed at the sensor level, and cortical source activations were estimated for both the EEG and MEG recordings; these were shown to be compatible with the spatiotemporal dynamics of the SEEG signals. In the average time-frequency domain, concordant patterns between the MEG/EEG and SEEG recordings were found below the 40 Hz level. Finally, a fine-grained coupling between the amplitudes of the three recording modalities was detected in the time domain, at the level of single evoked responses. Importantly, these correlations have shown a high level of spatial and temporal specificity. These findings provide a case for the ability of trimodal recordings (EEG, MEG, and SEEG) to reach a greater level of specificity in the investigation of brain signals and functions.

Realistic synthetic background neuronal activity for the analysis of MEG probe configurations

Magnetoencephalography (MEG) sensors are capable of recording the tiny magnetic activity from the brain. They can be constituted of either magnetometers or gradiometers that respectively record the magnetic field or its gradient. In this paper, we present a framework for constructing realistic MEG signals. This framework can be used to test different probe configurations and source localization algorithms. The methodology of generation of synthetic signals is presented, and synthetic signals are compared to real signals. Paroxysmal activity generated with this model and originating from a deep cerebral source is determined with two different localization algorithms. Preliminary results show that gradiometers even with a short baseline perform close to magnetometer and that the use of hybrid systems should be further investigated.

Despiking SEEG signals reveals dynamics of gamma band preictal activity

Interictal 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.