Reference estimation in EEG recordings

Unmasking local activity within local field potentials (LFPs) by removing distal electrical signals using independent component analysis

Local field potentials (LFPs) are commonly thought to reflect the aggregate dynamics in local neural circuits around recording electrodes. However, we show that when LFPs are recorded in awake behaving animals against a distal reference on the skull as commonly practiced, LFPs are significantly contaminated by non-local and non-neural sources arising from the reference electrode and from movement-related noise. In a data set with simultaneously recorded LFPs and electroencephalograms (EEGs) across multiple brain regions while rats perform an auditory oddball task, we used independent component analysis (ICA) to identify signals arising from electrical reference and from volume-conducted noise based on their distributed spatial pattern across multiple electrodes and distinct power spectral features. These sources of distal electrical signals collectively accounted for 23–77% of total variance in unprocessed LFPs, as well as most of the gamma oscillation responses to the target stimulus in EEGs. Gamma oscillation power was concentrated in volume-conducted noise and was tightly coupled with the onset of licking behavior, suggesting a likely origin of muscle activity associated with body movement or orofacial movement. The removal of distal signal contamination also selectively reduced correlations of LFP/EEG signals between distant brain regions but not within the same region. Finally, the removal of contamination from distal electrical signals preserved an event-related potential (ERP) response to auditory stimuli in the frontal cortex and also increased the coupling between the frontal ERP amplitude and neuronal activity in the basal forebrain, supporting the conclusion that removing distal electrical signals unmasked local activity within LFPs. Together, these results highlight the significant contamination of LFPs by distal electrical signals and caution against the straightforward interpretation of unprocessed LFPs. Our results provide a principled approach to identify and remove such contamination to unmask local LFPs.

Influence of the stereo-EEG sensors setup and of the averaging on the dipole localization problem

While scalp EEG/MEG source imaging have been extensively studied in the last two decades, the case of source localization from invasive measurements has resulted in few works to date. Yet there is a lot to gain from stereo-electroencephalographic (SEEG) recordings, providing high signal to noise ratio measurements of the explored brain structures. The SEEG setup consists in multi-contact electrodes inserted in the brain volume, each containing a dozen of collinear measuring contacts. This particular setup raises the question of the conditioning of the inverse problem. In recent works, we have evaluated the feasibility to localize a single dominant equivalent dipole facing different sensors and noise configurations. We deepen here the analysis by evaluating the influence of the chosen subset of sensors and of the number of averaged time samples on the accuracy of the localization. We conduct experiments on simulated data as well as on real epileptic spikes, illustrating the trade off to be made between these two factors.

Dipolar source localization from intracerebral SEEG recordings

This paper aims at exploring the feasibility of a brain source localization method from intracerebral stereo-electroencephalography (SEEG) measurements. The SEEG setup consists in multi-contact electrodes inserted in the brain volume, each containing about 10 collinear measuring contacts. In clinical context, these signals are usually observed using a bipolar montage (potential differences between neighbouring contacts of a SEEG electrode). The propagation of distant activity is thus suppressed, resulting in the observation of local activities around the contacts. We propose in this paper to take benefit of the propagation information by considering the original SEEG recordings (common reference montage), with the objective to localize sources possibly distant from the electrode contacts, and whose activities are propagating through the volume. Our method is based on an equivalent dipole model for the source and homogeneous infinite models for the propagation environment. This simple approach shows satisfactory localization performance under appropriate conditions, described in this paper. The proposed method is validated on real SEEG signals for the localisation of an intra-cortical electrical stimulation (ICS) generator.