Origin coordinate influence on performance of temporally extended signal space separation in magnetoencephalography

OBJECTIVE

Temporally extended signal space separation (tSSS) is a powerful method for artifact suppression in magnetoencephalography (MEG). Because tSSS first separates MEG signals coming from inside and outside a certain sphere, definition of the sphere origin is important. For this study, we explored the influence of origin choice on tSSS performance in spontaneous and evoked activity from epilepsy patients.

METHODS

Interictal epileptiform discharges (IEDs) and somatosensory evoked fields (SEFs) were processed with two tSSSs: one with the default origin of (0, 0, 40 mm) in the head coordinate, and the other with an individual origin estimated using each patient's anatomical magnetic resonance imaging (MRI). Equivalent current dipoles (ECDs) were calculated for the data. The ECD location and quality of estimation were compared across conditions.

RESULTS

MEG data from 21 patients revealed marginal differences in ECD location, but the estimation quality inferred from goodness of fit (GOF) and confidence volume (CV) was better for the tSSS with individual origins. This choice affected IEDs more than it affected SEFs.

CONCLUSIONS

Individual sphere model resulted in better GOF and CV.

SIGNIFICANCE

Application of tSSS using an individual origin would be more desirable when available. This parameter might influence spontaneous activity more strongly.

Stimulus-induced Robust Narrow-band Gamma Oscillations in Human EEG Using Cartesian Gratings

Stimulus-induced narrow-band gamma oscillations (20-70 Hz) are induced in the visual areas of the brain when particular visual stimuli, such as bars, gratings, or full-screen hue, are shown to the subject. Such oscillations are modulated by higher cognitive functions, like attention, and working memory, and have been shown to be abnormal in certain neuropsychiatric disorders, such as schizophrenia, autism, and Alzheimer's disease. However, although electroencephalogram (EEG) remains one of the most non-invasive, inexpensive, and accessible methods to record brain signals, some studies have failed to observe discernable gamma oscillations in human EEG. In this manuscript, we have described in detail a protocol to elicit robust gamma oscillations in human EEG. We believe that our protocol could help in developing non-invasive gamma-based biomarkers in human EEG, for the early detection of neuropsychiatric disorders.

Automated preprocessing and phase-amplitude coupling analysis of scalp EEG discriminates infantile spasms from controls during wakefulness

OBJECTIVE

Delta-gamma phase-amplitude coupling in EEG is useful for localizing epileptic sources and to evaluate severity in children with infantile spasms. We (1) develop an automated EEG preprocessing pipeline to clean data using artifact subspace reconstruction (ASR) and independent component (IC) analysis (ICA) and (2) evaluate delta-gamma modulation index (MI) as a method to distinguish children with epileptic spasms (cases) from normal controls during sleep and awake.

METHODS

Using 400 scalp EEG datasets (200 sleep, 200 awake) from 100 subjects, we calculated MI after applying high-pass and line-noise filters (Clean 0), and after ASR followed by either conservative (Clean 1) or stringent (Clean 2) artifactual IC rejection. Classification of cases and controls using MI was evaluated with Receiver Operating Characteristics (ROC) to obtain area under curve (AUC).

RESULTS

The artifact rejection algorithm reduced raw signal variance by 29-45% and 38-60% for Clean 1 and Clean 2, respectively. MI derived from sleep data, with or without preprocessing, robustly classified the groups (all AUC > 0.98). In contrast, group classification using MI derived from awake data was successful only after Clean 2 (AUC = 0.85).

CONCLUSIONS

We have developed an automated EEG preprocessing pipeline to perform artifact rejection and quantify delta-gamma modulation index.

Friends, not foes: Magnetoencephalography as a tool to uncover brain dynamics during transcranial alternating current stimulation

Brain oscillations are supposedly crucial for normal cognitive functioning and alterations are associated with cognitive dysfunctions. To demonstrate their causal role on behavior, entrainment approaches in particular aim at driving endogenous oscillations via rhythmic stimulation. Within this context, transcranial electrical stimulation, especially transcranial alternating current stimulation (tACS), has received renewed attention. This is likely due to the possibility of defining oscillatory stimulation properties precisely. Also, measurements comparing pre-tACS with post-tACS electroencephalography (EEG) have shown impressive modulations. However, the period during tACS has remained a blackbox until now, due to the enormous stimulation artifact. By means of application of beamforming to magnetoencephalography (MEG) data, we successfully recovered modulations of the amplitude of brain oscillations during weak and strong tACS. Additionally, we demonstrate that also evoked responses to visual and auditory stimuli can be recovered during tACS. The main contribution of the present study is to provide critical evidence that during ongoing tACS, subtle modulations of oscillatory brain activity can be reconstructed even at the stimulation frequency. Future tACS experiments will be able to deliver direct physiological insights in order to further the understanding of the contribution of brain oscillations to cognition and behavior.

The use of contact heat evoked potential stimulator (CHEPS) in magnetoencephalography for pain research

BACKGROUND

Contact heat evoked potentials (CHEP) is a thermal stimulus modality used in pain research. We examine a commercial CHEP stimulator (CHEPS) that is designed to work in an fMRI environment, but poorly understood in the MEG environment. The CHEPS attains target temperatures rapidly using sophisticated control signals that unfortunately induce artifacts in the MEG. In this paper, we summarize our experiences using the CHEPS in MEG to study pain using an experimental paradigm, and propose a novel method for managing its artifact.

NEW METHOD

We introduce a novel damped sinusoid modeling (DSM) technique to remove the CHEPS artifact based on estimates of the underlying sinusoids and damping factors. We show comparisons to signal space projection (SSP) and temporal signal space separation (tSSS) methods.

RESULTS

The CHEPS artifact is highly dynamic, yet deterministic, switching rapidly from one frequency to another, with different spatial components. The galvanic connection between the subject and the CHEPS probe alters its performance, making pre-characterization difficult.

COMPARISON WITH EXISTING METHODS

SSP methods failed to remove the artifact completely. TSSS performed better than SSP; however, tSSS requires the use of a multipolar head model that decreases the dimensionality and possibly the information content of the data. In contrast, DSM offers a strictly temporal modeling approach in which the artifact is estimated as a sum of damped sinusoids which is subtracted from the data.

CONCLUSION

Though the CHEPS increases the noise floor and introduces artifacts to the data, we believe the device can be successfully used in MEG if appropriate artifact removal techniques are followed.