Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality

Cortical surface alignment in multi-subject spatiotemporal independent EEG source imaging

Brain responses to stimulus presentations may vary widely across subjects in both time course and spatial origins. Multi-subject EEG source imaging studies that apply Independent Component Analysis (ICA) to data concatenated across subjects have overlooked the fact that projections to the scalp sensors from functionally equivalent cortical sources vary from subject to subject. This study demonstrates an approach to spatiotemporal independent component decomposition and alignment that spatially co-registers the MR-derived cortical topographies of individual subjects to a well-defined, shared spherical topology (Fischl et al., 1999). Its efficacy for identifying functionally equivalent EEG sources in multi-subject analysis is demonstrated by analyzing EEG and behavioral data from a stop-signal paradigm using two source-imaging approaches, both based on individual subject independent source decompositions. The first, two-stage approach uses temporal infomax ICA to separate each subject's data into temporally independent components (ICs), then estimates the source density distribution of each IC process from its scalp map and clusters similar sources across subjects (Makeig et al., 2002). The second approach, Electromagnetic Spatiotemporal Independent Component Analysis (EMSICA), combines ICA decomposition and source current density estimation of the artifact-rejected data into a single spatiotemporal ICA decomposition for each subject (Tsai et al., 2006), concurrently identifying both the spatial source distribution of each cortical source and its event-related dynamics. Applied to the stop-signal task data, both approaches gave IC clusters that separately accounted for EEG processes expected in stop-signal tasks, including pre/postcentral mu rhythms, anterior-cingulate theta rhythm, and right-inferior frontal responses, the EMSICA clusters exhibiting more tightly correlated source areas and time-frequency features.

Frequency specific interactions of MEG resting state activity within and across brain networks as revealed by the multivariate interaction measure

Resting state networks (RSNs) are sets of brain regions exhibiting temporally coherent activity fluctuations in the absence of imposed task structure. RSNs have been extensively studied with fMRI in the infra-slow frequency range (nominally <10(-1)Hz). The topography of fMRI RSNs reflects stationary temporal correlation over minutes. However, neuronal communication occurs on a much faster time scale, at frequencies nominally in the range of 10(0)-10(2)Hz. We examined phase-shifted interactions in the delta (2-3.5 Hz), theta (4-7 Hz), alpha (8-12 Hz) and beta (13-30 Hz) frequency bands of resting-state source space MEG signals. These analyses were conducted between nodes of the dorsal attention network (DAN), one of the most robust RSNs, and between the DAN and other networks. Phase shifted interactions were mapped by the multivariate interaction measure (MIM), a measure of true interaction constructed from the maximization of imaginary coherency in the virtual channels comprised of voxel signals in source space. Non-zero-phase interactions occurred between homologous left and right hemisphere regions of the DAN in the delta and alpha frequency bands. Even stronger non-zero-phase interactions were detected between networks. Visual regions bilaterally showed phase-shifted interactions in the alpha band with regions of the DAN. Bilateral somatomotor regions interacted with DAN nodes in the beta band. These results demonstrate the existence of consistent, frequency specific phase-shifted interactions on a millisecond time scale between cortical regions within RSN as well as across RSNs.

A signal-processing pipeline for magnetoencephalography resting-state networks

To study functional connectivity using magnetoencephalographic (MEG) data, the high-quality source-level reconstruction of brain activity constitutes a critical element. MEG resting-state networks (RSNs) have been documented by means of a dedicated processing pipeline: MEG recordings are decomposed by independent component analysis (ICA) into artifact and brain components (ICs); next, the channel maps associated with the latter ones are projected into the source space and the resulting voxel-wise weights are used to linearly combine the IC time courses. An extensive description of the proposed pipeline is provided here, along with an assessment of its performances with respect to alternative approaches. The following investigations were carried out: (1) ICA decomposition algorithm. Synthetic data are used to assess the sensitivity of the ICA results to the decomposition algorithm, by testing FastICA, INFOMAX, and SOBI. FastICA with deflation approach, a standard solution, provides the best decomposition. (2) Recombination of brain ICs versus subtraction of artifactual ICs (at the channel level). Both the recombination of the brain ICs in the sensor space and the classical procedure of subtracting the artifactual ICs from the recordings provide a suitable reconstruction, with a lower distortion using the latter approach. (3) Recombination of brain ICs after localization versus localization of artifact-corrected recordings. The brain IC recombination after source localization, as implemented in the proposed pipeline, provides a lower source-level signal distortion. (4) Detection of RSNs. The accuracy in source-level reconstruction by the proposed pipeline is confirmed by an improved specificity in the retrieval of RSNs from experimental data.

Brain potentials related to corpus cavernosum electromyography

The aim of this study was to elucidate the relation between electrical activity in the corpus cavernosum (CC), penile responses and brain processes. EEG potentials, penile circumference and electrical activity of the CC (CC-EMG) were recorded simultaneously while male subjects were exposed to visual sexual stimuli. The trials were sorted by the penile response of the subjects (erection, maintenance or detumescence). The corresponding EEG recordings were subjected to independent component analysis (ICA) and then correlated with CC activity. We found that CC activity was decreased in the case of erection. EEG activity was found to be correlated with CC activity in most cases at the same instant or with subsequent CC activity. EEG activity at early time points after stimulus onset (<300 ms) was found to be correlated with CC activity, indicating penile response preparation at a pre-attentive processing level. These data indicate that (i) CC activity is under the control of brain processing and (ii) autonomous input reaches the CC in fractions of a second after sexual stimulus onset. Our experimental paradigm should be used for the study of psychogenic erectile dysfunctions and could help in the development of an objective measurement of this disturbance.

Dissociable medial frontal negativities from a common monitoring system for self- and externally caused failure of goal achievement

Goal-directed behavior requires the ability to adapt performance strategies based on the attribution of unintended outcomes to internal or external causes. Using event-related brain potentials, the present research compared neural activity following self-generated errors induced by a flanker task and following externally generated errors induced by supposed "technical malfunctions". Errors and malfunctions were associated with temporally dissociable ERP components, the short-latency error-related negativity (ERN) and the longer-latency feedback-related negativity (FRN), respectively. Independent component analysis (ICA) was applied to compare the underlying neural components of ERN and FRN. ICA results revealed that the FRN is attributable to the neural sources of the ERN, suggesting that the two components share a source network. Furthermore, single-trial amplitudes of ERN and FRN were specifically related to the implementation of error correction and malfunction compensation: the stronger the failure signal, the more efficient was remedial behavior. Together the results demonstrate that internally and externally generated unintended action outcomes engage a common monitoring mechanism that manifests in two temporally distinct ERP components and induces similar compensatory processes. The temporal dissociation of the ERP components might provide the basis for further processes of outcome attribution underlying action selection and changes in performance strategy. In line with recent neuroimaging findings, ERN and FRN appear to reflect the use of different sources of information about action outcome to update action value.

The independent components of auditory P300 and CNV evoked potentials derived from single-trial recordings

The back-projected independent components (BICs) of single-trial, auditory P300 and contingent negative variation (CNV) evoked potentials (EPs) were derived using independent component analysis (ICA) and cluster analysis. The method was tested in simulation including a study of the electric dipole equivalents of the signal sources. P300 data were obtained from healthy and Alzheimer's disease (AD) subjects. The BICs were of approximately 100 ms duration and approximated positive- and negative-going half-sinusoids. Some positively and negatively peaking BICs constituting the P300 coincided with known peaks in the averaged P300. However, there were trial-to-trial differences in their occurrences, particularly where a positive or a negative BIC could occur with the same latency in different trials, a fact which would be obscured by averaging them. These variations resulted in marked differences in the shapes of the reconstructed, artefact-free, single-trial P300s. The latencies of the BIC associated with the P3b peak differed between healthy and AD subjects (p < 0.01). More reliable evidence than that obtainable from single-trial or averaged P300s is likely to be found by studying the properties of the BICs over a number of trials. For the CNV, BICs corresponding to both the orienting and the expectancy components were found.