Quantification of network perfusion in ASL cerebral blood flow data with seed based and ICA approaches

Independent component analysis (ICA) or seed based approaches (SBA) in functional magnetic resonance imaging blood oxygenation level dependent (BOLD) data became widely applied tools to identify functionally connected, large scale brain networks. Differences between task conditions as well as specific alterations of the networks in patients as compared to healthy controls were reported. However, BOLD lacks the possibility of quantifying absolute network metabolic activity, which is of particular interest in the case of pathological alterations. In contrast, arterial spin labeling (ASL) techniques allow quantifying absolute cerebral blood flow (CBF) in rest and in task-related conditions. In this study, we explored the ability of identifying networks in ASL data using ICA and to quantify network activity in terms of absolute CBF values. Moreover, we compared the results to SBA and performed a test-retest analysis. Twelve healthy young subjects performed a fingertapping block-design experiment. During the task pseudo-continuous ASL was measured. After CBF quantification the individual datasets were concatenated and subjected to the ICA algorithm. ICA proved capable to identify the somato-motor and the default mode network. Moreover, absolute network CBF within the separate networks during either condition could be quantified. We could demonstrate that using ICA and SBA functional connectivity analysis is feasible and robust in ASL-CBF data. CBF functional connectivity is a novel approach that opens a new strategy to evaluate differences of network activity in terms of absolute network CBF and thus allows quantifying inter-individual differences in the resting state and task-related activations and deactivations.

A tutorial on data-driven methods for statistically assessing ERP topographies

Dynamic changes in ERP topographies can be conveniently analyzed by means of microstates, the so-called "atoms of thoughts", that represent brief periods of quasi-stable synchronized network activation. Comparing temporal microstate features such as on- and offset or duration between groups and conditions therefore allows a precise assessment of the timing of cognitive processes. So far, this has been achieved by assigning the individual time-varying ERP maps to spatially defined microstate templates obtained from clustering the grand mean data into predetermined numbers of topographies (microstate prototypes). Features obtained from these individual assignments were then statistically compared. This has the problem that the individual noise dilutes the match between individual topographies and templates leading to lower statistical power. We therefore propose a randomization-based procedure that works without assigning grand-mean microstate prototypes to individual data. In addition, we propose a new criterion to select the optimal number of microstate prototypes based on cross-validation across subjects. After a formal introduction, the method is applied to a sample data set of an N400 experiment and to simulated data with varying signal-to-noise ratios, and the results are compared to existing methods. In a first comparison with previously employed statistical procedures, the new method showed an increased robustness to noise, and a higher sensitivity for more subtle effects of microstate timing. We conclude that the proposed method is well-suited for the assessment of timing differences in cognitive processes. The increased statistical power allows identifying more subtle effects, which is particularly important in small and scarce patient populations.

Agency and ownership are independent components of 'sensing the self' in the auditory-verbal domain

'Sensing the self' relies on the ability to distinguish self-generated from external stimuli. It requires functioning mechanisms to establish feelings of agency and ownership. Agency is defined causally, where the subjects action is followed by an effect. Ownership is defined by the features of the effect, independent from the action. In our study, we manipulated these qualities separately. 13 right-handed healthy individuals performed the experiment while 76-channel EEG was recorded. Stimuli consisted of visually presented words, read aloud by the subject. The experiment consisted of six conditions: (a) subjects saw a word, read it aloud, heard it in their own voice; (b) like a, but the word was heard in an unfamiliar voice; (c) subject heard a word in his/her own voice without speaking; (d) like c, but the word was heard in an unfamiliar voice; (e) like a, but subjects heard the word with a delay; (f) subjects read without hearing. ERPs and difference maps were computed for all conditions. Effects were analysed topographically. The N100 (86-172 ms) displayed significant main effects of agency and ownership. The topographies of the two effects shared little common variance, suggesting independent effects. Later effects (174-400 ms) of agency and ownership were topographically similar, suggesting common mechanisms. Replicating earlier studies, significant N100 suppression was observed, with a topography resembling the agency effect. 'Sensing the self' appears to recruit from at least two very distinct processes: an agency assessment that represents causality and an ownership assessment that compares stimulus features with memory content.

Detecting Functional Hubs of Ictogenic Networks

Quantitative EEG (qEEG) has modified our understanding of epileptic seizures, shifting our view from the traditionally accepted hyper-synchrony paradigm toward more complex models based on re-organization of functional networks. However, qEEG measurements are so far rarely considered during the clinical decision-making process. To better understand the dynamics of intracranial EEG signals, we examine a functional network derived from the quantification of information flow between intracranial EEG signals. Using transfer entropy, we analyzed 198 seizures from 27 patients undergoing pre-surgical evaluation for pharmaco-resistant epilepsy. During each seizure we considered for each network the in-, out- and total "hubs", defined respectively as the time and the EEG channels with the maximal incoming, outgoing or total (bidirectional) information flow. In the majority of cases we found that the hubs occur around the middle of seizures, and interestingly not at the beginning or end, where the most dramatic EEG signal changes are found by visual inspection. For the patients who then underwent surgery, good postoperative clinical outcome was on average associated with a higher percentage of out- or total-hubs located in the resected area (for out-hubs p = 0.01, for total-hubs p = 0.04). The location of in-hubs showed no clear predictive value. We conclude that the study of functional networks based on qEEG measurements may help to identify brain areas that are critical for seizure generation and are thus potential targets for focused therapeutic interventions.

Localization of Epileptogenic Zone on Pre-surgical Intracranial EEG Recordings: Toward a Validation of Quantitative Signal Analysis Approaches

In patients diagnosed with pharmaco-resistant epilepsy, cerebral areas responsible for seizure generation can be defined by performing implantation of intracranial electrodes. The identification of the epileptogenic zone (EZ) is based on visual inspection of the intracranial electroencephalogram (IEEG) performed by highly qualified neurophysiologists. New computer-based quantitative EEG analyses have been developed in collaboration with the signal analysis community to expedite EZ detection. The aim of the present report is to compare different signal analysis approaches developed in four different European laboratories working in close collaboration with four European Epilepsy Centers. Computer-based signal analysis methods were retrospectively applied to IEEG recordings performed in four patients undergoing pre-surgical exploration of pharmaco-resistant epilepsy. The four methods elaborated by the different teams to identify the EZ are based either on frequency analysis, on nonlinear signal analysis, on connectivity measures or on statistical parametric mapping of epileptogenicity indices. All methods converge on the identification of EZ in patients that present with fast activity at seizure onset. When traditional visual inspection was not successful in detecting EZ on IEEG, the different signal analysis methods produced highly discordant results. Quantitative analysis of IEEG recordings complement clinical evaluation by contributing to the study of epileptogenic networks during seizures. We demonstrate that the degree of sensitivity of different computer-based methods to detect the EZ in respect to visual EEG inspection depends on the specific seizure pattern.

EEG microstates during resting represent personality differences

We investigated the spontaneous brain electric activity of 13 skeptics and 16 believers in paranormal phenomena; they were university students assessed with a self-report scale about paranormal beliefs. 33-channel EEG recordings during no-task resting were processed as sequences of momentary potential distribution maps. Based on the maps at peak times of Global Field Power, the sequences were parsed into segments of quasi-stable potential distribution, the 'microstates'. The microstates were clustered into four classes of map topographies (A-D). Analysis of the microstate parameters time coverage, occurrence frequency and duration as well as the temporal sequence (syntax) of the microstate classes revealed significant differences: Believers had a higher coverage and occurrence of class B, tended to decreased coverage and occurrence of class C, and showed a predominant sequence of microstate concatenations from A to C to B to A that was reversed in skeptics (A to B to C to A). Microstates of different topographies, putative "atoms of thought", are hypothesized to represent different types of information processing.The study demonstrates that personality differences can be detected in resting EEG microstate parameters and microstate syntax. Microstate analysis yielded no conclusive evidence for the hypothesized relation between paranormal belief and schizophrenia.

Meditators and non-meditators: EEG source imaging during resting

Many meditation exercises aim at increased awareness of ongoing experiences through sustained attention and at detachment, i.e., non-engaging observation of these ongoing experiences by the intent not to analyze, judge or expect anything. Long-term meditation practice is believed to generalize the ability of increased awareness and greater detachment into everyday life. We hypothesized that neuroplasticity effects of meditation (correlates of increased awareness and detachment) would be detectable in a no-task resting state. EEG recorded during resting was compared between Qigong meditators and controls. Using LORETA (low resolution electromagnetic tomography) to compute the intracerebral source locations, differences in brain activations between groups were found in the inhibitory delta EEG frequency band. In the meditators, appraisal systems were inhibited, while brain areas involved in the detection and integration of internal and external sensory information showed increased activation. This suggests that neuroplasticity effects of long-term meditation practice, subjectively described as increased awareness and greater detachment, are carried over into non-meditating states.

Classes of multichannel EEG microstates in light and deep hypnotic conditions

The study assessed the brain electric mechanisms of light and deep hypnotic conditions in the framework of EEG temporal microstates. Multichannel EEG of healthy volunteers during initial resting, light hypnosis, deep hypnosis, and eventual recovery was analyzed into temporal EEG microstates of four classes. Microstates are defined by the spatial configuration of their potential distribution maps ([Symbol: see text]potential landscapes') on the head surface. Because different potential landscapes must have been generated by different active neural assemblies, it is reasonable to assume that they also incorporate different brain functions. The observed four microstate classes were very similar to the four standard microstate classes A, B, C, D [Koenig, T. et al. Neuroimage, 2002;16: 41-8] and were labeled correspondingly. We expected a progression of microstate characteristics from initial resting to light to deep hypnosis. But, all three microstate parameters (duration, occurrence/second and %time coverage) yielded values for initial resting and final recovery that were between those of the two hypnotic conditions of light and deep hypnosis. Microstates of the classes B and D showed decreased duration, occurrence/second and %time coverage in deep hypnosis compared to light hypnosis; this was contrary to microstates of classes A and C which showed increased values of all three parameters. Reviewing the available information about microstates in other conditions, the changes from resting to light hypnosis in certain respects are reminiscent of changes to meditation states, and changes to deep hypnosis of those in schizophrenic states.

The Influence of Pre-stimulus EEG Activity on Reaction Time During a Verbal Sternberg Task is Related to Musical Expertise

Abstract Previous work highlighted the possibility that musical training has an influence on cognitive functioning. The suggested reason for this influence is the strong recruitment of attention, planning, and working memory functions during playing a musical instrument. The purpose of the present work was twofold, namely to evaluate the general relationship between pre-stimulus electrophysiological activity and cognition, and more specifically the influence of musical expertise on working memory functions. With this purpose in mind, we used covariance mapping analyses to evaluate whether pre-stimulus electroencephalographic activity is predictive for reaction time during a visual working memory task (Sternberg paradigm) in musicians and non-musicians. In line with our hypothesis, we replicated previous findings pointing to a general predictive value of pre-stimulus activity for working memory performance. Most importantly, we also provide first evidence for an influence of musical expertise on working memory performance that could distinctively be predicted by pre-stimulus spectral power. Our results open novel perspectives for better comprehending the vast influences of musical expertise on cognition.

Towards Using Microstate-Neurofeedback for the Treatment of Psychotic Symptoms in Schizophrenia. A Feasibility Study in Healthy Participants

Spontaneous EEG signal can be parsed into sub-second periods of stable functional states (microstates) that assumingly correspond to brief large scale synchronization events. In schizophrenia, a specific class of microstate (class "D") has been found to be shorter than in healthy controls and to be correlated with positive symptoms. To explore potential new treatment options in schizophrenia, we tested in healthy controls if neurofeedback training to self-regulate microstate D presence is feasible and what learning patterns are observed. Twenty subjects underwent EEG-neurofeedback training to up-regulate microstate D presence. The protocol included 20 training sessions, consisting of baseline trials (resting state), regulation trials with auditory feedback contingent on microstate D presence, and a transfer trial. Response to neurofeedback was assessed with mixed effects modelling. All participants increased the percentage of time spent producing microstate D in at least one of the three conditions (p < 0.05). Significant between-subjects across-sessions results showed an increase of 0.42 % of time spent producing microstate D in baseline (reflecting a sustained change in the resting state), 1.93 % of increase during regulation and 1.83 % during transfer. Within-session analysis (performed in baseline and regulation trials only) showed a significant 1.65 % increase in baseline and 0.53 % increase in regulation. These values are in a range that is expected to have an impact upon psychotic experiences. Additionally, we found a negative correlation between alpha power and microstate D contribution during neurofeedback training. Given that microstate D has been related to attentional processes, this result provides further evidence that the training was to some degree specific for the attentional network. We conclude that microstate-neurofeedback training proved feasible in healthy subjects. The implementation of the same protocol in schizophrenia patients may promote skills useful to reduce positive symptoms by means of EEG-neurofeedback.

Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

Disturbances of agency and ownership in schizophrenia: An auditory verbal event related potentials study

A ‘sense of self’ is essentially the ability to distinguish between self-generated and external stimuli. It consists of at least two very basic senses: a sense of agency and a sense of ownership. Disturbances seem to provide a basic deficit in many psychiatric diseases. The aim of our study was to manipulate those qualities separately in 28 patients with schizophrenia (14 auditory hallucinators and 14 non-hallucinators) and 28 healthy controls (HC) and to investigate the effects on the topographies and the power of the event-related potential (ERP). We performed a 76-channel EEG while the participants performed the task as in our previous paper. We computed ERPs and difference maps for the conditions and compared the amount of agency and ownership between the HC and the patients. Furthermore, we compared the global field power and the topographies of these effects. Our data showed effects of agency and ownership in the healthy controls and the hallucinator group and to a lesser degree in the non-hallucinator group. We found a reduction of the N100 during the presence of agency, and a bilateral temporal negativity related to the presence of ownership. For the agency effects, we found significant differences between HC and the patients. Contrary to the expectations, our findings were more pronounced in non-hallucinators, suggesting a more profoundly disturbed sense of agency compared to hallucinators. A contemporary increase of global field power in both patient groups indicates a compensatory recruitment of other mechanisms not normally associated with the processing of agency and ownership.

Topographic mapping and source localization of the pattern onset visual evoked magnetic response

The topography of the visual evoked magnetic response (VEMR) to a pattern onset stimulus was investigated using 4 check sizes and 3 contrast levels. The pattern onset response consists of three early components within the first 200ms, CIm, CIIm and CIIIm. The CIIm is usually of high amplitude and is very consistent in latency within a subject. Half field (HF) stimuli produce their strongest response over the contralateral hemisphere; the RHF stimulus exhibiting a lower positivity (outgoing field) and an upper negativity (ingoing field), rotated towards the midline. LHF stimulation produced the opposite response, a lower negative and an upper positive. Larger check sizes produce a single area of ingoing and outgoing field while smaller checks produce on area of ingoing and outgoing field over each hemisphere. Latency did not appear to vary with change in contrast but amplitudes increased with increasing contrast. A more detailed topographic study incorporating source localisation procedures suggested a source for CIIm - 4cm below the scalp, close to the midline with current flowing towards the lateral surface. Similar depth and position estimates but with opposite polarity were obtained for the pattern shift P100m previously. Hence, the P100m and the CIIm may originate in similar areas of visual cortex but reveal different aspects of visual processing. © 1992 Human Sciences Press, Inc.

Topographic mapping and source localization of the pattern reversal visual evoked magnetic response

The topography of the visual evoked magnetic response (VEMR) to pattern reversal stimulation was studied in four normal subjects using a single channel BTI magnetometer. VEMRs were recorded from 20 locations over the occipital scalp and the topographic distribution of the most consistent component (P100M) studied. A single dipole in a sphere model was fitted to the data. Topographic maps were similar when recorded two months apart on the same subject to the same stimulus. Half field (HF) stimulation elicited responses from sources on the medial surface of the calcarine fissure mainly in the contralateral hemisphere as predicted by the cruciform model. The full field (FF) responses to large checks were approximately the sum of the HF responses. However, with small checks, FF stimulation appeared to activate a different combination of sources than the two HFs. In addition, HF topography was more consistent between subjects than FF for small check sizes. Topographic studies of the VEMR may help to explain the analogous visual evoked electrical response and will be essential to define optimal recording positions for clinical applications.