Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

In this review, we consider the potential functional role of beta-band oscillations, which at present is not yet well understood. We discuss evidence from recent studies on top-down mechanisms involved in cognitive processing, on the motor system and on the pathophysiology of movement disorders that suggest a unifying hypothesis: beta-band activity seems related to the maintenance of the current sensorimotor or cognitive state. We hypothesize that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected. Moreover, we suggest that pathological enhancement of beta-band activity is likely to result in an abnormal persistence of the status quo and a deterioration of flexible behavioural and cognitive control.

Beta-band oscillations--signalling the status quo?

This paper reviews and synthesizes functional imaging research that over the past decade has begun to offer new insights into the brain mechanisms underlying emotion regulation. Toward that end, the first section of the paper outlines a model of the processes and neural systems involved in emotion generation and regulation. The second section surveys recent research supporting and elaborating the model, focusing primarily on studies of the most commonly investigated strategy, which is known as reappraisal. At its core, the model specifies how prefrontal and cingulate control systems modulate activity in perceptual, semantic, and affect systems as a function of one's regulatory goals, tactics, and the nature of the stimuli and emotions being regulated. This section also shows how the model can be generalized to understand the brain mechanisms underlying other emotion regulation strategies as well as a range of other allied phenomena. The third and last section considers directions for future research, including how basic models of emotion regulation can be translated to understand changes in emotion across the life span and in clinical disorders.

Functional imaging studies of emotion regulation: a synthetic review and evolving model of the cognitive control of emotion.

In recent years, an explosion of neuroimaging studies has examined cognitive reappraisal, an emotion regulation strategy that involves changing the way one thinks about a stimulus in order to change its affective impact Existing models broadly agree that reappraisal recruits frontal and parietal control regions to modulate emotional responding in the amygdala, but they offer competing visions of how this is accomplished One view holds that control regions engage ventromedial prefrontal cortex (vmPFC), an area associated with fear extinction, that in turn modulates amygdala responses An alternative view is that control regions modulate semantic representations in lateral temporal cortex that indirectly influence emotion-related responses in the amygdala Furthermore, while previous work has emphasized the amygdala, whether reappraisal influences other regions implicated in emotional responding remains unknown To resolve these questions, we performed a meta-analysis of 48 neuroimaging studies of reappraisal, most involving downregulation of negative affect Reappraisal consistently 1) activated cognitive control regions and lateral temporal cortex, but not vmPFC, and 2) modulated the bilateral amygdala, but no other brain regions This suggests that reappraisal involves the use of cognitive control to modulate semantic representations of an emotional stimulus, and these altered representations in turn attenuate activity in the amygdala

/pdf/cognitive-reappraisal-of-emotion-a-meta-analysis-of-human-5dtqxqj6ks.pdf

Cognitive Reappraisal of Emotion: A Meta-Analysis of Human Neuroimaging Studies

State-Trait Anxiety Inventoryによるペインクリニック外来患者の不安の評価

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is tomaximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

/pdf/ragu-a-free-tool-for-the-analysis-of-eeg-and-meg-event-4fz1nz4pwu.pdf

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

BOLD correlates of EEG alpha phase-locking and the fMRI default mode network.

Modulation of anticipatory emotion and perception processing by cognitive control.

Background: fMRI Resting State Networks (RSNs) have gained importance in the present fMRI literature. Although their functional role is unquestioned and their physiological origin is nowadays widely accepted, little is known about their relationship to neuronal activity. The combined recording of EEG and fMRI allows the temporal correlation between fluctuations of the RSNs and the dynamics of EEG spectral amplitudes. So far, only relationships between several EEG frequency bands and some RSNs could be demonstrated, but no study accounted for the spatial distribution of frequency domain EEG.

Methodology/Principal Findings: In the present study we report on the topographic association of EEG spectral fluctuations and RSN dynamics using EEG covariance mapping. All RSNs displayed significant covariance maps across a broad EEG frequency range. Cluster analysis of the found covariance maps revealed the common standard EEG frequency bands. We found significant differences between covariance maps of the different RSNs and these differences depended on the frequency band.

Conclusions/Significance: Our data supports the physiological and neuronal origin of the RSNs and substantiates the assumption that the standard EEG frequency bands and their topographies can be seen as electrophysiological signatures of underlying distributed neuronal networks.

/pdf/topographic-electrophysiological-signatures-of-fmri-resting-3w1jggb822.pdf

Topographic electrophysiological signatures of FMRI Resting State Networks.

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.

/pdf/a-tutorial-on-data-driven-methods-for-statistically-2w16vkmd4b.pdf

Mara Kottlow

Papers

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

BOLD correlates of EEG alpha phase-locking and the fMRI default mode network.

Modulation of anticipatory emotion and perception processing by cognitive control.

Topographic electrophysiological signatures of FMRI Resting State Networks.

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