Overlapping communities reveal rich structure in large-scale brain networks during rest and task conditions.

Large-scale analysis of functional MRI data has revealed that brain regions can be grouped into stable "networks" or communities. In many instances, the communities are characterized as relatively disjoint. Although recent work indicates that brain regions may participate in multiple communities (for example, hub regions), the extent of community overlap is poorly understood. To address these issues, here we investigated large-scale brain networks based on "rest" and task human functional MRI data by employing a mixed-membership Bayesian model that allows each brain region to belong to all communities simultaneously with varying membership strengths. The approach allowed us to 1) compare the structure of disjoint and overlapping communities; 2) determine the relationship between functional diversity (how diverse is a region's functional activation repertoire) and membership diversity (how diverse is a region's affiliation to communities); 3) characterize overlapping community structure; 4) characterize the degree of non-modularity in brain networks; 5) study the distribution of "bridges", including bottleneck and hub bridges. Our findings revealed the existence of dense community overlap that was not limited to "special" hubs. Furthermore, the findings revealed important differences between community organization during rest and during specific task states. Overall, we suggest that dense overlapping communities are well suited to capture the flexible and task dependent mapping between brain regions and their functions.

Conflicting demands of abstract and specific visual object processing resolved by frontoparietal networks.

Object categorization and exemplar identification place conflicting demands on the visual system, yet humans easily perform these fundamentally contradictory tasks. Previous studies suggest the existence of dissociable visual processing subsystems to accomplish the two abilities-an abstract category (AC) subsystem that operates effectively in the left hemisphere and a specific exemplar (SE) subsystem that operates effectively in the right hemisphere. This multiple subsystems theory explains a range of visual abilities, but previous studies have not explored what mechanisms exist for coordinating the function of multiple subsystems and/or resolving the conflicts that would arise between them. We collected functional MRI data while participants performed two variants of a cue-probe working memory task that required AC or SE processing. During the maintenance phase of the task, the bilateral intraparietal sulcus (IPS) exhibited hemispheric asymmetries in functional connectivity consistent with exerting proactive control over the two visual subsystems: greater connectivity to the left hemisphere during the AC task, and greater connectivity to the right hemisphere during the SE task. Moreover, probe-evoked activation revealed activity in a broad frontoparietal network (containing IPS) associated with reactive control when the two visual subsystems were in conflict, and variations in this conflict signal across trials was related to the visual similarity of the cue-probe stimulus pairs. Although many studies have confirmed the existence of multiple visual processing subsystems, this study is the first to identify the mechanisms responsible for coordinating their operations.

Network organization unfolds over time during periods of anxious anticipation.

Entering a state of anxious anticipation triggers widespread changes across large-scale networks in the brain. The temporal aspects of this transition into an anxious state are poorly understood. To address this question, an instructed threat of shock paradigm was used while recording functional MRI in humans to measure how activation and functional connectivity change over time across the salience, executive, and task-negative networks and how they interact with key regions implicated in emotional processing; the amygdala and bed nucleus of the stria terminalis (BNST). Transitions into threat blocks were associated with transient responses in regions of the salience network and sustained responses in a putative BNST site, among others. Multivariate network measures of communication were computed, revealing changes to network organization during transient and sustained periods of threat, too. For example, the salience network exhibited a transient increase in network efficiency followed by a period of sustained decreased efficiency. The amygdala became more central to network function (as assessed via betweenness centrality) during threat across all participants, and the extent to which the BNST became more central during threat depended on self-reported anxiety. Together, our study unraveled a progression of responses and network-level changes due to sustained threat. In particular, our results reveal how network organization unfolds with time during periods of anxious anticipation.

Discovering networks altered by potential threat ("anxiety") using quadratic discriminant analysis.

Researchers have only recently begun using functional neuroimaging to explore the human response to periods of sustained anxious anticipation, namely potential threat. Here, we investigated brain responses acquired with functional MRI during an instructed threat of shock paradigm used to create sustained periods of aversive anticipation. In this re-analysis of previously published data, we employed quadratic discriminant analysis to classify the multivariate pattern of whole-brain functional connectivity and to identify connectivity changes during periods of potential threat. Our method identifies clusters with altered connectivity on a voxelwise basis, thus eschewing the need to define regions a priori. Classifier generalization was evaluated by testing on data from participants not used during training. Robust classification between threat and safe contexts was possible, and inspection of "diagnostic features" revealed altered functional connectivity involving the intraparietal sulcus, task-negative regions, striatum, and anterior cingulate cortex. We anticipate that the proposed method will prove useful to experimenters wishing to identify large-scale functional networks that distinguish between experimental conditions or groups.

Separability of abstract-category and specific-exemplar visual object subsystems: evidence from fMRI pattern analysis.

Previous research indicates that dissociable neural subsystems underlie abstract-category (AC) recognition and priming of objects (e.g., cat, piano) and specific-exemplar (SE) recognition and priming of objects (e.g., a calico cat, a different calico cat, a grand piano, etc.). However, the degree of separability between these subsystems is not known, despite the importance of this issue for assessing relevant theories. Visual object representations are widely distributed in visual cortex, thus a multivariate pattern analysis (MVPA) approach to analyzing functional magnetic resonance imaging (fMRI) data may be critical for assessing the separability of different kinds of visual object processing. Here we examined the neural representations of visual object categories and visual object exemplars using multi-voxel pattern analyses of brain activity elicited in visual object processing areas during a repetition-priming task. In the encoding phase, participants viewed visual objects and the printed names of other objects. In the subsequent test phase, participants identified objects that were either same-exemplar primed, different-exemplar primed, word-primed, or unprimed. In visual object processing areas, classifiers were trained to distinguish same-exemplar primed objects from word-primed objects. Then, the abilities of these classifiers to discriminate different-exemplar primed objects and word-primed objects (reflecting AC priming) and to discriminate same-exemplar primed objects and different-exemplar primed objects (reflecting SE priming) was assessed. Results indicated that (a) repetition priming in occipital-temporal regions is organized asymmetrically, such that AC priming is more prevalent in the left hemisphere and SE priming is more prevalent in the right hemisphere, and (b) AC and SE subsystems are weakly modular, not strongly modular or unified.

Can theories of visual representation help to explain asymmetries in amygdala function?

Emotional processing differs between the left and right hemispheres of the brain, and functional differences have been reported more specifically between the left and right amygdalae, subcortical structures heavily implicated in emotional processing. However, the empirical pattern of amygdalar asymmetries is inconsistent with extant theories of emotional asymmetries. Here we review this discrepancy, and we hypothesize that hemispheric differences in visual object processing help to explain the previously reported functional differences between the left and right amygdalae. The implication that perceptual factors play a large role in determining amygdalar asymmetries may help to explain amygdalar dysfunction in the development and maintenance of posttraumatic stress disorder.

Stress potentiates early and attenuates late stages of visual processing.

Stress can fundamentally alter neural responses to incoming information. Recent research suggests that stress and anxiety shift the balance of attention away from a task-directed mode, governed by prefrontal cortex, to a sensory-vigilance mode, governed by the amygdala and other threat-sensitive regions. A key untested prediction of this framework is that stress exerts dissociable effects on different stages of information processing. This study exploited the temporal resolution afforded by event-related potentials to disentangle the impact of stress on vigilance, indexed by early perceptual activity, from its impact on task-directed cognition, indexed by later postperceptual activity in humans. Results indicated that threat of shock amplified stress, measured using retrospective ratings and concurrent facial electromyography. Stress also double-dissociated early sensory-specific processing from later task-directed processing of emotionally neutral stimuli: stress amplified N1 (184-236 ms) and attenuated P3 (316-488 ms) activity. This demonstrates that stress can have strikingly different consequences at different processing stages. Consistent with recent suggestions, stress amplified earlier extrastriate activity in a manner consistent with vigilance for threat (N1), but disrupted later activity associated with the evaluation of task-relevant information (P3). These results provide a novel basis for understanding how stress can modulate information processing in everyday life and stress-sensitive disorders.

Electromyogenic Artifacts and Electroencephalographic Inferences Revisited.

Recent years have witnessed a renewed interest in using oscillatory brain electrical activity to understand the neural bases of cognition and emotion. Electrical signals originating from pericranial muscles represent a profound threat to the validity of such research. Recently, McMenamin et al (2010) examined whether independent component analysis (ICA) provides a sensitive and specific means of correcting electromyogenic (EMG) artifacts. This report sparked the accompanying commentary (Olbrich, Jödicke, Sander, Himmerich & Hegerl, in press), and here we revisit the question of how EMG can alter inferences drawn from the EEG and what can be done to minimize its pernicious effects. Accordingly, we briefly summarize salient features of the EMG problem and review recent research investigating the utility of ICA for correcting EMG and other artifacts. We then directly address the key concerns articulated by Olbrich and provide a critique of their efforts at validating ICA. We conclude by identifying key areas for future methodological work and offer some practical recommendations for intelligently addressing EMG artifact.

Identifying robust and sensitive frequency bands for interrogating neural oscillations.

Recent years have seen an explosion of interest in using neural oscillations to characterize the mechanisms supporting cognition and emotion. Oftentimes, oscillatory activity is indexed by mean power density in predefined frequency bands. Some investigators use broad bands originally defined by prominent surface features of the spectrum. Others rely on narrower bands originally defined by spectral factor analysis (SFA). Presently, the robustness and sensitivity of these competing band definitions remains unclear. Here, a Monte Carlo-based SFA strategy was used to decompose the tonic ("resting" or "spontaneous") electroencephalogram (EEG) into five bands: delta (1-5Hz), alpha-low (6-9Hz), alpha-high (10-11Hz), beta (12-19Hz), and gamma (>21Hz). This pattern was consistent across SFA methods, artifact correction/rejection procedures, scalp regions, and samples. Subsequent analyses revealed that SFA failed to deliver enhanced sensitivity; narrow alpha sub-bands proved no more sensitive than the classical broadband to individual differences in temperament or mean differences in task-induced activation. Other analyses suggested that residual ocular and muscular artifact was the dominant source of activity during quiescence in the delta and gamma bands. This was observed following threshold-based artifact rejection or independent component analysis (ICA)-based artifact correction, indicating that such procedures do not necessarily confer adequate protection. Collectively, these findings highlight the limitations of several commonly used EEG procedures and underscore the necessity of routinely performing exploratory data analyses, particularly data visualization, prior to hypothesis testing. They also suggest the potential benefits of using techniques other than SFA for interrogating high-dimensional EEG datasets in the frequency or time-frequency (event-related spectral perturbation, event-related synchronization/desynchronization) domains.

Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG.

Muscle electrical activity, or "electromyogenic" (EMG) artifact, poses a serious threat to the validity of electroencephalography (EEG) investigations in the frequency domain. EMG is sensitive to a variety of psychological processes and can mask genuine effects or masquerade as legitimate neurogenic effects across the scalp in frequencies at least as low as the alpha band (8-13 Hz). Although several techniques for correcting myogenic activity have been described, most are subjected to only limited validation attempts. Attempts to gauge the impact of EMG correction on intracerebral source models (source "localization" analyses) are rarer still. Accordingly, we assessed the sensitivity and specificity of one prominent correction tool, independent component analysis (ICA), on the scalp and in the source-space using high-resolution EEG. Data were collected from 17 participants while neurogenic and myogenic activity was independently varied. Several protocols for classifying and discarding components classified as myogenic and non-myogenic artifact (e.g., ocular) were systematically assessed, leading to the exclusion of one-third to as much as three-quarters of the variance in the EEG. Some, but not all, of these protocols showed adequate performance on the scalp. Indeed, performance was superior to previously validated regression-based techniques. Nevertheless, ICA-based EMG correction exhibited low validity in the intracerebral source-space, likely owing to incomplete separation of neurogenic from myogenic sources. Taken with prior work, this indicates that EMG artifact can substantially distort estimates of intracerebral spectral activity. Neither regression- nor ICA-based EMG correction techniques provide complete safeguards against such distortions. In light of these results, several practical suggestions and recommendations are made for intelligently using ICA to minimize EMG and other common artifacts.

Right dorsolateral prefrontal cortical activity and behavioral inhibition.

Individuals show marked variation in their responses to threat. Such individual differences in behavioral inhibition play a profound role in mental and physical well-being. Behavioral inhibition is thought to reflect variation in the sensitivity of a distributed neural system responsible for generating anxiety and organizing defensive responses to threat and punishment. Although progress has been made in identifying the key constituents of this behavioral inhibition system in humans, the involvement of dorsolateral prefrontal cortex (DLPFC) remains unclear. Here, we acquired self-reported Behavioral Inhibition System Sensitivity scores and high-resolution electroencephalography from a large sample (n= 51). Using the enhanced spatial resolution afforded by source modeling techniques, we show that individuals with greater tonic (resting) activity in right-posterior DLPFC rate themselves as more behaviorally inhibited. This observation provides novel support for recent conceptualizations of behavioral inhibition and clues to the mechanisms that might underlie variation in threat-induced negative affect.

Electromyogenic artifacts and electroencephalographic inferences.

Muscle or electromyogenic (EMG) artifact poses a serious risk to inferential validity for any electroencephalography (EEG) investigation in the frequency-domain owing to its high amplitude, broad spectrum, and sensitivity to psychological processes of interest. Even weak EMG is detectable across the scalp in frequencies as low as the alpha band. Given these hazards, there is substantial interest in developing EMG correction tools. Unfortunately, most published techniques are subjected to only modest validation attempts, rendering their utility questionable. We review recent work by our laboratory quantitatively investigating the validity of two popular EMG correction techniques, one using the general linear model (GLM), the other using temporal independent component analysis (ICA). We show that intra-individual GLM-based methods represent a sensitive and specific tool for correcting on-going or induced, but not evoked (phase-locked) or source-localized, spectral changes. Preliminary work with ICA shows that it may not represent a panacea for EMG contamination, although further scrutiny is strongly warranted. We conclude by describing emerging methodological trends in this area that are likely to have substantial benefits for basic and applied EEG research.

Comorbid anxiety moderates the relationship between depression history and prefrontal EEG asymmetry.

The internalizing spectrum of psychiatric disorders-depression and anxiety-are common, highly comorbid, and challenging to treat. Individuals with childhood onset depression have a particularly poor prognosis. There is compelling evidence that individuals with depression display reduced resting-state EEG activity at sensors overlying the left prefrontal cortex, even during periods of remission, but it remains unknown whether this asymmetry is evident among individuals with a comorbid anxiety disorder. Here, we demonstrate that women with a history of childhood onset depression and no anxiety disorder (n = 37) show reduced left lateral frontal activity compared to psychiatrically healthy controls (n = 69). In contrast, women with a history of childhood onset depression and pathological levels of anxious apprehension (n = 18)-as indexed by a current generalized anxiety disorder, obsessive compulsive disorder, or separation anxiety disorder diagnosis-were statistically indistinguishable from healthy controls. Collectively, these observations suggest that anxious apprehension can mask the relationship between prefrontal EEG asymmetry and depression. These findings have implications for understanding (a) prefrontal EEG asymmetry as a neurophysiological marker of depression, (b) the comorbidity of depression and anxiety, and (c) failures to replicate the relationship between prefrontal EEG asymmetry and depression. More broadly, they set the stage for developing refined interventions for internalizing psychopathology.

The Diagnosticity of Color for Emotional Objects.

Object classification can be facilitated if simple diagnostic features can be used to determine class membership. Previous studies have found that simple shapes may be diagnostic for emotional content and automatically alter the allocation of visual attention. In the present study, we analyzed whether color is diagnostic of emotional content and tested whether emotionally diagnostic hues alter the allocation of visual attention. Reddish-yellow hues are more common in (i.e., diagnostic of) emotional images, particularly images with positive emotional content. An exogenous cueing paradigm was employed to test whether these diagnostic hues orient attention differently from other hues due to the emotional diagnosticity. In two experiments, we found that participants allocated attention differently to diagnostic hues than to non-diagnostic hues, in a pattern indicating a broadening of spatial attention when cued with diagnostic hues. Moreover, the attentional broadening effect was predicted by self-reported measures of affective style, linking the behavioral effect to emotional processes. These results confirm the existence and use of diagnostic features for the rapid detection of emotional content.

Validation of regression-based myogenic correction techniques for scalp and source-localized EEG.

EEG and EEG source-estimation are susceptible to electromyographic artifacts (EMG) generated by the cranial muscles. EMG can mask genuine effects or masquerade as a legitimate effect-even in low frequencies, such as alpha (8-13 Hz). Although regression-based correction has been used previously, only cursory attempts at validation exist, and the utility for source-localized data is unknown. To address this, EEG was recorded from 17 participants while neurogenic and myogenic activity were factorially varied. We assessed the sensitivity and specificity of four regression-based techniques: between-subjects, between-subjects using difference-scores, within-subjects condition-wise, and within-subject epoch-wise on the scalp and in data modeled using the LORETA algorithm. Although within-subject epoch-wise showed superior performance on the scalp, no technique succeeded in the source-space. Aside from validating the novel epoch-wise methods on the scalp, we highlight methods requiring further development.