Working memory of identification of emotional vocal expressions: an fMRI study

Mental Workload evaluation using weighted phase lag index and coherence features extracted from EEG data

Electroencephalogram (EEG) represents an effective, non-invasive technology to study mental workload. However, volume conduction, a common EEG artifact, influences functional connectivity analysis of EEG data. EEG coherence has been used traditionally to investigate functional connectivity between brain areas associated with mental workload, while weighted Phase Lag Index (wPLI) is a measure that improves on coherence by reducing susceptibility to volume conduction, a common EEG artifact. The goal of this study was to compare two methods of functional connectivity analysis, wPLI and coherence, in the context of mental workload evaluation. The study involved model development for mental workload domains and comparing their performance using coherence-based features, wPLI-based features, and a combination of both. Generalized linear mixed-effects model (GLMM) with the least absolute shrinkage and selection operator (LASSO) feature selection method was used for model development. Results indicated that the model developed using a combination of both feature types demonstrated improved predictive performance across all mental workload domains, compared to models that used each feature type individually. The R2 values were 0.82 for perceived task complexity, 0.71 for distraction, 0.91 for mental demand, 0.85 for physical demand, 0.74 for situational stress, and 0.74 for temporal demand. Furthermore, task complexity and functional connectivity patterns in different brain areas were identified as significant contributors to perceived mental workload (p-value<0.05). Findings showed the potential of using EEG data for mental workload evaluation which suggests that combination of coherence and wPLI can improve the accuracy of mental workload domains prediction. Future research should aim to validate these results on larger, diverse datasets to confirm their generalizability and refine the predictive models.

Assessing mental demand in consecutive interpreting: Insights from an fNIRS study

Consecutive interpreting involves a demanding language task where mental workload (MWL) is crucial for assessing interpreters' performance. An elevated cognitive load in interpreters may lead to the interpretation failures. The widely used NASA-TLX questionnaire effectively measures MWL. However, a global score was employed in previous interpretation studies, overlooking the distinct contributions of MWL components to the interpreters' performance. Accordingly, we recruited twenty novice interpreters who were postgraduate students specializing in interpreting to complete the consecutive interpreting task. Throughout the process, we used functional near-infrared spectroscopy (fNIRS) to monitor the hemodynamic response in participants' brains. The NASA-TLX was used to measure the MWL during interpreting with six components, including mental demand, physical demand, temporal demand, performance, effort, and frustration. Five interpretation experts were invited to assess the interpretation quality. The Bayes factor approach was employed to explore the components that contributes the most to the interpretation quality. It indicated that mental demand strongly contributed to the interpretation quality. Moreover, the mediation analysis revealed a positive correlation between mental demand and brain activation in three brain areas, which, in turn, was negatively correlated with interpretation quality, indicating the predictive role of mental demand in interpretation quality through the mediating of brain activation. The functions of the mediating brain areas, including the inferior frontal gyrus, middle temporal gyrus, and inferior temporal gyrus, aligned with the three efforts proposed by Gile's effort model, which emphasizes the significance of three fundamental efforts in achieving successful interpreting. These findings have implications for interpreter learning and training.

Development of performance and learning rate evaluation models in robot-assisted surgery using electroencephalography and eye-tracking

The existing performance evaluation methods in robot-assisted surgery (RAS) are mainly subjective, costly, and affected by shortcomings such as the inconsistency of results and dependency on the raters' opinions. The aim of this study was to develop models for an objective evaluation of performance and rate of learning RAS skills while practicing surgical simulator tasks. The electroencephalogram (EEG) and eye-tracking data were recorded from 26 subjects while performing Tubes, Suture Sponge, and Dots and Needles tasks. Performance scores were generated by the simulator program. The functional brain networks were extracted using EEG data and coherence analysis. Then these networks, along with community detection analysis, facilitated the extraction of average search information and average temporal flexibility features at 21 Brodmann areas (BA) and four band frequencies. Twelve eye-tracking features were extracted and used to develop linear random intercept models for performance evaluation and multivariate linear regression models for the evaluation of the learning rate. Results showed that subject-wise standardization of features improved the R2 of the models. Average pupil diameter and rate of saccade were associated with performance in the Tubes task (multivariate analysis; p-value = 0.01 and p-value = 0.04, respectively). Entropy of pupil diameter was associated with performance in Dots and Needles task (multivariate analysis; p-value = 0.01). Average temporal flexibility and search information in several BAs and band frequencies were associated with performance and rate of learning. The models may be used to objectify performance and learning rate evaluation in RAS once validated with a broader sample size and tasks.

Exploring the Interplay of Working Memory, Apathy, and Mood/Emotional Factors

BACKGROUND

Previous investigations on healthy humans showed conflicting evidence regarding the impact of mood on working memory performance. A systematic investigation of how mood affects apathy levels in healthy participants is currently missing.

METHODS

We administered a visuospatial (VS) and a numerical (N) n-back task to a sample of 120 healthy individuals. In these participants, using a series of questionnaires, we also evaluated apathy, mood, working memory, perceived stress, PTSD symptoms caused by the COVID-19 pandemic outbreak, and general psychiatric symptoms. Successively, we investigated their performance in the n-back task as a function of scores to these questionnaires.

RESULTS

Participants performed better in the N block than in the VS one. Their accuracy decreased as a function of the n-back difficulty. We reported no differences in working memory performance or apathy as a function of mood, stress, or PTSD symptoms. We found that phobic anxiety negatively predicted accuracy to the numerical n-back task and that subjects with greater anxiety and difficulty in regulating emotions also showed higher levels of withdrawal from the task.

CONCLUSION

The study's results suggest that while mood did not significantly affect working memory performance, strong associations were found between WMQ scores and working memory capabilities.

Developing cognitive workload and performance evaluation models using functional brain network analysis

Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities and in learning new skills. The purpose of this study was to develop cognitive workload and performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network and spectral analyses. The EEG data were recorded from 124 brain areas of 26 healthy participants conducting two cognitive tasks on a robot simulator. The functional brain network and Power Spectral Density features were extracted from EEG data using coherence and spectral analyses, respectively. Participants reported their perceived cognitive workload using the SURG-TLX questionnaire after each exercise, and the simulator generated actual performance scores. The extracted features, actual performance scores, and subjectively assessed cognitive workload values were used to develop linear models for evaluating performance and cognitive workload. Furthermore, the Pearson correlation was used to find the correlation between participants' age, performance, and cognitive workload. The findings demonstrated that combined EEG features retrieved from spectral analysis and functional brain networks can be used to evaluate cognitive workload and performance. The cognitive workload in conducting only Matchboard level 3, which is more challenging than Matchboard level 2, was correlated with age (0.54, p-value = 0.01). This finding may suggest playing more challenging computer games are more helpful in identifying changes in cognitive workload caused by aging. The findings could open the door for a new era of objective evaluation and monitoring of cognitive workload and performance.

Deconvoluting human Brodmann area 8 based on its unique structural and functional connectivity

Brodmann area 8 (BA8) is traditionally defined as the prefrontal region of the human cerebrum just anterior to the premotor cortices and enveloping most of the superior frontal gyrus. Early studies have suggested the frontal eye fields are situated at its most caudal aspect, causing many to consider BA8 as primarily an ocular center which controls contralateral gaze and attention. However, years of refinement in cytoarchitectural studies have challenged this traditional anatomical definition, providing a refined definition of its boundaries with neighboring cortical areas and the presence of meaningful subdivisions. Furthermore, functional imaging studies have suggested its involvement in a diverse number of higher-order functions, such as motor, cognition, and language. Thus, our traditional working definition of BA8 has likely been insufficient to truly understand the complex structural and functional significance of this area. Recently, large-scale multi-modal neuroimaging approaches have allowed for improved mapping of the neural connectivity of the human brain. Insight into the structural and functional connectivity of the brain connectome, comprised of large-scale brain networks, has allowed for greater understanding of complex neurological functioning and pathophysiological diseases states. Simultaneously, the structural and functional connectivity of BA8 has recently been highlighted in various neuroimaging studies and detailed anatomic dissections. However, while Brodmann's nomenclature is still widely used today, such as for clinical discussions and the communication of research findings, the importance of the underlying connectivity of BA8 requires further review.

Driver's turning intent recognition model based on brain activation and contextual information

Traffic situations like turning at intersections are destined for safety-critical situations and accidents. Human errors are one of the main reasons for accidents in these situations. A model that recognizes the driver's turning intent could help to reduce accidents by warning the driver or stopping the vehicle before a dangerous turning maneuver. Most models that aim at predicting the probability of a driver's turning intent use only contextual information, such as gap size or waiting time. The objective of this study is to investigate whether the combination of context information and brain activation measurements enhances the recognition of turning intent. We conducted a driving simulator study while simultaneously measuring brain activation using high-density fNIRS. A neural network model for turning intent recognition was trained on the fNIRS and contextual data. The input variables were analyzed using SHAP (SHapley Additive exPlanations) feature importance analysis to show the positive effect of the inclusion of brain activation data. Both the model's evaluation and the feature importance analysis suggest that the combination of context information and brain activation leads to an improved turning intent recognition. The fNIRS results showed increased brain activation differences during the "turn" decision-making phase before turning execution in parts of the left motor cortices, such as the primary motor cortex (PMC; putative BA 4), premotor area (PMA; putative BA 6), and supplementary motor area (SMA; putative BA 8). Furthermore, we also observed increased activation differences in the left prefrontal areas, potentially in the left middle frontal gyrus (putative BA 9), which has been associated with the control of executive functions, such as decision-making and action planning. We hypothesize that brain activation measurements could be a more direct indicator with potentially high specificity for the turning behavior and thus help to increase the recognition model's performance.

Self- and Situation-Focused Reappraisal are not homogeneous: Evidence from behavioral and brain networks

Reappraisal is an effective emotion regulation strategy which can be divided into self- and situation-focused subtypes. Previous studies have produced inconsistent findings on the moderating effects and neural mechanisms of reappraisal; thus, further research is necessary to clarify these inconsistencies. In this study, a total of 44 participants were recruited and randomly assigned to two groups. 23 participants were assigned to the self-focused group, while 21 participants were assigned to the situation-focused group. The participants' resting EEG data were collected for 6 minutes before the experiment began, followed by an emotional regulation task. During this task, participants were asked to view emotion-provoking images under four emotion regulation conditions (View, Watch, Increase, and Decrease). Late positive potential (LPP) was obtained when these emotional images were observed. LPP is an effective physiological indicator of emotion regulation, enabling this study to explore emotion regulation under different reappraisal strategies, as well as the functional connectivity and node efficiency within the brain. It was found that, in terms of the effect on emotion regulation, situation-focused reappraisal was significantly better than self-focused reappraisal at enhancing the valence of negative emotion, while self-focused reappraisal was significantly better than situation-focused reappraisal at increasing the arousal of negative emotion. In terms of neural mechanisms, multiple brain regions such as the anterior cingulate cortex, the frontal lobe, the parahippocampal gyrus, parts of the temporal lobe, and parts of the parietal lobe were involved in both reappraisal processes. In addition, there were some differences in brain regions associated with different forms of cognitive reappraisal. Self-focused reappraisal was associated with the posterior cingulate gyrus, fusiform gyrus, and lingual gyrus, and situation-focused reappraisal was associated with the parietal lobule, anterior central gyrus, and angular gyrus. In conclusion, this research demonstrates that self- and situation-focused reappraisal are not homogenous in terms of their effects and neural mechanisms and clarifies the uncertainties over their regulatory effects. Different types of reappraisal activate different brain regions when used, and the functional connectivity or node efficiency of these brain regions seems to be a suitable indicator for assessing the effects of different types of reappraisal.

Effective Connectivity for Default Mode Network Analysis of Alcoholism

Introduction: With the recent technical advances in brain imaging modalities such as magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging (fMRI), researchers' interests have inclined over the years to study brain functions through the analysis of the variations in the statistical dependence among various brain regions. Through its wide use in studying brain connectivity, the low temporal resolution of the fMRI represented by the limited number of samples per second, in addition to its dependence on brain slow hemodynamic changes, makes it of limited capability in studying the fast underlying neural processes during information exchange between brain regions. Materials and Methods: In this article, the high temporal resolution of the electroencephalography (EEG) is utilized to estimate the effective connectivity within the default mode network (DMN). The EEG data are collected from 20 subjects with alcoholism and 25 healthy subjects (controls), and used to obtain the effective connectivity diagram of the DMN using the Partial Directed Coherence algorithm. Results: The resulting effective connectivity diagram within the DMN shows the unidirectional causal effect of each region on the other. The variations in the causal effects within the DMN between controls and alcoholics show clear correlation with the symptoms that are usually associated with alcoholism, such as cognitive and memory impairments, executive control, and attention deficiency. The correlation between the exchanged causal effects within the DMN and symptoms related to alcoholism is discussed and properly analyzed. Conclusion: The establishment of the causal differences between control and alcoholic subjects within the DMN regions provides valuable insight into the mechanism by which alcohol modulates our cognitive and executive functions and creates better possibility for effective treatment of alcohol use disorder.

Children and adolescents' neural response to emotional faces and voices: Age-related changes in common regions of activation

The perception of facial and vocal emotional expressions engages overlapping regions of the brain. However, at a behavioral level, the ability to recognize the intended emotion in both types of nonverbal cues follows a divergent developmental trajectory throughout childhood and adolescence. The current study a) identified regions of common neural activation to facial and vocal stimuli in 8- to 19-year-old typically-developing adolescents, and b) examined age-related changes in blood-oxygen-level dependent (BOLD) response within these areas. Both modalities elicited activation in an overlapping network of subcortical regions (insula, thalamus, dorsal striatum), visual-motor association areas, prefrontal regions (inferior frontal cortex, dorsomedial prefrontal cortex), and the right superior temporal gyrus. Within these regions, increased age was associated with greater frontal activation to voices, but not faces. Results suggest that processing facial and vocal stimuli elicits activation in common areas of the brain in adolescents, but that age-related changes in response within these regions may vary by modality.

Distinct neural networks for detecting violations of adjacent versus nonadjacent sequential dependencies: An fMRI study

The ability to learn and process sequential dependencies is essential for language acquisition and other cognitive domains. Recent studies suggest that the learning of adjacent (e.g., "A-B") versus nonadjacent (e.g., "A-X-B") dependencies have different cognitive demands, but the neural correlates accompanying such processing are currently underspecified. We developed a sequential learning task in which sequences of printed nonsense syllables containing both adjacent and nonadjacent dependencies were presented. After incidentally learning these grammatical sequences, twenty-one healthy adults (age M = 22.1, 12 females) made familiarity judgments about novel grammatical sequences and ungrammatical sequences containing violations of the adjacent or nonadjacent structure while in a 3T MRI scanner. Violations of adjacent dependencies were associated with increased BOLD activation in both posterior (lateral occipital and angular gyrus) as well as frontal regions (e.g., medial frontal gyrus, inferior frontal gyrus). Initial results indicated no regions showing significant BOLD activations for the violations of nonadjacent dependencies. However, when using a less stringent cluster threshold, exploratory analyses revealed that violations of nonadjacent dependencies were associated with increased activation in subcallosal cortex, paracingulate cortex, and anterior cingulate cortex (ACC). Finally, when directly comparing the adjacent condition to the nonadjacent condition, we found significantly greater levels of activation for the right superior lateral occipital cortex (BA 19) for the adjacent relative to nonadjacent condition. In sum, the detection of violations of adjacent and nonadjacent dependencies appear to involve distinct neural networks, with perceptual brain regions mediating the processing of adjacent but not nonadjacent dependencies. These results are consistent with recent proposals that statistical-sequential learning is not a unified construct but depends on the interaction of multiple neurocognitive mechanisms acting together.

The effect of age, educational level, gender and cognitive reserve on visuospatial working memory performance across adult life span

Working memory (WM) is a limited capacity cognitive system that temporarily holds information for processing. In the present study, we tested the effect of age, gender and cognitive reserve in terms of educational level, working and leisure time activities on an active visuospatial WM task. One-hundred thirty-four participants between 20 and 80 years old performed an n-back task with different degree of WM demanding. Reaction times (RTs) became slower and accuracy decreased with age; the former started to decline in participants that were 35 years old, the latter in participants that were 57 years old. Males were faster than females. Educational level (10 years in accuracy and 15 years in RTs) showed a positive effect on accuracy and RTs. Cognitive reserve had a positive effect on accuracy but no effect on RTs. In conclusion, age-related decline influenced earlier the speed and later the accuracy in a task that required active processes. While male was faster independently of WM demanding and age, middle school degree and an average cognitive reserve prevent errors during performance. Coherently, high school degree prevents slowing down but only in low demanding condition.

The homotopic connectivity of the functional brain: a meta-analytic approach

Homotopic connectivity (HC) is the connectivity between mirror areas of the brain hemispheres. It can exhibit a marked and functionally relevant spatial variability, and can be perturbed by several pathological conditions. The voxel-mirrored homotopic connectivity (VMHC) is a technique devised to enquire this pattern of brain organization, based on resting state functional connectivity. Since functional connectivity can be revealed also in a meta-analytical fashion using co-activations, here we propose to calculate the meta-analytic homotopic connectivity (MHC) as the meta-analytic counterpart of the VMHC. The comparison between the two techniques reveals their general similarity, but also highlights regional differences associated with how HC varies from task to rest. Two main differences were found from rest to task: (i) regions known to be characterized by global hubness are more similar than regions displaying local hubness; and (ii) medial areas are characterized by a higher degree of homotopic connectivity, while lateral areas appear to decrease their degree of homotopic connectivity during task performance. These findings show that MHC can be an insightful tool to study how the hemispheres functionally interact during task and rest conditions.

Different neural activities support auditory working memory in musicians and bilinguals

Musical training and bilingualism benefit executive functioning and working memory (WM)-however, the brain networks supporting this advantage are not well specified. Here, we used functional magnetic resonance imaging and the n-back task to assess WM for spatial (sound location) and nonspatial (sound category) auditory information in musician monolingual (musicians), nonmusician bilinguals (bilinguals), and nonmusician monolinguals (controls). Musicians outperformed bilinguals and controls on the nonspatial WM task. Overall, spatial and nonspatial WM were associated with greater activity in dorsal and ventral brain regions, respectively. Increasing WM load yielded similar recruitment of the anterior-posterior attention network in all three groups. In both tasks and both levels of difficulty, musicians showed lower brain activity than controls in superior prefrontal frontal gyrus and dorsolateral prefrontal cortex (DLPFC) bilaterally, a finding that may reflect improved and more efficient use of neural resources. Bilinguals showed enhanced activity in language-related areas (i.e., left DLPFC and left supramarginal gyrus) relative to musicians and controls, which could be associated with the need to suppress interference associated with competing semantic activations from multiple languages. These findings indicate that the auditory WM advantage in musicians and bilinguals is mediated by different neural networks specific to each life experience.

Neural mechanisms of behavioral change in young adults with high-functioning autism receiving virtual reality social cognition training: A pilot study

Measuring treatment efficacy in individuals with Autism Spectrum Disorder (ASD) relies primarily on behaviors, with limited evidence as to the neural mechanisms underlying these behavioral gains. This pilot study addresses this void by investigating neural and behavioral changes in a Phase I trial in young adults with high-functioning ASD who received an evidence-based behavioral intervention, Virtual Reality-Social Cognition Training over 5 weeks for a total of 10 hr. The participants were tested pre- and post-training with a validated biological/social versus scrambled/nonsocial motion neuroimaging task, previously shown to activate regions within the social brain networks. Three significant brain-behavior changes were identified. First, the right posterior superior temporal sulcus, a hub for socio-cognitive processing, showed increased brain activation to social versus nonsocial stimuli in individuals with greater gains on a theory-of-mind measure. Second, the left inferior frontal gyrus, a region for socio-emotional processing, tracked individual gains in emotion recognition with decreased activation to social versus nonsocial stimuli. Finally, the left superior parietal lobule, a region for visual attention, showed significantly decreased activation to nonsocial versus social stimuli across all participants, where heightened attention to nonsocial contingencies has been considered a disabling aspect of ASD. This study provides, albeit preliminary, some of the first evidence of the harnessable neuroplasticity in adults with ASD through an age-appropriate intervention in brain regions tightly linked to social abilities. This pilot trial motivates future efforts to develop and test social interventions to improve behaviors and supporting brain networks in adults with ASD. Autism Res 2018, 11: 713-725. © 2018 The Authors Autism Research published by International Society for Autism Research and Wiley Periodicals, Inc.

LAY SUMMARY

This study addresses how the behavioral changes after treatment for ASD reflect underlying brain changes. Before and after receiving VR-SCT, young adults with high-functioning ASD passively viewed biological motion stimuli in a MRI scanner, tapping changes in the social brain network. The results reveal neuroplasticity in this age population, extending the window of opportunity for interventions to impact social competency in adults with ASD.

Symbol Digit Modalities Test adaptation for Magnetic Resonance Imaging environment: A systematic review and meta-analysis

BACKGROUND

The Symbol Digit Modalities Test (SDMT) is widely used for cognitive evaluation of information processing speed (IPS), required in many cognitive operations. Despite being unspecific for different neurological disorders, it is sensitive to assess impaired performance related to stroke, Parkinson's disease, traumatic brain injury, and multiple sclerosis. However, in addition to evaluate the presence and severity of IPS impairment, it is of interest to determine the localization and integration of brain regions responsible for the functions assessed by the SDMT.

OBJECTIVE

To review the studies that adapted the SDMT to the magnetic resonance environment and obtain the brain areas associated with the performance of the task in healthy subjects with a meta-analysis.

METHODOLOGY

A systematic review was performed using ten studies published between 1990 and 2017, and selected from four databases. All studies included participants of both genders and age between 18 and 50 years, used Functional Magnetic Resonance Imaging (fMRI) and SDMT adaptation and reported brain regions associated with the task. Six of them also reported the region coordinates in a standard space, so they were included in a meta-analysis. Activation Likelihood Estimation algorithm, with significance for p < 0.05 corrected for multiple comparisons, was used to identify areas that are robustly related to the performance of the SDMT.

RESULTS

The areas predominantly reported in the studies of our meta-analysis were regions of the frontoparietal attentional network and occipital cortex, as well as cuneus, precuneus, and cerebellum. Individually all regions that survived the statistical threshold are consistent with what is expected after reviewing prospective studies.

CONCLUSIONS

The present study allowed the identification of brain areas activated during the performance of the SDMT in healthy subjects, and therefore it will help understanding the differences in brain activation by this task in clinical populations. Moreover, it may guide future studies of therapeutic strategies and interventions in those populations.

Mindfulness-related differences in neural response to own infant negative versus positive emotion contexts

Mindfulness is thought to promote well-being by shaping the way people respond to challenging social-emotional situations. Current understanding of how this occurs at the neural level is based on studies of response to decontextualized emotion stimuli that may not adequately represent lived experiences. In this study, we tested relations between mothers' dispositional mindfulness and neural responses to their own infant in different emotion-eliciting contexts. Mothers (n = 25) engaged with their 3-month-old infants in videorecorded tasks designed to elicit negative (arm restraint) or positive (peekaboo) emotion. During a functional MRI session, mothers were presented with 15-s clips from these recordings, and dispositional mindfulness scores were used to predict their neural responses to arm restraint > peekaboo videos. Mothers higher in nonreactivity showed relatively lower activation to their infants’ arm restraint compared to peekaboo videos in hypothesized regions—insula and dorsal prefrontal cortex—as well as non-hypothesized regions. Other mindfulness dimensions were associated with more limited areas of lower (nonjudgment) and higher (describing) activation in this contrast. Mothers who were higher in mindfulness generally activated more to the positive emotion context and less to the negative emotion context in perceptual and emotion processing areas, a pattern that may help to explain mindfulness-related differences in well-being.

Electroencephalography Based Analysis of Working Memory Load and Affective Valence in an N-back Task with Emotional Stimuli

Most brain-based measures of the electroencephalogram (EEG) are used in highly controlled lab environments and only focus on narrow mental states (e.g., working memory load). However, we assume that outside the lab complex multidimensional mental states are evoked. This could potentially create interference between EEG signatures used for identification of specific mental states. In this study, we aimed to investigate more realistic conditions and therefore induced a combination of working memory load and affective valence to reveal potential interferences in EEG measures. To induce changes in working memory load and affective valence, we used a paradigm which combines an N-back task (for working memory load manipulation) with a standard method to induce affect (affective pictures taken from the International Affective Picture System (IAPS) database). Subjective ratings showed that the experimental task was successful in inducing working memory load as well as affective valence. Additionally, performance measures were analyzed and it was found that behavioral performance decreased with increasing workload as well as negative valence, showing that affective valence can have an effect on cognitive processing. These findings are supported by changes in frontal theta and parietal alpha power, parameters used for measuring of working memory load in the EEG. However, these EEG measures are influenced by the negative valence condition as well and thereby show that detection of working memory load is sensitive to affective contexts. Unexpectedly, we did not find any effects for EEG measures typically used for affective valence detection (Frontal Alpha Asymmetry (FAA)). Therefore we assume that the FAA measure might not be usable if cognitive workload is induced simultaneously. We conclude that future studies should account for potential context-specifity of EEG measures.

Integrated cross-network connectivity of amygdala, insula, and subgenual cingulate associated with facial emotion perception in healthy controls and remitted major depressive disorder

Emotion perception deficits could be due to disrupted connectivity of key nodes in the salience and emotion network (SEN), including the amygdala, subgenual anterior cingulate cortex (sgACC), and insula. We examined SEN resting-state (rs-)fMRI connectivity in rMDD in relation to Facial Emotion Perception Test (FEPT) performance. Fifty-two medication-free people ages 18 to 23 years participated. Twenty-seven had major depressive disorder (MDD) in remission (rMDD, 10 males), as MDD is associated with emotion perception deficits and alterations in rsfMRI. Twenty-five healthy controls (10 males) also participated. Participants completed the FEPT during fMRI, in addition to an 8-minute eyes-open resting-state scan. Seed regions of interest were defined in the amygdala, anterior insula and sgACC. Multiple regression analyses co-varied diagnostic group, sex and movement parameters. Emotion perception accuracy was positively associated with connectivity between amygdala seeds and regions primarily in the SEN and cognitive control network (CCN), and also the default mode network (DMN). Accuracy was also positively associated with connectivity between the sgACC seeds and other SEN regions, and the DMN, particularly for the right sgACC. Connectivity negatively associated with emotion perception was mostly with regions outside of these three networks, other than the left insula and part of the DMN. This study is the first to our knowledge to demonstrate relationships between facial emotion processing and resting-state connectivity with SEN nodes and between SEN nodes and regions located within other neural networks.

Altered Topological Properties of Brain Networks in Social Anxiety Disorder: A Resting-state Functional MRI Study

Recent studies involving connectome analysis including graph theory have yielded potential biomarkers for mental disorders. In this study, we aimed to investigate the differences of resting-state network between patients with social anxiety disorder (SAD) and healthy controls (HCs), as well as to distinguish between individual subjects using topological properties. In total, 42 SAD patients and the same number of HCs underwent resting functional MRI, and the topological organization of the whole-brain functional network was calculated using graph theory. Compared with the controls, the patients showed a decrease in 49 positive connections. In the topological analysis, the patients showed an increase in the area under the curve (AUC) of the global shortest path length of the network (L_p) and a decrease in the AUC of the global clustering coefficient of the network (C_p). Furthermore, the AUCs of L_p and C_p were used to effectively discriminate the individual SAD patients from the HCs with high accuracy. This study revealed that the neural networks of the SAD patients showed changes in topological characteristics, and these changes were prominent not only in both groups but also at the individual level. This study provides a new perspective for the identification of patients with SAD.

Exploring Emotion Regulation in Juveniles Who Have Sexually Offended: An fMRI Study

This exploratory study compared juveniles who sexually offend to nonoffending juveniles in their capacities to behaviorally and neurologically regulate, or reappraise, negative emotions. Participants were 39 juvenile males, including 10 healthy, nonoffending control subjects and 29 juveniles who sexually offend, comprising 12 juveniles who sexually offend with history of child sexual abuse. Participants completed a clinical assessment and a reappraisal task during functional magnetic resonance imaging. Difficulties in Emotional Regulation Scale results showed significantly less difficulties in emotion regulation among controls compared to juveniles who sexually offend, but when self-rating reappraisal abilities during the functional magnetic resonance imaging, all groups obtained comparable results. The imaging results showed no significant differences in fronto-temporal regions between controls and juveniles who sexually offend. Differences were found in other regions indicated in cognitive control, working memory, and emotional processing between controls and juveniles who sexually offend as well as between juveniles who sexually offend and those without history of child sexual abuse. Findings suggest that juveniles who sexually offend are capable of emotion regulation.

The Cognitive Side of M1

The primary motor cortex (M1) is traditionally implicated in voluntary movement control. In order to test the hypothesis that there is a functional topography of M1 activation in studies where it has been implicated in higher cognitive tasks we performed activation-likelihood-estimation (ALE) meta-analyses of functional neuroimaging experiments reporting M1 activation in relation to six cognitive functional categories for which there was a sufficient number of studies to include, namely motor imagery, working memory, mental rotation, social/emotion/empathy, language, and auditory processing. The six categories activated different sub-sectors of M1, either bilaterally or lateralized to one hemisphere. Notably, the activations found in the M1 of the left or right hemisphere detected in our study were unlikely due to button presses. In fact, all contrasts were selected in order to eliminate M1 activation due to activity related to the finger button press. In addition, we identified the M1 sub-region of Area 4a commonly activated by 4/6 categories, namely motor imagery and working memory, emotion/empathy, and language. Overall, our findings lend support to the idea that there is a functional topography of M1 activation in studies where it has been found activated in higher cognitive tasks and that the left Area 4a can be involved in a number of cognitive processes, likely as a product of implicit mental simulation processing.

Don't forget the lyrics! Spatiotemporal dynamics of neural mechanisms spontaneously evoked by gaps of silence in familiar and newly learned songs

The vast majority of people experience musical imagery, the sensation of reliving a song in absence of any external stimulation. Internal perception of a song can be deliberate and effortful, but also may occur involuntarily and spontaneously. Moreover, musical imagery is also involuntarily used for automatically completing missing parts of music or lyrics from a familiar song. The aim of our study was to explore the onset of musical imagery dynamics that leads to the automatic completion of missing lyrics. High-density electroencephalography was used to record the cerebral activity of twenty healthy volunteers while they were passively listening to unfamiliar songs, very familiar songs, and songs previously listened to for two weeks. Silent gaps inserted into these songs elicited a series of neural activations encompassing perceptual, attentional and cognitive mechanisms (range 100-500ms). Familiarity and learning effects emerged as early as 100ms and lasted 400ms after silence occurred. Although participants reported more easily mentally imagining lyrics in familiar rather than passively learnt songs, the onset of neural mechanisms and the power spectrum underlying musical imagery were similar for both types of songs. This study offers new insights into the musical imagery dynamics evoked by gaps of silence and on the role of familiarity and learning processes in the generation of these dynamics. The automatic and effortless method presented here is a potentially useful tool to understand failure in the familiarity and learning processes of pathological populations.

Somatosensory Representations Link the Perception of Emotional Expressions and Sensory Experience

Studies of human emotion perception have linked a distributed set of brain regions to the recognition of emotion in facial, vocal, and body expressions. In particular, lesions to somatosensory cortex in the right hemisphere have been shown to impair recognition of facial and vocal expressions of emotion. Although these findings suggest that somatosensory cortex represents body states associated with distinct emotions, such as a furrowed brow or gaping jaw, functional evidence directly linking somatosensory activity and subjective experience during emotion perception is critically lacking. Using functional magnetic resonance imaging and multivariate decoding techniques, we show that perceiving vocal and facial expressions of emotion yields hemodynamic activity in right somatosensory cortex that discriminates among emotion categories, exhibits somatotopic organization, and tracks self-reported sensory experience. The findings both support embodied accounts of emotion and provide mechanistic insight into how emotional expressions are capable of biasing subjective experience in those who perceive them.

Cerebral white matter volume changes in patients with obsessive-compulsive disorder: Voxel-based morphometry

AIMS

We carried out a voxel-based morphometry (VBM) study to evaluate cerebral white matter (WM) volume alteration in obsessive-compulsive disorder (OCD) and its correlation with the scores of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS).

METHODS

Fourteen patients with OCD, who were diagnosed using the DSM-IV-TR, and 14 age-matched healthy controls participated. The high-resolution magnetic resonance imaging data were analyzed by voxel-based morphometry and Statistical Parametric Mapping 8.

RESULTS

There was no significant difference in the total intracranial volumes between OCD patients and healthy controls. However, patients with OCD showed significantly increased WM volumes in the right dorsolateral prefrontal cortex, middle frontal gyrus, precuneus, and inferior parietal lobule compared with healthy controls. In addition, the OCD patients showed a positive correlation between the WM volumes of the dorsolateral prefrontal cortex and Y-BOCS scores (r = 0.334, P = 0.03 and Pearson's correlation coefficient = 0.58) rating for the severity of OCD symptoms.

CONCLUSIONS

WM volume variations of the specific brain regions in patients with OCD will be helpful to understand the neural connectivity associated with a symptom of OCD. Furthermore, the findings would be valuable to aid the diagnostic accuracy of OCD in connection with morphometric magnetic resonance imaging analysis.

Neurofunctional topography of the human hippocampus

Much of what was assumed about the functional topography of the hippocampus was derived from a single case study over half a century ago. Given advances in the imaging sciences, a new era of discovery is underway, with potential to transform the understanding of healthy processing as well as the ability to treat disorders. Coactivation-based parcellation, a meta-analytic approach, and ultra-high field, high-resolution functional and structural neuroimaging to characterize the neurofunctional topography of the hippocampus was employed. Data revealed strong support for an evolutionarily preserved topography along the long-axis. Specifically, the left hippocampus was segmented into three distinct clusters: an emotional processing cluster supported by structural and functional connectivity to the amygdala and parahippocampal gyrus, a cognitive operations cluster, with functional connectivity to the anterior cingulate and inferior frontal gyrus, and a posterior perceptual cluster with distinct structural connectivity patterns to the occipital lobe coupled with functional connectivity to the precuneus and angular gyrus. The right hippocampal segmentation was more ambiguous, with plausible 2- and 5-cluster solutions. Segmentations shared connectivity with brain regions known to support the correlated processes. This represented the first neurofunctional topographic model of the hippocampus using a robust, bias-free, multimodal approach.

Reduced Functional Connectivity of Default Mode and Set-Maintenance Networks in Ornithine Transcarbamylase Deficiency

Background and Purpose

Ornithine transcarbamylase deficiency (OTCD) is an X-chromosome linked urea cycle disorder (UCD) that causes hyperammonemic episodes leading to white matter injury and impairments in executive functioning, working memory, and motor planning. This study aims to investigate differences in functional connectivity of two resting-state networks—default mode and set-maintenance—between OTCD patients and healthy controls.

Methods

Sixteen patients with partial OTCD and twenty-two control participants underwent a resting-state scan using 3T fMRI. Combining independent component analysis (ICA) and region-of-interest (ROI) analyses, we identified the nodes that comprised each network in each group, and assessed internodal connectivity.

Results

Group comparisons revealed reduced functional connectivity in the default mode network (DMN) of OTCD patients, particularly between the anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC) node and bilateral inferior parietal lobule (IPL), as well as between the ACC/mPFC node and the posterior cingulate cortex (PCC) node. Patients also showed reduced connectivity in the set-maintenance network, especially between right anterior insula/frontal operculum (aI/fO) node and bilateral superior frontal gyrus (SFG), as well as between the right aI/fO and ACC and between the ACC and right SFG.

Conclusion

Internodal functional connectivity in the DMN and set-maintenance network is reduced in patients with partial OTCD compared to controls, most likely due to hyperammonemia-related white matter damage. Because several of the affected areas are involved in executive functioning, it is postulated that this reduced connectivity is an underlying cause of the deficits OTCD patients display in this cognitive domain.

Broca's area network in language function: a pooling-data connectivity study

Background and Objective: Modern neuroimaging developments have demonstrated that cognitive functions correlate with brain networks rather than specific areas. The purpose of this paper was to analyze the connectivity of Broca’s area based on language tasks.

Methods: A connectivity modeling study was performed by pooling data of Broca’s activation in language tasks. Fifty-seven papers that included 883 subjects in 84 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the map; thresholds at p < 0.01 were corrected for multiple comparisons and false discovery rate. Resulting images were co-registered into MNI standard space.

Results: A network consisting of 16 clusters of activation was obtained. Main clusters were located in the frontal operculum, left posterior temporal region, supplementary motor area, and the parietal lobe. Less common clusters were seen in the sub-cortical structures including the left thalamus, left putamen, secondary visual areas, and the right cerebellum.

Conclusion: Broca’s area-44-related networks involved in language processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation, and limitations of the results are discussed.

Neural effects of cognitive-behavioural therapy on dysfunctional attitudes in depression

BACKGROUND

Dysfunctional attitudes are a feature of depression that has been correlated with receptor binding abnormalities in limbic and cortical regions. We sought to investigate the functional neuroanatomy of dysfunctional attitudes in major depressive disorder (MDD) and the effects of treatment with cognitive-behavioural therapy (CBT).

METHOD

Participants were 16 patients with unipolar depression in an acute depressive episode (mean age 40.0 years) and 16 matched healthy controls (mean age 39.9 years). Patients were medication free and received a course of treatment with CBT. All participants underwent functional magnetic resonance imaging (fMRI) scans at baseline and at week 16, prior to the initiation of therapy and following the course of CBT for patients. During each fMRI scan, participants indicated their attributions to statements from a modified Dysfunctional Attitudes Scale (mDAS-48).

RESULTS

MDD patients in an acute depressive episode endorsed a greater number of extreme responses to DAS statements, which normalized following CBT treatment. Extreme attributions were associated with greater activation in the left hippocampal region, inferior parietal lobe and precuneus in MDD patients as compared with healthy controls as a main effect of group. An interaction effect was found in the left parahippocampal region, which showed less attenuation in MDD patients at the follow-up scan relative to healthy controls.

CONCLUSIONS

Attenuation of activity in the parahippocampal region may be indicative of an improvement in dysfunctional thinking following CBT treatment in depression, while persistent engagement of regions involved in attentional processing and memory retrieval with extreme attributions reflects a trait feature of depression.

Coupled neural systems underlie the production and comprehension of naturalistic narrative speech

Neuroimaging studies of language have typically focused on either production or comprehension of single speech utterances such as syllables, words, or sentences. In this study we used a new approach to functional MRI acquisition and analysis to characterize the neural responses during production and comprehension of complex real-life speech. First, using a time-warp based intrasubject correlation method, we identified all areas that are reliably activated in the brains of speakers telling a 15-min-long narrative. Next, we identified areas that are reliably activated in the brains of listeners as they comprehended that same narrative. This allowed us to identify networks of brain regions specific to production and comprehension, as well as those that are shared between the two processes. The results indicate that production of a real-life narrative is not localized to the left hemisphere but recruits an extensive bilateral network, which overlaps extensively with the comprehension system. Moreover, by directly comparing the neural activity time courses during production and comprehension of the same narrative we were able to identify not only the spatial overlap of activity but also areas in which the neural activity is coupled across the speaker's and listener's brains during production and comprehension of the same narrative. We demonstrate widespread bilateral coupling between production- and comprehension-related processing within both linguistic and nonlinguistic areas, exposing the surprising extent of shared processes across the two systems.

Adaptation to vocal expressions reveals multistep perception of auditory emotion

The human voice carries speech as well as important nonlinguistic signals that influence our social interactions. Among these cues that impact our behavior and communication with other people is the perceived emotional state of the speaker. A theoretical framework for the neural processing stages of emotional prosody has suggested that auditory emotion is perceived in multiple steps (Schirmer and Kotz, 2006) involving low-level auditory analysis and integration of the acoustic information followed by higher-level cognition. Empirical evidence for this multistep processing chain, however, is still sparse. We examined this question using functional magnetic resonance imaging and a continuous carry-over design (Aguirre, 2007) to measure brain activity while volunteers listened to non-speech-affective vocalizations morphed on a continuum between anger and fear. Analyses dissociated neuronal adaptation effects induced by similarity in perceived emotional content between consecutive stimuli from those induced by their acoustic similarity. We found that bilateral voice-sensitive auditory regions as well as right amygdala coded the physical difference between consecutive stimuli. In contrast, activity in bilateral anterior insulae, medial superior frontal cortex, precuneus, and subcortical regions such as bilateral hippocampi depended predominantly on the perceptual difference between morphs. Our results suggest that the processing of vocal affect recognition is a multistep process involving largely distinct neural networks. Amygdala and auditory areas predominantly code emotion-related acoustic information while more anterior insular and prefrontal regions respond to the abstract, cognitive representation of vocal affect.

Better Neuronal Efficiency After Emotional Competences Training: An fMRI Study

Earlier studies demonstrated that adult emotional competences (EC) can be improved through relatively brief training. This increase has been investigated, thus far, using self-reported questionnaires and behavioral data. The aim of the present study was to evaluate the cerebral correlates underlying improvement in EC. An experimental group received an EC training and a control group received brief sessions of drama improvisation. Participants viewed negative, positive, and neutral pictures while attempting to decrease, increase, or not modulate their emotional reactions. Subjective reactions were assessed via on-line ratings. After the intervention, the training group showed less cerebral activity as compared to the control group within different regions related to emotional regulation and attention including prefrontal regions and the bilateral inferior parietal lobule, the right precentral gyrus and the intraparietal sulcus. These results suggest increased neural efficiency in the training group as a result of emotional competencies training.

A modified oddball paradigm for investigation of neural correlates of attention: a simultaneous ERP-fMRI study

Introduction

The objective of the presented study was to develop and evaluate a P300 experimental protocol for simultaneous registration of event-related potentials (ERPs) and functional MRI (fMRI) data with continuous imaging. It may be useful for investigating attention and working memory processes in specific populations, such as children and neuropsychiatric patients.

Materials and methods

Eleven children were investigated with simultaneous ERP–fMRI. To fulfill requirements of both BOLD and electroencephalographic signal registration, a modified oddball task was used. To verify the ERP–fMRI protocol we also performed a study outside the scanner using a typical two-stimuli oddball paradigm.

Results

Localization of the P300 component of ERPs partially corresponded with fMRI results in the frontal and parietal brain regions. FMRI activations were found in: middle frontal gyrus, insula, SMA, parietal lobule, thalamus, and cerebellum. Our modified oddball task provided ERP–fMRI results with high level of significance (EEG SNR = 35, fMRI p < 0.05–Bonf.). ERPs obtained in the scanner were comparable with those registered outside the scanner, although some differences in the amplitude were noticed, mainly in the N100 component.

Conclusion

In our opinion the presented paradigm may be successfully applied for simultaneous ERP–fMRI registration of neural correlates of attention in vulnerable populations.

Neural processing of criticism and positive comments from relatives in individuals with schizotypal personality traits

OBJECTIVES. High negative expressed emotion by family members towards schizophrenia patients increases the risk of subsequent relapse. The study aimed to determine whether individuals with high schizotypy (HS) and low schizotypy (LS) would differ in activation of brain areas involved in cognitive control when listening to relative criticism. METHODS. Twelve HS and 12 LS individuals listened to relative's critical, positive and neutral comments about them while undergoing functional MRI. Activation maps in the two groups during the comments were compared using SPM5. RESULTS. The left superior frontal and middle frontal gyri and bilateral posterior cingulate cortex were activated during criticism, compared to neutral comments, across all participants. While there were no group differences in brain activity for criticism versus neutral comments, the HS group, who had lower current mood relative to the LS group, activated to a lesser extent the thalamus, insula, putamen and brain stem during positive, compared to neutral, comments. CONCLUSIONS. Listening to relative criticism in healthy individuals engages brain areas for cognitive control of negative emotion and self-referential processing. However, HS individuals may have an attenuated ability to respond to rewarding aspects of positive comments due to their lower current mood.

How 'love' and 'hate' differ from 'sleep': using combined electro/magnetoencephalographic data to reveal the sources of early cortical responses to emotional words

Emotional words--as symbols for biologically relevant concepts--are preferentially processed in brain regions including the visual cortex, frontal and parietal regions, and a corticolimbic circuit including the amygdala. Some of the brain structures found in functional magnetic resonance imaging are not readily apparent in electro- and magnetoencephalographic (EEG; MEG) measures. By means of a combined EEG/MEG source localization procedure to fully exploit the available information, we sought to reduce these discrepancies and gain a better understanding of spatiotemporal brain dynamics underlying emotional-word processing. Eighteen participants read high-arousing positive and negative, and low-arousing neutral nouns, while EEG and MEG were recorded simultaneously. Combined current-density reconstructions (L2-minimum norm least squares) for two early emotion-sensitive time intervals, the P1 (80-120 ms) and the early posterior negativity (EPN, 200-300 ms), were computed using realistic individual head models with a cortical constraint. The P1 time window uncovered an emotion effect peaking in the left middle temporal gyrus. In the EPN time window, processing of emotional words was associated with enhanced activity encompassing parietal and occipital areas, and posterior limbic structures. We suggest that lexical access, being underway within 100 ms, is speeded and/or favored for emotional words, possibly on the basis of an "emotional tagging" of the word form during acquisition. This gives rise to their differential processing in the EPN time window. The EPN, as an index of natural selective attention, appears to reflect an elaborate interplay of distributed structures, related to cognitive functions, such as memory, attention, and evaluation of emotional stimuli.

Neural correlates of visual motion prediction

Predicting the trajectories of moving objects in our surroundings is important for many life scenarios, such as driving, walking, reaching, hunting and combat. We determined human subjects’ performance and task-related brain activity in a motion trajectory prediction task. The task required spatial and motion working memory as well as the ability to extrapolate motion information in time to predict future object locations. We showed that the neural circuits associated with motion prediction included frontal, parietal and insular cortex, as well as the thalamus and the visual cortex. Interestingly, deactivation of many of these regions seemed to be more closely related to task performance. The differential activity during motion prediction vs. direct observation was also correlated with task performance. The neural networks involved in our visual motion prediction task are significantly different from those that underlie visual motion memory and imagery. Our results set the stage for the examination of the effects of deficiencies in these networks, such as those caused by aging and mental disorders, on visual motion prediction and its consequences on mobility related daily activities.

Reduced cortical thickness in mental retardation

Mental retardation is a developmental disorder associated with impaired cognitive functioning and deficits in adaptive behaviors. Many studies have addressed white matter abnormalities in patients with mental retardation, while the changes of the cerebral cortex have been studied to a lesser extent. Quantitative analysis of cortical integrity using cortical thickness measurement may provide new insights into the gray matter pathology. In this study, cortical thickness was compared between 13 patients with mental retardation and 26 demographically matched healthy controls. We found that patients with mental retardation had significantly reduced cortical thickness in multiple brain regions compared with healthy controls. These regions include the bilateral lingual gyrus, the bilateral fusiform gyrus, the bilateral parahippocampal gyrus, the bilateral temporal pole, the left inferior temporal gyrus, the right lateral orbitofrontal cortex and the right precentral gyrus. The observed cortical thickness reductions might be the anatomical substrates for the impaired cognitive functioning and deficits in adaptive behaviors in patients with mental retardation. Cortical thickness measurement might provide a sensitive prospective surrogate marker for clinical trials of neuroprotective medications.

Disrupted functional connectivity in social anxiety disorder: a resting-state fMRI study

Dysfunction of the corticolimbic circuitry has been highlighted in social anxiety disorder (SAD) during social stimuli. However, few studies have investigated functional connectivity in SAD during the resting state, which may improve our understanding of SAD pathophysiology. The aim of this study was to investigate whether whole-brain functional connectivity might be aberrant in SAD patients, and if so, whether these changes are related to the measured clinical severity. Seventeen SAD patients and 19 healthy controls participated in resting-state functional magnetic resonance imaging. The brain was first divided into 90 paired brain regions and functional connectivity was then estimated by temporal correlation between each of these regions. Furthermore, connections that were significantly disrupted in SAD patients were correlated with clinical severity measured using the Liebowitz Social Anxiety Scale. Compared with healthy controls, SAD patients showed decreased positive connections within the frontal lobe and decreased negative connections between the frontal and occipital lobes. In particular, the weaker negative connections between the frontal lobe, which mainly involved the right median prefrontal cortex, and the occipital lobe had a significant positive correlation with the severity of SAD symptoms. The results support the hypothesis that some abnormalities of functional connectivity exist in SAD patients, which relate to the frontal cortex and occipital cortex. In addition, decreased functional connectivity between the frontal and occipital lobes and within the frontal lobe might be related to abnormal information processing and reflect disturbed neural organization resulting in defective social cognition, which could represent an early imaging biomarker for SAD.

Emotion processing influences working memory circuits in pediatric bipolar disorder and attention-deficit/hyperactivity disorder

OBJECTIVE

This functional magnetic resonance imaging (fMRI) study examined how working memory circuits are affected by face emotion processing in pediatric bipolar disorder (PBD) and attention-deficit/hyperactivity disorder (ADHD).

METHODS

A total of 23 patients with PBD, 14 patients with ADHD, and 19 healthy control (HC) subjects (mean age, 13.36 ± 2.55 years) underwent an affective, two-back fMRI task with blocks of happy, angry, and neutral faces.

RESULTS

For angry versus neutral faces PBD patients, relative to ADHD patients, exhibited increased activation in the subgenual anterior cingulate cortex (ACC) and orbitofrontal cortex, and reduced activation in the dorsolateral prefrontal cortex (DLPFC) and premotor cortex. Relative to the HC group, the PBD group showed no increased activation and reduced activation at the junction of DLPFC and ventrolateral prefrontal cortex (VLPFC). Relative to HC, the ADHD patients exhibited greater activation in the DLPFC and reduced activation in the ventral and medial PFC, pregenual ACC, striatum, and temporo-parietal regions. For happy versus neutral faces, relative to the ADHD group, the PBD group exhibited greater activation in the bilateral caudate, and relative to the HC group the ADHD group showed increased activation in the DLPFC, striatal, and parietal regions, and no reduced activation. The ADHD group, compared with the HC group, showed no reduced activation and increased activation in regions that were underactive for the angry face condition.

CONCLUSIONS

Relative to the ADHD group, the PBD group exhibited greater deployment of the emotion-processing circuitry and reduced deployment of working memory circuitry. Commonalities across PBD and ADHD patients, relative to the HC individuals, entailed cortico-subcortical activity that was reduced under negative emotional challenge and increased under positive emotional challenge.