Default network connectivity during a working memory task

Differential spatial working memory-related functional network reconfiguration in young and older adults

Functional brain networks have preserved architectures in rest and task; nevertheless, previous work consistently demonstrated task-related brain functional reorganization. Efficient rest-to-task functional network reconfiguration is associated with better cognition in young adults. However, aging and cognitive load effects, as well as contributions of intra- and internetwork reconfiguration, remain unclear. We assessed age-related and load-dependent effects on global and network-specific functional reconfiguration between rest and a spatial working memory (SWM) task in young and older adults, then investigated associations between functional reconfiguration and SWM across loads and age groups. Overall, global and network-level functional reconfiguration between rest and task increased with age and load. Importantly, more efficient functional reconfiguration associated with better performance across age groups. However, older adults relied more on internetwork reconfiguration of higher cognitive and task-relevant networks. These reflect the consistent importance of efficient network updating despite recruitment of additional functional networks to offset reduction in neural resources and a change in brain functional topology in older adults. Our findings generalize the association between efficient functional reconfiguration and cognition to aging and demonstrate distinct brain functional reconfiguration patterns associated with SWM in aging, highlighting the importance of combining rest and task measures to study aging cognition.

Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity

BACKGROUND

The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs, and time since most recent TBI.

METHODS

Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 90 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons).

RESULTS

The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* in the left posterior cingulate with SCAT symptom severity score (p = 0.05) and T2* in the left cuneus with headache frequency (p = 0.04).

CONCLUSIONS

Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Neurophysiological effective network connectivity supports a threshold-dependent management of dynamic working memory gating

To facilitate goal-directed actions, effective management of working memory (WM) is crucial, involving a hypothesized WM "gating mechanism." We investigate the underlying neural basis through behavioral modeling and connectivity assessments between neuroanatomical regions linked to theta, alpha, and beta frequency bands. We found opposing, threshold-dependent mechanisms governing WM gate opening and closing. Directed beta band connectivity in the parieto-frontal and parahippocampal-occipital networks was crucial for threshold-dependent WM gating dynamics. Fronto-parahippocampal connectivity in the theta band was also notable for both gating processes, although weaker than that in the beta band. Distinct roles for theta, beta, and alpha bands emerge in maintaining information in WM and shielding against interference, whereby alpha band activity likely acts as a "gatekeeper" supporting processes reflected by beta and theta band activity. The study shows that the decision criterion for WM gate opening/closing relies on concerted interplay within neuroanatomical networks defined by beta and theta band activities.

Brain Structural and Functional Abnormalities Associated with Acute Post-Traumatic Headache: Iron Deposition and Functional Connectivity

Background

The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs and time since most recent TBI.

Methods

Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 10 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons).

Results

The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* and SCAT symptom severity score in the left posterior cingulate (p = 0.05) and with headache frequency in the left cuneus (p = 0.04).

Conclusions

Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Trying to name what doesn't change: Neural nonresponse to Cognitive Therapy for depression

BACKGROUND

Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, ); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follows that identification of treatment-resistant aberrant neural processes in MDD may inform clinical and research efforts targeting sustained remission. Thus, we sought to identify brain regions showing aberrant neural functioning in MDD that either (1) fail to exhibit substantive change (nonresponse) or (2) exhibit functional changes (response) following CBT.

METHODS

To identify treatment-resistant neural processes (as well as neural processes exhibiting change after treatment), we collected functional magnetic resonance imaging (fMRI) data of MDD patients (n = 58) before and after CBT as well as never-depressed controls (n = 35) before and after a similar amount of time. We evaluated fMRI data using conjunction analyses, which utilized several contrast-based criteria to characterize brain regions showing both differences between patients and controls at baseline and nonresponse or response to CBT.

RESULTS

Findings revealed nonresponse in a cerebellar region and response in prefrontal and parietal regions.

CONCLUSIONS

Results are consistent with prior theoretical models of CBT's direct effect on cortical regulatory processes but expand on them with identification of additional regions (and associated neural systems) of response and nonresponse to CBT.

Toward staging differentiation for posttraumatic stress disorder treatment

OBJECTIVES

Several medical and psychiatric disorders have stage-based treatment decision-making methods. However, international treatment guidelines for posttraumatic stress disorder (PTSD) fail to give specific treatment recommendations based on chronicity or stage of the disorder. There is convincing evidence of a finite range of PTSD symptom trajectories, implying that different phenotypes of the disorder can be distinguished, which are highly relevant for a staging typology of PTSD.

METHODS

State-of-the-art review building on prior work on staging models in other disorders as a mapping tool to identify and synthesize toward PTSD.

RESULTS

We propose a four-stage model of PTSD ranging from stage 0: trauma-exposed asymptomatic but at risk to stage 4: severe unremitting illness of increasing chronicity. We favor a symptom description in various chronological characteristics based on neurobiological markers, information processing systems, stress reactivity, and consciousness dimensions. We also advocate for a separate phenomenology of treatment resistance since this can yield treatment recommendations.

CONCLUSION

A staging perspective in the field of PTSD is highly needed. This can facilitate the selection of interventions that are proportionate to patients' current needs and risk of illness progression and can also contribute to an efficient framework to organize biomarker data and guide service delivery. Therefore, we propose that a neurobiologically driven trajectory-based typology of PTSD can help deduct several treatment recommendations leading to a more personalized and refined grid to strategize, plan and evaluate treatment interventions.

Regional brain dysfunction in insomnia after ischemic stroke: A resting-state fMRI study

Objective

This study aimed to explore the abnormality of local brain function in patients with post-stroke insomnia (PSI) based on fMRI and explore the possible neuropathological mechanisms of insomnia in patients with PSI in combination with the Pittsburgh sleep quality index (PSQI) score and provide an objective evaluation index for the follow-up study of acupuncture treatment of PSI.

Methods

A total of 27 patients with insomnia after stroke were enrolled, and the PSQI was used to evaluate their sleep status. Twenty-seven healthy participants who underwent physical examinations during the same period were selected as controls. Resting-state brain function images and structural images of the two groups of participants were collected, and the abnormal changes in the regional brain function in patients with PSI were analyzed using three methods: regional homogeneity (ReHo), the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF), and a correlation analysis with the PSQI scale score.

Results

Compared with the HCs, the ReHo values of the PSI group in the bilateral lingual gyrus, right cuneus, right precentral and postcentral gyri were significantly lower, and the ReHo values of the left supramarginal gyrus were significantly higher. In the PSI group, the ALFF values in the bilateral lingual gyrus were significantly decreased, whereas those in the bilateral middle temporal gyrus, right inferior temporal gyrus, right inferior frontal gyrus, right limbic lobe, right precuneus, left posterior cingulate gyrus, and left middle occipital gyrus were significantly increased. Compared with HCs, the fALFF values of the bilateral lingual gyrus, bilateral inferior occipital gyrus, and bilateral cuneus in the PSI group were significantly higher. The ReHo value of the left supramarginal gyrus in the PSI group was significantly negatively correlated with the total PSQI score.

Conclusion

Patients with PSI have abnormal local activities in multiple brain regions, including the visual processing-related cortex, sensorimotor cortex, and some default-mode network (DMN) regions. Over-arousal of the DMN and over-sensitivity of the audiovisual stimuli in patients with PSI may be the main mechanisms of insomnia and can lead to a decline in cognitive function and abnormalities in emotion regulation simultaneously.

Tasks activating the default mode network map multiple functional systems

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

Contrasting Associations Between Heart Rate Variability and Brainstem-Limbic Connectivity in Posttraumatic Stress Disorder and Its Dissociative Subtype: A Pilot Study

Background

Increasing evidence points toward the need to extend the neurobiological conceptualization of posttraumatic stress disorder (PTSD) to include evolutionarily conserved neurocircuitries centered on the brainstem and the midbrain. The reticular activating system (RAS) helps to shape the arousal state of the brain, acting as a bridge between brain and body. To modulate arousal, the RAS is closely tied to the autonomic nervous system (ANS). Individuals with PTSD often reveal altered arousal patterns, ranging from hyper- to blunted arousal states, as well as altered functional connectivity profiles of key arousal-related brain structures that receive direct projections from the RAS. Accordingly, the present study aims to explore resting state functional connectivity of the RAS and its interaction with the ANS in participants with PTSD and its dissociative subtype.

Methods

Individuals with PTSD (n = 57), its dissociative subtype (PTSD + DS, n = 32) and healthy controls (n = 40) underwent a 6-min resting functional magnetic resonance imaging and pulse data recording. Resting state functional connectivity (rsFC) of a central node of the RAS – the pedunculopontine nuclei (PPN) – was investigated along with its relation to ANS functioning as indexed by heart rate variability (HRV). HRV is a prominent marker indexing the flexibility of an organism to react adaptively to environmental needs, with higher HRV representing greater effective adaptation.

Results

Both PTSD and PTSD + DS demonstrated reduced HRV as compared to controls. HRV measures were then correlated with rsFC of the PPN. Critically, participants with PTSD and participants with PTSD + DS displayed inverse correlations between HRV and rsFC between the PPN and key limbic structures, including the amygdala. Whereas participants with PTSD displayed a positive relationship between HRV and PPN rsFC with the amygdala, participants with PTSD + DS demonstrated a negative relationship between HRV and PPN rsFC with the amygdala.

Conclusion

The present exploratory investigation reveals contrasting patterns of arousal-related circuitry among participants with PTSD and PTSD + DS, providing a neurobiological lens to interpret hyper- and more blunted arousal states in PTSD and PTSD + DS, respectively.

Altered Dynamic Functional Connectivity of Cuneus in Schizophrenia Patients: A Resting-State fMRI Study

Objective: Schizophrenia (SZ) is a functional mental condition that has a significant impact on patients’ social lives. As a result, accurate diagnosis of SZ has attracted researchers’ interest. Based on previous research, resting-state functional magnetic resonance imaging (rsfMRI) reported neural alterations in SZ. In this study, we attempted to investigate if dynamic functional connectivity (dFC) could reveal changes in temporal interactions between SZ patients and healthy controls (HC) beyond static functional connectivity (sFC) in the cuneus, using the publicly available COBRE dataset. Methods: Sliding windows were applied to 72 SZ patients’ and 74 healthy controls’ (HC) rsfMRI data to generate temporal correlation maps and, finally, evaluate mean strength (dFC-Str), variability (dFC-SD and ALFF) in each window, and the dwelling time. The difference in functional connectivity (FC) of the cuneus between two groups was compared using a two-sample t-test. Results: Our findings demonstrated decreased mean strength connectivity between the cuneus and calcarine, the cuneus and lingual gyrus, and between the cuneus and middle temporal gyrus (TPOmid) in subjects with SZ. Moreover, no difference was detected in variability (standard deviation and the amplitude of low-frequency fluctuation), the dwelling times of all states, or static functional connectivity (sFC) between the groups. Conclusions: Our verdict suggest that dynamic functional connectivity analyses may play crucial roles in unveiling abnormal patterns that would be obscured in static functional connectivity, providing promising impetus for understanding schizophrenia disease.

Dynamic causal brain circuits during working memory and their functional controllability

Control processes associated with working memory play a central role in human cognition, but their underlying dynamic brain circuit mechanisms are poorly understood. Here we use system identification, network science, stability analysis, and control theory to probe functional circuit dynamics during working memory task performance. Our results show that dynamic signaling between distributed brain areas encompassing the salience (SN), fronto-parietal (FPN), and default mode networks can distinguish between working memory load and predict performance. Network analysis of directed causal influences suggests the anterior insula node of the SN and dorsolateral prefrontal cortex node of the FPN are causal outflow and inflow hubs, respectively. Network controllability decreases with working memory load and SN nodes show the highest functional controllability. Our findings reveal dissociable roles of the SN and FPN in systems control and provide novel insights into dynamic circuit mechanisms by which cognitive control circuits operate asymmetrically during cognition.

Task-evoked reconfiguration of the fronto-parietal network is associated with cognitive performance in brain tumor patients

In healthy participants, the strength of task-evoked network reconfigurations is associated with cognitive performance across several cognitive domains. It is, however, unclear whether the capacity for network reconfiguration also plays a role in cognitive deficits in brain tumor patients. In the current study, we examined whether the level of reconfiguration of the fronto-parietal (‘FPN’) and default mode network (‘DMN’) during task execution is correlated with cognitive performance in patients with different types of brain tumors. For this purpose, we combined data from a resting state and task-fMRI paradigm in patients with a glioma or meningioma. Cognitive performance was measured using the in-scanner working memory task, as well as an out-of-scanner cognitive flexibility task. Task-evoked changes in functional connectivity strength (defined as the mean of the absolute values of all connections) and in functional connectivity patterns within and between the FPN and DMN did not differ significantly across meningioma and fast (HGG) and slowly growing glioma (LGG) patients. Across these brain tumor patients, a significant and positive correlation was found between the level of task-evoked reconfiguration of the FPN and cognitive performance. This suggests that the capacity for FPN reconfiguration also plays a role in cognitive deficits in brain tumor patients, as was previously found for normal cognitive performance in healthy controls.

Ventromedial Prefrontal Cortex Drives the Prioritization of Self-Associated Stimuli in Working Memory

Humans show a pervasive bias for processing self- over other-related information, including in working memory (WM), where people prioritize the maintenance of self- (over other-) associated cues. To elucidate the neural mechanisms underlying this self-bias, we paired a self- versus other-associated spatial WM task with fMRI and transcranial direct current stimulation (tDCS) of human participants of both sexes. Maintaining self- (over other-) associated cues resulted in enhanced activity in classic WM regions (frontoparietal cortex), and in superior multivoxel pattern decoding of the cue locations from visual cortex. Moreover, ventromedial PFC (VMPFC) displayed enhanced functional connectivity with WM regions during maintenance of self-associated cues, which predicted individuals' behavioral self-prioritization effects. In a follow-up tDCS experiment, we targeted VMPFC with excitatory (anodal), inhibitory (cathodal), or sham tDCS. Cathodal tDCS eliminated the self-prioritization effect. These findings provide strong converging evidence for a causal role of VMPFC in driving self-prioritization effects in WM and provide a unique window into the interaction between social, self-referential processing and high-level cognitive control processes.SIGNIFICANCE STATEMENT People have a strong tendency to attend to self-related stimuli, such as their names. This self-bias extends to the automatic prioritization of arbitrarily self-associated stimuli held in working memory. Since working memory is central to high-level cognition, this bias could influence how we make decisions. It is therefore important to understand the underlying brain mechanisms. Here, we used neuroimaging and noninvasive neurostimulation techniques to show that the source of self-bias in working memory is the ventromedial PFC, which modulates activity in frontoparietal brain regions to produce prioritized representations of self-associated stimuli in sensory cortex. This work thus reveals a brain circuit underlying the socially motivated (self-referential) biasing of high-level cognitive processing.

Dynamic functional connectome predicts individual working memory performance across diagnostic categories

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We created transdiagnostic predictive working memory models using connectome-based predictive modeling (CPM).

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Dynamic functional connectivity-based CPM models successfully predicted working memory.

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Static functional connectivity-based CPM models fell short in prediction.

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Frontoparietal, somato-motor, default mode and visual networks contributed most to prediction.

Working memory impairment is a common feature of psychiatric disorders. Although its neural mechanisms have been extensively examined in healthy subjects or individuals with a certain clinical condition, studies investigating neural predictors of working memory in a transdiagnostic sample are scarce. The objective of this study was to create a transdiagnostic predictive working memory model from whole-brain functional connectivity using connectome-based predictive modeling (CPM), a recently developed machine learning approach. Resting-state functional MRI data from 242 subjects across 4 diagnostic categories (healthy controls and individuals with schizophrenia, bipolar disorder, and attention deficit/hyperactivity) were used to construct dynamic and static functional connectomes. Spatial working memory was assessed by the spatial capacity task. CPM was conducted to predict individual working memory from dynamic and static functional connectivity patterns. Results showed that dynamic connectivity-based CPM models successfully predicted overall working memory capacity and accuracy as well as mean reaction time, yet their static counterparts fell short in the prediction. At the neural level, we found that dynamic connectivity of the frontoparietal and somato-motor networks were negatively correlated with working memory capacity and accuracy, and those of the default mode and visual networks were positively associated with mean reaction time. Moreover, different feature selection thresholds, parcellation strategies and model validation methods as well as diagnostic categories did not significantly influence the prediction results. Our findings not only are coherent with prior reports that dynamic functional connectivity encodes more behavioral information than static connectivity, but also help advance the translation of cognitive “connectome fingerprinting” into real-world application.

Psychological resilience is correlated with dynamic changes in functional connectivity within the default mode network during a cognitive task

Resilience is a dynamic process that enables organisms to cope with demanding environments. Resting-state functional MRI (fMRI) studies have demonstrated a negative correlation between resilience and functional connectivities (FCs) within the default mode network (DMN). Considering the on-demand recruitment process of resilience, dynamic changes in FCs during cognitive load increases may reflect essential aspects of resilience. We compared DMN FC changes in resting and task states and their association with resilience. Eighty-nine healthy volunteers completed the Connor–Davidson Resilience Scale (CD-RISC) and an fMRI with an auditory oddball task. The fMRI time series was divided into resting and task periods. We focused on FC changes between the latter half of the resting period and the former half of the task phase (switching), and between the former and latter half of the task phase (sustaining). FCs within the ventral DMN significantly increased during “switching” and decreased during “sustaining”. For FCs between the retrosplenial/posterior cingulate and the parahippocampal cortex, increased FC during switching was negatively correlated with CD-RISC scores. In individuals with higher resilience, ventral DMN connectivities were more stable and homeostatic in the face of cognitive demand. The dynamic profile of DMN FCs may represent a novel biomarker of resilience.

Brain Network Modularity During a Sustained Working-Memory Task

Spontaneous oscillations of the blood oxygenation level-dependent (BOLD) signal are spatially synchronized within specific brain networks and are thought to reflect synchronized brain activity. Networks are modulated by the performance of a task, even if the exact features and degree of such modulations are still elusive. The presence of networks showing anticorrelated fluctuations lend initially to suppose that a competitive relationship between the default mode network (DMN) and task positive networks (TPNs) supports the efficiency of brain processing. However, more recent results indicate that cooperative and competitive dynamics between networks coexist during task performance. In this study, we used graph analysis to assess the functional relevance of the topological reorganization of brain networks ensuing the execution of a steady state working-memory (WM) task. Our results indicate that the performance of an auditory WM task is associated with a switching between different topological configurations of several regions of specific networks, including frontoparietal, ventral attention, and dorsal attention areas, suggesting segregation of ventral attention regions in the presence of increased overall integration. However, the correct execution of the task requires integration between components belonging to all the involved networks.

Dynamic reconfiguration of functional brain networks during working memory training

The functional network of the brain continually adapts to changing environmental demands. The consequence of behavioral automation for task-related functional network architecture remains far from understood. We investigated the neural reflections of behavioral automation as participants mastered a dual n-back task. In four fMRI scans equally spanning a 6-week training period, we assessed brain network modularity, a substrate for adaptation in biological systems. We found that whole-brain modularity steadily increased during training for both conditions of the dual n-back task. In a dynamic analysis,we found that the autonomy of the default mode system and integration among task-positive systems were modulated by training. The automation of the n-back task through training resulted in non-linear changes in integration between the fronto-parietal and default mode systems, and integration with the subcortical system. Our findings suggest that the automation of a cognitively demanding task may result in more segregated network organization.

Working memory training reshapes the brain functional network reorganization. Here, the authors demonstrate an increase of the whole-brain network segregation during the n-back task, accompanied by alterations in dynamic communication between the default mode system and task-positive systems.

Altered Relationship between Working Memory and Brain Microstructure after Mild Traumatic Brain Injury

BACKGROUND AND PURPOSE

Working memory impairment is one of the most troubling and persistent symptoms after mild traumatic brain injury (MTBI). Here we investigate how working memory deficits relate to detectable WM microstructural injuries to discover robust biomarkers that allow early identification of patients with MTBI at the highest risk of working memory impairment.

MATERIALS AND METHODS

Multi-shell diffusion MR imaging was performed on a 3T scanner with 5 b-values. Diffusion metrics of fractional anisotropy, diffusivity and kurtosis (mean, radial, axial), and WM tract integrity were calculated. Auditory-verbal working memory was assessed using the Wechsler Adult Intelligence Scale, 4th ed, subtests: 1) Digit Span including Forward, Backward, and Sequencing; and 2) Letter-Number Sequencing. We studied 19 patients with MTBI within 4 weeks of injury and 20 healthy controls. Tract-Based Spatial Statistics and ROI analyses were performed to reveal possible correlations between diffusion metrics and working memory performance, with age and sex as covariates.

RESULTS

ROI analysis found a significant positive correlation between axial kurtosis and Digit Span Backward in MTBI (Pearson r = 0.69, corrected P = .04), mainly present in the right superior longitudinal fasciculus, which was not observed in healthy controls. Patients with MTBI also appeared to lose the normal associations typically seen in fractional anisotropy and axonal water fraction with Letter-Number Sequencing. Tract-Based Spatial Statistics results also support our findings.

CONCLUSIONS

Differences between patients with MTBI and healthy controls with regard to the relationship between microstructure measures and working memory performance may relate to known axonal perturbations occurring after injury.

Pre-scan cortisol is differentially associated with enhanced connectivity to the cognitive control network in young adults with a history of depression

BACKGROUND

We have previously demonstrated that pre-scan salivary cortisol is associated with attentuated frontal-subcortical brain activation during emotion processesing and semantic list-learning paradigms in depressed subjects. Additionally, altered functional connectivity is observed after remission of acute depression symptoms (rMDD). It is unknown whether cortisol also predicts altered functional connectivity during remission.

METHODS

Participants were 47 healthy controls (HC) and 73 rMDD, 18-30 years old who provided salivary cortisol samples before and after undergoing resting-state fMRI. We tested whether salivary cortisol by diagnosis interactions were associated with seed-based resting connectivity of the default mode (DMN) and salience and emotion (SN) networks using whole-brain, cluster-level corrected (p < .01) regression in SPM8.

RESULTS

Pre-scan cortisol predicted decreased (HC) and increased (rMDD) cross-network connectivity to the dorsal anterior cingulate, dorso-medial and lateral- prefrontal cortex, brain stem and cerebellum (all seeds) and precuneus (DMN seeds). By and large, pre/post-scan cortisol change predicted the same pattern of findings. In network analyses, cortisol predominantly predicted enhanced cross-network connectivity to cognitive control network regions in rMDD.

CONCLUSIONS

The association of cortisol with connections of default and salience networks to executive brain networks differs between individuals with and without a history of depression. Further investigation is needed to better understand the role of cortisol and related stress hormones as a potential primary and interactive driver of network coherence in depression.

Adolescent sex differences in cortico-subcortical functional connectivity during response inhibition

Numerous lines of evidence have shown that cognitive processes engaged during response inhibition tasks are associated with structure and functional integration of regions within fronto-parietal networks. However, while prior studies have started to characterize how intrinsic connectivity during resting state differs between boys and girls, comparatively less is known about how functional connectivity differs between males and females when brain function is exogenously driven by the processing demands of typical Go/No-Go tasks that assess both response inhibition and error processing. The purpose of this study was to characterize adolescent sex differences and possible changes in sexually dimorphic regional functional connectivity across adolescent development in both cortical and subcortical brain connectivity elicited during a visual Go/No-Go task. A total of 130 healthy adolescents (ages 12-25 years) performed a Go/No-Go task during functional magnetic resonance imaging. High model-order group independent component analysis was used to characterize whole-brain network functional connectivity during response inhibition and then a univariate technique used to evaluate differences related to sex and age. As predicted and similar to previously described findings from non-task-driven resting state connectivity studies, functional connectivity sex differences were observed in several subcortical regions, including the amygdala, caudate, thalamus, and cortical regions, including inferior frontal gyrus engaged most strongly during successful response inhibition and/or error processing. Importantly, adolescent boys and girls exhibited different normative profiles of age-related changes in several default mode networks of regions and anterior cingulate cortex. These results suggest that cortical-subcortical functional networks supporting response inhibition operate differently between sexes during adolescence.

Disrupted functional connectivity within the default mode network and salience network in unmedicated bipolar II disorder

BACKGROUND

Recent studies demonstrate that functional disruption in resting-state networks contributes to cognitive and affective symptoms of bipolar disorder (BD), however, the functional connectivity (FC) pattern underlying BD II depression within the default mode network (DMN), salience network (SN), and frontoparietal network (FPN) is still not well understood. The primary aim of this study was to explore whether the pathophysiology of BD II derived from the pattern of FC within the DMN, SN, and FPN by using seed-based FC approach of resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

Ninety-six BD II patients and 100 HCs underwent rs-fMRI and three-dimensional structural data acquisition. All patients were either drug naive or unmedicated for at least 6 months. The following four regions of interest were used to conduct seed-based FC: the left posterior cingulate cortex (PCC) seed to probe the DMN, the left subgenual anterior cingulate cortex (sgACC) and amygdala seeds to probe the SN, the left dorsal lateral prefrontal cortex (dlPFC) seed to probe the FPN.

RESULTS

Compared with HCs, patients with BD II demonstrated hypoconnectivity of the left PCC to the bilateral medial prefrontal cortex (mPFC) and bilateral precuneus/PCC, and of the left sgACC to the right inferior temporal gyrus (ITG); nevertheless, the left amygdala and dlPFC had no within-network hypo- or hyperconnectivity to any other SN and FPN regions.

CONCLUSION

Our findings suggest that disrupted FC is located in the DMN and SN, especially in the PCC-mPFC and precuneus/PCC, and sgACC-ITG connectivity in BD II patients.

Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation

Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what extent the execution of a cognitive task affects the intrinsic activity of brain regions not involved in the task. Computational models can be useful to answer this question because they allow us to distinguish task from nontask neural elements while giving us the effects of task execution on nontask regions of interest at the neuroimaging level. The quantification of those effects in a computational model would represent a step toward elucidating the intrinsic versus task-evoked connection. In this study we used computational modeling and graph theoretical metrics to quantify changes in intrinsic functional brain connectivity due to task execution. We used our large-scale neural modeling framework to embed a computational model of visual short-term memory into an empirically derived connectome. We simulated a neuroimaging study consisting of 10 subjects performing passive fixation (PF), passive viewing (PV), and delayed match-to-sample (DMS) tasks. We used the simulated blood oxygen level-dependent functional magnetic resonance imaging time series to calculate functional connectivity (FC) matrices and used those matrices to compute several graph theoretical measures. After determining that the simulated graph theoretical measures were largely consistent with experiments, we were able to quantify the differences between the graph metrics of the PF condition and those of the PV and DMS conditions. Thus, we show that we can use graph theoretical methods applied to simulated brain networks to aid in the quantification of changes in intrinsic brain FC during task execution. Our results represent a step toward establishing a connection between intrinsic and task-related brain activities.

Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation

This study examines the impact of using different cerebrospinal fluid (CSF) and white matter (WM) nuisance signals for data-driven filtering of functional magnetic resonance imaging (fMRI) data as a cleanup method before analyzing intrinsic brain fluctuations. The routinely used temporal signal-to-noise ratio metric is inappropriate for assessing fMRI filtering suitability, as it evaluates only the reduction of data variability and does not assess the preservation of signals of interest. We defined a new metric that evaluates the preservation of selected neural signal correlates, and we compared its performance with a recently published signal-noise separation metric. These two methods provided converging evidence of the unfavorable impact of commonly used filtering approaches that exploit higher numbers of principal components from CSF and WM compartments (typically 5 + 5 for CSF and WM, respectively). When using only the principal components as nuisance signals, using a lower number of signals results in a better performance (i.e., 1 + 1 performed best). However, there was evidence that this routinely used approach consisting of 1 + 1 principal components may not be optimal for filtering resting-state (RS) fMRI data, especially when RETROICOR filtering is applied during the data preprocessing. The evaluation of task data indicated the appropriateness of 1 + 1 principal components, but when RETROICOR was applied, there was a change in the optimal filtering strategy. The suggested change for extracting WM (and also CSF in RETROICOR-corrected RS data) is using local signals instead of extracting signals from a large mask using principal component analysis.

Resting-State Connectivity and Its Association With Cognitive Performance, Educational Attainment, and Household Income in the UK Biobank

Background

Cognitive ability is an important predictor of lifelong physical and mental well-being, and impairments are associated with many psychiatric disorders. Higher cognitive ability is also associated with greater educational attainment and increased household income. Understanding neural mechanisms underlying cognitive ability is of crucial importance for determining the nature of these associations. In the current study, we examined the spontaneous activity of the brain at rest to investigate its relationships with not only cognitive ability but also educational attainment and household income.

Methods

We used a large sample of resting-state neuroimaging data from the UK Biobank (n = 3950).

Results

First, analysis at the whole-brain level showed that connections involving the default mode network (DMN), frontoparietal network (FPN), and cingulo-opercular network (CON) were significantly positively associated with levels of cognitive performance assessed by a verbal-numerical reasoning test (standardized β cingulo-opercular values ranged from 0.054 to 0.097, p_corrected < .038). Connections associated with higher levels of cognitive performance were also significantly positively associated with educational attainment (r = .48, n = 4160) and household income (r = .38, n = 3793). Furthermore, analysis on the coupling of functional networks showed that better cognitive performance was associated with more positive DMN–CON connections, decreased cross-hemisphere connections between the homotopic network in the CON and FPN, and stronger CON–FPN connections (absolute βs ranged from 0.034 to 0.063, p_corrected < .045).

Conclusions

The current study found that variation in brain resting-state functional connectivity was associated with individual differences in cognitive ability, largely involving the DMN and lateral prefrontal network. In addition, we provide evidence of shared neural associations of cognitive ability, educational attainment, and household income.

Effects of task complexity and age-differences on task-related functional connectivity of attentional networks

Studies investigating the strength and membership of regions within multiple functional networks primarily focus on either resting state or single cognitive tasks. The goals of the current study were to investigate whether task-related functional connectivity changes with task complexity, and whether this connectivity-complexity relationship is age-sensitive. We assessed seed-to-voxel functional connectivity for the default mode network (DMN) and two attentional networks [cingulo-opercular (CO), fronto-parietal (FP)] in three cognitive control tasks of increasing complexity (Single task, Dual task, and Memory Updating), across younger and older adults (N = 52; N_Young = 23; N_Old = 29). The three tasks systematically varied in cognitive control demands due to differing maintenance, switching, and updating requirements. Functional connectivity for all networks, resulting from task > rest contrasts, increased with greater task complexity, irrespective of age and gray matter volume. Moreover, between-network connectivity for DMN, CO, and FP regions was greatest for working memory updating, the most complex task. Regarding age-related differences in accuracy, none were observed for Single or Dual tasks, but older adults had poorer accuracy in Memory Updating. More anterior frontal clusters of functional connectivity were observed for older, compared to younger, adults; these were limited to seeds of the two attentional networks. Importantly, increased connectivity in these additional frontal regions in older adults were non-compensatory, because they were associated with detrimental task performance, especially Memory Updating. For the Memory Updating > Rest, the younger > older contrast resulted in greater DMN seed connectivity to regions in the other two attentional networks, implicating increased reliance on between-network connectivity for the DMN seeds during complex cognitive tasks. Our results also implicate functional connectivity between attentional networks and the cerebellum during cognitive control. Reliability of multiple seeds in the seed-to-voxel connectivity is also discussed.

Automated Extraction of Human Functional Brain Network Properties Associated with Working Memory Load through a Machine Learning-Based Feature Selection Algorithm

Working memory (WM) load-dependent changes of functional connectivity networks have previously been investigated by graph theoretical analysis. However, the extraordinary number of nodes represented within the complex network of the human brain has hindered the identification of functional regions and their network properties. In this paper, we propose a novel method for automatically extracting characteristic brain regions and their graph theoretical properties that reflect load-dependent changes in functional connectivity using a support vector machine classification and genetic algorithm optimization. The proposed method classified brain states during 2- and 3-back test conditions based upon each of the three regional graph theoretical metrics (degree, clustering coefficient, and betweenness centrality) and automatically identified those brain regions that were used for classification. The experimental results demonstrated that our method achieved a >90% of classification accuracy using each of the three graph metrics, whereas the accuracy of the conventional manual approach of assigning brain regions was only 80.4%. It has been revealed that the proposed framework can extract meaningful features of a functional brain network that is associated with WM load from a large number of nodal graph theoretical metrics without prior knowledge of the neural basis of WM.

Structural imaging of mild traumatic brain injury may not be enough: overview of functional and metabolic imaging of mild traumatic brain injury

A majority of patients with traumatic brain injury (TBI) present as mild injury with no findings on conventional clinical imaging methods. Due to this difficulty of imaging assessment on mild TBI patients, there has been much emphasis on the development of diffusion imaging modalities such as diffusion tensor imaging (DTI). However, basic science research in TBI shows that many of the functional and metabolic abnormalities in TBI may be present even in the absence of structural damage. Moreover, structural damage may be present at a microscopic and molecular level that is not detectable by structural imaging modality. The use of functional and metabolic imaging modalities can provide information on pathological changes in mild TBI patients that may not be detected by structural imaging. Although there are various differences in protocols of positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) methods, these may be important modalities to be used in conjunction with structural imaging in the future in order to detect and understand the pathophysiology of mild TBI. In this review, studies of mild TBI patients using these modalities that detect functional and metabolic state of the brain are discussed. Each modality's advantages and disadvantages are compared, and potential future applications of using combined modalities are explored.

Reliability, Convergent Validity and Time Invariance of Default Mode Network Deviations in Early Adult Major Depressive Disorder

There is substantial variability across studies of default mode network (DMN) connectivity in major depressive disorder, and reliability and time-invariance are not reported. This study evaluates whether DMN dysconnectivity in remitted depression (rMDD) is reliable over time and symptom-independent, and explores convergent relationships with cognitive features of depression. A longitudinal study was conducted with 82 young adults free of psychotropic medications (47 rMDD, 35 healthy controls) who completed clinical structured interviews, neuropsychological assessments, and 2 resting-state fMRI scans across 2 study sites. Functional connectivity analyses from bilateral posterior cingulate and anterior hippocampal formation seeds in DMN were conducted at both time points within a repeated-measures analysis of variance to compare groups and evaluate reliability of group-level connectivity findings. Eleven hyper- (from posterior cingulate) and 6 hypo- (from hippocampal formation) connectivity clusters in rMDD were obtained with moderate to adequate reliability in all but one cluster (ICC's range = 0.50 to 0.76 for 16 of 17). The significant clusters were reduced with a principle component analysis (5 components obtained) to explore these connectivity components, and were then correlated with cognitive features (rumination, cognitive control, learning and memory, and explicit emotion identification). At the exploratory level, for convergent validity, components consisting of posterior cingulate with cognitive control network hyperconnectivity in rMDD were related to cognitive control (inverse) and rumination (positive). Components consisting of anterior hippocampal formation with social emotional network and DMN hypoconnectivity were related to memory (inverse) and happy emotion identification (positive). Thus, time-invariant DMN connectivity differences exist early in the lifespan course of depression and are reliable. The nuanced results suggest a ventral within-network hypoconnectivity associated with poor memory and a dorsal cross-network hyperconnectivity linked to poorer cognitive control and elevated rumination. Study of early course remitted depression with attention to reliability and symptom independence could lead to more readily translatable clinical assessment tools for biomarkers.

Differential contributions of the middle frontal gyrus functional connectivity to literacy and numeracy

Literacy and numeracy equally affect an individual's success in and beyond schools, but these two competencies tend to be separately examined, particularly in neuroimaging studies. The current resting-state fMRI study examined the neural correlates of literacy and numeracy in the same sample of healthy adults. We first used an exploratory "Multivariate Distance Matrix Regression" (MDMR) approach to examine intrinsic functional connectivity (iFC), highlighting the middle frontal gyrus (MFG) for both competencies. Notably, there was a hemispheric asymmetry in the MDMR-based MFG findings, with literacy associated with the left MFG, whereas numeracy associated with the right MFG (R.MFG). Results of post-hoc seed-based correlation analyses further strengthened differential contributions of MFG connections to each competency. One of the most striking and novel findings from the present work was that numeracy was negatively related to R.MFG connections with the default network, which has been largely overlooked in the literature. Our results are largely consistent with prior neuroimaging work showing distinct neural mechanisms underlying literacy and numeracy, and also indicate potentially common iFC profiles to both competencies (e.g., R.MFG with cerebellum). Taken together, our iFC findings have a potential to provide novel insights into neural bases of literacy, numeracy, and impairments in these competencies.

Evidence for Two Independent Factors that Modify Brain Networks to Meet Task Goals

Humans easily and flexibly complete a wide variety of tasks. To accomplish this feat, the brain appears to subtly adjust stable brain networks. Here, we investigate what regional factors underlie these modifications, asking whether networks are either altered at (1) regions activated by a given task or (2) hubs that interconnect different networks. We used fMRI "functional connectivity" (FC) to compare networks during rest and three distinct tasks requiring semantic judgments, mental rotation, and visual coherence. We found that network modifications during these tasks were independently associated with both regional activation and network hubs. Furthermore, active and hub regions were associated with distinct patterns of network modification (differing in their localization, topography of FC changes, and variability across tasks), with activated hubs exhibiting patterns consistent with task control. These findings indicate that task goals modify brain networks through two separate processes linked to local brain function and network hubs.

Task-Related Modulations of BOLD Low-Frequency Fluctuations within the Default Mode Network

Spontaneous low-frequency Blood-Oxygenation Level-Dependent (BOLD) signals acquired during resting state are characterized by spatial patterns of synchronous fluctuations, ultimately leading to the identification of robust brain networks. The resting-state brain networks, including the Default Mode Network (DMN), are demonstrated to persist during sustained task execution, but the exact features of task-related changes of network properties are still not well characterized. In this work we sought to examine in a group of 20 healthy volunteers (age 33 ± 6 years, 8 F/12 M) the relationship between changes of spectral and spatiotemporal features of one prominent resting-state network, namely the DMN, during the continuous execution of a working memory n-back task. We found that task execution impacted on both functional connectivity and amplitude of BOLD fluctuations within large parts of the DMN, but these changes correlated between each other only in a small area of the posterior cingulate. We conclude that combined analysis of multiple parameters related to connectivity, and their changes during the transition from resting state to continuous task execution, can contribute to a better understanding of how brain networks rearrange themselves in response to a task.

Age-Related Differences in Dynamic Interactions Among Default Mode, Frontoparietal Control, and Dorsal Attention Networks during Resting-State and Interference Resolution

Resting-state fMRI (rs-fMRI) can identify large-scale brain networks, including the default mode (DMN), frontoparietal control (FPN) and dorsal attention (DAN) networks. Interactions among these networks are critical for supporting complex cognitive functions, yet the way in which they are modulated across states is not well understood. Moreover, it remains unclear whether these interactions are similarly affected in aging regardless of cognitive state. In this study, we investigated age-related differences in functional interactions among the DMN, FPN and DAN during rest and the Multi-Source Interference task (MSIT). Networks were identified using independent component analysis (ICA), and functional connectivity was measured during rest and task. We found that the FPN was more coupled with the DMN during rest and with the DAN during the MSIT. The degree of FPN-DMN connectivity was lower in older compared to younger adults, whereas no age-related differences were observed in FPN-DAN connectivity in either state. This suggests that dynamic interactions of the FPN are stable across cognitive states. The DMN and DAN were anti correlated and age-sensitive during the MSIT only, indicating variation in a task-dependent manner. Increased levels of anticorrelation from rest to task also predicted successful interference resolution. Additional analyses revealed that the degree of DMN-DAN anticorrelation during the MSIT was associated to resting cerebral blood flow (CBF) within the DMN. This suggests that reduced DMN neural activity during rest underlies an impaired ability to achieve higher levels of anticorrelation during a task. Taken together, our results suggest that only parts of age-related differences in connectivity are uncovered at rest and thus, should be studied in the functional connectome across multiple states for a more comprehensive picture.

Dynamic Default Mode Network across Different Brain States

The default mode network (DMN) is a complex dynamic network that is critical for understanding cognitive function. However, whether dynamic topological reconfiguration of the DMN occurs across different brain states, and whether this potential reorganization is associated with prior learning or experience is unclear. To better understand the temporally changing topology of the DMN, we investigated both nodal and global dynamic DMN-topology metrics across different brain states. We found that DMN topology changes over time and those different patterns are associated with different brain states. Further, the nodal and global topological organization can be rebuilt by different brain states. These results indicate that the post-task, resting-state topology of the brain network is dynamically altered as a function of immediately prior cognitive experience, and that these modulated networks are assembled in the subsequent state. Together, these findings suggest that the changing topology of the DMN may play an important role in characterizing brain states.

Does neuropsychological performance impact on real-life functional achievements in obsessive-compulsive disorder? A preliminary study

OBJECTIVE

We investigated the association between neuropsychological performance and real-life functioning in obsessive-compulsive disorder (OCD). As a secondary aim, we investigated the association between neuropsychological performance and self-reported quality of life (QoL).

METHODS

We retrospectively selected 68 of 240 inpatients with OCD, who had been hospitalised for a 4-week psychiatric rehabilitation programme. We used clinical information recorded in the patients' electronic medical records. We considered the following variables: neuropsychological performance (verbal/visual memory, sustained attention, visual-constructive ability, and language fluency; in a sub-sample of 37 subjects, divided attention, working memory, and attentional shifting were also available); real-life functional achievements (social/vocational outcomes and independent living); subjectively reported QoL (WHOQOL-BREF); obsessive-compulsive (OC) symptoms severity (DY-BOCS).

RESULTS

We found significant associations between poorer neuropsychological performance and poorer achievements in independent living and vocational outcomes. Among the different neuropsychological tests, we found significant associations between language fluency/executive processing and independent living, and between divided attention, attentional shifting, working memory and vocational outcome. We found no significant associations between neuropsychological performance and subjectively reported QoL. OC symptoms severity was not associated with real-life functional achievements.

CONCLUSIONS

Our preliminary results suggest that poorer neuropsychological performance may be associated with impaired real-life functioning in subjects with OCD.

Coronary artery calcium is associated with cortical thinning in cognitively normal individuals

To evaluate the association between coronary artery calcium (CAC) and cortical thickness in a large sample of cognitively normal individuals, with special emphasis in determining if the association thickness has regional brain specificity and if it is mediated by white matter hyperintensities (WMH). A total of 512 participants were included in this study. CAC scores were assessed by multi-detector computed tomography. Cortical thickness was measured using a surface-based method. Linear mixed models were used to assess the association between CAC scores and cortical thickness. In fully adjusted models, increased CAC scores were associated with cortical thinning across several brain regions, which generally overlapped with the distribution of default mode network. The association between CAC scores and cortical thickness was significantly stronger in participants with moderate or severe WMH compared to those with none or mild WMH, even though CAC scores were not associated with WMH. In cognitively normal adults, CAC was associated with cortical thinning in areas related to cognitive function. This association was evident after adjusting for multiple coronary artery disease risk factors and for WMH, suggesting that CAC may be more closely related to Alzheimer’s Disease-type disease rather than to cerebral small vessel disease.

Desynchronization of autonomic response and central autonomic network connectivity in posttraumatic stress disorder

OBJECTIVES

Although dysfunctional emotion regulatory capacities are increasingly recognized as contributing to posttraumatic stress disorder (PTSD), little work has sought to identify biological markers of this vulnerability. Heart rate variability (HRV) is a promising biomarker that, together with neuroimaging, may assist in gaining a deeper understanding of emotion dysregulation in PTSD. The objective of the present study was, therefore, to characterize autonomic response patterns, and their related neuronal patterns in individuals with PTSD at rest.

METHODS

PTSD patients (N = 57) and healthy controls (N = 41) underwent resting-state fMRI. Connectivity patterns of key regions within the central autonomic network (CAN)-including the ventromedial prefrontal cortex (vmPFC), amygdala, and periaqueductal gray (PAG)-were examined using a seed-based approach. Observed connectivity patterns were then correlated to resting HRV.

RESULTS

In contrast to controls, individuals with PTSD exhibited lower HRV. In addition, whereas controls engaged a localized connectivity pattern of CAN-related brain regions, in PTSD, key CAN regions were associated with widespread connectivity patterns in regions related to emotional reactivity (vmPFC and amygdala to insular cortex and lentiform nucleus; PAG to insula) and motor readiness (vmPFC and amygdala to precentral gyrus; PAG to precentral gyrus and cerebellum). Critically, whereas CAN connectivity in controls was strongly related to higher HRV (insula, mPFC, superior frontal cortex, thalamus), HRV covariation was absent in PTSD subjects.

CONCLUSIONS

This study provides the first evidence for a specific psychophysiological-neuronal profile in PTSD individuals characterized by lower resting HRV and a lack of HRV covariation with CAN-related brain connectivity. Hum Brain Mapp 38:27-40, 2017. © 2016 Wiley Periodicals, Inc.

Angular default mode network connectivity across working memory load

Initially identified during no-task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large-scale brain networks. Nevertheless, its contribution to whole-brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI-based n-back paradigm with parametric increases in difficulty. Using a voxel-wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n-back task load. Subsequent seed-based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large-scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n-back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41-52, 2017. © 2016 Wiley Periodicals, Inc.

Decoupling of the amygdala to other salience network regions in adolescent-onset recurrent major depressive disorder

BACKGROUND

Recent meta-analyses of resting-state networks in major depressive disorder (MDD) implicate network disruptions underlying cognitive and affective features of illness. Heterogeneity of findings to date may stem from the relative lack of data parsing clinical features of MDD such as phase of illness and the burden of multiple episodes.

METHOD

Resting-state functional magnetic resonance imaging data were collected from 17 active MDD and 34 remitted MDD patients, and 26 healthy controls (HCs) across two sites. Participants were medication-free and further subdivided into those with single v. multiple episodes to examine disease burden. Seed-based connectivity using the posterior cingulate cortex (PCC) seed to probe the default mode network as well as the amygdala and subgenual anterior cingulate cortex (sgACC) seeds to probe the salience network (SN) were conducted.

RESULTS

Young adults with remitted MDD demonstrated hyperconnectivity of the left PCC to the left inferior frontal gyrus and of the left sgACC to the right ventromedial prefrontal cortex (PFC) and left hippocampus compared with HCs. Episode-independent effects were observed between the left PCC and the right dorsolateral PFC, as well as between the left amygdala and right insula and caudate, whereas the burden of multiple episodes was associated with hypoconnectivity of the left PCC to multiple cognitive control regions as well as hypoconnectivity of the amygdala to large portions of the SN.

CONCLUSIONS

This is the first study of a homogeneous sample of unmedicated young adults with a history of adolescent-onset MDD illustrating brain-based episodic features of illness.

Failed cooperative, but not competitive, interaction between large-scale brain networks impairs working memory in schizophrenia

BACKGROUND

A large-scale network named the default mode network (DMN) dynamically cooperates and competes with an external attention system (EAS) to facilitate various cognitive functioning that is prominently impaired in schizophrenia. However, it is unclear whether the cognitive deficit in schizophrenia is related to the disrupted competition and/or cooperation between these two networks.

METHOD

A total of 35 schizophrenia patients and 30 healthy controls were scanned using gradient-echo echo-planar imaging during n-back working memory (WM) processing. Brain activities of the DMN and EAS were measured using general linear modelling of the functional magnetic resonance imaging data. Dynamic interaction between the DMN and EAS was decomposed into two directions using Granger causality analysis.

RESULTS

We observed a significant failure of DMN suppression in patients with schizophrenia, which was significantly related to WM/attentional deficit. Granger causality modelling showed that in healthy controls, while the EAS inhibitorily influenced the DMN, the DMN exerted an 'excitatory' or cooperative influence back on the EAS, especially in those with lower WM accuracy. In schizophrenia, this 'excitatory' DMN→EAS influence within the reciprocal EAS-DMN loop was significantly reduced, especially in patients with WM/attentional deficit.

CONCLUSIONS

The dynamic interaction between the DMN and EAS is likely to be comprised of both competitive and cooperative influences. In healthy controls, both the 'inhibitory' EAS→DMN interaction and 'excitatory' DMN→EAS interaction are correlated with WM performance. In schizophrenia, reduced 'cooperative' influence from the DMN to dorsal nodes of the EAS occurs in the context of non-suppression of the DMN and may form a possible pathophysiological substrate of WM deficit and attention disorder.

Multivariate pattern analysis strategies in detection of remitted major depressive disorder using resting state functional connectivity

Understanding abnormal resting-state functional connectivity of distributed brain networks may aid in probing and targeting mechanisms involved in major depressive disorder (MDD). To date, few studies have used resting state functional magnetic resonance imaging (rs-fMRI) to attempt to discriminate individuals with MDD from individuals without MDD, and to our knowledge no investigations have examined a remitted (r) population. In this study, we examined the efficiency of support vector machine (SVM) classifier to successfully discriminate rMDD individuals from healthy controls (HCs) in a narrow early-adult age range. We empirically evaluated four feature selection methods including multivariate Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net feature selection algorithms. Our results showed that SVM classification with Elastic Net feature selection achieved the highest classification accuracy of 76.1% (sensitivity of 81.5% and specificity of 68.9%) by leave-one-out cross-validation across subjects from a dataset consisting of 38 rMDD individuals and 29 healthy controls. The highest discriminating functional connections were between the left amygdala, left posterior cingulate cortex, bilateral dorso-lateral prefrontal cortex, and right ventral striatum. These appear to be key nodes in the etiopathophysiology of MDD, within and between default mode, salience and cognitive control networks. This technique demonstrates early promise for using rs-fMRI connectivity as a putative neurobiological marker capable of distinguishing between individuals with and without rMDD. These methods may be extended to periods of risk prior to illness onset, thereby allowing for earlier diagnosis, prevention, and intervention.

Functional magnetic resonance and diffusion tensor imaging analysis of verbal working memory in patients with temporal lobe epilepsy

OBJECTIVE

This study aimed to investigate the relationships between brain functions and verbal working memory (VWM) impairments in patients with temporal lobe epilepsy (TLE).

METHODS

Functional magnetic resonance imaging was performed on 15 healthy controls and 15 patients with TLE while they performed the N-back task in order to compare the brain areas that were activated during VWM. Diffusion tensor imaging was then performed to examine the integrity of the VWM-related fiber bundles.

RESULTS

The patient group exhibited a significant reduction in the activation of the brain areas that were negatively activated in the VWM task in the control group (P < 0.05), and no activation was observed in the patient group in the brain areas that were positively activated in the VWM task in the control group. The fractional anisotropy values of both cingulate bundles were significantly reduced in the patient group compared with those in the control group (P < 0.05), and these values were positively correlated with the number of activated pixels in the ipsilateral prefrontal areas (left: r = 0.790, P < 0.05; right: r = 0.852, P < 0.05).

CONCLUSIONS

Patients with TLE exhibited impaired VWM functions that were related to subtle alterations in the cingulate bundles.

Task-related modulation of functional connectivity variability and its behavioral correlations

Two new directions of functional connectivity investigation are emerging to advance studies of the brain's functional organization. First, the identification of task-related dynamics of functional connectivity has elicited a growing interest in characterizing the brain's functional reorganization due to task demands. Second, the nonstationarity of functional connectivity [i.e., functional connectivity variability (FCV)] within a single brain state has been increasingly recognized and studied. However, a combined investigation of these two avenues of research to explore the potential task-modulation of FCV is lacking, which, nevertheless, could both improve our understanding of the potential sources of FCV and also reveal new strategies to study the neural correlates of task performance. In this study, 19 human subjects underwent four functional magnetic resonance imaging (fMRI) scans including both resting and task states to study task-related modulation of FCV. Consistent with the hypothesis that FCV is partly underpinned by unconstrained mind wandering, FCV demonstrated significant task-related decreases measured at the regional, network and system levels, which was greater for between-network interactions than within-network connections. Conversely, there remained a significant degree of residual variability during the task scans, suggesting that FCV is not specific to the resting state and likely includes an intrinsic, physiologically driven component. Finally, the degree of task-induced decreases in FCV was significantly correlated with task performance accuracy, supporting its behavior significance. Overall, task modulation of FCV may represent an important direction for future studies, not only to provide insight into normal brain functioning but also to reveal potential biomarkers of various brain disorders.

The default mode network and the working memory network are not anti-correlated during all phases of a working memory task

Introduction

The default mode network and the working memory network are known to be anti-correlated during sustained cognitive processing, in a load-dependent manner. We hypothesized that functional connectivity among nodes of the two networks could be dynamically modulated by task phases across time.

Methods

To address the dynamic links between default mode network and the working memory network, we used a delayed visuo-spatial working memory paradigm, which allowed us to separate three different phases of working memory (encoding, maintenance, and retrieval), and analyzed the functional connectivity during each phase within and between the default mode network and the working memory network networks.

Results

We found that the two networks are anti-correlated only during the maintenance phase of working memory, i.e. when attention is focused on a memorized stimulus in the absence of external input. Conversely, during the encoding and retrieval phases, when the external stimulation is present, the default mode network is positively coupled with the working memory network, suggesting the existence of a dynamically switching of functional connectivity between “task-positive” and “task-negative” brain networks.

Conclusions

Our results demonstrate that the well-established dichotomy of the human brain (anti-correlated networks during rest and balanced activation-deactivation during cognition) has a more nuanced organization than previously thought and engages in different patterns of correlation and anti-correlation during specific sub-phases of a cognitive task. This nuanced organization reinforces the hypothesis of a direct involvement of the default mode network in cognitive functions, as represented by a dynamic rather than static interaction with specific task-positive networks, such as the working memory network.

Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity

Successful performance of challenging cognitive tasks depends on a consistent functional segregation of activity within the default-mode network, on the one hand, and control networks encompassing frontoparietal and cingulo-opercular areas on the other. Recent work, however, has suggested that in some cognitive control contexts nodes within the default-mode and control networks may actually cooperate to achieve optimal task performance. Here, we used functional magnetic resonance imaging to examine whether the ability to relate variables while solving a cognitive reasoning problem involves transient increases in connectivity between default-mode and control regions. Participants performed a modified version of the classic Wason selection task, in which the number of variables to be related is systematically varied across trials. As expected, areas within the default-mode network showed a parametric deactivation with increases in relational complexity, compared with neural activity in null trials. Critically, some of these areas also showed enhanced connectivity with task-positive control regions. Specifically, task-based connectivity between the striatum and the angular gyri, and between the thalamus and right temporal pole, increased as a function of relational complexity. These findings challenge the notion that functional segregation between regions within default-mode and control networks invariably support cognitive task performance, and reveal previously unknown roles for the striatum and thalamus in managing network dynamics during cognitive reasoning.

Goal-congruent default network activity facilitates cognitive control

Substantial neuroimaging evidence suggests that spontaneous engagement of the default network impairs performance on tasks requiring executive control. We investigated whether this impairment depends on the congruence between executive control demands and internal mentation. We hypothesized that activation of the default network might enhance performance on an executive control task if control processes engage long-term memory representations that are supported by the default network. Using fMRI, we scanned 36 healthy young adult humans on a novel two-back task requiring working memory for famous and anonymous faces. In this task, participants (1) matched anonymous faces interleaved with anonymous face, (2) matched anonymous faces interleaved with a famous face, or (3) matched a famous faces interleaved with an anonymous face. As predicted, we observed a facilitation effect when matching famous faces, compared with anonymous faces. We also observed greater activation of the default network during these famous face-matching trials. The results suggest that activation of the default network can contribute to task performance during an externally directed executive control task. Our findings provide evidence that successful activation of the default network in a contextually relevant manner facilitates goal-directed cognition.