Repetitive negative thinking in daily life and functional connectivity among default mode, fronto-parietal, and salience networks

Specific alterations of resting-state functional connectivity in the triple network related to comorbid anxiety in major depressive disorder

The brain's default mode network (DMN) and the executive control network (ECN) switch engagement are influenced by the ventral attention network (VAN). Alterations in resting-state functional connectivity (RSFC) within this so-called triple network have been demonstrated in patients with major depressive disorder (MDD) or anxiety disorders (ADs). This study investigated alterations in the RSFC in patients with comorbid MDD and ADs to better understand the pathophysiology of this prevalent group of patients. Sixty-eight participants (52.9% male, mean age 35.3 years), consisting of 25 patients with comorbid MDD and ADs (MDD + AD), 20 patients with MDD only (MDD) and 23 healthy controls (HCs) were investigated clinically and with 3T resting-state fMRI. RSFC utilizing a seed-based approach within the three networks belonging to the triple network was compared between the groups. Compared with HC, MDD + AD showed significantly reduced RSFC between the ECN and the VAN, the DMN and the VAN and within the ECN. No differences could be found for the MDD group compared with both other groups. Furthermore, symptom severity and medication status did not affect RSFC values. The results of this study show a distinct set of alterations of RSFC for patients with comorbid MDD and AD compared with HCs. This set of dysfunctions might be related to less adequate switching between the DMN and the ECN as well as poorer functioning of the ECN. This might contribute to additional difficulties in engaging and utilizing consciously controlled emotional regulation strategies.

Neuroscience meets behavior: A systematic literature review on magnetic resonance imaging of the brain combined with real-world digital phenotyping

A primary goal of neuroscience is to understand the relationship between the brain and behavior. While magnetic resonance imaging (MRI) examines brain structure and function under controlled conditions, digital phenotyping via portable automatic devices (PAD) quantifies behavior in real-world settings. Combining these two technologies may bridge the gap between brain imaging, physiology, and real-time behavior, enhancing the generalizability of laboratory and clinical findings. However, the use of MRI and data from PADs outside the MRI scanner remains underexplored. Herein, we present a Preferred Reporting Items for Systematic Reviews and Meta-Analysis systematic literature review that identifies and analyzes the current state of research on the integration of brain MRI and PADs. PubMed and Scopus were automatically searched using keywords covering various MRI techniques and PADs. Abstracts were screened to only include articles that collected MRI brain data and PAD data outside the laboratory environment. Full-text screening was then conducted to ensure included articles combined quantitative data from MRI with data from PADs, yielding 94 selected papers for a total of N = 14,778 subjects. Results were reported as cross-frequency tables between brain imaging and behavior sampling methods and patterns were identified through network analysis. Furthermore, brain maps reported in the studies were synthesized according to the measurement modalities that were used. Results demonstrate the feasibility of integrating MRI and PADs across various study designs, patient and control populations, and age groups. The majority of published literature combines functional, T1-weighted, and diffusion weighted MRI with physical activity sensors, ecological momentary assessment via PADs, and sleep. The literature further highlights specific brain regions frequently correlated with distinct MRI-PAD combinations. These combinations enable in-depth studies on how physiology, brain function and behavior influence each other. Our review highlights the potential for constructing brain-behavior models that extend beyond the scanner and into real-world contexts.

Unraveling how the adolescent brain deals with criticism using dynamic causal modeling

Sensitivity to criticism, which can be defined as a negative evaluation that a person receives from someone else, is considered a risk factor for the development of psychiatric disorders in adolescents. They may be more vulnerable to social evaluation than adults and exhibit more inadequate emotion regulation strategies such as rumination. The neural network involved in dealing with criticism in adolescents may serve as a biomarker for vulnerability to depression. However, the directions of the functional interactions between the brain regions within this neural network in adolescents are still unclear. In this study, 64 healthy adolescents (aged 14 to 17 years) were asked to listen to a series of self-referential auditory segments, which included negative (critical), positive (praising), and neutral conditions, during fMRI scanning. Dynamic Causal Modeling (DCM) with Parametric Empirical Bayesian (PEB) analysis was performed to map the interactions within the neural network that was engaged during the processing of these segments. Three regions were identified to form the interaction network: the left pregenual anterior cingulate cortex (pgACC), the left dorsolateral prefrontal cortex (DLPFC), and the right precuneus (preCUN). We quantified the modulatory effects of exposure to criticism and praise on the effective connectivity between these brain regions. Being criticized was found to significantly inhibit the effective connectivity from the preCUN to the DLPFC. Adolescents who scored high on the Perceived Criticism Measure (PCM) showed less inhibition of the preCUN-to-DLPFC connectivity when being criticized, which may indicate that they required more engagement of the Central Executive Network (which includes the DLPFC) to sufficiently disengage from negative self-referential processing. Furthermore, the inhibitory connectivity from the DLPFC to the pgACC was strengthened by exposure to praise as well as criticism, suggesting a recruitment of cognitive control over emotional responses when dealing with positive and negative evaluative feedback. Our novel findings contribute to a more profound understanding of how criticism affects the adolescent brain and can help to identify potential biomarkers for vulnerability to develop mood disorders before or during adulthood.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Recent advances in the neuroscience of spontaneous and off-task thought: implications for mental health

People spend a remarkable 30-50% of awake life thinking about something other than what they are currently doing. These experiences of being "off-task" can be described as spontaneous thought when mental dynamics are relatively flexible. Here we review recent neuroscience developments in this area and consider implications for mental wellbeing and illness. We provide updated overviews of the roles of the default mode network and large-scale network dynamics, and we discuss emerging candidate mechanisms involving hippocampal memory (sharp-wave ripples, replay) and neuromodulatory (noradrenergic and serotonergic) systems. We explore how distinct brain states can be associated with or give rise to adaptive and maladaptive forms of thought linked to distinguishable mental health outcomes. We conclude by outlining new directions in the neuroscience of spontaneous and off-task thought that may clarify mechanisms, lead to personalized biomarkers, and facilitate therapy developments toward the goals of better understanding and improving mental health.

Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state

Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.

Functional connectivity in rumination: a systematic review of magnetic resonance imaging studies

INTRODUCTION

Rumination, defined as intrusive and repetitive thoughts in response to negative emotions, uncertainty, and inconsistency between goal and current situation, is a significant risk factor for depressive disorders. The rumination literature presents diverse findings on functional connectivity and shows heterogeneity in research methods. This systematic review seeks to integrate these findings and provide readers diverse perspectives.

METHOD

For this purpose, the literature on functional connectivity in rumination was reviewed according to the PRISMA guidelines. Regional connectivity and network connectivity results were scrutinized according to the presence of depression, research methods, and type of rumination. After screening 492 articles, a total of 36 studies were included.

RESULTS

The results showed that increased connectivity of the default mode network (DMN) was consistently reported. Other important findings include alterations in the connectivity between the DMN and the frontoparietal network and the salience network (SN) and impaired regulatory function of the SN. Region-level connectivity studies consistently show that increased connectivity between the posterior cingulate cortex and the prefrontal cortex is associated with rumination, which may cause the loss of control of the frontoparietal network over self-referential processes. We have seen that the number of studies examining brooding and reflective rumination as separate dimensions are relatively limited. Although there are overlaps between the connectivity patterns of the two types of rumination in these studies, it can be thought that reflective rumination is more associated with more increased functional connectivity of the prefrontal cortex.

CONCLUSIONS

Although there are many consistent functional connectivity outcomes associated with trait rumination, less is known about connectivity changes during state rumination. Relatively few studies have taken into account the subjective aspect of this thinking style. In order to better explain the relationship between rumination and depression, rumination induction studies during episode and remission periods of depression are needed.

In situ fNIRS measurements during cognitive behavioral emotion regulation training in rumination-focused therapy: A randomized-controlled trial

Repetitive negative thinking (RNT), including rumination, plays a key role in various psychopathologies. Although several psychotherapeutic treatments have been developed to reduce RNT, the neural correlates of those specific treatments and of psychotherapy in general are largely unknown. Functional near-infrared spectroscopy (fNIRS) offers the potential to investigate the neural correlates of psychotherapeutic techniques in situ. Therefore, in this study we investigated the efficacy and neural correlates of a fNIRS adapted Mindfulness-based Emotion Regulation Training (MBERT) for the treatment of depressive rumination in 42 subjects with major depressive disorder (MDD) in a cross-over designed randomized controlled trial. Using psychometric measures, subjective ratings and fNIRS, we analyzed in situ changes in depressive symptom severity, ruminative thoughts and cortical activity in the Cognitive Control Network (CCN). Our results show that MBERT is effective in treating depressive symptoms and rumination. On a neural level, we found consistently higher cortical activation during emotion regulation training compared to control trials in the bilateral inferior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC). Furthermore, cortical oxygenation decreased from session to session in the bilateral DLPFC. The relevance of the results for the psychotherapeutic treatment of MDD as well as further necessary investigations are discussed.

Social support and overeating in young women: The role of altering functional network connectivity patterns and negative emotions

Research suggests that social support has a protective effect on emotional health and emotionally induced overeating. Women are especially more sensitive to benefits from social support when facing eating problems. Although it has been demonstrated that social support can affect the neural processes of emotion regulation and reward perception, it is unclear how social support alters synergistic patterns in large-scale brain networks associated with negative emotions and overeating. We used a large sample of young women aged 17-22 years (N = 360) to examine how social support influences the synchrony of five intrinsic networks (executive control network [ECN], default mode network, salience network [SN], basal ganglia network, and precuneus network [PN]) and how these networks influence negative affect and overeating. Additionally, we explored these analyses in another sample of males (N = 136). After statistically controlling for differences in age and head movement, we observed significant associations of higher levels of social support with increased intra- and inter-network functional synchrony, particularly for ECN-centered network connectivity. Subsequent chain-mediated analyses showed that social support predicted overeating through the ECN-SN and ECN-PN network connectivity and negative emotions. However, these results were not found in men. These findings suggest that social support influences the synergistic patterns within and between intrinsic networks related to inhibitory control, emotion salience, self-referential thinking, and reward sensitivity. Furthermore, they reveal that social support and its neural markers may play a key role in young women's emotional health and eating behavior.

Understanding and predicting future relapse in depression from resting state functional connectivity and self-referential processing

BACKGROUND

The recurrent nature of Major Depressive Disorder (MDD) asks for a better understanding of mechanisms underlying relapse. Previously, self-referential processing abnormalities have been linked to vulnerability for relapse. We investigated whether abnormalities in self-referential cognitions and functioning of associated brain-networks persist upon remission and predict relapse.

METHODS

Remitted recurrent MDD patients (n = 48) and never-depressed controls (n = 23) underwent resting-state fMRI scanning at baseline and were additionally assessed for their implicit depressed self-associations and ruminative behaviour. A template-based dual regression approach was used to investigate between-group differences in default mode, cingulo-opercular and frontoparietal network resting-state functional connectivity (RSFC). Additional prediction of relapse status at 18-month follow-up was investigated within patients using both regression analyses and machine learning classifiers.

RESULTS

Remitted patients showed higher rumination, but no implicit depressed self-associations or RSFC abnormalities were observed between patients and controls. Nevertheless, relapse was related to i) baseline RSFC between the ventral default mode network and the precuneus, dorsomedial frontal gyrus, and inferior occipital lobe, ii) implicit self-associations, and iii) uncontrollability of ruminative thinking, when controlled for depressive symptomatology. Moreover, preliminary machine learning classifiers demonstrated that RSFC within the investigated networks predicted relapse on an individual basis.

CONCLUSIONS

Remitted MDD patients seem to be commonly characterized by abnormal rumination, but not by implicit self-associations or abnormalities in relevant brain networks. Nevertheless, relapse was predicted by self-related cognitions and default mode RSFC during remission, suggesting that variations in self-relevant processing play a role in the complex dynamics associated with the vulnerability to developing recurrent depressive episodes.

CLINICAL TRIAL REGISTRATION

Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15.

Task-based attentional and default mode connectivity associated with science and math anxiety profiles among university physics students

PURPOSE

Attentional control theory (ACT) posits that elevated anxiety increases the probability of re-allocating cognitive resources needed to complete a task to processing anxiety-related stimuli. This process impairs processing efficiency and can lead to reduced performance effectiveness. Science, technology, engineering, and math (STEM) students frequently experience anxiety about their coursework, which can interfere with learning and performance and negatively impact student retention and graduation rates. The objective of this study was to extend the ACT framework to investigate the neurobiological associations between science and math anxiety and cognitive performance among 123 physics undergraduate students.

PROCEDURES

Latent profile analysis (LPA) identified four profiles of science and math anxiety among STEM students, including two profiles that represented the majority of the sample (Low Science and Math Anxiety; 59.3% and High Math Anxiety; 21.9%) and two additional profiles that were not well represented (High Science and Math Anxiety; 6.5% and High Science Anxiety; 4.1%). Students underwent a functional magnetic resonance imaging (fMRI) session in which they performed two tasks involving physics cognition: the Force Concept Inventory (FCI) task and the Physics Knowledge (PK) task.

FINDINGS

No significant differences were observed in FCI or PK task performance between High Math Anxiety and Low Science and Math Anxiety students. During the three phases of the FCI task, we found no significant brain connectivity differences during scenario and question presentation, yet we observed significant differences during answer selection within and between the dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). Further, we found significant group differences during the PK task were limited to the DAN, including DAN-VAN and within-DAN connectivity.

CONCLUSIONS

These results highlight the different cognitive processes required for physics conceptual reasoning compared to physics knowledge retrieval, provide new insight into the underlying brain dynamics associated with anxiety and physics cognition, and confirm the relevance of ACT theory for science and math anxiety.

A dorsomedial prefrontal cortex-based dynamic functional connectivity model of rumination

Rumination is a cognitive style characterized by repetitive thoughts about one's negative internal states and is a common symptom of depression. Previous studies have linked trait rumination to alterations in the default mode network, but predictive brain markers of rumination are lacking. Here, we adopt a predictive modeling approach to develop a neuroimaging marker of rumination based on the variance of dynamic resting-state functional connectivity and test it across 5 diverse subclinical and clinical samples (total n = 288). A whole-brain marker based on dynamic connectivity with the dorsomedial prefrontal cortex (dmPFC) emerges as generalizable across the subclinical datasets. A refined marker consisting of the most important features from a virtual lesion analysis further predicts depression scores of adults with major depressive disorder (n = 35). This study highlights the role of the dmPFC in trait rumination and provides a dynamic functional connectivity marker for rumination.

Trait repetitive negative thinking in depression is associated with functional connectivity in negative thinking state rather than resting state

Resting-state functional connectivity (RSFC) has been proposed as a potential indicator of repetitive negative thinking (RNT) in depression. However, identifying the specific functional process associated with RSFC alterations is challenging, and it remains unclear whether alterations in RSFC for depressed individuals are directly related to the RNT process or to individual characteristics distinct from the negative thinking process per se. To investigate the relationship between RSFC alterations and the RNT process in individuals with major depressive disorder (MDD), we compared RSFC with functional connectivity during an induced negative-thinking state (NTFC) in terms of their predictability of RNT traits and associated whole-brain connectivity patterns using connectome-based predictive modeling (CPM) and connectome-wide association (CWA) analyses. Thirty-six MDD participants and twenty-six healthy control participants underwent both resting state and induced negative thinking state fMRI scans. Both RSFC and NTFC distinguished between healthy and depressed individuals with CPM. However, trait RNT in depressed individuals, as measured by the Ruminative Responses Scale-Brooding subscale, was only predictable from NTFC, not from RSFC. CWA analysis revealed that negative thinking in depression was associated with higher functional connectivity between the default mode and executive control regions, which was not observed in RSFC. These findings suggest that RNT in depression involves an active mental process encompassing multiple brain regions across functional networks, which is not represented in the resting state. Although RSFC indicates brain functional alterations in MDD, they may not directly reflect the negative thinking process.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones

Together, data from brain scanners and smartphones have sufficient coverage of biology, psychology, and environment to articulate between-person differences in the interplay within and across biological, psychological, and environmental systems thought to underlie psychopathology. An important next step is to develop frameworks that combine these two modalities in ways that leverage their coverage across layers of human experience to have maximum impact on our understanding and treatment of psychopathology. We review literature published in the last 3 years highlighting how scanners and smartphones have been combined to date, outline and discuss the strengths and weaknesses of existing approaches, and sketch a network science framework heretofore underrepresented in work combining scanners and smartphones that can push forward our understanding of health and disease.

Default Mode Network Modulation by Psychedelics: A Systematic Review

Psychedelics are a unique class of drug that commonly produce vivid hallucinations as well as profound psychological and mystical experiences. A grouping of interconnected brain regions characterized by increased temporal coherence at rest have been termed the Default Mode Network (DMN). The DMN has been the focus of numerous studies assessing its role in self-referencing, mind wandering, and autobiographical memories. Altered connectivity in the DMN has been associated with a range of neuropsychiatric conditions such as depression, anxiety, post-traumatic stress disorder, attention deficit hyperactive disorder, schizophrenia, and obsessive-compulsive disorder. To date, several studies have investigated how psychedelics modulate this network, but no comprehensive review, to our knowledge, has critically evaluated how major classical psychedelic agents-lysergic acid diethylamide, psilocybin, and ayahuasca-modulate the DMN. Here we present a systematic review of the knowledge base. Across psychedelics there is consistent acute disruption in resting state connectivity within the DMN and increased functional connectivity between canonical resting-state networks. Various models have been proposed to explain the cognitive mechanisms of psychedelics, and in one model DMN modulation is a central axiom. Although the DMN is consistently implicated in psychedelic studies, it is unclear how central the DMN is to the therapeutic potential of classical psychedelic agents. This article aims to provide the field with a comprehensive overview that can propel future research in such a way as to elucidate the neurocognitive mechanisms of psychedelics.

Decreased functional connectivity in patients with major depressive disorder and a history of childhood traumatization through experiences of abuse

BACKGROUND

Childhood trauma (CT) increases vulnerability for the development of major depressive disorder (MDD). Alterations in resting-state functional connectivity (RSFC) have frequently been reported for MDD. These alterations may be much more prominent in depressive patients with a history of CT. The present study aims to compare RSFC in different brain networks of patients with MDD and CT (MDD+CT) vs. MDD and no CT compared to healthy controls.

METHODS

45 patients (22 with CT) were compared to 23 age-and-gender-matched healthy control subjects. Demographic parameters, severity of MDD, severity of CT and comorbid anxiety disorders were assessed. For assessment of RSFC alterations, a seed-based approach within five well-established RSFC networks was used.

RESULTS

CT in MDD patients predicts severity of comorbid anxiety. A significant decrease in in-between network RSFC-values of MDD patients compared to controls was found in the network pairs of default mode network (DMN) - dorsal attention network (DAN), ventral attention network (VAN) - DMN and DAN - affective network (AN). MDD+CT patients presented more aberrant RSFC than MDD-CT patients. MDD scores predicted the decrease in RSFC for MDD patients. Higher Childhood Trauma Questionnaire (CTQ) scores are linked to reduced functional connectivity (FC) between DMN - DAN.

CONCLUSIONS

Our study shows reduced RSFC in MDD patients for DMN - DAN, VAN - DMN, DAN - AN and MDD+CT patients presented more aberrant RSFC so that we suspect CT to be a considerable factor in the etiology of MDD. Through dysregulated neural circuits, CT is likely to contribute to a distinct MDD pathophysiology.

Neural signal variability relates to maladaptive rumination in depression

Rumination is a common feature of depression and predicts the onset and maintenance of depressive episodes. Maladaptive and adaptive subtypes of rumination contribute to distinct outcomes, with brooding worsening negative mood and reflection related to fewer depression symptoms in healthy populations. Neuroimaging studies have implicated several cortical midline and lateral prefrontal brain regions in rumination. Recent research indicates that blood oxygen level-dependent (BOLD) signal variability may be a novel predictor of cognitive flexibility. However, no prior studies have investigated whether brooding and reflection are associated with distinct patterns of BOLD signal variability in depression. We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depression. We examined differences in BOLD signal variability (BOLD_SD) related to rumination subtypes for the following regions of interest previously implicated in rumination: amygdala, medial prefrontal, anterior cingulate, posterior cingulate, and dorsolateral prefrontal cortices (dlPFC). Rumination subtype was associated with BOLD_SD in the dlPFC, with greater levels of brooding associated with lower BOLD_SD in the dlPFC, even after controlling for depression severity. Depression history was related to BOLD_SD in the dlPFC, with reduced BOLD_SD in those with current depression versus no history of depression. These findings provide a novel demonstration of the neural circuitry associated with maladaptive rumination in depression and implicate decreased prefrontal neural signal variability in the pathophysiology of depression.

Resting state brain dynamics: Associations with childhood sexual abuse and major depressive disorder

Early life stress (ELS) and major depressive disorder (MDD) share neural network abnormalities. However, it is unclear how ELS and MDD may separately and/or jointly relate to brain networks, and whether neural differences exist between depressed individuals with vs without ELS. Moreover, prior work evaluated static versus dynamic network properties, a critical gap considering brain networks show changes in coordinated activity over time. Seventy-one unmedicated females with and without childhood sexual abuse (CSA) histories and/or MDD completed a resting state scan and a stress task in which cortisol and affective ratings were collected. Recurring functional network co-activation patterns (CAPs) were examined and time in CAP (number of times each CAP is expressed) and transition frequencies (transitioning between different CAPs) were computed. The effects of MDD and CSA on CAP metrics were examined and CAP metrics were correlated with depression and stress-related variables. Results showed that MDD, but not CSA, related to CAP metrics. Specifically, individuals with MDD (N = 35) relative to HCs (N = 36), spent more time in a posterior default mode (DMN)-frontoparietal network (FPN) CAP and transitioned more frequently between posterior DMN-FPN and prototypical DMN CAPs. Across groups, more time spent in a posterior DMN-FPN CAP and greater DMN-FPN and prototypical DMN CAP transition frequencies were linked to higher rumination. Imbalances between the DMN and the FPN appear central to MDD and might contribute to MDD-related cognitive dysfunction, including rumination. Unexpectedly, CSA did not modulate such dysfunctions, a finding that needs to be replicated by future studies with larger sample sizes.

Neural correlates of repetitive negative thinking: Dimensional evidence across the psychopathological continuum

Repetitive negative thinking (RNT) captures an important transdiagnostic factor that predisposes to a maladaptive stress response and contributes to diverse psychiatric disorders. Although RNT can best be seen as a continuous symptom dimension that cuts across boundaries from health to various psychiatric disorders, the neural mechanisms underlying RNT have almost exclusively been studied in health and stress-related disorders, such as depression and anxiety disorders. We set out to study RNT from a large-scale brain network perspective in a diverse population consisting of healthy subjects and patients with a broader range of psychiatric disorders. We studied 46 healthy subjects along with 153 patients with a stress-related and/or neurodevelopmental disorder. We focused on three networks, that are associated with RNT and diverse psychiatric disorders: the salience network, default mode network (DMN) and frontoparietal network (FPN). We investigated the relationship of RNT with both network connectivity strength at rest and with the stress-induced changes in connectivity. Across our whole sample, the level of RNT was positively associated with the connectivity strength of the left FPN at rest, but negatively associated with stress-induced changes in DMN connectivity. These findings may reflect an upregulation of the FPN in an attempt to divert attention away from RNT, while the DMN result may reflect a less flexible adaptation to stress, related to RNT. Additionally, we discuss how our findings fit into the non-invasive neurostimulation literature. Taken together, our results provide initial insight in the neural mechanisms of RNT across the spectrum from health to diverse psychiatric disorders.

Intermittent brain network reconfigurations and the resistance to social media influence

Since its development, social media has grown as a source of information and has a significant impact on opinion formation. Individuals interact with others and content via social media platforms in a variety of ways, but it remains unclear how decision-making and associated neural processes are impacted by the online sharing of informational content, from factual to fabricated. Here, we use EEG to estimate dynamic reconfigurations of brain networks and probe the neural changes underlying opinion change (or formation) within individuals interacting with a simulated social media platform. Our findings indicate that the individuals who changed their opinions are characterized by less frequent network reconfigurations while those who did not change their opinions tend to have more flexible brain networks with frequent reconfigurations. The nature of these frequent network configurations suggests a fundamentally different thought process between intervals in which individuals are easily influenced by social media and those in which they are not. We also show that these reconfigurations are distinct to the brain dynamics during an in-person discussion with strangers on the same content. Together, these findings suggest that brain network reconfigurations may not only be diagnostic to the informational context but also the underlying opinion formation.

Psychiatric Comorbidity Among Eating Disorders and Obsessive-Compulsive Disorder and Underlying Shared Mechanisms and Features: An Updated Review

Eating disorders (EDs) are highly comorbid with obsessive-compulsive disorder (OCD), with comorbidity rates as high as 41%. In the current review, we summarize the literature regarding the prevalence of ED-OCD comorbidity. We also identify and review the literature assessing shared features (i.e., shared characteristics or symptoms) and mechanisms (i.e., variables that may explain ED or OCD symptoms) of EDs and OCD. Potential shared features of EDs and OCD include age of onset, course of illness, obsessions, compulsions and ritualistic behaviors, and thought action fusion. Shared mechanisms that may explain ED-OCD comorbidity include genetic and neurobiological mechanisms, anxiety and fear, repetitive negative thinking, perfectionism, intolerance of uncertainty, distress tolerance, and impulsivity. Based on these shared features and mechanisms, a theoretical conceptualization of ED and OCD comorbidity is developed, and outline considerations for assessment, differential diagnosis, treatment, and future research regarding ED-OCD comorbidity are described.

Cognitive behavioral therapy may rehabilitate abnormally functional communication pattern among the triple-network in major depressive disorder: A follow-up study

BACKGROUND

Cognitive behavioral therapy (CBT) is an established treatment for Major Depressive Disorder (MDD). MDD is characterized by imbalanced communication patterns among three networks: the central executive network (CEN), the default mode network (DMN) and the salience network (SN). The effect of CBT in restoring communications among these networks in MDD is unknown.

METHODS

Thirty-three patients with MDD and 27 healthy controls (HC) participated in the study. Patients were treated with CBT. Resting-state functional magnetic resonance imaging (rs-fMRI) data were obtained in patients at three stages (T0: before treatment; T1: after 6 weeks CBT; T2: after 28 weeks CBT) and in HC (only T0). Both independent component analysis (ICA) and granger causality analysis (GCA) were used to explore dynamic causal communication patterns among the three networks (CEN, DMN, SN) over a course of CBT treatment.

RESULTS

In the HC group, the SN had an inhibitory causal effect on CEN; the CEN and DMN had an excitatory causal effect on the SN. The SN had an inhibitory causal effect on the CEN and the DMN; only the DMN had an excitatory causal effect on the SN in the MDD patients at the T0 stage. As the CBT treatment went on for MDD patients, the CEN restored excitatory causal effect on the SN, and the SN lost inhibitory effect on the DMN. This result mimicked the one found in the HC group. Four regions, left ventromedial prefrontal cortex (lvmPFC), posterior cingulate gyrus (PCC), right inferior parietal lobule (rIPL) and right insula, were implicated in mediating network communications.

LIMITATIONS

The findings should be considered preliminary given the small sample sizes, and assessed only one stage in HC subjects.

CONCLUSION

CBT may enhance the regulatory function of the SN, and rehabilitate the imbalanced brain network communication mode in the MDD. PCC, lvmPFC and rIPL may all be potential targets of CBT.

C-reactive protein is related to a distinct set of alterations in resting-state functional connectivity contributing to a differential pathophysiology of major depressive disorder

BACKGROUND

Several studies in major depressive disorder (MDD) have found inflammation, especially C-reactive protein (CRP), to be consistently associated with MDD and network dysfunction. The aim was to investigate whether CRP is linked to a distinct set of resting-state functional connectivity (RSFC) alterations.

METHODS

For this reason, we investigated the effects of diagnosis and elevated blood plasma CRP levels on the RSFC in 63 participants (40 females, mean age 31.4 years) of which were 27 patients with a primary diagnosis of MDD and 36 healthy control-subjects (HC), utilizing a seed-based approach within five well-established RSFC networks obtained using fMRI.

RESULTS

Of the ten network pairs examined, five showed increased between-network RSFC-values unambiguously connected either to a diagnosis of MDD or elevated CRP levels. For elevated CRP levels, increased RSFC between DMN and AN was found. Patients showed increased RSFC within DMN areas and between the DMN and ECN and VAN, ECN and AN and AN and DAN.

CONCLUSIONS

The results of this study show dysregulated neural circuits specifically connected to elevated plasma CRP levels and independent of other alterations of RSFC in MDD. This dysfunction in neural circuits might in turn result in a certain immune-inflammatory subtype of MDD.

Multivariate patterns of brain-behavior associations across the adult lifespan

The nature of brain-behavior covariations with increasing age is poorly understood. In the current study, we used a multivariate approach to investigate the covariation between behavioral-health variables and brain features across adulthood. We recruited healthy adults aged 20–73 years-old (29 younger, mean age = 25.6 years; 30 older, mean age = 62.5 years), and collected structural and functional MRI (s/fMRI) during a resting-state and three tasks. From the sMRI, we extracted cortical thickness and subcortical volumes; from the fMRI, we extracted activation peaks and functional network connectivity (FNC) for each task. We conducted canonical correlation analyses between behavioral-health variables and the sMRI, or the fMRI variables, across all participants. We found significant covariations for both types of neuroimaging phenotypes (ps = 0.0004) across all individuals, with cognitive capacity and age being the largest opposite contributors. We further identified different variables contributing to the models across phenotypes and age groups. Particularly, we found behavior was associated with different neuroimaging patterns between the younger and older groups. Higher cognitive capacity was supported by activation and FNC within the executive networks in the younger adults, while it was supported by the visual networks’ FNC in the older adults. This study highlights how the brain-behavior covariations vary across adulthood and provides further support that cognitive performance relies on regional recruitment that differs between older and younger individuals.

Neuroimaging Correlates of Treatment Response with Psychedelics in Major Depressive Disorder: A Systematic Review

Preliminary evidence supports the use of psychedelics for major depressive disorder (MDD). However, less attention has been given to the neural mechanisms behind their effects. We conducted a systematic review examining the neuroimaging correlates of antidepressant response following psychedelic interventions for MDD. Through MEDLINE, Embase, and APA PsycINFO, 187 records were identified and 42 articles were screened. Six published studies and one conference abstract were included. Five ongoing trials were included from subjective outcomesTrials.gov. Our search covered several psychedelics, though included studies were specific to psilocybin, ayahuasca, and lysergic acid diethylamide. Three psilocybin studies noted amygdala activity and functional connectivity (FC) alterations that correlated with treatment response. Two psilocybin studies reported that FC changes in the medial and ventromedial prefrontal cortices correlated with treatment response. Two trials from a single study reported global decreases in brain network modularity which correlated with antidepressant response. One ayahuasca study reported increased activity in the limbic regions following treatment. Preliminary evidence suggests that the default mode and limbic networks may be a target for future research on the neural mechanisms of psychedelics. More data is required to corroborate these initial findings as the evidence summarized in this review is based on four datasets.

Stronger functional network connectivity and social support buffer against negative affect during the COVID-19 outbreak and after the pandemic peak

Health and financial uncertainties, as well as enforced social distancing, during the COVID-19 pandemic have adversely affected the mental health of people. These impacts are expected to continue even after the pandemic, particularly for those who lack support from family and friends. The salience network (SN), default mode network (DMN), and frontoparietal network (FPN) function in an interconnected manner to support information processing and emotional regulation processes in stressful contexts. In this study, we examined whether functional connectivity of the SN, DMN, and FPN, measured using resting-state functional magnetic resonance imaging before the pandemic, is a neurobiological marker of negative affect (NA) during the COVID-19 pandemic and after its peak in a large sample (N = 496, 360 females); the moderating role of social support in the brain-NA association was also investigated. We found that participants reported an increase in NA during the pandemic compared to before the pandemic, and the NA did not decrease, even after the peak period. People with higher connectivity within the SN and between the SN and the other two networks reported less NA during and after the COVID-19 outbreak peak, and the buffer effect was stronger if their social support was greater. These findings suggest that the functional networks that are responsible for affective processing and executive functioning, as well as the social support from family and friends, play an important role in protecting against NA under stressful and uncontrollable situations.

No associations in preregistered study of youth depression and functional connectivity of fronto-parietal and default mode networks

Adolescence is characterized by vulnerability to the onset of major depressive disorder (MDD). The goal of this preregistered study was to assess neural correlates of depression symptoms in young adolescents, both cross-sectionally and longitudinally. The default mode network (DMN) is believed to support internal attention towards self-referential thoughts, while the fronto-parietal network (FPN) is theorized to support cognitive control and regulation of attention. As MDD diagnosis has been associated with heightened connectivity within DMN regions and diminished connectivity within FPN regions relative to healthy controls, our study builds upon group-difference analyses by using dimensional measures of depression severity. Our preregistered hypotheses were that within-DMN functional connectivity would be positively associated with concurrent depression severity, while within-FPN functional connectivity would be negatively associated with concurrent depression severity. Preregistered analyses also examined between DMN-FPN connectivity as an alternative predictor variable, and assessed the longitudinal associations between all three functional connectivity measures and change in depression severity over three subsequent waves. Multiple regression models tested cross-sectional analyses and hierarchical linear models tested longitudinal analyses. One hundred and twenty-four youth completed a resting state functional MRI. Their depression severity was assessed at the time of the scan and at three follow-up sessions. None of the predictor variables were associated with concurrent depression severity, nor with the slope of depression symptom trajectories in longitudinal analyses. These negative results add to extant cross-sectional studies, and may inform future investigations of brain correlates of depression psychopathology in youth.

Brain parcellation selection: An overlooked decision point with meaningful effects on individual differences in resting-state functional connectivity

Over the past decade extensive research has examined the segregation of the human brain into large-scale functional networks. The resulting network maps, i.e. parcellations, are now commonly used for the a priori identification of functional networks. However, the use of these parcellations, particularly in developmental and clinical samples, hinges on four fundamental assumptions: (1) the various parcellations are equally able to recover the networks of interest; (2) adult-derived parcellations well represent the networks in children’s brains; (3) network properties, such as within-network connectivity, are reliably measured across parcellations; and (4) parcellation selection does not impact the results with regard to individual differences in given network properties. In the present study we examined these assumptions using eight common parcellation schemes in two independent developmental samples. We found that the parcellations are equally able to capture networks of interest in both children and adults. However, networks bearing the same name across parcellations (e.g., default network) do not produce reliable within-network measures of functional connectivity. Critically, parcellation selection significantly impacted the magnitude of associations of functional connectivity with age, poverty, and cognitive ability, producing meaningful differences in interpretation of individual differences in functional connectivity based on parcellation choice. Our findings suggest that work employing parcellations may benefit from the use of multiple schemes to confirm the robustness and generalizability of results. Furthermore, researchers looking to gain insight into functional networks may benefit from employing more nuanced network identification approaches such as using densely-sampled data to produce individual-derived network parcellations. A transition towards precision neuroscience will provide new avenues in the characterization of functional brain organization across development and within clinical populations.

Frontoinsular cortical microstructure is linked to life satisfaction in young adulthood

Life satisfaction is a component of subjective well-being that reflects a global judgement of the quality of life according to an individual's own needs and expectations. As a psychological construct, it has attracted attention due to its relationship to mental health, resilience to stress, and other factors. Neuroimaging studies have identified neurobiological correlates of life satisfaction; however, they are limited to functional connectivity and gray matter morphometry. We explored features of gray matter microstructure obtained through compartmental modeling of multi-shell diffusion MRI data, and we examined cortical microstructure in frontoinsular cortex in a cohort of 807 typical young adults scanned as part of the Human Connectome Project. Our experiments identified the orientation dispersion index (ODI), and analogously fractional anisotropy (FA), of frontoinsular cortex as a robust set of anatomically-specific lateralized diffusion MRI microstructure features that are linked to life satisfaction, independent of other demographic, socioeconomic, and behavioral factors. We further validated our findings in a secondary test-retest dataset and found high reliability of our imaging metrics and reproducibility of outcomes. In our analysis of twin and non-twin siblings, we found basic microstructure in frontoinsular cortex to be strongly genetically determined. We also found a more moderate but still very significant genetic role in determining microstructure as it relates to life satisfaction in frontoinsular cortex. Our findings suggest a potential linkage between well-being and microscopic features of frontoinsular cortex, which may reflect cellular morphology and architecture and may more broadly implicate the integrity of the homeostatic processing performed by frontoinsular cortex as an important component of an individual's judgements of life satisfaction.

Cognitive behavioral based group psychotherapy focusing on repetitive negative thinking: Decreased uncontrollability of rumination is related to brain perfusion increases in the left dorsolateral prefrontal cortex

Repetitive negative thinking (RNT) is a core process underlying various psychiatric disorders. 'Uncontrollability of rumination (UOR)' is one the most maladaptive factors of rumination, but little is known on how cognitive behavioral focused RNT psychotherapy may alter brain activity. In a subsample of 47 patients suffering from RNT who also underwent brain imaging (registered RCT trial NCT01983033), we evaluated the effect of cognitive behavioral based group psychotherapy (CBGP) (n = 25) as compared to a delayed treatment control group (DTCG) (n = 22) on frontolimbic brain perfusion with a focus on UOR. This RNT construct was measured using the subscale 'uncontrollability' of the Dutch version of the Rumination on Sadness Scale (LARSS-U). Brain perfusion was assessed with arterial spin labeling (ASL)-fMRI. LARSS-U scale scores significantly decreased in the CBGP cohort whereas no significant changes emerged in the DTCG group. Compared to the DTCG, this decrease on UOR in the CBGP group was related to significant perfusion increases in the left (dorsolateral) prefrontal cortex, part of the executive network. Besides the fact that CBGP significantly reduced RNT, this attenuation of uncontrollable ruminative thoughts was related to brain perfusion increases areas documented to be involved in the top down control of adaptive emotion regulation and the inhibition of ruminative processes.

Temporal networks of tobacco withdrawal symptoms during smoking cessation treatment

A recently developed network perspective on tobacco withdrawal posits that withdrawal symptoms causally influence one another across time, rather than simply being indicators of a latent syndrome. Evidence supporting a network perspective would shift the focus of tobacco withdrawal research and intervention toward studying and treating individual withdrawal symptoms and intersymptom associations. Here we construct and examine temporal tobacco withdrawal networks that describe the interplay among withdrawal symptoms across time using experience-sampling data from 1,210 participants (58.35% female, 86.24% White) undergoing smoking cessation treatment. We also construct person-specific withdrawal networks and capture individual differences in the extent to which withdrawal symptom networks promote the spread of symptom activity through the network across time using impulse response analysis. Results indicate substantial moment-to-moment associations among withdrawal symptoms, substantial between-person differences in withdrawal network structure, and reductions in the interplay among withdrawal symptoms during combination smoking cessation treatment. Overall, findings suggest the utility of a network perspective and also highlight challenges associated with the network approach stemming from vast between-person differences in symptom networks. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Does Psychedelic Therapy Have a Transdiagnostic Action and Prophylactic Potential?

Addressing global mental health is a major 21st-century challenge. Current treatments have recognized limitations; in this context, new ones that are prophylactic and effective across diagnostic boundaries would represent a major advance. The view that there exists a core of transdiagnostic overlap between psychiatric disorders has re-emerged in recent years, and evidence that psychedelic therapy holds promise for a range of psychiatric disorders supports the position that it may be transdiagnostically effective. Here, we propose that psychedelic therapy's core, transdiagnostically relevant action lies in its ability to increase neuronal and mental plasticity, thus enhancing the potential for change, which we consider to be a key to its therapeutic benefits. Moreover, we suggest that enhanced plasticity via psychedelics, combined with a psychotherapeutic approach, can aid healthy adaptability and resilience, which are protective factors for long-term well-being. We present candidate neurological and psychological markers of this plasticity and link them with a predictive processing model of the action of psychedelics. We propose that a model of psychedelic-induced plasticity combined with an adequate therapeutic context has prophylactic and transdiagnostic potential, implying that it could have a broad, positive impact on public health.

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations

Multilayer network models have been proposed as an effective means of capturing the dynamic configuration of distributed neural circuits and quantitatively describing how communities vary over time. Beyond general insights into brain function, a growing number of studies have begun to employ these methods for the study of individua differences. However, test–retest reliabilities for multilayer network measures have yet to be fully quantified or optimized, potentially limiting their utility for individual difference studies. Here, we systematically evaluated the impact of multilayer community detection algorithms, selection of network parameters, scan duration, and task condition on test–retest reliabilities of multilayer network measures (i.e., flexibility, integration, and recruitment). A key finding was that the default method used for community detection by the popular generalized Louvain algorithm can generate erroneous results. Although available, an updated algorithm addressing this issue is yet to be broadly adopted in the neuroimaging literature. Beyond the algorithm, the present work identified parameter selection as a key determinant of test–retest reliability; however, optimization of these parameters and expected reliabilities appeared to be dataset-specific. Once parameters were optimized, consistent with findings from the static functional connectivity literature, scan duration was a much stronger determinant of reliability than scan condition. When the parameters were optimized and scan duration was sufficient, both passive (i.e., resting state, Inscapes, and movie) and active (i.e., flanker) tasks were reliable, although reliability in the movie watching condition was significantly higher than in the other three tasks. The minimal data requirement for achieving reliable measures for the movie watching condition was 20 min, and 30 min for the other three tasks. Our results caution the field against the use of default parameters without optimization based on the specific datasets to be employed – a process likely to be limited for most due to the lack of test–retest samples to enable parameter optimization.

Neural correlates of mindful emotion regulation in high and low ruminators

Depressive rumination is considered a prominent risk factor for the occurrence, severity, and duration of depressive episodes. A variety of treatment options have been developed to treat depressive rumination of which mindfulness based programs are especially promising. In the current study, we investigated the neural underpinnings of a short mindfulness intervention and mindful emotion regulation in high and low trait ruminators in an ecologically valid environment using functional near-infrared spectroscopy (fNIRS). Participants were randomly assigned to a mindfulness instruction (MT) group or an instructed thinking (IT) group. Participants in the MT group were trained to either focus their attention mindfully on their breath or their emotions, while the IT group focused their attention on the past or future. Afterwards, all participants underwent an emotion regulation paradigm in which they either watched negative or neutral movie clips. During both paradigms cortical hemodynamic changes were assessed by means of fNIRS. Participants in the MT group showed lower activity in the cognitive control network (CCN) during the focus on breath condition in comparison to the focus on emotion condition. Additionally, oxygenated hemoglobin in the MT group tended to be lower than in the IT group. Further, self-reports of emotional distress during the instruction paradigm were reduced in the MT group. During the emotion regulation paradigm, we observed reduced emotional reactivity in terms of emotional distress and avoidance in the MT group in comparison to the IT group. Furthermore, on a neural level, we observed higher CCN activity in the MT group in comparison to the IT group. We did not find any effect of rumination, neither on the intervention nor on the emotion regulation task. The results of this pilot study are discussed in light of the present literature on the neural correlates of mindfulness based interventions in rumination and emphasize the use of fNIRS to track neural changes in situ over the course of therapy.

Dysregulation of oxytocin and dopamine in the corticostriatal circuitry in bipolar II disorder

The oxytocin (OXT) and dopamine systems synergistically facilitate striatal reactivity. Abnormal striatal activation has repeatedly been observed in patients with bipolar disorder (BD); however, such abnormality remains unclear in BD II. Here we aimed to investigate whether the corticostriatal connectivity was altered and the possible relationships among corticostriatal connectivity, OXT, and dopamine systems in BD II. Twenty-five BD II patients, as defined by the DSM-V, and 29 healthy controls (HC) were enrolled in this study. Plasma OXT was measured and striatal dopamine transporter (DAT) availability was assessed using [^99mTc]TRODAT-1 single-photon emission computed tomography (SPECT). Brain network functional connectivity (FC) was measured during the resting-state using functional magnetic resonance imaging, and the dorsal caudate (DC) was selected as the seed region. The results showed that the OXT level was significantly lower in the BD II patients, while the striatal DAT availability was not significantly different between the BD II and HC groups. The BD II patients exhibited significantly lower FC between the DC and the executive control network (dorsolateral prefrontal, anterior cingulate cortex, and posterior parietal cortex) as compared with the HC. Only observed in HC, the DC-posterior parietal cortex FC was negatively correlated with the OXT level and striatal DAT availability. Our findings in the HC support a model in which the OXT and dopamine systems act in tandem to regulate corticostriatal circuitry, while the synergistic interaction was perturbed in BD II. Taken together, these results implied a maladaptive neuroplasticity in BD II.

Restrained Eating and Vegan, Vegetarian and Omnivore Dietary Intakes

There are a significant number of studies on cognitive restraint among individuals with varying dietary patterns. Although most research has found that vegetarians report higher levels of cognitive restraint compared to non-vegetarians, many studies have contributed inconsistent results. The aim of the current study, therefore, was to assess any differences between groups with varying dietary patterns on cognitive restraint and other disordered eating pattern. The second objective was to examine determinants of cognitive restraint in individuals adhering to a vegan diet, a vegetarian diet and an omnivore diet. Two-hundred and fifty-four participants with varying dietary patterns completed the Three-Factor Eating Questionnaire, the Perseverative Thinking Questionnaire and the Eating Habits Questionnaire. Our results indicated that both vegetarian and vegan groups showed a significantly lower cognitive restraint, lower emotional eating and lower uncontrolled eating than those who followed an omnivorous diet. In addition, these both groups following a plant-based diet have shown more cognitions, behaviours and feelings related to an extreme focus on healthy eating (orthorexia nervosa) than group following an omnivorous diet. There were no significant differences between the groups in perseverative thinking. Core characteristics of repetitive negative thinking was a significant predictor of cognitive restraint in vegans. Feeling positively about healthy eating predicted cognitive restraint among vegetarians. Problems associated with healthy eating and feeling positively about healthy eating predicted cognitive restraint among individuals following an omnivorous diet. Knowledge of predictors of cognitive restraint may serve as a psychological intervention goal or psychoeducation goal among individuals with varying dietary patterns.

Differences in the modulation of functional connectivity by self-talk tasks between people with low and high life satisfaction

Self-respect is a practical way to promote life satisfaction through gratifying basic psychological needs, whereas self-criticism is associated with life dissatisfaction. The goal of the present study was to investigate the effect of two positive and negative self-talks on the functional connectome with respect to life satisfaction and its relationships with basic psychological needs. Forty-eight individuals with low life satisfaction (LLS, n ​= ​24) and with high life satisfaction (HLS, n ​= ​24) were scanned using functional magnetic resonance imaging at a baseline state and during and after self-respect or self-criticism tasks. Functional connectivity analysis was conducted to identify the modulatory effects of the tasks on the self-referential, default mode, and reward-motivation networks. We found that self-respect changed only the connection between the posterior cingulate cortex (PCC) and frontoparietal network, whereas self-criticism changed almost all of the connections examined. The group x condition interaction effect of self-respect was identified only in connection between the PCC and left ventrolateral prefrontal cortex, while that of self-criticism was observed in various connections based on the ventromedial prefrontal cortex and nucleus accumbens. In respect to basic psychological needs, functional connectivity after self-criticism was significant in predicting the needs of autonomy and relatedness only in the LLS group, whereas functional connectivity after self-respect could predict the needs of autonomy and competence only in the HLS group. Overall, self-criticism produces more noticeable negative changes in the brain than the positive changes of self-respect. Individuals with low life satisfaction may be more vulnerable to be negatively affected not only by self-criticism but also self-respect than individuals with high life satisfaction. The satisfaction of basic psychological needs can play a mediating role in the effects of self-talk tasks differently concerning life satisfaction.

Linking inhibition and anxiety symptoms following sleep restriction: The moderating role of prior sleep efficiency

Although sleep loss increases state anxiety, the effects of partial sleep restriction on specific anxiety symptoms and mechanisms that may influence this relation remain unknown. It is also unknown whether prior sleep buffers the impact of sleep restriction on anxiety symptoms. Thus, the present study examined the relations between inhibition and repetitive negative thinking (RNT), obsessions, and other OCD symptoms following sleep restriction and the moderating role of prior night's sleep efficiency. Healthy sleeping adults (n = 73) completed measures of inhibition, anxiety symptoms, and sleep before and after one night of sleep restriction (4 h between 4:00am and 8:00am). Results indicate significant associations between decreased post-sleep restriction inhibition and increased post-sleep restriction RNT and obsessions. Prior night's subjective and objective sleep efficiency significantly moderated these relations, such that the highest post-sleep restriction anxiety symptoms were reported by those with the lowest post-sleep restriction inhibition and the lowest pre-sleep restriction sleep efficiency. These findings suggest decreased inhibition may be one mechanism by which sleep loss affects anxiety, and those with worse sleep prior to acute sleep loss may be particularly vulnerable. The implications for the prevention and treatment of anxiety-related disorders characterized by intrusive cognition are discussed.

Data-Driven Approaches to Neuroimaging Analysis to Enhance Psychiatric Diagnosis and Therapy

Combining advanced neuroimaging with novel computational methods in network science and machine learning has led to increasingly meaningful descriptions of structure and function in both the normal and the abnormal brain, thereby contributing significantly to our understanding of psychiatric disorders as circuit dysfunctions. Despite its marked potential for psychiatric care, this approach has not yet extended beyond the research setting to any clinically useful applications. Here we review current developments in the study of neuroimaging data using network models and machine learning methods, with a focus on their promise in offering a framework for clinical translation. We discuss 3 potential contributions of these methods to psychiatric care: 1) a better understanding of psychopathology beyond current diagnostic boundaries; 2) individualized prediction of treatment response and prognosis; and 3) formal theories to guide the development of novel interventions. Finally, we highlight current obstacles and sketch a forward-looking perspective of how the application of machine learning and network modeling methods should proceed to accelerate their potential transformation of clinically useful tools.