The ability to extinguish a maladaptive conditioned fear response is crucial for healthy emotional processing and resiliency to aversive experiences. Therefore, enhancing fear extinction learning has immense potential emotional and health benefits. Mindfulness training enhances both fear conditioning and recall of extinguished fear; however, its effects on fear extinction learning are unknown. Here we investigated the impact of mindfulness training on brain mechanisms associated with fear-extinction learning, compared to an exercise-based program.

We investigated BOLD activations in response to a previously learned fear-inducing cue during an extinction paradigm, before and after an 8-week mindfulness-based stress reduction program (MBSR, n = 49) or exercise-based stress management education program (n = 27).

The groups exhibited similar reductions in stress, but the MBSR group was uniquely associated with enhanced activation of salience network nodes and increased hippocampal engagement.

Our results suggest that mindfulness training increases attention to anticipatory aversive stimuli, which in turn facilitates decreased aversive subjective responses and enhanced reappraisal of the memory.

Cognitive-behavior therapy (CBT) is a well-established first-line intervention for anxiety-related disorders, including specific phobia, social anxiety disorder, panic disorder/agoraphobia, generalized anxiety disorder, obsessive-compulsive disorder, and posttraumatic stress disorder. Several neural predictors of CBT outcome for anxiety-related disorders have been proposed, but previous results are inconsistent.

We conducted a systematic review and meta-analysis of task-based functional magnetic resonance imaging (fMRI) studies investigating whole-brain predictors of CBT outcome in anxiety-related disorders (17 studies, n = 442).

Across different tasks, we observed that brain response in a network of regions involved in salience and interoception processing, encompassing fronto-insular (the right inferior frontal gyrus-anterior insular cortex) and fronto-limbic (the dorsomedial prefrontal cortex-dorsal anterior cingulate cortex) cortices was strongly associated with a positive CBT outcome.

Our results suggest that there are robust neural predictors of CBT outcome in anxiety-related disorders that may eventually lead (probably in combination with other data) to develop personalized approaches for the treatment of these mental disorders.

Suicide is the second-leading cause of death in youth. Understanding the neural correlates of suicide ideation (SI) in children is crucial to ongoing efforts to understand and prevent youth suicide. This study characterized key neural networks during rest and emotion task conditions in an epidemiologically informed sample of children who report current, past, or no SI.

Data are from the adolescent brain cognitive development study, including 8248 children (ages 9–10; mean age = 119.2 months; 49.2% female) recruited from the community. Resting-state functional connectivity (RSFC) and activation to emotional stimuli in the salience (SN) and default mode (DMN) networks were measured through fMRI. Self-reported SI and clinical profiles were gathered. We examined the replicability of our model results through repeated sub-sample reliability analyses.

Children with current SI (2.0%), compared to those without any past SI, showed lower DMN RSFC (B = −0.267, p < 0.001) and lower DMN activation in response to negative as compared to neutral faces (B = −0.204, p = 0.010). These results were robust to the effects of MDD, ADHD, and medication use. Sub-sample analysis further supported the robustness of these results. We did not find support for differences in SN RSFC or in SN activation to positive or negative stimuli for children with or without SI.

Results from a large brain imaging study using robust statistical approaches suggest aberrant DMN functioning in children with current suicide ideation. Findings suggest potential mechanisms that may be targeted in suicide prevention efforts.

Understanding the neurobiological underpinnings of childhood maltreatment is vital given consistent links with poor mental health. Dimensional models of adversity purport that different types of adversity likely have distinct neurobiological consequences. Adolescence is a key developmental period, during which deviations from normative neurodevelopment may have particular relevance for mental health. However, longitudinal work examining links between different forms of maltreatment, neurodevelopment, and mental health is limited.

In the present study, we explored associations between abuse, neglect, and longitudinal development of within-network functional connectivity of the salience (SN), default mode (DMN), and executive control network in 142 community residing adolescents. Resting-state fMRI data were acquired at age 16 (T1; M = 16.46 years, s.d. = 0.52, 66F) and 19 (T2; mean follow-up period: 2.35 years). Mental health data were also collected at T1 and T2. Childhood maltreatment history was assessed prior to T1.

Abuse and neglect were both found to be associated with increases in within-SN functional connectivity from age 16 to 19. Further, there were sex differences in the association between neglect and changes in within-DMN connectivity. Finally, increases in within-SN connectivity were found to mediate the association between abuse/neglect and lower problematic substance use and higher depressive symptoms at age 19.

Our findings suggest that childhood maltreatment is associated with altered neurodevelopmental trajectories, and that changes in salience processing may be linked with risk and resilience for the development of depression and substance use problems during adolescence, respectively. Further work is needed to understand the distinct neurodevelopmental and mental health outcomes of abuse and neglect.

Characterizing neuroanatomical markers of different stages of schizophrenia (SZ) to assess of how the disorder develops is extremely important for the clinical practice. It still remains uncertain how abnormalities are formed as SZ progresses.

We reviewed and analyzed 113 voxel based morphometry studies on people at risk of or with schizophrenia to assess GM alterations at different stages of the disorder and to functionally characterize these GM variations.

We performed a meta-analysis of voxel-based morphometry studies of genetic and clinical high-risk subjects (g-/c-HR), recently diagnosed (RDSZ) and chronic SZ patients (ChSZ). We quantified gray matter (GM) changes associated with these four conditions and compared them with contrast and conjunctional data. We performed the behavioral analysis and networks decomposition of alterations to obtain their functional characterization.

Compared to previous investigations, results reveal a robust cortical-subcortical, left-to-right homotopic progression of GM loss. The right anterior cingulate is the only altered region in all conditions. Contrast analyses show left-lateralized insular, amygdalar and parahippocampal GM reduction in RDSZ, which appears bilateral in ChSZ. An overlap between RDSZ and ChSZ is observed in the left insula, amygdala, precentral and inferior frontal gyri. Functional decomposition shows involvement of the salience network, with an enlargement of the sensorimotor network in RDSZ and the thalamus-basal nuclei network in ChSZ.

These results can help the research on diagnostic and neuroimaging biomarkers of SZ staging, as well as on the identification of new therapeutics neuroanotomic targets that could be addressed with focused magnetic or non-invasive electric stimulation.

No significant relationships.

Subanesthetic ketamine infusion therapy can produce fast-acting antidepressant effects in patients with major depression. How single and repeated ketamine treatment modulates the whole-brain functional connectome to affect clinical outcomes remains uncharacterized.

Data-driven whole brain functional connectivity (FC) analysis was used to identify the functional connections modified by ketamine treatment in patients with major depressive disorder (MDD). MDD patients (N = 61, mean age = 38, 19 women) completed baseline resting-state (RS) functional magnetic resonance imaging and depression symptom scales. Of these patients, n = 48 and n = 51, completed the same assessments 24 h after receiving one and four 0.5 mg/kg intravenous ketamine infusions. Healthy controls (HC) (n = 40, 24 women) completed baseline assessments with no intervention. Analysis of RS FC addressed effects of diagnosis, time, and remitter status.

Significant differences (p < 0.05, corrected) in RS FC were observed between HC and MDD at baseline in the somatomotor network and between association and default mode networks. These disruptions in FC in MDD patients trended toward control patterns with ketamine treatment. Furthermore, following serial ketamine infusions, significant decreases in FC were observed between the cerebellum and salience network (SN) (p < 0.05, corrected). Patient remitters showed increased FC between the cerebellum and the striatum prior to treatment that decreased following treatment, whereas non-remitters showed the opposite pattern.

Results support that ketamine treatment leads to neurofunctional plasticity between distinct neural networks that are shown as disrupted in MDD patients. Cortico-striatal-cerebellar loops that encompass the SN could be a potential biomarker for ketamine treatment.

Generalization of conditioned-fear, a core feature of post-traumatic stress disorder (PTSD), has been the focus of several recent neuroimaging studies. A striking outcome of these studies is the frequency with which neural correlates of generalization fall within hubs of well-established functional networks including salience (SN), central executive (CEN), and default networks (DN). Neural substrates of generalization found to date may thus reflect traces of large-scale brain networks that form more expansive neural representations of generalization. The present study includes the first network-based analysis of generalization and PTSD-related abnormalities therein.

fMRI responses in established intrinsic connectivity networks (ICNs) representing SN, CEN, and DN were assessed during a generalized conditioned-fear task in male combat veterans (N = 58) with wide-ranging PTSD symptom severity. The task included five rings of graded size. Extreme sizes served as conditioned danger-cues (CS+: paired with shock) and safety-cues (CS−), and the three intermediate sizes served as generalization stimuli (GSs) forming a continuum-of-size between CS+ and CS–. Generalization-gradients were assessed as behavioral and ICN response slopes from CS+, through GSs, to CS–. Increasing PTSD symptomatology was predicted to relate to less-steep slopes indicative of stronger generalization.

SN, CEN, and DN responses fell along generalization-gradients with levels of generalization within and between SN and CEN scaling with PTSD symptom severity.

Neural substrates of generalized conditioned-fear include large-scale networks that adhere to the functional organization of the brain. Current findings implicate levels of generalization in SN and CEN as promising neural markers of PTSD.

Disruptions in neural circuits underlying emotion regulation (ER) may be a mechanism linking child maltreatment with psychopathology. We examined the associations of maltreatment with neural responses during passive viewing of negative emotional stimuli and attempts to modulate emotional responses. We investigated whether the influence of maltreatment on neural activation during ER differed across development and whether alterations in brain function mediated the association between maltreatment and a latent general psychopathology (‘p’) factor.

Youth aged 8–16 years with (n = 79) and without (n = 72) exposure to maltreatment completed an ER task assessing neural responses during passive viewing of negative and neutral images and effortful attempts to regulate emotional responses to negative stimuli. P-factor scores were defined by a bi-factor model encompassing internalizing and externalizing psychopathology.

Maltreated youth had greater activation in left amygdala and salience processing regions and reduced activation in multiple regions involved in cognitive control (bilateral superior frontal gyrus, middle frontal gyrus, and dorsal anterior cingulate cortex) when viewing negative v. neutral images than youth without maltreatment exposure. Reduced neural recruitment in cognitive control regions mediated the association of maltreatment with p-factor in whole-brain analysis. Maltreated youth exhibited increasing recruitment with age in ventrolateral prefrontal cortex during reappraisal while control participants exhibited decreasing recruitment with age. Findings were similar after adjusting for co-occurring neglect.

Child maltreatment influences the development of regions associated with salience processing and cognitive control during ER in ways that contribute to psychopathology.

Recently, a triple-network model suggested the abnormal interactions between the executive-control network (ECN), default-mode network (DMN) and salience network (SN) are important characteristics of addiction, in which the SN plays a critical role in allocating attentional resources toward the ECN and DMN. Although increasing studies have reported dysfunctions in these brain networks in Internet gaming disorder (IGD), interactions between these networks, particularly in the context of the triple-network model, have not been investigated in IGD. Thus, we aimed to assess alterations in the inter-network interactions of these large-scale networks in IGD, and to associate the alterations with IGD-related behaviors.

DMN, ECN and SN were identified using group-level independent component analysis (gICA) in 39 individuals with IGD and 34 age and gender matched healthy controls (HCs). Then alterations in the SN-ECN and SN-DMN connectivity, as well as in the modulation of ECN versus DMN by SN, using a resource allocation index (RAI) developed and validated previously in nicotine addiction, were assessed. Further, associations between these altered network coupling and clinical assessments were also examined.

Compared with HCs, IGD had significantly increased SN-DMN connectivity and decreased RAI in right hemisphere (rRAI), and the rRAI in IGD was negatively associated with their scores of craving.

These findings suggest that the deficient modulation of ECN versus DMN by SN might provide a mechanistic framework to better understand the neural basis of IGD and might provide novel evidence for the triple-network model in IGD.

Previous studies have analyzed brain functional connectivity to reveal the neural physiopathology of bipolar disorder (BD) and major depressive disorder (MDD) based on the triple-network model [involving the salience network, default mode network (DMN), and central executive network (CEN)]. However, most studies assumed that the brain intrinsic fluctuations throughout the entire scan are static. Thus, we aimed to reveal the dynamic functional network connectivity (dFNC) in the triple networks of BD and MDD.

We collected resting state fMRI data from 51 unmedicated depressed BD II patients, 51 unmedicated depressed MDD patients, and 52 healthy controls. We analyzed the dFNC by using an independent component analysis, sliding window correlation and k-means clustering, and used the parameters of dFNC state properties and dFNC variability for group comparisons.

The dFNC within the triple networks could be clustered into four configuration states, three of them showing dense connections (States 1, 2, and 4) and the other one showing sparse connections (State 3). Both BD and MDD patients spent more time in State 3 and showed decreased dFNC variability between posterior DMN and right CEN (rCEN) compared with controls. The MDD patients showed specific decreased dFNC variability between anterior DMN and rCEN compared with controls.

This study revealed more common but less specific dFNC alterations within the triple networks in unmedicated depressed BD II and MDD patients, which indicated their decreased information processing and communication ability and may help us to understand their abnormal affective and cognitive functions clinically.

Early diagnosis of schizophrenia could improve the outcomes and limit the negative effects of untreated illness. Although participants with schizophrenia show aberrant functional connectivity in brain networks, these between-group differences have a limited diagnostic utility. Novel methods of magnetic resonance imaging (MRI) analyses, such as machine learning (ML), may help bring neuroimaging from the bench to the bedside. Here, we used ML to differentiate participants with a first episode of schizophrenia-spectrum disorder (FES) from healthy controls based on resting-state functional connectivity (rsFC).

We acquired resting-state functional MRI data from 63 patients with FES who were individually matched by age and sex to 63 healthy controls. We applied linear kernel support vector machines (SVM) to rsFC within the default mode network, the salience network and the central executive network.

The SVM applied to the rsFC within the salience network distinguished the FES from the control participants with an accuracy of 73.0% (p = 0.001), specificity of 71.4% and sensitivity of 74.6%. The classification accuracy was not significantly affected by medication dose, or by the presence of psychotic symptoms. The functional connectivity within the default mode or the central executive networks did not yield classification accuracies above chance level.

Seed-based functional connectivity maps can be utilized for diagnostic classification, even early in the course of schizophrenia. The classification was probably based on trait rather than state markers, as symptoms or medications were not significantly associated with classification accuracy. Our results support the role of the anterior insula/salience network in the pathophysiology of FES.

Salience network (SN) dysconnectivity has been hypothesized to contribute to schizophrenia. Nevertheless, little is known about the functional and structural dysconnectivity of SN in subjects at risk for psychosis. We hypothesized that SN functional and structural connectivity would be disrupted in subjects with At-Risk Mental State (ARMS) and would be associated with symptom severity and disease progression.

We examined 87 ARMS and 37 healthy participants using both resting-state functional magnetic resonance imaging and diffusion tensor imaging. Group differences in SN functional and structural connectivity were examined using a seed-based approach and tract-based spatial statistics. Subject-level functional connectivity measures and diffusion indices of disrupted regions were correlated with CAARMS scores and compared between ARMS with and without transition to psychosis.

ARMS subjects exhibited reduced functional connectivity between the left ventral anterior insula and other SN regions. Reduced fractional anisotropy (FA) and axial diffusivity were also found along white-matter tracts in close proximity to regions of disrupted functional connectivity, including frontal-striatal-thalamic circuits and the cingulum. FA measures extracted from these disrupted white-matter regions correlated with individual symptom severity in the ARMS group. Furthermore, functional connectivity between the bilateral insula and FA at the forceps minor were further reduced in subjects who transitioned to psychosis after 2 years.

Our findings support the insular dysconnectivity of the proximal SN hypothesis in the early stages of psychosis. Further developed, the combined structural and functional SN assays may inform the prognosis of persons at-risk for psychosis.

Childhood emotional maltreatment (CEM) has been associated with disturbances in emotional and behavioral functioning, and with changes in regional brain morphology. However, whether CEM has any effect on the intrinsic organization of the brain is not known. In this study, we investigated the effects of CEM on resting-state functional connectivity (RSFC) using seeds in the limbic network, the default-mode network (DMN) and the salience network, and the left dorsomedial prefrontal cortex (dmPFC).

Using 3-T magnetic resonance imaging (MRI), resting-state functional MRI (RS-fMRI) scans were obtained. We defined seeds in the bilateral amygdala, the dorsal anterior cingulate cortex (dACC), the posterior cingulate cortex (PCC) and the left dmPFC, and used these to examine whether individuals reporting CEM (n=44) differed from individuals reporting no CEM (n=44) in RSFC with other brain regions. The two groups were matched for age, gender, handedness and the presence of psychopathology.

CEM was associated with decreased RSFC between the right amygdala and the bilateral precuneus and a cluster extending from the left insula to the hippocampus and putamen. In addition, CEM was associated with decreased RSFC between the dACC and the precuneus and also frontal regions of the brain.

We found that CEM has a profound effect on RSFC in the limbic network and the salience network. Regions that show aberrant connectivity are related to episodic memory encoding, retrieval and self-processing operations.

An intrinsic cerebral network comprising the anterior cingulate and anterior insula (the salience network) is considered to play an important role in salience detection in healthy volunteers. Aberrant salience has been proposed as an important mechanism in the production of psychotic symptoms such as delusions and hallucinations (reality distortion). We investigated whether structural deficits in the salience network are associated with the reality distortion seen in schizophrenia.

A sample of 57 patients in a clinically stable state of schizophrenia and 41 controls were studied with high-resolution magnetic resonance imaging.

Bilateral volume reduction was seen in the anterior cingulate and anterior insula in patients with schizophrenia. Reduced volume in the two left-sided regions of the salience network was significantly correlated with the severity of reality distortion.

These findings suggest that a deficit of grey matter in the salience network leads to an impaired attribution of salience to stimuli that is associated with delusions and hallucinations in schizophrenia.