Symptom provocation in obsessive-compulsive disorder: Validation of the Braga Obsessive Compulsive image set (BOCIS).

Symptom provocation paradigms are paramount to understand a heterogeneous disorder as obsessive-compulsive disorder (OCD). The main aim of our work was to develop and validate an open-access set of OCD-related images comprising three main subtypes: washing, checking, and symmetry. Twenty-six OCD patients and 25 controls provided valence and arousal ratings for a set of OCD-related, aversive, and neutral images. Linear mixed model analyses were used to estimate the main effects of group, image category, and group-image category interaction in image ratings. All main effects were found to be significant for both arousal and valence ratings, except for the group in arousal ratings. Path analysis confirmed our hypothesis that the OCI-R subscales influenced the subjective ratings of the corresponding image categories, particularly among patients. Independent samples t-tests were performed for each OCD picture to compose the set. Arousal demonstrated a greater capacity to distinguish controls and patients, thus sustaining our choice of using these ratings for the final Braga Obsessive-Compulsive Image Set (BOCIS). Our study demonstrated that the stimuli of the BOCIS reliably portray OCD-like triggers for washing, checking and symmetry subtypes. Its open-access availability will facilitate significant progress in both clinical and research settings.

Mindfulness-based cognitive therapy neurobiology in treatment-resistant obsessive-compulsive disorder: A domain-related resting-state networks approach.

Mindfulness-based cognitive therapy (MBCT) stands out as a promising augmentation psychological therapy for patients with obsessive-compulsive disorder (OCD). To identify potential predictive and response biomarkers, this study examines the relationship between clinical domains and resting-state network connectivity in OCD patients undergoing a 3-month MBCT programme. Twelve OCD patients underwent two resting-state functional magnetic resonance imaging sessions at baseline and after the MBCT programme. We assessed four clinical domains: positive affect, negative affect, anxiety sensitivity, and rumination. Independent component analysis characterised resting-state networks (RSNs), and multiple regression analyses evaluated brain-clinical associations. At baseline, distinct network connectivity patterns were found for each clinical domain: parietal-subcortical, lateral prefrontal, medial prefrontal, and frontal-occipital. Predictive and response biomarkers revealed significant brain-clinical associations within two main RSNs: the ventral default mode network (vDMN) and the frontostriatal network (FSN). Key brain nodes -the precuneus and the frontopolar cortex- were identified within these networks. MBCT may modulate vDMN and FSN connectivity in OCD patients, possibly reducing symptoms across clinical domains. Each clinical domain had a unique baseline brain connectivity pattern, suggesting potential symptom-based biomarkers. Using these RSNs as predictors could enable personalised treatments and the identification of patients who would benefit most from MBCT.

Effective connectivity of the locus coeruleus in patients with late-life Major Depressive Disorder or mild cognitive impairment.

INTRODUCTION: We compared effective connectivity from the locus coeruleus (LC) during the resting-state in patients with late-life Major Depressive Disorder (MDD), individuals with amnestic Mild Cognitive Impairment (aMCI), and Healthy Controls (HCs). PARTICIPANTS: 23 patients with late-life MDD, 22 patients with aMCI, and 28 HCs. MATERIAL AND METHODS: Participants were assessed in two time-points, 2 years apart. They underwent a resting-state functional magnetic resonance imaging and a high-resolution anatomical acquisition, as well as clinical assessments. Functional imaging data were analyzed with dynamic causal modeling, and parametric empirical Bayes model was used to map effective connectivity between 7 distinct nodes: 4 from the locus coeruleus and 3 regions displaying gray matter decreases during the two-year follow-up period. RESULTS: Longitudinal analysis of structural data identified three clusters of larger over-time gray matter volume reduction in patients (MDD+aMCI vs. HCs): the right precuneus, and the visual association and parahippocampal cortices. aMCI patients showed decreased effective connectivity from the left rostral to caudal portions of the LC, while connectivity from the left rostral LC to the parahippocampal cortex increased. In MDD, there was a decline in effective connectivity across LC caudal seeds, and increased connectivity from the left rostral to the left caudal LC seed over time. Connectivity alterations with cortical regions involved cross-hemisphere increases and same-hemisphere decreases. CONCLUSIONS: Our discoveries provide insight into the dynamic changes in effective connectivity in individuals with late-life MDD and aMCI, also shedding light on the mechanisms potentially contributing to the onset of neurodegenerative disorders.

Childhood adversity modulates structural brain changes in borderline personality but not in major depression disorder.

Adverse childhood experiences (ACEs) negatively affect the function and structure of emotion brain circuits, increasing the risk of various psychiatric disorders. It is unclear if ACEs show disorder specificity with respect to their effects on brain structure. We aimed to investigate whether the structural brain effects of ACEs differ between patients with major depression (MDD) and borderline personality disorder (BPD). These disorders share many symptoms but likely have different etiologies. To achieve our goal, we obtained structural 3T-MRI images from 20 healthy controls (HC), 19 MDD patients, and 18 BPD patients, and measured cortical thickness and subcortical gray matter volumes. We utilized the Adverse Childhood Experiences (ACE) questionnaire to quantify self-reported exposure to childhood trauma. Our findings suggest that individuals with MDD exhibit a smaller cortical thickness when compared to those with BPD. However, ACEs showed a significantly affected relationship with cortical thickness in BPD but not in MDD. ACEs were found to be associated with thinning in cortical regions involved in emotional behavior in BPD, whereas HC showed an opposite association. Our results suggest a potential mechanism of ACE effects on psychopathology involving changes in brain structure. These findings highlight the importance of early detection and intervention strategies.

Trait anxiety is associated with attentional brain networks.

Trait anxiety is a well-established risk factor for anxiety and depressive disorders, yet its neural correlates are not clearly understood. In this study, we investigated the neural correlates of trait anxiety in a large sample (n = 179) of individuals who completed the trait and state versions of the State-Trait Anxiety Inventory and underwent resting-state functional magnetic resonance imaging. We used independent component analysis to characterize individual resting-state networks (RSNs), and multiple regression analyses to assess the relationship between trait anxiety and intrinsic connectivity. Trait anxiety was significantly associated with intrinsic connectivity in different regions of three RSNs (dorsal attention network, default mode network, and auditory network) when controlling for state anxiety. These RSNs primarily support attentional processes. Notably, when state anxiety was not controlled for, a different pattern of results emerged, highlighting the importance of considering this factor in assessing the neural correlates of trait anxiety. Our findings suggest that trait anxiety is uniquely associated with resting-state brain connectivity in networks mainly supporting attentional processes. Moreover, controlling for state anxiety is crucial when assessing the neural correlates of trait anxiety. These insights may help refine current neurobiological models of anxiety and identify potential targets for neurobiologically-based interventions.

Computational modelling of reinforcement learning and functional neuroimaging of probabilistic reversal for dissociating compulsive behaviours in gambling and cocaine use disorders.

BACKGROUND: Individuals with cocaine use disorder or gambling disorder demonstrate impairments in cognitive flexibility: the ability to adapt to changes in the environment. Flexibility is commonly assessed in a laboratory setting using probabilistic reversal learning, which involves reinforcement learning, the process by which feedback from the environment is used to adjust behavior. AIMS: It is poorly understood whether impairments in flexibility differ between individuals with cocaine use and gambling disorders, and how this is instantiated by the brain. We applied computational modelling methods to gain a deeper mechanistic explanation of the latent processes underlying cognitive flexibility across two disorders of compulsivity. METHOD: We present a re-analysis of probabilistic reversal data from individuals with either gambling disorder (n = 18) or cocaine use disorder (n = 20) and control participants (n = 18), using a hierarchical Bayesian approach. Furthermore, we relate behavioural findings to their underlying neural substrates through an analysis of task-based functional magnetic resonanceimaging (fMRI) data. RESULTS: We observed lower 'stimulus stickiness' in gambling disorder, and report differences in tracking expected values in individuals with gambling disorder compared to controls, with greater activity during reward expected value tracking in the cingulate gyrus and amygdala. In cocaine use disorder, we observed lower responses to positive punishment prediction errors and greater activity following negative punishment prediction errors in the superior frontal gyrus compared to controls. CONCLUSIONS: Using a computational approach, we show that individuals with gambling disorder and cocaine use disorder differed in their perseverative tendencies and in how they tracked value neurally, which has implications for psychiatric classification.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression.

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Corrigendum: Complexity changes in functional state dynamics suggest focal connectivity reductions.

[This corrects the article DOI: 10.3389/fnhum.2022.958706.].

Exploring the influence of circulating endocannabinoids and nucleus accumbens functional connectivity on anorexia nervosa severity.

Anorexia nervosa (AN) is a severe psychiatric disorder characterized by a harmful persistence of self-imposed starvation resulting in significant weight loss. Research suggests that alterations in the nucleus accumbens (NAcc) and circulating endocannabinoids (eCBs), such as anandamide (AEA) and 2-arachidonoylglycerol (2-AG), may contribute to increased severity and maladaptive behaviors in AN, warranting an examination of the interplay between central reward circuitry and eCBs. For this purpose, we assessed NAcc functional connectivity and circulating AEA and 2-AG concentrations in 18 individuals with AN and 18 healthy controls (HC) to test associations between circulating eCBs, NAcc functional connectivity, and AN severity, as defined by body mass index (BMI). Decreased connectivity was observed between the NAcc and the right insula (NAcc-insula; pFWE < 0.001) and the left supplementary motor area (NAcc-SMA; pFWE < 0.001) in the AN group compared to HC. Reduced NAcc-insula functional connectivity mediated the association between AEA concentrations and BMI in the AN group. However, in HC, NAcc-SMA functional connectivity had a mediating role between AEA concentrations and BMI. Although no significant differences in eCBs concentrations were observed between the groups, our findings provide insights into how the interaction between eCBs and NAcc functional connectivity influences AN severity. Altered NAcc-insula and NAcc-SMA connectivity in AN may impair the integration of interoceptive, somatosensory, and motor planning information related to reward stimuli. Furthermore, the distinct associations between eCBs concentrations and NAcc functional connectivity in AN and HC could have clinical implications for weight maintenance, with eCBs being a potential target for AN treatment.

Dynamic fronto-amygdalar interactions underlying emotion-regulation deficits in women at higher weight.

OBJECTIVE: The regulation of negative emotions entails the modulation of subcortical regions, such as the amygdala, by prefrontal regions. There is preliminary evidence suggesting that individuals at higher weight may present with hypoactivity in prefrontal regulatory systems during emotional regulation, although the directionality of these pathways has not been tested. In this study, we compared fronto-amygdalar effective connectivity during cognitive reappraisal as a function of BMI in 48 adult women with obesity and 54 control participants. METHODS: Dynamic causal modeling and parametric empirical Bayes were used to map effective connectivity between the dorsomedial prefrontal cortex, orbitofrontal cortex, dorsolateral prefrontal cortex, and the amygdala. RESULTS: Difficulty in Emotion Regulation Scale scores were higher in the obesity group compared with control participants (p < 0.001). A top-down cortical model best explained our functional magnetic resonance imaging data (posterior probability = 86%). Participants at higher BMI were less effective at inhibiting activity in the amygdala via the orbitofrontal cortex and dorsomedial prefrontal cortex during reappraisal compared with those at lower BMI. In contrast, increased excitatory modulation of dorsolateral prefrontal cortex-to-amygdalar connectivity was found in participants at lower BMI. CONCLUSIONS: These findings support a framework involving alterations in fronto-amygdalar connectivity contributing to difficulties in regulating negative affect in individuals at higher weight.

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders.

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression.

Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this common causal network (CCN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis (Principal Component Analysis, PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CCN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CCN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes. This evidence further supports that treatment interventions converge on a CCN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression.

Association of anandamide and 2-arachidonoylglycerol concentrations with clinical features and body mass index in eating disorders and obesity.

BACKGROUND: Anandamide (AEA) and 2-arachidonoylglycerol (2-AG) play a pivotal role in stimulating motivational behavior toward food and energy metabolism. Aberrant functioning of the endocannabinoid system has been observed in extreme weight conditions (EWCs), suggesting it may influence pathophysiology. Then, we aimed to analyze fasting AEA and 2-AG plasma concentrations among individuals with EWC (i.e., anorexia nervosa [AN] and obesity with and without eating disorders [EDs]) compared with healthy controls (HCs), and its association with clinical variables and body mass index (BMI). METHODS: The sample included 113 adult women. Fifty-seven belonged to the obesity group, 37 without EDs (OB-ED) and 20 with ED (OB+ED classified within the binge spectrum disorders), 27 individuals from the AN group, and 29 from the HC group. Peripheral blood samples, several clinical variables, and BMI were evaluated. RESULTS: Unlike 2-AG, AEA concentrations showed significant differences between groups (p < 0.001). Increased AEA was observed in the OB-ED and OB+ED compared with both HC and AN group, respectively. Likewise, AEA was differentially associated with emotional dysregulation, general psychopathology, food addiction, and BMI in all clinical groups. CONCLUSIONS: These results support the interaction between biological and clinical factors contributing to delineating vulnerability pathways in EWC that could help fit personalized therapeutic approaches.

Brain volumetric correlates of electroconvulsive therapy versus transcranial magnetic stimulation for treatment-resistant depression.

BACKGROUND: Electroconvulsive therapy (ECT) and repetitive transcranial magnetic stimulation (rTMS) are effective neuromodulation therapies for treatment-resistant depression (TRD). While ECT is generally considered the most effective antidepressant, rTMS is less invasive, better tolerated and leads to more durable therapeutic benefits. Both interventions are established device antidepressants, but it remains unknown if they share a common mechanism of action. Here we aimed to compare the brain volumetric changes in patients with TRD after right unilateral (RUL) ECT versus left dorsolateral prefrontal cortex (lDLPFC) rTMS. METHODS: We assessed 32 patients with TRD before the first treatment session and after treatment completion using structural magnetic resonance imaging. Fifteen patients were treated with RUL ECT and seventeen patients received lDLPFC rTMS. RESULTS: Patients receiving RUL ECT, in comparison with patients treated with lDLPFC rTMS, showed a greater volumetric increase in the right striatum, pallidum, medial temporal lobe, anterior insular cortex, anterior midbrain, and subgenual anterior cingulate cortex. However, ECT- or rTMS-induced brain volumetric changes were not associated with the clinical improvement. LIMITATIONS: We evaluated a modest sample size with concurrent pharmacological treatment and without neuromodulation therapies randomization. CONCLUSIONS: Our findings suggest that despite comparable clinical outcomes, only RUL ECT is associated with structural change, while rTMS is not. We hypothesize that structural neuroplasticity and/or neuroinflammation may explain the larger structural changes observed after ECT, whereas neurophysiological plasticity may underlie the rTMS effects. More broadly, our results support the notion that there are multiple therapeutic strategies to move patients from depression to euthymia.

Sirtuin-2, NAD-Dependent Deacetylase, Is a New Potential Therapeutic Target for HIV-1 Infection and HIV-Related Neurological Dysfunction.

The implementation and access to combined antiretroviral treatment (cART) have dramatically improved the quality of life of people living with HIV (PLWH). However, some comorbidities, such as neurological disorders associated with HIV infection still represent a serious clinical challenge. Soluble factors in plasma that are associated with control of HIV replication and neurological dysfunction could serve as early biomarkers and as new therapeutic targets for this comorbidity. We used a customized antibody array for determination of blood plasma factors in 40 untreated PLWH with different levels of viremia and found sirtuin-2 (SIRT2), an NAD-dependent deacetylase, to be strongly associated with elevated viral loads and HIV provirus levels, as well as with markers of neurological damage (a-synuclein [SNCA], brain-derived neurotrophic factor [BDNF], microtubule-associated protein tau [MAPT], and neurofilament light protein [NFL]). Also, longitudinal analysis in HIV-infected individuals with immediate (n = 9) or delayed initiation (n = 10) of cART revealed that after 1 year on cART, SIRT2 plasma levels differed between both groups and correlated inversely with brain orbitofrontal cortex involution. Furthermore, targeting SIRT2 with specific small-molecule inhibitors in in vitro systems using J-LAT A2 and primary glial cells led to diminished HIV replication and virus reactivation from latency. Our data thus identify SIRT2 as a novel biomarker of uncontrolled HIV infection, with potential impact on neurological dysfunction and offers a new therapeutic target for HIV treatment and cure. IMPORTANCE Neurocognitive disorders are frequently reported in people living with HIV (PLWH) even with the introduction of combined antiretroviral treatment (cART). To identify biomarkers and potential therapeutic tools to target HIV infection in peripheral blood and in the central nervous system (CNS), plasma proteomics were applied in untreated chronic HIV-infected individuals with different levels of virus control. High plasma levels of sirtuin-2 (SIRT2), an NAD+ deacetylase, were detected in uncontrolled HIV infection and were strongly associated with plasma viral load and proviral levels. In parallel, SIRT2 levels in the peripheral blood and CNS were associated with markers of neurological damage and brain involution and were more pronounced in individuals who initiated cART later in infection. In vitro infection experiments using specific SIRT2 inhibitors suggest that specific targeting of SIRT2 could offer new therapeutic treatment options for HIV infections and their associated neurological dysfunction.

Right Prefrontal Cortical Thickness Is Associated With Response to Cognitive-Behavioral Therapy in Children With Obsessive-Compulsive Disorder.

OBJECTIVE: Cognitive-behavioral therapy (CBT) is considered a first-line treatment for obsessive-compulsive disorder (OCD) in pediatric and adult populations. Nevertheless, some patients show partial or null response. The identification of predictors of CBT response may improve clinical management of patients with OCD. Here, we aimed to identify structural magnetic resonance imaging (MRI) predictors of CBT response in 2 large series of children and adults with OCD from the worldwide ENIGMA-OCD consortium. METHOD: Data from 16 datasets from 13 international sites were included in the study. We assessed which variations in baseline cortical thickness, cortical surface area, and subcortical volume predicted response to CBT (percentage of baseline to post-treatment symptom reduction) in 2 samples totaling 168 children and adolescents (age range 5-17.5 years) and 318 adult patients (age range 18-63 years) with OCD. Mixed linear models with random intercept were used to account for potential cross-site differences in imaging values. RESULTS: Significant results were observed exclusively in the pediatric sample. Right prefrontal cortex thickness was positively associated with the percentage of CBT response. In a post hoc analysis, we observed that the specific changes accounting for this relationship were a higher thickness of the frontal pole and the rostral middle frontal gyrus. We observed no significant effects of age, sex, or medication on our findings. CONCLUSION: Higher cortical thickness in specific right prefrontal cortex regions may be important for CBT response in children with OCD. Our findings suggest that the right prefrontal cortex plays a relevant role in the mechanisms of action of CBT in children.

Neural predictors of cognitive-behavior therapy outcome in anxiety-related disorders: a meta-analysis of task-based fMRI studies.

BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.

Structural covariance predictors of clinical improvement at 2-year follow-up in first-episode psychosis.

The relationship between structural brain alterations and prediction of clinical improvement in first-episode psychosis (FEP) has been scarcely studied. We investigated whether structural covariance, a well-established approach to identify abnormal patterns of volumetric correlation across distant brain regions, which allows incorporating network-level information to structural assessments, is associated with longitudinal clinical course. We assessed a sample of 74 individuals from a multicenter study. Magnetic resonance imaging scans were acquired at baseline, and clinical assessments at baseline and at a 2-year follow-up. Participants were split in two groups as a function of their clinical improvement after 2 years (i.e., ≥ < 40% reduction in psychotic symptom severity, (n = 29, n = 45)). We performed a seed-based approach and focused our analyses on 3 cortical and 4 subcortical regions of interest to identify alterations in cortical and cortico-subcortical networks. Improvers presented an increased correlation between the volumes of the right posterior cingulate cortex (PCC) and the left precentral gyrus, and between the left PCC and the left middle occipital gyrus. They also showed an increased correlation between right posterior hippocampus and left angular gyrus volumes. Our study provides a novel mean to identify structural correlates of clinical improvement in FEP, describing clinically-relevant anatomical differences in terms of large-scale brain networks, which is better aligned with prevailing neurobiological models of psychosis. The results involve brain regions considered to participate in the multisensory processing of bodily signals and the construction of bodily self-consciousness, which resonates with recent theoretical accounts in psychosis research.

Development and Validation of a Smartphone-Based App for the Longitudinal Assessment of Anxiety in Daily Life.

Current methods to assess human anxiety often ignore that anxiety is a dynamic process and have limitations such as high recall bias and low generalizability to real life. Smartphone apps using ecological momentary assessment (EMA) may overcome such limitations. We developed a smartphone app for the longitudinal evaluation of anxiety symptoms using EMA. We assessed the feasibility (retention and compliance) and psychometric properties (reliability and validity) of the app over 6 months in a sample of 99 participants with different levels of anxiety. The EMA-based smartphone app was highly feasible. It showed excellent within-person and between-person reliability, high convergent and moderate discriminant validity, and significant incremental validity. Assessing anxiety longitudinally using a smartphone and following EMA principles is feasible and can be reliable and valid. Studies combining EMA-based anxiety longitudinal assessments with other assessment methods deserve further research and may offer novel insights into human anxiety.