Explore the vast range of titles available.

Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the “fear circuit”, including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety. •We defined 34 network nodes based on task-based SAD fMRI meta-analytic studies.•SAD had higher functional connectivity in a single connected component.•SAD had a shift of brain network topology toward randomized configurations.•Abnormal connectivity in SAD was significantly associated with anxiety symptoms.

Abstract The recent renaissance of psychedelic science has reignited interest in the similarity of drug-induced experiences to those more commonly observed in psychiatric contexts such as the schizophrenia-spectrum. This report from a multidisciplinary working group of the International Consortium on Hallucinations Research (ICHR) addresses this issue, putting special emphasis on hallucinatory experiences. We review evidence collected at different scales of understanding, from pharmacology to brain-imaging, phenomenology and anthropology, highlighting similarities and differences between hallucinations under psychedelics and in the schizophrenia-spectrum disorders. Finally, we attempt to integrate these findings using computational approaches and conclude with recommendations for future research.

An increasing concern affecting a growing aging population is working memory (WM) decline. Consequently, there is great interest in improving or stabilizing WM, which drives expanded use of brain training exercises. Such regimens generally result in temporary WM benefits to the trained tasks but minimal transfer of benefit to untrained tasks. Pairing training with neurostimulation may stabilize or improve WM performance by enhancing plasticity and strengthening WM-related cortical networks. We tested this possibility in healthy older adults. Participants received 10 sessions of sham (control) or active (anodal, 1.5 mA) tDCS to the right prefrontal, parietal, or prefrontal/parietal (alternating) cortices. After ten minutes of sham or active tDCS, participants performed verbal and visual WM training tasks. On the first, tenth, and follow-up sessions, participants performed transfer WM tasks including the spatial 2-back, Stroop, and digit span tasks. The results demonstrated that all groups benefited from WM training, as expected. However, at follow-up 1-month after training ended, only the participants in the active tDCS groups maintained significant improvement. Importantly, this pattern was observed for both trained and transfer tasks. These results demonstrate that tDCS-linked WM training can provide long-term benefits in maintaining cognitive training benefits and extending them to untrained tasks.

Abstract Social interaction is impaired in schizophrenia, including the use of hand gestures, which is linked to poor social perception and outcome. Brain imaging suggests reduced neural activity in a left-lateralized frontoparietal network during gesture preparation; therefore, gesturing might be improved through facilitation of left hemispheric brain areas or via disruption of interhemispheric inhibition from the right homolog. This study tested whether repetitive transcranial magnetic stimulation (rTMS) protocols would improve gesture performance in schizophrenia. This randomized, placebo-controlled, double-blind, crossover trial applied 3 different protocols of rTMS separated by 48 h. Twenty right-handed schizophrenia patients and 20 matched healthy controls received facilitatory intermittent theta burst stimulation (iTBS) over the left inferior frontal gyrus (IFG), inhibitory continuous theta burst stimulation (cTBS) over right inferior parietal lobe (IPL), and placebo over left IPL in randomized order. Primary outcome was change in the test of upper limb apraxia (TULIA), rated from video recordings of hand gesture performance. Secondary outcome was change in manual dexterity using the coin rotation task. Participants improved on both tasks following rTMS compared with baseline. Only patients improved gesture performance following right IPL cTBS compared with placebo (P = .013). The results of the coin rotation parallel those of the TULIA, with improvements following right IPL cTBS in patients (P = .001). Single sessions of cTBS on the right IPL substantially improved both gesture performance accuracy and manual dexterity. The findings point toward an inhibition of interhemispheric rivalry as a potential mechanism of action.

Dynamic Functional Connectivity (dFC) in the resting state (rs) is considered as a correlate of cognitive processing. Describing dFC as a flow across morphing connectivity configurations, our notion of dFC speed quantifies the rate at which FC networks evolve in time. Here we probe the hypothesis that variations of rs dFC speed and cognitive performance are selectively interrelated within specific functional subnetworks. In particular, we focus on Sleep Deprivation (SD) as a reversible model of cognitive dysfunction. We found that whole-brain level (global) dFC speed significantly slows down after 24h of SD. However, the reduction in global dFC speed does not correlate with variations of cognitive performance in individual tasks, which are subtle and highly heterogeneous. On the contrary, we found strong correlations between performance variations in individual tasks –including Rapid Visual Processing (RVP, assessing sustained visual attention)– and dFC speed quantified at the level of functional sub-networks of interest. Providing a compromise between classic static FC (no time) and global dFC (no space), modular dFC speed analyses allow quantifying a different speed of dFC reconfiguration independently for sub-networks overseeing different tasks. Importantly, we found that RVP performance robustly correlates with the modular dFC speed of a characteristic frontoparietal module. •Sleep Deprivation (SD) slows down the random walk in FC space implemented by Dynamic Functional Connectivity (dFC) at rest.•Whole-brain level slowing of dFC speed does not selectively correlate with fine and task-specific changes in performance.•We quantify dFC speed separately for different link-based modules coordinated by distinct regional “meta-hubs”.•Modular dFC speed variations capture subtle and task-specific variations of cognitive performance induced by SD.

A large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network. A personalized repetitive transcranial magnetic stimulation protocol significantly alleviates clinical symptoms in obsessive‐compulsive disorder. Nearly half of the patients showed more than 35% symptom reduction after 2 weeks of treatment. The baseline profile of target connectivity significantly predicted symptom outcome.

One of the fundamental questions in real‐time functional magnetic resonance imaging neurofeedback (rt‐fMRI NF) investigations is the definition of a suitable neural target for training. Previously, we applied a meta‐analytical approach to define a network‐level target for connectivity‐based rt‐fMRI NF in substance use disorders. The analysis yielded consistent connectivity alterations between the insula and anterior cingulate cortex (ACC) as well as the dorsal striatum and the ACC. In the current investigation, we addressed the feasibility of regulating this network and its functional relevance using connectivity‐based neurofeedback. In a double‐blind, sham‐controlled design, 60 nicotine users were randomly assigned to the experimental or sham control group for one NF training session. The preregistered primary outcome was defined as improved inhibitory control performance after regulation of the target network compared to sham control. Secondary outcomes were (1) neurofeedback‐specific changes in functional connectivity of the target network; (2) changes in smoking behavior and impulsivity measures; and (3) changes in resting‐state connectivity profiles. Our results indicated no differences in behavioral measures after receiving feedback from the target network compared to the sham feedback. Target network connectivity was increased during regulation blocks compared to rest blocks, however, the experimental and sham groups could regulate to a similar degree. Accordingly, the observed activation patterns may be related to the mental strategies used during regulation attempts irrespective of the group assignment. We discuss several crucial factors regarding the efficacy of a single‐session connectivity‐based neurofeedback for the target network. This includes high fluctuation in the connectivity values of the target network that may impact controllability of the signal. To our knowledge, this investigation is the first randomized, double‐blind controlled real‐time fMRI study in nicotine users. This raises the question of whether previously observed effects in nicotine users are specific to the neurofeedback signal or reflect more general self‐regulation attempts. In a double‐blind, sham‐controlled design, we investigated the feasibility of targeting a meta‐analytically defined network (comprised of the anterior cingulated cortex, insula, and dorsal striatum) using connectivity‐based real‐time fMRI neurofeedback. Our findings indicate no superiority of receiving feedback from the target network over sham feedback.

Default mode network (DMN) dysfunction (particularly within the anterior cingulate cortex (ACC) and medial prefrontal cortex (mPFC)) has been implicated in major depressive disorder (MDD); however, its contribution to treatment outcome has not been clearly established. Here we tested the role of DMN functional connectivity as a general and differential biomarker for predicting treatment outcomes in a large, unmedicated adult sample with MDD. Seventy-five MDD outpatients completed fMRI scans before and 8 weeks after randomization to escitalopram, sertraline, or venlafaxine-XR. A whole-brain voxel-wise t-test identified profiles of pretreatment intrinsic functional connectivity that distinguished patients who were subsequently classified as remitters or non-remitters at follow-up. Connectivity was seeded in the PCC, an important node of the DMN. We further characterized differences between remitters, non-remitters, and 31 healthy controls and characterized changes pretreatment to posttreatment. Remitters were distinguished from non-remitters by relatively intact connectivity between the PCC and ACC/mPFC, not distinguishable from healthy controls, while non-remitters showed relative hypo-connectivity. In validation analyses, we demonstrate that PCC–ACC/mPFC connectivity predicts remission status with >80% cross-validated accuracy. In analyses testing whether intrinsic connectivity differentially relates to outcomes for a specific type of antidepressant, interaction models did not survive the corrected threshold. Our findings demonstrate that the overall capacity to remit on commonly used antidepressants may depend on intact organization of intrinsic functional connectivity between PCC and ACC/mPFC prior to treatment. The findings highlight the potential utility of functional scans for advancing a more precise approach to tailoring antidepressant treatment choices.

The experience of auditory verbal hallucinations in schizophrenia is associated with changes in brain network function. In particular, studies indicate altered functional coupling between nodes of the language and default mode networks. Neurofeedback based on real-time functional magnetic resonance imaging (rtfMRI) can be used to modulate such aberrant network connectivity. We investigated resting-state connectivity changes after neurofeedback (NF) in 21 patients with schizophrenia and 35 healthy individuals. All participants underwent two days of neurofeedback training of important nodes of the left-hemispheric language network including the inferior frontal gyrus (IFG) and posterior superior temporal gyrus (pSTG). In a double-blind randomized cross-over design, participants learned to down- and up-regulate their brain activation in the designated target regions based on NF. Prior to and after each training day, a resting state measurement took place. Coupling between nodes of the language and the default mode network (DMN) selectively increased after down-as compared to up-regulation NF. Network analyses revealed more pronounced increases in functional connectivity between nodes of the language network and the DMN in patients compared to healthy individuals. In particular, down-regulation NF led to increased coupling between nodes of the language network and bilateral inferior parietal lobe (IPL) as well as posterior cingulate cortex (PCC)/precuneus in patients. Up-regulation strengthened connectivity with the medial prefrontal cortex (mPFC). Improved well-being four weeks after the training predicted increased functional coupling between the left IFG and left IPL. Modulatory effects emerged as increased internetwork communication, indicating that down-regulation NF selectively enhances coupling between language and DM network nodes in patients with AVH. RtfMRI NF may thus be used to modulate brain network function that is relevant to the phenomenology of AVH. Specific effects of self-regulation on symptom improvement have to be explored in therapeutic interventions.

Negative symptoms are core contributors to vocational and social deficits in schizophrenia (SZ). Available antipsychotic medications typically fail to reduce these symptoms. The neurohormone oxytocin (OT) is a promising treatment for negative symptoms, given its role in complex social behaviors mediated by the amygdala. In sample 1, we used a double-blind, placebo-controlled, crossover design to test the effects of a single dose of intranasal OT on amygdala resting-state functional connectivity (rsFC) in SZ (n = 22) and healthy controls (HC, n = 24) using a whole-brain corrected approach: we identified regions for which OT modulated SZ amygdala rsFC, assessed whether OT-modulated circuits were abnormal in SZ relative to HC on placebo, and evaluated whether connectivity on placebo and OT-induced connectivity changes correlated with baseline negative symptoms in SZ. Given our modest sample size, we used a second SZ (n = 183) and HC (n = 178) sample to replicate any symptom correlations. In sample 1, OT increased rsFC between the amygdala and left middle temporal gyrus, superior temporal sulcus, and angular gyrus (MTG/STS/AngG) in SZ compared to HC. Further, SZ had hypo-connectivity in this circuit compared to HC on placebo. More severe negative symptoms correlated with less amygdala-to-left-MTG/STS/AngG connectivity on placebo and with greater OT-induced connectivity increases. In sample 2, we replicated the correlation between amygdala-left-MTG/STS/AngG hypo-connectivity and negative symptoms, finding a specific association with expressive negative symptoms. These data suggest intranasal OT can normalize functional connectivity in an amygdala-to-left-MTG/STS/AngG circuit that contributes to negative symptoms in SZ.