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Parenting styles encompass negative and positive approaches, potentially affecting adolescents' brain reward and emotion regulation systems. However, the association between parenting style and brain networks remains unknown. This study investigates the link between parenting style and functional connectivity (FC) within the reward and emotion regulation brain networks, using resting-state functional magnetic resonance imaging (rs-fMRI). A total of forty-two middle-aged adolescents (26 males; 16 females) with no neurological or psychiatric symptoms participated in this study. We assessed parenting behaviors and extracted reward/emotion regulation FC from rs-fMRI. We examined the association between FC and parenting style, identified through principal component analysis. Correlation analysis investigated these links while controlling for sex. We delineated both positive (love-autonomy) and negative (hostility-control) parenting styles, accounting for 79 % of the explained variance in parenting behaviors. The negative parenting style displayed connections with FC within the reward system, particularly in the left nucleus accumbens (NAc), showcasing links to multiple frontal regions. Furthermore, it correlated with the social reward network, specifically the insula-NAc FC in bilateral hemispheres. Conversely, the positive parenting style exhibited an association with FC between the hippocampus and right lateral prefrontal cortex. Our findings support negative parenting's association with an immature reward system and suggest positive parenting's potential to enhance emotion regulation in brain function. These observations highlight two distinct parenting styles, including single-parenting behaviors. Thus, we advance understanding of each style's unique contributions to adolescent reward- and emotion regulation-related brain network development. • We identified positive (love-autonomy) and negative (hostility-control) parenting style components. • Negative style component was related to functional connectivity in the reward system during adolescence. • Positive style component was associated with brain network of emotion regulation. • Advanced insights into the differential roles of parenting style in brain functions during adolescence. [ABSTRACT FROM AUTHOR]

[Display omitted] • Functional neuroimaging alterations in AOID patients with anxiety. • Correlations analysis support neural basis of anxiety symptoms in AOID. • Candidate imaging biomarkers to distinguish AOID patients with/without anxiety. Psychiatric disturbances are commonly associated with adult-onset isolated dystonia (AOID); however, the mechanisms underlying psychiatric abnormalities in AOID remain unknown. We aimed to investigate the structural and functional brain changes in AOID patients with anxiety, and identify imaging biomarkers for diagnosing anxiety. Structural and functional magnetic resonance was performed on 69 AOID patients and 35 healthy controls (HCs). The Hamilton Anxiety Scale (HAMA) was used to assess anxiety symptoms in AOID patients and assign patients to AOID with and without anxiety groups. Group differences in grey matter volume, amplitude of low-frequency fluctuations (ALFF), fractional ALFF, and regional homogeneity (ReHo) were evaluated. Area under the receiver operating characteristic curve (ROC AUC) was used as a metric to identify imaging biomarkers for diagnosing anxiety. AOID patients with anxiety exhibited an increased ALFF and ReHo in the left angular gyrus (ANG.L) compared with those without and HCs (voxel P <0.001 and cluster P <0.05, corrected using GRF). A significant positive correlation was observed between ALFF (r = 0.627, P <0.001) and ReHo (r = 0.515, P <0.001) in the ANG.L and HAMA scores in AOID patients. ALFF and ReHo in the ANG.L exhibited an ROC AUC of 0.904 and 0.851, respectively, in distinguishing AOID patients with anxiety from those without and an ROC AUC of 0.887 and 0.853, respectively, in distinguishing AOID patients with anxiety from HCs. These findings provide new insights into the pathophysiology of psychiatric disturbances and highlight potential candidate biomarkers for identifying anxiety in AOID patients. [ABSTRACT FROM AUTHOR]

The putamen has been proposed to play a critical role in the development of obsessive-compulsive disorder (OCD). The primary objective of this study was to examine the resting-state regional activity and functional connectivity patterns of the putamen in individuals diagnosed with OCD. To achieve this, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to collect data from a sample of 45 OCD patients and 53 healthy control participants. We aimed to use the regional amplitude of low-frequency fluctuation (ALFF) analysis to generate the ROI masks of the putamen and then conduct the whole brain functional connectivity of the putamen in individuals with OCD. Compared to controls, the OCD group demonstrated decreased ALFF in bilateral putamen. The right putamen also displayed decreased FC with the left putamen extending to the inferior frontal gyrus (IFG), bilateral precuneus extending to calcarine, the right middle occipital cortex extending to the right middle temporal cortex, and the left middle occipital gyrus. The decreased connectivity between the right putamen and the left IFG was negatively correlated with Yale-Brown Obsessive Compulsive scale (Y-BOCS) Obsession Scores. This study aimed to reveal the putamen changes in resting-state activity and connectivity in OCD patients, highlighting the significance of aberrant ALFF/FC of the putamen is a key characteristic of OCD. • Explored network-level neural function of the putamen in OCD patients. • Patients showed decreased ALFF in bilateral putamen. • Abnormal FC with the left putamen/IFG, precuneus, visual and auditory networks. • Dysconnectivitybetween the right patumen and the left putamen/IFG negatively correlated with Y-BOCS Obsession Scores. [ABSTRACT FROM AUTHOR]

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646. • This study examines how suicidal ideation, cognitive function, and brain connectivity are related in depressed patients. • Distinct connectivity patterns linked to suicidal ideation were found in frontoparietal (FPN) and default mode networks (DMN). • These findings offer new insights into MDD-related suicidal ideation and may influence treatment strategies. [ABSTRACT FROM AUTHOR]

Electroconvulsive therapy (ECT) is an effective treatment for patients with major depressive disorder (MDD), but its underlying neural mechanisms remain largely unknown. The aim of this study was to identify changes in brain connectome dynamics after ECT in MDD and to explore their associations with treatment outcome. We collected longitudinal resting-state functional magnetic resonance imaging data from 80 patients with MDD (50 with suicidal ideation [MDD-SI] and 30 without [MDD-NSI]) before and after ECT and 37 age- and sex-matched healthy control participants. A multilayer network model was used to assess modular switching over time in functional connectomes. Support vector regression was used to assess whether pre-ECT network dynamics could predict treatment response in terms of symptom severity. At baseline, patients with MDD had lower global modularity and higher modular variability in functional connectomes than control participants. Network modularity increased and network variability decreased after ECT in patients with MDD, predominantly in the default mode and somatomotor networks. Moreover, ECT was associated with decreased modular variability in the left dorsal anterior cingulate cortex of MDD-SI but not MDD-NSI patients, and pre-ECT modular variability significantly predicted symptom improvement in the MDD-SI group but not in the MDD-NSI group. We highlight ECT-induced changes in MDD brain network dynamics and their predictive value for treatment outcome, particularly in patients with SI. This study advances our understanding of the neural mechanisms of ECT from a dynamic brain network perspective and suggests potential prognostic biomarkers for predicting ECT efficacy in patients with MDD. [ABSTRACT FROM AUTHOR]

Anhedonia stands as a life-threatening transdiagnostic feature of many mental illnesses, most notably major depression and involves neural circuits for processing reward information. The paraventricular nucleus of the thalamus (PVT) is associated with reward-seeking behavior, however, links between the PVT circuit and anhedonia have not been investigated in humans. In a sample of adults with and without psychiatric symptoms (n = 75, 18–41 years, 55 female), we generated an anhedonia factor score for each participant using a latent factor analysis, utilizing data from depression and anxiety assessments. Functional connectivity between the PVT and the nucleus accumbens (NAc) was calculated from high-resolution (1.5 mm) resting state fMRI. Anhedonia factor scores showed a positive relationship with functional connectivity between the PVT and the NAc, principally in males and in those with psychiatric symptoms. In males, connectivity between other midline thalamic nuclei and the NAc did not show these relationships, suggesting that this link may be specific to PVT. This cohort was originally recruited to study depression and not anhedonia per se. The distribution of male and female participants in our cohort was not equal. Partial acquisition in high-resolution fMRI scans restricted regions of interest outside of the thalamus and reward networks. We report evidence that anhedonia is associated with enhanced functional connectivity between the PVT and the NAc, regions that are relevant to reward processing. These results offer clues as to the potential prevention and prevention and treatment of anhedonia. • Anhedonia has been associated with alterations in reward processing neural circuits. • The paraventricular nucleus of the thalamus (PVT) projects to reward and threat regions. • Altering PVT is associated with anhedonia in animal models. • In humans, anhedonia symptoms are associated with increased functional connectivity between PVT and nucleus accumbens, particularly in males. • This provides evidence that the human PVT circuit is involved in anhedonia. [ABSTRACT FROM AUTHOR]

Systemic lupus erythematosus (SLE) is an immune-mediated and multi-systemic disease which may affect the nervous system, causing neuropsychiatric SLE (NPSLE). Recent neuroimaging studies have examined brain functional alterations in SLE. However, discrepant findings were reported. This meta-analysis aims to identify consistent resting-state functional abnormalities in SLE. PubMed and Web of Science were searched to identify candidate resting-state functional MRI studies assessing SLE. A voxel-based meta-analysis was performed using the anisotropic effect-size version of the seed-based d mapping (AES-SDM). The abnormal intrinsic functional patterns extracted from SDM were mapped onto the brain functional network atlas to determine brain abnormalities at a network level. Twelve studies evaluating fifteen datasets were included in this meta-analysis, comprising 572 SLE patients and 436 healthy controls (HCs). Compared with HCs, SLE patients showed increased brain activity in the bilateral hippocampus and right superior temporal gyrus, and decreased brain activity in the left superior frontal gyrus, left middle temporal gyrus, bilateral thalamus, left inferior frontal gyrus and right cerebellum. Mapping the abnormal patterns to the network atlas revealed the default mode network and the limbic system as core neural systems commonly affected in SLE. The number of included studies is relatively small, with heterogeneous analytic methods and a risk of publication bias. Brain functional alterations in SLE are predominantly found in the default mode network and the limbic system. These findings uncovered a consistent pattern of resting-state functional network abnormalities in SLE which may serve as a potential objective neuroimaging biomarker. • This study is the first meta-analysis to investigate the resting-state functional alterations in SLE. • SLE-related brain abnormalities are predominantly found in the default mode network and the limbic system. • Resting-state fMRI may be an objective neuroimaging biomarker for identifying brain abnormalities in SLE. [ABSTRACT FROM AUTHOR]

Psilocybin is a serotonergic psychedelic drug under assessment as a potential therapy for treatment-resistant and major depression. Heterogeneous treatment responses raise interest in predicting the outcome from baseline data. A machine learning pipeline was implemented to investigate baseline resting-state functional connectivity measured with functional magnetic resonance imaging (fMRI) as a predictor of symptom severity in psilocybin monotherapy for treatment-resistant depression (16 patients administered two 5 mg capsules followed by 25 mg, separated by one week). Generalizability was tested in a sample of 22 patients who participated in a psilocybin vs. escitalopram trial for moderate-to-severe major depression (two separate doses of 25 mg of psilocybin 3 weeks apart plus 6 weeks of daily placebo vs. two separate doses of 1 mg of psilocybin 3 weeks apart plus 6 weeks of daily oral escitalopram). The analysis was repeated using both samples combined. Functional connectivity of visual, default mode and executive networks predicted early symptom improvement, while the salience network predicted responders up to 24 weeks after treatment (accuracy≈0.9). Generalization performance was borderline significant. Consistent results were obtained from the combined sample analysis. Fronto-occipital and fronto-temporal coupling predicted early and late symptom reduction, respectively. The number of participants and differences between the two datasets limit the generalizability of the findings, while the lack of a placebo arm limits their specificity. Baseline neurophysiological measurements can predict the outcome of psilocybin treatment for depression. Future research based on larger datasets should strive to assess the generalizability of these predictions. • Baseline connectivity predicted responders up to 24 weeks after psilocybin treatment. • Visual, default mode and executive networks predicted early improvement. • Salience network was relevant for the prediction of late responders to treatment. • Fronto-occipital and fronto-temporal coupling predicted early and late improvement. [ABSTRACT FROM AUTHOR]

• High definition motor cortex tDCS in migraine patients decreased BOLD signal variability in the thalamus assessed with fMRI and increased it in the rostral anterior cingulate cortex. • The active tDCS group showed altered functional connectivity, assessed with fMRI, in both ascending trigeminal somatosensory and descending pain pathways. • Changes in BOLD signal variability in the thalamic medial pulvinar nucleus mediated the reduction in moderate-to-severe headache days. This study investigated how high-definition transcranial direct current stimulation (HD-tDCS) over the primary motor cortex (M1) affects brain signal variability and functional connectivity in the trigeminal pain pathway, and their association with changes in migraine attacks. Twenty-five episodic migraine patients were randomized for ten daily sessions of active or sham M1 HD-tDCS. Resting-state blood-oxygenation-level-dependent (BOLD) signal variability and seed-based functional connectivity were assessed pre- and post-treatment. A mediation analysis was performed to test whether BOLD signal variability mediates the relationship between treatment group and moderate-to-severe headache days. The active M1 HD-tDCS group showed reduced BOLD variability in the spinal trigeminal nucleus (SpV) and thalamus, but increased variability in the rostral anterior cingulate cortex (rACC) compared to the sham group. Connectivity decreased between medial pulvinar-temporal pole, medial dorsal-precuneus, and the ventral posterior medial nucleus-SpV, but increased between the rACC-amygdala, and the periaqueductal gray-parahippocampal gyrus. Changes in medial pulvinar variability mediated the reduction in moderate-to-severe headache days at one-month post-treatment. M1 HD-tDCS alters BOLD signal variability and connectivity in the trigeminal somatosensory and modulatory pain system, potentially alleviating migraine headache attacks. M1 HD-tDCS realigns brain signal variability and connectivity in migraineurs closer to healthy control levels. [ABSTRACT FROM AUTHOR]

Late-life depression (LLD) is associated with risk of dementia, yet intervention of LLD provides an opportunity to attenuate subsequent cognitive decline. Omega-3 polyunsaturated fatty acids (PUFAs) supplement is a potential intervention due to their beneficial effect in depressive symptoms and cognitive function. To explore the underlying neural mechanism, we used resting-state functional MRI (rs-fMRI) before and after omega-3 PUFAs supplement in older adults with LLD. A 52-week double-blind randomized controlled trial was conducted. We used multi-scale sample entropy to analyze rs-fMRI data. Comprehensive cognitive tests and inflammatory markers were collected to correlate with brain entropy changes. A total of 20 patients completed the trial with 11 under omega-3 PUFAs and nine under placebo. While no significant global cognitive improvement was observed, a marginal enhancement in processing speed was noted in the omega-3 PUFAs group. Importantly, participants receiving omega-3 PUFAs exhibited decreased brain entropy in left posterior cingulate gyrus (PCG), multiple visual areas, the orbital part of the right middle frontal gyrus, and the left Rolandic operculum. The brain entropy changes of the PCG in the omega-3 PUFAs group correlated with improvement of language function and attenuation of interleukin-6 levels. Sample size is small with only marginal clinical effect. These findings suggest that omega-3 PUFAs supplement may mitigate cognitive decline in LLD through anti-inflammatory mechanisms and modulation of brain entropy. Larger clinical trials are warranted to validate the potential therapeutic implications of omega-3 PUFAs for deterring cognitive decline in patients with late-life depression. • Brain entropy decreased in left posterior cingulate gyrus (PCC) and various brain regions after omega-3 PUFAs use in late-life depressed patients. • The reduction of brain entropy in left PCG correlated with improvement in language function and IL-6 level. • Only marginal improvement in processing speed was found clinically after omega-3 PUFAs supplement. • The anti-inflammatory and beneficial cognitive effects of omega-3 PUFAs in late-life depression are associated with brain entropy changes in left PCG. [ABSTRACT FROM AUTHOR]

• The pain-related network exhibits abnormalities in GAD with pain symptoms. • Pain symptoms in GAD are linked to an increase in regional homogeneity within the left anterior insula. • The thalamus exhibits a decrease in gray matter volume, correlating with somatic symptoms in GAD. Pain symptoms significantly impact the well-being and work capacity of individuals with generalized anxiety disorder (GAD), and hinder treatment and recovery. Despite existing literature focusing on the neural substrate of pain and anxiety separately, further exploration is needed to understand the possible neuroimaging mechanisms of the pain symptoms in GAD patients. We recruited 73 GAD patients and 75 matched healthy controls (HC) for clinical assessments, as well as resting-state functional and structural magnetic resonance imaging scans. We defined a pain-related network through a published meta-analysis, including the insula, thalamus, periaqueductal gray, prefrontal cortex, anterior cingulate cortex, amygdala, and hippocampus. Subsequently, we conducted the regional homogeneity (ReHo) and the gray matter volume (GMV) within the pain-related network. Correlation analysis was then employed to explore associations between abnormal regions and self-reported outcomes, assessed using the Patient Health Questionnaire-15 (PHQ-15) and pain scores. We observed significantly increased ReHo in the bilateral insula but decreased GMV in the bilateral thalamus of GAD compared to HC. Further correlation analysis revealed a positive correlation between ReHo of the left anterior insula and pain scores in GAD patients, while a respective negative correlation between GMV of the bilateral thalamus and PHQ-15 scores. In summary, GAD patients exhibit structural and functional abnormalities in pain-related networks. The enhanced ReHo in the left anterior insula is correlated with pain symptoms, which might be a crucial brain region of pain symptoms in GAD. [ABSTRACT FROM AUTHOR]

Post-stroke fatigue (PSF) was a common complication after stroke. This study aimed to explore the neuroimaging mechanism of PSF, which was rarely studied. Patients with the first episode of ischemic stroke were recruited from the First Affiliated Hospital of Wenzhou Medical University between March 2021 and December 2022. The fatigue severity scale (FSS) was used to assess fatigue symptoms. PSF was diagnosed by a neurologist based on the FSS score and PSF diagnostic criteria. All the patients were scanned by resting-state functional MRI (rs-fMRI). Precuneus, the posterior node of default-mode network (pDMN), was related to fatigue. Therefore, imaging data were further analyzed by the seed-based resting-state functional connectivity (FC) approach, with the left (PCUN.L) and right precuneus (PCUN.R) being the seeds. A total of 70 patients with acute ischemic stroke were finally recruited, comprising 40 patients with PSF and 30 patients without PSF. Both the PCUN.L and PCUN.R seeds (pDMN) exhibited decreased FC with the prefrontal lobes located at the anterior part of DMN (aDMN), and the FC values were negatively correlated with FSS scores (both p < 0.001). These two seeds also exhibited increased FC with the right insula, and the FC values were positively correlated with FSS scores (both p < 0.05). The abnormal FC between the aDMN and pDMN was associated with PSF. Besides, the insula, related to interoception, might also play an important role in PSF. • Post-stroke fatigue exerts a severe impact on patients. • There is a relationship between the Default Mode Network and fatigue. • Insula plays an important role in post-stroke fatigue. [ABSTRACT FROM AUTHOR]

To evaluate the effect of acupuncture on anisometropic amblyopia (AA) and explore its potential mechanism for children with AA. Seventy-six children with monocular AA were randomized into a conventional treatment group and a combined treatment group of acupuncture and conventional treatment, with 38 patients in each group. In the conventional treatment group, on the base of patching regimen, the red flashing, grating and visual stimulation were delivered. Each approach lasted for 5 min per session and was given once every two days, three times a week, for 4 consecutive weeks. In the acupuncture-combined treatment group, on the base of the regimen of conventional treatment group, acupuncture was applied to Jingming (BL1), Cuanzhu (BL2), Fengchi (GB20) and Guangming (GB37), with needles retained for 20 min per session, once every two days, three times of intervention a week and for 4 consecutive weeks. Before and after treatment, the best corrected vision acuity (BCVA) was observed to evaluate the clinical effect in the two groups. Before treatment started, 15 patients with AA on left side were randomized selected from each group and the resting-state functional magnetic resonance imaging (rs-fMRI) was operated before and after treatment. Simultaneously, eight healthy children with normal visual acuity were recruited to be the normal control group and received one-time rs-fMRI scanning. Based on the activation likelihood estimation (ALE), the visual "what" pathway network was constructed. By analyzing the amplitude of low frequency fluctuation (ALFF) and the regional homogeneity (ReHo), the differences in the regional autonomous function activities in the key brain areas of the "what" pathway were compared among the three groups. (1) Clinical effect: After treatment, BCVA was (0.6 [0.5, 0.6]), higher than that (0.4 [0.3, 0.5]) before treatment, presenting the statistical difference (P < 0.05) in the conventional treatment group. BCVA was (0.6 [0.6, 0.8]), higher than that (0.4 [0.4, 0.5]) before treatment, presenting the statistical difference (P < 0.05) in the acupuncture-combined treatment group. BCVA in the acupuncture-combined treatment group was higher than that of the conventional treatment group (P < 0.05) after treatment. The total effective rate was 86.1% in the acupuncture-combined treatment group, higher than that (65.8%) of the conventional treatment group (P < 0.05). (2) Mechanism: ① ALFF: In comparison with the healthy control group, the ALFF in the primary visual cortex of the "what" pathway for AA children was reduced significantly (P < 0.05), and ALFF in the right fusiform gyrus and the right inferior temporal gyrus increased significantly when compared with the healthy children (P < 0.05). Compared with that before treatment, there was no significant difference in the brain areas of the "what" pathway after treatment in the conventional treatment group (P > 0.05). In the acupuncture-combined treatment group, ALFF in the right inferior occipital gyrus and the right fusiform gyrus of the "what" pathway increased after treatment when compared with that before treatment (P < 0.05). After treatment, in comparison with the conventional treatment group, there was no significant difference in the brain areas of "what" pathway in the acupuncture-combined treatment group (P > 0.05). ② ReHo: ReHo in the right inferior occipital gyrus, the right fusiform gyrus and the right inferior temporal gyrus in the "what" pathway was elevated significantly in AA children when compared with that in the healthy control group (P < 0.05). ReHo of the left inferior occipital gyrus and the left fusiform gyrus increased significantly after treatment when compared with that before treatment in the conventional treatment group (P <0.05). ReHo of the right inferior occipital gyrus, the left and the right fusiform gyrus increased significantly after treatment when compared with that before treatment in the acupuncture-combined treatment group (P < 0.05). After treatment, ReHo of the right inferior temporal gyrus in the "what" pathway in the acupuncture-combined treatment group was significantly higher than that of the conventional treatment group (P < 0.05). The acupuncture combined with conventional treatment improves BCVA and the total effective rate of AA children. The changes in the regional function activity of the brain areas within the "what" pathway were dominated by the compensatory increase of the autonomous activity in the occipital lobe (inferior occipital gyrus) and the temporal lobe (inferior temporal gyrus) in AA children. Both conventional treatment and acupuncture can enhance the intensity of autonomous function activities in the occipital lobe (inferior occipital gyrus) and the temporal lobe (fusiform gyrus / inferior temporal gyrus) in the "what" pathway so as to relieve visual impairment. ReHo in the inferior temporal gyrus in the acupuncture-combined treatment group was higher than that of the conventional treatment group and it suggests that the inferior temporal gyrus may be the key brain area to the improvement of visual function in the "what" pathway. [ABSTRACT FROM AUTHOR]

In acute brain injury of neonates, resting-state functional magnetic resonance imaging (MRI) (RS) showed incremental association with consciousness, mortality, cognitive and motor development, and epilepsy, with correction for multiple comparisons, at six months postgestation in neonates with suspected acute brain injury (ABI). However, there are relatively few developmental milestones at six months to benchmark against, thus, we extended this cohort study to evaluate two-year outcomes. In 40 consecutive neonates with ABI and RS, ordinal scores of resting-state networks; MRI, magnetic resonance spectroscopy, and electroencephalography; and up to 42-month outcomes of mortality, general and motor development, Pediatric Cerebral Performance Category Scale (PCPC), and epilepsy informed associations between tests and outcomes. Mean gestational age was 37.8 weeks, 68% were male, and 60% had hypoxic-ischemic encephalopathy. Three died in-hospital, four at six to 42 months, and five were lost to follow-up. Associations included basal ganglia network with PCPC (P = 0.0003), all-mortality (P = 0.005), and motor (P = 0.0004); language/frontoparietal network with developmental delay (P = 0.009), PCPC (P = 0.006), and all-mortality (P = 0.01); default mode network with developmental delay (P = 0.003), PCPC (P = 0.004), neonatal intensive care unit mortality (P = 0.01), and motor (P = 0.009); RS seizure onset zone with epilepsy (P = 0.01); and anatomic MRI with epilepsy (P = 0.01). For the first time, at any age, resting state functional MRI in ABI is associated with long-term epilepsy and RSNs predicted mortality in neonates. Severity of RSN abnormality was associated with incrementally worsened neurodevelopment including cognition, language, and motor function over two years. [ABSTRACT FROM AUTHOR]

• Our study explored the executive function deficits(EFD) after trauma exposed. • The adult who has lost their only child is a special type of trauma. • The results of the excessive connection between the anterior insula and DMN might contribute to EFD after trauma exposed. There is increasing evidence that major trauma can adversely affect the brain and cognition. In some cases, trauma may lead to deficits in executive function (EF). The anterior insula may be a causal outflow hub acting to coordinate EF-related brain networks. To clarify the neural underpinnings of EF deficits (EFD) after trauma, we performed a resting-state functional magnetic resonance imaging (rs-fMRI) study of anterior insular subnetworks in adults who have lost their only child. A total of 167 participants completed various psychological and cognitive assessments to assess EF-related deficits. Correlations were computed between abnormal connectivity and cognitive/post-traumatic stress symptoms. The results showed abnormal anterior insular subregion connectivity in the default mode network (DMN), prefrontal lobe, and cerebellum lobe in participants with EFD. No correlation was found between abnormal connectivity and cognitive/post-traumatic stress symptoms in participants with EFD. These results suggest that excessive connections between the insula and DMN could contribute to EFD after trauma. Overall, this study provides novel references into the neural mechanisms of EF status after trauma exposure. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is associated with increased cardiac morbidity. Reduced heart rate variability (HRV) as well as lower interoceptive accuracy (IAc) have been observed in MDD as possible sympathomimetic mechanisms related to insula activity. The salience network (SN) anchored by the insula has been posited as a crucial functional network for cardiac sensations and the default mode network (DMN) for MDD. This study aimed to investigate the relation between insula-centered and depression-related brain networks, IAc and HRV in patients with depression as a possible mechanism by which MDD increases cardiac morbidity. 30 depressed inpatients and 30 healthy subjects (derived from the population-based "Characteristics and Course of Heart Failure Stages A-B and Determinants of Progression" cohort study, STAAB) all over 50 years were examined. HRV and IAc were assessed via electrocardiogram and a heartbeat perception task prior to a 3 T resting-state functional magnetic resonance imaging. Seed-to-voxel resting-state functional connectivity (FC) analysis was conducted with six seeds in the insula and two seeds in the DMN. Depressed patients on the one hand showed decreased FC between insula cortex and frontal as well occipital cortical brain regions compared to controls. Depressed patients on the other hand exhibited higher FC between the medial prefrontal cortex and the insula cortex compared to controls. However, depressed patients did not differ in HRV nor in IAc compared to controls. Thus, differences in insula-related brain networks in depression in our study were not mirrored by differences in HRV and IAc. Future research is needed to define the mechanism by which depression increases cardiac morbidity. [ABSTRACT FROM AUTHOR]

• PTSD patients exhibit both functional and structural anomalies within the DMN. • DMN alterations may be used to differentiate PTSD patients from controls. • Multimodal fusion MRI offers a comprehensive viewpoint on PTSD alterations. Diagnosing posttraumatic stress disorder (PTSD) using only single-modality images is controversial. We aimed to use multimodal magnetic resonance imaging (MRI) combining structural, diffusion, and functional MRI to possibly provide a more comprehensive viewpoint on the decisive characteristics of PTSD patients. Typhoon-exposed individuals with (n = 26) and without PTSD (n = 32) and healthy volunteers (n = 30) were enrolled. Five MRI features from three modalities, including two resting-state functional MRI (rs-fMRI) features (amplitude of low-frequency fluctuation, ALFF; and regional homogeneity, ReHo), one structural MRI feature (gray matter density, GM), and two diffusion tensor imaging (DTI) features (fractional anisotropy, FA; and mean diffusivity, MD) were investigated simultaneously with a multimodal canonical correlation analysis + joint independent component analysis model to identify abnormalities in the PTSD brain. We identified statistical differences between PTSD patients and healthy controls in terms of 1 rs-fMRI (ALFF, ReHo) alterations in the superior frontal gyrus, precuneus, inferior parietal lobule (IPL), anterior cingulate cortex (ACC), and posterior cingulate cortex (PCC), 2 DTI (FA, MD) changes in the pons, genu, and splenium of the corpus callosum, and 3 Structural MRI abnormalities in the precuneus, IPL, ACC, and PCC. A novel ReHo component was found to distinguish PTSD and trauma-exposed controls, including the precuneus, IPL, middle frontal gyrus, middle occipital gyrus, and cerebellum. This study reveals that PTSD individuals exhibit intertwined functional and structural anomalies within the default mode network. Some alterations within this network may serve as a potential marker to distinguish between PTSD patients and trauma-exposed controls. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11–93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder. [ABSTRACT FROM AUTHOR]

Older adults often experience more fragmented and less restful sleep than younger individuals. However, the mechanisms in the brain that underlie these phenomena have been rarely studied. The aim of this study was to identify the differences in global brain network properties between older adults with good and poor sleep quality and to explore the relationship between these network properties and symptoms of insomnia. We performed a graph-theoretic analysis of resting-state functional magnetic resonance imaging data from two groups of older adults: 59 with good sleep quality and 59 with poor sleep quality. Functional connectivity among 264 brain regions of interest was estimated, and undirected graphs were constructed. Network topological properties were compared using one-way repeated-measures analysis of variance. Pearson's correlation analysis assessed the relationship between the mean scores of the global network properties across network sparsity and insomnia symptoms, as measured using the global Pittsburgh Sleep Quality Index score. Older adults with poor sleep quality displayed increased small-world-ness, global efficiency and modularity in the functional brain network during rest. Conversely, they exhibited decreased local efficiency, characteristic path length and clustering coefficient. In the total population, we found associations between insomnia symptoms and global network characteristics, except for betweenness centrality and modularity. In older adults with poor sleep quality, global network measures revealed a functional brain architecture that tended towards integration rather than segregation. Further research is needed to better understand what these findings mean about the effects of aging on poor sleep quality. [ABSTRACT FROM AUTHOR]

Brain functional abnormalities have been commonly reported in anxiety disorders, including generalized anxiety disorder, social anxiety disorder, panic disorder, agoraphobia, and specific phobias. The role of functional abnormalities in the discrimination of these disorders can be tested with machine learning (ML) techniques. Here, we aim to provide a comprehensive overview of ML studies exploring the potential discriminating role of functional brain alterations identified by functional magnetic resonance imaging (fMRI) in anxiety disorders. We conducted a search on PubMed, Web of Science, and Scopus of ML investigations using fMRI as features in patients with anxiety disorders. A total of 12 studies (resting-state fMRI n = 5, task-based fMRI n = 6, resting-state and task-based fMRI n=1) met our inclusion criteria. Overall, the studies showed that, regardless of the classifiers, alterations in functional connectivity and aberrant neural activation involving the amygdala, anterior cingulate cortex, hippocampus, insula, orbitofrontal cortex, temporal pole, cerebellum, default mode network, dorsal attention network, sensory network, and affective network were able to discriminate patients with anxiety from controls, with accuracies spanning from 36 % to 94 %. The small sample size, different ML approaches and heterogeneity in the selection of regions included in the multivariate pattern analyses limit the conclusions of the present review. ML methods using fMRI as features can distinguish patients with anxiety disorders from healthy controls, indicating that these techniques could be used as a helpful tool for the diagnosis and the development of more targeted treatments for these disorders. • fMRI has the potential to predict anxiety disorder subtypes. • The review summarizes ML studies exploring this potential in patients and HC. • Insula and DMN create the most discriminative patterns in fMRI. • ML applied to fMRI is able to distinguish subtypes of anxiety disorders. • Results need to be replicated in bigger and more homogeneous samples. [ABSTRACT FROM AUTHOR]

Distinguishing bipolar disorder (BD) and unipolar disorder (UD) remains challenging. To identify the common and diagnosis-specific neuropathological alterations and their potential molecular mechanisms in patients with UD and BD (with a current depressive episode). Resting-state functional magnetic resonance imaging was obtained from 279 participants (95 BD patients, 107 UD patients and 77 health controls). Connectome gradients analysis was performed to explore the shared and diagnosis-specific gradient alterations in BD and UD. The Allen Human Brain Atlas data was used to explore the potential gene mechanisms of the gradient alterations. BD and UD had shared hierarchical disorganisation, including downgrading and contraction from the unimodal sensory networks (vision and sensorimotor) to the transmodal cognitive networks (limbic, frontoparietal, dorsal attention, and default) (all P < 0.05, FDR corrected) in gradient 1 and gradient 2. The BD patients had specific connectome gradient dysfunction in the subcortical network. Moreover, the hierarchical disorganisation was closely correlated with profiles of gene expression specific to the neuroglial cells in the prefrontal cortex in BD and UD, while the most correlated gene ontology biological processes and function were concentrated in synaptic signalling, calcium ion binding, and transmembrane transporter activity. These findings reveal the shared and diagnosis-specific neurobiological mechanism underlying BD and UD patients, which advances our understanding of the neuromechanisms of these disorders. • BD and UD had shared connectome gradient dysfunction and gene expression profiles. • BD had diagnosis-specific connectome gradient dysfunction in the subcortical network. [ABSTRACT FROM AUTHOR]

Decreased physical fitness and being overweight are highly prevalent in schizophrenia, represent a major risk factor for comorbid cardio-vascular diseases and decrease the life expectancy of the patients. Thus, it is important to understand the underlying mechanisms that link psychopathology and weight gain. We hypothesize that the dopaminergic reward system plays an important role in this. We analyzed the seed-based functional connectivity (FC) of the ventral tegmental area (VTA) in a group of schizophrenic patients (n =32) and age-, as well as gender-, matched healthy controls (n =27). We then correlated the resting-state results with physical fitness parameters, obtained in a fitness test, and psychopathology. The FC analysis revealed decreased functional connections between the VTA and the anterior cingulate cortex (ACC), as well as the dorsolateral prefrontal cortex, which negatively correlated with psychopathology, and increased FC between the VTA and the middle temporal gyrus in patients compared to healthy controls, which positively correlated with psychopathology. The decreased FC between the VTA and the ACC of the patient group further positively correlated with total body fat (p =.018, FDR-corr.) and negatively correlated with the overall physical fitness (p =.022). This study indicates a link between decreased physical fitness and higher body fat with functional dysconnectivity between the VTA and the ACC. These findings demonstrate that a dysregulated reward system might also be involved in comorbidities and could pave the way for future lifestyle therapy interventions. [ABSTRACT FROM AUTHOR]

Caudate functional abnormalities have been identified as one critical neural substrate underlying sensory gating impairments that lead to auditory phantom hallucinations in both patients with schizophrenia (SZ) and tinnitus, characterized by the perception of internally generated sounds in the absence of external environmental auditory stimuli. In this study, we tested the hypothesis as to whether functional connectivity abnormalities in distinct caudate subdivisions implicated in sensory gating and auditory phantom percepts in tinnitus, which are currently being localized for neuromodulation targeting using deep brain stimulation techniques, would be associated with auditory phantom hallucination severity in SZ. Twenty five SZ and twenty eight demographically-matched healthy control (HC) participants, completed this fMRI resting-state study and clinical assessments. Between-group seed-to-voxel analyses revealed only one region, the caudate anterior head, which showed reduced functional connectivity with the thalamus that survived whole-brain multiple comparison corrections. Importantly, connectivity between the caudate anterior head with thalamus negatively correlated with hallucination severity. In the present study, we deliver the first evidence of caudate subdivision specificity for the neural pathophysiology underlying hallucinations in schizophrenia within a sensory gating framework that has been developed for auditory phantoms in patients with tinnitus. Our findings provide transdiagnostic convergent evidence for the role of the caudate in the gating of auditory phantom hallucinations, observed across patients with SZ and tinnitus by specifying the anterior caudate division is key to mediation of hallucinations, and creating a path towards personalized treatment approaches to arrest auditory phantom hallucinations from reaching perceptual awareness. [ABSTRACT FROM AUTHOR]

Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials. [ABSTRACT FROM AUTHOR]

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. 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. 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. 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. Netherlands Trial Register, August 18, 2015, trial number NL53205.042.15. [ABSTRACT FROM AUTHOR]

• There are differences in attention and memory function among PBD patients with different first-episode symptoms. • SN, DMN, ECN and LN showed abnormalities in PBD patients with different first-episode symptoms. • There is an association between cognitive deficits and abnormal brain function in PBD patients. • First-episode symptoms are important for understanding the pathogenesis of PBD. Bipolar disorder may begin as depression or mania, which can affect the treatment and prognosis of bipolar disorder. However, the physiological and pathological differences of pediatric bipolar disorder (PBD) patients with different onset symptoms are not clear. The purpose of this study was to investigate the differences of clinical, cognitive function and intrinsic brain networks in PBD patients with first-episode depression and first-episode mania. A total of 63 participants, including 43 patients and 20 healthy controls, underwent resting-state fMRI scans. PBD patients were classified as first-episode depressive and first-episode manic based on their first-episode symptoms. Cognitive tests were used to measure attention and memory of all participants. Independent component analysis (ICA) was used to extract the salience network (SN), default-mode network (DMN), central executive network (ECN) and limbic network (LN) for each participant. Spearman rank correlation analysis was performed between abnormal activation and clinical and cognitive measures. The results showed that there were differences in cognitive functions such as attention and visual memory between first-episode depression and mania, as well as differences activation in anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), precuneus, inferior parietal cortex and parahippocampus. And significant associations of brain activity with clinical assessments or cognition were found in different patients. In conclusion, we found differential impairments in cognitive and brain network activation in first-episode depressive and first-episode manic PBD patients, and correlations were found between these impairments. These evidences may shed light on the different developmental paths of bipolar disorder. [ABSTRACT FROM AUTHOR]

• We delineated brain network correlates of two executive functions in older adults. • Frontoparietal functional connectivity was linked to working memory updating. • Cortico-basal ganglia functional connectivity was linked to decision-making. • Frontoparietal tract integrity was associated with updating, but not decision-making. • Function-specific targeted modulation of brain networks may delay cognitive decline. Executive functions, essential for daily life, are known to be impaired in older age. Some executive functions, including working memory updating and value-based decision-making, are specifically sensitive to age-related deterioration. While their neural correlates in young adults are well-described, a comprehensive delineation of the underlying brain substrates in older populations, relevant to identify targets for modulation against cognitive decline, is missing. Here, we assessed letter updating and Markov decision-making task performance to operationalize these trainable functions in 48 older adults. Resting-state functional magnetic resonance imaging was acquired to quantify functional connectivity (FC) in task-relevant frontoparietal and default mode networks. Microstructure in white matter pathways mediating executive functions was assessed with diffusion tensor imaging and quantified by tract-based fractional anisotropy (FA). Superior letter updating performance correlated with higher FC between dorsolateral prefrontal cortex and left frontoparietal and hippocampal areas, while superior Markov decision-making performance correlated with decreased FC between basal ganglia and right angular gyrus. Furthermore, better working memory updating performance was related to higher FA in the cingulum bundle and the superior longitudinal fasciculus. Stepwise linear regression showed that cingulum bundle FA added significant incremental contribution to the variance explained by fronto-angular FC alone. Our findings provide a characterization of distinct functional and structural connectivity correlates associated with performance of specific executive functions. Thereby, this study contributes to the understanding of the neural correlates of updating and decision-making functions in older adults, paving the way for targeted modulation of specific networks by modulatory techniques such as behavioral interventions and non-invasive brain stimulation. [ABSTRACT FROM AUTHOR]

Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains. A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria. Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients. The heterogeneity of the reviewed studies, in terms of the cognitive domains explored and the neuroimaging acquisitions employed, limited the comparability of the findings. rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients. • This review highlights rs-fMRI correlations with executive functions (EF) and social cognition (SC) in Bipolar Disorder (BD) patients • The Default Mode Network (DMN), and especially the mPFC-PCC connections, seem to be involved in EF and SC deficits in BD patients • A relevant role of cerebellar connections and Sensory-Motor Network (SMN) in EF and SC was also observed. • Further studies are needed in order to better delineate the relationship between sensoriality, motility and cognition in BD. [ABSTRACT FROM AUTHOR]

Type A personality (TAP) was characterized by impatience, competitiveness, aggressiveness, and hostility. Higher TAP was proved to be associated with more eating disorder symptoms (EDS). While little is known about the underlying neural substrates of TAP and how TAP is linked to EDS at the neural level. To investigate the neural basis of TAP, we adopted fractional amplitude of low-frequency fluctuations (fALFF) and resting-state functional connectivity (RSFC) via resting-state functional magnetic resonance imaging (rs-fMRI) (N = 1620). Mediation models were examined to explore the relationship between TAP, EDS, and brain activity. TAP was associated with decreased fALFF in the left middle frontal gyrus (MFG) and increased fALFF in the left precentral gyrus (PreCG). Furthermore, TAP was positively correlated to RSFC between the left MFG and left inferior temporal gyrus (ITG) and between the left PreCG and right middle temporal gyrus (MTG). Mediation analysis showed TAP fully mediated the association of the left MFG activity, MFG-ITG connectivity, and PreCG-MTG connectivity with EDS. The cross-sectional design of this study precludes us from specifying the causal relationship in the associations we observed. Our results suggested spontaneous activity in the left MFG and PreCG is associated with TAP, and even in general sample, people with higher TAP showed more EDS. The present study is the first to investigate the neurobiological underpinnings of TAP in a large sample and further offered new insights into the relation between TAP and EDS from a neural basis perspective. • TAP was associated with spontaneous activity in the left MFG, PreCG, ITG, and right MTG. • Even in the general sample, people with higher levels of TAP showed more EDS. • TAP fully mediated the association of the left MFG activity, MFG-ITG connectivity, and PreG-MTG connectivity with EDS. [ABSTRACT FROM AUTHOR]

Ketamine has recently been proposed as a treatment option for suicidality. Whilst its mechanism of action has been explored at molecular levels, the effect on the brain at the organ level remains unclear. Here we investigate immediate post-treatment and prolonged large-scale resting-state neural network changes to elucidate the neuronal underpinnings associated with ketamine's therapeutic effects. Twenty-eight adults (aged 22–72 years) participated in the Oral Ketamine Trial On Suicidality, which is an open-label trial of weekly sub-anaesthetic doses of oral ketamine over 6 weeks. MRI was acquired at baseline, post-treatment, and follow-up. Functional connectivity changes at post-treatment and follow-up were examined using seed based and independent component analysis. The seed-based connectivity analysis revealed significantly reduced connectivity at post-treatment from the right hippocampus to both right and left superior frontal gyrus, from the left anterior parahippocampus to right superior frontal gyrus, left superior frontal gyrus, right middle frontal gyrus, and left frontal operculum cortex. Compared with baseline, the ICA showed reduced anterior default mode network connectivities to bilateral posterior cingulate cortex, middle and anterior cingulate cortex, lingual gyrus, and cuneus and increased connectivity of the frontoparietal network to the right superior parietal lobule at post-treatment. Open label pilot study. We have shown sub-anaesthetic doses of ketamine alters connectivity in networks which have been shown to be aberrantly hyper-connected in numerous psychiatric conditions. These neurocircuitry changes are supported by significant reductions in suicide ideation. Our results provide support for the use of ketamine as a treatment for suicidality. • Sub-anaesthetic doses of oral ketamine alters functional connectivity in networks implicated in emotional processing. • Changes in neurocircuitry are supported by significant reductions in suicide ideation. • Ketamine response path is similar to other antidepressants and provides support for ist use as a treatment for suicidality. [ABSTRACT FROM AUTHOR]

Electroconvulsive therapy (ECT) is a novel treatment strategy for adolescents with major depressive disorder (MDD). However, its related neurobiological changes associated with ECT remain undetermined. To elucidate the impact of ECT on the regional cerebral blood flow (CBF), and to identify alterations in the CBF associated with clinical outcomes in adolescents with MDD. Fifty-two treatment-naive adolescents who had experienced their first episode of MDD and 36 healthy controls (HCs) were recruited. To assess baseline parameters, all subjects were scanned with arterial spin labeling resting-state functional magnetic resonance imaging (ASL-fMRI) at the beginning of the study. Subsequently, 27 MDD adolescents were re-scanned after 2 weeks after ECT. CBF imaging was used for the prediction of specific clinical outcomes. Lastly, the associations between alterations seen on brain imaging alterations after ECT and ECT clinical efficacy (ΔHAMD scores) were determined. Relative to HCs, adolescents with MDD exhibited reduced CBF in the left medial superior frontal gyrus (SFGmed) (cluster = 243, peak t = −3.9373, and P < 0.001) and augmented CBF in the right percental gyrus (PerCG) (cluster = 321, peak t = 4.3332, and P < 0.001) at baseline. Following ECT, MDD adolescents exhibited reduced CBF in the right fusiform gyrus (FFG) (cluster = 309, peak t = −4.346, and P < 0.001) and left hippocampus (HIP) (cluster = 290, peak t = −4.706, and P < 0.001), and enhanced CBF in the left orbital part of the inferior frontal gyrus (ORBinf) (cluster = 214, peak t = 4.073, and P < 0.001). Correlation analysis suggested an inverse association between ΔHAMD scores and CBF values in the left ORBinf (R2 = 0.196, P = 0.021). It was found that ECT resulted in alterations in CBF in specific brain areas, highlighting the significance of ORBinf in ECT pathophysiology in MDD adolescents. • The fMRI neuroimaging showed that ECT was effective for treating first-episode MDD in treatment-naive adolescents. • This is the first ASL-based study showing a relationship between ECT treatment and altered CBF in these patients. • The results indicate that ORBinf is important for understanding the pathophysiology of cognitive issues. [ABSTRACT FROM AUTHOR]

The lack of effective objective diagnostic biomarkers for major depressive disorder (MDD) leads to high misdiagnosis. Compared with healthy controls (HC), abnormal brain functions and protein levels are often observed in MDD. However, it is unclear whether combining these changed multidimensional indicators could help improve the diagnosis of MDD. Sixty-three MDD and eighty-one HC subjects underwent resting-state fMRI scans, among whom 37 MDD and 45 HC provided blood samples. Amplitudes of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and serum levels of brain-derived neurotrophic factor (BDNF), cortisol, and multiple cytokines were measured and put into the linear discriminant analysis (LDA) to construct corresponding MDD diagnostic models. The area under the receiver operating characteristic curve (AUC) of 5-fold cross-validation was calculated to evaluate each model's performance. Compared with HC, MDD patients' spontaneous brain activity, serum BDNF, cortisol, interleukin (IL)-4, IL-6, and IL-10 levels changed significantly. The combinations of unidimensional multi-indicator had better diagnostic performance than a single one. The model consisted of multidimensional multi-indicator further exhibited conspicuously superior diagnostic efficiency than those constructed with unidimensional multi-indicator, and its AUC, sensitivity, specificity, and accuracy of 5-fold cross-validation were 0.99, 92.0 %, 100.0 %, and 96.3 %, respectively. This cross-sectional study consists of relatively small samples and should be replicated in larger samples with follow-up data to optimize the diagnostic model. MDD patients' neuroimaging features and serum protein levels significantly changed. The model revealed by LDA could diagnose MDD with high accuracy, which may serve as an ideal diagnostic biomarker for MDD. • Many imaging indicators and serum proteins changed markedly in depressed patients. • Changed indicators of imaging and protein are associated with clinical features. • Diagnostic power of multi-indicator model is better than a single indicator. • Multidimensional data model significantly improved the diagnosis of depression. [ABSTRACT FROM AUTHOR]

Hippocampal functional connectivity (FC) alterations, which may happen following ketamine treatment, play a key role in major depression remission. This study aims to investigate the resting-state FC changes of the hippocampus associated with clinical remission after repeated ketamine infusions. Forty-four major depressive patients received six intravenous ketamine (0.5 mg/kg) infusions in 12 days. The FC change of the hippocampus subregions following ketamine treatment was compared between remitters (MADRS score ≤ 10 post-treatment) and nonremitters. We also investigated whether baseline hippocampus FC predicted the antidepressant efficiency of ketamine using Receiver Operating Characteristic Curve analyses. Thirty-nine patients were included in the analysis. There were significant differences in change of left rostral hippocampus FC with the right angular gyrus (the key node of the default mode network, DMN), left inferior parietal cortex and the right superior parietal cortex (parts of the dorsal attention network, dAN) between remitters and nonremitters following ketamine treatment. Specifically, while the remitters showed significantly less negative hippocampus FC than the nonremitters at baseline, the FC significantly decreased in remitters but increased in nonremitters after ketamine injections. Moreover, baseline hippocampus FC with the above three regions predicted the antidepressant effect of ketamine, with the highest predictive strength identified in the hippocampus-right angular gyrus FC (Area-Under-Curve = 0.8179, p < 0.05). Ketamine treat depression by modulating the left rostral hippocampus resting-state FC with the DMN and dAN. The FC between the hippocampus and parts of the DMN and dAN may show promising potential in predicting remission after ketamine treatment in MDD. • We investigated the mechanism of ketamine in the treatment of MDD though rs-fMRI • The hippocampal functional connectivity alterations was associated with clinical remission in major depression and could predict the effect of ketamine before injection. • The variability and concordance of alterations of rs-fMRI indices could be useful in finding appropriate patients for ketamine. [ABSTRACT FROM AUTHOR]

• There were 4 recurring brain connectivity patterns across all subjects. • The temporal evolution of brain states was gradually altered with cognition decline. • A switch to strongly connected states was more difficult in patients than in controls. • The connectivity between attention and default network played a role in transition. Alterations in the temporal evolution of brain states in the process of cognitive impairment aggravation due to subcortical ischemic vascular disease (SIVD) is not understood. The dynamic functional connectivity was investigated to identify the abnormal temporal properties of brain states associated with cognitive impairment caused by SIVD. Eighteen patients with subcortical ischemic vascular cognitive impairment with no dementia (SIVCIND), 19 dementia patients (SIVaD) and 26 normal controls were enrolled. We found that the occupancy rate and mean lifetime of brain states were associated with cognitive performance. SIVCIND had a higher occupancy rate and longer mean lifetime in weakly connected states than normal controls. SIVaD had similar but more extensive changes in the temporal properties of brain states. In addition, switching from weakly connected states to more strongly connected states was more difficult in SIVCIND and SIVaD patients than in normal controls, especially in SIVaD patients. The results revealed that not only the transition to but also maintenance in strongly connected states became increasingly difficult when SIVD-related cognitive impairment progressed into a more severe stage. [ABSTRACT FROM AUTHOR]

Background: Emotion dysregulation (ED) is a common clinical feature of attention-deficit/hyperactivity disorder (ADHD). The present study examined the role of cognitive reappraisal (CR) and expressive suppression (ES) in adults with ADHD. In addition, resting-state fMRI (rs-fMRI) data were analyzed to identify neural substrates of CR/ES-ED relationships.Methods: A total of 309 adults with ADHD and 163 healthy controls were recruited. ED was assessed using the 'emotional control' (EC) subscale from Behavior Rating Inventory of Executive Function-Adult Version. The Emotion Regulation Questionnaire was used to measure CR and ES. The functional connectivities (FCs) with the amygdala as Region of Interest, were analyzed in a subsample to explore their association with CR, ES and EC, respectively.Results: Higher EC scores (indicative of lesser emotional control), as well as lower CR and higher ES utilization were detected in adults with ADHD compared with healthy controls. CR and ES were both negatively correlated with EC in adults with ADHD. Mediation analysis detected a potential effect of ADHD diagnosis on EC via CR. In addition, a unique significant mediation effect was found between ES-related FC of the right amygdala-prefrontal cortex and ED expression in adults with ADHD, confirming the '↑ES → ↓FCs [amygR-PFC] →↓EC' relationship.Limitations: Only self-reported scales and rs-fMRI data were included in these analyses.Conclusions: Our findings provide preliminary evidence that in adults with ADHD, less frequent use of CR accounts for ED expression, while more frequent use of ES may play a unique compensatory role in emotion regulation. [ABSTRACT FROM AUTHOR]

Objective: The resting-state functional magnetic resonance imaging (rs-fMRI) have been used to explore functional abnormality of the brain in MDD patients with suicidal ideation (SI). However, few studies reported the variability and concordance of alterations of rs-fMRI indices in MDD with SI. In this study, we aimed to explore the variability and concordance of alterations of rs-fMRI indices in MDD with SI.Methods: A sliding window analysis was performed among 36 MDD patients with SI, 66 MDD patients without SI (NSI), and 50 healthy controls (HCs). Furthermore, the correlation between voxel-wise concordance and cognitive function was examined in the SI group.Results: The SI group had a lower dynamics degree centrality (dDC) value than the NSI group in left inferior occipital gyrus, and a lower voxel mirrored homotopic connectivity (dVMHC) value than the NSI group in the right and left inferior occipital gyrus. The mean values of volume wise concordance of HCs group shown higher than SI group and NSI group. SI group revealed decreased voxel-wise concordance in right cerebellum, left fusiform gyrus, left lingual gyrus, right middle temporal gyrus, left postcentral gyrus, and right supplementary motor area compared to NSI group. Moreover, the voxel-wise concordance of left middle occipital gyrus was negatively correlated with verbal learning and memory and working memory in the SI group.Limitation: This is a cross-sectional analysis, limiting causal inferences.Conclusions: The abnormal voxel-wise concordance of left middle occipital gyrus could be useful in understanding the pathophysiology of MDD patients with SI. [ABSTRACT FROM AUTHOR]

There is growing interest in understanding the dynamic functional connectivity (DFC) between distributed brain regions. However, it remains challenging to reliably estimate the temporal dynamics from resting-state functional magnetic resonance imaging (rs-fMRI) due to the limitations of current methods. We propose a new model called HDP-HSMM-BPCA for sparse DFC analysis of high-dimensional rs-fMRI data, which is a temporal extension of probabilistic principal component analysis using Bayesian nonparametric hidden semi-Markov model (HSMM). Specifically, we utilize a hierarchical Dirichlet process (HDP) prior to remove the parametric assumption of the HMM framework, overcoming the limitations of the standard HMM. An attractive superiority is its ability to automatically infer the state-specific latent space dimensionality within the Bayesian formulation. The experiment results of synthetic data show that our model outperforms the competitive models with relatively higher estimation accuracy. In addition, the proposed framework is applied to real rs-fMRI data to explore sparse DFC patterns. The findings indicate that there is a time-varying underlying structure and sparse DFC patterns in high-dimensional rs-fMRI data. Compared with the existing DFC approaches based on HMM, our method overcomes the limitations of standard HMM. The observation model of HDP-HSMM-BPCA can discover the underlying temporal structure of rs-fMRI data. Furthermore, the relevant sparse DFC construction algorithm provides a scheme for estimating sparse DFC. We describe a new computational framework for sparse DFC analysis to discover the underlying temporal structure of rs-fMRI data, which will facilitate the study of brain functional connectivity. • Our method provides a novel scheme for sparse DFC estimation. • Our method overcomes the limitations of standard HMM. • The Bayesian inference makes the method free from model selection. [ABSTRACT FROM AUTHOR]

• Left amygdala connections linked to withdrawn/depressed (w/d) behaviors in a large sample of children from the ABCD study. • Left amygdala connections to an auditory network region linked to w/d behaviors. • Left amygdala connections to dorsal attention network regions linked to w/d behaviors. • Left amygdala connections to a frontoparietal network region linked to w/d behaviors • Social behaviors were linked to amygdala connections associated with w/d behaviors. Many psychopathologies tied to internalizing symptomatology emerge during adolescence, therefore identifying neural markers of internalizing behavior in childhood may allow for early intervention. We utilized data from the Adolescent Brain and Cognitive Development (ABCD) Study® to evaluate associations between cortico-amygdalar functional connectivity, polygenic risk for depression (PRS D), traumatic events experienced, internalizing behavior, and internalizing subscales: withdrawn/depressed behavior, somatic complaints, and anxious/depressed behaviors. Data from 6371 children (ages 9–11) were used to analyze amygdala resting-state fMRI connectivity to Gordon parcellation based whole-brain regions of interest (ROIs). Internalizing behaviors were measured using the parent-reported Child Behavior Checklist. Linear mixed-effects models were used to identify patterns of cortico-amygdalar connectivity associated with internalizing behaviors. Results indicated left amygdala connections to auditory, frontoparietal network (FPN), and dorsal attention network (DAN) ROIs were significantly associated with withdrawn/depressed symptomatology. Connections relevant for withdrawn/depressed behavior were linked to social behaviors. Specifically, amygdala connections to DAN were associated with social anxiety, social impairment, and social problems. Additionally, an amygdala connection to the FPN ROI and the auditory network ROI was associated with social anxiety and social problems, respectively. Therefore, it may be important to account for social behaviors when looking for brain correlates of depression. [ABSTRACT FROM AUTHOR]

The brain exhibits intrinsic dynamics characterized by spontaneous spatiotemporal reorganization of neural activity or metastability, which is associated closely with functional integration and segregation. Compared to dynamic functional connectivity, state-dependent effective connectivity (i.e., dynamic effective connectivity) is more suitable for exploring the metastability as its ability to infer causalities between brain regions. However, methods for state-dependent effective connectivity are scarce and urgently needed. In this study, a novel data-driven computational framework, named NHSMM-MAR-sdNC integrating nonparametric hidden semi-Markov model combined with multivariate autoregressive model and state-dependent new causality, is proposed to investigate the state-dependent effective connectivity. The framework is not constrained by any biological assumptions. Furthermore, state number can be inferred from the observed data directly and the state duration distributions will be estimated explicitly rather than restricted by geometric form, which overcomes limitations of hidden Markov model. Experimental results of synthetic data show that the framework can identify the state number adaptively and the state-dependent causality networks accurately. The dynamics of state-related causality networks are also revealed by the new method on real-world resting-state fMRI data. Our method provides a new data-driven computational framework for identifying state-dependent effective connectivity, which will facilitate the identification and assessment of metastability and itinerant dynamics of the brain. • NHSMM-MAR-sdNC is free from biophysical hypotheses and prior parameters. • NHSMM-MAR-sdNC overcomes the limitations of standard HMM. • NHSMM-MAR-sdNC can identify the state-dependent causality networks directly. [ABSTRACT FROM AUTHOR]

Hormonal changes in ovarian hormones like estradiol (E2) during the menstrual cycle affect emotional processes, including emotion recognition, memory, and regulation. So far, the neural underpinnings of the effect of E2 on emotional experience have been investigated using task-based functional magnetic resonance imaging (fMRI) and functional connectivity. In the present study, we examined whether the intrinsic network dynamics at rest (i.e., directed effective connectivity) related to emotion regulation are (1) modulated by E2 levels and (2) linked to behavioral emotion regulation ability. Hence, 29 naturally cycling women participated in two resting-state fMRI scans in their early follicular phase after being administered a placebo or an E2 valerate, respectively. Emotion regulation ability was assessed using a standard emotion regulation task in which participants were asked to down-regulate their emotions in response to negative images. The regions of two functionally predefined neural networks related to emotional down-regulation and reactivity were used to investigate effective connectivity at rest using spectral dynamic causal modelling. We found that E2, compared to placebo, resulted in changes in effective connectivity in both networks. In the regulation network, prefrontal regions showed distinct connectivity in the E2 compared to the placebo condition, while mixed results evolved in the emotional reactivity network. Stepwise regressions revealed that in the E2 condition a connection from the parietal to the prefrontal cortex predicted regulation ability. Our results demonstrate that E2 levels influence effective connectivity in networks underlying emotion regulation and emotional reactivity. Thus, E2 and its potential modification via hormonal administration may play a supporting role in the treatment of mental disorders that show a dysregulation of emotions. • Estradiol (E2) administration successfully elevated E2 levels in healthy females within 24hrs. • Using spectral dynamic causal modelling, we investigated effective connectivity at rest of two neural networks. • In the regulation network, prefrontal regions showed distinct connectivity in the E2 condition. • Effective connectivity from the parietal to the prefrontal cortex predicted regulation ability in the E2 condition. • Our results show that E2 levels influence emotion regulation and effective connectivity in the underlying neural networks. [ABSTRACT FROM AUTHOR]

[Display omitted] • Functional connectivity patterns of table tennis players are more flexible. • White matter structure of table tennis players is related to their attention level. • First probe of brain structure in table tennis players using high-field MRI. Table tennis training has been employed as an exercise treatment to enhance cognitive brain functioning in patients with mental illnesses. However, research on its underlying mechanisms remains limited. In this study, we investigated functional and structural changes in large-scale brain regions between 20 table tennis players (TTPs) and 21 healthy controls (HCs) using 7-Tesla magnetic resonance imaging (MRI) techniques. Compared with those of HCs, TTPs exhibited significantly greater fractional anisotropy (FA) and axial diffusivity (AD) values in multiple fiber tracts. We used the locations with the most significant structural changes in white matter as the seed areas and then compared static and dynamic functional connectivity (sFC and dFC). Brodmann 11, located in the orbitofrontal cortex, showed altered dFC values to large-scale brain regions, such as the occipital lobe, thalamus, and cerebellar hemispheres, in TTPs. Brodmann 48, located in the temporal lobe, showed altered dFC to the parietal lobe, frontal lobe, cerebellum, and occipital lobe. Furthermore, the AD values of the forceps minor (Fmi) and right anterior thalamic radiations (ATRs) were negatively correlated with useful field of view (UFOV) test scores in TTPs. Our results suggest that table tennis players exhibit a unique pattern of dynamic neural activity, this provides evidence for potential mechanisms through which table tennis interventions can enhance attention and other cognitive functions. [ABSTRACT FROM AUTHOR]

Global brain connectivity (GBC) enables measuring brain regions' functional connectivity strength at rest by computing the average correlation between each brain voxel's time-series and that of all other voxels. We used resting-state fMRI (rs-fMRI) data of young adult participants from the Human Connectome Project (HCP) dataset to explore the test-retest stability of GBC, the brain regions with higher or lower GBC, as well as the associations of this measure with age, sex, and fluid intelligence. GBC was computed by considering separately the positive and negative correlation coefficients (positive GBC and negative GBC). Test-retest stability was higher for positive compared to negative GBC. Areas with higher GBC were located in the default mode network, insula, and visual areas, while regions with lower GBC were in subcortical regions, temporal cortex, and cerebellum. Higher age was related to global reduction of positive GBC. Males displayed higher positive GBC in the whole brain. Fluid intelligence was associated to increased positive GBC in fronto-parietal, occipital and temporal regions. Compared to previous works, this study adopted a larger sample size and tested GBC stability using data from different rs-fMRI sessions. Moreover, these associations were examined by testing positive and negative GBC separately. Lower stability for negative compared to positive GBC suggests that negative correlations may reflect less stable couplings between brain regions. Our findings indicate a greater importance of positive compared to negative GBC for the associations of functional connectivity strength with biological and neurocognitive variables. • Global brain connectivity (GBC) reflects brain's most connected regions. • Positive GBC reflects more stable couplings between brain regions. • Higher age is related to lower positive GBC. • Males show higher positive GBC. • Fluid intelligence is related to higher positive GBC in fronto-parietal regions. [ABSTRACT FROM AUTHOR]

Background: Subclinical depression (SD) and major depressive disorder (MDD) can be considered as the early and late stages of depression, but the characteristics of intrinsic neural activity in different depressive stages are largely unknown.Methods: Twenty-six SD, 36 MDD subjects and 33 well-matched healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Voxel-wise regional homogeneity (ReHo) was analyzed to explore the alterations of intrinsic neural activity, and machine learning classification based on ReHo features was performed to assess potential performance for diagnostic classification.Results: Common alterations of ReHo in both SD and MDD groups were found in the bilateral middle temporal gyrus and the left middle occipital gyrus. Opposite alterations in SD and MDD groups were found in the right superior cerebellum. Moreover, increased ReHo in the bilateral precuneus was only found in MDD, while increased ReHo in the right middle frontal gyrus and precentral gyrus were unique to SD. The distinct ReHo values correctly identified SD, MDD, and HC by linear support vector machine (SVM) with an accuracy of 77.89 %, which further verified the discrimination ability of altered ReHo in these brain regions.Limitation: The sample size is relatively small.Conclusion: Common and unique ReHo alterations provided insights into the development of brain impairments in depression, and helped to understand the pathophysiology of SD and MDD. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment is common in Parkinson's disease (PD) and often leads to dementia, with no effective treatment. Aging studies suggest that physical activity (PA) intensity has a positive impact on cognition and enhanced functional connectivity may underlie these benefits. However, less is known in PD. This cross-sectional study examined the relationship between PA intensity, cognitive performance, and resting state functional connectivity in PD and whether PA intensity influences the relationship between functional connectivity and cognitive performance.Methods: 96 individuals with mild-moderate PD completed a comprehensive neuropsychological battery. Intensity of PA was objectively captured over a seven-day period using a wearable device (ActiGraph). Time spent in light and moderate intensity PA was determined based on standardized actigraphy cut points. Resting-state fMRI was assessed in a subset of 50 individuals to examine brain-wide functional connectivity.Results: Moderate intensity PA (MIPA), but not light PA, was associated with better global cognition, visuospatial function, memory, and executive function. Individuals who met the WHO recommendation of ≥150 min/week of MIPA demonstrated better global cognition, executive function, and visuospatial function. Resting-state functional connectivity associated with MIPA included a combination of brainstem, hippocampus, and regions in the frontal, cingulate, and parietal cortices, which showed higher connectivity across the brain in those achieving the WHO MIPA recommendation. Meeting this recommendation positively moderated the associations between identified functional connectivity and global cognition, visuospatial function, and language.Conclusion: Encouraging MIPA, particularly the WHO recommendation of ≥150 min of MIPA/week, may represent an important prescription for PD cognition. [ABSTRACT FROM AUTHOR]

Endometriosis is the leading cause of chronic pelvic pain. Alterations in brain functional connectivity have been reported in adult women with endometriosis-associated pain (EAP), however, it is still unknown if similar patterns of changes exist in adolescents. Methods : In this pilot study, resting-state fMRI scans were obtained from 11 adolescent and young women with EAP and 14 healthy female controls. Using a seed-to-voxel approach, we investigated functional connectivity between the anterior insula, medial prefrontal cortex, and the rest of the brain. Furthermore, we explored whether potential functional connectivity differences were correlated with clinical characteristics including disease duration, pain intensity, and different psychosocial factors (pain catastrophizing, fear of pain, functional disability, anxiety, and depression). Results : Our findings revealed that patients with EAP demonstrated significantly decreased connectivity between the right anterior insula and two clusters: one in the right cerebellum, and one in the left middle frontal gyrus compared to controls. Additionally, functional connectivity between the right anterior insula and the right cerebellum was positively associated with pain intensity levels. In patients with EAP, brain changes were also correlated with state anxiety and fear of pain. Conclusions: Our results are relevant not only for understanding the brain characteristics underlying EAP at a younger age, but also in enhancing future pain treatment efforts by supporting the involvement of the central nervous system in endometriosis. • Altered brain function in young patients with endometriosis-associated pain (EAP). • Less functional connectivity between the right anterior insula and pain-related regions. • Anterior insula and cerebellum connectivity was linked to greater pain intensity. • Alterations in the pain regulatory pathways in endometriosis. • Endometriosis management should include centrally mediated treatments. [ABSTRACT FROM AUTHOR]

Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging–based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism. [ABSTRACT FROM AUTHOR]

Background: Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD.Methods: A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3.Results: 25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm3, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm3, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions.Conclusion: Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD. [ABSTRACT FROM AUTHOR]

Background: COVID-19 is an infectious disease that has spread worldwide in 2020, causing a severe pandemic. In addition to respiratory symptoms, neuropsychiatric manifestations are commonly observed, including chronic fatigue, depression, and anxiety. The neural correlates of neuropsychiatric symptoms in COVID-19 are still largely unknown.Methods: A total of 79 patients with COVID-19 (COV) and 17 healthy controls (HC) underwent 3 T functional magnetic resonance imaging at rest, as well as structural imaging. Regional homogeneity (ReHo) was calculated. We also measured depressive symptoms with the Patient Health Questionnaire (PHQ-9), anxiety using the General Anxiety Disorder 7-item scale, and fatigue with the Multidimension Fatigue Inventory.Results: In comparison with HC, COV showed significantly higher depressive scores. Moreover, COV presented reduced ReHo in the left angular gyrus, the right superior/middle temporal gyrus and the left inferior temporal gyrus, and higher ReHo in the right hippocampus. No differences in gray matter were detected in these areas. Furthermore, we observed a negative correlation between ReHo in the left angular gyrus and PHQ-9 scores and a trend toward a positive correlation between ReHo in the right hippocampus and PHQ-9 scores.Limitations: Heterogeneity in the clinical presentation in COV, the different timing from the first positive molecular swab test to the MRI, and the cross-sectional design of the study limit the generalizability of our findings.Conclusions: Our results suggest that COVID-19 infection may contribute to depressive symptoms via a modulation of local functional connectivity in cortico-limbic circuits. [ABSTRACT FROM AUTHOR]

Background: While previous neuroimaging studies are mainly focused on dichotomous classification of obsessive-compulsive disorder (OCD) from controls, predicting continuous severity of specific symptom is also pivotal to clinical diagnosis and treatment.Methods: We applied a machine-learning approach, connectome-based predictive modeling, on functional and structural brain networks constructed from resting-state functional magnetic resonance imaging and diffusion tensor imaging data to decode compulsions and obsessions of fifty-four patients with OCD.Results: We successfully predicted individualized compulsions with a positive model of structural brain network and with a negative model of functional brain network. The structural predictive brain network comprises the motor cortex, cerebellum and limbic lobe, which are involved in basic motor control, motor execution and emotion processing, respectively. The functional predictive brain network is composed by the prefrontal and limbic systems which are related to cognitive and affective control. Computational lesion analysis shows that functional connectivity among the salience network (SN), the frontal parietal network and the default mode network, as well as structural connectivity within the SN are vital in the individualized prediction of compulsions in OCD.Limitations: There was no external validation of large samples to test the robustness of our predictive model.Conclusions: These findings provide the first evidence for the predictive role of the triple network model in individualized compulsions and have important implications in diagnosis, prognosis and treatment of patients with OCD. [ABSTRACT FROM AUTHOR]

• Resting-state fMRI detected early radiation-induced brain functional abnormalities. • Brain nodal changes were dynamic, mainly manifesting an 'impairment-recovery' pattern. • D 20cc was an important prognostic determinant for nodal changes of STG.R. To investigate radiotherapy (RT)-related brain network changes in patients with nasopharyngeal carcinoma (NPC) over time and develop least absolute shrinkage and selection operator (LASSO)-based multivariable normal tissue complication probability (NTCP) models to predict RT-related brain network changes. 36 NPC patients were followed up at four timepoints: baseline, within 3 months (acute), 6 months (subacute), and 12 months (delayed) post-RT. 15 comparable healthy controls (HCs) were finally included and followed up in parallel. Functional neuroimaging data, dose–volume parameters of bilateral temporal lobes and Montreal Cognitive Assessment (MoCA) were acquired. Graph theoretical analysis and mixed-design analysis of variance were performed to investigate how the brain global and nodal changes were affected by RT. Multivariate logistic regression NTCP models were developed. LASSO with nested cross-validation strategy was used to select features. The relationships between network changes and MoCA changes were also examined. Significant changes were detected in nodal efficiency (NE) in NPC patients but not in HCs over time. Altered NE was distributed in the bilateral frontal, temporal lobes and the right insula, which showed a "decrease-increase/recovery" pattern over time. Among all models, the model for predicting NE changes of STG.R showed a relatively good performance (area under the receiver operating curve: 0.68), and D 20cc and V 20 to right temporal lobe outperformed in this model. Our findings indicate that RT-induced brain injury begin at the acute period and follow a recovery over time. Furthermore, our study presents prediction models for brain dysfunction based on the dosimetric and clinical parameters. [ABSTRACT FROM AUTHOR]