Altered resting‐state network connectivity in congenital blind

Schizophrenia is characterized by the distributed dysconnectivity of resting-state multiple brain networks. However, the abnormalities of intra- and inter-network functional connectivity (FC) in schizophrenia and its relationship to symptoms remain unknown. The aim of the present study is to compare the intra- and inter-connectivity of the intrinsic networks between a large sample of patients with schizophrenia and healthy controls. Using the Region of interest (ROI) to ROI FC analyses, the intra- and inter-network FC of the eight resting state networks [default mode network (DMN); salience network (SN); frontoparietal network (FPN); dorsal attention network (DAN); language network (LN); visual network (VN); sensorimotor network (SMN); and cerebellar network (CN)] were investigated in 196 schizophrenia and 169-healthy controls. Compared to the healthy control group, the schizophrenia group exhibited increased intra-network FC in the DMN and decreased intra-network FC in the CN. Additionally, the schizophrenia group showed the decreased inter-network FC mainly involved the SN-DMN, SN-LN and SN-CN while increased inter-network FC in the SN-SMN and SN-DAN (p < 0.05, FDR-corrected). Our study suggests widespread intra- and inter-network dysconnectivity among large-scale RSNs in schizophrenia, mainly involving the DMN, SN and SMN, which may further contribute to the dysconnectivity hypothesis of schizophrenia.

Long-term intensive gymnastic training can induce brain structural and functional reorganization. Previous studies have identified structural and functional network differences between world class gymnasts (WCGs) and non-athletes at the whole-brain level. However, it is still unclear how interactions within and between functional networks are affected by long-term intensive gymnastic training. We examined both intra- and inter-network functional connectivity of gymnasts relative to non-athletes using resting-state fMRI (R-fMRI). R-fMRI data were acquired from 13 WCGs and 14 non-athlete controls. Group-independent component analysis (ICA) was adopted to decompose the R-fMRI data into spatial independent components and associated time courses. An automatic component identification method was used to identify components of interest associated with resting-state networks (RSNs). We identified nine RSNs, the basal ganglia network (BG), sensorimotor network (SMN), cerebellum (CB), anterior and posterior default mode networks (aDMN/pDMN), left and right fronto-parietal networks (lFPN/rFPN), primary visual network (PVN), and extrastriate visual network (EVN). Statistical analyses revealed that the intra-network functional connectivity was significantly decreased within the BG, aDMN, lFPN, and rFPN, but increased within the EVN in the WCGs compared to the controls. In addition, the WCGs showed uniformly decreased inter-network functional connectivity between SMN and BG, CB, and PVN, BG and PVN, and pDMN and rFPN compared to the controls. We interpret this generally weaker intra- and inter-network functional connectivity in WCGs during the resting state as a result of greater efficiency in the WCGs' brain associated with long-term motor skill training.

Objective To investigate the regulatory effect of cognitive behavioral therapy (CBT) on the functional connectivity of cognitive control network in untreated obsessive-compulsive disorder (OCD) patients, so as to provide evidence for understanding the neurobiological mechanism of CBT. Methods A total of 45 OCD patients and 45 matched normal controls were recruited at the outpatient clinic in Beijing Anding Hospital. Four therapists provided 14 times of CBT treatment for OCD patients. All subjects underwent clinical symptom assessment and magnetic resonance imaging at baseline and at the end of 12 weeks. The clinical symptoms were assessed by the psychiatrists using Y-BOCS, HAMD17 and HAMA. The clinical symptoms of OCD patients before and after CBT treatment were compared. The GRETNA software package was used to preprocess the resting-state fMRI data. The whole brain function network was constructed with the template of Power 264 functional brain area as the network node. The function connection intensity outside the cognitive control network was calculated, and the function connection of 2 groups of brain networks at two timepoints were compared by repeated measurement of variance analysis. Results A total of 41 patients completed CBT. The scores of obsessive-compulsive symptoms, anxiety symptoms and depressive symptoms decreased at the end of 12th week, of which 32 patients were improved (Y-BOCS reduction ≥35%). Single factor repeated analysis of variance and post hoc tests were performed between patients with improvement and normal controls. At baseline, the functional connection between the cingulo-opercular network and the salience network of OCD patients was lower than that of the normal control (0.172±0.060 vs. 0.215±0.076, t=1.731, P=0.040), it increased after treatment (0.186±0.171 vs. 0.172±0.060, t=2.480, P=0.010). At baseline, the functional connection of cingulo-opercular network and subcortical network in OCD patients was lower than that of normal control (0.119±0.081 vs. 0.129±0.070, t=1.640, P=0.040), and it increased after treatment (0.130±0.161 vs. 0.119±0.081, t=2.421, P=0.020). At baseline, the functional connection between the frontal-parietal network and subcortical network was lower than that of normal controls (-0.004±0.039 vs. 0.021±0.054, t=2.280, P=0.020), and it increased after treatment (0.020±0.042 vs.-0.004±0.039, t=-2.300 P=0.020). Conclusions CBT could effectively improve obsessive-compulsive symptoms accompanying with improvement of the external functional connectivity of cognitive control network in OCD patients. Key words: Obsessive-compulsive disorder; Cognitive therapy; Cognitive control network; Functional connectivity

Very little is known about the pathogenesis of orthostatic tremor (OT). We have observed that OT patients might have deficits in specific aspects of neuropsychological function, particularly those thought to rely on the integrity of the prefrontal cortex, which suggests a possible involvement of frontocerebellar circuits. We examined whether resting-state functional magnetic resonance imaging (fMRI) might provide further insights into the pathogenesis on OT. Resting-state fMRI data in 13 OT patients (11 women and 2 men) and 13 matched healthy controls were analyzed using independent component analysis, in combination with a “dual-regression” technique, to identify group differences in several resting-state networks (RSNs). All participants also underwent neuropsychological testing during the same session. Relative to healthy controls, OT patients showed increased connectivity in RSNs involved in cognitive processes (default mode network [DMN] and frontoparietal networks), and decreased connectivity in the cerebellum and sensorimotor networks. Changes in network integrity were associated not only with duration (DMN and medial visual network), but also with cognitive function. Moreover, in at least 2 networks (DMN and medial visual network), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, visual memory, and language). In this exploratory study, we observed selective impairments of RSNs in OT patients. This and other future resting-state fMRI studies might provide a novel method to understand the pathophysiological mechanisms of motor and nonmotor features of OT.

Neural correlates of olfactory processing in congenital blindness

BackgroundThree intrinsic connectivity networks in the brain, namely the central executive, salience, and default mode networks, have been identified as crucial to the understanding of higher cognitive functioning, and the functioning of these networks has been suggested to be impaired in psychopathology, including posttraumatic stress disorder (PTSD).Objective1) To describe three main large-scale networks of the human brain; 2) to discuss the functioning of these neural networks in PTSD and related symptoms; and 3) to offer hypotheses for neuroscientifically-informed interventions based on treating the abnormalities observed in these neural networks in PTSD and related disorders.MethodLiterature relevant to this commentary was reviewed.ResultsIncreasing evidence for altered functioning of the central executive, salience, and default mode networks in PTSD has been demonstrated. We suggest that each network is associated with specific clinical symptoms observed in PTSD, including cognitive dysfunction (central executive network), increased and decreased arousal/interoception (salience network), and an altered sense of self (default mode network). Specific testable neuroscientifically-informed treatments aimed to restore each of these neural networks and related clinical dysfunction are proposed.ConclusionsNeuroscientifically-informed treatment interventions will be essential to future research agendas aimed at targeting specific PTSD and related symptoms.

Altered connectivity within and between the default mode, central executive, and salience networks in obsessive-compulsive disorder

BackgroundNumerous studies have confirmed that long-term shift work is not only associated with increased health problems and acute impact on safety but also with impaired cognitive abilities. However, very little is known about effects of shift work on cognition-related brain resting-state networks. The aim of this study was to explore the effects of shift work disorder (SWD) on granger causality connection among resting-state brain networks.MethodsThirty patients with SWD and 25 matched healthy subjects were recruited to undergo the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and resting-state fMRI scanning. We employed independent component analysis (ICA) to extract resting-state brain networks and granger causality analysis (GCA) to characterize the difference of granger causality connection among cognition-related resting-state brain networks.ResultsCompared with healthy subjects, patients with SWD showed impairments on the attention and immediate memory. Seven resting-state brain networks were identified, and patients with SWD showed more numerous granger causality connections in comparison with healthy subjects. Two-sample t test results showed that there were significantly increased inflows from the anterior default mode network (aDMN) to sensorimotor network (SMN) and left frontoparietal network (LFPN) to salience network (SN). Correlation analyses showed that the increased inflows from aDMN to SMN were negatively associated with the score of attention, while LFPN to SN were negatively associated with the score of visuospatial/constructional ability.ConclusionsThis study indicates that SWD impairs cognitive performance, and the specific intrinsic brain granger causality connectivity among resting-state networks in SWD patients is affected after long-term shift works.

Emotional empathy is the ability to experience and/or share another person’s emotional states and responses. Although some research has examined the neural correlates of emotional empathy, there has been little research investigating whether this component of empathy is related to the functional connectivity of resting state networks in the brain. In the current study, 32 participants answered a trait emotional empathy questionnaire in a session previous to their functional magnetic resonance imaging scan. Results indicate that emotional empathy scores were correlated with different patterns of functional connectivity in the default mode network (DMN), salience network (SN), and left and right central executive networks. For example, within the DMN, emotional empathy scores positively correlated with connectivity in the premotor cortex. Within the SN, empathy scores were positively correlated with the fusiform gyrus and cuneus. These findings demonstrate that emotional empathy is associated with unique patterns of functional connectivity in four of the brain’s resting state networks.

Perinatal brain injury is a significant cause of adverse neurodevelopmental outcomes. The objective of this systematic review was to identify patterns of altered brain function, quantified using functional connectivity (FC) changes in resting-state fMRI (rs-fMRI) data, that were associated with motor and language outcomes in individuals with a history of perinatal brain injury. A systematic search using electronic databases was conducted to identify relevant studies. A total of 10 studies were included in the systematic review, representing 260 individuals with a history of perinatal brain injury. Motor and language outcomes were measured at time points ranging from 4 months to 29 years 1 month. Relations between FC and motor measures revealed increased intra-hemispheric FC, reduced inter-hemispheric FC and impaired lateralization of motor-related brain regions associated with motor outcomes. Altered FC within sensorimotor, visual, cerebellum and frontoparietal networks, and between sensorimotor, visual, auditory and higher-order networks, including cerebellum, frontoparietal, default-mode, salience, self-referential and attentional networks were also associated with motor outcomes. In studies assessing the relationship between rs-fMRI and language outcome, reduced intra-hemispheric FC, increased inter-hemispheric FC and right-hemisphere lateralization of language-related brain regions correlated with language outcomes. Evidence from this systematic review suggests a possible association between diaschisis and motor and language impairments in individuals after perinatal brain lesions. These findings support the need to explore the contributions of additional brain regions functionally connected but remote from the primary lesioned brain area for targeted treatments and appropriate intervention, though more studies with increased standardization across neuroimaging and neurodevelopmental assessments are needed.

Major depressive disorder (MDD) involves subtle, distributed alterations across multiple large-scale resting-state brain networks (RSNs), highlighting the need for integrative approaches to uncover synergistic network patterns driving clinical symptoms. In this study, we used a dynamic systems approach to investigate patterns of simultaneous RSN activation-i.e., coactivation-in 867 participants, including 487 healthy control participants (HCs), 175 patients with current MDD (cMDD), and 205 patients with remitted MDD (rMDD) from the Marburg-Münster Affective Disorders Cohort Study. Using a pairwise maximum entropy model, we estimated RSN coactivation probabilities based on resting-state fMRI data of 7 RSNs-default mode network (DMN), frontoparietal network (FPN), sensorimotor network (SMN), visual network (VIS), salience network, dorsal attention network (DAN), and language network (LAN)-capturing 128 possible states of coactivation. General linear models revealed elevated coactivation probabilities in cMDD, particularly for states involving the DMN, FPN, and VIS, with the coactivation state involving the DMN, VIS, DAN, FPN, and LAN showing the strongest association with MDD diagnosis, clinical status, and symptom severity. Furthermore, canonical correlation analysis (CCA) on the total sample identified 2 distinct network-symptom profiles: canonical variate (CV) 1 linked high DMN and DAN coactivation probabilities to cognitive, insomnia, and mood/anhedonia symptoms, while CV2 tied the SMN and VIS to cognitive and somatic symptom domains. These results demonstrate that MDD, especially during acute episodes, is marked by a dominance of DMN, FPN, and VIS coactivation, pointing to altered dynamic network organization. Further, the results highlight how changes in brain state dynamics are linked to MDD symptoms.

A resting-state functional connectivity (rsFC)-constructed functional network (FN) derived from functional magnetic resonance imaging (fMRI) data can effectively mine alterations in brain function during aging due to the non-invasive and effective advantages of fMRI. With global health research focusing on aging, several open fMRI datasets have been made available that combine deep learning with big data and are a new, promising trend and open issue for brain information detection in fMRI studies of brain aging. In this study, we proposed a new method based on deep learning from the perspective of big data, named Deep neural network (DNN) with Autoencoder (AE) pretrained Functional connectivity Analysis (DAFA), to deeply mine the important functional connectivity changes in fMRI during brain aging. First, using resting-state fMRI data from 421 subjects from the CamCAN dataset, functional connectivities were calculated using sliding window method, and the complex functional patterns were mined by an AE. Then, to increase the statistical power and reliability of the results, we used an AE-pretrained DNN to relabel the functional connectivities of each subject to classify them as belonging to the attributes of young or old individuals. A method called search-back analysis was performed to find alterations in brain function during aging according to the relabeled functional connectivities. Finally, behavioral data regarding fluid intelligence and response time were used to verify the revealed functional changes. Compared to traditional methods, DAFA revealed additional, important aged-related changes in FC patterns [e.g., FC connections within the default mode (DMN) and the sensorimotor and cingulo-opercular networks, as well as connections between the frontoparietal and cingulo-opercular networks, between the DMN and the frontoparietal/cingulo-opercular/sensorimotor/occipital/cerebellum networks, and between the sensorimotor and frontoparietal/cingulo-opercular networks], which were correlated to behavioral data. These findings demonstrated that the proposed DAFA method was superior to traditional FC-determining methods in discovering changes in brain functional connectivity during aging. In addition, it may be a promising method for exploring important information in other fMRI studies.

目的 探讨精神分裂症患者脑静息态默认网络、中心执行网络及突显网络的网络内及网络间的功能连接特点.方法 对74例精神分裂症患者(患者组)和79名相匹配的健康者(对照组)进行静息态fMRI扫描.采取功能连接分析方法,以内侧前额叶皮质及右侧前岛叶为感兴趣区域分别提取默认网络、中心执行网络及突显网络,分析3个网络内及网络间静息态功能连接情况;并对有差异的功能连接与精神症状及病程等进行偏相关分析.结果 与对照组相比,患者组内侧前额叶皮质与双侧背外侧前额叶皮质(左侧-0.02±0.18与-0.12±0.12,t=4.25,P＜0.01;右侧-0.02±0.11与-0.10±0.10,t=5.40,P＜0.01)、双侧豆状壳核(左侧0.14±0.12与0.04±0.10,t=5.03,P＜0.01;右侧0.13±0.11与0.03±0.98,t=4.96,P＜0.01)的功能连接增强;右侧前岛叶与左侧额中回(-0.05±0.17与-0.07±0.17,t=4.60,P＜0.01)及楔前叶/后扣带回(0.01±0.13与-0.09±0.14,t=4.01,P＜0.01)的功能连接增强(均采用高斯随机场理论校正,体素水平P＜0.01,簇水平P＜0.05);默认网络与中心执行网络、突显网络间的负向功能连接减小甚至消失(Bonferroni校正P＜0.05).患者组PANSS阳性症状分与右侧前岛叶与楔前叶/后扣带回皮质间的功能连接呈正相关(r=0.232,P=0.025);患者组病程与右侧前岛叶与左侧额中回(r=0.288,P=0.007)、楔前叶/后扣带回(r=0.196,P=0.049)间的功能连接呈正相关.结论 精神分裂症患者存在静息态默认网络、中心执行网络及突显网络3个网络间的连接异常,可能与精神分裂症的病理机制有关.

Background The Rorschach test is one of the most popular tests used in clinical settings for psychopathology and personality assessment; however, there is still little evidence regarding the functional correlates of test responses. Functional magnetic resonance imaging (fMRI) allows for the investigation of biological correlates associated with different psychological functions. Among other applications, fMRI has been used to identify different networks that reflect brain activity in the resting state (rs-fMRI), that is, when an individual is not engaged in any specific task. Among these resting-state networks (RSN), the best-known and most studied are the Default Mode Network (DMN), along with other networks such as salience, frontoparietal, sensorimotor, temporo-parietal, visual, and cerebellar networks. Methods We used this type of analysis to obtain new evidence regarding Rorschach. This study aimed to analyze the functional brain architecture underlying Rorschach’s personality variables, administered according to Exner’s Comprehensive System (CS). In particular, the aims are: 1) to ascertain the existence of correlations between CS variables and activity of the RSN, and 2) to use these profiles of activity to develop a new data-driven clustering of the CS variables. Archival data from twenty-four non-clinical subjects were analyzed. Independent Component Analysis (ICA) and partial least squares regression (PLS) were used to analyze the fMRI data. Results The results showed specific associations with the given Rorschach variables (several of which could be grouped into higher-order latent factors) and activity of the main RSN. Moreover, the cluster analysis outlined important groupings of Rorschach variables, particularly regarding their clinical implications. Conclusions Our study could be comprised in the existing literature providing strong evidence about the neurobiological validity of the Rorschach test.

The aim of this study was to investigate alterations in functional connectivity (FC) within and interactions between resting-state networks involved in salience, executive control, and interoception in participants with obesity (OB). Using resting-state functional magnetic resonance imaging with independent component analysis and FC, alterations within and interactions between resting-state networks in 35 OB and 35 normal-weightcontrols (NW) were investigated. Compared with NW, OB showed reduced FC strength in the ventromedial prefrontal cortex and posterior cingulate cortex/precuneus within the default-mode network, dorsal anterior cingulate cortex within the salience network (SN), bilateral dorsolateral prefrontal cortex-angular gyrus within the frontoparietal network (FPN), and increased FC strength in the insula (INS) (Pfamilywise error < 0.0125). The dorsal anterior cingulate cortex FC strength was negatively correlated with craving for food cues, left dorsolateral prefrontal cortex FC strength was negatively correlated with Yale Food Addiction Scale scores, and right INS FC strength was positively correlated with craving for high-calorie food cues. Compared with NW, OB also showed increased FC between theSN and FPN driven by altered FC of bilateral INS and anterior cingulate cortex-angular gyrus. Alterations in FC within and interactions between the SN, default-mode network, and FPN might contribute to the high incentive value of food (craving), lack of control of overeating (compulsive overeating), and increased awareness of hunger (impaired interoception) in OB.