SC-FC Coupling Research Articles

Heritability and genetic contribution analysis of structural-functional coupling in human brain

Abstract The flow of functional connectivity (FC) is thought to be supported by white matter structural connectivity (SC). While research on the correlations between SC and FC (SC-FC coupling) has progressed, the genetic implications of SC-FC coupling have not been thoroughly examined. Traditionally, SC-FC coupling investigations utilize predefined atlases. Here, we adopted an atlas-free SC-FC coupling built on the high-resolution white surface (the interface of white matter and gray matter) to uncover common genetic variations. Leveraging data from the Human Connectome Project, we demonstrated considerable heritability in areas within the early and intermediate visual cortex and across dorsal-attention, language, and somatomotor functional networks. We detected 334 genetic loci (spanning 234 cytogenetic bands) linked to SC-FC coupling (P < 1.26 × 10−11), notably in cingulo-opercular, somatomotor, and default mode networks. Using an external dataset from the Adolescent Brain Cognitive Development study, we confirmed 187 cytogenetic bands associated with SC-FC coupling across 22 brain regions (P < 1 × 10-5). Genetic correlation analyses revealed high genetic interrelatedness for SC-FC coupling in neighboring regions. Furthermore, it showed genetic correlations with a spectrum of complex traits, encompassing various neurological and psychiatric conditions. In essence, our study paves the way towards deciphering the genetic interplay between structural and functional connectivity of the brain.

Effects of sleep on the glymphatic functioning and multimodal human brain network affecting memory in older adults.

Understanding how sleep affects the glymphatic system and human brain networks is crucial for elucidating the neurophysiological mechanism underpinning aging-related memory declines. We analyzed a multimodal dataset collected through magnetic resonance imaging (MRI) and polysomnographic recording from 72 older adults. A proxy of the glymphatic functioning was obtained from the Diffusion Tensor Image Analysis along the Perivascular Space (DTI-ALPS) index. Structural and functional brain networks were constructed based on MRI data, and coupling between the two networks (SC-FC coupling) was also calculated. Correlation analyses revealed that DTI-ALPS was negatively correlated with sleep quality measures [e.g., Pittsburgh Sleep Quality Index (PSQI) and apnea-hypopnea index]. Regarding human brain networks, DTI-ALPS was associated with the strength of both functional connectivity (FC) and structural connectivity (SC) involving regions such asthe middle temporal gyrus and parahippocampal gyrus, as well as with the SC-FC coupling ofrich-club connections. Furthermore, we found that DTI-ALPS positively mediated the association between sleep quality and rich-club SC-FC coupling. The rich-club SC-FC coupling further mediated the association between DTI-ALPS and memory function in good sleepers but not in poor sleepers. The results suggest a disrupted glymphatic-brain relationship in poor sleepers, which underlies memory decline. Our findings add important evidence that sleep quality affects cognitive health through the underlying neural relationships and the interplay between the glymphatic system and multimodal brain networks.

Structural-functional connectomics in major depressive disorder following aiTBS treatment

Major depressive disorder (MDD) has been associated with changes in the structural (SC) and functional connectivity (FC) of the brain. This study investigated the effects of accelerated intermittent theta burst stimulation (aiTBS) on SC-FC coupling and graph theory measures, focusing on the association between baseline SC-FC coupling of the dorsolateral prefrontal cortex (dlPFC) and clinical improvement. In a randomized, sham-controlled, quadruple-blind, crossover study, aiTBS was delivered to the left dlPFC of depressed patients with MDD, and diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rsfMRI) data were acquired. In 77 MDD patients, significantly increased whole-brain SC-FC coupling was observed, primarily driven by default mode network (DMN) SC-FC coupling, along with increased somatomotor network FC, and decreased FC between the DMN hubs and limbic regions after active aiTBS. Furthermore, significant increases were observed in structural global and local efficiency measures that were not specific to the stimulation condition (active/sham aiTBS). However, these changes did not significantly correlate with clinical improvement. Notably, baseline SC-FC coupling of the left dlPFC was a significant predictor of clinical improvement. Our findings highlight the potential of left dlPFC SC-FC coupling as a predictor of aiTBS treatment outcomes, as well as the effect of aiTBS in enhancing SC-FC coupling.

Structure-function coupling in highly sampled individual brains.

Structural connectivity (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to SC may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78min of diffusion-weighted MRI for SC and 360min of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas.

Aberrant brain structural-functional connectivity coupling associated with cognitive dysfunction in different cerebral small vessel disease burdens.

Emerging evidence suggests that cerebral small vessel disease (CSVD) pathology changes brain structural connectivity (SC) and functional connectivity (FC) networks. Although network-level SC and FC are closely coupled in the healthy population, how SC-FC coupling correlates with neurocognitive outcomes in patients with different CSVD burdens remains largely unknown. Using multimodal MRI, we reconstructed whole-brain SC and FC networks for 54 patients with severe CSVD burden (CSVD-s), 106 patients with mild CSVD burden (CSVD-m), and 79 healthy controls. We then investigated the aberrant SC-FC coupling and functional network topology in CSVD and their correlations with cognitive dysfunction. Compared with controls, the CSVD-m patients showed no significant change in any SC-FC coupling, but the CSVD-s patients exhibited significantly decreased whole-brain (p = 0.014), auditory/motor (p = 0.033), and limbic modular (p = 0.011) SC-FC coupling. For functional network topology, despite no change in global efficiency, CSVD-s patients exhibited significantly reduced nodal efficiency of the bilateral amygdala (p = 0.024 and 0.035) and heschl gyrus (p = 0.001 and 0.005). Notably, for the CSVD-s patients, whole-brain SC-FC coupling showed a significantly positive correlation with MoCA (r = 0.327, p = 0.020) and SDMT (r = 0.373, p = 0.008) scores, limbic/subcortical modular SC-FC coupling showed a negative correlation (r = -0.316, p = 0.025) with SCWT score, and global/local efficiency (r = 0.367, p = 0.009 and r = 0.353, p = 0.012) showed a positive correlation with AVLT score. For the CSVD-m group, whole-brain and auditory/motor modular SC-FC couplings showed significantly positive correlations with SCWT (r = 0.217, p = 0.028 and r = 0.219, p = 0.027) and TMT (r = 0.324, p = 0.001 and r = 0.245, p = 0.013) scores, and global/local efficiency showed positive correlations with AVLT (r = 0.230, p = 0.020 and r = 0.248, p = 0.012) and SDMT (r = 0.263, p = 0.008 and r = 0.263, p = 0.007) scores. Our findings demonstrated that decreased whole-brain and module-dependent SC-FC coupling associated with reduced functional efficiency might underlie more severe burden and worse cognitive decline in CSVD. SC-FC coupling might serve as a more sensitive neuroimaging biomarker of CSVD burden and provided new insights into the pathophysiologic mechanisms of clinical development of CSVD.

Brain structural–functional coupling mechanism in mild subcortical stroke and its relationship with cognition

ObjectivesStroke can lead to significant restructuring of brain structure and function. However, the precise changes in the coordination between brain structure and function in subcortical stroke patients remain unclear. We investigated alterations in brain structural–functional coupling (SC-FC coupling) and their impact on cognitive function in subcortical basal ganglia infarction patients. MethodsThe study comprised 40 patients with mild stroke with basal ganglia region infarcts and 29 healthy controls (HC) who underwent multidimensional neuroimaging examination and neuropsychological testing. The subcortical stroke patients were divided into post-stroke cognitive impairment (PSCI) and stroke with no cognitive impairment (NPSCI) groups based on cognitive performance, with 22 individuals undergoing follow-up examination after three months. We investigated differences in brain structural–functional coupling across three groups, and their associations with cognitive functions. ResultsCompared to both HC participants and NPSCI, PSCI exhibited significantly reduced structural–functional coupling strength in specific brain regions. After a three-month period, there was observed an increase in structural–functional coupling strength within the frontal lobe (precentral gyrus and paracentral lobule). The strength of SC-FC coupling within the precentral gyrus, precuneus, and paracentral lobule regions demonstrated a decline correlating with the deterioration of cognitive function (MoCA, memory and visual motor speed functions). ConclusionsAfter subcortical basal ganglia stroke, PSCI patients demonstrated decreased SC-FC coupling in the frontal lobe region, correlating with multidimensional cognitive impairment. Three months later, there was an increase in SC-FC coupling in the frontal lobe, suggesting a compensatory mechanism during the recovery phase of cognitive impairment following stroke.

Regional structural-functional connectivity coupling in major depressive disorder is associated with neurotransmitter and genetic profiles

BackgroundAbnormalities in structural–functional connectivity (SC–FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms underlying regional SC–FC coupling patterns are not well understood. MethodsWe enrolled 182 patients with MDD and 157 healthy control (HC) subjects, quantifying the intergroup differences in regional SC–FC coupling. The extreme gradient boosting (XGBoost), support vector machines (SVM) and random forest (RF) models were constructed to assess the potential of SC–FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC–FC coupling in patients with MDD, neurotransmitter distributions, and gene expression. ResultsWe observed increased regional SC–FC coupling in default mode network (T = 3.233) and decreased coupling in frontoparietal network (T = −3.471) in MDD relative to HC. XGBoost (AUC = 0.853), SVM (AUC = 0.832) and RF (p < 0.05) models exhibited good prediction performance. The alterations in regional SC–FC coupling in patients with MDD were correlated with the distributions of four neurotransmitters (p < 0.05) and expression maps of specific genes. These genes were strongly enriched in genes implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on two brain atlases. ConclusionsThis work enhances our understanding of MDD and pave the way for the development of additional targeted therapeutic interventions.

Distinct brain network patterns in complete and incomplete spinal cord injury patients based on graph theory analysis.

To compare the changes in brain network topological properties and structure-function coupling in patients with complete spinal cord injury (CSCI) and incomplete spinal cord injury (ICSCI), to unveil the potential neurobiological mechanisms underlying the different effects of CSCI and ICSCI on brain networks and identify objective neurobiological markers to differentiate between CSCI and ICSCI patients. Thirty-five SCI patients (20 CSCI and 15 ICSCI) and 32 healthy controls (HCs) were included in the study. Here, networks were constructed using resting-state functional magnetic resonance imaging to analyze functional connectivity (FC) and diffusion tensor imaging for structural connectivity (SC). Then, graph theory analysis was used to examine SC and FC networks, as well as to estimate SC-FC coupling values. Compared with HCs, CSCI patients showed increased path length (Lp), decreased global efficiency (Eg), and local efficiency (Eloc) in SC. For FC, ICSCI patients exhibited increased small-worldness, clustering coefficient (Cp), normalized clustering coefficient, and Eloc. Also, ICSCI patients showed increased Cp and Eloc than CSCI patients. Additionally, ICSCI patients had reduced SC-FC coupling values compared to HCs. Moreover, in CSCI patients, the SC network's Lp and Eg values were significantly correlated with motor scores, while in ICSCI patients, the FC network's Cp, Eloc, and SC-FC coupling values were related to sensory/motor scores. These results suggest that CSCI patients are characterized by decreased efficiency in the SC network, while ICSCI patients are distinguished by increased local connections and SC-FC decoupling. Moreover, the differences in network metrics between CSCI and ICSCI patients could serve as objective biological markers, providing a basis for diagnosis and treatment strategies.

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/β-hydrolase domain-containing 6 (ABHD6), β 1,3-N-acetylglucosaminyltransferase-9(β3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, β3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Spatial and temporal pattern of structure-function coupling of human brain connectome with development.

Brain structural circuitry shapes a richly patterned functional synchronization, supporting for complex cognitive and behavioural abilities. However, how coupling of structural connectome (SC) and functional connectome (FC) develops and its relationships with cognitive functions and transcriptomic architecture remain unclear. We used multimodal magnetic resonance imaging data from 439 participants aged 5.7-21.9 years to predict functional connectivity by incorporating intracortical and extracortical structural connectivity, characterizing SC-FC coupling. Our findings revealed that SC-FC coupling was strongest in the visual and somatomotor networks, consistent with evolutionary expansion, myelin content, and functional principal gradient. As development progressed, SC-FC coupling exhibited heterogeneous alterations dominated by an increase in cortical regions, broadly distributed across the somatomotor, frontoparietal, dorsal attention, and default mode networks. Moreover, we discovered that SC-FC coupling significantly predicted individual variability in general intelligence, mainly influencing frontoparietal and default mode networks. Finally, our results demonstrated that the heterogeneous development of SC-FC coupling is positively associated with genes in oligodendrocyte-related pathways and negatively associated with astrocyte-related genes. This study offers insight into the maturational principles of SC-FC coupling in typical development.

Structural-functional brain network coupling predicts human cognitive ability

Individual differences in general cognitive ability (GCA) have a biological basis within the structure and function of the human brain. Network neuroscience investigations revealed neural correlates of GCA in structural as well as in functional brain networks. However, whether the relationship between structural and functional networks, the structural-functional brain network coupling (SC-FC coupling), is related to individual differences in GCA remains an open question. We used data from 1030 adults of the Human Connectome Project, derived structural connectivity from diffusion weighted imaging, functional connectivity from resting-state fMRI, and assessed GCA as a latent g-factor from 12 cognitive tasks. Two similarity measures and six communication measures were used to model possible functional interactions arising from structural brain networks. SC-FC coupling was estimated as the degree to which these measures align with the actual functional connectivity, providing insights into different neural communication strategies. At the whole-brain level, higher GCA was associated with higher SC-FC coupling, but only when considering path transitivity as neural communication strategy. Taking region-specific variations in the SC-FC coupling strategy into account and differentiating between positive and negative associations with GCA, allows for prediction of individual cognitive ability scores in a cross-validated prediction framework (correlation between predicted and observed scores: r = 0.25, p < .001). The same model also predicts GCA scores in a completely independent sample (N = 567, r = 0.19, p < .001). Our results propose structural-functional brain network coupling as a neurobiological correlate of GCA and suggest brain region-specific coupling strategies as neural basis of efficient information processing predictive of cognitive ability.

Structural-functional coupling abnormalities in temporal lobe epilepsy.

Nowadays, researchers are using advanced multimodal neuroimaging techniques to construct the brain network connectome to elucidate the complex relationship among the networks of brain functions and structure. The objective of this study was to evaluate the coupling of structural connectivity (SC) and functional connectivity (FC) in the entire brain of healthy controls (HCs), and to investigate modifications in SC-FC coupling in individuals suffering from temporal lobe epilepsy (TLE). We evaluated 65 patients with TLE matched for age and gender with 48 healthy controls. The SC-FC coupling between regions was determined, based on which whole-brain nodes were clustered. Differences in the coupling among the three groups of nodes were compared. To further validate the results obtained, the within-cluster coupling indices of the three groups were compared to determine the inter-group differences. Nodes were divided into five clusters. Cluster 1 was primarily located in the limbic system (n = 9/27), whereas cluster 5 was mainly within the visual network (n = 12/29). By comparing average cluster SC-FC coupling in each cluster of the three groups, we identified marked discrepancies within the three cohorts in Cluster 3 (p = 0.001), Cluster 4 (p < 0.001), and Cluster 5 (p < 0.001). Post-hoc analysis revealed that the SC-FC coupling strengths in LTLE and RTLE were significantly lower than that in HCs in Cluster 3 (PL = 0.001/PR = 0.003), Cluster 4 (PL = 0.001/PR < 0.001), and Cluster 5 (PL < 0.001/PR < 0.001). We also observed that the within-cluster SC-FC coupling in cluster 5 of left- and right TLE was significantly lower than in HCs (PL = 0.0001, PR = 0.0005). The SC and FC are inconsistently coupled across the brain with spatial heterogeneity. In the fifth cluster with the highest degree of coupling in HCs, the average SC-FC coupling index of individuals with TLE was notably less than that of HCs, manifesting that brain regions with high coupling may be more delicate and prone to pathological disruption.

Aberrant Multimodal Connectivity Pattern Involved in Default Mode Network and Limbic Network in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder that progressively affects bulbar and limb function. Despite increasing recognition of the disease as a multinetwork disorder characterized by aberrant structural and functional connectivity, its integrity agreement and its predictive value for disease diagnosis remain to be fully elucidated. In this study, we recruited 37 ALS patients and 25 healthy controls (HCs). High-resolution 3D T1-weighted imaging and resting-state functional magnetic resonance imaging were, respectively, applied to construct multimodal connectomes. Following strict neuroimaging selection criteria, 18 ALS and 25 HC patients were included. Network-based statistic (NBS) and the coupling of grey matter structural-functional connectivity (SC-FC coupling) were performed. Finally, the support vector machine (SVM) method was used to distinguish the ALS patients from HCs. Results showed that, compared with HCs, ALS individuals exhibited a significantly increased functional network, predominantly encompassing the connections between the default mode network (DMN) and the frontoparietal network (FPN). The increased structural connections predominantly involved the inter-regional connections between the limbic network (LN) and the DMN, the salience/ventral attention network (SVAN) and FPN, while the decreased structural connections mainly involved connections between the LN and the subcortical network (SN). We also found increased SC-FC coupling in DMN-related brain regions and decoupling in LN-related brain regions in ALS, which could differentiate ALS from HCs with promising capacity based on SVM. Our findings highlight that DMN and LN may play a vital role in the pathophysiological mechanism of ALS. Additionally, SC-FC coupling could be regarded as a promising neuroimaging biomarker for ALS and shows important clinical potential for early recognition of ALS individuals.

Modular Level Alterations Of Structural-Functional Connectivity Coupling in Mild Cognitive Impairment Patients and Interactions with Age Effect.

Structural-functional connectivity (SC- FC) coupling is related to various cognitive functions and more sensitive for the detection of subtle brain alterations. To investigate whether decoupling of SC-FC was detected in mild cognitive impairment (MCI) patients on a modular level, the interaction effect of aging and disease, and its relationship with network efficiency. 73 patients with MCI and 65 healthy controls were enrolled who underwent diffusion tensor imaging and resting-state functional MRI to generate structural and functional networks. Five modules were defined based on automated anatomical labeling 90 atlas, including default mode network (DMN), frontoparietal attention network (FPN), sensorimotor network (SMN), subcortical network (SCN), and visual network (VIS). Intra-module and inter-module SC-FC coupling were compared between two groups. The interaction effect of aging and group on modular SC-FC coupling was further analyzed by two-way ANCOVA. The correlation between the coupling and network efficiency was finally calculated. In MCI patients, aberrant intra-module coupling was noted in SMN, and altered inter-module coupling was found in the other four modules. Intra-module coupling exhibited significant age-by-group effects in DMN and SMN, and inter-module coupling showed significant age-by-group effects in DMN and FPN. In MCI patients, both positive or negative correlations between coupling and network efficiency were found in DMN, FPN, SCN, and VIS. SC-FC coupling could reflect the association of SC and FC, especially in modular levels. In MCI, SC-FC coupling could be affected by the interaction effect of aging and disease, which may shed light on advancing the pathophysiological mechanisms of MCI.

Hierarchical brain structural-functional coupling associated with cognitive impairments in mild traumatic brain injury.

Mild traumatic brain injury (mTBI) disrupts the integrity of white matter microstructure, which affects brain functional connectivity supporting cognitive function. Although the relationship between structural and functional connectivity (SC and FC), here called SC-FC coupling, has been studied on global level in brain disorders, the long-term disruption of SC-FC coupling in mTBI at regional scale was still unclear. The current study investigated the alteration pattern of regional SC-FC coupling in 104 acute mTBI patients (41 with 6-12months of follow-up) and 56 healthy controls (HCs). SC and FC networks were constructed to measure regional, intra-network, and inter-network SC-FC coupling. Compared with HCs, acute mTBI exhibited altered SC-FC coupling of the sensorimotor network (SMN). The coupling laterality indicators of the SMN can identify mTBI from controls. The persistent SC-FC decoupling of the SMN and the additional decoupling of the default mode network (DMN) were observed in chronic mTBI. Crucially, decoupling of the SMN and DMN predicted better cognitive outcomes. The findings revealed the SC-FC coupling alternations exhibited hierarchical trend originating from the sensorimotor cortex to high-order cognitive regions with the progression of mTBI. The regional and hierarchical SC-FC coupling may be a prognostic biomarker to provide insights into the pathophysiology mechanism of mTBI.

Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study.

The relationship between structural connectivity (SC) and functional connectivity (FC) captured from magnetic resonance imaging, as well as its interaction with disability and cognitive impairment, is not well understood in people with multiple sclerosis (pwMS). The Virtual Brain (TVB) is an open-source brain simulator for creating personalized brain models using SC and FC. The aim of this study was to explore SC-FC relationship in MS using TVB. Two different model regimes have been studied: stable and oscillatory, with the latter including conduction delays in the brain. The models were applied to 513 pwMS and 208 healthy controls (HC) from 7 different centers. Models were analyzed using structural damage, global diffusion properties, clinical disability, cognitive scores, and graph-derived metrics from both simulated and empirical FC. For the stable model, higher SC-FC coupling was associated with pwMS with low Single Digit Modalities Test (SDMT) score (F=3.48, P$\lt$0.05), suggesting that cognitive impairment in pwMS is associated with a higher SC-FC coupling. Differences in entropy of the simulated FC between HC, high and low SDMT groups (F=31.57, P$\lt$1e-5), show that the model captures subtle differences not detected in the empirical FC, suggesting the existence of compensatory and maladaptive mechanisms between SC and FC in MS.

Comparison of brain network between schizophrenia and bipolar disorder: A multimodal MRI analysis of comparative studies

ObjectiveCognitive impairment is a shared symptom of Schizophrenia (SCZ) and bipolar disorder (BP), but the underlying neural mechanisms for both remain unclear. We aimed to identify abnormalities in the structural and functional brain network of patients with SCZ and BP. MethodsThe study included 69 patients with SCZ, 40 with BP, and 63 healthy controls (HC). After neurocognitive function assessment, resting-state functional magnetic resonance imaging and diffusion tensor imaging were acquired respectively. We compared the network of structural connectivity (SC) and functional connectivity (FC) among the three groups and performed graph theoretical analyses. The SC-FC coupling was calculated, and the correlations between the cognitive function scores and network properties were ascertained. ResultsThe BP group showed significantly higher indicators in subnetworks and graph theory analysis than SCZ and HC. Several brain regions, such as the inferior parietal lobe, exhibited differences among all pairwise comparisons and showed significant correlations with cognitive scores in both SCZ and BP. SC-FC coupling did not significantly differ between the three groups but showed close associations with clinical performance. Interestingly, the direction of correlations between the network properties and cognition tends to present the opposite between SCZ and BP, especially regarding the working memory, attention, and language sections. ConclusionsThe FC and SC network of the SCZ group appeared more inefficient and disconnected than BP. The network demonstrated to be closely but differently associated with cognitive function at both local and global levels, indicating the potentially separated pathologies of cognition deficits in SCZ and BP.

Altered higher-order coupling between brain structure and function with embedded vector representations of connectomes in schizophrenia.

It has been shown that the functional dependency of the brain exists in both direct and indirect regional relationships. Therefore, it is necessary to map higher-order coupling in brain structure and function to understand brain dynamic. However, how to quantify connections between not directly regions remains unknown to schizophrenia. The word2vec is a common algorithm through create embeddings of words to solve these problems. We apply the node2vec embedding representation to characterize features on each node, their pairwise relationship can give rise to correspondence relationships between brain regions. Then we adopt pearson correlation to quantify the higher-order coupling between structure and function in normal controls and schizophrenia. In addition, we construct direct and indirect connections to quantify the coupling between their respective functional connections. The results showed that higher-order coupling is significantly higher in schizophrenia. Importantly, the anomalous cause of coupling mainly focus on indirect structural connections. The indirect structural connections play an essential role in functional connectivity-structural connectivity (SC-FC) coupling. The similarity between embedded representations capture more subtle network underlying information, our research provides new perspectives for understanding SC-FC coupling. A strong indication that the structural backbone of the brain has an intimate influence on the resting-state functional.

Targeting disrupted rich-club network organization with neuroplasticity-based computerized cognitive remediation in major depressive disorder patients

Disrupted rich-club organization has been extensively studied in major depressive disorder (MDD) patients. Although data indicate that neuroplasticity-based computerized cognitive remediation (nCCR) can accelerate clinical responses in MDD patients, the mechanisms underlying its antidepressant efficacy are unknown. In this study, all MDD patients underwent two (baseline and week 4) neuropsychological assessments and DTI imaging. Additionally, 17 MDD patients did nCCR for 30 hours spread across 4 weeks. Rich-club organization was calculated with a graph-theoretical approach, and SC-FC coupling was explored. After 4 weeks of treatment, the number of rich-club connections, global efficiency, and SC-FC coupling strength increased significantly and were negatively associated with TMT-B scores. The effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD. Effects of nCCR on disrupted rich-club organization may partly underlie its efficacy in improving the executive function of patients with MDD.

Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy.

Neuroimaging studies have shown that juvenile myoclonic epilepsy (JME) is characterized by impaired brain networks. However, few studies have investigated the potential disruptions in rich‐club organization—a core feature of the brain networks. Moreover, it is unclear how structure–function relationships dynamically change over time in JME. Here, we quantify the anatomical rich‐club organization and dynamic structural and functional connectivity (SC–FC) coupling in 47 treatment‐naïve newly diagnosed patients with JME and 40 matched healthy controls. Dynamic functional network efficiency and its association with SC–FC coupling were also calculated to examine the supporting of structure–function relationship to brain information transfer. The results showed that the anatomical rich‐club organization was disrupted in the patient group, along with decreased connectivity strength among rich‐club hub nodes. Furthermore, reduced SC–FC coupling in rich‐club organization of the patients was found in two functionally independent dynamic states, that is the functional segregation state (State 1) and the strong somatomotor‐cognitive control interaction state (State 5); and the latter was significantly associated with disease severity. In addition, the relationships between SC–FC coupling of hub nodes connections and functional network efficiency in State 1 were found to be absent in patients. The aberrant dynamic SC–FC coupling of rich‐club organization suggests a selective influence of densely interconnected network core in patients with JME at the early phase of the disease, offering new insights and potential biomarkers into the underlying neurodevelopmental basis of behavioral and cognitive impairments observed in JME.