Compressed sensorimotor-to-transmodal hierarchical organization in schizophrenia

Dynamic modular dysregulation in multilayer networks underlies cognitive and clinical deficits in first-episode schizophrenia

Schizophrenia has been identified to exhibit significant abnormalities in brain functional networks, which are likely to underpin the cognitive and functional impairments observed in patients. Graph theoretical analysis revealed the disrupted modularity in schizophrenia, however, the dynamic network abnormalities in schizophrenia remains unclear. We collected the resting-state functional magnetic resonance imaging data from 82 first-episode schizophrenia (FES) patients and 55 healthy control (HC) subjects. Dynamic functional connectivity matrices were constructed and a multilayer network model was employed to run the dynamic modularity analysis. We also performed correlation analyses to investigate the relationship between flexibility, cognitive function and clinical symptoms. Our findings indicate that FES patients exhibit higher multilayer modularity. The node flexibility of FES patients were found elevated in several brain regions, which were included in the default mode network, fronto-parietal network, salience network and visual network. The node flexibility metrics in aberrant brain regions were found to demonstrate significant correlations with cognitive function and negative symptoms in patients with FES. These findings suggest a pathological imbalance in brain network dynamics, where abnormal modular organization might contribute to the cognitive impairment and functional deficits in schizophrenia.

Cortical structure in relation to empathy and psychopathy in 800 incarcerated men

Background

Reduced affective empathy is a hallmark of psychopathy, which incurs major interpersonal and societal costs. Advancing our neuroscientific understanding of this reduction and other psychopathic traits is crucial for improving their treatment.

Methods

In 804 incarcerated adult men, we administered the Perspective Taking (IRI-PT) and Empathic Concern (IRI-EC) subscales of the Interpersonal Reactivity Index, Hare Psychopathy Checklist-Revised (PCL-R; two factors), and T1-weighted MRI to quantify cortical thickness (CT) and surface area (SA). We also included the male sample of the Human Connectome Project (HCP; N = 501) to replicate patterns of macroscale structural organization.

Results

Factor 1 (Interpersonal/Affective) uniquely negatively related to IRI-EC, while Factor 2 (Lifestyle/Antisocial) uniquely negatively related to IRI-PT. Cortical structure did not relate to either IRI subscale, although there was effect-size differentiation by microstructural class and/or functional network. CT related to Factor 1 (mostly positively), SA related to both factors (only positively), and both cortical indices demonstrated out-of-sample predictive utility for Factor 1. The high-psychopathy group (N = 178) scored uniquely lower on IRI-EC while having increased SA (but not CT). Regionally, these SA increases localized primarily in the paralimbic class and somatomotor network, with meta-analytic task-based activations corroborating affective-sensory importance. High psychopathy also showed "compressed" global and/or network-level organization of both cortical indices, and this organization in the total sample replicated in HCP. All findings accounted for age, IQ, and/or total intracranial volume.

Conclusions

Psychopathy had negative relationships with affective empathy and positive relationships with paralimbic/somatomotor SA, highlighting the role of affect and sensation.

Advanced concentrative absorption meditation reorganizes functional connectivity gradients of the brain: 7T MRI and phenomenology case study of jhana meditation

There is growing scientific interest in advanced meditation, and particularly the Theravada Buddhist advanced concentrative absorption meditation known as jhana (ACAM-J). ACAM-J includes a series of eight consecutive meditative states, which are radically altered states of consciousness. The neuroscience of ACAM-J, specifically brain reorganization, remains underspecified in part due to the difficulty of finding and studying expert ACAM-J meditators and challenges related to laboratory investigation of ACAM-J. Using a nonlinear dimensionality reduction technique applied to human functional neuroimaging in an intensive case study, we investigated brain reorganization during ACAM-J. We applied linear mixed models and correlations to explore relations among brain reorganization and ACAM-J phenomenology. Results demonstrated that ACAM-J induces disruption of the hierarchical organization of the brain by shifting the gradients toward a more globally integrated rather than segregated state between sensory-related and higher-order cognitive regions. Additionally, ACAM-J induces a separation between sensory-related and attention modulation-related regions, resulting in greater differentiation in functional organization of these regions, consistent with phenomenological reports. This study highlights the need for further research into brain reorganization and health-related implications of both short-term and long-term practice of ACAM-J. Key points/highlights The neuroscience of advanced concentrative absorption meditation (ACAM) has the potential to improve our knowledge of well-being and altered states of consciousness but remains underexplored due to methodological challenges. We investigated functional reorganization of the brain during ACAM-J using gradient analysis and demonstrated that ACAM-J disrupts the hierarchical organization of the brain during meditation. Additionally, we demonstrated that ACAM-J increases differentiation between primary sensory areas and areas related to attention modulation.

Dynamic and Static Functional Gradient in Temporal Lobe Epilepsy With Hippocampal Sclerosis Versus Healthy Controls

AIMS

The gradient captures the continuous transitions in connectivity, representing an intrinsic hierarchical architecture of the brain. Previous works hinted at the dynamics of the gradient but did not verify them. Cognitive impairment is a common comorbidity of temporal lobe epilepsy (TLE). Gradient techniques provide a framework that could promote the understanding of the neural correlations of cognitive decline.

METHODS

Thirty patients with TLE and hippocampal sclerosis and 29 matched healthy controls (HC) were investigated with verbal fluency task-based functional MRI and gradient techniques. The correlation between task-based activation/deactivation and healthy gradients, task-based gradients, and dynamic features calculated with sliding window approaches was compared between HC and TLE.

RESULTS

The allegiance in the real data of HC and TLE was more widespread compared to static null models. TLE has lower dynamic recruitment of gradient, atypical activation-gradient correlation, and contracted principal gradient. Correlation analysis proved that the reconfiguration of principal gradient did not drive the reorganization of activation. The atypical activation pattern and impaired recruitment were correlated with cognition scales in TLE.

DISCUSSION

The principal gradient is dynamic. TLE disrupted activation/deactivation patterns, the principal gradient, and the dynamics of the gradient, which were correlated with cognitive decline.

Disruption of structural connectome hierarchy in age-related hearing loss

Introduction

Age-related hearing loss (ARHL) is a common sensory disability among older adults and is considered a risk factor for the development of dementia. Previous work has shown altered brain connectome topology in ARHL, including abnormal nodal strength and clustering coefficient. However, whether ARHL affects the hierarchical organization of structural connectome and how these alterations relate to transcriptomic signatures remain unknown.

Methods

Here, we apply a gradient mapping framework to the structural connectome derived from diffusion magnetic resonance imaging. We focus on the first three structural gradients that reflect distinct hierarchical organization of structural connectome, and assess ARHL-related changes.

Results

We find that, compared to controls, ARHL patients exhibit widespread disruptions of structural connectome organization, spanning from primary sensory areas (e.g., somatomotor network) to high-order association areas (e.g., default mode network). Subsequently, by employing subcortical-weighted gradients derived from weighting cortical gradients by subcortical-cortical connectivity, we observe that ARHL patients show significantly altered subcortical-cortical connectivity in the left caudate, left nucleus accumbens, right hippocampus, and right amygdala. Finally, we investigate the relationship between gene expression and alterations in structural gradients. We observe that these alterations in structural gradients are associated with weighted gene expression profiles, with relevant genes preferentially enriched for inorganic ion transmembrane transport and terms related to regulating biological processes.

Discussion

Taken together, these findings highlight that ARHL is associated with abnormal structural connectome hierarchy and reveal the transcriptomic relevance of these abnormalities, contributing to a richer understanding of the neurobiological substrates in ARHL.

Altered Hemispheric Asymmetry of Functional Hierarchy in Schizophrenia

BACKGROUND/OBJECTIVES

Schizophrenia is a severe psychiatric disorder characterized by deficits in perception and advanced cognitive functions. Prior studies have reported abnormal lateralization in cortical morphology and functional connectivity in schizophrenia. However, it remains unclear whether schizophrenia affects hemispheric asymmetry in the hierarchical organization of functional connectome.

METHODS

Here, we apply a gradient mapping framework to the hemispheric functional connectome to estimate the first three gradients, which characterize unimodal-to-transmodal, visual-to-somatomotor, and somatomotor/default mode-to-multiple demand hierarchy axes. We then assess between-group differences in intra- and inter-hemispheric asymmetries of these three functional gradients.

RESULTS

We find that, compared to healthy controls, patients with schizophrenia exhibit significantly altered hemispheric asymmetry in functional gradient across multiple networks, including the dorsal attention, ventral attention, visual, and control networks. Region-level analyses further reveal that patients with schizophrenia show significantly abnormal hemispheric gradient asymmetries in several cortical regions in the dorsal prefrontal gyrus, medial superior frontal gyrus, and somatomotor areas. Lastly, we find that hemispheric asymmetries in functional gradients can differentiate between patients and healthy controls and predict the severity of positive symptoms in schizophrenia.

CONCLUSIONS

Collectively, these findings suggest that schizophrenia is associated with altered hemispheric asymmetry in functional hierarchy, providing novel perspectives for understanding the atypical brain lateralization in schizophrenia.

Analysis of the effect of combined rehabilitation training and transcutaneous vagus nerve electrical stimulation on promoting central nervous system remodeling in stroke patients

OBJECTIVE

To explore the effect of combined rehabilitation training and transcutaneous vagus nerve electrical stimulation (t-VNS) on promoting central nervous system remodeling and neurological function recovery in stroke patients.

METHODS

A total of 124 S patients admitted to our hospital from January to December 2023 were included in this study. The therapeutic effects were evaluated using the Modified Barthel Index (MBI) and the simplified Fugl-Meyer Assessment Scale (sFMA) to measure patients' activities of daily living and motor function recovery. Additionally, neurophysiological assessments, including electromyography (EMG) and motor evoked potentials (MEPs), were conducted to evaluate changes in neuromuscular and central nervous system function. Changes in neural activity in the frontal lobe and motor cortex were assessed through transcutaneous vagus nerve stimulation and electroencephalography. Moreover, all adverse events were recorded.

RESULTS

After treatment, patients in the t-VNS combined with rehabilitation training group showed significant improvements in sFMA and MBI scores compared to the pure rehabilitation training group (P < 0.05). In terms of neurophysiology, patients in the combined treatment group exhibited significant increases in electromyographic activity and MEPs (P < 0.05). EEG results indicated enhanced neuroplasticity of the frontal lobe and motor cortex with t-VNS treatment. The incidence of skin stimulation and ear pain in the combined treatment group was significantly higher than that in the pure rehabilitation training group.

CONCLUSION

Combined rehabilitation training and transcutaneous vagus nerve electrical stimulation have significant effects on neurological function recovery and central nervous system remodeling in stroke patients, effectively improving patients' motor function and activities of daily living.

Functional differentiation of the default and frontoparietal control networks predicts individual differences in creative achievement: evidence from macroscale cortical gradients

Much of the research on the neural correlates of creativity has emphasized creative cognition, and growing evidence suggests that creativity is related to functional properties of the default and frontoparietal control networks. The present work expands on this body of evidence by testing associations of creative achievement with connectivity profiles of brain networks assessed using macroscale cortical gradients. Using resting-state connectivity functional magnetic resonance imaging in 2 community samples (N's = 236 and 234), we found evidence that creative achievement is positively associated with greater functional dissimilarity between core regions of the default and frontoparietal control networks. These results suggest that creative achievement is supported by the ability of these 2 networks to carry out distinct cognitive roles. This research provides further evidence, using a cortical gradient approach, that individual differences in creative achievement can be predicted from functional properties of brain networks involved in higher-order cognition, and it aligns with past research on the functional connectivity correlates of creative task performance.

Dysfunction in the hierarchy of morphometric similarity network in Alzheimer's disease and its correlation with cognitive performance and gene expression profiles

BACKGROUND

Previous research has shown abnormal functional network gradients in Alzheimer's disease (AD). Structural network gradient is capable of capturing continuous changes in brain morphology and has the ability to elucidate the underlying processes of neurodevelopment. However, it remains unclear whether structural network gradients are altered in AD and what associations exist between these changes and cognitive function, and gene expression profiles.

METHODS

By constructing an individualized structural network gradient decomposition framework, we calculated the morphological similarity network (MSN) gradients for 404 subjects (186 AD patients and 218 normal controls). We investigated AD-related alterations in MSN gradients, along with the associations between MSN gradients and cognitive function, MSN topological properties, and gene expression profiles.

RESULTS

Our findings indicated that the principal MSN gradient alterations in AD were primarily characterized by an increase in the primary and secondary sensory cortices and a decrease in the association cortex 1. The primary and higher-order cortices exhibited opposite associations with cognition, including executive function, language skills, and memory processes. Moreover, the principal MSN gradients were found to significantly predict cognitive function in AD. The altered gradient pattern was 14.8% attributable to gene expression profiles, and the genes demonstrating the highest correlation are involved in metabolic activity and synaptic signaling.

CONCLUSIONS

Our results offered novel insights into the underlying mechanisms of structural brain network impairment in AD patients, enhancing our understanding of the neurobiological processes responsible for impaired cognition in patients with AD, and offering a new dimensional structural biomarker for AD.

Motor Functional Hierarchical Organization of Cerebrum and Its Underlying Genetic Architecture in Parkinson's Disease

Hierarchy has been identified as a principle underlying the organization of human brain networks. However, it remains unclear how the network hierarchy is disrupted in Parkinson's disease (PD) motor symptoms and how it is modulated by the underlying genetic architecture. The aim of this study was to explore alterations in the motor functional hierarchical organization of the cerebrum and their underlying genetic mechanism. In this study, the brain network hierarchy of each group was described through a connectome gradient analysis among 68 healthy controls (HC), 70 postural instability and gait difficulty (PIGD) subtype, and 69 tremor-dominant (TD) subtype, including both male and female participants, according to its motor symptoms. Furthermore, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control gradient differences were performed to identify genes associated with gradient alterations. Different PD motor subtypes exhibited contracted principal and secondary functional gradients relative to HC. The identified genes in different PD motor subtypes enriched for shared biological processes like metal ion transport and inorganic ion transmembrane transport. In addition, these genes were overexpressed in Ntsr+ neurons cell, enriched in extensive cortical regions and wide developmental time windows. Aberrant cerebral functional gradients in PD-related motor symptoms have been detected, and the motor-disturbed genes have shared biological functions. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying hierarchical alterations in PD.

Cognition-related connectome gradient dysfunctions of thalamus and basal ganglia in drug-naïve first-episode major depressive disorder

BACKGROUND

Subcortical functional abnormalities are believed to contribute to clinical symptoms and cognitive impairments in major depressive disorder (MDD). By introducing functional gradient mapping, the present study evaluated subcortical gradients in MDD patients and their association with cognitive features.

METHODS

Organization patterns and between-group differences in the principal subcortical gradient were investigated in 145 never-treated first-episode MDD patients and 145 healthy controls (HCs) across limbic, thalamic, and basal ganglia (BG) systems and their structural and functional subregions. We also assessed the associations between significant gradient alterations and clinical characteristics and neuropsychological functioning.

RESULTS

Overall, MDD patients showed a relatively compressed and disturbed gradient organization than HCs, with limbic and BG regions located at the two extreme ends of the principal gradient. Specifically, MDD patients had lower principal gradient values in thalamus and limbic system but higher values in BG than HCs. These gradient alterations, associated with intrinsic Euclidian distance and functional connectivity patterns, manifested as spatial rearrangements of gradient values within each respective subregion. Lower gradient values in thalamic subregion projecting to default mode network were associated with higher principal gradient values in BG subregion projecting to ventral attention network, and these gradient alterations were correlated with poorer episodic memory performance in MDD patients.

LIMITATIONS

The specific neuropathological mechanisms driving the gradient alterations still require further investigation.

CONCLUSIONS

Opposing gradient alterations in the thalamic and BG regions synergistically impact episodic memory performance in MDD, revealing an internally differentiated and cognition related pattern of subcortical gradient dysfunction in MDD.

A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity

Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Recently, low-dimensional representations of the connectome such as macroscale cortical gradients and gradient dispersion have been proposed, with studies noting consistent gradient and dispersion differences in psychiatric conditions. However, it is unknown which of these derived measures has the highest predictive capacity and how they compare to raw functional connectivity specifically in the case of schizophrenia. Our study evaluates which connectome features derived from resting state functional MRI - functional connectivity, gradients, or gradient dispersion - best identify schizophrenia. To this end, we leveraged data of 936 individuals from three large open-access datasets: COBRE, LA5c, and SRPBS-1600. We developed a pipeline which allows us to aggregate over a million different features and assess their predictive potential in a single, computationally efficient experiment. We selected top 1% of features with the largest permutation feature importance and trained 13 classifiers on them using 10-fold cross-validation. Our findings indicate that functional connectivity outperforms its low-dimensional derivatives such as cortical gradients and gradient dispersion in identifying schizophrenia (Mann-Whitney test conducted on test accuracy: connectivity vs. 1st gradient: U = 142, p < 0.003; connectivity vs. neighborhood dispersion: U = 141, p = 0.004). Additionally, we demonstrated that the edges which contribute the most to classification performance are the ones connecting primary sensory regions. Functional connectivity within the primary sensory regions showed the highest discrimination capabilities between subjects with schizophrenia and neurotypical controls. These findings along with the feature selection pipeline proposed here will facilitate future inquiries into the prediction of schizophrenia subtypes and transdiagnostic phenomena.

Individualized functional connectome abnormalities obtained using two normative model unveil neurophysiological subtypes of obsessive compulsive disorder

The high heterogeneity observed among patients with obsessive-compulsive disorder (OCD) underscores the need to identify neurophysiological OCD subtypes to facilitate personalized diagnosis and treatment. In this study, our aim was to identify potential OCD subtypes based on individualized functional connectome abnormalities. We recruited a total of 99 patients with OCD and 104 healthy controls (HCs) matched for demographic characteristics. Individualized functional connectome abnormalities were obtained using normative models of functional connectivity strength (FCS) and used as features to unveil OCD subtypes. Sensitivity analyses were conducted to assess the reproducibility and robustness of the clustering outcomes. Patients exhibited significant intersubject heterogeneity in individualized functional connectome abnormalities. Two subtypes with distinct patterns of FCS abnormalities relative to HCs were identified. Subtype 1 patients primarily exhibited significantly decreased FCS in regions including the frontal gyrus, insula, hippocampus, and precentral/postcentral gyrus, whereas subtype 2 patients demonstrated increased FCS in widespread brain regions. When all patients were combined, no significant differences were observed. Additionally, the identified subtypes showed significant differences in age of onset. Furthermore, sensitivity analyses confirmed the reproducibility of our subtyping results. In conclusion, the identified OCD subtypes shed new light on the taxonomy and neurophysiological heterogeneity of OCD.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Brain structural damage networks at different stages of schizophrenia

BACKGROUND

Neuroimaging studies have documented brain structural changes in schizophrenia at different stages of the illness, including clinical high-risk (cHR), genetic high-risk (gHR), first-episode schizophrenia (FES), and chronic schizophrenia (ChS). There is growing awareness that neuropathological processes associated with a disease fail to map to a specific brain region but do map to a specific brain network. We sought to investigate brain structural damage networks across different stages of schizophrenia.

METHODS

We initially identified gray matter alterations in 523 cHR, 855 gHR, 2162 FES, and 2640 ChS individuals relative to 6963 healthy controls. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to four specific networks.

RESULTS

Brain structural damage networks of cHR and gHR had limited and non-overlapping spatial distributions, with the former mainly involving the frontoparietal network and the latter principally implicating the subcortical network, indicative of distinct neuropathological mechanisms underlying cHR and gHR. By contrast, brain structural damage networks of FES and ChS manifested as similar patterns of widespread brain areas predominantly involving the somatomotor, ventral attention, and subcortical networks, suggesting an emergence of more prominent brain structural abnormalities with illness onset that have trait-like stability over time.

CONCLUSIONS

Our findings may not only provide a refined picture of schizophrenia neuropathology from a network perspective, but also potentially contribute to more targeted and effective intervention strategies for individuals at different schizophrenia stages.

Disruption of network hierarchy pattern in bulimia nervosa reveals brain information integration disorder

The human brain works as a hierarchical organization that is a continuous axis spanning sensorimotor cortex to transmodal cortex (referring to cortex that integrates multimodal sensory information and participates in complex cognitive functions). Previous studies have demonstrated abnormalities in several specific networks that may account for their multiple behavioral deficits in patients with bulimia nervosa (BN), but whether and how the network hierarchical organization changes in BN remain unknown. This study aimed to investigate alterations of the hierarchy organization in BN network and their clinical relevance. Connectome gradient analyses were applied to depict the network hierarchy patterns of fifty-nine patients with BN and thirty-nine healthy controls (HCs). Then, we evaluated the network- and voxel-level gradient alterations of BN by comparing gradient values in each network and each voxel between patients with BN and HCs. Finally, the association between altered gradient values and clinical variables was explored. In the principal gradient, patients with BN exhibited reduced gradient values in dorsal attention network and increased gradient values in subcortical regions compared to HCs. In the secondary gradient, patients with BN showed decreased gradient values in ventral attention network and increased gradient values in limbic network. Regionally, the areas with altered principal or secondary gradient values in BN group were mainly located in transmodal networks, i.e., the default-mode and frontoparietal network. In BN group, the principal gradient values of right inferior frontal gyrus were negatively associated with external eating behavior. This study revealed the disordered network hierarchy patterns in patients with BN, which suggested a disturbance of brain information integration from attention network and subcortical regions to transmodal networks in these patients. These findings may provide insight into the neurobiological underpinnings of BN.

A longitudinal multimodal MRI study of the visual network in postoperative delirium

Although structural and functional damage to the brain is considered to be an important neurobiological mechanism of postoperative delirium (POD), alterations in the visual cortical network related to this vulnerability have not yet been determined. In this study, we investigated the impact of alterations in the visual network (VN), as measured by structural and functional magnetic resonance imaging (MRI), on the development of POD. Thirty-six adult patients with frontal glioma who underwent elective craniotomy were recruited. The primary outcome was POD 1-7 days after surgery, as assessed by the Confusion Assessment Method. Cognition before surgery was measured by a battery of neuropsychological tests. Then, we evaluated preoperative and postoperative gray matter volume (GMV) and functional connectivity (FC) alterations by voxel-based morphometry and resting-state functional MRI (rs-fMRI) between the POD and non-POD groups. Multiple logistic regression models were used to investigate the associations between neuroimaging biomarkers and the occurrence of POD. Compared to those in the non-POD group, a decreased GMV in the fusiform gyrus (0.181 [0.018] vs. 0.207 [0.022], FDRp = 0.001) and decreased FC between the fusiform gyrus and VN (0.351 [0.153] vs. 0.610 [0.197], GFRp < 0.001) were observed preoperatively in the POD group, and increased FC between the fusiform gyrus and ventral attentional network (0.538 [0.180] vs. 0.452 [0.184], GFRp =  < 0.001) was observed postoperatively in the POD group. According to our multiple logistic regression analysis, age (Odds ratio [OR]: 1.141 [1.015 to 1.282], P = 0.03) and preoperative fusiform-VN FC (OR 0.001 [0.001 to 0.067], P = 0.01) were significantly related to risk of POD. Our findings suggested that preoperative functional disconnectivity between fusiform and VN might be highly involved in the development of POD. These findings may allow for the discovery of additional underlying mechanisms.

Shared differential factors underlying individual spontaneous neural activity abnormalities in major depressive disorder

BACKGROUND

In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.

METHODS

To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.

RESULTS

Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.

CONCLUSIONS

This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.

Macroscale Gradient Dysfunction in Alzheimer's Disease: Patterns With Cognition Terms and Gene Expression Profiles

Macroscale functional gradient techniques provide a continuous coordinate system that extends from unimodal regions to transmodal higher-order networks. However, the alterations of these functional gradients in AD and their correlations with cognitive terms and gene expression profiles remain to be established. In the present study, we directly studied the functional gradients with functional MRI data from seven scanners. We adopted data-driven meta-analytic techniques to unveil AD-associated changes in the functional gradients. The principal primary-to-transmodal gradient was suppressed in AD. Compared to NCs, AD patients exhibited global connectome gradient alterations, including reduced gradient range and gradient variation, increased gradient scores in the somatomotor, ventral attention, and frontoparietal regions, and decreased in the default mode network. More importantly, the Gene Ontology terms of biological processes were significantly enriched in the potassium ion transport and protein-containing complex remodeling. Our compelling evidence provides a new perspective in understanding the connectome alterations in AD.

Changes in the structure of spontaneous speech predict the disruption of hierarchical brain organization in first-episode psychosis

Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher-order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis. We hypothesized that these changes as revealed in spontaneous speech patterns may act as readouts of alterations in the configuration of this unimodal-to-transmodal axis of cortical organization in psychosis. Results from 29 patients with first-episodic psychosis (FEP) and 29 controls scanned with 7 T resting-state fMRI confirmed a compression of the cortical hierarchy in FEP, which affected metrics of the hierarchical distance between the sensorimotor and default mode networks, and of the hierarchical organization within the semantic network. These organizational changes were predicted by graphs representing semantic and syntactic associations between meaningful units in speech produced during picture descriptions. These findings unite psychosis, language, and the cortical hierarchy in a single conceptual scheme, which helps to situate language within the neurocognition of psychosis and opens the clinical prospect for mental dysfunction to become computationally measurable in spontaneous speech.

The relationship between changes in functional connectivity gradients and cognitive-emotional disorders in sudden sensorineural hearing loss

Sudden sensorineural hearing loss, a prevalent emergency in otolaryngology, is known to potentially precipitate cognitive and emotional disorders in affected individuals. Extensive research has documented the phenomenon of cortical functional reorganization in patients with sudden sensorineural hearing loss. However, the potential link between this neural functional remodelling and cognitive-emotional disorders remains unclear. To investigate this issue, 30 bilateral sudden sensorineural hearing loss patients and 30 healthy adults were recruited for this study. We collected clinical data and resting-state functional magnetic resonance imaging data from the participants. Gradient mapping analysis was employed to calculate the first three gradients for each subject. Subsequently, gradient changes in sudden sensorineural hearing loss patients were compared with healthy controls at global, regional and network levels. Finally, we explored the relationship between gradient values and clinical variables. The results revealed that at the global level, sudden sensorineural hearing loss did not exhibit significant differences in the primary gradient but showed a state of compression in the second and third gradients. At the regional level, sudden sensorineural hearing loss patients exhibited a significant reduction in the primary gradient values in the temporal pole and ventral prefrontal cortex, which were closely related to neuro-scale scores. Regarding the network level, sudden sensorineural hearing loss did not show significant differences in the primary gradient but instead displayed significant changes in the control network and default mode network in the second and third gradients. This study revealed disruptions in the functional hierarchy of sudden sensorineural hearing loss, and the alterations in functional connectivity gradients were closely associated with cognitive and emotional disturbances in patients. These findings provide new evidence for understanding the functional remodelling that occurs in sudden sensorineural hearing loss.

Principles of cortical areas and their implications for neuroimaging

Cortical organization should constrain the study of how the brain performs behavior and cognition. A fundamental concept in cortical organization is that of arealization: that the cortex is parceled into discrete areas. In part one of this report, we review how non-human animal studies have illuminated principles of cortical arealization by revealing: (1) what defines a cortical area, (2) how cortical areas are formed, (3) how cortical areas interact with one another, and (4) what "computations" or "functions" areas perform. In part two, we discuss how these principles apply to neuroimaging research. In doing so, we highlight several examples where the commonly accepted interpretation of neuroimaging observations requires assumptions that violate the principles of arealization, including nonstationary areas that move on short time scales, large-scale gradients as organizing features, and cortical areas with singular functionality that perfectly map psychological constructs. Our belief is that principles of neurobiology should strongly guide the nature of computational explanations.

Morphological Brain Networks of White Matter: Mapping, Evaluation, Characterization, and Application

Although white matter (WM) accounts for nearly half of adult brain, its wiring diagram is largely unknown. Here, an approach is developed to construct WM networks by estimating interregional morphological similarity based on structural magnetic resonance imaging. It is found that morphological WM networks showed nontrivial topology, presented good-to-excellent test-retest reliability, accounted for phenotypic interindividual differences in cognition, and are under genetic control. Through integration with multimodal and multiscale data, it is further showed that morphological WM networks are able to predict the patterns of hamodynamic coherence, metabolic synchronization, gene co-expression, and chemoarchitectonic covariance, and associated with structural connectivity. Moreover, the prediction followed WM functional connectomic hierarchy for the hamodynamic coherence, is related to genes enriched in the forebrain neuron development and differentiation for the gene co-expression, and is associated with serotonergic system-related receptors and transporters for the chemoarchitectonic covariance. Finally, applying this approach to multiple sclerosis and neuromyelitis optica spectrum disorders, it is found that both diseases exhibited morphological dysconnectivity, which are correlated with clinical variables of patients and are able to diagnose and differentiate the diseases. Altogether, these findings indicate that morphological WM networks provide a reliable and biologically meaningful means to explore WM architecture in health and disease.

Chronic hypercortisolism disrupts the principal functional gradient in Cushing's disease: A multi-scale connectomics and transcriptomics study

Cushing's disease (CD) represents a state of cortisol excess, serving as a model to investigate the effects of prolonged hypercortisolism on functional brain. Potential alterations in the functional connectome of the brain may explain frequently reported cognitive deficits and affective disorders in CD patients. This study aims to elucidate the effects of chronic hypercortisolism on the principal functional gradient, which represents a hierarchical architecture with gradual transitions across cognitive processes, by integrating connectomics and transcriptomics approaches. Utilizing resting-state functional magnetic resonance imaging data from 140 participants (86 CD patients, 54 healthy controls) recruited at a single center, we explored the alterations in the principal gradient in CD patients. Further, we thoroughly explored the underlying associative mechanisms of the observed characteristic alterations with cognitive function domains, biological attributes, and neuropsychiatric representations, as well as gene expression profiles. Compared to healthy controls, CD patients demonstrated changes in connectome patterns in both primary and higher-order networks, exhibiting an overall converged trend along the principal gradient axis. The gradient values in CD patients' right prefrontal cortex and bilateral sensorimotor cortices exhibited a significant correlation with cortisol levels. Moreover, the cortical regions showing gradient alterations were principally associated with sensory information processing and higher-cognitive functions, as well as correlated with the gene expression patterns which involved synaptic components and function. The findings suggest that converged alterations in the principal gradient in CD patients may mediate the relationship between hypercortisolism and cognitive impairments, potentially involving genes regulating synaptic components and function.

Brain network functional connectivity changes in long illness duration chronic schizophrenia

Introduction

Chronic schizophrenia has a course of 5 years or more and has a widespread abnormalities in brain functional connectivity. This study aimed to find characteristic functional and structural changes in a long illness duration chronic schizophrenia (10 years or more).

Methods

Thirty-six patients with a long illness duration chronic schizophrenia and 38 healthy controls were analyzed by independent component analysis of brain network functional connectivity. Correlation analysis with clinical duration was performed on six resting state networks: auditory network, default mode network, dorsal attention network, fronto-parietal network, somatomotor network, and visual network.

Results

The differences in the resting state network between the two groups revealed that patients exhibited enhanced inter-network connections between default mode network and multiple brain networks, while the inter-network connections between somatomotor network, default mode network and visual network were reduced. In patients, functional connectivity of Cuneus_L was negatively correlated with illness duration. Furthermore, receiver operating characteristic curve of functional connectivity showed that changes in Thalamus_L, Rectus_L, Frontal_Mid_R, and Cerebelum_9_L may indicate a longer illness duration chronic schizophrenia.

Discussion

In our study, we also confirmed that the course of disease is significantly associated with specific brain regions, and the changes in specific brain regions may indicate that chronic schizophrenia has a course of 10 years or more.

The efficacy of low frequency repetitive transcial magnetic stimulation for treating auditory verbal hallucinations in schizophrenia: Insights from functional gradient analyses

Background

Auditory Verbal Hallucinations (AVH) constitute a prominent feature of schizophrenia. Although low-frequency repetitive transcranial magnetic stimulation (rTMS) has demonstrated therapeutic benefits in ameliorating AVH, the underlying mechanisms of its efficacy necessitate further elucidation.

Objective

This study investigated the cortical gradient characteristics and their associations with clinical responses in schizophrenia patients with AVH, mediated through 1 Hz rTMS targeting the left temporoparietal junction.

Method

Functional gradient metrics were employed to examine the hierarchy patterns of cortical organization, capturing whole-brain functional connectivity profiles in patients and controls.

Results

The 1 Hz rTMS treatment effectively ameliorated the positive symptoms in patients, specifically targeting AVH. Initial evaluations revealed expanded global gradient distribution patterns and specific principal gradient variations in certain brain regions in patients at baseline compared to a control cohort. Following treatment, these divergent global and local patterns showed signs of normalizing. Furthermore, there was observed a closer alignment in between-network dispersion among various networks after treatment, including the somatomotor, attention, and limbic networks, indicating a potential harmonization of brain functionality.

Conclusion

Low-frequency rTMS induces alternations in principal functional gradient patterns, may serve as imaging markers to elucidate the mechanisms underpinning the therapeutic efficacy of rTMS on AVH in schizophrenia.

Differences of individual gray matter networks between MCI patients who converted to AD within 3 Years and nonconverters

Objective

Here we aimed to explore the differences in individual gray matter (GM) networks at baseline in mild cognitive impairment patients who converted to Alzheimer's disease (AD) within 3 years (MCI-C) and nonconverters (MCI-NC).

Materials and methods

Data from 461 MCI patients (180 MCI-C and 281 MCI-NC) were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For each subject, a GM network was constructed using 3D-T1 imaging and the Kullback-Leibler divergence method. Gradient and topological analyses of individual GM networks were performed, and partial correlations were calculated to evaluate relationships among network properties, cognitive function, and apolipoprotein E (APOE) €4 alleles. Subsequently, a support vector machine (SVM) model was constructed to discriminate the MCI-C and MCI-NC patients at baseline.

Results

The gradient analysis revealed that the principal gradient score distribution was more compressed in the MCI-C group than in the MCI-NC group, with scores for the left lingual gyrus, right fusiform gyrus and left middle temporal gyrus being increased in the MCI-C group (p < 0.05, FDR corrected). The topological analysis showed significant differences in nodal efficiency in four nodes between the two groups. Furthermore, the regional gradient scores or nodal efficiency were found to be significantly related to the neuropsychological test scores, and the left middle temporal gyrus gradient scores were positively associated with the number of APOE €4 alleles (r = 0.192, p = 0.002). Ultimately, the SVM model achieved a balanced accuracy of 79.4% in classifying MCI-C and MCI-NC patients (p < 0.001).

Conclusion

The whole-brain GM network hierarchy in the MCI-C group was more compressed than that in the MCI-NC group, suggesting more serious cognitive impairments in the MCI-C group. The left middle temporal gyrus gradient scores were related to both cognitive function and APOE €4 alleles, thus serving as potential biomarkers distinguishing MCI-C from MCI-NC at baseline.

Functional gradients reveal cortical hierarchy changes in multiple sclerosis

Functional gradient (FG) analysis represents an increasingly popular methodological perspective for investigating brain hierarchical organization but whether and how network hierarchy changes concomitant with functional connectivity alterations in multiple sclerosis (MS) has remained elusive. Here, we analyzed FG components to uncover possible alterations in cortical hierarchy using resting-state functional MRI (rs-fMRI) data acquired in 122 MS patients and 97 healthy control (HC) subjects. Cortical hierarchy was assessed by deriving regional FG scores from rs-fMRI connectivity matrices using a functional parcellation of the cerebral cortex. The FG analysis identified a primary (visual-to-sensorimotor) and a secondary (sensory-to-transmodal) component. Results showed a significant alteration in cortical hierarchy as indexed by regional changes in FG scores in MS patients within the sensorimotor network and a compression (i.e., a reduced standard deviation across all cortical parcels) of the sensory-transmodal gradient axis, suggesting disrupted segregation between sensory and cognitive processing. Moreover, FG scores within limbic and default mode networks were significantly correlated (ρ = 0.30 $$ \rho =0.30 $$ , p < .005 after Bonferroni correction for both) with the symbol digit modality test (SDMT) score, a measure of information processing speed commonly used in MS neuropsychological assessments. Finally, leveraging supervised machine learning, we tested the predictive value of network-level FG features, highlighting the prominent role of the FG scores within the default mode network in the accurate prediction of SDMT scores in MS patients (average mean absolute error of 1.22 ± 0.07 points on a hold-out set of 24 patients). Our work provides a comprehensive evaluation of FG alterations in MS, shedding light on the hierarchical organization of the MS brain and suggesting that FG connectivity analysis can be regarded as a valuable approach in rs-fMRI studies across different MS populations.

Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges

Idiopathic generalized epilepsy (IGE) is characterized by cryptogenic etiology and the striatum and cerebellum are recognized as modulators of epileptic network. We collected simultaneous electroencephalogram and functional magnetic resonance imaging data from 145 patients with IGE, 34 of whom recorded interictal epileptic discharges (IEDs) during scanning. In states without IEDs, hierarchical connectivity was performed to search core cortical regions which might be potentially modulated by striatum and cerebellum. Node-node and edge-edge moderation models were constructed to depict direct and indirect moderation effects in states with and without IEDs. Patients showed increased hierarchical connectivity with sensorimotor cortices (SMC) and decreased connectivity with regions in the default mode network (DMN). In the state without IEDs, striatum, cerebellum, and thalamus were linked to weaken the interactions of regions in the salience network (SN) with DMN and SMC. In periods with IEDs, overall increased moderation effects on the interaction between regions in SN and DMN, and between regions in DMN and SMC were observed. The thalamus and striatum were implicated in weakening interactions between regions in SN and SMC. The striatum and cerebellum moderated the cortical interaction among DMN, SN, and SMC in alliance with the thalamus, contributing to the dysfunction in states with and without IEDs in IGE. The current work revealed state-specific modulation effects of striatum and cerebellum on thalamocortical circuits and uncovered the potential core cortical targets which might contribute to develop new clinical neuromodulation techniques.

Motor learning and performance in schizophrenia and aging: two different patterns of decline

Psychomotor slowing has consistently been observed in schizophrenia, however research on motor learning in schizophrenia is limited. Additionally, motor learning in schizophrenia has never been compared with the waning of motor learning abilities in the elderly. Therefore, in an extensive study, 30 individuals with schizophrenia, 30 healthy age-matched controls and 30 elderly participants were compared on sensorimotor learning tasks including sequence learning and adaptation (both explicit and implicit), as well as tracking and aiming. This paper presents new findings on an explicit motor sequence learning task, an explicit verbal learning task and a simple aiming task and summarizes all previously published findings of this large investigation. Individuals with schizophrenia and elderly had slower Movement Time (MT)s compared with controls in all tasks, however both groups improved over time. Elderly participants learned slower on tracking and explicit sequence learning while individuals with schizophrenia adapted slower and to a lesser extent to movement perturbations in adaptation tasks and performed less well on cognitive tests including the verbal learning task. Results suggest that motor slowing is present in schizophrenia and the elderly, however both groups show significant but different motor skill learning. Cognitive deficits seem to interfere with motor learning and performance in schizophrenia while task complexity and decreased movement precision interferes with motor learning in the elderly, reflecting different underlying patterns of decline in these conditions. In addition, evidence for motor slowing together with impaired implicit adaptation supports the influence of cerebellum and the cerebello-thalamo-cortical-cerebellar (CTCC) circuits in schizophrenia, important for further understanding the pathophysiology of the disorder.

Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age

Functional connectome gradients represent fundamental organizing principles of the brain. Here, we report the development of the connectome gradients in preterm and term babies aged 31-42 postmenstrual weeks using task-free functional MRI and its association with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present during the late preterm period and continuously evolves toward a term-like pattern. The global measurements of this gradient, characterized by explanation ratio, gradient range, and gradient variation, increased with age (p < 0.05, corrected). Focal gradient development mainly occurs in the sensorimotor, lateral, and medial parietal regions, and visual regions (p < 0.05, corrected). The connectome gradient at birth predicts cognitive and language outcomes at 2-year follow-up (p < 0.005). These results are replicated using an independent dataset from the Developing Human Connectome Project. Our findings highlight early emergent rules of the brain connectome gradient and their implications for later cognitive growth.

Abnormal higher-order network interactions in Parkinson's disease visual hallucinations

Visual hallucinations in Parkinson's disease can be viewed from a systems-level perspective, whereby dysfunctional communication between brain networks responsible for perception predisposes a person to hallucinate. To this end, abnormal functional interactions between higher-order and primary sensory networks have been implicated in the pathophysiology of visual hallucinations in Parkinson's disease, however the precise signatures remain to be determined. Dimensionality reduction techniques offer a novel means for simplifying the interpretation of multidimensional brain imaging data, identifying hierarchical patterns in the data that are driven by both within- and between-functional network changes. Here, we applied two complementary non-linear dimensionality reduction techniques-diffusion-map embedding and t-distributed stochastic neighbour embedding (t-SNE)-to resting state functional MRI data, in order to characterize the altered functional hierarchy associated with susceptibility to visual hallucinations. Our study involved 77 people with Parkinson's disease (31 with hallucinations; 46 without hallucinations) and 19 age-matched healthy control subjects. In patients with visual hallucinations, we found compression of the unimodal-heteromodal gradient consistent with increased functional integration between sensory and higher order networks. This was mirrored in a traditional functional connectivity analysis, which showed increased connectivity between the visual and default mode networks in the hallucinating group. Together, these results suggest a route by which higher-order regions may have excessive influence over earlier sensory processes, as proposed by theoretical models of hallucinations across disorders. By contrast, the t-SNE analysis identified distinct alterations in prefrontal regions, suggesting an additional layer of complexity in the functional brain network abnormalities implicated in hallucinations, which was not apparent in traditional functional connectivity analyses. Together, the results confirm abnormal brain organization associated with the hallucinating phenotype in Parkinson's disease and highlight the utility of applying convergent dimensionality reduction techniques to investigate complex clinical symptoms. In addition, the patterns we describe in Parkinson's disease converge with those seen in other conditions, suggesting that reduced hierarchical differentiation across sensory-perceptual systems may be a common transdiagnostic vulnerability in neuropsychiatric disorders with perceptual disturbances.

Resolving heterogeneity in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder through individualized structural covariance network analysis

Disruptions in large-scale brain connectivity are hypothesized to contribute to psychiatric disorders, including schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. However, high inter-individual variation among patients with psychiatric disorders hinders achievement of unified findings. To this end, we adopted a newly proposed method to resolve heterogeneity of differential structural covariance network in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. This method could infer individualized structural covariance aberrance by assessing the deviation from healthy controls. T1-weighted anatomical images of 114 patients with psychiatric disorders (schizophrenia: n = 37; bipolar I disorder: n = 37; attention-deficit/hyperactivity disorder: n = 37) and 110 healthy controls were analyzed to obtain individualized differential structural covariance network. Patients exhibited tremendous heterogeneity in profiles of individualized differential structural covariance network. Despite notable heterogeneity, patients with the same disorder shared altered edges at network level. Moreover, individualized differential structural covariance network uncovered two distinct psychiatric subtypes with opposite differences in structural covariance edges, that were otherwise obscured when patients were merged, compared with healthy controls. These results provide new insights into heterogeneity and have implications for the nosology in psychiatric disorders.

Reshaping the Cortical Connectivity Gradient by Long-Term Cognitive Training During Development

The organization of the brain follows a topological hierarchy that changes dynamically during development. However, it remains unknown whether and how cognitive training administered over multiple years during development can modify this hierarchical topology. By measuring the brain and behavior of school children who had carried out abacus-based mental calculation (AMC) training for five years (starting from 7 years to 12 years old) in pre-training and post-training, we revealed the reshaping effect of long-term AMC intervention during development on the brain hierarchical topology. We observed the development-induced emergence of the default network, AMC training-promoted shifting, and regional changes in cortical gradients. Moreover, the training-induced gradient changes were located in visual and somatomotor areas in association with the visuospatial/motor-imagery strategy. We found that gradient-based features can predict the math ability within groups. Our findings provide novel insights into the dynamic nature of network recruitment impacted by long-term cognitive training during development.

Functional connectome hierarchy dysfunction in Alzheimer's disease and its relationship with cognition and gene expression profiling

Numerous researches have shown that the human brain organizes as a continuum axis crossing from sensory motor to transmodal cortex. Functional network alterations were commonly found in Alzheimer's disease (AD). Whether the hierarchy of AD brain networks has changed and how these changes related to gene expression profiling and cognition is unclear. Using resting-state functional magnetic resonance imaging data from 233 subjects (185 AD patients and 48 healthy controls), we studied the changes in the functional network gradients in AD. Moreover, we investigated the relationships between gradient alterations and cognition, and gene expression profiling, respectively. We found that the second gradient organizes as a continuum axis crossing from the sensory motor to the transmodal cortex. Compared to the healthy controls, the secondary gradient scores of the visual and somatomotor network (SOM) increased significantly in AD, and the secondary gradient scores of default mode and frontoparietal network decreased significantly in AD. The secondary gradient scores of SOM and salience network (SAL) significantly positively correlated with memory function in AD. The secondary gradient in SAL also significantly positively correlated with language function. The AD-related second gradient alterations were spatially associated with the gene expression and the relevant genes enriched in neurobiology-related pathways, specially expressed in various tissues, cell types, and developmental stages. These findings suggested the changes in the functional network gradients in AD and deepened our understanding of the correlation between macroscopic gradient structure and microscopic gene expression profiling in AD.

Test-retest reliability and predictive utility of a macroscale principal functional connectivity gradient

Mapping individual differences in brain function has been hampered by poor reliability as well as limited interpretability. Leveraging patterns of brain-wide functional connectivity (FC) offers some promise in this endeavor. In particular, a macroscale principal FC gradient that recapitulates a hierarchical organization spanning molecular, cellular, and circuit level features along a sensory-to-association cortical axis has emerged as both a parsimonious and interpretable measure of individual differences in behavior. However, the measurement reliabilities of this FC gradient have not been fully evaluated. Here, we assess the reliabilities of both global and regional principal FC gradient measures using test-retest data from the young adult Human Connectome Project (HCP-YA) and the Dunedin Study. Analyses revealed that the reliabilities of principal FC gradient measures were (1) consistently higher than those for traditional edge-wise FC measures, (2) higher for FC measures derived from general FC (GFC) in comparison with resting-state FC, and (3) higher for longer scan lengths. We additionally examined the relative utility of these principal FC gradient measures in predicting cognition and aging in both datasets as well as the HCP-aging dataset. These analyses revealed that regional FC gradient measures and global gradient range were significantly associated with aging in all three datasets, and moderately associated with cognition in the HCP-YA and Dunedin Study datasets, reflecting contractions and expansions of the cortical hierarchy, respectively. Collectively, these results demonstrate that measures of the principal FC gradient, especially derived using GFC, effectively capture a reliable feature of the human brain subject to interpretable and biologically meaningful individual variation, offering some advantages over traditional edge-wise FC measures in the search for brain-behavior associations.

Association Between MRI-Assessed Patterns of Connectome Gradient and Gene-Expression Profiles in Two Independent Patient Cohorts With Hepatitis B Virus-Related Cirrhosis

BACKGROUND

Patients with hepatitis B virus-related cirrhosis (HBV-RC) exhibit progressive neurologic dysfunction from primary sensorimotor to high-order cognition, as their disease advances. However, the exact neurobiologic mechanisms and the potential association with gene-expression profiles are not fully understood.

PURPOSE

To explore the hierarchical disorganization in the large-scale functional connectomes in HBV-RC patients and to investigate its potential underlying molecular basis.

STUDY TYPE

Prospective.

POPULATION

Fifty HBV-RC patients and 40 controls (Cohort 1) and 30 HBV-RC patients and 38 controls (Cohort 2).

FIELD STRENGTH/SEQUENCE

Gradient-echo echo-planar and fast field echo sequences at 3.0 T (Cohort 1) and 1.5 T (Cohort 2).

ASSESSMENT

Data were processed with Dpabi and the BrainSpace package. Gradient scores were evaluated from global to voxel level. Cognitive measurement and patients grouping were based on psychometric hepatic encephalopathy scores. The whole-brain microarray-based gene-expression data were obtained from the AIBS website.

STATISTICAL TESTS

One-way ANOVA, chi-square test, two-sample t-test, Kruskal-Wallis test, Spearman's correlation coefficient (r), the gaussian random field correction, false discovery rate (FDR) correction and the Bonferroni correction. Significance level: P < 0.05.

RESULTS

HBV-RC patients exhibited a robust and replicable connectome gradient dysfunction, which was significantly associated with the gene-expression profiles in both cohorts (r = 0.52 and r = 0.56, respectively). The most correlated genes were enriched in γ-aminobutyric acid (GABA) and GABA-related receptor genes (FDR q value <0.05). Moreover, the connectome gradient dysfunction at network level observed in HBV-RC patients correlated with their poor cognitive performance (Cohort 2: visual network, r = -0.56; subcortical network, r = 0.66; frontoparietal network, r = 0.51).

DATA CONCLUSION

HBV-RC patients had hierarchical disorganization in the large-scale functional connectomes, which may underly their cognitive impairment. In addition, we showed the potential molecular mechanism of the connectome gradient dysfunction, which suggested the importance of GABA and GABA-related receptor genes.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

Atypical Hierarchical Connectivity Revealed by Stepwise Functional Connectivity in Aging

Hierarchical functional structure plays a crucial role in brain function. We aimed to investigate how aging affects hierarchical functional structure and to evaluate the relationship between such effects and molecular, microvascular, and cognitive features. We used resting-state functional magnetic resonance imaging (fMRI) data from 95 older adults (66.94 ± 7.23 years) and 44 younger adults (21.8 ± 2.53 years) and employed an innovative graph-theory-based analysis (stepwise functional connectivity (SFC)) to reveal the effects of aging on hierarchical functional structure in the brain. In the older group, an SFC pattern converged on the primary sensory-motor network (PSN) rather than the default mode network (DMN). Moreover, SFC decreased in the DMN and increased in the PSN at longer link-steps in aging, indicating a reconfiguration of brain hub systems during aging. Subsequent correlation analyses were performed between SFC values and molecular, microvascular features, and behavioral performance. Altered SFC patterns were associated with dopamine and serotonin, suggesting that altered hierarchical functional structure in aging is linked to the molecular fundament with dopamine and serotonin. Furthermore, increased SFC in the PSN, decreased SFC in the DMN, and accelerated convergence rate were all linked to poorer microvascular features and lower executive function. Finally, a mediation analysis among SFC features, microvascular features, and behavioral performance indicated that the microvascular state may influence executive function through SFC features, highlighting the interactive effects of SFC features and microvascular state on cognition.

Revising a Self-Regulation Phenotype for Depression Through Individual Differences in Macroscale Brain Organization

Self-regulation denotes the processes by which people initiate, maintain, and control their own thoughts, behaviors, or emotions to produce a desired outcome or avoid an undesired outcome. Self-regulation brings the influence of distal factors such as biology, temperament, and socialization history onto cognition, motivation, and behavior. Dysfunction in self-regulation represents a contributory causal factor for psychopathology. Accordingly, we previously proposed a risk phenotype model for depression drawing from regulatory focus theory and traditional task-based fMRI studies. In this article, we revise and expand our risk phenotype model using insights from new methodologies allowing quantification of individual differences in task-free macroscale brain organization. We offer a set of hypotheses as examples of how examination of intrinsic macroscale brain organization can extend and enrich investigations of self-regulation and depression. In doing so, we hope to promote a useful heuristic for model development and for identifying transdiagnostic risk phenotypes in psychopathology.

Cortical hierarchy disorganization in major depressive disorder and its association with suicidality

Objectives

To explore the suicide risk-specific disruption of cortical hierarchy in major depressive disorder (MDD) patients with diverse suicide risks.

Methods

Ninety-two MDD patients with diverse suicide risks and 38 matched controls underwent resting-state functional MRI. Connectome gradient analysis and stepwise functional connectivity (SFC) analysis were used to characterize the suicide risk-specific alterations of cortical hierarchy in MDD patients.

Results

Relative to controls, patients with suicide attempts (SA) had a prominent compression from the sensorimotor system; patients with suicide ideations (SI) had a prominent compression from the higher-level systems; non-suicide patients had a compression from both the sensorimotor system and higher-level systems, although it was less prominent relative to SA and SI patients. SFC analysis further validated this depolarization phenomenon.

Conclusion

This study revealed MDD patients had suicide risk-specific disruptions of cortical hierarchy, which advance our understanding of the neuromechanisms of suicidality in MDD patients.

Influence of vigilance-related arousal on brain dynamics: Potentials of new approaches

Growing research has focused on how mesoscopic activity in the brain develops over time and space. Recent influential studies using functional imaging have characterized brain dynamics in terms of the spread of activation across the brain following a unimodal to transmodal axis. In parallel, a number of studies have assessed changes of brain connectivity in terms of vigilance-linked arousal. Here I offer a view on how these two lines of research can lead to a deeper understanding of how arousal shapes the brain's dynamic behavior. This knowledge could have great impact on the investigation of mental disease.

Abnormal Structural Network Communication Reflects Cognitive Deficits in Schizophrenia

Schizophrenia has long been thought to be a disconnection syndrome and several previous studies have reported widespread abnormalities in white matter tracts in individuals with schizophrenia. Furthermore, reductions in structural connectivity may also impair communication between anatomically unconnected pairs of brain regions, potentially impacting global signal traffic in the brain. Therefore, we used different communication models to examine direct and indirect structural connections (polysynaptic) communication in large-scale brain networks in schizophrenia. Diffusion-weighted magnetic resonance imaging scans were acquired from 62 patients diagnosed with schizophrenia and 35 controls. In this study, we used five network communication models including, shortest paths, navigation, diffusion, search information and communicability to examine polysynaptic communication in large-scale brain networks in schizophrenia. We showed less efficient communication between spatially widespread brain regions particulary encompassing cortico-subcortical basal ganglia network in schizophrenia group relative to controls. Then, we also examined whether reduced communication efficiency was related to clinical symptoms in schizophrenia group. Among different measures of communication efficiency, only navigation efficiency was associated with global cognitive impairment across multiple cognitive domains including verbal learning, processing speed, executive functions and working memory, in individuals with schizophrenia. We did not find any association between communication efficiency measures and positive or negative symptoms within the schizophrenia group. Our findings are important for improving our mechanistic understanding of neurobiological process underlying cognitive symptoms in schizophrenia.

The genetic influence of the DRD3 rs6280 polymorphism (Ser9Gly) on functional connectivity and gray matter volume of the hippocampus in patients with first-episode, drug-naïve schizophrenia

The D3 dopamine receptor (DRD3) plays a major role in cognitive function and is a candidate gene for schizophrenia. DRD3 is widely distributed in the hippocampus, but whether there are potential associations between the rs6280 genotype, the hippocampus, and cognitive function in first-episode, drug-naïve (FES) patients and healthy controls (HCs) is still poorly understood. First, using functional and structural magnetic resonance imaging data, we calculated the gray matter volume (GMV) and functional connectivity (FC) of the hippocampus. Then, we examined the possible interaction effect of the DRD3 genotype and the disease on the FC and GMV of the hippocampus in 52 FES patients and 51 HCs. Finally, the correlation between the FC and GMV in the hippocampus, influenced by rs6280, and the cognitive performance of subjects was analyzed. A significant interaction effect of diagnostic group by genotype of rs6280 on the GMV of the left hippocampus was found, with lower GMV in FES patients that were C carriers compared with TT homozygotes; the opposite pattern was found in the genetic subgroups of HCs. In the FES group, C carriers performed significantly worse on reasoning and problem-solving tests than TT homozygotes. The left hippocampal GMV positively correlated with reasoning and problem-solving performance in TT homozygotes, but this correlation disappeared in FES patients that were C carriers and in genetic subgroups of HCs. Together, these results suggest that FES patients that are C carriers of rs6280 have lower GMV in the hippocampus, resulting in greater cognitive impairment.

Hierarchical functional system development supports executive function

In this perspective, we describe how developmental improvements in youth executive function (EF) are supported by hierarchically organized maturational changes in functional brain systems. We first highlight evidence that functional brain systems are embedded within a hierarchical sensorimotor-association axis of cortical organization. We then review data showing that functional system developmental profiles vary along this axis: systems near the associative end become more functionally segregated, while those in the middle become more integrative. Developmental changes that strengthen the hierarchical organization of the cortex may support EF by facilitating top-down information flow and balancing within- and between-system communication. We propose a central role for attention and frontoparietal control systems in the maturation of healthy EF and suggest that reduced functional system differentiation across the sensorimotor-association axis contributes to transdiagnostic EF deficits.

Altered nonlinear Granger causality interactions in the large-scale brain networks of patients with schizophrenia

Objective.It has been demonstrated that schizophrenia (SZ) is characterized by functional dysconnectivity involving extensive brain networks. However, the majority of previous studies utilizing resting-state functional magnetic resonance imaging (fMRI) to infer abnormal functional connectivity (FC) in patients with SZ have focused on the linear correlation that one brain region may influence another, ignoring the inherently nonlinear properties of fMRI signals.Approach. In this paper, we present a neural Granger causality (NGC) technique for examining the changes in SZ's nonlinear causal couplings. We develop static and dynamic NGC-based analyses of large-scale brain networks at several network levels, estimating complicated temporal and causal relationships in SZ patients.Main results. We find that the NGC-based FC matrices can detect large and significant differences between the SZ and healthy control groups at both the regional and subnetwork scales. These differences are persistent and significantly overlapped at various network sparsities regardless of whether the brain networks were built using static or dynamic techniques. In addition, compared to controls, patients with SZ exhibited extensive NGC confusion patterns throughout the entire brain.Significance. These findings imply that the NGC-based FCs may be a useful method for quantifying the abnormalities in the causal influences of patients with SZ, hence shedding fresh light on the pathophysiology of this disorder.

Functional Gradients of the Cerebellum: a Review of Practical Applications

Gradient-based analyses have contributed to the description of cerebellar functional neuroanatomy. More recently, functional gradients of the cerebellum have been used as a multi-purpose tool for neuroimaging research. Here, we provide an overview of the many practical applications of cerebellar functional gradient analyses. These practical applications include examination of intra-cerebellar and cerebellar-extracerebellar organization; transformation of functional gradients into parcellations with discrete borders; projection of functional gradients calculated within cerebellar structures to other extracerebellar structures; interpretation of cerebellar neuroimaging findings using qualitative and quantitative methods; detection of differences in patient populations; and other more complex practical applications of cerebellar gradient-based analyses. This review may serve as an introduction and catalog of options for neuroscientists who wish to design and analyze imaging studies using functional gradients of the cerebellum.

Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan

An increasing number of studies have shown that the functional interactions between the thalamus and cerebral cortices play an important role in cognitive function and are influenced by age. Previous studies have revealed age-related changes in the thalamo-cortical system within individuals, while neglecting differences between individuals. Here, we characterized inter-subject functional correlation (ISFC) between the thalamus and several cortical brain networks in 500 healthy participants aged 18–87 years old from the Cambridge Centre for Aging and Neuroscience (Cam-CAN) cohort using movie-watching state fMRI data. General linear models (GLM) were performed to assess age-related changes in ISFC of thalamo-cortical networks and the relationship between ISFC and fluid intelligence. We found significant age-related decreases in ISFC between the posterior thalamus (e.g., ventral posterior nucleus and pulvinar) and the attentional network, sensorimotor network, and visual network (FDR correction with p &lt; 0.05). Meanwhile, the ISFC between the thalamus (mainly the mediodorsal nucleus and ventral thalamic nuclei) and higher-order cortical networks, including the default mode network, salience network and control network, showed complex changes with age. Furthermore, the altered ISFC of thalamo-cortical networks was positively correlated with decreased fluid intelligence (FDR correction with p &lt; 0.05). Overall, our results provide further evidence that alterations in the functional integrity of the thalamo-cortical system might play an important role in cognitive decline during aging.

Cortical connectivity gradients and local timescales during cognitive states are modulated by cognitive loads

Although resting-state fMRI studies support that human brain is topographically organized regarding localized and distributed processes, it is still unclear about the task-modulated cortical hierarchy in terms of distributed functional connectivity and localized timescales. To address, current study investigated the effect of cognitive load on cortical connectivity gradients and local timescales in the healthy brain using resting state fMRI as well as 1- and 2-back working memory task fMRI. The results demonstrated that (1) increased cognitive load was associated with lower principal gradient in transmodal cortices, higher principal gradient in primary cortices, decreased decay rate and reduced timescale variability; (2) global properties including gradient variability, timescale decay rate, timescale variability and network topology were all modulated by cognitive load, with timescale variability related to behavioral performance; and (3) at 2-back state, the timescale variability was indirectly and negatively linked with global network integration, which was mediated by gradient variability. In conclusion, current study provides novel evidence for load-modulated cortical connectivity gradients and local timescales during cognitive states, which could contribute to better understanding about cognitive load theory and brain disorders with cognitive dysfunction.

The development of cortical functional hierarchy is associated with the molecular organization of prenatal/postnatal periods

The human cerebral cortex conforms to specific functional hierarchies facilitating information processing and higher-order cognition. Prior studies in adults have unveiled a dominant functional hierarchy spanning from sensorimotor regions to transmodal regions, which is also present in younger cohorts. However, how the functional hierarchy develops and the underlying molecular mechanisms remain to be investigated. Here, we set out to investigate the developmental patterns of the functional hierarchy for preschool children (#scans = 141, age = 2.41-6.90 years) using a parsimonious general linear model and the underlying biological mechanisms by combining the neuroimaging developmental pattern with two separate transcriptomic datasets (i.e. Allen Human Brain Atlas and BrainSpan Atlas). Our results indicated that transmodal regions were further segregated from sensorimotor regions and that such changes were potentially driven by two gene clusters with distinct enrichment profiles, namely prenatal gene cluster and postnatal gene cluster. Additionally, we found similar developmental profiles manifested in subsequent developmental periods by conducting identical analyses on the Human Connectome Projects in Development (#scans = 638, age = 5.58-21.92 years) and Philadelphia Neurodevelopment Cohort datasets (#scans = 795, age = 8-21 years), driven by concordant two gene clusters. Together, these findings illuminate a comprehensive developmental principle of the functional hierarchy and the underpinning molecular factors, and thus may shed light on the potential pathobiology of neurodevelopmental disorders.

Charting the dorsal-medial functional gradient of the default mode network in major depressive disorder

Major depressive disorder (MDD) is a common and disabling psychiatric condition associated with aberrant functional activity of the default mode network (DMN). However, it is unclear how the DMN dysfunction in MDD patients is characterized by functional connectivity diversity or gradient and whether antidepressant therapy causes the abnormal functional gradient of the DMN to change toward normalization. In current work, we estimated the functional gradient of the DMN derived from resting state functional magnetic resonance imaging in MDD patients (n = 70) and matching healthy controls (n = 43) and identified MDD-related functional connectivity diversity of the DMN. The longitudinal changes of the DMN functional gradient in 36 MDD patients were assessed before and after 12-week antidepressant treatment. Compared to the healthy controls, the functional gradient of the DMN exhibited relatively relative compression along the dorsal-medial axis in MDD patients at baseline and antidepressant treatment could normalize these DMN gradient abnormalities. A regularized least-squares regression model based on DMN gradient features at baseline significantly predicted the change of Hamilton Depression Rating (HAMD) Scale scores after antidepressant treatment. The medial prefrontal cortex gradient had a more contribution to prediction of antidepressant efficacy. Our findings provided a novel insight into the neurobiological mechanism underlying MDD from the perspective of the DMN functional gradient.