Resting-state functional connectivity reflects structural connectivity in the default mode network

The architecture of the human default mode network explored through cytoarchitecture, wiring and signal flow

The default mode network (DMN) is implicated in many aspects of complex thought and behavior. Here, we leverage postmortem histology and in vivo neuroimaging to characterize the anatomy of the DMN to better understand its role in information processing and cortical communication. Our results show that the DMN is cytoarchitecturally heterogenous, containing cytoarchitectural types that are variably specialized for unimodal, heteromodal and memory-related processing. Studying diffusion-based structural connectivity in combination with cytoarchitecture, we found the DMN contains regions receptive to input from sensory cortex and a core that is relatively insulated from environmental input. Finally, analysis of signal flow with effective connectivity models showed that the DMN is unique amongst cortical networks in balancing its output across the levels of sensory hierarchies. Together, our study establishes an anatomical foundation from which accounts of the broad role the DMN plays in human brain function and cognition can be developed.

Functional movement disorder is associated with abnormal interoceptive brain activity: a task-based functional MRI study

Background

Aberrant interoceptive processing has been hypothesized to contribute to the pathophysiology of functional neurological disorder, although findings have been inconsistent. Here, we utilized functional magnetic resonance imaging (fMRI) to examine neural correlates of interoceptive attention - the conscious focus and awareness of bodily sensations - in functional movement disorder (FMD).

Methods

We used voxelwise analyses to compare blood oxygenation level-dependent responses between 13 adults with hyperkinetic FMD and 13 healthy controls (HCs) during a task requiring attention to different bodily sensations and to an exteroceptive stimulus. Additionally, we examined between-group differences in self-reported measures of interoception and evaluated their relationship with neural activity.

Results

Interoceptive conditions (heartbeat, stomach and 'body', indicating sensations from the body part or limb affected in FMD participants) activated a network involving the precuneus, the posterior cingulate cortex (PCC) and caudate nucleus (CN) bilaterally, and the right anterior insula (aINS) (p <0.05, corrected). Group differences in brain activity were mainly driven by processing of disease-related interoceptive signals, which in the FMD group was associated with a broader neural activation than monitoring gastric interoception, while no group differences were detected during cardiac interoception. Differences based on interoceptive focus (body vs heartbeat and stomach) between FMD subjects and HCs were found in PCC, CN, angular gyrus, thalamus, and in the mid-insula (p <0.05, corrected).

Conclusions

This is, to our knowledge, the first study showing that FMD is associated with abnormal interoceptive processing in regions involved in monitoring body state, attentional focus, and homeostatic inference.

From histology to macroscale function in the human amygdala

The amygdala is a subcortical region in the mesiotemporal lobe that plays a key role in emotional and sensory functions. Conventional neuroimaging experiments treat this structure as a single, uniform entity, but there is ample histological evidence for subregional heterogeneity in microstructure and function. The current study characterized subregional structure-function coupling in the human amygdala, integrating post-mortem histology and in vivo MRI at ultra-high fields. Core to our work was a novel neuroinformatics approach that leveraged multiscale texture analysis as well as non-linear dimensionality reduction techniques to identify salient dimensions of microstructural variation in a 3D post-mortem histological reconstruction of the human amygdala. We observed two axes of subregional variation in this region, describing inferior-superior as well as mediolateral trends in microstructural differentiation that in part recapitulated established atlases of amygdala subnuclei. Translating our approach to in vivo MRI data acquired at 7 Tesla, we could demonstrate the generalizability of these spatial trends across 10 healthy adults. We then cross-referenced microstructural axes with functional blood-oxygen-level dependent (BOLD) signal analysis obtained during task-free conditions, and revealed a close association of structural axes with macroscale functional network embedding, notably the temporo-limbic, default mode, and sensory-motor networks. Our novel multiscale approach consolidates descriptions of amygdala anatomy and function obtained from histological and in vivo imaging techniques.

Microvascular structure variability explains variance in fMRI functional connectivity

The influence of regional brain vasculature on resting-state fMRI BOLD signals is well documented. However, the role of brain vasculature is often overlooked in functional connectivity research. In the present report, utilizing publicly available whole-brain vasculature data in the mouse, we investigate the relationship between functional connectivity and brain vasculature. This is done by assessing interregional variations in vasculature through a novel metric termed vascular similarity. First, we identify features to describe the regional vasculature. Then, we employ multiple linear regression models to predict functional connectivity, incorporating vascular similarity alongside metrics from structural connectivity and spatial topology. Our findings reveal a significant correlation between functional connectivity strength and regional vasculature similarity, especially in anesthetized mice. We also show that multiple linear regression models of functional connectivity using standard predictors are improved by including vascular similarity. We perform this analysis at the cerebrum and whole-brain levels using data from both male and female mice. Our findings regarding the relation between functional connectivity and the underlying vascular anatomy may enhance our understanding of functional connectivity based on fMRI and provide insights into its disruption in neurological disorders.

Simultaneous tACS-fMRI reveals state- and frequency-specific modulation of hippocampal-cortical functional connectivity

Non-invasive indirect hippocampal-targeted stimulation is of broad scientific and clinical interest. Transcranial alternating current stimulation (tACS) is appealing because it allows oscillatory stimulation to study hippocampal theta (3-8 Hz) activity. We found that tACS administered during functional magnetic resonance imaging yielded a frequency-, mental state- and topologically-specific effect of theta stimulation (but not other frequencies) enhancing right (but not left) hippocampal-cortical connectivity during resting blocks but not during task blocks. Control analyses showed that this effect was not due to possible stimulation-induced changes in signal quality or head movement. Our findings are promising for targeted network modulations of deep brain structures for research and clinical intervention.

The Effect of Modular Degeneracy on Neuroimaging Data

Introduction: The concept of community structure, based on modularity, is widely used to address many systems-level queries. However, its algorithm, based on the maximization of the modularity index Q, suffers from degeneracy problem, which yields a set of different possible solutions. Methods: In this work, we explored the degeneracy effect of modularity principle on resting-state functional magnetic resonance imaging (rsfMRI) data, when it is used to parcellate the cingulate cortex using data from the Human Connectome Project. We proposed a new iterative approach to address this limitation. Results: Our results show that current modularity approaches furnish a variety of different solutions, when these algorithms are repeated, leading to different number of subdivisions for the cingulate cortex. Our new proposed method, however, overcomes this limitation and generates more stable solution for the final partition. Conclusion: With this new method, we were able to mitigate the degeneracy problem and offer a tool to use modularity in a more reliable manner, when applying it to rsfMRI data.

Alterations in resting-state EEG functional connectivity in patients with major depressive disorder receiving electroconvulsive therapy: A systematic review

Electroconvulsive therapy (ECT) is highly efficacious for the treatment of major depressive disorder (MDD), but its mechanisms still require clarification. Even though depression is associated with alterations in functional connectivity (FC), EEG studies investigating effects of ECT on FC have not been systematically reviewed. Understanding these effects may help to identify the role of functional brain circuits in depression and its remission. This systematic review aimed to synthesize EEG studies investigating FC changes in ECT-treated patients with depression. A systematic literature search was conducted following PRISMA guidelines. Peer-reviewed studies on pre-to post-ECT resting-state EEG FC changes in adult patients with MDD were included. Three of 143 studies were included, of which two reported reduced FC in the alpha and beta frequency bands and increased theta band FC in patients with ECT-treated MDD. Changes in alpha band FC were associated with treatment outcomes. Patients with MDD exhibit increased electrophysiological resting-state alpha band FC, particularly frontally, compared with healthy subjects. Thus, ECT-induced decrease might indicate a trend toward normalization of oscillatory brain rhythms. As brain oscillations have been proposed to be involved in neuronal synchronization, which is important for communication between networks, the potential restoration in patients with depression and the association of FC changes with clinical improvement may indicate a potential mechanism of action of ECT. Understanding ECT's underlying mechanisms might ultimately enable treatment optimization, thus enhancing patient care. However, the number of studies is limited, with low-to-moderate EEG study quality, small sample sizes, and different electrophysiological FC measures.

An insight from the default mode network in patients with amnesia following left thalamic infarction involving the mediodorsal nucleus and mammillothalamic tract

The role of the medial part of the thalamus, and in particular the mediodorsal nucleus (MD) and the mammillothalamic tract (MTT), in memory has long been studied, but their contribution remains unclear. While the main functional hypothesis regarding the MTT focuses on memory, some authors postulate that the MD plays a supervisory executive role (indirectly affecting memory retrieval) due to its dense structural connectivity with the prefrontal cortex (PFC). Recently, it has been proposed that the MD, MTT and PFC form part of the DMN the default mode network (DMN). Due to the theoretical presence of MD and MTT in the DMN, we aimed to show the effect of thalamic lesions on functional connectivity (FC) and its putative role in cognitive impairment. We recruited 12 patients with left thalamic infarction and 12 matched healthy controls. They underwent neuropsychological assessment including memory tasks, morphological 3D MRI and resting state fMRI. A ROI-to-ROI method was used for group-level FC analyses. Patients had lesions in the MD and ventrolateral nuclei, with a damaged mammillothalamic tract (MTT) in seven of them. They showed lower performance than controls on verbal memory, executive function and language tests, with more impairment in memory, working memory, semantic verbal fluency and attention in the MTT-damaged patients. Contrast analyses between patients and matched controls showed lower FC in the ventral and dorsal DMN. Correlation analyses (patients and controls pooled) showed i/a positive correlation between memory and DMN, and ii/that MTT volume correlated with decreased functional connectivity in the dorsal DMN, whereas there was no correlation with MD lesion volume. These results suggest that both the memory impairment and the DMN functional change we observed may reflect an effect of the MTT lesion rather than MD damage.

Linking structural and functional changes during healthy aging and semantic dementia using multilayer brain network analysis

Healthy aging is characterized by frontal and diffuse brain changes, while certain age-related pathologies such as semantic dementia will be associated with more focal brain lesions, particularly in the temporo-parietal regions. These changes in structural integrity could influence functional brain networks. Here we use multilayer brain network analysis on structural (DWI) and functional (fMRI) data in younger and older healthy individuals and patients with semantic dementia. Relative to younger adults, results revealed lower levels of similarity of connectivity patterns between brain structure and function, and an increased network clustering in frontal regions in healthy older individuals. These changes were either associated with a preservation (similarity) and a decrease (clustering) in cognitive performance. Patients with semantic dementia showed an increase in the similarity of structural and functional connectivity patterns, as well as an increase in clustering in temporo-parietal regions. These changes were respectively associated with a preservation and a decrease in cognitive performance. These results provide a better characterization of distinct profiles of age- and pathology-brain network changes and their association with the preservation or the decline of cognitive functions.

Early changes in spatiotemporal dynamics of remapped circuits and global networks predict functional recovery after stroke in mice

Significance

Stroke is the leading cause of chronic disability in the United States. How stroke size affects post-stroke repair and recovery is poorly understood.

Aim

We aim to investigate the effects of stroke size on early repair patterns and determine how early changes in neuronal circuits and networks predict functional outcomes after stroke.

Approach

We used wide-field optical imaging, photothrombosis, and the cylinder-rearing assay to examine changes in neuronal circuit and network activity in the context of functional recovery after stroke.

Results

Larger strokes ablating S 1 FP caused diffuse and widespread forepaw stimulus-evoked cortical activation, including contralesional regions evolving within 4 weeks post-stroke; smaller strokes resulted in more focused ipsilesional activation. Larger strokes decreased neuronal fidelity and bilateral coherence during stimulation of either the affected or unaffected forepaw within this 4-week period. Mice in the larger lesion group demonstrated hyperconnectivity within the contralesional hemisphere at the resting state. Greater degrees of remapping diffusivity, neuronal fidelity degradation, and hyperconnectivity predicted worse 8-week recovery after statistically controlling for the effect of infarct size.

Conclusions

These results suggest that diffuse patterns of remapping, and desynchronization and hyperconnectivity of cortical networks, evolving early after stroke may reflect maladaptive plasticity, predicting poor long-term functional recovery.

Sex-Specific White Matter Abnormalities Across the Dynamic Pain Connectome in Neuropathic Pain: A Fixel-Based Analysis Study

A fundamental issue in neuroscience is a lack of understanding regarding the relationship between brain function and the white matter architecture that supports it. Individuals with chronic neuropathic pain (NP) exhibit functional abnormalities throughout brain networks collectively termed the "dynamic pain connectome" (DPC), including the default mode network (DMN), salience network, and ascending nociceptive and descending pain modulation systems. These functional abnormalities are often observed in a sex-dependent fashion. However, the enigmatic white matter structural features underpinning these functional networks and the relationship between structure and function/dysfunction in NP remain poorly understood. Here we used fixel-based analysis of diffusion weighted imaging data in 80 individuals (40 with NP [21 female, 19 male] and 40 sex- and age-matched healthy controls [HCs]) to evaluate white matter microstructure (fiber density [FD]), macrostructure (fiber bundle cross section) and combined microstructure and macrostructure (fiber density and cross section) within anatomical connections that support the DPC. We additionally examined whether there are sex-specific abnormalities in NP white matter structure. We performed fixel-wise and connection-specific mean analyses and found three main ways in which individuals with NP differed from HCs: (1) people with NP exhibited abnormally low FD and FDC within the corona radiata consistent with the ascending nociceptive pathway between the sensory thalamus and primary somatosensory cortex (S1). Furthermore, the entire sensory thalamus-S1 pathway exhibited abnormally low FD and FDC in people with NP, and this effect was driven by the females with NP; (2) females, but not males, with NP had abnormally low FD within the cingulum consistent with the right medial prefrontal cortex-posterior cingulate cortex DMN pathway; and (3) individuals with NP had higher connection-specific mean FDC than HCs in the anterior insula-temporoparietal junction and sensory thalamus-posterior insula pathways. However, sex-specific analyses did not corroborate these connection-specific findings in either females or males with NP. Our findings suggest that females with NP exhibit microstructural and macrostructural white matter abnormalities within the DPC networks including the ascending nociceptive system and DMN. We propose that aberrant white matter structure contributes to or is driven by functional abnormalities associated with NP. Our sex-specific findings highlight the utility and importance of using sex-disaggregated analyses to identify white matter abnormalities in clinical conditions such as chronic pain.

Aberrant functional connectivity between the retrosplenial cortex and hippocampal subregions in amnestic mild cognitive impairment and Alzheimer's disease

The posterior cingulate cortex and hippocampus are the core regions involved in episodic memory, and they exhibit functional connectivity changes in the development and progression of Alzheimer's disease. Previous studies have demonstrated that the posterior cingulate cortex and hippocampus are both cytoarchitectonically heterogeneous regions. Specifically, the retrosplenial cortex, typically subsumed under the posterior cingulate cortex, is an area functionally and anatomically distinct from the posterior cingulate cortex, and the hippocampus is composed of several subregions that participate in multiple cognitive processes. However, little is known about the functional connectivity patterns of the retrosplenial cortex or other parts of the posterior cingulate cortex with hippocampal subregions and their differential vulnerability to Alzheimer's disease pathology. Demographic data, neuropsychological assessments, and resting-state functional magnetic resonance imaging data were collected from 60 Alzheimer's disease participants, 60 participants with amnestic mild cognitive impairment, and 60 sex-matched normal controls. The bilateral retrosplenial cortex, other parts of the posterior cingulate cortex, and hippocampus subregions (including the bilateral anterior hippocampus and posterior hippocampus) were selected to investigate functional connectivity alterations in amnestic mild cognitive impairment and Alzheimer's disease. Resting-state functional connectivity analysis demonstrated heterogeneity in the degree of connectivity between the hippocampus and different parts of the total posterior cingulate cortex, with considerably greater functional connectivity of the retrosplenial cortex with the hippocampus compared with other parts of the posterior cingulate cortex. Furthermore, the bilateral retrosplenial cortex exhibited widespread intrinsic functional connectivity with all anterior-posterior hippocampus subregions. Compared to the normal controls, the amnestic mild cognitive impairment and Alzheimer's disease groups showed different magnitudes of decreased functional connectivity between the retrosplenial cortex and the contralateral posterior hippocampus. Additionally, diminished functional connectivity between the left retrosplenial cortex and right posterior hippocampus was correlated with clinical disease severity in amnestic mild cognitive impairment subjects, and the combination of multiple functional connectivity indicators of the retrosplenial cortex can discriminate the three groups from each other. These findings confirm and extend previous studies suggesting that the retrosplenial cortex is extensively and functionally connected with hippocampus subregions and that these functional connections are selectively affected in the Alzheimer's disease continuum, with prominent disruptions in functional connectivity between the retrosplenial cortex and contralateral posterior hippocampus underpinning episodic memory impairment associated with the disease.

White Matter-Gray Matter Correlation Analysis Based on White Matter Functional Gradient

BACKGROUND

The spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals of the brain's gray matter (GM) have been interpreted as representations of neural activity variations. In previous research, white matter (WM) signals, often considered noise, have also been demonstrated to reflect characteristics of functional activity and interactions among different brain regions. Recently, functional gradients have gained significant attention due to their success in characterizing the functional organization of the whole brain. However, previous studies on brain functional gradients have predominantly focused on GM, neglecting valuable functional information within WM.

METHODS

In this paper, we have elucidated the symmetrical nature of the functional hierarchy in the left and right brain hemispheres in healthy individuals, utilizing the principal functional gradient of the whole-brain WM while also accounting for gender differences.

RESULTS

Interestingly, both males and females exhibit a similar degree of asymmetry in their brain regions, albeit with distinct regional variations. Additionally, we have thoroughly examined and analyzed the distribution of functional gradient values in the spatial structure of the corpus callosum (CC) independently, revealing that a simple one-to-one correspondence between structure and function is absent. This phenomenon may be associated with the intricacy of their internal structural connectivity.

CONCLUSIONS

We suggest that the functional gradients within the WM regions offer a fresh perspective for investigating the structural and functional characteristics of WM and may provide insights into the regulation of neural activity between GM and WM.

Neural processing of sad and happy autobiographical memories in women with depression and borderline personality disorder

Patients with major depressive disorder (MDD) and borderline personality disorder (BPD) are reported to have disrupted autobiographical memory (AM). Using functional magnetic resonance imaging we investigated behavioral and neural processing of the recall of emotional (sad and happy) memories in 30 MDD, 18 BPD, and 34 healthy control (HC) unmedicated women. The behavioral results showed that the MDD group experienced more sadness than the HC after the sad recall, while BPD participants experienced less happiness than HC after the happy recall. The fMRI results for sad AMs, compared to happy AMs, elicited greater activation in multiple brain regions (i.e., medial prefrontal cortex, posterior cingulate cortex, insula) linked to self-related information, emotional processing, and semantic recollection across all groups. Functional connectivity analysis revealed a significant main effect of group between the occipital cortex and precuneus and between occipital cortex and posterior cingulate cortex. The effect was driven by stronger connectivity between the occipital cortex and precuneus in the clinical groups taken together than in the HC. Our results suggest a need for stronger coordination between visual imagery and contextual recall for vivid memory retrieval in these clinical groups.

Effects on Multimodal Connectivity Patterns in Female Schizophrenia During 8 Weeks of Antipsychotic Treatment

BACKGROUND AND HYPOTHESIS

Respective abnormal structural connectivity (SC) and functional connectivity (FC) have been reported in individuals with schizophrenia. However, transmodal associations between SC and FC following antipsychotic treatment, especially in female schizophrenia, remain unclear. We hypothesized that increased SC-FC coupling may be found in female schizophrenia, and could be normalized after antipsychotic treatment.

STUDY DESIGN

Sixty-four female drug-naïve patients with first-diagnosed schizophrenia treated with antipsychotic drugs for 8 weeks, and 55 female healthy controls (HCs) were enrolled. Magnetic resonance imaging (MRI) data were collected from HCs at baseline and from patients at baseline and after treatment. SC and FC were analyzed by network-based statistics, calculating nonzero SC-FC coupling of the whole brain and altered connectivity following treatment. Finally, an Elastic-net logistic regression analysis was employed to establish a predictive model for evaluating the clinical efficacy treatment.

STUDY RESULTS

At baseline, female schizophrenia patients exhibited abnormal SC in cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, and limbic-cerebellar connectivity compared to HCs, while FC showed no abnormalities. Following treatment, cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, temporal-cerebellar, and limbic-cerebellar connectivity were altered in both SC and FC. Additionally, SC-FC coupling of altered connectivity was higher in patients at baseline than in HC, trending toward normalization after treatment. Furthermore, identified FC or/and SC predicted changes in psychopathological symptoms and cognitive impairment among female schizophrenia following treatment.

CONCLUSIONS

SC-FC coupling may be a potential predictive biomarker of treatment response. Cortico-cortical, frontal-limbic, frontal-striatal, limbic-striatal, temporal-cerebellar, and limbic-cerebellar could represent major targets for antipsychotic drugs in female schizophrenia.

Structural-functional connectivity decoupling in multiscale brain networks in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative disease associated with functional and structural alterations beyond the nigrostriatal dopamine projection. However, the structural-functional (SC-FC) coupling changes in combination with subcortical regions at the network level are rarely investigated in PD.

METHODS

SC-FC coupling networks were systematically constructed using the structural connectivity obtained by diffusion tensor imaging and the functional connectivity obtained by resting-state functional magnetic resonance imaging in 53 PD and 72 age- and sex-matched healthy controls (HCs). Then, we explored how SC-FC coupling varied within and between several well-defined functional domains.

RESULTS

Results showed that the SC-FC coupling in patients with PD was globally reduced in comparison with HCs. Specifically, regional SC-FC decoupled in the inferior parietal lobule, occipitotemporal cortex, motor cortex, and higher-order association cortex in patients with PD. Moreover, PD showed intranetwork SC-FC decoupling in the visual network (VIS), limbic and higher-order association networks. Furthermore, internetwork decoupling mainly linked to the VIS, the somatomotor network (SOM), the dorsal attention network, and the default mode network, was observed, increased internetwork coupling was found between the subcortical network and the SOM in PD (all p < 0.05, FDR corrected).

CONCLUSIONS

These findings suggest that PD is characterized by SC-FC decoupling in topological organization of multiscale brain networks, providing insights into the brain network mechanisms in PD.

Discovering prominent differences in structural and functional connectomes using a multinomial stochastic block model

Understanding the differences between functional and structural human brain connectivity has been a focus of an extensive amount of neuroscience research. We employ a novel approach using the multinomial stochastic block model (MSBM) to explicitly extract components that characterize prominent differences across graphs. We analyze structural and functional connectomes derived from high-resolution diffusion-weighted MRI and fMRI scans of 250 Human Connectome Project subjects, analyzed at group connectivity level across 50 subjects. The inferred brain partitions revealed consistent, spatially homogeneous clustering patterns across inferred resolutions demonstrating the MSBM's reliability in identifying brain areas with prominent structure-function differences. Prominent differences in low-resolution brain maps (K = {3, 4} clusters) were attributed to weak functional connectivity in the bilateral anterior temporal lobes, while higher resolution results (K ≥ 25) revealed stronger interhemispheric functional than structural connectivity. Our findings emphasize significant differences in high-resolution functional and structural connectomes, revealing challenges in extracting meaningful connectivity measurements from both modalities, including tracking fibers through the corpus callosum and attenuated functional connectivity in anterior temporal lobe fMRI data, which we attribute to increased noise levels. The MSBM emerges as a valuable tool for understanding differences across graphs, with potential future applications and avenues beyond the current focus on characterizing modality-specific distinctions in connectomics data.

Contributions of the left and right thalami to language: A meta-analytic approach

BACKGROUND

Despite a pervasive cortico-centric view in cognitive neuroscience, subcortical structures including the thalamus have been shown to be increasingly involved in higher cognitive functions. Previous structural and functional imaging studies demonstrated cortico-thalamo-cortical loops which may support various cognitive functions including language. However, large-scale functional connectivity of the thalamus during language tasks has not been examined before.

METHODS

The present study employed meta-analytic connectivity modeling to identify language-related coactivation patterns of the left and right thalami. The left and right thalami were used as regions of interest to search the BrainMap functional database for neuroimaging experiments with healthy participants reporting language-related activations in each region of interest. Activation likelihood estimation analyses were then carried out on the foci extracted from the identified studies to estimate functional convergence for each thalamus. A functional decoding analysis based on the same database was conducted to characterize thalamic contributions to different language functions.

RESULTS

The results revealed bilateral frontotemporal and bilateral subcortical (basal ganglia) coactivation patterns for both the left and right thalami, and also right cerebellar coactivations for the left thalamus, during language processing. In light of previous empirical studies and theoretical frameworks, the present connectivity and functional decoding findings suggest that cortico-subcortical-cerebellar-cortical loops modulate and fine-tune information transfer within the bilateral frontotemporal cortices during language processing, especially during production and semantic operations, but also other language (e.g., syntax, phonology) and cognitive operations (e.g., attention, cognitive control).

CONCLUSION

The current findings show that the language-relevant network extends beyond the classical left perisylvian cortices and spans bilateral cortical, bilateral subcortical (bilateral thalamus, bilateral basal ganglia) and right cerebellar regions.

Exploring the late maturation of an intrinsic episodic memory network: A resting-state fMRI study

Previous research suggests that episodic memory relies on functional neural networks,which are present even in the absence of an explicit task. The regions that integrate.these networks and the developmental changes in intrinsic functional connectivity.remain elusive. In the present study, we outlined an intrinsic episodic memory network.(iEMN) based on a systematic selection of functional connectivity studies, and.inspected network differences in resting-state fMRI between adolescents (13-17 years.old) and adults (23-27 years old) from the publicly available NKI-Rockland Sample.Through a review of brain regions commonly associated with episodic memory.networks, we identified a potential iEMN composed by 14 bilateral ROIs, distributed.across temporal, frontal and parietal lobes. Within this network, we found an increase.in resting-state connectivity from adolescents to adults between the right temporal pole.and two regions in the right lateral prefrontal cortex. We argue that the coordination of.these brain regions, connecting areas of semantic processing and areas of controlled.retrieval, arises as an important feature towards the full maturation of the episodic.memory system. The findings add to evidence suggesting that adolescence is a key.period in memory development and highlights the role of intrinsic functional.connectivity in such development.

Strengthening through adversity: The hormesis model in developmental psychopathology

BACKGROUND

Employing a developmental psychopathology framework, we tested the utility of the hormesis model in examining the strengthening of children and youth through limited levels of adversity in relation to internalizing and externalizing outcomes within a brain-by-development context.

METHODS

Analyzing data from the Adolescent Brain and Cognitive Development study (N = 11,878), we formed latent factors of threat, deprivation, and unpredictability. We examined linear and nonlinear associations between adversity dimensions and youth psychopathology symptoms and how change of resting-state functional connectivity (rsFC) in the default mode network (DMN) from Time 1 to Time 5 moderates these associations.

RESULTS

A cubic association was found between threat and youth internalizing problems; low-to-moderate family conflict levels reduced these problems. Deprivation also displayed a cubic relation with youth externalizing problems, with moderate deprivation levels associated with fewer problems. Unpredictability linearly increased both problem types. Change in DMN rsFC significantly moderated the cubic link between threat levels and internalizing problems, with declining DMN rsFC levels from Time 1 to Time 5 facilitating hormesis. Hormetic effects peaked earlier, emphasizing the importance of sensitive periods and developmental timing of outcomes related to earlier experiences.

CONCLUSIONS

Strengthening through limited environmental adversity is crucial for developing human resilience. Understanding this process requires considering both linear and nonlinear adversity-psychopathology associations. Testing individual differences by brain and developmental context will inform preventive intervention programming.

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.

Brain structure and function differences across varying levels of endurance training: a cross-sectional study

Background

Although previous studies have shown that athletes engaged in endurance sports exhibit unique characteristics of brain plasticity, there has been no systematic investigation into the structural and functional brain characteristics of endurance athletes with varying training levels.

Methods

Utilizing the "expert-novice paradigm" design, we employed functional magnetic resonance imaging (fMRI) to obtain images of brain structure and functional activity. We compared differences in gray matter volume (GMV), fractional amplitude of low-frequency fluctuations (fALFF), and degree centrality (DC) among high-level endurance athletes, moderate-level endurance athletes, and non-athlete controls.

Results

(1) High-level endurance athletes exhibited significantly greater GMV in the left parahippocampal gyrus, bilateral thalamus, right temporal lobe, and bilateral cerebellum compared to both moderate-level endurance athletes and controls. The GMV in these regions showed an increasing trend with more years of endurance training and higher endurance capacity. Additionally, these athletes had significantly higher fALFF in the left superior medial frontal gyrus and right precuneus, as well as higher DC in the right lateral occipital lobe compared to moderate-level endurance athletes. They also had significantly higher DC in the right precuneus and cerebellum compared to the control group. (2) Moderate-level endurance athletes demonstrated significantly greater GMV in the right prefrontal cortex, bilateral medial frontal lobe, right temporal pole, right striatum, and bilateral insula compared to high-level endurance athletes. They also had significantly higher fALFF in the left posterior cingulate gyrus compared to high-level endurance athletes. (3) Control group showed significantly greater GMV in the right amygdala, higher fALFF in the left medial frontal lobe, and greater DC in the left lateral occipital lobe compared to moderate-level endurance athletes.

Conclusion

Adaptive benefits exhibit different characteristics across different endurance levels. High-level endurance athletes exhibit pronounced enhancements in gray matter volume and functional activity in regions associated with memory, motor control, and sensory processing. While moderate-level athletes demonstrate distinct functional reorganization in the default mode network and cerebellum.

Relationship Between DWI-Based Acute Ischemic Stroke Volume, Location and Severity of Dysphagia

BACKGROUND/OBJECTIVES

The impact of stroke location and volume on the development of post-stroke dysphagia is not fully understood. The aim of this study is to evaluate the relationship between acute ischemic lesions and the severity of dysphagia.

METHODS

Brain MRIs were obtained with a 1.5 Tesla MRI system (Magnetom Avanto B13, Siemens, Erlangen, Germany). The brain MRI protocol included axial echo planar diffusion-weighted imaging (DWI). The acute ischemic volume was obtained using DWI by drawing regions of interest (ROIs). The diagnosis and assessment of the severity of dysphagia was carried out by a multidisciplinary team and included the Dysphagia Outcome and Severity Scale (DOSS), the Penetration-Aspiration Scale (PAS), and the Pooling score (P-score). The threshold for statistical significance was set at 5%.

RESULTS

Among all the patients enrolled (n = 64), 28 (43.8%) were males and 36 (56.2%) were females, with a mean age of 78.8 years. Thirty-three (51.6%) of them had mild dysphagia and thirty-one (48.4%) had moderate-severe dysphagia. The total ischemic volume was negatively correlated with the DOSS (r = -0.441, p = 0.0003) and positively with the P-score (rs = 0.3054, p = 0.0328).

CONCLUSIONS

There are significant associations between the severity of dysphagia and the quantitative DWI-based data of the acute ischemic volume and anatomical location.

The neural basis underlying the association between parents' socioeconomic status and depressive symptoms among college students

Objective

Depression is increasingly prevalent among adolescents, with parents' socioeconomic status (SES) serving as significant predictors. Understanding the link between parents' SES and college students' depressive symptoms is of paramount concern. However, the neural basis linking the association between parents' SES and students' depressive symptoms still remains to be explored. In order to address this issue, this study aims to investigate the relationship between parents' SES and students' depressive symptoms, and the role of brain functional connectivity (FC) pattern in this relationship.

Methods

In this study, a total of 363 college students without a history of mental or neurological disorders underwent depressive symptoms assessment and resting-state functional magnetic resonance imaging scans. We used a connectome-based predictive modeling (CPM) approach to identify neural biomarkers of depressive symptoms.

Results

The results indicate that there is a negative correlation between parents' SES and students' depression tendencies (Father's education level and SDS: r  = -0.119, p < 0.05; Mother's education level and SDS: r  = -0.117, p < 0.05), suggesting that students whose parents have a higher educational level are less likely to suffer from depression. Furthermore, a FC pattern that can significantly predict depressive symptoms outside of the body was identified (r  = 0.13, p < 0.005), with most of the FCs belonging to the default mode network (DMN) and ventral attention network (VAN). Additionally, the FC pattern associated with depressive symptoms mediate the relationship between parents' SES and depressive symptoms.

Conclusion

Therefore, we believe that improving the education levels of parents may have a practical effect in reducing depressive symptoms among adolescents.

Altered resting-state connectivity of the auditory cortex in congenital amusia: A functional magnetic resonance imaging study in Mandarin speakers

Brain imaging studies have reported that the neural deficits of congenital amusia in non-tonal language speakers are mainly in the connectivity between the auditory cortex and the inferior frontal gyrus (IFG) in the right hemisphere. However, the relationship between the functional connectivity (FC) in these regions and the music perception ability of amusia in tonal language speakers remains unclear. In this study, we investigated the FC characteristics of amusia in Mandarin speakers in resting-state functional magnetic resonance imaging data by voxel-wise connectivity analyses with seeds in left and right Heschl's gyri (HG) and region of interest (ROI)-to-ROI connectivity analyses. Our findings indicate increased connectivity between right HG and bilateral posterior superior temporal gyrus, as determined by voxel-wise connectivity analyses in amusia. Conversely, reduced connectivity was observed between bilateral HG and bilateral IFG (orbital part) as assessed through ROI-to-ROI connectivity analyses in amusia when compared to controls. Moreover, the music perception scores of amusia in Mandarin speakers were associated with diminished connectivity between the left HG and the right IFG. This study furnishes direct evidence for the link between music perception deficits and the aberrant frontotemporal connectivity of congenital amusia in tonal language speakers in resting state.

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Breakdown of TMS evoked EEG signal propagation within the default mode network in Alzheimer's disease

BACKGROUND

The neural activity of the Default Mode Network (DMN) is disrupted in patients with In Alzheimer's disease (AD).

OBJECTIVES

We used a novel multimodal approach to track neural signal propagation within the DMN in AD patients.

METHODS

Twenty mild to moderate AD patients were recruited. We used transcranial magnetic stimulation (TMS) pulses to probe with a millisecond time resolution the propagation of evoked electroencephalography (EEG) signal following the neural activation of the Precuneus (PC), which is a key hub area of the DMN. Moreover, functional and structural magnetic resonance imaging (MRI) data were collected to reconstruct individual features of the DMN.

RESULTS

In AD patients a probe TMS pulse applied over the PC evokes an increased local activity unmasking underlying hyperexcitability. In contrast, the EEG evoked neural signal did not propagate efficiently within the DMN showing a remarkable breakdown of signal propagation. fMRI and structural tractography showed that impaired signal propagation was related to the same connectivity matrices derived from DMN BOLD signal and transferred by specific white matter bundles forming the cingulum. These features were not detectable stimulating other areas (left dorsolateral prefrontal cortex) or for different networks (fronto-parietal network). Finally, connectivity breakdown was associated with cognitive impairment, as measured with the Clinical Dementia Rating Scale sum of boxes (CDR-SB).

CONCLUSIONS

TMS-EEG in AD shows both local hyperexcitability and a lack of signal propagation within the DMN. These neurophysiological features also correlate with structural and cognitive attributes of the patients.

SIGNIFICANCE

Neuronavigated TMS-EEG may be used as a novel neurophysiological biomarker of DMN connectivity in AD patients.

The unique role of anosognosia in the clinical progression of Alzheimer's disease: a disorder-network perspective

Alzheimer's disease (AD) encompasses a long continuum from a preclinical phase, characterized by neuropathological alterations albeit normal cognition, to a symptomatic phase, marked by its clinical manifestations. Yet, the neural mechanisms responsible for cognitive decline in AD patients remain poorly understood. Here, we posit that anosognosia, emerging from an error-monitoring failure due to early amyloid-β deposits in the posterior cingulate cortex, plays a causal role in the clinical progression of AD by preventing patients from being aware of their deficits and implementing strategies to cope with their difficulties, thus fostering a vicious circle of cognitive decline.

Brain-to-brain synchrony increased during interpersonal touch in romantic lovers: an EEG-based hyperscanning study

BACKGROUND

Interpersonal touch is an essential element of human social life. It's unclear whether the neural patterns of interpersonal touch are specific to intimate relationships or generally apply to other social relationships. Romantic lovers are typically intimate and have a high level of interpersonal touch. Currently, researchers focused on the neurobiological basis and neural processes of romantic love.

METHODS

110 participants finished two resting-state blocks, no-handholding and handholding conditions, with Electroencephalogram (EEG). We aimed to explore the differences in the brain-brain synchrony pattern of interpersonal touch between romantic lovers and strangers by calculating dynamic interpersonal functional connectivity (dIFC) via EEG-based hyperscanning.

RESULTS

Our results supported that the neural processing of interpersonal touch is a dynamic process. At first half, both groups tended to adapt, and then interpersonal touch increased the dIFC between romantic lovers and decreased the dIFC between strangers. Finally, we employed Support Vector Machine (SVM) to classify EEG signals into two different relationships. SVM recognized two relationships with an accuracy of 71% and 0.77 AUC of ROC at the first half, a 73% accuracy and 0.8 AUC of ROC at the second half.

CONCLUSIONS

Our study indicates that interpersonal touch may have different meanings between romantic lovers and strangers. Specifically, interpersonal touch enhances the dIFC between romantic lovers while reducing the dIFC between strangers. The research has important implications for planning touch-based interventions in social and medical care.

Pseudo-Resting-State Functional MRI Derived from Dynamic Susceptibility Contrast Perfusion MRI Can Predict Cognitive Impairment in Glioma

BACKGROUND AND PURPOSE

Resting-state functional MRI (rs-fMRI) can be used to estimate functional connectivity (FC) between different brain regions, which may be of value for identifying cognitive impairment in patients with brain tumors. Unfortunately, neither rs-fMRI nor neurocognitive assessments are routinely assessed clinically, mostly due to limitations in examination time and cost. Since DSC perfusion MRI is often used clinically to assess tumor vascularity and similarly uses a gradient-echo-EPI sequence for T2*-sensitivity, we theorized a "pseudo-rs-fMRI" signal could be derived from DSC perfusion to simultaneously quantify FC and perfusion metrics, and these metrics can be used to estimate cognitive impairment in patients with brain tumors.

MATERIALS AND METHODS

Twenty-four consecutive patients with gliomas were enrolled in a prospective study that included DSC perfusion MRI, resting-sate functional MRI (rs-fMRI), and neurocognitive assessment. Voxelwise modeling of contrast bolus dynamics during DSC acquisition was performed and then subtracted from the original signal to generate a residual "pseudo-rs-fMRI" signal. Following the preprocessing of pseudo-rs-fMRI, full rs-fMRI, and a truncated version of the full rs-fMRI (first 100 timepoints) data, the default mode, motor, and language network maps were generated with atlas-based ROIs, Dice scores were calculated for the resting-state network maps from pseudo-rs-fMRI and truncated rs-fMRI using the full rs-fMRI maps as reference. Seed-to-voxel and ROI-to-ROI analyses were performed to assess FC differences between cognitively impaired and nonimpaired patients.

RESULTS

Dice scores for the group-level and patient-level (mean±SD) default mode, motor, and language network maps using pseudo-rs-fMRI were 0.905/0.689 ± 0.118 (group/patient), 0.973/0.730 ± 0.124, and 0.935/0.665 ± 0.142, respectively. There was no significant difference in Dice scores between pseudo-rs-fMRI and the truncated rs-fMRI default mode (P = .97) or language networks (P = .30), but there was a difference in motor networks (P = .02). A multiple logistic regression classifier applied to ROI-to-ROI FC networks using pseudo-rs-fMRI could identify cognitively impaired patients (sensitivity = 84.6%, specificity = 63.6%, receiver operating characteristic area under the curve (AUC) = 0.7762 ± 0.0954 (standard error), P = .0221) and performance was not significantly different from full rs-fMRI predictions (AUC = 0.8881 ± 0.0733 (standard error), P = .0013, P = .29 compared with pseudo-rs-fMRI).

CONCLUSIONS

DSC perfusion MRI-derived pseudo-rs-fMRI data can be used to perform typical rs-fMRI FC analyses that may identify cognitive decline in patients with brain tumors while still simultaneously performing perfusion analyses.

Hypothalamus Connectivity in Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Adolescent Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disabling illness of unknown etiology. Increasing evidence suggests hypothalamic involvement in ME/CFS pathophysiology, which has rarely been explored using magnetic resonance imaging (MRI) in the condition. This work aimed to use MRI to examine hypothalamus connectivity in adolescents with ME/CFS and explore how this relates to fatigue severity and illness duration. 25 adolescents with ME/CFS and 23 healthy controls completed a neuroimaging protocol consisting of structural and multishell diffusion-weighted imaging sequences, in addition to the PedsQL Multidimensional Fatigue Scale to assess fatigue severity. Information about illness duration was acquired at diagnosis. Preprocessing and streamlines tractography was performed using QSIPrep combined with a custom parcellation scheme to create structural networks. The number (degree) and weight (strength) of connections between lateralized hypothalamus regions and cortical and subcortical nodes were extracted, and relationships between connectivity measures, fatigue severity, and illness duration were performed using Bayesian regression models. We observed weak-to-moderate evidence of increased degree, but not strength, of connections from the bilateral anterior-inferior (left: pd [%] = 99.18, median [95% CI] = -22.68[-40.96 to 4.45]; right: pd [%] = 99.86, median [95% CI] = -23.35[-38.47 to 8.20]), left anterior-superior (pd [%] = 99.33, median [95% CI] = -18.83[-33.45 to 4.07]) and total left hypothalamus (pd [%] = 99.44, median [95% CI] = -47.18[-83.74 to 11.03]) in the ME/CFS group compared with controls. Conversely, bilateral posterior hypothalamus degree decreased with increasing ME/CFS illness duration (left: pd [%] = 98.13, median [95% CI]: -0.47[-0.89 to 0.03]; right: pd [%] = 98.50, median [95% CI]:-0.43[-0.82 to 0.05]). Finally, a weak relationship between right intermediate hypothalamus connectivity strength and fatigue severity was identified in the ME/CFS group (pd [%] = 99.35, median [95% CI] = -0.28[-0.51 to 0.06]), which was absent in controls. These findings suggest changes in hypothalamus connectivity may occur in adolescents with ME/CFS, warranting further investigation.

The body mirroring thought: The relationship between thought transitions and fluctuations in autonomic nervous activity mediated by interoception

Our thought states change without intention. This study verified that the transition of thought states varies with fluctuations in autonomic nervous activity, and that this effect is modulated by interoceptive accuracy. The participants completed the heartbeat counting task (HCT) and vigilance task. We assessed the participants' interoceptive accuracy based on their performance on the HCT. The vigilance task is a simple attention task, and during this task, we asked the participants to report the content and contemplation of their thoughts. Consequently, participants with accurate interoception were more likely to remain in a highly contemplative thought state when parasympathetic activity was suppressed. In contrast, the dominance of parasympathetic activity facilitated transitions to different thought states or experiences of less contemplative thought states in them. The results suggest that even subtle changes in bodily responses at rest can affect thought transitions in people with accurate interoception.

Assessing the impact of infantile hydrocephalus on visuomotor integration through behavioural and neuroimaging studies

Infantile hydrocephalus considerably impacts neurodevelopment, warranting attention to potential long-term consequences on visuomotor functions. The current study investigated the impact of infantile hydrocephalus on functional connectivity within the posterior cortex. Fourteen patients, who were treated for infantile hydrocephalus, were matched for age and sex with 14 typically-developing controls. Both groups had a mean age of 9 years old. Resting-state functional MRI was used to conduct a functional connectivity analysis within the visuomotor integration network, including the inferior frontal occipital fasciculus, superior longitudinal fasciculus, and frontal aslant tract. Patients had reduced functional connectivity in visuomotor pathways compared to typically-developing children with notable impact on the left and right fusiform gyrus and precuneus. Children with infantile hydrocephalus also performed significantly lower in tasks involving visuomotor integration, visual processing, visuospatial skills, motor coordination, and fine motor manipulation. This study enhances our understanding of the multifaceted impact of infantile hydrocephalus on both neural connectivity and considering behavioral outcomes.

Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach

Neuroimaging genetics represents a multivariate approach aimed at elucidating the intricate relationships between high-dimensional genetic variations and neuroimaging data. Predominantly, existing methodologies revolve around Sparse Canonical Correlation Analysis (SCCA), a framework we expand to 1) encompass multiple imaging modalities and 2) promote the simultaneous identification of structurally linked features across imaging modalities. The structurally linked brain regions were assessed using diffusion tensor imaging, which quantifies the presence of neuronal fibers, thereby grounding our approach in biologically well-founded prior knowledge within the SCCA model. In our proposed structurally linked SCCA framework, we leverage T1-weighted MRI and functional MRI (fMRI) time series data to delineate both the structural and functional characteristics of the brain. Genetic variations, specifically single nucleotide polymorphisms (SNPs), are also incorporated as a genetic modality. Validation of our methodology was conducted using a simulated dataset and large-scale normative data from the Human Connectome Project (HCP). Our approach demonstrated superior performance compared to existing methods on simulated data and revealed interpretable gene-imaging associations in the real dataset. Thus, our methodology lays the groundwork for elucidating the genetic underpinnings of brain structure and function, thereby providing novel insights into the field of neuroscience. Our code is available at https://github.com/mungegg.

Fibration symmetry-breaking supports functional transitions in a brain network engaged in language

In his book 'A Beautiful Question', physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.

Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis

BACKGROUND

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis.

METHODS

Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome.

RESULTS

Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001).

CONCLUSIONS

Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.

Pretreatment Brain White Matter Integrity Associated With Neuropathic Pain Relief and Changes in Temporal Summation of Pain Following Ketamine

Neuropathic pain (NP) is a prevalent condition often associated with heightened pain responsiveness suggestive of central sensitization. Neuroimaging biomarkers of treatment outcomes may help develop personalized treatment strategies, but white matter (WM) properties have been underexplored for this purpose. Here we assessed whether WM pathways of the default mode network (DMN: medial prefrontal cortex [mPFC], posterior cingulate cortex, and precuneus) and descending pain modulation system (periaqueductal gray [PAG]) are associated with ketamine analgesia and attenuated temporal summation of pain (TSP, reflecting central sensitization) in NP. We used a fixel-based analysis of diffusion-weighted imaging data to evaluate WM microstructure (fiber density [FD]) and macrostructure (fiber bundle cross-section) within the DMN and mPFC-PAG pathways in 70 individuals who underwent magnetic resonance imaging and TSP testing; 35 with NP who underwent ketamine treatment and 35 age- and sex-matched pain-free individuals. Individuals with NP were assessed before and 1 month after treatment; those with ≥30% pain relief were considered responders (n = 18), or otherwise as nonresponders (n = 17). We found that WM structure within the DMN and mPFC-PAG pathways did not differentiate responders from nonresponders. However, pretreatment FD in the anterior limb of the internal capsule correlated with pain relief (r=.48). Moreover, pretreatment FD in the DMN (left mPFC-precuneus/posterior cingulate cortex; r=.52) and mPFC-PAG (r=.42) negatively correlated with changes in TSP. This suggests that WM microstructure in the DMN and mPFC-PAG pathway is associated with the degree to which ketamine reduces central sensitization. Thus, fixel metrics of WM structure may hold promise to predict ketamine NP treatment outcomes. PERSPECTIVE: We used advanced fixel-based analyses of MRI diffusion-weighted imaging data to identify pretreatment WM microstructure associated with ketamine outcomes, including analgesia and markers of attenuated central sensitization. Exploring associations between brain structure and treatment outcomes could contribute to a personalized approach to treatment for individuals with NP.

The brain network hub degeneration in Alzheimer's disease

Alzheimer's disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.

Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals

Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by 'electrophysiology-invisible' signals. These findings offer a novel perspective on our understanding of RSN interpretation.

Magnetic resonance imaging connectivity features associated with response to transcranial magnetic stimulation in major depressive disorder

Transcranial magnetic stimulation (TMS) is an FDA-approved neuromodulation treatment for major depressive disorder (MDD), thought to work by altering dysfunctional brain connectivity pathways, or by indirectly modulating the activity of subcortical brain regions. Clinical response to TMS remains highly variable, highlighting the need for baseline predictors of response and for understanding brain changes associated with response. This systematic review examined brain connectivity features, and changes in connectivity features, associated with clinical improvement following TMS in MDD. Forty-one studies met inclusion criteria, including 1097 people with MDD. Most studies delivered one of two types of TMS to left dorsolateral prefrontal cortex and measured connectivity using resting-state functional MRI. The subgenual anterior cingulate cortex was the most well-studied brain region, particularly its connectivity with the TMS target or with the "executive control network" of brain regions. There was marked heterogeneity in findings. There is a need for greater understanding of how cortical TMS modulates connectivity with, and the activity of, subcortical regions, and how these effects change within and across treatment sessions.

Predicting performance in attention by measuring key metabolites in the PCC with 7T MRS

The posterior cingulate cortex (PCC) is a key hub of the default mode network and is known to play an important role in attention. Using ultra-high field 7 Tesla magnetic resonance spectroscopy (MRS) to quantify neurometabolite concentrations, this exploratory study investigated the effect of the concentrations of myo-inositol (Myo-Ins), glutamate (Glu), glutamine (Gln), aspartate or aspartic acid (Asp) and gamma-amino-butyric acid (GABA) in the PCC on attention in forty-six healthy participants. Each participant underwent an MRS scan and cognitive testing, consisting of a trail-making test (TMT A/B) and a test of attentional performance. After a multiple regression analysis and bootstrapping for correction, the findings show that Myo-Ins and Asp significantly influence (p < 0.05) attentional tasks. On one hand, Myo-Ins shows it can improve the completion times of both TMT A and TMT B. On the other hand, an increase in aspartate leads to more mistakes in Go/No-go tasks and shows a trend towards enhancing reaction time in Go/No-go tasks and stability of alertness without signal. No significant (p > 0.05) influence of Glu, Gln and GABA was observed.

Functional Movement Disorder Is Associated with Abnormal Interoceptive Brain Activity: A Task-based Functional MRI Study

Background

Aberrant interoceptive processing has been hypothesized to contribute to the pathophysiology of functional neurological disorder, although findings have been inconsistent. Here, we utilized functional magnetic resonance imaging (fMRI) to examine neural correlates of interoceptive attention - the conscious focus and awareness of bodily sensations - in functional movement disorder (FMD).

Methods

We used voxelwise analyses to compare blood oxygenation level-dependent responses between 13 adults with hyperkinetic FMD and 13 healthy controls (HCs) during a task requiring attention to different bodily sensations and to an exteroceptive stimulus. Additionally, we examined between-group differences in self-reported measures of interoception and evaluated their relationship with neural activity.

Results

Interoceptive conditions (heartbeat, stomach and 'body', indicating sensations from the body part or limb affected in FMD participants) activated a network involving the precuneus, the posterior cingulate cortex (PCC) and caudate nucleus (CN) bilaterally, and the right anterior insula (aINS) (p <0.05, corrected). Group differences in brain activity were mainly driven by processing of disease-related interoceptive signals, which in the FMD group was associated with a broader neural activation than monitoring gastric interoception, while no group differences were detected during cardiac interoception. Differences based on interoceptive focus (body vs heartbeat and stomach) between FMD subjects and HCs were found in PCC, CN, angular gyrus, thalamus, and in the mid-insula (p <0.05, corrected).

Conclusions

This is, to our knowledge, the first study showing that FMD is associated with abnormal interoceptive processing in regions involved in monitoring body state, attentional focus, and homeostatic inference.

Biofluid, Imaging, Physiological, and Functional Biomarkers of Mild Traumatic Brain Injury and Subconcussive Head Impacts

Post-concussive symptoms are frequently reported by individuals who sustain mild traumatic brain injuries (mTBIs) and subconcussive head impacts, even when evidence of intracranial pathology is lacking. Current strategies used to evaluate head injuries, which primarily rely on self-report, have a limited ability to predict the incidence, severity, and duration of post-concussive symptoms that will develop in an individual patient. In addition, these self-report measures have little association with the underlying mechanisms of pathology that may contribute to persisting symptoms, impeding advancement in precision treatment for TBI. Emerging evidence suggests that biofluid, imaging, physiological, and functional biomarkers associated with mTBI and subconcussive head impacts may address these shortcomings by providing more objective measures of injury severity and underlying pathology. Interest in the use of biomarker data has rapidly accelerated, which is reflected by the recent efforts of organizations such as the National Institute of Neurological Disorders and Stroke and the National Academies of Sciences, Engineering, and Medicine to prioritize the collection of biomarker data during TBI characterization in acute-care settings. Thus, this review aims to describe recent progress in the identification and development of biomarkers of mTBI and subconcussive head impacts and to discuss important considerations for the implementation of these biomarkers in clinical practice.

Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling

MAIN PROBLEM

Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia.

METHODS

A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients.

RESULTS

CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method.

CONCLUSIONS

This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.

Cortico-cortical transfer of socially derived information gates emotion recognition

Emotion recognition and the resulting responses are important for survival and social functioning. However, how socially derived information is processed for reliable emotion recognition is incompletely understood. Here, we reveal an evolutionarily conserved long-range inhibitory/excitatory brain network mediating these socio-cognitive processes. Anatomical tracing in mice revealed the existence of a subpopulation of somatostatin (SOM) GABAergic neurons projecting from the medial prefrontal cortex (mPFC) to the retrosplenial cortex (RSC). Through optogenetic manipulations and Ca2+ imaging fiber photometry in mice and functional imaging in humans, we demonstrate the specific participation of these long-range SOM projections from the mPFC to the RSC, and an excitatory feedback loop from the RSC to the mPFC, in emotion recognition. Notably, we show that mPFC-to-RSC SOM projections are dysfunctional in mouse models relevant to psychiatric vulnerability and can be targeted to rescue emotion recognition deficits in these mice. Our findings demonstrate a cortico-cortical circuit underlying emotion recognition.

Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals

Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by "electrophysiology-invisible" signals. These findings offer a novel perspective on our understanding of RSN interpretation.

Disparity in temporal and spatial relationships between resting-state electrophysiological and fMRI signals

Resting-state brain networks (RSNs) have been widely applied in health and disease, but the interpretation of RSNs in terms of the underlying neural activity is unclear. To address this fundamental question, we conducted simultaneous recordings of whole-brain resting-state functional magnetic resonance imaging (rsfMRI) and electrophysiology signals in two separate brain regions of rats. Our data reveal that for both recording sites, spatial maps derived from band-specific local field potential (LFP) power can account for up to 90% of the spatial variability in RSNs derived from rsfMRI signals. Surprisingly, the time series of LFP band power can only explain to a maximum of 35% of the temporal variance of the local rsfMRI time course from the same site. In addition, regressing out time series of LFP power from rsfMRI signals has minimal impact on the spatial patterns of rsfMRI-based RSNs. This disparity in the spatial and temporal relationships between resting-state electrophysiology and rsfMRI signals suggests that electrophysiological activity alone does not fully explain the effects observed in the rsfMRI signal, implying the existence of an rsfMRI component contributed by "electrophysiology-invisible" signals. These findings offer a novel perspective on our understanding of RSN interpretation.

Distance and grid-like codes support the navigation of abstract social space in the human brain

People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a 'social cognitive map' organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

Fibration symmetry-breaking supports functional transitions in a brain network engaged in language

In his book 'A Beautiful Question' 1, physicist Frank Wilczek argues that symmetry is 'nature's deep design,' governing the behavior of the universe, from the smallest particles to the largest structures 1-4. While symmetry is a cornerstone of physics, it has not yet been found widespread applicability to describe biological systems 5, particularly the human brain. In this context, we study the human brain network engaged in language and explore the relationship between the structural connectivity (connectome or structural network) and the emergent synchronization of the mesoscopic regions of interest (functional network). We explain this relationship through a different kind of symmetry than physical symmetry, derived from the categorical notion of Grothendieck fibrations 6. This introduces a new understanding of the human brain by proposing a local symmetry theory of the connectome, which accounts for how the structure of the brain's network determines its coherent activity. Among the allowed patterns of structural connectivity, synchronization elicits different symmetry subsets according to the functional engagement of the brain. We show that the resting state is a particular realization of the cerebral synchronization pattern characterized by a fibration symmetry that is broken 7 in the transition from rest to language. Our findings suggest that the brain's network symmetry at the local level determines its coherent function, and we can understand this relationship from theoretical principles.

The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis

The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.