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.

Resting state of human brain measured by fMRI experiment is governed more dominantly by essential mode as a global signal rather than default mode network.

Resting-state of the human brain has been described by a combination of various basis modes including the default mode network (DMN) identified by fMRI BOLD signals in human brains. Whether DMN is the most dominant representation of the resting-state has been under question. Here, we investigated the unexplored yet fundamental nature of the resting-state. In the absence of global signal regression for the analysis of brain-wide spatial activity pattern, the fMRI BOLD spatiotemporal signals during the rest were completely decomposed into time-invariant spatial-expression basis modes (SEBMs) and their time-evolution basis modes (TEBMs). Contrary to our conventional concept above, similarity clustering analysis of the SEBMs from 166 human brains revealed that the most dominant SEBM cluster is an asymmetric mode where the distribution of the sign of the components is skewed in one direction, for which we call essential mode (EM), whereas the second dominant SEBM cluster resembles the spatial pattern of DMN. Having removed the strong 1/f noise in the power spectrum of TEBMs, the genuine oscillatory behavior embedded in TEBMs of EM and DMN-like mode was uncovered around the low-frequency range below 0.2 Hz.

Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study.

Representing data using time-resolved networks is valuable for analyzing functional data of the human brain. One commonly used method for constructing time-resolved networks from data is sliding window Pearson correlation (SWPC). One major limitation of SWPC is that it applies a high-pass filter to the activity time series. Therefore, if we select a short window (desirable to estimate rapid changes in connectivity), we will remove important low-frequency information. Here, we propose an approach based on single sideband modulation (SSB) in communication theory. This allows us to select shorter windows to capture rapid changes in the time-resolved functional network connectivity (trFNC). We use simulation and real resting-state functional magnetic resonance imaging (fMRI) data to demonstrate the superior performance of SSB+SWPC compared to SWPC. We also compare the recurring trFNC patterns between individuals with the first episode of psychosis (FEP) and typical controls (TC) and show that FEPs stay more in states that show weaker connectivity across the whole brain. A result exclusive to SSB+SWPC is that TCs stay more in a state with negative connectivity between subcortical and cortical regions. Based on all the results, we argue that SSB+SWPC is more sensitive for capturing temporal variation in trFNC.

Analyzing asymmetry in brain hierarchies with a linear state-space model of resting-state fMRI data.

This study challenges the traditional focus on zero-lag statistics in resting-state functional magnetic resonance imaging (rsfMRI) research. Instead, it advocates for considering time-lag interactions to unveil the directionality and asymmetries of the brain hierarchy. Effective connectivity (EC), the state matrix in dynamical causal modeling (DCM), is a commonly used metric for studying dynamical properties and causal interactions within a linear state-space system description. Here, we focused on how time-lag statistics are incorporated within the framework of DCM resulting in an asymmetric EC matrix. Our approach involves decomposing the EC matrix, revealing a steady-state differential cross-covariance matrix that is responsible for modeling information flow and introducing time-irreversibility. Specifically, the system's dynamics, influenced by the off-diagonal part of the differential covariance, exhibit a curl steady-state flow component that breaks detailed balance and diverges the dynamics from equilibrium. Our empirical findings indicate that the EC matrix's outgoing strengths correlate with the flow described by the differential cross covariance, while incoming strengths are primarily driven by zero-lag covariance, emphasizing conditional independence over directionality.

Modeling large-scale brain dynamics offers insight into the main principles of brain self-organization. In particular, the identification of traces of nonequilibrium steady-state dynamics also at the mascroscale level has been recently linked to the presence of intrinsic brain networks. Quantifying these aspects is generally limited by numerical difficulties. However, for resting-state BOLD data, a linear stochastic state-space model has demonstrated efficacy, simplifying analysis. Specifically, the asymmetric structure of effective connectivity, that is, the state interaction matrix, directly reflects nonequilibrium steady-state dynamics and time-irreversibility. By disentangling this asymmetry, we quantified departure from equilibrium and discerned primary directions of information propagation, identifying brain regions as sources or sinks.

Individual variability in neural representations of mind-wandering.

Mind-wandering is a frequent, daily mental activity, experienced in unique ways in each person. Yet neuroimaging evidence relating mind-wandering to brain activity, for example in the default mode network (DMN), has relied on population- rather than individual-based inferences owing to limited within-person sampling. Here, three densely sampled individuals each reported hundreds of mind-wandering episodes while undergoing multi-session functional magnetic resonance imaging. We found reliable associations between mind-wandering and DMN activation when estimating brain networks within individuals using precision functional mapping. However, the timing of spontaneous DMN activity relative to subjective reports, and the networks beyond DMN that were activated and deactivated during mind-wandering, were distinct across individuals. Connectome-based predictive modeling further revealed idiosyncratic, whole-brain functional connectivity patterns that consistently predicted mind-wandering within individuals but did not fully generalize across individuals. Predictive models of mind-wandering and attention that were derived from larger-scale neuroimaging datasets largely failed when applied to densely sampled individuals, further highlighting the need for personalized models. Our work offers novel evidence for both conserved and variable neural representations of self-reported mind-wandering in different individuals. The previously unrecognized interindividual variations reported here underscore the broader scientific value and potential clinical utility of idiographic approaches to brain-experience associations.

While everyone experiences that their mind "wanders" throughout daily life, the content and form of inner experience is different in different people. In this study, we found that brain activity representing mind-wandering is different in each person, reflecting unique mental experiences. While people consistently engaged the brain's default mode network (DMN) during mind-wandering, there were inconsistencies in the way that the DMN was engaged and in the other networks throughout the brain that were engaged. Our study highlights that personalized approaches, which require that individuals are sampled more densely than is common in current practice, enable accurate insights into relationships between brain activity and inner experience.

Comprehensive MRI assessment reveals subtle brain findings in non-hospitalized post-COVID patients with cognitive impairment.

Background: Impaired cognitive ability is one of the most frequently reported neuropsychiatric symptoms in the post-COVID phase among patients. It is unclear whether this condition is related to structural or functional brain changes. Purpose: In this study, we present a multimodal magnetic resonance imaging study of 36 post-COVID patients and 36 individually matched controls who had a mild form of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) infection from March 2020 to February 2022. This study aimed to investigate structural and functional brain alterations and their correlation with post-COVID symptoms and neurocognitive functions. Materials and methods: The study protocol comprised an assessment of physical fatigue [Fatigue Severity Scale (FSS)], mental fatigue (Mental Fatigue Scale (MFS)], depression [Montgomery Asberg Depression Rating Scale (MADRS)], anxiety [Hospital Anxiety and Depression Scale (HAD)], post-COVID Symptoms Severity Score, and neurocognitive status [Repeatable Battery for the Assessment of Neuropsychological Status Update (RBANS)]. The magnetic resonance imaging protocol included morphological sequences, arterial spin labeling (ASL) and dynamic susceptibility contrast-enhanced (DSC) perfusion, diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (fMRI) sequences. Using these protocols, the assessments of macrostructural abnormalities, perfusion, gray matter density, white matter integrity, and brain connectivity were performed. Results: Post-COVID patients had higher levels of physical fatigue, mental fatigue, depression, and anxiety than controls and showed cognitive impairment in all the RBANS domains except in Visuospatial/Construction. The subjective mental fatigue correlated with objective impaired cognitive ability in the RBANS test, particularly in the Attention domain. There were no differences between patients and controls regarding macrostructural abnormalities, regional volumes, regional perfusion metrics, gray matter density, or DTI parameters. We observed a significant positive correlation between RBANS Total Scale Index score and gray matter volume in the right superior/middle-temporal gyrus (p < 0.05) and a significant negative correlation between the white matter integrity and post-COVID symptoms (p < 0.05) in the same area. The connectivity differences were observed between patients and controls in a few regions, including the right middle frontal gyrus, an important area of convergence of the dorsal and ventral attention networks. We also noted a positive correlation between post-COVID symptoms and increased connectivity in the right temporoparietal junction, which is part of the ventral attention system. Conclusion: In non-hospitalized subjects with post-COVID, we did not find any structural brain changes or changes in perfusion, compared to controls. However, we noted differences in connectivity within an important area for attention processes, which may be associated with post-COVID brain fog.

Cerebellum and basal ganglia connectivity in isolated REM sleep behaviour disorder and Parkinson's disease: an exploratory study.

REM sleep behaviour disorder (RBD) is a parasomnia characterised by dream-enacting behaviour with loss of muscle atonia during REM sleep and is a prodromal feature of α-synucleinopathies like Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. Although cortical-to-subcortical connectivity is well-studied in RBD, cerebellar and subcortical nuclei reciprocal connectivity is less established. Nonetheless, it could be relevant since RBD pathology involves brainstem structures with an ascending gradient. In this study, we utilised resting-state functional MRI to investigate 13 people with isolated RBD (iRBD), 17 with Parkinson's disease and 16 healthy controls. We investigated the connectivity between the basal ganglia, thalamus and regions of the cerebellum. The cerebellum was segmented using a functional atlas, defined by a resting-state network-based parcellation, rather than an anatomical one. Controlling for age, we found a significant group difference (F4,82 = 5.47, pFDR = 0.017) in cerebellar-thalamic connectivity, with iRBD significantly lower compared to both control and Parkinson's disease. Specifically, cerebellar areas involved in this connectivity reduction were related to the default mode, language and fronto-parietal resting-state networks. Our findings show functional connectivity abnormalities in subcortical structures that are specific to iRBD and may be relevant from a pathophysiological standpoint. Further studies are needed to investigate how connectivity changes progress over time and whether specific changes predict disease course or phenoconversion.

Common and unique brain aging patterns between females and males quantified by large-scale deep learning.

There has been extensive evidence that aging affects human brain function. However, there is no complete picture of what brain functional changes are mostly related to normal aging and how aging affects brain function similarly and differently between males and females. Based on resting-state brain functional connectivity (FC) of 25,582 healthy participants (13,373 females) aged 49-76 years from the UK Biobank project, we employ deep learning with explainable AI to discover primary FCs related to progressive aging and reveal similarity and difference between females and males in brain aging. Using a nested cross-validation scheme, we conduct 4200 deep learning models to classify all paired age groups on the main data for females and males separately and then extract gender-common and gender-specific aging-related FCs. Next, we validate those FCs using additional 21,000 classifiers on the independent data. Our results support that aging results in reduced brain functional interactions for both females and males, primarily relating to the positive connectivity within the same functional domain and the negative connectivity between different functional domains. Regions linked to cognitive control show the most significant age-related changes in both genders. Unique aging effects in males and females mainly involve the interaction between cognitive control and the default mode, vision, auditory, and frontoparietal domains. Results also indicate females exhibit faster brain functional changes than males. Overall, our study provides new evidence about common and unique patterns of brain aging in females and males.

Similarity and characterization of structural and functional neural connections within species under isoflurane anesthesia in the common marmoset.

The common marmoset is an essential model for understanding social cognition and neurodegenerative diseases. This study explored the structural and functional brain connectivity in a marmoset under isoflurane anesthesia, aiming to statistically overcome the effects of high inter-individual variability and noise-related confounds such as physiological noise, ensuring robust and reliable data. Similarities and differences in individual subject data, including assessments of functional and structural brain connectivities derived from resting-state functional MRI and diffusion tensor imaging were meticulously captured. The findings highlighted the high consistency of structural neural connections within the species, indicating a stable neural architecture, while functional connectivity under anesthesia displayed considerable variability. Through independent component and dual regression analyses, several distinct brain connectivities were identified, elucidating their characteristics under anesthesia. Insights into the structural and functional features of the marmoset brain from this study affirm its value as a neuroscience research model, promising advancements in the field through fundamental and translational studies.

Altered Functional Coupling of the Bed Nucleus of the Stria Terminalis and Amygdala in Spider Phobic Fear.

Background: Individuals with spider phobic (SP) fear show hypervigilance and amygdala hyperactivity toward fear-associated stimuli, which may promote the development of other anxiety disorders. The amygdala is a key region within the fear network, which is connected to the anxiety system, where the bed nucleus of the stria terminalis (BNST) plays a crucial role. However, the BNST's involvement in phobic fear is unknown. Therefore, this study investigated the association of phobic fear and anxiety on these regions' functional connectivity (FC) in SP compared to healthy controls (HC). Methods: 7T-functional MRI resting-state FC of 30 individuals with SP and 45 HC was assessed to detect network differences between these groups. The association of phobic fear severity, trait anxiety, and social anxiety on FC was explored using linear regressions combined with seed-to-voxel analyses with amygdala and BNST as primary seeds, corrected for age and sex. Results: In SP, phobic fear was associated with reduced FC between the left amygdala and the right supramarginal gyrus. In contrast, anxiety severity was related to increased FC between the right BNST and the left inferior frontal gyrus. Moreover, social anxiety was related to decreased FC between bilateral BNST and left precuneus. Conclusions: These findings show changes in FC in SP, connecting fear with altered activity in the BNST and amygdala. The results suggest that persistent anxiety in phobic fear is associated with abnormal brain function in these regions, potentially explaining susceptibility to anxiety disorders and processes involved in phobic fear, such as threat perception, avoidance, and salience. Impact statement This is the first study to report altered FC mechanisms of BNST and amygdala in individuals with SP using 7T ultra-high field resting-state data. So far, only distinct characterization of brain regions, especially of BNST and amygdala, involved in those disorders exists. Our results contribute to closing this knowledge gap by providing the first evidence that deviant BNST and amygdala function in SP might elucidate the susceptibility to other anxiety disorders.

Periaqueductal gray connectivity in spinal cord injury-induced neuropathic pain.

BACKGROUND AND PURPOSE: Neuropathic pain (NP) is a debilitating condition following spinal cord injury (SCI). The role of periaqueductal gray (PAG) in NP development following SCI remains underexplored. Using resting-state functional MRI (rsfMRI), our study aimed to demonstrate the alterations in functional connectivity (FC) of PAG in NP following SCI. METHODS: Ten SCI patients (SCI + NP, n = 7, and SCI - NP, n = 3), alongside 10 healthy controls (HCs), were enrolled. rsfMRI was conducted followed by seed-to-voxel analysis using PAG as the seed region and then group-based analysis comprising three groups (SCI + NP, SCI - NP, and HC). Age and gender were considered as confounding variables. RESULTS: Compared to HCs, SCI + NP demonstrated decreased FC between PAG and right insula, right frontal orbital cortex, right pallidum, dorsal raphe nucleus (DRN), red nuclei (RN), substantia nigra (SN), and ventral posterolateral (VPL) thalamic nuclei. Compared to SCI - NP, SCI + NP demonstrated increased FC between PAG and posterior cingulate cortex (PCC), hippocampus, cerebellar vermis lobules IV and V, and thalamic structures (posterior and lateral pulvinar, the mediodorsal nuclei, and the ventral lateral nuclei). Additionally, decreased FC between the PAG and VPL, geniculate bodies, intralaminar nuclei of thalamus, DRN, RN, SN, and prefrontal cortex was observed in this comparison. CONCLUSIONS: Altered FC between PAG and right anterior insula, VPL, DRN, RN, SN, cerebellar vermis lobules IV and V, frontal cortex, and PCC was associated with NP sequelae of SCI. Additionally, SCI was independently associated with decreased FC between PAG and right posterior insula, cerebellar lobules IV and V, and cerebellar vermis lobules III, IV, and V.

Amygdala connectivity is associated with withdrawn/depressed behavior in a large sample of children from the Adolescent Brain Cognitive Development (ABCD) Study®.

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

Addressing inconsistency in functional neuroimaging: A replicable data-driven multi-scale functional atlas for canonical brain networks.

The advent of various neuroimaging methodologies has greatly aided in the conceptualization of large-scale brain networks in the field of cognitive neuroscience. However, there is inconsistency across studies in both nomenclature and the functional entities being described. There is a need for a unifying framework which standardizes terminology across studies while also bringing analyses and results into the same reference space. Here we present a functional whole-brain atlas of canonical brain networks derived from more than 100k resting-state fMRI datasets. These data-driven networks are highly replicable across datasets as well as multiple spatial scales. We have organized, labeled, and described them with terms familiar to the fields of cognitive and affective neuroscience in order to optimize their utility in future neuroimaging analyses and enhance the accessibility of new findings. The benefits of this atlas are not limited to future template-based or reference-guided analyses, but also extend to other data-driven neuroimaging approaches across modalities, such as those using blind independent component analysis (ICA). Future studies utilizing this atlas will contribute to greater harmonization and standardization in functional neuroimaging research.

Motor impulsivity and spicy food craving: A mediation analysis of insula-based resting state functional connectivity.

In China, the rate of spicy food consumption is rising, and chili pepper is among the most popular spicy foods consumed nationwide. However, little effort has been made to understand the mechanism behind spicy food craving. This exploratory study aimed to investigate differences in insula-based resting state functional connectivity (rsFC) between spicy food cravers and non-cravers, and the association between rsFC, impulsivity and spicy food craving. A group of extreme cravers (n = 49) and a group of age- and sex-matched non-cravers (n = 46) completed a resting-state fMRI scan, during which participants were instructed to keep their eyes closed, to not think of anything in particular, and to remain awake. Participants completed the Spicy Food Craving Questionnaire, Barratt Impulsiveness Scale, Sensation Seeking Scale and Positive and Negative Affect Schedule, and rated the frequency of spicy food intake. Results revealed increased insula-occipital lobe resting-state functional connectivity in individuals with spicy food cravings, and the positive correlations between insula-middle occipital gyrus rsFC, impulsivity and spicy food craving. Specifically, the insula-middle occipital gyrus rsFC strength mediated the relationship between the motor impulsivity and spicy food craving. It is hoped that our exploratory findings may shed new insights into the neural mechanisms of spicy food craving and motivate further exploration of spicy food craving in diverse contexts and cultures.

Static and temporal dynamic alterations of regional homogeneity in chronic insomnia: a resting-state fMRI study.

To explore brain function alterations in chronic insomnia (CI). 65 CI patients and 48 healthy controls were included to analyze abnormal alterations in brain spontaneous activity using static regional homogeneity (sReHo) and dynamic regional homogeneity (dReHo) methods. CI patients focused on decreased sReHo in bilateral lingual gyrus, bilateral middle occipital gyrus, bilateral inferior occipital gyrus and right superior occipital gyrus; decreased dReHo in bilateral superior occipital gyrus, bilateral cortical area around the talus fissure, and right middle occipital gyrus. CI patients exhibit abnormal activity in multiple brain regions, which can reflect the sleep quality index. Supplementary Information: The online version contains supplementary material available at 10.1007/s41105-024-00541-0.

The imprint of dissociative seizures on the brain.

BACKGROUND: Increased resting state functional connectivity between regions involved in emotion control with regions with other specializations, e.g. motor control (emotional hyperconnectivity) is one of the most consistent imaging findings in persons suffering from dissociative seizures (DS). The overall goal of this study was to better characterize DS-related emotional hyperconnectivity using dynamic resting state analysis combined with brainstem volumetry to investigate 1. If emotional hyperconnectivity is restricted to a single state. 2. How volume losses within the modulatory and emotional motor subnetworks of the neuromodulatory system influence the expression of the emotional hyperconnectivity. METHODS: 13 persons with dissociative seizures (PDS) (f/m:10/3, mean age (SD) 44.6 (11.5)) and 15 controls (CON) (f/m:10/5, mean age (SD) 41.7 (13.0)) underwent a mental health test battery and structural and functional imaging at 3 T. Deformation based morphometry was used to assess brain volume loss by extracting the mean Jacobian determinants from 457 brain, forebrain and brainstem structures. The bold signals from 445 brainstem and brain rois were extracted with CONN and a dynamic fMRI analysis combined with graph and hierarchical analysis was used to identify and characterize 9 different brain states. Welch's t tests and Kendall tau tests were used for group comparisons and correlation analyses. RESULTS: The duration of Brain state 6 was longer in PDS than in CON (93.1(88.3) vs. 23.4(31.2), p = 0.01) and positively correlated with higher degrees of somatization, depression, PTSD severity and dissociation. Its global connectivity was higher in PDS than CON (90.4(3.2) vs 86.5(4.2) p = 0.01) which was caused by an increased connectivity between regions involved in emotion control and regions involved in sense of agency/body control. The brainstem and brainstem-forebrain modulatory and emotional motor subnetworks of the neuromodulatory system were atrophied in PDS. Atrophy severity within the brainstem-forebrain subnetworks was correlated with state 6 dwell time (modulatory: tau = -0.295, p = 0.03; emotional motor: tau = -0.343, p = 0.015) and atrophy severity within the brainstem subnetwork with somatization severity (modulatory: tau = -0.25, p = 0.036; emotional motor: tau = -0.256, p = 0.033). CONCLUSION: DS-related emotional hyperconnectivity was restricted to state 6 episodes. The remaining states were not different between PDS and CON. The modulatory subnetwork synchronizes brain activity across brain regions. Atrophy and dysfunction within that subnetwork could facilitate the abnormal interaction between regions involved in emotion control with those controlling sense of agency/body ownership during state 6 and contribute to the tendency for somatization in PDS. The emotional motor subnetwork controls the activity of spinal motoneurons. Atrophy and dysfunction within this subnetwork could impair that control resulting in motor symptoms during DS. Taken together, these findings indicate that DS have a neurophysiological underpinning.

Abnormal large-scale resting-state functional networks in anti-N-methyl-D-aspartate receptor encephalitis.

Background: Patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis often experience severe symptoms. Resting-state functional MRI (rs-fMRI) has revealed widespread impairment of functional networks in patients. However, the changes in information flow remain unclear. This study aims to investigate the intrinsic functional connectivity (FC) both within and between resting-state networks (RSNs), as well as the alterations in effective connectivity (EC) between these networks. Methods: Resting-state functional MRI (rs-fMRI) data were collected from 25 patients with anti-NMDAR encephalitis and 30 healthy controls (HCs) matched for age, sex, and educational level. Changes in the intrinsic functional connectivity (FC) within and between RSNs were analyzed using independent component analysis (ICA). The functional interaction between RSNs was identified by granger causality analysis (GCA). Results: Compared to HCs, patients with anti-NMDAR encephalitis exhibited lower performance on the Wisconsin Card Sorting Test (WCST), both in terms of correct numbers and correct categories. Additionally, these patients demonstrated decreased scores on the Montreal Cognitive Assessment (MoCA). Neuroimaging studies revealed abnormal intra-FC within the default mode network (DMN), increased intra-FC within the visual network (VN) and dorsal attention network (DAN), as well as increased inter-FC between VN and the frontoparietal network (FPN). Furthermore, aberrant effective connectivity (EC) was observed among the DMN, DAN, FPN, VN, and somatomotor network (SMN). Conclusion: Patients with anti-NMDAR encephalitis displayed noticeable deficits in both memory and executive function. Notably, these patients exhibited widespread impairments in intra-FC, inter-FC, and EC. These results may help to explain the pathophysiological mechanism of anti-NMDAR encephalitis.

Consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI.

Background: Individualized cortical functional networks parcellation has been reported as highly reproducible at 3.0 T. However, in view of the complexity of cortical networks and the greatly increased sensitivity provided by ultra-high field 5.0 T MRI, the parcellation consistency between different magnetic fields is unclear. Purpose: To explore the consistency and stability of individualized cortical functional networks parcellation at 3.0 T and 5.0 T MRI based on spatial and functional connectivity analysis. Materials and methods: Thirty healthy young participants were enrolled. Each subject underwent resting-state fMRI at both 3.0 T and 5.0 T in a random order in less than 48 h. The individualized cortical functional networks was parcellated for each subject using a previously proposed iteration algorithm. Dice coefficient was used to evaluate the spatial consistency of parcellated networks between 3.0 T and 5.0 T. Functional connectivity (FC) consistency was evaluated using the Euclidian distance and Graph-theory metrics. Results: A functional cortical atlas consisting of 18 networks was individually parcellated at 3.0 T and 5.0 T. The spatial consistency of these networks at 3.0 T and 5.0 T for the same subject was significantly higher than that of inter-individuals. The FC between the 18 networks acquired at 3.0 T and 5.0 T were highly consistent for the same subject. Positive cross-subject correlations in Graph-theory metrics were found between 3.0 T and 5.0 T. Conclusion: Individualized cortical functional networks at 3.0 T and 5.0 T showed consistent and stable parcellation results both spatially and functionally. The 5.0 T MR provides finer functional sub-network characteristics than that of 3.0 T.

Associations between differential connectivity patterns of executive control networks and APOE ɛ4 in the Alzheimer continuum.

The APOE ɛ4 allele and age are risk factors for Alzheimer's disease (AD) and contribute to decreased executive function. However, the influence of APOE ɛ4 on the executive control network (ECN) in the AD continuum is still unclear. This study included 269 participants aged between 50 and 95 years old, based on ADNI data, including 104 cognitively normal (CN) individuals, 72 individuals with early mild cognitive impairment (EMCI), 55 individuals with late mild cognitive impairment (LMCI), and 38 AD patients. Within each disease group, participants were subdivided into APOE ɛ4 carriers and non-carriers. We explored brain regions within the ECN affected by the interactions between genes and disease states by resting-state functional magnetic resonance imaging (fMRI) and voxel-based two-way analysis of variance (ANOVA). Subsequently, functional connectivity (FC) between seeds and peak clusters were extracted and correlated with the cognitive performance. We found that the damages of carrying APOE ɛ4 in ECNs mainly distributed in the fronto-parietal and parietal-temporal systems. Functional network intergroup differences indicated increased intrafrontal and fronto-parietal connectivity at the early stage of AD and increased connectivity between the parietal lobe and related regions at late disease in these APOE ɛ4 carriers. Our conclusion is that the functional connectivity in the ECN exhibits different distinguishably patterns of impairment in the AD continuum under the influence of the APOE ɛ4 allele. Patients with different genotypes showed heterogeneity in functional network changes in the early stages of disease, which may be a potential biomarker for early AD.

Effects of connectivity hyperalignment (CHA) on estimated brain network properties: from coarse-scale to fine-scale.

Recent gains in functional magnetic resonance imaging (fMRI) studies have been driven by increasingly sophisticated statistical and computational techniques and the ability to capture brain data at finer spatial and temporal resolution. These advances allow researchers to develop population-level models of the functional brain representations underlying behavior, performance, clinical status, and prognosis. However, even following conventional preprocessing pipelines, considerable inter-individual disparities in functional localization persist, posing a hurdle to performing compelling population-level inference. Persistent misalignment in functional topography after registration and spatial normalization will reduce power in developing predictive models and biomarkers, reduce the specificity of estimated brain responses and patterns, and provide misleading results on local neural representations and individual differences. This study aims to determine how connectivity hyperalignment (CHA)-an analytic approach for handling functional misalignment-can change estimated functional brain network topologies at various spatial scales from the coarsest set of parcels down to the vertex-level scale. The findings highlight the role of CHA in improving inter-subject similarities, while retaining individual-specific information and idiosyncrasies at finer spatial granularities. This highlights the potential for fine-grained connectivity analysis using this approach to reveal previously unexplored facets of brain structure and function.