Most recent paper

Exp Gerontol. 2024 Jun 10:112478. doi: 10.1016/j.exger.2024.112478. Online ahead of print.

ABSTRACT

BACKGROUND: Cerebral small vessel disease (CSVD) closely correlates to cognitive impairment, but its pathophysiology and the neurovascular mechanisms of cognitive deficits were unclear. We aimed to explore the dysfunctional patterns of neurovascular coupling (NVC) in patients with CSVD and further investigate the neurovascular mechanisms of CSVD-related cognitive impairment.

METHODS: Forty-three patients with CSVD and twenty-four healthy controls were recruited. We adopted resting-state functional magnetic resonance imaging combined with arterial spin labeling to investigate the NVC dysfunctional patterns in patients with CSVD. The Human Brain Atlas with 246 brain regions was applied to extract the NVC coefficients for each brain region. Partial correlation analysis and mediation analysis were used to explore the relationship between CSVD pathological features, NVC dysfunctional patterns, and cognitive decline.

RESULTS: 8 brain regions with NVC dysfunction were found in patients with CSVD (p < 0.025, Bonferroni correction). The NVC dysfunctional patterns in regions of the default mode network and subcortical nuclei were negatively associated with lacunes, white matter hyperintensities burden, and the severity of CSVD (FDR correction, q < 0.05). The NVC decoupling in regions located in the default mode network positively correlated with delayed recall deficits (FDR correction, q < 0.05). Mediation analysis suggested that the decreased NVC pattern of the left superior frontal gyrus partially mediated the impact of white matter hyperintensities on delayed recall (Mediation effect: -0.119; 95%CI: -11.604,-0.458; p < 0.05).

CONCLUSION: The findings of this study reveal the NVC dysfunctional pattern in patients with CSVD and illustrate the neurovascular mechanism of CSVD-related cognitive impairment. The NVC function in the left superior frontal gyrus may serve as a promising biomarker and therapeutic target for memory deficits in patients with CSVD.

PMID:38866193 | DOI:10.1016/j.exger.2024.112478

Hum Brain Mapp. 2024 Jun 1;45(8):e26753. doi: 10.1002/hbm.26753.

ABSTRACT

Predicting individual behavior from brain functional connectivity (FC) patterns can contribute to our understanding of human brain functioning. This may apply in particular if predictions are based on features derived from circumscribed, a priori defined functional networks, which improves interpretability. Furthermore, some evidence suggests that task-based FC data may yield more successful predictions of behavior than resting-state FC data. Here, we comprehensively examined to what extent the correspondence of functional network priors and task states with behavioral target domains influences the predictability of individual performance in cognitive, social, and affective tasks. To this end, we used data from the Human Connectome Project for large-scale out-of-sample predictions of individual abilities in working memory (WM), theory-of-mind cognition (SOCIAL), and emotion processing (EMO) from FC of corresponding and non-corresponding states (WM/SOCIAL/EMO/resting-state) and networks (WM/SOCIAL/EMO/whole-brain connectome). Using root mean squared error and coefficient of determination to evaluate model fit revealed that predictive performance was rather poor overall. Predictions from whole-brain FC were slightly better than those from FC in task-specific networks, and a slight benefit of predictions based on FC from task versus resting state was observed for performance in the WM domain. Beyond that, we did not find any significant effects of a correspondence of network, task state, and performance domains. Together, these results suggest that multivariate FC patterns during both task and resting states contain rather little information on individual performance levels, calling for a reconsideration of how the brain mediates individual differences in mental abilities.

PMID:38864353 | DOI:10.1002/hbm.26753

Brain Commun. 2024 Jun 4;6(3):fcae194. doi: 10.1093/braincomms/fcae194. eCollection 2024.

ABSTRACT

Lysergic acid diethylamide is a hallucinogen with complex neurobiological and behavioural effects. This is the first study to use MRI to follow functional changes in brain activity in response to different doses of lysergic acid diethylamide in fully awake, drug-naive rats. We hypothesized that lysergic acid diethylamide would show a dose-dependent increase in activity in the prefrontal cortex and thalamus while decreasing hippocampal activity. Female and male rats were given intraperitoneal injections of vehicle or lysergic acid diethylamide in doses of 10 or 100 µg/kg while fully awake during the imaging session. Changes in blood oxygen level-dependent signal were recorded over a 30-min window. Approximately 45-min post-injection data for resting-state functional connectivity were collected. All data were registered to rat 3D MRI atlas with 173 brain regions providing site-specific increases and decreases in global brain activity and changes in functional connectivity. Treatment with lysergic acid diethylamide resulted in a significant dose-dependent increase in negative blood oxygen level-dependent signal. The areas most affected were the primary olfactory system, prefrontal cortex, thalamus and hippocampus. This was observed in both the number of voxels affected in these brains regions and the changes in blood oxygen level-dependent signal over time. However, there was a significant increase in functional connectivity between the thalamus and somatosensory cortex and the cerebellar nuclei and the surrounding brainstem areas. Contrary to our hypothesis, there was an acute dose-dependent increase in negative blood oxygen level-dependent signal that can be interpreted as a decrease in brain activity, a finding that agrees with much of the behavioural data from preclinical studies. The enhanced connectivity between thalamus and sensorimotor cortices is consistent with the human literature looking at lysergic acid diethylamide treatments in healthy human volunteers. The unexpected finding that lysergic acid diethylamide enhances connectivity to the cerebellar nuclei raises an interesting question concerning the role of this brain region in the psychotomimetic effects of hallucinogens.

PMID:38863575 | PMC:PMC11166175 | DOI:10.1093/braincomms/fcae194

Aging (Albany NY). 2024 Jun 10;16. doi: 10.18632/aging.205913. Online ahead of print.

ABSTRACT

OBJECTIVE: A neurodevelopmental illness termed as the autism spectrum disorder (ASD) is described by social interaction impairments. Previous studies employing resting-state functional imaging (rs-fMRI) identified both hyperconnectivity and hypoconnectivity patterns in ASD people. However, specific patterns of connectivity within and between networks linked to ASD remain largely unexplored.

METHODS: We utilized a meticulously selected subset of high-quality data, comprising 45 individuals diagnosed with ASD and 47 HCs, obtained from the ABIDE dataset. The pre-processed rs-fMRI time series signals were partitioned into ninety regions of interest. We focused on eight intrinsic connectivity networks and further performed intra- and inter-network analysis. Finally, support vector machine was used to discriminate ASD from HC.

RESULTS: Through different sparsities, ASD exhibited significantly decreased intra-network connectivity within default mode network and dorsal attention network, increased connectivity between limbic network and subcortical network, and decreased connectivity between default mode network and limbic network. Using the classifier trained on altered intra- and inter-network connectivity, multivariate pattern analyses classified the ASD from HC with 71.74% accuracy, 70.21% specificity and 75.56% sensitivity in 10% sparsity of functional connectivity.

CONCLUSIONS: ASD showed characteristic reorganization of the brain networks and this provided new insight into the underlying process of the functional connectome dysfunction in ASD.

PMID:38862259 | DOI:10.18632/aging.205913

Eur Child Adolesc Psychiatry. 2024 Jun 11. doi: 10.1007/s00787-024-02476-w. Online ahead of print.

ABSTRACT

Although it is well recognized that autism spectrum disorder (ASD) is associated with atypical dynamic functional connectivity patterns, the dynamic changes in brain intrinsic activity over each time point and the potential molecular mechanisms associated with atypical dynamic temporal characteristics in ASD remain unclear. Here, we employed the Hidden Markov Model (HMM) to explore the atypical neural configuration at every scanning time point in ASD, based on resting-state functional magnetic resonance imaging (rs-fMRI) data from the Autism Brain Imaging Data Exchange. Subsequently, partial least squares regression and pathway enrichment analysis were employed to explore the potential molecular mechanism associated with atypical neural dynamics in ASD. 8 HMM states were inferred from rs-fMRI data. Compared to typically developing, individuals on the autism spectrum showed atypical state-specific temporal characteristics, including number of states and occurrences, mean life time and transition probability between states. Moreover, these atypical temporal characteristics could predict communication difficulties of ASD, and states assoicated with negative activation in default mode network and frontoparietal network, and positive activation in somatomotor network, ventral attention network, and limbic network, had higher predictive contribution. Furthermore, a total of 321 genes was revealed to be significantly associated with atypical dynamic brain states of ASD, and these genes are mainly enriched in neurodevelopmental pathways. Our study provides new insights into characterizing the atypical neural dynamics from a moment-to-moment perspective, and indicates a linkage between atypical neural configuration and gene expression in ASD.

PMID:38861168 | DOI:10.1007/s00787-024-02476-w

Front Hum Neurosci. 2024 May 27;18:1404759. doi: 10.3389/fnhum.2024.1404759. eCollection 2024.

ABSTRACT

OBJECTIVE: Recent research has highlighted the insula as a critical hub in human brain networks and the most susceptible region to subjective cognitive decline (SCD). However, the changes in functional connectivity of insular subregions in SCD patients remain poorly understood. The present study aims to clarify the altered functional connectivity patterns within insular subregions in individuals with SCD using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: In this study, we collected rs-fMRI data from 30 patients with SCD and 28 healthy controls (HCs). By defining three subregions of the insula, we mapped whole-brain resting-state functional connectivity (RSFC). We identified several distinct RSFC patterns of the insular subregions. Specifically, for positive connectivity, three cognitive-related RSFC patterns were identified within the insula, suggesting anterior-to-posterior functional subdivisions: (1) a dorsal anterior zone of the insula that shows RSFC with the executive control network (ECN); (2) a ventral anterior zone of the insula that shows functional connectivity with the salience network (SN); and (3) a posterior zone along the insula that shows functional connectivity with the sensorimotor network (SMN).

RESULTS: Compared to the controls, patients with SCD exhibited increased positive RSFC to the sub-region of the insula, demonstrating compensatory plasticity. Furthermore, these abnormal insular subregion RSFCs are closely correlated with cognitive performance in the SCD patients.

CONCLUSION: Our findings suggest that different insular subregions exhibit distinct patterns of RSFC with various functional networks, which are affected differently in patients with SCD.

PMID:38859994 | PMC:PMC11163085 | DOI:10.3389/fnhum.2024.1404759

medRxiv [Preprint]. 2024 May 27:2024.05.26.24307943. doi: 10.1101/2024.05.26.24307943.

ABSTRACT

INTRODUCTION: A recently developed mild behavioral impairment (MBI) diagnostic framework standardizes the early characterization of neuropsychiatric symptoms in older adults. However, the links between MBI, brain function, and Alzheimer's disease (AD) biomarkers are unclear.

METHODS: Using data from 128 participants with diagnosis of amnestic mild cognitive impairment and mild dementia - Alzheimer's type, we test a novel model assessing direct relationships between AD biomarker status and MBI symptoms, as well as mediated effects through segregation of the salience and default-mode networks.

RESULTS: We identified a mediated effect of tau positivity on MBI through functional segregation of the salience network from the other high-level, association networks. There were no direct effects of AD biomarkers status on MBI.

DISCUSSION: Our findings suggest an indirect role of tau pathology in MBI through brain network dysfunction and emphasize the role of the salience network in mediating relationships between neuropathological changes and behavioral manifestations.

PMID:38854100 | PMC:PMC11160832 | DOI:10.1101/2024.05.26.24307943

Biol Psychiatry. 2024 Jun 8:S0006-3223(24)01365-9. doi: 10.1016/j.biopsych.2024.05.025. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer's Disease (AD), identified as the most common type of dementia, presents considerable heterogeneity in clinical manifestations. Early intervention at the stage of mild cognitive impairment (MCI) holds potential in AD prevention. However, characterizing the heterogeneity of neurobiological abnormalities and identifying MCI subtypes pose significant challenges.

METHODS: We constructed sex-specific normative age models of dynamic brain functional networks and mapped the deviations of the brain characteristics for individuals from multiple datasets, including 295 AD patients, 441 MCI patients, and 1160 normal controls (NC). Then, based on these individual deviation patterns, subtypes for both AD and MCI were identified using the clustering method and comprehensively assessed their similarity and differences.

RESULTS: Individuals with AD and MCI were clustered into 2 subtypes, and these subtypes exhibited significant differences in both their intrinsic brain functional phenotypes and spatial atrophy patterns, as well as in disease progression and cognitive decline trajectories. The subtypes with positive deviations in AD and MCI shared similar deviation patterns, as well as those with negative deviations. There was a potential transformation of MCI with negative deviation patterns into AD, and these MCI have a more severe cognitive decline rate.

CONCLUSIONS: This study quantifies neurophysiological heterogeneity by analyzing deviation patterns from the dynamic functional connectome normative model and identifies disease subtypes in AD and MCI using a comprehensive resting-state fMRI multicenter dataset. It provides new insights for developing early prevention and personalized treatment strategies for AD.

PMID:38857821 | DOI:10.1016/j.biopsych.2024.05.025

J Headache Pain. 2024 Jun 11;25(1):97. doi: 10.1186/s10194-024-01803-5.

ABSTRACT

BACKGROUND: Mindfulness practice has gained interest in the management of Chronic Migraine associated with Medication Overuse Headache (CM-MOH). Mindfulness is characterized by present-moment self-awareness and relies on attention control and emotion regulation, improving headache-related pain management. Mindfulness modulates the Default Mode Network (DMN), Salience Network (SN), and Fronto-Parietal Network (FPN) functional connectivity. However, the neural mechanisms underlying headache-related pain management with mindfulness are still unclear. In this study, we tested neurofunctional changes after mindfulness practice added to pharmacological treatment as usual in CM-MOH patients.

METHODS: The present study is a longitudinal phase-III single-blind Randomized Controlled Trial (MIND-CM study; NCT03671681). Patients had a diagnosis of CM-MOH, no history of neurological and severe psychiatric comorbidities, and were attending our specialty headache centre. Patients were divided in Treatment as Usual (TaU) and mindfulness added to TaU (TaU + MIND) groups. Patients underwent a neuroimaging and clinical assessment before the treatment and after one year. Longitudinal comparisons of DMN, SN, and FPN connectivity were performed between groups and correlated with clinical changes. Vertex-wise analysis was performed to assess cortical thickness changes.

RESULTS: 177 CM-MOH patients were randomized to either TaU group or TaU + MIND group. Thirty-four patients, divided in 17 TaU and 17 TaU + MIND, completed the neuroimaging follow-up. At the follow-up, both groups showed an improvement in most clinical variables, whereas only TaU + MIND patients showed a significant headache frequency reduction (p = 0.028). After one year, TaU + MIND patients showed greater SN functional connectivity with the left posterior insula (p-FWE = 0.007) and sensorimotor cortex (p-FWE = 0.026). In TaU + MIND patients only, greater SN-insular connectivity was associated with improved depression scores (r = -0.51, p = 0.038). A longitudinal increase in cortical thickness was observed in the insular cluster in these patients (p = 0.015). Increased anterior cingulate cortex thickness was also reported in TaU + MIND group (p-FWE = 0.02).

CONCLUSIONS: Increased SN-insular connectivity might modulate chronic pain perception and the management of negative emotions. Enhanced SN-sensorimotor connectivity could reflect improved body-awareness of painful sensations. Expanded cingulate cortex thickness might sustain improved cognitive processing of nociceptive information. Our findings unveil the therapeutic potential of mindfulness and the underlying neural mechanisms in CM-MOH patients.

TRIAL REGISTRATION: Name of Registry; MIND-CM study; Registration Number ClinicalTrials.gov identifier: NCT0367168; Registration Date: 14/09/2018.

PMID:38858629 | DOI:10.1186/s10194-024-01803-5

Commun Biol. 2024 Jun 10;7(1):716. doi: 10.1038/s42003-024-06335-x.

ABSTRACT

The awake mammalian brain is functionally organized in terms of large-scale distributed networks that are constantly interacting. Loss of consciousness might disrupt this temporal organization leaving patients unresponsive. We hypothesize that characterizing brain activity in terms of transient events may provide a signature of consciousness. For this, we analyze temporal dynamics of spatiotemporally overlapping functional networks obtained from fMRI transient activity across different anesthetics and levels of anesthesia. We first show a striking homology in spatial organization of networks between monkeys and humans, indicating cross-species similarities in resting-state fMRI structure. We then track how network organization shifts under different anesthesia conditions in macaque monkeys. While the spatial aspect of the networks is preserved, their temporal dynamics are highly affected by anesthesia. Networks express for longer durations and co-activate in an anesthetic-specific configuration. Additionally, hierarchical brain organization is disrupted with a consciousness-level-signature role of the default mode network. In conclusion, large-scale brain network temporal dynamics capture differences in anesthetic-specific consciousness-level, paving the way towards a clinical translation of these cortical signature.

PMID:38858589 | DOI:10.1038/s42003-024-06335-x

bioRxiv [Preprint]. 2024 May 30:2024.05.29.596506. doi: 10.1101/2024.05.29.596506.

ABSTRACT

BACKGROUND: Predicting future brain health is a complex endeavor that often requires integrating diverse data sources. The neural patterns and interactions iden-tified through neuroimaging serve as the fundamental basis and early indica-tors that precede the manifestation of observable behaviors or psychological states.

NEW METHOD: In this work, we introduce a multimodal predictive modeling approach that leverages an imaging-informed methodology to gain insights into fu-ture behavioral outcomes. We employed three methodologies for evalua-tion: an assessment-only approach using support vector regression (SVR), a neuroimaging-only approach using random forest (RF), and an image-assisted method integrating the static functional network connectivity (sFNC) matrix from resting-state functional magnetic resonance imaging (rs-fMRI) alongside assessments. The image-assisted approach utilized a partially con-ditional variational autoencoder (PCVAE) to predict brain health constructs in future visits from the behavioral data alone.

RESULTS: Our performance evaluation indicates that the image-assisted method ex-cels in handling conditional information to predict brain health constructs in subsequent visits and their longitudinal changes. These results suggest that during the training stage, the PCVAE model effectively captures relevant in-formation from neuroimaging data, thereby potentially improving accuracy in making future predictions using only assessment data.

COMPARISON WITH EXISTING METHODS: The proposed image-assisted method outperforms traditional assessment-only and neuroimaging-only approaches by effectively integrating neuroimag-ing data with assessment factors.

CONCLUSION: This study underscores the potential of neuroimaging-informed predictive modeling to advance our comprehension of the complex relationships between cognitive performance and neural connectivity.

HIGHLIGHTS: Multifaceted perspective for studying longitudinal brain health changes.Showcases the versatility of methodologies through assessment-only, neuroimaging-only, and image-assisted predictive approaches.Provides predictive insights by revealing the neural patterns corresponding to alterations in behavior.

PMID:38854031 | PMC:PMC11160794 | DOI:10.1101/2024.05.29.596506

bioRxiv [Preprint]. 2024 Jun 1:2023.08.13.553101. doi: 10.1101/2023.08.13.553101.

ABSTRACT

There are a growing number of neuroimaging studies motivating joint structural and functional brain connectivity. Brain connectivity of different modalities provides insight into brain functional organization by leveraging complementary information, especially for brain disorders such as schizophrenia. In this paper, we propose a multi-modal independent component analysis (ICA) model that utilizes information from both structural and functional brain connectivity guided by spatial maps to estimate intrinsic connectivity networks (ICNs). Structural connectivity is estimated through whole-brain tractography on diffusion-weighted MRI (dMRI), while functional connectivity is derived from resting-state functional MRI (rs-fMRI). The proposed structural-functional connectivity and spatially constrained ICA (sfCICA) model estimates ICNs at the subject level using a multi-objective optimization framework. We evaluated our model using synthetic and real datasets (including dMRI and rs-fMRI from 149 schizophrenia patients and 162 controls). Multi-modal ICNs revealed enhanced functional coupling between ICNs with higher structural connectivity, improved modularity, and network distinction, particularly in schizophrenia. Statistical analysis of group differences showed more significant differences in the proposed model compared to the unimodal model. In summary, the sfCICA model showed benefits from being jointly informed by structural and functional connectivity. These findings suggest advantages in simultaneously learning effectively and enhancing connectivity estimates using structural connectivity.

PMID:38853973 | PMC:PMC11160563 | DOI:10.1101/2023.08.13.553101

Neuroimage. 2024 Jun 7:120669. doi: 10.1016/j.neuroimage.2024.120669. Online ahead of print.

ABSTRACT

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

PMID:38852805 | DOI:10.1016/j.neuroimage.2024.120669

Alzheimers Res Ther. 2024 Jun 8;16(1):124. doi: 10.1186/s13195-024-01486-9.

ABSTRACT

BACKGROUND: Higher order regulation of autonomic function is maintained by the coordinated activity of specific cortical and subcortical brain regions, collectively referred to as the central autonomic network (CAN). Autonomic changes are frequently observed in Alzheimer's disease (AD) and dementia, but no studies to date have investigated whether plasma AD biomarkers are associated with CAN functional connectivity changes in at risk older adults.

METHODS: Independently living older adults (N = 122) without major neurological or psychiatric disorder were recruited from the community. Participants underwent resting-state brain fMRI and a CAN network derived from a voxel-based meta-analysis was applied for overall, sympathetic, and parasympathetic CAN connectivity using the CONN Functional Toolbox. Sensorimotor network connectivity was studied as a negative control. Plasma levels of amyloid (Aβ42, Aβ40), neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) were assessed using digital immunoassay. The relationship between plasma AD biomarkers and within-network functional connectivity was studied using multiple linear regression adjusted for demographic covariates and Apolipoprotein E (APOE) genotype. Interactive effects with APOE4 carrier status were also assessed.

RESULTS: All autonomic networks were positively associated with Aβ42/40 ratio and remained so after adjustment for age, sex, and APOE4 carrier status. Overall and parasympathetic networks were negatively associated with GFAP. The relationship between the parasympathetic CAN and GFAP was moderated by APOE4 carrier status, wherein APOE4 carriers with low parasympathetic CAN connectivity displayed the highest plasma GFAP concentrations (B = 910.00, P = .004). Sensorimotor connectivity was not associated with any plasma AD biomarkers, as expected.

CONCLUSION: The present study findings suggest that CAN function is associated with plasma AD biomarker levels. Specifically, lower CAN functional connectivity is associated with decreased plasma Aβ42/40, indicative of cerebral amyloidosis, and increased plasma GFAP in APOE4 carriers at risk for AD. These findings could suggest higher order autonomic and parasympathetic dysfunction in very early-stage AD, which may have clinical implications.

PMID:38851772 | DOI:10.1186/s13195-024-01486-9

Neuroimage. 2024 Jun 6:120672. doi: 10.1016/j.neuroimage.2024.120672. Online ahead of print.

ABSTRACT

Age-related white matter hyperintensities are a common feature and are known to be negatively associated with structural integrity, functional connectivity, and cognitive performance. However, this has yet to be fully understood mechanistically. We analyzed multiple MRI modalities acquired in 465 non-demented individuals from the Swedish BioFINDER study including 334 cognitively normal and 131 participants with mild cognitive impairment. White matter hyperintensities were automatically quantified using fluid-attenuated inversion recovery MRI and parameters from diffusion tensor imaging were estimated in major white matter fibre tracts. We calculated fMRI resting state-derived functional connectivity within and between predefined cortical regions structurally linked by the white matter tracts. How change in functional connectivity is affected by white matter lesions and related to cognition (in the form of executive function and processing speed) was explored. We examined the functional changes using a measure of sample entropy. As expected hyperintensities were associated with disrupted structural white matter integrity and were linked to reduced functional interregional lobar connectivity, which was related to decreased processing speed and executive function. Simultaneously, hyperintensities were also associated with increased intraregional functional connectivity, but only within the frontal lobe. This phenomenon was also associated with reduced cognitive performance. The increased connectivity was linked to increased entropy (reduced predictability and increased complexity) of the involved voxels' blood oxygenation level-dependent signal. Our findings expand our previous understanding of the impact of white matter hyperintensities on cognition by indicating novel mechanisms that may be important beyond this particular type of brain lesions.

PMID:38851551 | DOI:10.1016/j.neuroimage.2024.120672

Neuroimage Clin. 2024 Jun 2;43:103628. doi: 10.1016/j.nicl.2024.103628. Online ahead of print.

ABSTRACT

OBJECTIVE: Benign childhood epilepsy with centrotemporal spikes (BECTS) affects brain network hierarchy and cognitive function; however, itremainsunclearhowhierarchical changeaffectscognition in patients with BECTS. A major aim of this study was to examine changes in the macro-network function hierarchy in BECTS and its potential contribution to cognitive function.

METHODS: Overall, the study included 50 children with BECTS and 69 healthy controls. Connectome gradient analysis was used to determine the brain network hierarchy of each group. By comparing gradient scores at each voxel level and network between groups, we assessed changes in whole-brain voxel-level and network hierarchy. Functional connectivity was used to detect the functional reorganization of epilepsy caused by these abnormal brain regions based on these aberrant gradients. Lastly, we explored the relationships between the change gradient and functional connectivity values and clinical variables and further predicted the cognitive function associated with BECTS gradient changes.

RESULTS: In children with BECTS, the gradient was extended at different network and voxel levels. The gradient scores frontoparietal network was increased in the principal gradient of patients with BECTS. The left precentral gyrus (PCG) and right angular gyrus gradient scores were significantly increased in the principal gradient of children with BECTS. Moreover, in regions of the brain with abnormal principal gradients, functional connectivity was disrupted. The left PCG gradient score of children with BECTS was correlated with the verbal intelligence quotient (VIQ), and the disruption of functional connectivity in brain regions with abnormal principal gradients was closely related to cognitive function. VIQ was significantly predicted by the principal gradient map of patients.

SIGNIFICANCE: The results indicate connectome gradient disruption in children with BECTS and its relationship to cognitive function, thereby increasing our understanding of the functional connectome hierarchy and providing potential biomarkers for cognitive function of children with BECTS.

PMID:38850833 | DOI:10.1016/j.nicl.2024.103628

Brain Behav. 2024 Jun;14(6):e3591. doi: 10.1002/brb3.3591.

ABSTRACT

PURPOSE: Vestibular migraine (VM) is a disorder with prominent vestibular symptoms that are causally correlated with migraine and is the most prevalent neurological cause of episodic vertigo. Nevertheless, the functional underpinnings of VM remain largely unclear. This study aimed to reveal concordant alteration patterns of functional connectivity (FC) in VM patients.

METHODS: We searched literature measuring resting-state FC abnormalities of VM patients in PubMed, Embase, Cochrane, and Scopus databases before May 2023. Furthermore, we applied the anisotropic effect size-signed differential mapping (AES-SDM) to conduct a whole-brain voxel-wise meta-analysis to identify the convergence of FC alterations in VM patients.

RESULTS: Nine studies containing 251 VM patients and 257 healthy controls (HCs) were included. Relative to HCs, VM patients showed reduced activity in the left superior temporal gyrus and left midcingulate/paracingulate gyri, and increased activity in the precuneus, right superior parietal gyrus, and right middle frontal gyrus. Jackknife's analysis and subgroup analysis further supported the generalization and robustness of the main results. Furthermore, meta-regression analyses indicated that the Dizziness Handicap Inventory (DHI) ratings were positively correlated with the activity in the precuneus, while higher Headache Impact Test-6 and DHI scores were associated with lower activity within the left midcingulate/paracingulate gyri.

CONCLUSIONS: The study indicates that VM is associated with specific functional deficits of VM patients in crucial regions involved in the vestibular and pain networks and provides further information on the pathophysiological mechanisms of VM.

PMID:38849984 | DOI:10.1002/brb3.3591

Brain Behav. 2024 Jun;14(6):e3585. doi: 10.1002/brb3.3585.

ABSTRACT

INTRODUCTION: Premature ejaculation (PE), a common male sexual dysfunction, often accompanies by abnormal psychological factors, such as depression. Recent neuroimaging studies have revealed structural and functional brain abnormalities in PE patients. However, there is limited neurological evidence supporting the comorbidity of PE and depression. This study aimed to explore the topological changes of the functional brain networks of PE patients with depression.

METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 60 PE patients (30 with depression and 30 without depression) and 29 healthy controls (HCs). Functional brain networks were constructed for all participants based on rs-fMRI data. The nodal parameters including nodal centrality and efficiency were calculated by the method of graph theory analysis and then compared between groups. In addition, the results were corrected for multiple comparisons by family-wise error (FWE) (p < .05).

RESULTS: PE patients with depression had increased degree centrality and global efficiency in the right pallidum, as well as increased degree centrality in the right thalamus when compared with HCs. PE patients without depression showed increased degree centrality in the right pallidum and thalamus, as well as increased global efficiency in the right precuneus, pallidum, and thalamus when compared with HCs. PE patients with depression demonstrated decreased degree centrality in the right pallidum and thalamus, as well as decreased global efficiency in the right precuneus, pallidum, and thalamus when compared to those without depression. All the brain regions above survived the FWE correction.

CONCLUSION: The results suggested that increased and decreased functional connectivity, as well as the capability of global integration of information in the brain, might be related to the occurrence of PE and the comorbidity depression in PE patients, respectively. These findings provided new insights into the understanding of the pathological mechanisms underlying PE and those with depression.

PMID:38849981 | DOI:10.1002/brb3.3585

BMC Psychiatry. 2024 Jun 7;24(1):428. doi: 10.1186/s12888-024-05869-y.

ABSTRACT

BACKGROUND: Theoretical and empirical evidence indicates the critical role of the default mode network (DMN) in the pathophysiology of the bipolar disorder (BD). This study aims to identify the specific brain regions of the DMN that is impaired in patients with BD.

METHODS: A total of 56 patients with BD and 71 healthy controls (HC) underwent resting-state functional magnetic resonance imaging. Three commonly used functional indices, i.e., fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC), were utilized to identify the brain region showing abnormal spontaneous brain activity in patients with BD. Then, this region served as the seed region for resting-state functional connectivity (rsFC) analysis.

RESULTS: Compared to the HC group, the BD group showed reduced fALFF, ReHo, and DC values in the left precuneus. Moreover, patients exhibited decreased rsFCs within the left precuneus and between the left precuneus and the medial prefrontal cortex. Additionally, there was diminished negative connectivity between the left precuneus and the left putamen, extending to the left insula (putamen/insula). The abnormalities in DMN functional connectivity were confirmed through various analysis strategies.

CONCLUSIONS: Our findings provide convergent evidence for the abnormalities in the DMN, particularly located in the left precuneus. Decreased functional connectivity within the DMN and the reduced anticorrelation between the DMN and the salience network are found in patients with BD. These findings suggest that the DMN is a key aspect for understanding the neural basis of BD, and the altered functional patterns of DMN may be a potential candidate biomarker for diagnosis of BD.

PMID:38849793 | DOI:10.1186/s12888-024-05869-y

Commun Biol. 2024 Jun 7;7(1):703. doi: 10.1038/s42003-024-06405-0.

ABSTRACT

Novelty and appropriateness are two fundamental components of creativity. However, the way in which novelty and appropriateness are separated at behavioral and neural levels remains poorly understood. In the present study, we aim to distinguish behavioral and neural bases of novelty and appropriateness of creative idea generation. In alignment with two established theories of creative thinking, which respectively, emphasize semantic association and executive control, behavioral results indicate that novelty relies more on associative abilities, while appropriateness relies more on executive functions. Next, employing a connectome predictive modeling (CPM) approach in resting-state fMRI data, we define two functional network-based models-dominated by interactions within the default network and by interactions within the limbic network-that respectively, predict novelty and appropriateness (i.e., cross-brain prediction). Furthermore, the generalizability and specificity of the two functional connectivity patterns are verified in additional resting-state fMRI and task fMRI. Finally, the two functional connectivity patterns, respectively mediate the relationship between semantic association/executive control and novelty/appropriateness. These findings provide global and predictive distinctions between novelty and appropriateness in creative idea generation.

PMID:38849461 | DOI:10.1038/s42003-024-06405-0