Most recent paper

J Cell Neurosci. 2025;2(1):1-11. doi: 10.31586/jcn.2025.1241. Epub 2025 Feb 25.

ABSTRACT

BACKGROUND: The Cingulo-Opercular Network (CON) is a crucial executive control network involved in regulating actions and facilitating higher-order cognitive processes. Resting-state functional connectivity between the CON and the Default Mode Network (DMN) plays a vital role in cognitive regulation, enabling the transition between internally focused and externally directed tasks. This study investigates whether resting-state functional connectivity between the CON and DMN mediates the effects of social determinants, such as educational opportunities and family structure, on cognitive outcomes in youth.

AIMS: This study aims to explore how CON-DMN connectivity influences the relationship between social gradients and cognition in youth. Specifically, it examines whether resting-state functional connectivity between these networks mediates the effects of educational opportunities and family structure on cognitive outcomes and seeks to uncover the neural mechanisms underlying these social gradients.

METHODS: Data were derived from the Adolescent Brain Cognitive Development (ABCD) study, a large longitudinal dataset of over 11,000 children aged 9-10 years. Cognitive outcomes were assessed using standardized NIH toolbox measures: Total Composite, Fluid Reasoning, Picture Vocabulary, Pattern Recognition, and Card Sorting. Social determinants were operationalized using indicators such as parental education, family composition, and neighborhood educational opportunities (COI). Resting-state functional connectivity (rsFC) between the CON and DMN was measured using functional magnetic resonance imaging (fMRI). Structural equation modeling (SEM) was employed to test whether CON-DMN rsFC mediated the relationship between social determinants and cognitive outcomes, adjusting for potential confounders such as age, sex, and race/ethnicity.

RESULTS: Stable family structure and greater educational opportunities were significantly associated with improved cognitive performance. These relationships were mediated by reduced functional connectivity between the CON and DMN.

CONCLUSION: Reduced functional connectivity between the CON and DMN serves as a neural mechanism linking social gradients, such as educational opportunities and family structure, to better cognitive outcomes in youth.

PMID:40060241 | PMC:PMC11887688 | DOI:10.31586/jcn.2025.1241

World Neurosurg. 2025 Mar 7:123875. doi: 10.1016/j.wneu.2025.123875. Online ahead of print.

ABSTRACT

OBJECT: Utilizing whole-brain functional magnetic resonance imaging(fMRI) to investigate abnormal spontaneous brain activity in the resting state of patients with trigeminal neuralgia (TN) and explore their relationship with pain symptoms and negative emotions.

METHODS: This study included 46 patients with TN diagnosed at our hospital from December 2022 to June 2023 and 35 healthy controls (HCs). All patients with TN completed questionnaires related to pain and emotions. The data analysis used the DPABI toolkit based on MATLAB platform and compared amplitude of low frequency fluctuation (ALFF) in brain between TN and HC groups. To delve deeper, we will utilize Pearson correlation analysis to explore the intricate relationships between pain symptoms, negative emotions, and brain functional abnormalities in patients of TN.

RESULT: Compared with HCs, patients of TN exhibited significantly reduced ALFF in the left superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), bilateral inferior frontal gyrus (IFG), right precentral gyrus (PrG), right superior temporal gyrus (STG), bilateral middle temporal gyrus (MTG) , left inferior temporal gyrus (ITG), right cingulate gyrus (CG) (p<0.05). In correlation analysis, ALFF in the left SFG and right CG were negatively correlated with pain symptoms and negative emotions in patients of TN.

CONCLUSION: Patients of TN show functional abnormalities in several key brain regions that are involved in pain perception and emotional regulation. These abnormalities primarily manifest as a reduction in spontaneous neural activity. The ALFF in the left SFG and right CG is negatively correlated with the severity of pain and negative emotions, indicating that the more severe the pain and negative emotions in patients of TN, the more obvious the decrease in neural activity in specific brain regions. This suggests that the left SFG and right CG may be characteristic brain regions in the pathophysiological mechanism of TN.

PMID:40058640 | DOI:10.1016/j.wneu.2025.123875

Biol Psychiatry Cogn Neurosci Neuroimaging. 2025 Mar 7:S2451-9022(25)00070-9. doi: 10.1016/j.bpsc.2025.02.013. Online ahead of print.

ABSTRACT

INTRODUCTION: Children with externalizing disorders (EDs) often have difficulties with impulsivity and emotion regulation. These constructs have been associated with dysfunction in the recruitment of reward processing circuits and striatal connectivity with cortical networks. However, it is unclear to what extent co-presentations of impulsivity and emotion regulation are associated with differences in striatocortical connectivity.

METHODS: In Study 1, a latent profile analysis (LPA) was conducted in a sample of 198 youths with EDs (Oppositional Defiant Disorder and/or Conduct Disorder) to investigate co-presentation of impulsivity and emotion regulation symptoms. Participants completed the UPPS Impulsivity Scale (UPPS) and the Emotion Regulation Checklist (ERC). LPA was applied to the subscales of the UPPS and ERC. In Study 2, we examined 169 participants who completed a resting state fMRI scan to examine differences in striatocortical connectivity between profiles.

RESULTS: The LPA identified three profiles: Moderate Impulsivity (IMP)/Moderate Emotion Regulation, High IMP/Low Emotion Regulation (ER), and High IMP/Moderate Emotion Regulation. The two High IMP profiles were associated with greater connectivity between the posterior caudate nucleus and parietal cortex. The High IMP/Low ER profile was associated with increased connectivity between the anterior caudate and anterior insula.

DISCUSSION: The current data indicate that the profiles associated with high impulsivity are associated with greater caudate-parietal cortex connectivity while the profile associated with high impulsivity and impaired emotion regulation showed increased anterior caudate-AIC connectivity. The current work contributes to the literature by examining the relationship between heterogeneity of externalizing symptoms and functional connectivity.

PMID:40058459 | DOI:10.1016/j.bpsc.2025.02.013

Neuroimage Clin. 2025 Mar 5;46:103763. doi: 10.1016/j.nicl.2025.103763. Online ahead of print.

ABSTRACT

INTRODUCTION: Current multimodal prediction models can determine the prognosis of about half of comatose cardiac arrest patients. We investigated whether whole-brain graph-theoretical measures from early resting-state functional magnetic resonance imaging (fMRI) three days after cardiac arrest discriminate between good and poor outcome and improve outcome prediction.

METHODS: We conducted a prospective cohort study on comatose cardiac arrest patients on intensive care units. Resting-state fMRI three days after cardiac arrest was used to quantify whole-brain functional connectivity, global efficiency, clustering coefficient, and modularity. Neurological outcome at six months was classified as good or poor (Cerebral Performance Category 1-2 vs 3-5). Logistic regression models were used to examine between-group differences and study the additional value of graph-theoretical measures to clinical and EEG-based prediction.

RESULTS: In seventy included patients (good outcome n = 44, poor n = 26), whole-brain functional connectivity and clustering coefficient (but not global efficiency and modularity) were significantly lower in patients with poor outcome. Connectivity of nodes in posterior brain areas most prominently correlated with outcome. Clustering coefficient showed strong correlation with whole-brain functional connectivity. Patients with continuous EEG patterns differed in whole-brain functional connectivity levels from those with suppressed or epileptiform patterns. Combining functional connectivity or graph measures with clinical and EEG-based predictors slightly improved outcome prediction.

CONCLUSION: fMRI-based whole-brain functional connectivity is a sensitive measure for encephalopathy severity after cardiac arrest, according to relations with established EEG categories and discrimination between good and poor outcome. Additional predictive values for outcome seem small. Graph measures do not provide complementary information.

PMID:40056784 | DOI:10.1016/j.nicl.2025.103763

IEEE Trans Neural Syst Rehabil Eng. 2025 Mar 7;PP. doi: 10.1109/TNSRE.2025.3549380. Online ahead of print.

ABSTRACT

Mirror therapy (MT) is an effective approach in stroke recovery, but its impact on subcortical neural reorganization remains unclear. Thus, we aimed to investigate the neuroplastic effects on white matter due to MT. In this study, thirty-three participants with stroke were recruited and randomly assigned into the MT group (n=16) or the control group (n=17) for a 4-week intervention. Before and after the intervention, motor recovery was evaluated using the Fugl-Meyer Assessment upper limb subscale (FMA-UL), and the white matter structure and function were investigated using DTI and resting-state fMRI, focusing on the corticospinal tract and the corpus callosum. Significant correlations between the improvements of the FMA-UL and the baseline fractional anisotropy of ipsilesional corticospinal tract (p < 0.001) and corpus callosum (p = 0.009) were observed only in the MT group. Additionally, no significant structural alterations were found between the two groups after the intervention. The fractional amplitude of low-frequency fluctuation of ipsilesional corticospinal tract (p = 0.003) and corpus callosum (p = 0.005) were significantly enhanced only in the MT group, which were correlated with the improvements of the FMA-UL (p < 0.001). Furthermore, partial correlation analysis and subsequent mediation model analysis suggested that the changes of fractional amplitude of low-frequency fluctuation in corpus callosum partially mediated the effect of the baseline fractional anisotropy of ipsilesional corticospinal tract on the FMA-UL improvements in the MT group. This study provided neuroimaging evidence on white matter reorganization after MT, specifically the corpus callosum, suggesting a potential interhemispheric transcallosal neuroplastic mechanism of MT.

PMID:40053618 | DOI:10.1109/TNSRE.2025.3549380

Curr Med Imaging. 2025 Mar 6. doi: 10.2174/0115734056344477250222060225. Online ahead of print.

ABSTRACT

BACKGROUND: The basal ganglia area is a frequent site of stroke, which commonly causes intricate functional impairments. This study aims to uncover disparities in static and dynamic functional connectivity (FC) of the brain in patients afflicted with left-sided basal ganglia stroke (L-BGS) and right-sided basal ganglia region stroke (R-BGS), furthermore scrutinising the mechanism behind the lateralisation of the stroke.

METHODS: A total of 23 patients with L-BGS and 20 patients with R-BGS were recruited, alongside 20 healthy control subjects. Resting-state functional magnetic resonance imaging and sliding window techniques were employed to conduct static and dynamic FC analyses on both patient groups and controls, which can enable a more refined evaluation of the variations in neural signals.

RESULTS: The inter-network connectivity analysis showed significant changes only in the L-BGS patient group (p < 0.05). The R-BGS group showed increased connectivity in the auditory and posterior visual networks, while the L-BGS group showed reduced connectivity. In dynamic connectivity analyses, the L-BGS group exhibited greater positive network connectivity reorganization.

CONCLUSION: Within one month of stroke onset, the L-BGS group showed a more pronounced impairment of inter-network connectivity, alongside enhanced FC compensatory changes of a positive nature. Differential changes in the two patient groups may provide useful information for individualized rehabilitation strategies.

PMID:40051368 | DOI:10.2174/0115734056344477250222060225

Brain Imaging Behav. 2025 Mar 6. doi: 10.1007/s11682-025-00984-0. Online ahead of print.

ABSTRACT

This study aimed to elucidate distinctive patterns of brain functional activity in tremor-dominant Multiple System Atrophy (MSA) and Parkinson's Disease (PD) patients and develop a diagnostic model distinguishing between the two conditions based on these changes. Resting-state fMRI data from 45 MSA patients, 55 PD patients, and 48 healthy controls were analyzed using Percent Amplitude of Fluctuation (PerAF), Functional (FC) and Effective Connectivity (EC) analyses. The Support Vector Machine (SVM) was used to create the diagnostic model from the identified functional alterations. Partial correlation analyses explored the relationship between functional abnormalities and tremors. Both MSA and PD patients with tremors exhibited similar activity changes in bilateral Orbital part of the superior frontal gyrus (ORBsup), Cerebellum VIII (CRBL8), left Cerebellum IV-V (CRBL45.L), right rectus (REC), and FC based on the seeds of PUT.L, CRBL8.R, and REC.R. These changes were more pronounced in MSA patients. However, MSA patients exhibited heightened putamen activity and enhanced EC from caudate (CAU) to putamen, whereas these activity and connectivity were decreased in PD patients. The SVM model achieved strong performance, with the putamen exerting the most significant influence on classification. In summary, dysfunction within the cerebello-cortical and basal ganglia network circuits is implicated in the tremors of both MSA and PD patients. The alteration in cerebellar-cortical regions were similar, with MSA displaying more pronounced changes, contrasting changes were observed in the basal ganglia region. The putamen may serve as crucial neurobiological indicators for the precise differentiation of MSA and PD patients.

PMID:40050534 | DOI:10.1007/s11682-025-00984-0

Sci Rep. 2025 Mar 6;15(1):7828. doi: 10.1038/s41598-025-89023-y.

ABSTRACT

The time-varying functional connectivity of the Central Executive Network (CEN), Default Mode Network (DMN), and Salience Network (SN) in flight trainees during a resting state was investigated using dynamic functional network connectivity (dFNC). The study included 39 flight trainees and 37 age- and sex-matched healthy controls. Resting-state fMRI data and behavioral test outcomes were obtained from both groups. Independent component analysis (ICA), sliding window, and K-means clustering approaches were utilized for evaluating functional network connectivity (FNC) and temporal metrics based on the triple networks. Correlation analyses were performed on the behavioral assessments and these metrics. The flight trainees demonstrated a significantly enhanced functional connection linking the CEN and DMN in state 2 (P < 0.05, FDR corrected). Additionally, flight trainees spent less time in state 5, while they exhibited a protracted mean dwell time and fractional windows in state 2, which were significantly correlated with accuracy on the Berg Card Sorting Test (BCST) and Change Detection Test (all P < 0.05). The improved connectivity of flight trainees between the CEN and DMN following the completion of rigorous flight training resulted in increased stability. This enhancement may be relevant to cognitive abilities such as decision-making, memory, and information integration. When multitasking, flight trainees displayed superior visual processing skills and enhanced cognitive flexibility. dFNC research provides a unique perspective on the sophisticated cognitive capabilities that are required in high-demand, high-stress occupations such as piloting, thereby providing significant insights into the intricate brain mechanisms that are inherent in these domains.

PMID:40050304 | DOI:10.1038/s41598-025-89023-y

Neurotherapeutics. 2025 Mar 5:e00556. doi: 10.1016/j.neurot.2025.e00556. Online ahead of print.

ABSTRACT

Intermittent theta burst stimulation (iTBS), a novel protocol within repetitive transcranial magnetic stimulation (rTMS), has shown superior therapeutic effects for depression compared to conventional high-frequency rTMS (HF-rTMS). However, the neural mechanisms underlying iTBS remain poorly understood. Brain entropy (BEN), a measure of the irregularity of brain activity, has recently emerged as a promising marker for regional brain function and has demonstrated sensitivity to depression and HF-rTMS. Given its potential, BEN may help elucidate the mechanisms of iTBS. In this study, we computed BEN using resting-state fMRI data from sixteen healthy participants obtained from OpenNeuro. Participants underwent iTBS over the left dorsolateral prefrontal cortex (L-DLPFC) at two different intensities (90 ​% and 120 ​% of resting motor threshold (rMT)) on separate days. We used a 2 ​× ​2 repeated measures analysis of variance (ANOVA) to analyze the interaction between iTBS stimulation intensity and the pre- vs. post-stimulation effects on BEN and paired sample t-tests to examine the specific BEN effects of iTBS at different intensities. Additionally, spatial correlation analysis was conducted to determine whether iTBS altered the baseline coupling between BEN and neurotransmitter receptors/transporters, to investigate potential neurotransmitter changes induced by iTBS. Our results indicate that subthreshold iTBS (90 ​% rMT) reduced striatal BEN, while suprathreshold iTBS (120 ​% rMT) increased it. Subthreshold iTBS led to changes in the baseline coupling between BEN and several neurotransmitter receptor/transporter maps, primarily involving serotonin (5-HT), cannabinoid (CB), acetylcholine (ACh), and glutamate (Glu). Our findings suggest that BEN is sensitive to the effects of iTBS, with different stimulation intensities having distinct effects on neural activity. Notably, subthreshold iTBS may offer more effective stimulation. This research highlights the crucial role of stimulation intensity in modulating brain activity and lays the groundwork for future clinical studies focused on optimizing therapeutic outcomes through precise stimulation intensity.

PMID:40050146 | DOI:10.1016/j.neurot.2025.e00556

Biol Psychiatry. 2025 Mar 4:S0006-3223(25)01011-X. doi: 10.1016/j.biopsych.2025.02.897. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, with available treatments often showing limited efficacy. Recent research suggests targeting specific subtypes of depression and understanding the underlying brain mechanisms can improve treatment outcomes. This study investigates the potential of the potassium KCNQ (Kv7) channel opener ezogabine to modulate the resting-state functional connectivity (RSFC) of the brain's reward circuitry and alleviate depressive symptoms, including anhedonia, a core feature of MDD.

METHODS: A double-blind, randomized, placebo-controlled clinical trial in individuals aged 18 to 65 with MDD compared daily dosing with ezogabine (n=19) to placebo (n=21) for five weeks. Functional magnetic resonance imaging (fMRI) assessed RSFC of the brain's key reward regions (ventral caudate, nucleus accumbens) at baseline and post-treatment. Clinical symptoms were measured using the Snaith-Hamilton Pleasure Scale (SHAPS), Montgomery-Åsberg Depression Rating Scale (MADRS), and other clinical symptom scales.

RESULTS: Ezogabine significantly reduced RSFC between the reward seeds and the posterior cingulate cortex (PCC)/precuneus compared to placebo, which was associated with a reduction in depression severity. Improvements in anhedonia (SHAPS) and depressive symptoms (MADRS) with ezogabine compared to placebo were also associated with decreased connectivity between the reward seeds and mid/posterior cingulate regions (MCC, PCC, precuneus).

CONCLUSIONS: The findings suggest that ezogabine's antidepressant effects are mediated through modulation of striatal-mid/posterior cingulate connectivity, indicating a potential therapeutic mechanism for KCNQ-targeted drugs for MDD and anhedonia. Future studies should validate these results in larger trials.

CLINICALTRIALS: gov identifier: NCT03043560.

PMID:40049579 | DOI:10.1016/j.biopsych.2025.02.897

Neuroimage. 2025 Mar 4:121119. doi: 10.1016/j.neuroimage.2025.121119. Online ahead of print.

ABSTRACT

The development of the human brain is a complex, lifelong process during which collective behaviors of neurons exhibit self-organizing dynamics. Metastable states play a crucial role in understanding the complex dynamical mechanisms of the brain, and analyzing them helps to reveal the mechanisms of functional changes in the brain throughout development and aging. Specifically, global metastable state provides a overall perspective on the flexibility of brain reorganization, while the evolution trajectories of transient functional patterns capture detailed changes in brain activity. The leading eigenvector dynamics analysis (LEiDA) method significantly reduces the dimensionality of data and is widely used to capture the temporal trajectory characteristics of transient functional patterns, i.e., metastable brain states. However, LEiDA's linear dimensionality reduction of high-dimensional raw brain data may overlook non-linear information and lose some relationships between features. We developed a framework based on Phase Coherence Graph Autoencoder (PCGAE) that employs graph autoencoders (GAE) for non-linear dimensionality reduction of phase coherence matrices. This approach clusters to identify more distinct metastable brain states and is applied to the analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data across the human lifespan. This paper investigates age-related differences and continuity changes from different perspectives: metastable state indicators and state trajectory indicators (occurrence probability, lifetime, and state transition metrics). Global metastable state shows a linear decline with age, while both linear and quadratic effects of age-related changes are observed in detailed state metastable and state trajectory indicators. Finally, the proposed feature extraction scheme demonstrates good classification performance for categorizing brain age groups. These findings can help us understand the self-organizing reorganization characteristics associated with aging and their complex dynamic changes, providing new insights into brain development throughout the entire lifespan.

PMID:40049301 | DOI:10.1016/j.neuroimage.2025.121119

PLoS One. 2025 Mar 6;20(3):e0319346. doi: 10.1371/journal.pone.0319346. eCollection 2025.

ABSTRACT

BACKGROUND: Nearest-neighbor projected-distance regression (NPDR) is a metric-based machine learning feature selection algorithm that uses distances between samples and projected differences between variables to identify variables or features that may interact to affect the prediction of complex outcomes. Typical tabular bioinformatics data consist of separate variables of interest, such as genes or proteins. In contrast, resting-state functional MRI (rs-fMRI) data are composed of time-series for brain regions of interest (ROIs) for each subject, and these within-brain time-series are typically transformed into correlations between pairs of ROIs. These pairs of variables of interest can then be used as inputs for feature selection or other machine learning methods. Straightforward feature selection would return the most significant pairs of ROIs; however, it would also be beneficial to know the importance of individual ROIs.

RESULTS: We extend NPDR to compute the importance of individual ROIs from correlation-based features. We introduce correlation-difference and centrality-based versions of NPDR. Centrality-based NPDR can be coupled with any centrality method and can be coupled with importance scores other than NPDR, such as random forest importance scores. We develop a new simulation method using random network theory to generate artificial correlation data predictors with variations in correlations that affect class prediction.

CONCLUSIONS: We compared feature selection methods based on detection of functional simulated ROIs, and we applied the new centrality NPDR approach to a resting-state fMRI study of major depressive disorder (MDD) participants and healthy controls. We determined that the areas of the brain that have the strongest network effect on MDD include the middle temporal gyrus, the inferior temporal gyrus, and the dorsal entorhinal cortex. The resulting feature selection and simulation approaches can be applied to other domains that use correlation-based features.

PMID:40048476 | DOI:10.1371/journal.pone.0319346

Front Aging Neurosci. 2025 Feb 19;17:1501082. doi: 10.3389/fnagi.2025.1501082. eCollection 2025.

ABSTRACT

BACKGROUND: Cognitive impairment is a common dysfunction following stroke, significantly affecting patients' quality of life. Studies suggest that post-stroke cognitive impairment (PSCI) may be related to neural activity in specific brain regions. However, the neural mechanisms remain to be further explored. This study aimed to investigate the alterations in brain function in patients with PSCI.

METHODS: This was a case-control study. Thirty patients with PSCI, thirty with non-PSCI (NPSCI), and thirty age- and gender-matched healthy controls (HCs) were selected in a 1:1:1 ratio. Resting-state functional magnetic resonance imaging (rs-fMRI) were acquired from all participants to study the potential neural mechanisms of PSCI patients by comparing the differences in fractional amplitude of low-frequency fluctuation (fALFF), Kendall's coefficient of concordance-regional homogeneity (KCC-ReHo), and seed-based functional connectivity (FC). Additionally, the Montreal Cognitive Assessment (MoCA) scores of PSCI patients were collected, and Pearson correlation was used to analyze the correlation between functional indicators and cognitive performance in PSCI patients.

RESULTS: fALFF analysis revealed that the PSCI group had decreased zfALFF values in the left caudate, right inferior temporal gyrus (ITG), anterior cingulate cortex (ACC), left putamen, and left superior temporal gyrus. In contrast, increased zfALFF values were observed in the right Cerebellum_6. KCC-ReHo analysis indicated that the PSCI group had decreased SzKCC-ReHo values in the right middle frontal gyrus (MFG) and left postcentral lobe, while increased SzKCC-ReHo values in the left cerebellum_ crus 1, and left cerebellum_4-5. Furthermore, seed-based FC analysis revealed decreased zFC values between brain regions in the PSCI group, especially between the angular gyrus and precuneus. Additionally, correlation analysis showed that the zfALFF value of ACC was positively correlated with MoCA scores in the PSCI group.

CONCLUSION: This study demonstrated significant changes in the spontaneous neural activity intensity, regional homogeneity, and FC of multiple cognition-related brain regions in PSCI patients, shedding light on the underlying neural mechanisms of brain function in PSCI.

PMID:40046780 | PMC:PMC11880027 | DOI:10.3389/fnagi.2025.1501082

Brain Imaging Behav. 2025 Mar 6. doi: 10.1007/s11682-025-00993-z. Online ahead of print.

ABSTRACT

Numerous previous studies have classified brain regions related to social processing into the "social brain" regions. Recent genetic studies showed that gene expression has a crucial effect on both brain functions and behavioral social performance. However, studies still lack a clear understanding of the organization of the social gene expression (SocGene) network. This study aimed to distinguish the difference between the SocGene network and the social brain network (SBN) and further explored their deficits in schizophrenia (SCZ) patients. The SocGene network was constructed by generating the gene expression maps of six social neuropeptide receptors from the Allen Human Brain Atlas. Then, we recruited a general population sample of 37 participants and a clinical sample including 26 SCZ and 25 Healthy controls (HCs) successively to construct the resting-state SocGene and SBN at the individual level. The integration (global efficiency, GE) and segregation (local efficiency, LE) of these brain networks were calculated using the graphic analysis. Results showed that the GE and LE of the SocGene network were significantly higher than those of the SBN in both two cohorts. The SCZ patients showed significantly diminished LE of the two brain networks compared to HCs, especially in the SocGene network. These findings implied that the SocGene network strengthened the integration and segregation compared to the SBN. SCZ patients mainly exhibited deficits in the segregation of these two brain networks. The current findings provide a new perspective on combining genetic expression and brain function in understanding the psychopathology of social functioning.

PMID:40045109 | DOI:10.1007/s11682-025-00993-z

Brain Dev. 2025 Mar 4;47(2):104340. doi: 10.1016/j.braindev.2025.104340. Online ahead of print.

ABSTRACT

Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by persistent inattention, hyperactivity, and/or impulsivity that significantly affects academic, occupational, and social functioning. This review summarizes key findings of structural and functional magnetic resonance imaging (MRI) studies investigating the neural underpinnings of ADHD, focusing on T1-weighted structural MRI, diffusion tensor imaging (DTI), task-based functional MRI (task fMRI), and resting-state functional MRI (rs-fMRI). T1-weighted structural MRI studies have revealed reduced gray matter volume in regions implicated in executive function, particularly the frontal cortex, basal ganglia, and cerebellum, along with evidence of delayed cortical maturation. DTI findings highlighted abnormalities in white matter integrity, particularly in the fronto-striatal-cerebellar circuits and connections between the corpus callosum and cingulum. Task fMRI studies have demonstrated reduced activation of brain networks involved in cognitive control, timing, and reward processing, including fronto-striatal and fronto-parietal networks. Furthermore, rs-fMRI research has shown altered connectivity patterns within and between key brain networks, including the default mode, fronto-parietal, and salience networks. Despite these insights, inconsistencies across studies underscore the need for larger and more standardized research efforts. Future research should employ multimodal imaging techniques and advanced analytical methods such as machine learning to better subtype ADHD and customize interventions. Moreover, establishing harmonized imaging protocols across institutions, as exemplified by innovative strategies, such as the traveling-subject method, is crucial for mitigating intersite variability. Through collaborative efforts, neuroimaging studies in ADHD are anticipated to enhance our understanding of the disorder's heterogeneity while informing the development of precise clinical diagnoses and personalized therapeutic interventions.

PMID:40043540 | DOI:10.1016/j.braindev.2025.104340

Brain Imaging Behav. 2025 Mar 5. doi: 10.1007/s11682-024-00947-x. Online ahead of print.

ABSTRACT

Alteration of functional connectivity in brain regions is one of the potential neuropathological mechanisms underlying cognitive impairment in patients with minimal hepatic encephalopathy (MHE). Artificial liver therapy has been shown to improve cognitive impairment in patients, suggesting a potential neuroprotective effect on the brain. This study investigates the impact of artificial liver therapy (AL) on cognitive impairment in patients with minimal hepatic encephalopathy (MHE) by examining alterations in brain functional connectivity. Resting-state functional magnetic resonance imaging (fMRI) data was collected from healthy controls and MHE patients before and after therapy. The MHEpost-AL group showed improved memory, reaction time, and executive function compared to the MHEpre-AL group. Functional connectivity analysis revealed increased connectivity in specific brain regions in the MHEpre-AL group compared to healthy controls, with subsequent decreased connectivity after therapy. Lower MoCA scores, higher blood ammonia levels, and lower cholinesterase levels were associated with higher functional connectivity in the MHEpre-AL group. The study suggests that artificial liver therapy improves cognitive impairment in MHE patients, with changes in blood biochemistry mediating the link between functional connectivity and cognitive function. Correcting blood biochemistry levels may reverse abnormal brain connectivity and enhance cognitive function in MHE patients.

PMID:40042700 | DOI:10.1007/s11682-024-00947-x

Hum Brain Mapp. 2025 Mar;46(4):e70163. doi: 10.1002/hbm.70163.

ABSTRACT

Movie-watching fMRI has emerged as a theoretically viable platform for studying neurobiological substrates of affective states and emotional disorders such as pathological anxiety. However, using anxiety-inducing movie clips to probe relevant states impacted by psychopathology could risk exacerbating in-scanner movement, decreasing signal quality/quantity and thus statistical power. This could be especially problematic in target populations such as children who typically move more in the scanner. Consequently, we assessed: (1) the extent to which an anxiety-inducing movie clip altered in-scanner data quality (movement, censoring, and DVARS) in a pediatric sample with and without anxiety disorders (n = 78); and (2) investigated interactions between anxiety symptoms and movie-attenuated motion in a highly powered, transdiagnostic pediatric sample (n = 2058). Our results suggest anxiogenic movie-watching in fact reduces in-scanner movement compared to resting-state, increasing the quantity/quality of data. In one measure, pathological anxiety appeared to impact movie-attenuated motion, but the effect was small. Given potential boosts to data quality, future developmental neuroimaging studies of anxiety may benefit from the use of movie paradigms.

PMID:40042099 | DOI:10.1002/hbm.70163

J Neurosci Res. 2025 Mar;103(3):e70029. doi: 10.1002/jnr.70029.

ABSTRACT

Laterality of motor deficits is a hallmark of Parkinson's disease (PD), which is strongly correlated with disease progression. The cerebellum is an important node in the motor-related network in PD. However, the role of the cerebellum in PD lateralization remains unclear. This study enrolled 48 left-dominant-affected PD patients (LPD), 60 right-dominant-affected PD patients (RPD) and 92 age- and sex-matched healthy controls (HCs). We utilized dynamic functional connectivity and co-activation pattern analysis to investigate dynamic alterations of the cerebellum between PD patients and HCs by resting-state fMRI. Pearson partial correlation was used to measure brain-clinical correlations. We revealed two states and five co-activation patterns during the scans. Compared to HCs and RPD, LPD patients more frequently displayed State II and persisted in this state for a more extended period. The mean dwell time (MDT) in State II rose from HCs to RPD and to LPD. The MDT in State II was positively correlated with sleep disturbance in LPD patients. Regarding co-activation patterns (CAPs), LPD and RPD patients were less likely to exhibit CAP2. LPD patients were less likely to demonstrate CAP1 compared to HCs. The CAP1 metrics were positively associated with motor deficits in LPD patients. These results revealed the dynamic alterations of the cerebellum in different dominant-affected PD patients, which were related to motor deficits and sleep disturbances in PD patients. Our findings suggest that the dynamic cerebellar features may be significant factors in the lateralization of PD.

PMID:40041986 | DOI:10.1002/jnr.70029

Neural Plast. 2025 Feb 25;2025:8003718. doi: 10.1155/np/8003718. eCollection 2025.

ABSTRACT

Background and Purpose: Motor impairment is a common occurrence in patients with acute basal ganglia (BG) ischemic stroke (ABGIS). However, the underlying mechanisms of poststroke motor dysfunction remain incompletely elucidated. In this study, we employed multifrequency band wavelet transform-based amplitude of low-frequency fluctuations (Wavelet-ALFFs) to investigate the alterations of spontaneous regional neural activity in patients with ABGIS. Methods: A total of 39 ABGIS patients with motor dysfunction and 45 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging. Wavelet-ALFF values were calculated in the conventional frequency band (0.01-0.08 Hz), slow-5 frequency band (0.01-0.027 Hz), and slow-4 frequency band (0.027-0.073 Hz). A two-sample t-test was performed to compare the Wavelet-ALFF values between the two groups with sex as a covariate and Gaussian random field (GRF) theory (voxel p < 0.001, cluster p < 0.05, two-tailed) was used for the multiple corrections. Furthermore, spearman correlation analysis was performed to assess the relationship between alterations in regional neural activity between Fugl-Meyer Assessment (FMA) and National Institutes of Health Stroke Scale (NIHSS) scores. Results: In comparison to HCs, patients with ABGIS showed significantly increased Wavelet-ALFF in the left middle temporal gyrus (MTG) and decreased Wavelet-ALFF in the right inferior frontal operculum (IFO) across all three frequency bands (conventional, slow-4, and slow-5). In the left superior occipital gyrus (SOG), Wavelet-ALFF was decreased in the conventional frequency band but increased in the slow-4 frequency band. Additionally, patients with ABGIS demonstrated reduced Wavelet-ALFF in the right superior temporal gyrus (STG) in the conventional and slow-4 frequency bands. In the slow-5 frequency band, increased Wavelet-ALFF was observed in the left calcarine cortex (CC), left middle frontal gyrus (MFG), left supramarginal gyrus (SMG), and left postcentral gyrus (PCG), while decreased Wavelet-ALFF was noted in the right precuneus (PCu). Correlation analysis revealed that increased Wavelet-ALFF in the left CC in the slow-5 frequency band was positively correlated with the FMA score. No other correlations were detected in the conventional and slow-4 frequency bands. Conclusions: The altered spontaneous neural activity was frequency-specific in patients with ABGIS, and the slow-5 frequency band exhibited better results. Furthermore, the relationship between spontaneous brain activity and clinical characteristics highlighted patterns of neural alterations associated with motor dysfunction. These findings may provide novel insights into the neural mechanisms underlying motor dysfunction in ABGIS.

PMID:40041455 | PMC:PMC11879565 | DOI:10.1155/np/8003718

Imaging Neurosci (Camb). 2024 Nov 18;2:1-18. doi: 10.1162/imag_a_00373. eCollection 2024 Nov 1.

ABSTRACT

Premature birth affects brain maturation, illustrated by altered brain functional connectivity at term equivalent age (TEA) and alters neurobehavioral outcome. To correct early developmental differences and improve neurological outcome, music during the neonatal intensive care unit (NICU) stay has been proposed as an auditory enrichment with modulatory effects on functional and structural brain development, but longitudinal effects of such interventions have not been studied so far. We longitudinally investigated resting-state functional connectivity (RS-FC) maturation in preterm infants (n = 43). Data-driven Independent Component Analyses (ICA) were performed on scans obtained at 33- and 40-week gestational age (GA), determining the presence of distinct resting-state networks (RSNs). Connectome analysis "accordance measure" quantitively examined the RS-FC both at 33- and 40-week GA. Further comparing the internetwork RS-FC at 33- and 40-week GA provided a circuitry of interest (COI) for significant maturational changes in which the effects on the RS-FC of a music intervention were tested. The connectome analyses resulted in a COI of RS-FC connections significantly maturing from 33 to 40 weeks GA, namely between the thalamic/brainstem and prefrontal-limbic, salience, sensorimotor, auditory, and prefrontal cortical networks; between the prefrontal-limbic and cerebellar, visual and left hemispheric precuneus networks; between the salience and visual, and cerebellar networks; and between the sensorimotor and auditory, and posterior cingulate/precuneus networks. The infants exposed to music exhibited significantly increased maturation in RS-FC between the thalamic/brainstem and salience networks, compared with controls. This study exemplifies that preterm infant RS-FC maturation is modulated through NICU music exposure, highlighting the importance of environmental enrichment for neurodevelopment in premature newborns.

PMID:40041298 | PMC:PMC11873764 | DOI:10.1162/imag_a_00373