Most recent paper

Sci Rep. 2025 Mar 20;15(1):9636. doi: 10.1038/s41598-025-91465-3.

ABSTRACT

Cocaine-use disorder (CUD) affects both structure and function of the brain. A triple network model of large-scale brain networks has been useful for identifying aberrant resting-state functional connectivity (rsFC) associated with mental health disorders including addiction. The present study investigated differences between people with CUD vs. controls (CONs) and whether putative differences were associated with drug-use outcomes. Participants with CUD (n = 38) and CONs (n = 34) completed a resting functional magnetic resonance imaging (fMRI) scan. Participants with CUD completed several mental health measures and participated in an 8-week, drug-use outcomes phase. A classification framework based on the triple network model was built, and triple networks (salience [SN], executive control [ECN], default mode [DMN]) and subcortical (striatum [ST], hippocampus/amygdala) regions were identified with the algorithm of group-information-guided independent components analysis (GIG-ICA) and subsequent support-vector machines. This classifier achieved 77.1% accuracy, 73.8% sensitivity, and 80.0% specificity, with an area under the curve of 0.87 for distinguishing CUD vs. CON. The two groups differed in SN-anterior DMN (aDMN) and ECN-aDMN rsFC, with the CUD group exhibiting stronger rsFC compared to CONs. They also differed in rsFC between several subcortical and triple networks, with CUD generally showing a lack of rsFC. Within the CUD group, ST-aDMN and ST-rECN rsFC were associated with differential drug-use outcomes. Exploratory results suggested SN-aDMN rsFC was associated with anxiety symptoms. These results add to the growing literature showing aberrant triple network and subcortical rsFC associated with substance use disorders. They suggest the aDMN specifically may underlie important differences between people with CUD and CONs and may be a potential target for intervention.

PMID:40113802 | DOI:10.1038/s41598-025-91465-3

Brain Res. 2025 Mar 18:149586. doi: 10.1016/j.brainres.2025.149586. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate alterations in brain activity in patients with Type 2 Diabetes and explore the relationship between altered regions and neuropsychological performances.

METHODS: A total of 36 patients with Type 2 Diabetes and 40 age- and education-matched healthy controls were recruited for this case-control study. All participants underwent resting-state functional magnetic resonance imaging (Resting-state fMRI) and neuropsychological tests. The neuropsychological scales included the Auditory Verbal Learning Test (AVLT), Shape Trajectory Test B (STT-B), Hamilton Anxiety Scale (HAMA), Hamilton Depression Scale (HAMD), and Boston Naming Test (BNT), Symbol Digit Modality Test (SDMT), Regional homogeneity (ReHo) and the amplitude of low-frequency fluctuations (ALFF) were used to assess differences in spontaneous regional brain activity. For functional connectivity (FC) analyses, the differences identified among the groups were selected as seed regions. Then, the correlations between neuropsychological scale scores (AVLT, HAMA, HAMD, STT-B, BNT, and SDMT) and ALFF/ReHo values were specifically analyzed in the focal regions that exhibited significant alterations between the T2DM and control groups, as detailed in Tables 2 and 3.

RESULTS: Patients with Type 2 Diabetes exhibited significantly higher ALFF values in the superior lobe of the cerebellum, specifically in the left cerebellar crus I (Cerebellum_Crus I_L), left cerebellar lobule VI (Cerebellum_6_L), and left cerebellar lobule IV-V (Cerebellum_4_5_L). Additionally, they exhibited elevated ReHo values in the Cerebellum_Crus I_L and Cerebellum_6_L. The findings were statistically significant with a family-wise error-corrected, cluster-level p-value of less than 0.05. However, the FC analysis was not significant. AVLT scores were significantly lower in the diabetes group. The correlation analysis demonstrated a negative association between ALFF values of the Cerebellum_6_L and AVLT scores (R2 = 0.1375, P < 0.001). The ReHo values within the Cerebellum_6_L also exhibited a negative association with AVLT scores (R2 = 0.0937, P = 0.007).

CONCLUSION: Patients with Type 2 Diabetes showed abnormal neural activities in diverse cerebellar regions mainly related to cognitive functions. This provides supplementary information to deepen our insight into the neural mechanisms by which Type 2 Diabetes affects the functional activity of the brain's posterior circulation, as well as the potential association of these changes with cognitive impairment.

PMID:40113193 | DOI:10.1016/j.brainres.2025.149586

Brain Res. 2025 Mar 18:149576. doi: 10.1016/j.brainres.2025.149576. Online ahead of print.

ABSTRACT

This study investigates the impact of basal ganglia network asymmetry on motor function in Parkinson's Disease (PD). Using resting-state functional magnetic resonance imaging (rs-fMRI), functional connectivity and network asymmetry were analyzed in 15 non-demented PD patients and 15 healthy controls. Sixteen basal ganglia substructures, including the caudate, putamen, and globus pallidus, were selected for a unified analysis of variance framework to evaluate inter-hemispheric connectivity differences. After spatial preprocessing, regions of interest were defined, and time-series data were extracted for functional connectivity and network asymmetry analysis. The results revealed significant alterations in the functional connectivity of the caudate, putamen, and nucleus accumbens (NAc) in PD patients. Notably, the absence of intra-network asymmetry in the left NAc and bilateral amygdala correlated with motor dysfunction, likely due to overactivity of the inhibitory indirect pathway. Furthermore, pronounced asymmetry in the left putamen and right frontal gyrus suggested a compensatory neural mechanism supporting motor performance. These findings highlight the critical role of basal ganglia network asymmetry in the pathophysiology of PD. The identified asymmetry characteristics may serve as potential biomarkers for early diagnosis and disease progression monitoring, offering new directions for targeted therapeutic interventions.

PMID:40113192 | DOI:10.1016/j.brainres.2025.149576

Dev Cogn Neurosci. 2025 Mar 12;73:101551. doi: 10.1016/j.dcn.2025.101551. Online ahead of print.

ABSTRACT

The human cerebral cortex contains groups of areas that support sensory, motor, cognitive, and affective functions, often categorized into functional networks. These networks show stronger internal and weaker external functional connectivity (FC), with FC profiles more similar within the same network. Previous studies have shown these networks develop from nascent forms before birth to their mature, adult-like structures in childhood. However, these analyses often rely on adult functional network definitions. This study assesses the potential misidentification of infant functional networks when using adult models and explores the consequences and possible solutions to this problem. Our findings suggest that although adult networks only marginally describe infant FC organization better than chance, misidentification is primarily driven by specific areas. Restricting functional networks to areas with adult-like network clustering revealed consistent within-network FC across scans and throughout development. These areas are also near locations with low network identity variability. Our results highlight the implications of using adult networks for infants and offer guidance for selecting and utilizing functional network models based on research questions and scenarios.

PMID:40112680 | DOI:10.1016/j.dcn.2025.101551

PLoS One. 2025 Mar 20;20(3):e0319925. doi: 10.1371/journal.pone.0319925. eCollection 2025.

ABSTRACT

The present functional magnetic resonance imaging (fMRI) study investigated neural correlates of switching between task-processing and periods of rest in a conventional ON-OFF block-design in patients with auditory verbal hallucinations (AVHs) and healthy controls. It has been proposed that auditory hallucinations are a failure of top-down control of bottom-up perceptual processes which could be due to aberrant up- and down regulation of brain networks. A version of the Eriksen Flanker task was used to assess cognitive flexibility and conflict control. BOLD fMRI with alternating blocks of task engagement and rest was collected using a 3T MR scanner. The objective of the study was to explore how patients would dynamically modulate relevant brain networks in response to shifting environmental demands, while transitioning from a resting state to active task-processing. Analysis of performance data found significant behavioral effects between the groups, where AVH patients performed the Flanker task significantly less accurately and with longer reaction times (RTs) than the healthy control group, indicating that AVH patients displayed reduced top-down guided conflict control. A network connectivity analysis of the fMRI data showed that both groups recruited similar networks related to task-present and task-absent conditions. However, the controls displayed increased network variability across task-present and task-absent conditions. This would indicate that the controls were better at switching between networks and conditions when demands changed from task-present to task-absent, with the consequence that they would perform the Flanker task better than the AVH patients.

PMID:40112006 | DOI:10.1371/journal.pone.0319925

Alzheimers Dement. 2025 Mar;21(3):e70061. doi: 10.1002/alz.70061.

ABSTRACT

INTRODUCTION: Autosomal dominant Alzheimer's disease (ADAD) through genetic mutations can result in near complete expression of the disease. Tracking AD pathology development in an ADAD cohort of Presenilin-1 (PSEN1) E280A carriers' mutation has allowed us to observe incipient tau tangles accumulation as early as 6 years prior to symptom onset.

METHODS: Resting-state functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) scans were acquired in a group of PSEN1 carriers (n = 32) and non-carrier family members (n = 35). We applied connectome-based predictive modeling (CPM) to examine the relationship between the participant's functional connectome and their respective tau/amyloid-β levels and cognitive scores (word list recall).

RESULTS: CPM models strongly predicted tau concentrations and cognitive scores within the carrier group. The connectivity patterns between the temporal cortex, default mode network, and other memory networks were the most informative of tau burden.

DISCUSSION: These results indicate that resting-state functional magnetic resonance imaging (fMRI) methods can complement PET methods in early detection and monitoring of disease progression in ADAD.

HIGHLIGHTS: Connectivity-based predictive modeling of tau and amyloid-β in ADAD carriers. Strong predictions for tau deposition; weaker predictions for amyloid-β. Cognitive scores for memory and mental state are predicted strongly. Connectivity between IPL, DAN, DMN, temporal cortex most predictive.

PMID:40110659 | DOI:10.1002/alz.70061

Front Neurosci. 2025 Mar 5;19:1444999. doi: 10.3389/fnins.2025.1444999. eCollection 2025.

ABSTRACT

INTRODUCTION: Brain dynamics offer a more direct insight into brain function than network structure, providing a profound understanding of dysregulation and control mechanisms within intricate brain systems. This study investigates the dynamics of functional brain networks in major depressive disorder (MDD) patients to decipher the mechanisms underlying brain dysfunction during depression and assess the impact of repetitive transcranial magnetic stimulation (rTMS) intervention.

METHODS: We employed energy landscape analysis of functional magnetic resonance imaging (fMRI) data to examine the dynamics of functional brain networks in MDD patients. The analysis focused on key dynamical indicators of the default mode network (DMN), the salience network (SN), and the central execution network (CEN). The effects of rTMS intervention on these networks were also evaluated.

RESULTS: Our findings revealed notable dynamical alterations in the pDMN, the vDMN, and the aSN, suggesting their potential as diagnostic and therapeutic markers. Particularly striking was the altered activity observed in the dDMN in the MDD group, indicative of patterns associated with depressive rumination. Notably, rTMS intervention partially reverses the identified dynamical alterations.

DISCUSSION: Our results shed light on the intrinsic dysfunction mechanisms of MDD from a dynamic standpoint and highlight the effects of rTMS intervention. The identified alterations in brain network dynamics provide promising analytical markers for the diagnosis and treatment of MDD. Future studies should further explore the clinical applications of these markers and the comprehensive dynamical effects of rTMS intervention.

PMID:40109660 | PMC:PMC11920141 | DOI:10.3389/fnins.2025.1444999

Int J Radiat Oncol Biol Phys. 2025 Mar 17:S0360-3016(25)00247-0. doi: 10.1016/j.ijrobp.2025.03.017. Online ahead of print.

ABSTRACT

BACKGROUND: This prospective observational study employed resting-state functional MRI (rs-fMRI) to investigate network-level disturbances associated with neurocognitive function (NCF) changes in patients with gliomas following partial-brain radiation therapy (RT).

METHODS: Adult post-operative patients with either IDH-wildtype or IDH-mutant gliomas underwent computerized NCF testing and rs-fMRI at baseline and 6 months post-RT. rs-fMRI data were assessed using seed-based functional connectivity (FC). NCF changes were quantified by the percent change in age-normalized composite scores from baseline (ΔNCFcomp). Connectivity-regression analysis assessed the association between network FC changes and NCF changes, using a split-sample approach with a 26-patient training set and a 6-patient validation set, iterated 200 times. Permutation tests evaluated the significance of network selection.

RESULTS: Between September 2020 and December 2023, 43 patients were enrolled, with 32 completing both baseline and follow-up evaluations. The mean ΔNCFcomp was 2.9% (SD: 13.7%), with 38% experiencing a decline. Patients with IDH-mutant glioma had similar NCF changes compared to those with IDH-wildtype glioma. Intra-hemispheric FC was similar between ipsilateral and contralateral hemispheres for 91% patients at baseline, and 69% had similar intra-hemispheric FC change post-treatment. FC changes accounted for a moderate fraction of variance in NCF changes (mean R2: 0.301, SD: 0.249), with intra-network FC of the Parietal Memory Network (PMN-PMN, p=0.001) and inter-network FC between the PMN and the Visual Network (PMN-VN, p=0.002) as the most significant factors. Similar findings were obtained by sensitivity analyses using only the FC data from the hemisphere contralateral to the tumor.

CONCLUSIONS: Post-RT rs-fMRI changes significantly reflected NCF decline, highlighting rs-fMRI as a promising imaging biomarker for neurocognitive decline after RT.

PMID:40107623 | DOI:10.1016/j.ijrobp.2025.03.017

Neurologist. 2025 Mar 19. doi: 10.1097/NRL.0000000000000622. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore the effects of Intermittent Theta Burst Stimulation (iTBS) on the posterior inferior frontal gyrus of the left hemisphere on the expression function of patients with aphasia after stroke, and to explore the specific mechanism of fractional amplitude of low-frequency fluctuation (fALFF) analysis and degree centrality (DC) analysis of resting-state functional MRI.

METHODS: According to the inclusion and exclusion criteria, 40 patients with poststroke aphasia were randomized into a treatment group (iTBS group) and a control group (S-iTBS group). Patients in the iTBS group received iTBS +speech training, and patients in the S-iTBS group received sham iTBS + speech training. The Western aphasia test (Chinese version) was used to assess spontaneous language, naming, retelling, and aphasia quotient before and after treatment; resting-state fMRI scans were performed before and after treatment, and the scanned image data were analyzed to explore specific activated or suppressed brain regions.

RESULTS: Compared with before and after treatment, the scores of spontaneous language, naming, retelling, and aphasia quotient of the patients in iTBS group improved significantly, and the spontaneous language, naming, retelling, and aphasia quotient of the patients in S-iTBS group also improved. After the treatment, the scores of naming, retelling and aphasia quotient of the patients in the iTBS group improved significantly compared with that of the patients in the S-iTBS group. The resting-state fMRI results of the 2 groups before and after treatment were fALFF analysis found that the fALFF value increased in multiple brain regions in the left frontal and temporal lobes of the patients in iTBS group. Meanwhile, DC analysis also found increased DC values in multiple frontotemporal brain regions of the left hemisphere of patients in the iTBS group, indicating that the improved activation of the above brain regions of the patients in the iTBS group was significantly compared with that of the patients in the S-iTBS group.

CONCLUSIONS: iTBS combined with conventional speech training significantly improved the expression function of patients with aphasia after stroke. After iTBS action on the left hemisphere, increased activation of multiple brain regions in the left hemisphere may be one of the important mechanisms by which iTBS improves expression function in poststroke aphasia patients.

PMID:40104992 | DOI:10.1097/NRL.0000000000000622

Int J Ophthalmol. 2025 Mar 18;18(3):487-495. doi: 10.18240/ijo.2025.03.16. eCollection 2025.

ABSTRACT

AIM: To investigate changes in local brain activity after laser assisted in situ keratomileusis (LASIK) in myopia patients, and further explore whether post-LASIK (POL) patients and healthy controls (HCs) can be distinguished by differences in dynamic amplitude of low-frequency fluctuations (dALFF) in specific brain regions.

METHODS: The resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 15 myopic patients who underwent LASIK and 15 matched healthy controls. This method was selected to calculate the corresponding dALFF values of each participant, to compare dALFF between the groups and to determine whether dALFF distinguishes reliably between myopic patients after LASIK and HCs using the linear support vector machine (SVM) permutation test (5000 repetitions).

RESULTS: dALFF was lower in POL than in HCs at the right precentral gyrus and right insula. Classification accuracy of the SVM was 89.1% (P<0.001).

CONCLUSION: The activity of spontaneous neurons in the right precentral gyrus and right insula of myopic patients change significantly after LASIK. SVM can correctly classify POL patients and HCs based on dALFF differences.

PMID:40103964 | PMC:PMC11865659 | DOI:10.18240/ijo.2025.03.16

Int J Ophthalmol. 2025 Mar 18;18(3):469-477. doi: 10.18240/ijo.2025.03.14. eCollection 2025.

ABSTRACT

AIM: To assess the alterations in the resting-state function connections between the two cerebral hemispheres in patients with optic neuritis (ON) and healthy controls (HCs).

METHODS: A total of 12 ON patients (six males and six females) and 12 HCs (six males and six females) who were highly matched for sex, age, and educational level were recruited. They underwent functional magnetic resonance imaging (fMRI), testing and brain activities were assessed using the degree centrality (DC) method. Correlation analysis between the mean DC values in specific brain areas and behavior performances was analyzed as well. Linear correlations between A anxiety scale (AS) and depression scale (DS) values and DC values in brain regions of patients with ON were also analyzed.

RESULTS: The areas that showed a higher DC value in ON patients were the right angular gyrus and bilateral precuneus, while the left insula and left superior temporal gyrus (LSTG) were regions that presented a lower DC value in ON patients. A receiver operating characteristic (ROC) curve analysis confirmed the accuracy of the area under the curve (AUC) assessment. Linear analysis showed anxiety scale (AS) and depression scale (DS) values in the left insula were both negatively correlated with DC values, while best corrected visual acuity logMAR-R (BCVA logMAR-R) showed a negative correlation with DC in the LSTG.

CONCLUSION: The study explores altered brain activities of specific regions in patients with ON. The results provide clues for revealing the underlying mechanism of ON development.

PMID:40103952 | PMC:PMC11865650 | DOI:10.18240/ijo.2025.03.14

Cereb Cortex. 2025 Mar 6;35(3):bhaf063. doi: 10.1093/cercor/bhaf063.

ABSTRACT

Accumulating evidence suggests that individuals with high sensory processing sensitivity often experience sensory overload and have difficulty sustaining attention, which can particularly resemble attention deficit symptoms of attention-deficit/hyperactivity disorder. However, due to the lack of understanding about the potential neural pathways involved in those processes, a comprehensive view of how sensory processing sensitivity and attention deficit are related is generally limited. Here, we quantified the sensory processing sensitivity and attention deficit using the Highly Sensitive Person Scale and the Adult Attention-deficit/Hyperactivity Disorder Self-Report Scale, respectively, to investigate the association between sensory processing sensitivity and attention deficit and further identify the corresponding neural substrates via the use of resting-state functional Magnetic Resonance Imaging (fMRI) analyses. On the behavioral level, the results indicated a significantly positive correlation between sensory processing sensitivity and attention deficit traits, while on the neural level, the sensory processing sensitivity score was positively correlated with functional connectivity between the rostral hippocampus and inferior parietal lobule, which is the core regions of the attention network. Mediation analysis revealed that hippocampus-Inferior Parietal Lobule (IPL) connectivity can further influence attention deficit through a mediating role of sensory processing sensitivity. Overall, these findings suggest that enhanced functional coupling between the hippocampus and attention network regions may heighten sensitivity to environmental stimuli, leading to increased distractibility and potentially contributing to attention deficit.

PMID:40103362 | DOI:10.1093/cercor/bhaf063

Neuroimage. 2025 Mar 16:121155. doi: 10.1016/j.neuroimage.2025.121155. Online ahead of print.

ABSTRACT

Older adults exhibit larger individual differences in walking ability and cognitive function than young adults. Characterizing intrinsic brain connectivity differences in older adults across a wide walking performance spectrum may provide insight into the mechanisms of functional decline in some older adults and resilience in others. Thus, the objectives of this study were to: (1) determine whether young adults and high- and low-functioning older adults show group differences in brain network segregation, and (2) determine whether network segregation is associated with working memory and walking function in these groups. The analysis included 21 young adults and 81 older adults. Older adults were further categorized according to their physical function using a standardized assessment; 54 older adults had low physical function while 27 were considered high functioning. Structural and functional resting state magnetic resonance images were collected using a Siemens Prisma 3T scanner. Working memory was assessed with the NIH Toolbox list sorting test. Walking speed was assessed with a 400 m walk test at participants' self-selected speed. We found that network segregation in mobility-related networks (sensorimotor, vestibular) was higher in older adults with higher physical function compared to older adults with lower physical function. There were no group differences in laterality effects on network segregation. We found multivariate associations between working memory and walking speed with network segregation scores. The interaction of left sensorimotor network segregation and age groups was associated with higher working memory function. Higher left sensorimotor, left vestibular, right anterior cingulate cortex, and interaction of left anterior cingulate cortex network segregation and age groups were associated with faster walking speed. These results are unique and significant because they demonstrate higher network segregation is largely related to higher physical function and not age alone.

PMID:40101865 | DOI:10.1016/j.neuroimage.2025.121155

PLoS One. 2025 Mar 18;20(3):e0319746. doi: 10.1371/journal.pone.0319746. eCollection 2025.

ABSTRACT

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

PMID:40100891 | DOI:10.1371/journal.pone.0319746

Front Aging Neurosci. 2025 Mar 3;17:1499262. doi: 10.3389/fnagi.2025.1499262. eCollection 2025.

ABSTRACT

BACKGROUND: Chronic pain is a common non-motor symptom of Parkinson's disease (PD) that significantly impacts patients' quality of life, but its neural mechanisms remain poorly understood. This study investigated changes in spontaneous neuronal activity and functional connectivity (FC) associated with chronic pain in PD patients.

METHODS: The study included 41 PD patients with chronic pain (PDP), 41 PD patients without pain (nPDP), and 29 healthy controls. Pain severity was assessed using the visual analog scale (VAS). Resting-state fMRI images were used to measure the amplitude of low-frequency fluctuations (ALFF) as an indicator of regional brain activity. Subsequently, FC analysis was performed to evaluate synchronization between ALFF-identified regions and the entire brain.

RESULTS: Compared to nPDP patients, PDP patients exhibited decreased ALFF in the right putamen, and increased ALFF in motor regions, including the right superior frontal gyrus/supplementary motor area and the left paracentral lobule/primary motor cortex. Additionally, PDP patients exhibited diminished right putamen-based FC in the midbrain, anterior cingulate cortex, orbitofrontal cortex, middle frontal gyrus, middle temporal gyrus, and posterior cerebellar lobe. The correlation analysis revealed that ALFF values in the right putamen were negatively associated with VAS scores in PDP patients.

CONCLUSION: This study demonstrates that chronic pain in PD is associated with reduced ALFF in the putamen and disrupted FC with brain regions involved in pain perception and modulation, highlighting the critical role of dopaminergic degeneration in the development and maintenance of pain in PD.

PMID:40099248 | PMC:PMC11911387 | DOI:10.3389/fnagi.2025.1499262

Ann Gen Psychiatry. 2025 Mar 17;24(1):14. doi: 10.1186/s12991-025-00553-1.

ABSTRACT

BACKGROUND: The growing popularity of internet gaming among adolescents and young adults has driven an increase in both casual and excessive gaming behavior. Nevertheless, it remains unclear how progressive increases in internet gaming engagement led to changes within and between brain networks. This study aims to investigate these connectivity alterations across varying levels of gaming involvement.

METHODS: In this cross-sectional study, 231 participants were recruited and classified into three groups according to Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for Internet Gaming Disorder (IGD): IGD group, highly engaged gaming(HEG) group, and lowly engaged gaming (LEG) group. Resting-state fMRI data from 217 participants (143 males, 74 females) were included in the final analysis. Independent component analysis was used to examine differences in intra- and inter-network functional connectivity (FC)across the three groups.

RESULTS: No significant differences were found in intra-network FC across the three groups. However, significant inter-network differences between the dorsal attention network(dAN)and the visual network (VN) among the three groups were observed. The HEG group exhibited significantly higher dAN-VN functional network connectivity (FNC) compared to the LEG group. Linear correlation analyses showed no significant correlation between the dAN-VN FNC values and IGD-20T scores.

CONCLUSION: Throughout the development of IGD, increasing levels of engagement are associated with a rise and subsequent decline in FNC of DAN-VN. This pattern may reflect top-down attentional regulation in the early stages of addiction, followed by attentional bias as addiction progresses.

PMID:40098002 | DOI:10.1186/s12991-025-00553-1

Transl Psychiatry. 2025 Mar 17;15(1):86. doi: 10.1038/s41398-025-03265-y.

ABSTRACT

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant functional connectivity in large-scale brain networks. However, it is unclear how the network dysfunction is characterized by imbalance or derangement of network modular interaction in MDD patients and whether this disruption is associated with gene expression profiles. We included 262 MDD patients and 297 healthy controls, embarking on a comprehensive analysis of intrinsic brain activity using resting-state functional magnetic resonance imaging (R-fMRI). We assessed brain network integration by calculating the Participation Coefficient (PC) and conducted an analysis of intra- and inter-modular connections to reveal the dysconnectivity patterns underlying abnormal PC manifestations. Besides, we explored the potential relationship between the above graph theory measures and clinical symptoms severity in MDD. Finally, we sought to uncover the association between aberrant graph theory measures and postmortem gene expression data sourced from the Allen Human Brain Atlas (AHBA). Relative to the controls, alterations in systemic functional connectivity were observed in MDD patients. Specifically, increased PC within the bilateral visual network (VIS) was found, accompanied by elevated functional connectivities (FCs) between VIS and both higher-order networks and Limbic network (Limbic), contrasted by diminished FCs within the VIS and between the VIS and the sensorimotor network (SMN). The clinical correlations indicated positive associations between inter-VIS FCs and depression symptom, whereas negative correlations were noted between intra-VIS FCs with depression symptom and cognitive disfunction. The transcriptional profiles explained 21-23.5% variance of the altered brain network system dysconnectivity pattern, with the most correlated genes enriched in trans-synaptic signaling and ion transport regulation. These results highlight the modular connectome dysfunctions characteristic of MDD and its linkage with gene expression profiles and clinical symptomatology, providing insight into the neurobiological underpinnings and holding potential implications for clinical management and therapeutic interventions in MDD.

PMID:40097427 | DOI:10.1038/s41398-025-03265-y

Cold Spring Harb Perspect Med. 2025 Mar 17:a041841. doi: 10.1101/cshperspect.a041841. Online ahead of print.

ABSTRACT

Functional neuroimaging techniques are increasingly being used to advance the diagnosis and management of Parkinson's disease (PD). Methods such as [18F]-fluorodeoxyglucose positron emission tomography (FDG PET), resting-state functional magnetic resonance imaging (rs-fMRI), arterial spin labeling (ASL) MRI, and single-photon emission computed tomography (SPECT) enable the identification of disease-specific patterns like the PD-related pattern (PDRP) and PD cognition-related pattern (PDCP), which correlate with motor and cognitive symptoms. Network analysis using graph theory further elucidates the alterations in brain connectivity associated with PD, providing insights into disease progression and response to treatment. Moreover, these neuroimaging patterns assist in distinguishing PD from atypical parkinsonian syndromes, enhancing diagnostic accuracy. Understanding the impact of genetic variants like LRRK2 and GBA1 on functional connectivity highlights the potential for precision medicine in PD. As neuroimaging technologies evolve, their integration into clinical practice will be pivotal in the personalized management of PD, offering improved diagnostic precision and targeted therapeutic interventions.

PMID:40097189 | DOI:10.1101/cshperspect.a041841

Hum Brain Mapp. 2025 Apr 1;46(5):e70193. doi: 10.1002/hbm.70193.

ABSTRACT

Delineating the functional organization of mesoscale cortical columnar structure is essential for understanding brain function. We have previously demonstrated a high spatial correspondence between BOLD fMRI and LFP responses to tactile stimuli in the primary somatosensory cortex area 3b of nonhuman primates. This study aims to explore how 2D spatial profiles of the functional column vary across cortical layers (defined by three cortical depths) in both tactile stimulation and resting states using fMRI. At 9.4 T, we acquired submillimeter-resolution oblique fMRI data from cortical areas 3b and 1 of anesthetized squirrel monkeys and obtained fMRI signals from three cortical layers. In both areas 3b and 1, the tactile stimulus-evoked fMRI activation foci were fitted with point spread functions (PSFs), from which shape parameters, including full width at half maximum (FWHM), were derived. Seed-based resting-state fMRI data analysis was then performed to measure the spatial profiles of resting-state connectivity within and between areas 3b and 1. We found that the tactile-evoked fMRI response and local resting-state functional connectivity were elongated at the superficial layer, with the major axes oriented in lateral to medial (from digit 1 to digit 5) direction. This elongation was significantly reduced in the deeper (middle and bottom) layers. To assess the robustness of these spatial profiles in distinguishing cortical layers, shape parameters describing the spatial extents of activation and resting-state connectivity profiles were used to classify the layers via self-organizing maps (SOM). A minimal overall classification error (~13%) was achieved, effectively classifying the layers into two groups: the superficial layer exhibited distinct features from the two deeper layers in the rsfMRI data. Our results support distinct 2D spatial profiles for superficial versus deeper cortical layers and reveal similarities between stimulus-evoked and resting-state configurations.

PMID:40095731 | DOI:10.1002/hbm.70193

J Alzheimers Dis. 2025 Mar 17:13872877251317489. doi: 10.1177/13872877251317489. Online ahead of print.

ABSTRACT

BackgroundGenetic susceptibility is a primary factor contributing to etiology of late-onset Alzheimer's disease (LOAD). The exact mechanisms and timeline through which APOE/PICALM influence brain functions and contribute to LOAD remain unidentified. This includes their effects on individuals prior to the development of the disease.ObjectiveTo investigate the effects of APOE and PICALM risk genes on brain health and function in non-demented individuals. This study aims to differentiate the combined risk effects of both genes from the risk associated solely with APOE, and to examine how PICALM alleles influence the risk linked to APOE.MethodsAPOE/PICALM alleles were assessed to determine the genetic risk of LOAD in 79 healthy, middle-aged participants who underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. The resting-state signal was analyzed to estimate relative spectral power, complexity (Higuchi's algorithm), and connectivity (coherence in EEG and independent component analysis-based connectivity in fMRI).ResultsThe main findings indicated that individuals at risk for LOAD exhibited reduced signal complexity and the so-called "slowing of EEG" which are well-known EEG markers of Alzheimer's disease. Additionally, these individuals showed altered functional connectivity in fMRI (within attention-related areas).ConclusionsRisk alleles of APOE/PICALM may affect brain integrity and function prior to the clinical onset of the disease.

PMID:40095677 | DOI:10.1177/13872877251317489