Most recent paper

Commun Biol. 2025 Mar 21;8(1):473. doi: 10.1038/s42003-025-07928-w.

ABSTRACT

Head motion during magnetic resonance imaging (MRI) examinations of patients with autism spectrum disorder (ASD) can influence the identification of brain differences as well as early diagnosis and precise MRI-based interventions for ASD. This study aims to address head motion issues in resting-state functional MRI (rs-fMRI) data by comparing various correction methods. Specifically, we evaluate the independent component analysis-based automatic removal of motion artifacts (ICA-AROMA) against traditional preprocessing pipelines, including head motion realignment parameters and global signal regression (GSR). Our dataset consisted of 306 participants, including 148 individuals with ASD and 158 participants with typical development (TD). We find that ICA-AROMA, particularly when combined with GSR and physiological noise correction, outperformed other strategies in differentiating ASD from TD participants based on functional connectivity (FC) analyses. The correlation of quality control with functional connectivity (QC-FC) is statistically significant in proportion and distance after applying each denoising pipeline. The mean FC between groups is significant for Yeo's 17-Network in each denoising strategy. ICA-AROMA head motion correction outperformed other strategies, revealing more significant FC networks and distinct brain regions linked to the posterior cingulate cortex and postcentral gyrus. This suggests ICA-AROMA enhances fMRI preprocessing, aiding ASD diagnosis and biomarker development.

PMID:40118993 | DOI:10.1038/s42003-025-07928-w

Brain Imaging Behav. 2025 Mar 21. doi: 10.1007/s11682-025-00997-9. Online ahead of print.

ABSTRACT

To explore the structural and functional changes of Cerebellar Subregion in patients with pediatric bipolar disorder (PBD) patients and its clinical significance by using multimodal magnetic resonance imaging, so as to further explore the specific role of the cerebellum in PBD. This study included 48 pediatric patients with bipolar disorder (PBD) in the depressive phase from the outpatient clinic of the Department of Psychosomatic Medicine of the First Affiliated Hospital of Nanchang University. 22 healthy controls (HCs) matched for gender, age, handedness and education level were chosen from the community as the control group. All subjects underwent 3.0T resting-state functional magnetic resonance imaging (rs-fMRI) scans and completed clinical scales, including the Hamilton Depression Scale (HAMD) and Young Mania Rating Scale (YMRS). The cerebellum was categorized into 34 distinct subregions (R17, L17) based on SUIT and designated as seed points to perform whole-brain functional connectivity (FC). Group differences in categorical variables were assessed using the chi-square test, while continuous variables were compared employing the two-sample t-test. Correlations between FC and clinical parameters were analyzed for differential brain intervals. Compared with HCs, PBD patients in the depressive phase showed reduced FC between the left cerebellar lobules I-IV and the occipital inferior lobe (Occipital_Inf_L), cerebellar vermis VIIIa, and VIIIb; decreased FC between cerebellar cerebellar vermis VI and the frontal inferior orbital gyrus (Frontal_Inf_Orb_L), as well as the right cerebellar Crus 1; reduced FC between the left cerebellar Crus I and the dentate nucleus; decreased FC between cerebellar vermis VIIIa and the left superior frontal gyrus; reduced FC between the right cerebellar lobule IX and the right lingual gyrus; lowered FC between the left dentate and the dorsolateral prefrontal cortex, and the left lingual gyrus; FC between the left fastigial nucleus and the right cerebellar X decreased. Depressive phase of PBD patients exhibit altered functional connectivity within various subregions of the cerebellum, suggesting that the cerebellum is involved in central neural reorganization in PBD, which may be instructive for the understanding of central mechanisms and its future diagnostic and therapeutic target development.

PMID:40117108 | DOI:10.1007/s11682-025-00997-9

Acta Neuropsychiatr. 2025 Mar 21:1-32. doi: 10.1017/neu.2025.9. Online ahead of print.

ABSTRACT

OBJECTIVE: New developments in neuro-navigation and machine learning have allowed for personalized approaches to repetitive transcranial magnetic stimulation (rTMS) to treat various neuropsychiatric disorders. One specific approach, known as the Cingulum Framework, identifies individualized brain parcellations from resting state fMRI based on a machine-learning algorithm. Theta burst stimulation, a more rapid form of rTMS, is then delivered for 25 sessions, 5 per day, over 5 days consecutively or spaced out over 10 days. Preliminary studies have documented this approach for various neurological and psychiatric ailments. However, the safety and tolerability of this approach is unclear.

METHODS: We performed a retrospective study on 165 unique patients (202 Target Sets) treated with this personalized approach between January 2020 to December 2023.

RESULTS: Common side effects included fatigue (102/202, 50%), local muscle twitching (89/202, 43%), headaches (49/202, 23%), and discomfort (31/202, 17%), all transient. The top 10 unique parcellations commonly found in the Target Sets included L8av (52%), LPGs (28%), LTe1m (21%), RTe1m (18%), LPFM (17%), Ls6-8 (13%), Rs6-8 (9%), L46 (7%), L1 (6%), and L6v (6%). Fatigue was most common in Target Sets that contained R6v (6/6, 100%) and L8c (5/5, 100%). Muscle twitches were most common in Target Sets that contained RTGv (5/5, 100%) and LTGv (4/4, 100%).

CONCLUSION: These side effects were all transient and well-tolerated. No serious side effects were recorded. Results suggested that individualized, connectome-guided rTMS is safe and contain side effect profiles similar to other TMS approaches reported in the literature.

PMID:40116602 | DOI:10.1017/neu.2025.9

Front Psychiatry. 2025 Mar 6;16:1479283. doi: 10.3389/fpsyt.2025.1479283. eCollection 2025.

ABSTRACT

INTRODUCTION: The Attention Training Technique (ATT) is a psychotherapeutic intervention in Metacogntive Therapy (MCT) and aims at reducing maladaptive processes by strengthening attentional flexibility. ATT has demonstrated efficacy in treating depression on a clinical level. Here, we evaluated ATT at the neural level. We examined functional connectivity (FC) of the default mode network (DMN).

METHOD: 48 individuals diagnosed with Major Depressive Disorder (MDD) and 51 healthy controls (HC) participated in a resting-state (rs) functional magnetic resonance imaging (fMRI) experiment. The participants received either one week of ATT or a sham intervention. Rs-fMRI scans before and after treatment were compared using seed-to-voxel analysis.

RESULTS: The 2x2x2 analysis did not reach significance. Nevertheless, a resting-state connectivity effect was found on the basis of a posttest at the second measurement time point in MDD. After one week, MDD patients who had received ATT intervention presented lower functional connectivity between the left posterior cingulate cortex (PCC) and the bilateral middle frontal gyrus (MFG) as well as between the right PCC and the left MFG compared to the MDD patients in the sham group. In HC we observed higher rsFC in spatially close but not the same brain regions under the same experimental condition.

CONCLUSION: We found a first hint of a change at the neural level on the basis of ATT. Whether the changes in rsFC found here indicate an improvement in the flexible shift of attentional focus due to ATT needs to be investigated in further research paradigms. Further experiments have to show whether this change in functional connectivity can be used as a specific outcome measure of ATT treatment.

PMID:40115647 | PMC:PMC11922856 | DOI:10.3389/fpsyt.2025.1479283

Eur J Neurosci. 2025 Mar;61(6):e70082. doi: 10.1111/ejn.70082.

ABSTRACT

Human social functioning is thought to rely on the action observation network (AON) and the mentalizing system (MS). It is debated whether AON and MS are functionally separate or if they interact. To this end, we combined resting-state connectivity with task-based fMRI to characterize the functional connectome within and between these systems. In detail, we computed resting-state connectivity within and between the AON and MS using single subject-defined regions of interest (ROIs). Our results showed a positive coupling between ROIs within each system and negative coupling between the two systems, supporting the existence of two independent networks at rest. Still, two regions (pSTS, aIFG) showed hybrid coupling, connecting with regions of both systems, suggesting that they might mediate cross-network communication. This characterization of the interplay between MS and AON in the healthy brain might provide the starting point to further investigate aberrant "connectivity" fingerprints associated with neuropsychiatric disorders characterized by impairments in social cognition.

PMID:40114360 | DOI:10.1111/ejn.70082

Sci Rep. 2025 Mar 21;15(1):9711. doi: 10.1038/s41598-025-94790-9.

ABSTRACT

Anxiety symptoms occur more frequently during adolescence and early adulthood, increasing the risk of future anxiety disorders. Neuroscientific research on anxiety has primarily focused on adulthood, employing mostly univariate approaches, discounting large-scale alterations of the brain. Indeed adolescents with trait anxiety may display similar abnormalities shown by adults in brain regions ascribed to the default mode network, associated with self-referential thinking and rumination-related processes. The present study aims to explore resting-state connectivity patterns associated with trait anxiety in a large sample of young individuals. We analyzed the rs-fMRI images of 1263 adolescents (mean age 20.55 years) and their scores on anxiety trait. A significant association between trait anxiety and resting-state functional connectivity in two networks was found, with some regions overlapping with the default mode network, such as the cingulate gyrus, the middle temporal gyri and the precuneus. Of note, the higher the trait anxiety, the lower the connectivity within both networks, suggesting abnormal self-referential processing, awareness, and emotion regulation abilities in adolescents with high anxiety trait. These findings provided a better understanding of the association between trait anxiety and brain rs-functional connectivity, and may pave the way for the development of potential biomarkers in adolescents with anxiety.

PMID:40114036 | DOI:10.1038/s41598-025-94790-9

Sci Data. 2025 Mar 20;12(1):466. doi: 10.1038/s41597-025-04828-w.

ABSTRACT

The dataset investigates the neural correlates of appetite in people living with motor neuron disease (plwMND) compared to non-neurodegenerative disease controls. Thirty-six plwMND and twenty-three controls underwent two fMRI sessions: one in a fasted state and one postprandial. Participants viewed visual stimuli of non-food items, low-calorie foods, and high-calorie foods in a randomised block design. Imaging data included T1w, T2w, and task-based and resting-state fMRI scans, and measures are complemented by subjective appetite questionnaires and anthropometric measures. This dataset is unique for its inclusion of functional imaging across prandial states, offering insights into the neural mechanisms of appetite regulation in patients with MND. Researchers can explore various aspects of the data, including the functional responses to food stimuli and their associations with clinical and appetite measures. The data, deposited in OpenNeuro, follows the Brain Imaging Data Structure (BIDS) standard, ensuring compatibility and reproducibility for future research. This comprehensive dataset provides a resource for studying the central mechanisms of appetite regulation in MND.

PMID:40113810 | DOI:10.1038/s41597-025-04828-w

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