Most recent paper

Schizophrenia (Heidelb). 2025 Apr 2;11(1):52. doi: 10.1038/s41537-025-00581-6.

ABSTRACT

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including the rationale for various choices. This protocol includes T1- and T2-weighted structural scans, resting-state fMRI, and diffusion-weighted imaging collected at two time points, approximately 2 months apart. We also present preliminary variance component analyses of several measures, such as signal- and contrast-to-noise ratio (SNR/CNR) and spatial smoothness, to provide quantitative data on the relative percentages of participant, site, and platform (i.e., scanner model) variance. Site-related variance is generally small (typically <10%). For the SNR/CNR measures from the structural and fMRI scans, participant variance is the largest component (as desired; 40-76%). However, for SNR/CNR in the diffusion scans, there is substantial platform-related variance (>55%) due to differences in the diffusion imaging hardware capabilities of the different scanners. Also, spatial smoothness generally has a large platform-related variance due to inherent, difficult to control, differences between vendors in their acquisitions and reconstructions. These results illustrate some of the factors that will need to be considered in analyses of the AMP SCZ neuroimaging data, which will be the largest CHR cohort to date.Watch Dr. Harms discuss this article at https://vimeo.com/1059777228?share=copy#t=0 .

PMID:40175382 | DOI:10.1038/s41537-025-00581-6

Transl Psychiatry. 2025 Apr 2;15(1):117. doi: 10.1038/s41398-025-03330-6.

ABSTRACT

Electroconvulsive therapy (ECT) is an effective and rapid neuromodulatory intervention for treatment-resistant major depressive disorders (MDD). However, the precise mechanisms underlying their efficacies remain unclear. Resting-state functional magnetic resonance imaging (fMRI) data were collected from 84 individuals with MDD and healthy controls before and after ECT, and coefficient of variation of the BOLD signal (CVBOLD) analysis was combined with region of interest (ROI) functional connectivity (FC) analysis. To assess the reliability of the antidepressant mechanism of ECT, we analyzed the changes in CVBOLD in a separate cohort consisting of 35 patients with MDD who underwent ECT. Moreover, transcriptomic and neurotransmitter receptor data were used to reveal the genetic and molecular bases of the changes in CVBOLD. Patients with MDD who underwent ECT demonstrated increased CVBOLD in the left angular cortex and left precuneus. Following ECT, an increase in FC between the left precuneus and right lingual lobes was associated with improvements in Hamilton Depression Rating Scale (HAMD) scores. validation analysis consistently demonstrated similar changes in CVBOLD in two independent cohorts of patients with MDD. Moreover, these changes in CVBOLD were closely associated with thyroid hormone synthesis, oxidative phosphorylation, endocytosis, and the insulin signaling pathway, and were significantly correlated with the receptor/transporter density of serotonin and dopamine. These findings suggest that ECT modulates abnormal functions in the left angular cortex and left precuneus, leading to widespread changes in functional connectivity and neuroplasticity, especially in the default mode network, and exerts an antidepressant effect.

PMID:40175334 | DOI:10.1038/s41398-025-03330-6

Clin Neurophysiol. 2025 Mar 24;173:205-212. doi: 10.1016/j.clinph.2025.03.021. Online ahead of print.

ABSTRACT

OBJECTIVE: To investigate the changes in resting-state functional connectivity (rs-FC) of different anterior cingulate cortex (ACC) subregions in patients with somatic depression (SD), and its correlation with clinical characteristics.

METHODS: We recruited 38 patients with SD, 33 patients with non-somatic depression (NSD), and 30 healthy controls (HC).All subjects underwent resting-state functional magnetic resonance imaging(rs-fMRI).The ACC subregions (pregenual ACC(pgACC), subgenual ACC(sgACC), and supracallosal ACC(supACC)) were used as regions of interest to make functional connections with the whole brain.Using correlation analysis to explore the relationship between rs-FC values and the severity of clinical symptoms.

RESULTS: SD group showed decreased rs-FC between the right pgACC and the left superior temporal gyrus (STG)/ left middle temporal gyrus (MTG) (MNI: x = -45, y = -12, z = -9, t = 4.36/MNI: x = -48, y = -33, z = -3, t = 3.89, AlphaSim correction, voxel-level P < 0.001, cluster-level P < 0.05), and rs-FC was negatively correlated with Somatic subscale (SS) (r = -0.572, P < 0.0001). But there was no significant correlation with Depression Subscale (DS) (P > 0.05).

CONCLUSIONS: The group of SD exhibit functional alterations in the right pgACC and left STG/left MTG, which may be the neuroimaging basis for the occurrence of SD.

SIGNIFICANCE: The functional abnormality between the ACC subregions and temporal lobe show a new neural circuit for SD patients and provide a theoretical basis for further clinical intervention.

PMID:40174241 | DOI:10.1016/j.clinph.2025.03.021

Brain Behav. 2025 Apr;15(4):e70465. doi: 10.1002/brb3.70465.

ABSTRACT

BACKGROUND: Hearing loss affects communication and hinders personal attention and cognitive ability. We hypothesized that noise-induced hearing loss (NIHL) patients during long-term noise exposure may result in multimodal plastic changes in the nonauditory central nervous system.

OBJECTIVE: To investigate the functional connectivity (FC) of the default mode network (DMN) and visual network (VN) in patients with occupational NIHL using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: Ninety-eight people with NIHL and 78 healthy controls (HCs) matched for age and educational level were enrolled. The mini-mental state examination (MMSE) was conducted, and rs-fMRI scanning was performed. The data were processed and analyzed to identify FC changes between DMN, VN, and the whole brain.

RESULTS: Compared with the HCs, the NIHL group showed significantly enhanced connectivity with multiple brain regions when utilizing the DMN as seed regions of interest (ROI), with only some brain regions showing significantly decreased connectivity. When the VN was used as the seed ROI, the NIHL group showed significantly enhanced connectivity with multiple brain regions (corrected by GRF, p < 0.05). In the present study, the FC between multiple brain areas of VN and DMN in the NIHL patient group was enhanced compared to the normal population. The phenomenon of "perceptual compensation" is confirmed. The results of this study suggest that NIHL causes various changes in brain function related to emotion, decision-making, social cognition, and psychopathology. It suggests that changes in brain functional networks involve complex processes involving plasticity and damage to multiple networks.

CONCLUSIONS: The NIHL patients showed abnormal FC changes in both the DMN and VN, indicating widespread multimodal plasticity and reorganization of nonauditory central nervous system functions in people with NIHL.

PMID:40170553 | DOI:10.1002/brb3.70465

Commun Biol. 2025 Apr 1;8(1):535. doi: 10.1038/s42003-025-07964-6.

ABSTRACT

Emerging studies suggest that time-dependent consolidation enables memory stabilization by promoting memory integration and hippocampal-cortical transfer. Compared to massed learning, how time-dependent consolidation contributes to forming durable memory and what neural signatures predict durable memory in spaced learning remain unclear. We recruited 48 participants who underwent either 3-day spaced learning or 1-day massed learning, and both resting-state and task-based fMRI data were collected in multiple delayed tests (i.e., immediate, 1-week, and 1-month). We use representational similarity analysis to assess neural integration and replay in the hippocampus and default mode network (DMN) subsystems. In contrast with massed learning, spaced learning induces higher neural pattern similarity during immediate retrieval only in DMN subsystems. Particularly, the neural pattern similarity in the dorsal-medial DMN (DMNdm) and medial-temporal DMN subsystems predicts the durable memory defined by 1-month delay. Moreover, we find increased neural replay of durable memory in the DMNdm for spaced learning and in the hippocampus for both spaced and massed learning. Our findings suggest that time-dependent consolidation promotes neural integration and replay in the cortex rather than in the hippocampus, which may underlie the formation of durable memory after spaced learning.

PMID:40169798 | DOI:10.1038/s42003-025-07964-6

Int Psychogeriatr. 2025 Mar 31:100067. doi: 10.1016/j.inpsyc.2025.100067. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of this study was to determine whether individuals with Subjective Cognitive Decline (SCD), particularly those with a neurostructural marker of risk for AD (SCD+), exhibit differences in the functional connectivity of the Default-Mode Network (DMN) relative to controls, as this network is known to be altered in the AD continuum.

DESIGN: Cross-sectional study.

SETTING: Galicia, Northwest Spain.

PARTICIPANTS: The sample compromised 133 participants: 69 controls, 51 SCD and 13 SCD+.

MEASUREMENTS: Seed-to-voxel analysis was conducted using four DMN ROIs. Dynamic independent component analysis of the DMN was also performed.

RESULTS: The SCD and SCD+ groups exhibited DMN hyperconnectivity, which was more extensive in the SCD+ group. Increased anti-correlations between DMN and task-positive parietal regions were related to poorer executive scores in SCD+ and a tendency for higher DMN recurrence in SCD+.

CONCLUSIONS: Hippocampal atrophy as a SCD+ biomarker is associated with extensive DMN hyperconnectivity and increased anti-correlations between DMN and task-positive network regions.

PMID:40169304 | DOI:10.1016/j.inpsyc.2025.100067

Brain Stimul. 2025 Mar 30:S1935-861X(25)00077-4. doi: 10.1016/j.brs.2025.03.020. Online ahead of print.

ABSTRACT

BACKGROUND: Systems neuroscience studies have shown that baseline brain activity can be categorized into large-scale networks (resting-state-networks, RNSs), with influence on cognitive abilities and clinical symptoms. These insights have guided millimeter-precise selection of brain stimulation targets based on RSNs. Concurrently, Transcranial Magnetic Stimulation (TMS) studies revealed that baseline brain states, measured by EEG signal power or phase, affect stimulation outcomes. However, EEG dynamics in these studies are mostly limited to single regions or channels, lacking the spatial resolution needed for accurate network-level characterization.

OBJECTIVE: We aim at mapping brain networks with high spatial and temporal precision and to assess whether the occurrence of specific network-level-states impact TMS outcome. To this end, we will identify large-scale brain networks and explore how their dynamics relates to corticospinal excitability.

METHODS: This study leverages Hidden Markov Models to identify large-scale brain states from pre-stimulus source space high-density-EEG data collected during TMS targeting the left primary motor cortex in twenty healthy subjects. The association between states and fMRI-defined RSNs was explored using the Yeo atlas, and the trial-by-trial relation between states and corticospinal excitability was examined.

RESULTS: We extracted fast-dynamic large-scale brain states with unique spatiotemporal and spectral features resembling major RSNs. The engagement of different networks significantly influences corticospinal excitability, with larger motor evoked potentials when baseline activity was dominated by the sensorimotor network.

CONCLUSIONS: These findings represent a step forward towards characterizing brain network in EEG-TMS with both high spatial and temporal resolution and underscore the importance of incorporating large-scale network dynamics into TMS experiments.

PMID:40169093 | DOI:10.1016/j.brs.2025.03.020

Neurology. 2025 Apr 22;104(8):e213502. doi: 10.1212/WNL.0000000000213502. Epub 2025 Apr 1.

ABSTRACT

BACKGROUND AND OBJECTIVES: Pediatric concussion can disrupt functional brain network connectivity, but prospective longitudinal research is needed to clarify recovery and identify moderators of change. This study investigated network functional connectivity (FC) up to 6 months after pediatric concussion.

METHODS: This prospective longitudinal concurrent cohort observational study consecutively recruited children (aged 8 to 17 years) at 5 Canadian pediatric hospital emergency departments within 48 hours of sustaining a concussion or mild orthopaedic injury (OI). Children completed 3T MRI scanning postacutely (2 to 33 days) and at either 3 or 6 months after injury (randomly assigned at the postacute visit). Reliable change between retrospective preinjury (based on parent report) and 1-month postinjury symptom ratings based on parent and child report was used to classify concussion with or without persisting symptoms. Within-network and between-network FC was computed for 8 brain networks from resting-state fMRI scans and analyzed using linear mixed-effects models, with multiple comparison correction.

RESULTS: Groups (385 with concussion/198 with OI; 59% male; 69% White; age 12.42 ± 2.29 years) did not differ in within-network FC. Relative to OI, connectivity between the visual and ventral attention networks was lower after concussion, d (95% CI) = -0.46 (-0.79 to -0.14), across time. Connectivity between the visual and default mode networks was lower at 6 months after concussion, -0.60 (-0.92 to -0.27). At 3 months after concussion, connectivity between the frontoparietal and ventral attention networks was lower in younger children, -0.98 (-1.58 to -0.37), but higher in older children, 0.81 (0.20 to 1.42). For symptom groups based on parent report, connectivity between the dorsal and ventral attention networks was higher in female children at 3 months after concussion without persisting symptoms relative to concussion with persisting symptoms, 1.25 (2.05 to 0.46), and OI, 0.87 (0.25 to 1.49).

DISCUSSION: Time after injury, age at injury, biological sex, and persistent symptom status are important moderators of FC after pediatric concussion for children seen in emergency department settings. Postacute FC may not enhance clinical diagnosis. Although within-network connectivity is preserved, between-network connectivity differences emerge after most children clinically recover and persist up to 6 months after pediatric concussion, providing a potential objective biomarker for lasting changes in brain function.

PMID:40168632 | DOI:10.1212/WNL.0000000000213502

Radiology. 2025 Apr;315(1):e233264. doi: 10.1148/radiol.233264.

ABSTRACT

Background Special operations forces members often face multiple blast injuries and have a higher risk of traumatic brain injury. However, the relationship between neuroimaging markers, the cumulative severity of injury, and long-term symptoms has not previously been well-established in the literature. Purpose To determine the relationship between the frequency of blast injuries, persistent clinical symptoms, and related cortical volumetric and functional connectivity (FC) changes observed at brain MRI in special operations forces members. Materials and Methods A cohort of 220 service members from a prospective study between January 2021 and May 2023 with a history of repetitive blast exposure underwent psychodiagnostics and a comprehensive neuroimaging evaluation, including structural and resting-state functional MRI (fMRI). Of these, 212 met the inclusion criteria. Participants were split into two datasets for model development and validation, and each dataset was divided into high- and low-exposure groups based on participants' exposure to various explosives. Differences in FC were analyzed using a general linear model, and cortical gray matter volumes were compared using the Mann-Whitney U test. An external age- and sex-matched healthy control group of 212 participants was extracted from the SRPBS Multidisorder MRI Dataset for volumetric analyses. A multiple linear regression model was used to assess correlations between clinical scores and FC, while a logistic regression model was used to predict exposure group from fMRI scans. Results In the 212 participants (mean age, 43.0 years ± 8.6 [SD]; 160 male [99.5%]) divided into groups with low or high blast exposure, the high-exposure group had higher scores for the Neurobehavioral Symptom Inventory (NSI) (t = 3.16, P < .001) and Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PCL-5) (t = 2.72, P = .01). FC differences were identified in the bilateral superior and inferior lateral occipital cortex (LOC) (P value range, .001-.04), frontal medial cortex (P < .001), left superior frontal gyrus (P < .001), and precuneus (P value range, .02-.03). Clinical scores from NSI and PCL-5 were inversely correlated with FC in the LOC, superior parietal lobule, precuneus, and default mode networks (r = -0.163 to -0.384; P value range, <.001 to .04). The high-exposure group showed increased cortical volume in regions of the LOC compared with healthy controls and the low-exposure group (P value range, .01-.04). The predictive model helped accurately classify participants into high- and low-exposure groups based on fMRI data with 88.00 sensitivity (95% CI: 78.00, 98.00), 67% specificity (95% CI: 53.00, 81.00), and 73% accuracy (95% CI: 60.00, 86.00). Conclusion Repetitive blast exposure leads to distinct alterations in FC and cortical volume, which correlate with neurobehavioral symptoms. The predictive model suggests that even in the absence of observable anatomic changes, FC may indicate blast-related trauma. © RSNA, 2025 Supplemental material is available for this article.

PMID:40167438 | DOI:10.1148/radiol.233264

ArXiv [Preprint]. 2025 Mar 18:arXiv:2503.14700v1.

ABSTRACT

In brain network analysis using resting-state fMRI, there is growing interest in modeling higher-order interactions beyond simple pairwise connectivity via persistent homology. Despite the promise of these advanced topological tools, robust and consistently observed higher-order interactions over time remain elusive. In this study, we investigate why conventional analyses often fail to reveal complex higher-order structures - such as interactions involving four or more nodes - and explore whether such interactions truly exist in functional brain networks. We utilize a simplicial complex framework often used in persistent homology to address this question.

PMID:40166738 | PMC:PMC11957234

Arthritis Res Ther. 2025 Mar 31;27(1):70. doi: 10.1186/s13075-025-03526-7.

ABSTRACT

BACKGROUND: Pain remains a principal complaint for people with psoriatic arthritis (PsA), despite successful mitigation of inflammation. This situation alludes to the co-existence of distinct pain mechanisms. Nociceptive and nociplastic mechanisms are clinically challenging to distinguish. Advances in brain functional magnetic resonance imaging (fMRI) have successfully characterised distinct pain mechanisms across several disorders, in particular implicating the insula. This is the first study to characterise neurobiological markers of pain mechanisms in PsA employing fMRI.

METHODS: PsA participants underwent a 6-minutes resting-state fMRI brain scan, and questionnaire assessments of nociplastic pain (2011 ACR fibromyalgia criteria) and body pain, assessed using the Numeric Rating Scale (NRS, 0-100). Functional connectivity between insula seeds (anterior, mid, posterior), and the whole brain was correlated with the above pain outcomes correcting for age and sex, and false discovery rate (FDR) for multiple comparisons.

RESULTS: A total of 46 participants were included (age 49 ± 11.2; 52% female; FM score 12.5 ± 5.7; overall pain 34.8 ± 23.5). PsA participants with higher fibromyalgia scores displayed increased connectivity between: (1) right anterior insula to DMN (P < 0.05), (2) right mid and left posterior insula to parahippocampal gyri (P < 0.01 FDR); and (3) right mid insula to left frontal pole (P = 0.001 FDR). Overall pain was correlated with connectivity of left posterior insula to classical nociceptive regions, including thalamus (P = 0.01 FDR) and brainstem (P = 0.002 FDR).

CONCLUSION: For the first time, we demonstrate objectively that nociceptive and nociplastic pain mechanisms co-exist in PsA. PsA pain cannot be assumed to be only nociceptive in origin and screening for nociplastic pain in the future will inform supplementary analgesic approaches.

PMID:40165287 | DOI:10.1186/s13075-025-03526-7

BMC Psychiatry. 2025 Mar 31;25(1):308. doi: 10.1186/s12888-025-06747-x.

ABSTRACT

BACKGROUND: Clinical high-risk (CHR) refers to prodromal phase before schizophrenia onset, characterized by attenuated psychotic symptoms and functional decline. They exhibit similar but milder cognitive impairments, brain abnormalities and eye movement change compared with first-episode schizophrenia (FSZ). These alterations may increase vulnerability to transitioning to the disease. This study explores cognitive-related functional connectivity (FC) and eye movement abnormalities to examine differences in the progression of schizophrenia.

METHODS: Thirty drug-naive FSZ, 28 CHR, and 30 healthy controls (HCs) were recruited to undergo resting-state functional magnetic resonance imaging (rs-fMRI). Connectome-based predictive modeling (CPM) was employed to extract cognitive-related brain regions, which were then selected as seeds to form FC networks. Support vector machine (SVM) was used to distinguish FSZ from CHR. Smooth pursuit eye-tracking tasks were conducted to assess eye movement features.

RESULTS: FSZ displayed decreased cognitive-related FC between right posterior cingulate cortex and right superior frontal gyrus compared with HCs and between right amygdala and left inferior parietal gyrus (IPG) compared with CHR. SVM analysis indicated a combination of BACS-SC and CFT-A scores, and FC between right amygdala and left IPG could serve as a potential biomarker for distinguishing FSZ from CHR with high sensitivity. FSZ also exhibited a wide range of eye movement abnormalities compared with HCs, which were associated with alterations in cognitive-related FC.

CONCLUSIONS: FSZ and CHR exhibited different patterns of cognitive-related FC and eye movement alteration. Our findings illustrate potential neuroimaging and cognitive markers for early identification of psychosis that could help in the intervention of schizophrenia in high-risk groups.

PMID:40165149 | DOI:10.1186/s12888-025-06747-x

J Comput Assist Tomogr. 2025 Mar 14. doi: 10.1097/RCT.0000000000001740. Online ahead of print.

ABSTRACT

OBJECTIVE: Cognitive impairment is a prevalent complication among patients with diabetes mellitus. It tends to be more prominent in patients with diabetic retinopathy (DR) compared with patients with diabetes without DR (NDR). However, the functional connectivity (FC) between bilateral cerebral hemispheres in both remains poorly understood. This study aimed to investigate altered brain connectivity in patients with DR and NDR.

SUBJECTS AND METHODS: We selected 26 patients with DR, 30 patients with NDR, and 30 healthy controls (HCs) to participate in resting-state functional magnetic resonance imaging (rs-fMRI) and high-resolution T1-weighted structural scans. We employed the DPABI toolbox in MATLAB to preprocess the acquired images and applied voxel-mirrored homotopic connectivity (VMHC) and FC analysis methods to estimate differences among the 3 groups. The patients also underwent neuropsychological assessment scales. We utilized partial correlation analysis to explore the associations between aberrant connections and clinical variables as well as neuropsychological characteristics in patients with DR. Receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of VMHC values in distinct brain regions for differentiating DR patients from NDR patients.

RESULTS: The results showed significantly altered VMHC values across the 3 groups, including bilateral lingual gyrus (LING_B), superior temporal gyrus (STG_B), and postcentral gyrus (PoCG_B). Significant differences in FC values were found across the LING_B, right cuneus (CUN_R), STG_R, PoCG_B, right precentral gyrus (PreCG_R), right precuneus (PCUN_R), and middle temporal gyrus (MTG_L) among the 3 groups. Moreover, a negative correlation was noted between the VMHC values of LING_B and disease duration in patients with DR. Positive correlations were detected between FC values in PoCG_B and fasting blood glucose (FBG) levels. Furthermore, ROC analysis of the VMHC values demonstrated that combining all the differential regions achieved the highest area under the curve of 0.826.

CONCLUSIONS: Significant alterations in VMHC and FC may reflect the underlying neuropathology of cognitive dysfunction in DR and NDR. These altered connectivity patterns could serve as neuroimaging biomarkers, offering insights into the early diagnosis and intervention of cognitive impairments in DR patients.

PMID:40164961 | DOI:10.1097/RCT.0000000000001740

J Anesth. 2025 Mar 31. doi: 10.1007/s00540-025-03477-y. Online ahead of print.

ABSTRACT

BACKGROUND: In recent years, the effects of general anesthetics on the brain have been widely studied at the sedation level using resting-state functional magnetic resonance imaging (rs-fMRI). Most anesthesia protocols use a single agent, and changes in spontaneous brain activity are examined to show the characteristics of each anesthetic agent. However, no studies have used rs-fMRI to evaluate the effects of anesthesia during actual surgery. We examined the feasibility of evaluating the effects of general anesthesia with sevoflurane using rs-fMRI during neurosurgery.

METHODS: We enrolled 20 adult patients scheduled for transsphenoidal surgery. We compared differences between before and during general anesthesia in terms of brain functional connectivity of the thalamus by seed-to-voxel correlation analysis and local neural activity using fractional amplitude of low-frequency fluctuations (fALFF) analysis. An exclusion mask was applied to exclude brain areas showing intraoperative spatial artifacts and correct for differences in the magnitude of intra- and preoperative head movements.

RESULTS: We analyzed 16 patients. Functional connectivity of the thalamus to the contralateral thalamus, bilateral caudate nucleus and globus pallidus were significantly decreased during anesthesia. The precuneus and posterior cingulate cortex showed significantly decreased fALFF values during anesthesia.

CONCLUSION: These findings were consistent with previous studies and indicate the feasibility of intraoperative rs-fMRI during general anesthesia.

PMID:40164844 | DOI:10.1007/s00540-025-03477-y

Mol Psychiatry. 2025 Mar 31. doi: 10.1038/s41380-025-02974-6. Online ahead of print.

ABSTRACT

Major depressive disorder (MDD) presents a substantial health burden with low treatment response rates. Predicting antidepressant efficacy is challenging due to MDD's complex and varied neuropathology. Identifying biomarkers for antidepressant treatment requires thorough analysis of clinical trial data. Multimodal neuroimaging, combined with advanced data-driven methods, can enhance our understanding of the neurobiological processes influencing treatment outcomes. To address this, we analyzed resting-state fMRI and EEG connectivity data from 130 patients treated with sertraline and 135 patients with placebo from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. A deep learning framework was developed using graph neural networks to integrate data-augmented connectivity and cross-modality correlation, aiming to predict individual symptom changes by revealing multimodal brain network signatures. The results showed that our model demonstrated promising prediction accuracy, with an R2 value of 0.24 for sertraline and 0.20 for placebo. It also exhibited potential in transferring predictions using only EEG. Key brain regions identified for predicting sertraline response included the inferior temporal gyrus (fMRI) and posterior cingulate cortex (EEG), while for placebo response, the precuneus (fMRI) and supplementary motor area (EEG) were critical. Additionally, both modalities identified the superior temporal gyrus and posterior cingulate cortex as significant for sertraline response, while the anterior cingulate cortex and postcentral gyrus were common predictors in the placebo arm. Additionally, variations in the frontoparietal control, ventral attention, dorsal attention, and limbic networks were notably associated with MDD treatment. By integrating fMRI and EEG, our study established novel multimodal brain network signatures to predict individual responses to sertraline and placebo in MDD, providing interpretable neural circuit patterns that may guide future targeted interventions. Trial Registration: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) ClinicalTrials.gov Identifier: NCT#01407094.

PMID:40164695 | DOI:10.1038/s41380-025-02974-6

Sci Data. 2025 Mar 31;12(1):538. doi: 10.1038/s41597-025-04901-4.

ABSTRACT

Fake news poses significant societal risks by spreading rapidly on social media. While existing research predominantly examines its propagation patterns and psychological drivers, the neural underpinnings remain insufficiently understood. Moreover, current studies often focus on Western political contexts, overlooking cultural variations where social-lifestyle fake news may be more prevalent, such as in China. In this paper, we introduce a multimodal dataset that combines neuroimaging, behavioral data, and standardized Chinese social-lifestyle fake and true news materials. The dataset includes T1 structural, resting-state, and task-based fMRI data from 43 college students, capturing brain activity during tasks involving sharing news and assessing its accuracy. Additionally, participants' trait and rating data were collected to explore individual differences in brain structure, intrinsic functional states, and responses to fake and true news. This dataset could inform future studies on misinformation, offering deeper insights into the neural and psychological aspects of fake news. An overview of the data acquisition, cleaning, and sharing procedures is presented.

PMID:40164637 | DOI:10.1038/s41597-025-04901-4

Brain Imaging Behav. 2025 Mar 31. doi: 10.1007/s11682-025-00999-7. Online ahead of print.

ABSTRACT

Anhedonia is a core feature of depression. It contains a consummatory and a motivational aspect. Whilst much neuroimaging research in patients with depression focused on the consummatory aspect of anhedonia, less is known about its motivational aspect. This study aimed to explore the neurobiology of networks related to motivational anhedonia. Thirty-eight patients with major depressive disorder (MDD) and 19 healthy controls underwent diffusion-weighted and resting state functional magnetic resonance imaging (rs-fMRI). For assessment of motivational anhedonia, we summed the values of the CORE non-interactiveness score, and the items 1 (hopelessness) and 7 (work and activities) of the Hamilton Depression Rating Scale. Whole-brain voxel-wise statistical analysis of fractional anisotropy (FA) data was performed using Tract-Based Spatial Statistics (TBSS). Additionally, we performed a whole-brain comparison of integrated local correlation of rs-fMRI signal (LCOR), to investigate regional functional differences between patients and healthy controls. Whole brain correlations between motivational anhedonia and measures of structural and functional connectivity (FA, and LCOR) were calculated. TBSS-analyses revealed reduced FA in the left superior longitudinal fasciculus (SLF) in patients with MDD. LCOR was reduced in patients with depression in an adjacent cluster localized in bilateral precunei. Within patients, there was a positive correlation between motivational anhedonia and LCOR in the precunei and a negative correlation in bilateral sensorimotor areas. FA-values did not show significant correlations. These findings suggest that motivational anhedonia in depression is linked to alterations of functional connectivity within bilateral precunei. Observed white matter microstructural alterations in the SLF do not show such an association.

PMID:40163222 | DOI:10.1007/s11682-025-00999-7

J Mood Anxiety Disord. 2025 Mar;9:100096. doi: 10.1016/j.xjmad.2024.100096. Epub 2024 Dec 9.

ABSTRACT

Self-judgment is a trans-diagnostic symptom among various psychological disorders, therefore can be a therapeutic target for many common psychiatric conditions. Self-judgment often arises among those who experienced childhood maltreatment, which increases the risk for developing comorbid psychiatric disorders that are resistant to traditional pharmacological and psychological interventions. Understanding the neural correlates of the therapeutic effect of behavioral interventions for reducing self-judgment is key for developing and refining evidence-based intervention programs. This single arm pilot study (N = 24) explored the neural correlates of reduction in self-judgment after an eight-week mindful self-compassion (MSC) intervention program for a sample of adult patients with either anxiety or depressive disorders, with 83 % having more than one diagnoses. The results demonstrated significant reduction of self-judgment after the intervention (p < 0.001, d = -1.04) along with increased self-compassion (p < 0.001, d =1.20); in particular, participants with above median score on the Childhood Trauma Questionnaire had significantly more improvement than those with below median scores (p < 0.05). Resting state fMRI was used to study neural correlates and showed that reduced self-judgment was associated with increased posterior cingulate cortex functional connectivity with dorsal lateral prefrontal cortex, inferior frontal gyrus, and dorsal medial prefrontal cortex, accompanied by reduced posterior cingulate cortex functional connectivity with the amygdala-hippocampal complex. These findings suggest reduced self-judgment after MSC training was substantiated by reduced fear circuitry influences on self-referential processes along with enhanced frontal regulation from the executive network and language network.

PMID:40162192 | PMC:PMC11952680 | DOI:10.1016/j.xjmad.2024.100096

Netw Neurosci. 2025 Mar 3;9(1):61-76. doi: 10.1162/netn_a_00421. eCollection 2025.

ABSTRACT

Brain function can be modeled as dynamic interactions between functional sources at different spatial scales, and each spatial scale can contain its functional sources with unique information, thus using a single scale may provide an incomplete view of brain function. This paper introduces a novel approach, termed "telescopic independent component analysis (TICA)," designed to construct spatial functional hierarchies and estimate functional sources across multiple spatial scales using fMRI data. The method employs a recursive independent component analysis (ICA) strategy, leveraging information from a larger network to guide the extraction of information about smaller networks. We apply our model to the default mode network (DMN), visual network (VN), and right frontoparietal network (RFPN). We investigate further on the DMN by evaluating the difference between healthy people and individuals with schizophrenia. We show that the TICA approach can detect the spatial hierarchy of the DMN, VN, and RFPN. In addition, the TICA revealed DMN-associated group differences between cohorts that may not be captured if we focus on a single-scale ICA. In sum, our proposed approach represents a promising new tool for studying functional sources.

PMID:40161992 | PMC:PMC11949590 | DOI:10.1162/netn_a_00421

Netw Neurosci. 2025 Mar 20;9(1):392-420. doi: 10.1162/netn_a_00438. eCollection 2025.

ABSTRACT

Despite significant research, discovering causal relationships from fMRI remains a challenge. Popular methods such as Granger causality and dynamic causal modeling fall short in handling contemporaneous effects and latent common causes. Methods from causal structure learning literature can address these limitations but often scale poorly with network size and need acyclicity. In this study, we first provide a taxonomy of existing methods and compare their accuracy and efficiency on simulated fMRI from simple topologies. This analysis demonstrates a pressing need for more accurate and scalable methods, motivating the design of Causal discovery for Large-scale Low-resolution Time-series with Feedback (CaLLTiF). CaLLTiF is a constraint-based method that uses conditional independence between contemporaneous and lagged variables to extract causal relationships. On simulated fMRI from the macaque connectome, CaLLTiF achieves significantly higher accuracy and scalability than all tested alternatives. From resting-state human fMRI, CaLLTiF learns causal connectomes that are highly consistent across individuals, show clear top-down flow of causal effect from attention and default mode to sensorimotor networks, exhibit Euclidean distance dependence in causal interactions, and are highly dominated by contemporaneous effects. Overall, this work takes a major step in enhancing causal discovery from whole-brain fMRI and defines a new standard for future investigations.

PMID:40161986 | PMC:PMC11949584 | DOI:10.1162/netn_a_00438