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Body Image. 2025 Oct 15;55:101984. doi: 10.1016/j.bodyim.2025.101984. Online ahead of print.

ABSTRACT

OBJECTIVE: Muscularity-oriented disordered eating, characterized by disordered eating symptoms driven by the pursuit of a muscular physique, is an emerging public health concern. Although childhood maltreatment has been linked to thinness-oriented disordered eating, underpinned by the pursuit of a thin ideal, little is known about the longitudinal associations between specific subtypes and muscularity-oriented disordered eating or the neural mechanisms mediating these associations.

METHOD: This study used two-wave data from an ongoing research project tracking college freshmen at a university in Chongqing, China. At Time 1, 212 participants (Age: M (SD) = 18.87 (0.97) years; 38% men) completed behavioral assessments and resting-state fMRI scans, and 144 returned for follow-up at Time 2. We examined these relationships through connectome-based predictive modeling (CPM) and mediation analysis.

RESULTS: Only childhood physical abuse showed a significant indirect effect on T2 muscularity-oriented disordered eating via T1 muscularity-oriented disordered eating. CPM identified the most significant predictive connections in the dorsolateral prefrontal cortex, inferior frontal gyrus, and cerebellum, with positive muscularity-oriented disordered eating networks primarily linking the salience/limbic network to the cerebellum and the fronto-parietal network to the default mode network. In the brain-behavior model, childhood physical abuse's effect on muscularity-oriented disordered eating was partly mediated by these CPM-derived networks.

CONCLUSIONS: Childhood physical abuse emerged as a predictor of muscularity-oriented disordered eating from both behavioral and neural perspectives. These findings underscore the clinical importance of early identification of childhood physical abuse and support the development of integrated psychological and neurobiological interventions to prevent the development of muscularity-oriented disordered eating.

PMID:41101090 | DOI:10.1016/j.bodyim.2025.101984

PLoS One. 2025 Oct 16;20(10):e0334028. doi: 10.1371/journal.pone.0334028. eCollection 2025.

ABSTRACT

The COVID-19 pandemic had profound effects on developing adolescents that, to date, remain incompletely understood. Youth with preexisting mental health problems and associated brain alterations were at increased risk for higher stress and poor mental health. This study investigated impacts of adolescent pre-pandemic mental health problems and their neural correlates on stress, negative emotions and poor mental health during the first 15 months of the COVID-19 pandemic. N = 2,641 adolescents (median age = 12.0 years) from the Adolescent Brain Cognitive Development (ABCD) cohort were studied, who had pre-pandemic data on anxiety, depression, and behavioral (attention, aggression, social withdrawal, internalizing, externalizing) problems, longitudinal survey data on mental health, stress and emotions during the first 15 months following the outbreak, structural MRI, and resting-state fMRI. Data were analyzed using mixed effects mediation and moderation models. Preexisting mental health and behavioral problems predicted higher stress, negative affect and negative emotions (β = 0.09-0.21, CI=[0.03,0.32]), and lower positive affect (β = -0.21 to -0.09, CI=[-0.31,-0.01]) during the first ~6 months of the outbreak. Pre-pandemic structural characteristics of brain regions supporting social function and emotional processing (insula, superior temporal gyrus, orbitofrontal cortex, and the cerebellum) mediated some of these relationships (β = 0.10-0.15, CI=[0.01,0.24]). The organization of pre-pandemic brain circuits moderated (attenuated) associations between preexisting mental health and pandemic stress and negative emotions (β = -0.17 to -0.06, CI=[-0.27,-0.01]). Preexisting mental health problems and their structural brain correlates were risk factors for youth stress and negative emotions during the early months of the outbreak. In addition, the organization of some brain circuits was protective and attenuated the effects of preexisting mental health issues on youth responses to the pandemic's stressors.

PMID:41100534 | DOI:10.1371/journal.pone.0334028

Eur Phys J Spec Top. 2025;234(15):4127-4137. doi: 10.1140/epjs/s11734-025-01591-2. Epub 2025 Mar 25.

ABSTRACT

This mini-review examines functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) among opioid users. The goal is to summarize existing research data and clarify the implications of altered brain connectivity in this population. The first part of the review addresses the critical question of how opioid addiction influences the functional connectivity of key brain networks, such as the default mode network (DMN), salience network (SN), and executive control network (ECN). It examines the neurological basis of opioid addiction, the principles of rs-fMRI, different methodologies employed in this type of research, and inconsistencies and methodological challenges that complicate the interpretation of findings. The second part of the article presents findings derived from our ongoing research in the field. We tested 42 participants of whom 23 healthy controls and 19 patients with opioid use disorder. Each participant underwent an MRI scanning procedure comprised of structural, resting-state and task sequences. The neuroimaging data was processed using the CONN Toolbox running on MATLAB. Our preliminary rs-fMRI findings reveal significant disruptions in functional connectivity in individuals with opioid addiction within DMN and SN networks involved in cognitive functions such as decision-making and impulse control. The review concludes by emphasizing the importance of standardizing research practices, conducting longitudinal randomized studies, and developing a more holistic approach to understanding the effects of heroin addiction. These efforts would contribute to the development of personalized and effective intervention strategies.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1140/epjs/s11734-025-01591-2.

PMID:41098388 | PMC:PMC12518422 | DOI:10.1140/epjs/s11734-025-01591-2

Schizophr Res. 2025 Oct 14;285:323-329. doi: 10.1016/j.schres.2025.10.007. Online ahead of print.

ABSTRACT

BACKGROUND: Early-onset schizophrenia (EOS) is a rare and severe subtype of schizophrenia, characterized by auditory hallucinations (AH). However, studies on AH in EOS are significantly fewer than in adult schizophrenia, and the underlying mechanisms remain unclear.

METHODS: We studied 81 first-episode, drug-naïve EOS patients, grouped by the severity of AH, and compared them with 32 healthy controls. We analyzed the topological properties of the brain's functional network. Using nodes with distinct topological properties as regions of interest (ROI), we examined the correlation between ROI-based functional connectivity and AH scores.

RESULTS: The resting-state brain functional network of EOS patients exhibited small-world network properties (sparsity = 0.05-0.34). Significant differences in degree centrality (DC) and nodal efficiency (NE) were found in the left superior temporal gyrus (STG) (false discovery rate-corrected P [PFDR] < 0.05). Post hoc multiple comparisons revealed that in DC, there were no significant differences between the non-AH group and the mild AH group, but significant differences were observed among the other groups (PFDR < 0.05). In NE, no significant differences were found between the non-AH group and both the mild and severe AH groups, while significant differences were observed among the other groups (PFDR < 0.05). Changes in functional connectivity between the left STG and the left cingulate gyrus (CG) were significantly correlated with AH scores (r = 0.316, PFDR = 0.0303).

CONCLUSIONS: This study implicates dysfunctional circuitry between the left superior temporal gyrus and the left cingulate gyrus in the neurobiology of auditory hallucinations in EOS.

PMID:41092760 | DOI:10.1016/j.schres.2025.10.007

Soc Cogn Affect Neurosci. 2025 Oct 15:nsaf109. doi: 10.1093/scan/nsaf109. Online ahead of print.

ABSTRACT

Identifying the neural characteristics of impulsivity and anxiety is important, as both traits confer risk for mental health conditions. In this study, we applied a Hidden Semi-Markov Model (HSMM) to capture the temporal patterns of brain activity to identify brain states associated with impulsivity and anxiety. Using the Leipzig Study for Mind-Body Emotion Interactions (LEMON) resting-state fMRI dataset of healthy individuals (N = 56), we analyzed three groups: High Impulsivity (HI), High Anxiety (HA), and High Impulsivity & High Anxiety (HIHA), assessed with the STAI-T and UPPS scales. HSMM identified three distinct functional brain states characterized by mean activation, functional connectivity, and topological properties of the frontoparietal, default mode, salience/ventral attention, and limbic networks. Notably, the HI group spent more time in a state with an inverse pattern between the default mode network and the salience/ventral attention network, with anticorrelated connectivity and opposing activation, compared with the HA and HIHA groups. Furthermore, the HI group showed a stronger tendency to persist in this state, which may reflect the neural characteristic distinguishing impulsivity from anxiety. However, no distinctive features were observed in the HIHA group. Nevertheless, these findings provide initial insights into the time-varying characteristics of impulsivity and anxiety.

PMID:41092314 | DOI:10.1093/scan/nsaf109

Neuromodulation. 2025 Oct 15:S1094-7159(25)01025-6. doi: 10.1016/j.neurom.2025.08.415. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aims to investigate the modulatory effects of transcutaneous auricular vagus nerve stimulation (taVNS) and transcutaneous greater auricular nerve stimulation (tGANS) on the brainstem's vagus nerve pathway hubs-the nucleus tractus solitarius (NTS), locus coeruleus (LC), and raphe nucleus (RN)-in individuals with chronic low back pain (cLBP).

MATERIALS AND METHODS: A total of 70 patients with cLBP were randomly assigned to receive four weeks of either taVNS or tGANS. Resting-state functional and structural magnetic resonance imaging (fMRI/sMRI) data were collected at baseline and post treatment. Analyses focused on static and dynamic functional connectivity (sFC/dFC) and fractional anisotropy (FA) using the NTS, LC, and RN--three brainstem nuclei within the central vagus nerve pathway-as seed regions.

RESULTS: Overall, 51 participants completed the treatment. Both groups showed significant pain improvement, with no significant difference between the taVNS and tGANS groups. taVNS was found to influence connectivity between the NTS and cingulate cortex, sensorimotor areas, thalamus, insula, operculum, and prefrontal cortex; between the LC and primary motor area and amygdala; and between the RN and sensory and prefrontal regions. In contrast, tGANS affected connectivity between the NTS and temporoparietal junction; between the LC and prefrontal cortex; and between the RN and insula and hippocampus. Changes in FA further supported the sFC findings. Notably, in the taVNS group, an increase in FA was negatively correlated with a decrease in sFC between the LC and precentral cortex.

CONCLUSIONS: Both taVNS and tGANS can modulate functional and structural connectivity between brainstem nuclei of the central vagus nerve pathway and multiple cortical/subcortical regions, albeit through different neural circuits.

CLINICAL TRIAL REGISTRATION: The Clinicaltrials.gov registration number for the study is NCT03959111.

PMID:41091086 | DOI:10.1016/j.neurom.2025.08.415

Arthritis Res Ther. 2025 Oct 14;27(1):190. doi: 10.1186/s13075-025-03640-6.

ABSTRACT

BACKGROUND: Systemic lupus erythematosus (SLE) is a chronic autoimmune disease that often affects the central nervous system (CNS), leading to structural and functional brain alterations. Although neuroimaging studies have reported significant cortical and white matter changes in SLE, findings remain inconsistent, particularly regarding disease duration and organ damage. This study aimed to comprehensively investigate multimodal brain alterations in SLE using structural and functional neuroimaging.

METHODS: This cross-sectional study included 30 SLE patients without overt neuropsychiatric manifestations and 34 age-matched healthy controls (HCs). Neuroimaging data were acquired using a 3 T magnetic resonance imaging (MRI) scanner. Structural analyses included cortical and subcortical volume measurements via FreeSurfer (30 SLE, 34 HC) and white matter connectometry based on diffusion tensor imaging (DTI) using DSI Studio (29 SLE, 28 HC). Interhemispheric functional connectivity was assessed using resting-state fMRI in the CONN toolbox (27 per group). Clinical assessments included the SLEDAI-2 K, SLICC Damage Index, and SLICC Frailty Index, along with neurocognitive tests that assessed working memory, psychomotor speed, and executive function. Statistical analyses involved ANCOVA adjusted for age and intracranial volume, along with correlation analyses to explore associations between neuroimaging findings and clinical or neurocognitive measures.

RESULTS: SLE patients exhibited significantly reduced volumes in the right occipital lobe (F = 11.274, η2 = 0.153, corrected p = .008) and left thalamus (F = 10.502, η2 = 0.140, corrected p = .028). DTI revealed reduced fractional anisotropy (FA) in the corpus callosum, right cingulum, and brainstem. FA values negatively correlated with disease duration, especially in the left and right inferior fronto-occipital fasciculi and the left cingulum. Patients with organ damage exhibited further FA reductions in the brainstem and left cingulum. FA decreases were also associated with poorer cognitive performance. While global interhemispheric functional connectivity was preserved, patients with moderate disease activity showed reduced connectivity in the frontal operculum and insula.

CONCLUSIONS: Even in the absence of overt neuropsychiatric symptoms, SLE patients demonstrated structural brain changes-specifically reduced occipital and thalamic volumes and widespread white matter disruptions-associated with disease duration, organ damage, and neurocognitive dysfunction. Functional interhemispheric connectivity was globally preserved but impaired in the moderate activity subgroup.

PMID:41088383 | DOI:10.1186/s13075-025-03640-6

Proc Natl Acad Sci U S A. 2025 Oct 21;122(42):e2425388122. doi: 10.1073/pnas.2425388122. Epub 2025 Oct 13.

ABSTRACT

Altered psychomotor behavior in psychosis is poorly understood. Novel insights into the physiology of the motor cortex prompted a revision of the motor homunculus. Next to core motor effector areas, the primary motor cortex (M1) contains intereffector regions with more integrative connectivity patterns, suggestive of serving psychomotor behavior. Here, we test whether patterns of connectivity differ between patients with and without psychomotor slowing and which cortical areas are associated with aberrant motor behavior in psychosis. This resting-state functional MRI study included 83 patients with psychosis and psychomotor slowing, 43 patients without psychomotor slowing, and 63 matched healthy subjects. We tested group differences in connectivity and regressed motor behavior measures with connectivity in patients with psychomotor slowing. Across subjects, we found distinct rs-fMRI connectivity profiles of the intereffector areas in M1, extending to premotor cortices and cerebellum. Patients with psychomotor slowing had stronger connectivity from the intereffectors than controls or patients without slowing. Finally, motor behavior correlated with connectivity from M1 intereffector regions in patients. Connectivity profiles of intereffectors suggest a role in planning and controlling complex behavioral repertoires. Collectively, these findings in patients with psychomotor slowing stress the importance of intereffector regions in shaping psychomotor behaviors in mental disorders.

PMID:41082669 | DOI:10.1073/pnas.2425388122

Elife. 2025 Oct 13;13:RP101688. doi: 10.7554/eLife.101688.

ABSTRACT

The resting primate brain is traversed by spontaneous functional connectivity patterns that show striking differences between conscious and unconscious states. Transcranial direct current stimulation (tDCS), a non-invasive neuromodulatory technique, can improve signs of consciousness in disorders of consciousness (DOCs); however, can it influence both conscious and unconscious dynamic functional connectivity? We investigated the modulatory effect of prefrontal cortex (PFC) tDCS on brain dynamics in awake and anesthetized non-human primates using functional MRI. In awake macaques receiving either anodal or cathodal tDCS, we found that cathodal stimulation robustly disrupted the repertoire of functional connectivity patterns, increased structure-function correlation (SFC), decreased Shannon entropy, and favored transitions toward anatomically based patterns. Under deep sedation, anodal tDCS significantly altered brain pattern distribution and reduced SFC. The prefrontal stimulation also modified dynamic connectivity arrangements typically associated with consciousness and unconsciousness. Our findings offer compelling evidence that PFC tDCS induces striking modifications in the fMRI-based dynamic organization of the brain across different states of consciousness. This study contributes to an enhanced understanding of tDCS neuromodulation mechanisms and has important clinical implications for DOCs.

PMID:41081761 | DOI:10.7554/eLife.101688

Neuroimage Rep. 2025 Sep 26;5(4):100291. doi: 10.1016/j.ynirp.2025.100291. eCollection 2025 Dec.

ABSTRACT

BACKGROUND: Research has linked individual differences in resting state functional connectivity (RSFC) of subcortical brain regions to internalizing disorders, but little research has examined if these changes are pre-morbid risk factors. This study examined individual differences in subcortical RSFC as risk factors for the first lifetime onset of an internalizing disorder in youth at familial risk.

METHODS: Participants (n = 93) were adolescents with a parental history of internalizing disorders, but with no such history themselves. Youth completed resting state fMRI scans, as well as the MINI-Kid and the Youth Self Report internalizing symptoms scale at baseline. The MINI-Kid was completed again at 9 or 18-month follow-up to assess onset of internalizing disorders. Seed-to-whole brain analyses consisted of a multiple regression models controlling for sex, age, in scanner motion, and baseline symptoms.

RESULTS: First onsets at follow-up were associated with increased baseline RSFC between the left caudate and the bilateral SMA (pFDR = .002), and between the right nucleus accumbens and the right superior parietal lobule (pFDR = .0003).

CONCLUSION: Altered RSFC of subcortical regions may represent a pre-morbid risk factor for developing a first onset of an internalizing disorder. Results may have implications for understanding the neural bases of internalizing disorders and for early identification and prevention efforts.

PMID:41081250 | PMC:PMC12510205 | DOI:10.1016/j.ynirp.2025.100291

Quant Imaging Med Surg. 2025 Oct 1;15(10):8938-8952. doi: 10.21037/qims-2025-81. Epub 2025 Sep 18.

ABSTRACT

BACKGROUND: Gouty arthritis (GA) is a common inflammatory disease characterized by severe pain and hyperuricemia (HUA). To date, the interaction between GA and cognitive function has remained unclear. This study aimed to investigate the cognitive impairment and related brain function changes in GA patients.

METHODS: A total of 21 male GA patients and 21 age-, gender-, and education-matched healthy controls (HC) were recruited. All participants underwent multimodal functional magnetic resonance imaging (fMRI) examinations and completed the Montreal Cognitive Assessment (MoCA) scale. We utilized supervised machine learning (ML) models based on whole-brain functional connectivity of resting-state fMRI (rs-fMRI) to distinguish GA patients from HC and exported the significantly neuroanatomical regions as functional connectivity matrices features. Meanwhile, task-state fMRI (ts-fMRI) performed during a mental rotation task (MRT) was used to investigate brain functional alterations associated with visuospatial working memory (VSWM) in GA patients.

RESULTS: GA patients performed worse on MoCA scores and MRT behavioral performance than the HC group (P<0.001). The support vector machine (SVM) model demonstrated superior classification performance (P<0.05) in rs-fMRI compared to other supervised learning models, with a classification accuracy of 77.78% and an area under the curve (AUC) of 0.7685. Functional connectivity with nodes in the cuneus, superior occipital gyrus, inferior parietal lobule, superior parietal gyrus, and middle frontal gyrus frequently appeared in the model's weight coefficient matrix. Compared to the HC group, GA patients showed abnormal activation in fMRI results during the MRT, especially in the left inferior parietal lobule and right hippocampus during the 100° rotation task (P<0.05).

CONCLUSIONS: This study comprehensively reveals VSWM impairment in GA patients and identifies the related brain activation differences in the frontoparietal network and diagnosis of cognitive impairment in GA patients and for further research on the underlying neural mechanisms.

PMID:41081237 | PMC:PMC12514683 | DOI:10.21037/qims-2025-81

Quant Imaging Med Surg. 2025 Oct 1;15(10):9921-9936. doi: 10.21037/qims-2025-93. Epub 2025 Sep 17.

ABSTRACT

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication deficits and repetitive behaviors. Neurobiomarkers for ASD are lacking, which hinders early diagnosis and personalized treatment. This study aimed to identify potential biomarkers for ASD using complex network analysis, specifically causal brain networks, to identify functional closed-loop pathways in the brains of children with ASD.

METHODS: The study included 58 ASD patients and 57 typically developing (TD) children ages 6-12 years. Brain causal networks and temporal-lag networks were constructed using a deep learning model to infer the causal relationships between brain regions and the temporal-lag of signal transmissions. Statistical analysis was performed to compare differences between the TD and ASD groups and to identify the potential associations between different symptoms of the ASD group.

RESULTS: The results revealed numerous aberrant functional pathways, mainly located in the junction of the frontal and parietal lobes, as well as the occipital lobes, in children with ASD, when compared to TD children. Three closed-loop pathways were significantly negatively correlated with the total score of the combined social-communication domain in the Autism Diagnostic Observation Schedule, Second Edition (ADOS-2), including lenticular nucleus putamen left (PUT.L)→lenticular nucleus pallidum right (PAL.R)→PUT.L (r=-0.448, P=0.001), PAL.R→lenticular nucleus putamen right (PUT.R)→PAL.R (r=-0.362, P=0.012), and insula right (INS.R)→Heschl gyrus right (HES.R)→INS.R (r=-0.345, P=0.016). Importantly, a positive interaction among these closed-loop pathways was observed with a weak intensity, indicating that social impairments and stereotyped behaviors were interrelated with a weak effect in children with ASD.

CONCLUSIONS: The study showed the potential of identifying multiple abnormal closed-loop pathways using complex network analysis in aiding early diagnosis and treatment of ASD. These findings provided insights into the neurobiological basis of social impairments and stereotyped behaviors in children with ASD, which may aid in the development of personalized interventions and therapeutic targets for this disorder.

PMID:41081232 | PMC:PMC12514598 | DOI:10.21037/qims-2025-93

Quant Imaging Med Surg. 2025 Oct 1;15(10):9362-9374. doi: 10.21037/qims-24-1843. Epub 2025 Sep 16.

ABSTRACT

BACKGROUND: The neural mechanisms associated with age-related hearing loss (ARHL) and their broader implications for brain function remain incompletely understood. This study explored the dynamic network reconfiguration in ARHL using dynamic graph theory and multilayer network analysis.

METHODS: Resting-state functional magnetic resonance imaging (MRI) assessments were conducted on 62 patients with ARHL and 58 healthy controls (HCs) matched for age (≥60 years), sex (ARHL: 32 males, 30 females; HCs: 30 males and 28 females), and education level (all at least 8 years). Cognitive performance was comprehensively assessed in both groups with a battery of standardized neuropsychological tests. Dynamic brain functional networks were analyzed via graph theory to investigate local and global network metrics. Multilayer network analysis was employed to identify changes in global brain network exchanges in ARHL. Spearman correlation analysis was used to calculate the relationship between functional MRI data and cognitive scores.

RESULTS: No demographic differences were observed between patients with ARHL and HCs (P>0.05). However, patients with ARHL exhibited significantly poorer pure-tone audiometry results (P<0.001) and inferior performance on both Trail Making Test-B and Complex Figure Test delayed tests (P<0.05). The ARHL group exhibited reduced local efficiency (P=0.01) and increased node efficiency (P=0.00054). Significant differences in network-switching rates were observed in the left orbital middle frontal gyrus (P=0.006), right frontal orbital inferior (P=0.032), right olfactory cortex (P=0.010), left medial superior frontal gyrus (P=0.045), right middle occipital gyrus (P=0.021), right superior parietal gyrus (P=0.008), left inferior parietal lobule (P=0.034), right caudate nucleus (P=0.020), left globus pallidus (P=0.007), and left superior temporal pole (TPOsup.L) (P=0.022). The network-switching rate of the left TPOsup in the ARHL group was positively correlated with cognitive scores (r=0.270; P=0.034).

CONCLUSIONS: Based on dynamic graph theory and multilayer network analysis, abnormal dynamic network reconfiguration in patients with ARHL were revealed, with reduced network-switching rates in several brain regions. These findings highlight the functional significance of network-switching rates and provide new insights into the neural mechanisms associated with ARHL.

PMID:41081212 | PMC:PMC12514650 | DOI:10.21037/qims-24-1843

Imaging Neurosci (Camb). 2025 Oct 9;3:IMAG.a.918. doi: 10.1162/IMAG.a.918. eCollection 2025.

ABSTRACT

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of premature mortality among people with epilepsy. Evidence from witnessed and monitored SUDEP cases indicates seizure-induced cardiovascular and respiratory failures; yet, the underlying mechanisms remain obscure. SUDEP occurs often during the night and early morning hours, suggesting that sleep or circadian rhythm-induced changes in physiology contribute to the fatal event. Resting-state functional MRI (fMRI) studies have found altered functional connectivity between brain structures involved in cardiorespiratory regulation in later SUDEP cases and in individuals at high risk of SUDEP. However, those connectivity findings have not been related to changes in cardiovascular or respiratory patterns. Here, we compared fMRI patterns of brain connectivity associated with regular and irregular cardiorespiratory rhythms in SUDEP cases with those of living epilepsy patients of varying SUDEP risk and healthy controls. We analysed resting-state fMRI data from 98 patients with epilepsy (9 who subsequently succumbed to SUDEP, 43 categorized as low SUDEP risk (no tonic-clonic seizures (TCS) in the year preceding the fMRI scan), and 46 as high SUDEP risk (>3 TCS in the year preceding the scan)), and 25 healthy controls. The global signal amplitude (GSA), defined as the moving standard deviation of the fMRI global signal, was used to identify periods with regular ("low state") and irregular ("high state") cardiorespiratory rhythms. Correlation maps were derived from seeds in 12 regions with a key role in autonomic or respiratory regulation for the low and high states. Following principal component analysis, component weights were compared between the groups. We found widespread alterations in connectivity of precuneus/posterior cingulate cortex in epilepsy compared with controls in the low state (regular cardiorespiratory activity). In the low state, and to a lesser degree in the high state, reduced anterior insula connectivity (mainly with anterior and posterior cingulate cortex) in epilepsy appeared, relative to healthy controls. For SUDEP cases, the insula connectivity differences were inversely related to the interval between the fMRI scan and death. The findings suggest that anterior insula connectivity measures may provide a biomarker of SUDEP risk. The neural correlates of autonomic brain structural activity associated with different cardiorespiratory rhythms may shed light on the mechanisms underlying the fatal event in SUDEP.

PMID:41079767 | PMC:PMC12511790 | DOI:10.1162/IMAG.a.918

Front Neurosci. 2025 Sep 26;19:1645903. doi: 10.3389/fnins.2025.1645903. eCollection 2025.

ABSTRACT

BACKGROUND: Functional stability within brain networks, particularly the sensorimotor network (SMN), is crucial for coherent motor control. Temporal Interference (TI) stimulation offers a non-invasive method to modulate deep brain structures like the striatum, yet its impact on dynamic functional stability across motor networks remains largely unexplored.

METHODS: Twenty-six healthy male participants separately underwent TI stimulation and Sham stimulation in a crossover, double-blind, randomized controlled trial with counterbalanced protocol. resting-state functional magnetic resonance imaging (rs-fMRI) was acquired before and during the stimulation. A total of 20 min TI stimulation (10 mA, Δf = 20 Hz) was applied to the right striatum using personalized electrode montages optimized. Dynamic functional connectivity (dFC) was computed using a sliding-window approach. Voxel-wise functional stability across the whole brain was quantified by Kendall's concordance coefficient of voxel-to-voxel dFC. Seed-based dFC variability in the right striatum was measured as the standard deviation of dFC across windows.

RESULTS: (1) Functional stability: TI stimulation significantly decreased functional stability in bilateral SMA regions (predominantly SMA proper, with parts of pre-SMA) compared to Sham and baseline conditions (P < 0.01). (2) Dynamic functional connectivity: TI stimulation reduced dFC variability between the right striatum and left SMA region (predominantly SMA proper, with parts of pre-SMA) compared to baseline (P < 0.01). (3) Safety: No adverse cognitive effects or side effects were observed, with good blinding effectiveness maintained throughout the study.

CONCLUSION: Our findings indicate that TI stimulation targeting the striatum effectively modulates sensorimotor network stability and dFC variability within the cortico-striatal pathway, highlighting its potential as a non-invasive neuromodulation approach for motor network disorders.

CLINICAL TRIAL REGISTRATION: [www.chictr.org.cn;], identifier [ChiCTR2500098699].

PMID:41079480 | PMC:PMC12511026 | DOI:10.3389/fnins.2025.1645903

Pediatr Res. 2025 Oct 11. doi: 10.1038/s41390-025-04460-9. Online ahead of print.

ABSTRACT

BACKGROUND: Alterations in dynamic brain functional connectivity (dFC) have been observed in epilepsy, few studies have directly compared the dynamic functional network connectivity (dFNC) patterns between patients with self-limited epilepsy with centrotemporal spikes (SeLECTS) and those with childhood absence epilepsy (CAE). This study aimed to explore differences in dFNC between these two epilepsy types and investigate how these patterns relate to clinical features.

METHODS: Resting-state functional MRI data were collected from 34 SeLECTS patients, 22 CAE patients, and 32 healthy controls. Independent component analysis (ICA) was combined with a sliding-window technique to examine characteristics of dynamic FNC, including state transitions, connectivity strength, and temporal properties.

RESULTS: Three recurring dFNC states were identified. SeLECTS patients spent significantly more time in a highly flexible state characterized by strong network integration, whereas CAE patients more frequently occupied a state marked by weak inter-network connectivity. Furthermore, SeLECTS patients showed greater variability in dFNC states over time. Certain clinical factors-particularly seizure frequency-were found to correlate with specific dFNC states, most notably in the SeLECTS group.

CONCLUSIONS: The study highlights distinct dynamic connectivity patterns between SeLECTS and CAE patients, suggesting that these two epilepsy types involve different network-level mechanisms. These findings contribute to a deeper understanding of epilepsy subtypes and may inform future diagnostic and treatment strategies.

IMPACT: This study identifies distinct dFNC patterns in two common childhood epilepsies: SeLECTS and CAE. It demonstrates the value of dynamic resting-state brain network analysis in pediatric epilepsy. These findings provide new neuroimaging biomarkers for early classification of epilepsy subtypes. Results may contribute to the development of personalized diagnosis and treatment strategies in children with epilepsy.

PMID:41076473 | DOI:10.1038/s41390-025-04460-9

J Affect Disord. 2025 Oct 9:120396. doi: 10.1016/j.jad.2025.120396. Online ahead of print.

ABSTRACT

BACKGROUND: Emerging evidence suggests that individuals with major depressive disorder (MDD) at risk for bipolar disorder (BD) may represent a distinct subtype within the mood disorder spectrum. However, the neurocognitive and neurofunctional characteristics of this group remain underexplored.

METHODS: Resting-state fMRI and cognitive assessments were obtained from currently depressed participants. BD risk factors were identified by Hypomania Checklist-32 (HCL-32) scores ≥14 and/or a first-degree family history of BD. 139 BD, 181 MDD+ (with BD risk), and 138 MDD- (without BD risk) patients were identified. Neuroimaging analyses included the amplitude of low-frequency fluctuations (ALFF) and seed-based functional connectivity (FC). Correlational analyses were conducted to explore the relationships among clinical characteristics, neuroimaging indices, and cognitive performance.

RESULTS: Compared to MDD-, MDD+ demonstrated increased ALFF in the right postcentral gyrus and stronger intra-regional and inter-regional FC with the left supramarginal gyrus. Relative to BD, MDD+ showed reduced ALFF in the left putamen and weakened FC between with the right precuneus. MDD+ also outperformed both MDD- and BD in processing speed and cognitive flexibility. In MDD+, ALFF in the left putamen correlated with processing speed. In BD, ALFF in the left cuneus correlated positively with mania severity and negatively with family history. However, brain-behavior associations did not survive correction for multiple comparisons.

CONCLUSIONS: MDD+ demonstrated distinct cognitive and neural patterns, supporting the notion of a unique depressive subtype. These findings emphasize the importance of refined phenotyping to facilitate early recognition and personalized treatment strategies.

PMID:41076154 | DOI:10.1016/j.jad.2025.120396

J Affect Disord. 2025 Oct 9:120406. doi: 10.1016/j.jad.2025.120406. Online ahead of print.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is a chronic and relapsing condition. This study aims to investigate alterations in structural-functional connectivity (SC-FC) coupling in patients with MDD and their associations with clinical profiles, particularly with episode status.

METHODS: SC-FC coupling was calculated from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) data collected in 124 patients with MDD and 97 healthy controls (HCs). Primary analysis focused on group-level differences in SC-FC coupling between MDD and HCs, and its correlations with clinical symptom severity. Secondary analysis aimed to detect SC-FC coupling differences between first-episode MDD (fMDD, n = 77) and recurrent MDD (rMDD, n = 52) subgroups.

RESULTS: Compared with HCs, patients exhibited increased SC-FC coupling in the left orbital gyrus, left inferior frontal gyrus, right superior temporal gyrus (rSTG), bilateral inferior parietal lobule, bilateral postcentral gyrus and left insula, which mainly located at the default mode network (DMN), somatomotor network (SMN), frontoparietal network (FPN), and dorsal lateral attention network (DAN). The increased SC-FC coupling of the left orbital gyrus was correlated with more severe depressive and anxiety symptoms. Meanwhile, specific alterations were identified in rMDD with increased SC-FC coupling in the rSTG.

CONCLUSIONS: This study suggests the general increased SC-FC coupling in MDD, mainly involves the SMN and DMN. A specific alteration pattern of SC-FC coupling in rSTG was identified among MDD with different episode status. These results may shed light on the neuropathological basis of MDD and potential biological markers for predicting its recurrence.

PMID:41076152 | DOI:10.1016/j.jad.2025.120406

Neuroimage. 2025 Oct 9:121520. doi: 10.1016/j.neuroimage.2025.121520. Online ahead of print.

ABSTRACT

Vividness of visual imagery varies considerably across individuals, yet its neural underpinnings remain unclear. As emphasized in recent debates, a key controversy is whether early sensory architecture explains imagery or whether it is explained by interactions of high-level visual and fronto-parietal areas. This study examined how individual differences in imagery vividness, measured via the Vividness of Visual Imagery Questionnaire (VVIQ-2), relate to intrinsic brain network organization using graph theory applied to structural and functional connectomes from diffusion-weighted imaging (DWI; n=525) and resting-state fMRI (n=556). Connectivity was assessed in an imagery-specific network and three canonical resting-state networks: occipital, salience, and default mode. In functional connectivity analyses, vividness correlated positively with local efficiency in the left fusiform gyrus, a high-level visual region implicated in integrative imagery processes. In structural connectivity analyses, higher vividness was associated with greater local efficiency and clustering in the occipital network, suggesting that vivid imagery depends on well-segregated low-level visual networks. Additionally, greater global efficiency in the right insular cortex-a key salience network hub-was linked to vividness, indicating that efficient salience-driven control may stabilize internal imagery. Multivariate analysis found that no single factor explained imagery better than a combined model, with the fusiform imagery node (FIN) as the strongest single predictor, while other structural factors contributed to the best overall model. These findings reconcile competing accounts of imagery by demonstrating that vivid imagery emerges from the interplay between sensory-based structural networks, salience-based regulatory hubs, and higher-order visual integration.

PMID:41076035 | DOI:10.1016/j.neuroimage.2025.121520

Hum Brain Mapp. 2025 Oct 1;46(14):e70352. doi: 10.1002/hbm.70352.

ABSTRACT

Neuromodulation of subcortical network hubs by pharmacologic, electrical, or ultrasonic stimulation is a promising therapeutic strategy for patients with disorders of consciousness (DoC). However, optimal subcortical targets for therapeutic stimulation are not well established. Here, we leveraged 7 Tesla resting-state functional MRI (rs-fMRI) data from 168 healthy subjects from the Human Connectome Project to map the subcortical connectivity of six canonical cortical networks that modulate higher-order cognition and function: the default mode, executive control, salience, dorsal attention, visual, and somatomotor networks. Based on spatiotemporally overlapped networks generated by the Nadam-Accelerated SCAlable and Robust (NASCAR) tensor decomposition method, our goal was to identify subcortical hubs that are functionally connected to multiple cortical networks. We found that the ventral tegmental area (VTA) in the midbrain and the central lateral and parafascicular nuclei of the thalamus-regions that have historically been targeted by neuromodulatory therapies to restore consciousness-are subcortical hubs widely connected to multiple cortical networks. Further, we identified a subcortical hub in the pontomesencephalic tegmentum that overlapped with multiple reticular and extrareticular arousal nuclei and that encompassed a well-established "hot spot" for coma-causing brainstem lesions. Multiple hubs within the brainstem arousal nuclei and thalamic intralaminar nuclei were functionally connected to both the default mode and salience networks, emphasizing the importance of these cortical networks in integrative subcortico-cortical signaling. Additional subcortical connectivity hubs were observed within the caudate head, putamen, amygdala, hippocampus, and bed nucleus of the stria terminalis, regions classically associated with modulation of cognition, behavior, and sensorimotor function. Collectively, these results suggest that multiple subcortical hubs in the brainstem tegmentum, thalamus, basal ganglia, and medial temporal lobe modulate cortical function in the human brain. Our findings strengthen the evidence for targeting subcortical hubs in the VTA, thalamic intralaminar nuclei, and pontomesencephalic tegmentum to restore consciousness in patients with DoC. We release the subcortical connectivity maps to support ongoing efforts at therapeutic neuromodulation of consciousness.

PMID:41074653 | DOI:10.1002/hbm.70352