Most recent paper

Eur Child Adolesc Psychiatry. 2026 Oct 26. doi: 10.1007/s00787-026-03237-7. Online ahead of print.

ABSTRACT

Children with ADHD exhibit decision-making deficits characterized by lower efficiency in evidence accumulation and a preference for smaller, sooner rewards in intertemporal choices. This study aimed to preliminarily explore computational subtypes of ADHD in children and to investigate differences in prefrontal functional connectivity between ADHD subtypes. A total of 94 children with ADHD and 63 typically developing children matched for sex, age, and IQ were included. All participants completed the Two Choice Impulsivity Paradigm (TCIP) and the ADHD Symptom Rating Scale, and 43 children with ADHD underwent resting-state fMRI. A hierarchical drift diffusion model was applied to analyze TCIP task performance, followed by two-step cluster analysis to identify decision-making subtypes. Differences in prefrontal functional connectivity among ADHD decision-making subtypes were then compared. The ADHD group showed fewer square selections in the TCIP (p < 0.001), lower drift rates (pBayes < 0.001), and shorter non-decision times (pBayes = 0.002). Two decision-making subtypes were identified: a decision-making deficit subtype and a decision-making normal subtype, characterized by lower and higher drift rates, respectively. The ADHD decision-making deficit subtype exhibited stronger functional connectivity between the left medial superior frontal gyrus and both the right middle frontal gyrus and the right postcentral gyrus, as well as between the right medial superior frontal gyrus and the right postcentral gyrus (all p < 0.05). The results reveal decision-making deficits and internal heterogeneity in children with ADHD during intertemporal choice, with this heterogeneity possibly associated with abnormal functional connectivity between the medial superior frontal gyrus and the middle frontal gyrus/postcentral gyrus.

PMID:42931927 | DOI:10.1007/s00787-026-03237-7

Neurol Int. 2026 Oct 13;18(10):191. doi: 10.3390/neurolint18100191.

ABSTRACT

Background: Alzheimer's disease (AD) is an irreversible neurodegenerative disorder where early diagnosis at the mild cognitive impairment (MCI) stage is critical for timely intervention. While structural MRI (sMRI) and resting-state functional MRI (rs-fMRI) provide complementary pathological information, clinical translation is limited by high feature heterogeneity and the heavy computational burden of 3D deep learning networks. This study aims to propose a lightweight, hybrid multimodal fusion model to overcome these limitations and improve diagnostic efficiency. Methods: A lightweight MobileViT-XS network was utilized to extract global and local pathological features from gray-matter sMRI images to reduce computational costs. Concurrently, graph theory was applied to rs-fMRI data to construct brain functional networks and calculate global topological properties. Following pretraining, feature-level fusion was performed to integrate sMRI features, rs-fMRI properties, demographic information, and two clinical neuropsychological examinations. Results: The validation results show that the proposed hybrid model achieved high diagnostic performance in the three-class classification task, yielding an accuracy of 0.928 ± 0.010, sensitivity of 0.901 ± 0.014, precision of 0.933 ± 0.014, and an F1 score of 0.911 ± 0.012. On the held-out testing subset of the independently collected dataset after dataset-specific fine-tuning, the proposed model achieved an accuracy of 0.857, with a sensitivity of 0.867, a precision of 0.867, and an F1 score of 0.859. Conclusions: The proposed framework successfully minimizes computational overhead while maintaining high classification accuracy. These findings suggest that the hybrid multimodal fusion model provides a promising computer-aided approach for three-class classification of AD, MCI, and NC.

PMID:42931145 | DOI:10.3390/neurolint18100191

Mol Pain. 2026 Jan-Dec;22:17448069261491126. doi: 10.1177/17448069261491126. Epub 2026 Oct 26.

ABSTRACT

Background: Both depressive and pain symptoms are highly prevalent and relevant comorbid conditions in Veterans with Gulf War Illness (GWI). This study assessed how the severity of depressive symptoms may affect supraspinal pain modulatory functional connectivity (FC) in Veterans with GWI-related chronic Headache And body, muscle, and joint Pain conditions (GWI-HAP) and how depressive symptoms alone or paired with pain symptomology or other neuropsychological and functional assessments were able to predict supraspinal functional connectivity (FC) relevant to pain modulation. Methods: Resting state functional MRI (rs-fMRI) conducted in Veterans with GWI-HAP and moderate to severe depressive symptoms reflected by the Hamilton Rating Scale for Depression (HRSD) score <14(GWI ≥ 14) and their counterparts with no or mild depressive symptoms (GWI<14) were compared along with pain symptomology, functional, quality of life, and Post-Traumatic Stress Disorder assessments. Results: Region of interest (ROI)-to-ROI rs-fMRI FC analyses indicated the GWI ≥ 14 group (N=33) showed significantly enhanced FC of the left dorsolateral prefrontal cortex (DLPFC) with the contralateral Insula (BA 13; P < 0.001; T= 7.14), visuomotor cortex (BA7, P<0.01, T=4.82) and two regions of contralateral thalamus (P < 0.01, P < 0.001; T= 5.32, T= 5.25, respectively); and decreased FC with the ipsilateral premotor cortex (BA 6; P < 0.01; t = -3.34) and contralateral anterior cingulate cortex (BA 32; P < 0.001; T= -3.64) than the GWI<14 group (N=33). Independent T-tests also indicated that the GWI ≥ 14 group demonstrated a significantly (P<0.05) higher level of pain severity, functional, and quality of life impairments, and PTSD symptomology in comparison with the GWI<14 group. Stepwise regression analyses of the combined group indicated that despite the detected significant between-group difference in supraspinal FC of the left DLPFC to other pain-relevant supraspinal regions, either the degree of depressive symptoms or any other study assessment was able to reliably predict the FC of the left DLPFC to the right ACC. In addition, other assessments alone did not reliably predict the left DLPFC to other pain relevant ROI. However, adding other pain symptomology, neuropsychological, and functional assessments to depressive symptom severity assessment can enhance the prediction of the supraspinal FC relevant to pain modulation. Conclusions: While significant between-group differences in supraspinal modulatory FC were found based on the severity of depressive symptoms, pain symptomology, functional, and quality of life impairments, these assessments alone did not predict the FC correlation of left the DLPFC in most detected ROI differences. However, individually pairing mood with other pain and functional assessments can enhance the prediction of the underlying supraspinal pain modulatory FC. Potential non-invasive brain stimulation interventions such as TMS with various treatment targeting options, which are applicable for addressing these highly prevalent co-morbid conditions and functional impairments, may incorporate this mechanistic correlation and prediction in formulating a corresponding therapeutic strategy.

PMID:42929460 | DOI:10.1177/17448069261491126

CNS Neurosci Ther. 2026 Oct;32(10):e71231. doi: 10.1002/cns.71231.

ABSTRACT

OBJECTIVE: To evaluate the effects of cerebellar continuous theta burst stimulation (cTBS) in insomnia disorder (ID).

METHODS: In this randomized sham-controlled trial, patients with ID received 2 weeks of active or sham cerebellar cTBS. The primary outcome was a ≥ 3-point improvement in Pittsburgh Sleep Quality Index (PSQI) score after treatment. Secondary outcomes included changes in sleep, mood, and resting-state fMRI.

RESULTS: Seventy-two patients (51 women; mean age, 44.3 ± 11.6 years) were included in the intention-to-treat analysis. More patients in the active than sham group achieved a ≥ 3-point PSQI improvement after treatment (75.0% vs. 33.3%; adjusted OR, 6.06; 95% CI, 2.17-18.50; p < 0.001). Active cTBS reduced PSQI scores versus sham both post-treatment (adjusted mean difference, -3.34; 95% CI, -4.57 to -2.12; p < 0.001) and at 1 month (-3.70; 95% CI, -4.93 to -2.48; p < 0.001), and also improved Insomnia Severity Index, Hamilton Anxiety Scale, and Hamilton Depression Scale at both time points (all p < 0.01). Exploratory fMRI analyses identified several post-treatment connectivity differences between groups, but only right amygdala-right orbitofrontal connectivity showed a significant group-by-time interaction (FDR-adjusted p = 0.038). No serious adverse events occurred.

CONCLUSION: Cerebellar cTBS was well tolerated and promising for ID.

TRIAL REGISTRATION: ClinicalTrials.gov (NCT05992285).

PMID:42929074 | DOI:10.1002/cns.71231

PeerJ. 2026 Oct 22;14:e21811. doi: 10.7717/peerj.21811. eCollection 2026.

ABSTRACT

BACKGROUND: Dance and music are two of the oldest and most universal forms of artistic expression, each requiring extensive training. Prolonged training is known to induce neuroplastic changes and enhance socio-emotional abilities such as empathy. The mirror neuron system (MNS) is associated with empathy; however, few studies systematically explored how dance and music training modulate the core empathy network, including subcortical regions within the limbic MNS.

METHOD: Resting-state functional magnetic resonance imaging (fMRI) data were obtained from 25 dancers, 24 musicians and 39 demographically matched control group (both groups are healthy). Core regions within relevant brain networks, along with key subcortical components of limbic MNS, specifically the amygdala and basal ganglia, were defined as regions of interest (ROIs) to build a core empathy network. Graph-theoretical metrics, including within-network degree (WND) and between-network degree (BND), were calculated to evaluate connectivity patterns. These metrics were further correlated with empathy scores.

RESULTS: Both dancers and musicians exhibited altered connectivity within the core empathy network. Dancers showed increased WND and BND between basal ganglia regions and the ventral attention network, whereas musicians demonstrated enhanced WND between the amygdala and the subcortical network. Notably, both groups exhibited reduced WND between the superior frontal gyrus and the sensorimotor network. The neural changes were correlated with Interpersonal Reactivity Index (IRI) empathy subscale scores, indicating training-related modulations in affective and cognitive empathy.

CONCLUSION: Dance and music training induce both distinct and overlapping patterns of neuroplasticity within the core empathy network that are associated with enhanced empathic ability. The findings support the potential of dance and music as systematic intervention programs.

PMID:42928792 | PMC:PMC13695966 | DOI:10.7717/peerj.21811

J Cachexia Sarcopenia Muscle. 2026 Oct;17(5):e70411. doi: 10.1002/jcsm.70411.

ABSTRACT

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a devastating neuromuscular disease characterised by progressive muscle wasting and functional decline. Although cortical motor network disruption is a hallmark of ALS, the large-scale functional hierarchy alterations and their underlying molecular mechanisms in the early stage of the disease (ALS-ES) remain poorly understood. We aimed to characterise cortical gradient changes in early-stage ALS and to examine their neurochemical and transcriptomic correlates, as well as their cross-sectional associations with clinical functional status.

METHODS: We recruited 97 patients with early-stage ALS, all at King's stage 1 and 94 healthy controls with comparable age and sex distributions. The ALS-ES group included 65 women and had a median ALSFRS-R score of 40 (IQR, 37-44). Resting-state fMRI was used to construct the principal functional gradient. We integrated neurochemical maps of 19 neurotransmitter receptors/transporters, and transcriptomic data from the Allen Human Brain Atlas. Partial least squares (PLS) regression and cell-type enrichment analysis were employed to identify molecular correlates of gradient alterations.

RESULTS: Compared with HCs, ALS-ES patients exhibited a significant spatial contraction of the principal gradient. Specifically, gradient values significantly increased in the somatomotor network (SMN; t = 3.670, pFDR = 0.001) and decreased in the default mode network (DMN; t = -4.124, pFDR < 0.001). Within the ALS-ES group, higher SMN gradient values were associated with lower ALSFRS-R scores, whereas higher DMN gradient values were associated with higher ALSFRS-R scores. These macroscale alterations showed spatial correspondence with normative 5-HT4 receptor and norepinephrine transporter maps. PLS analysis identified a primary gene set (PLS1+) enriched in oligodendrocytes and mitochondrial functions (pFDR < 0.05), whereas the negative set (PLS1-) was associated with astrocytes, GABAergic neurons and RNA splicing pathways. Chromosome-level analysis revealed significant enrichment of PLS1- genes on chromosomes 5 and 16 (p < 0.05).

CONCLUSIONS: Early-stage ALS is characterised by a collapsed cortical functional hierarchy centred on the motor-somatosensory axis. These alterations were spatially associated with normative neurochemical maps and distinct transcriptomic annotations related to energy metabolism and RNA processing. These findings identify cross-sectional cortical functional-hierarchy alterations associated with functional status in early-stage ALS and provide a multi-scale framework for investigating their neurochemical and transcriptomic correlates.

PMID:42927931 | DOI:10.1002/jcsm.70411

J Affect Disord. 2026 Oct 25:122665. doi: 10.1016/j.jad.2026.122665. Online ahead of print.

ABSTRACT

Mood-congruent attention in depression has been studied via emotional interference tasks, including tasks comparing responses to sad and happy stimuli. Mood induction offers a way to experimentally induce sad mood in non-clinical samples and examine its association with subsequent emotional interference, including Sad-Happy interference. Previous studies have separately linked resting-state global neural dynamics (synchrony, metastability) to depressive symptoms and attentional processing. However, whether individual differences in baseline global synchrony and metastability relate to how individuals respond to sad mood remains largely unclear. This study therefore examined the relationship between neural dynamics, sadder mood after induction, and Sad-Happy interference. Depressive symptoms also encompass somatic domains alongside cognitive-affective domains, though these are rarely distinguished in neuroimaging studies. We further examined whether baseline neural dynamics and their association with sadder mood and Sad-Happy interference were related to depressive symptoms (total, cognitive-affective, and somatic). Forty-eight non-clinical individuals completed resting-state neuroimaging, mood induction (sad or non-sad), and an emotional Stroop task. We found in a cross-sectional moderated mediation model that sadder mood after induction was associated with greater interference from sad compared to happy stimuli at medium and high levels of global synchrony, particularly in exploratory path models that included somatic symptoms. Findings suggest that individual differences in resting-state global synchrony may be a neural correlate of sadder mood after induction and Sad-Happy interference in non-clinical individuals. This study offers preliminary associations linking neural dynamics, sad mood, emotional interference, and somatic symptoms, providing insights into the role of neural dynamics in emotional and attentional processing.

PMID:42927849 | DOI:10.1016/j.jad.2026.122665

Epilepsy Behav. 2026 Oct 25;186:111322. doi: 10.1016/j.yebeh.2026.111322. Online ahead of print.

ABSTRACT

OBJECTIVE: To compare the differences in functional brain activity between patients with temporal lobe epilepsy comorbid with depressive disorder (TLE-D) and those with temporal lobe epilepsy without depressive disorder (TLE-ND) via a meta‑analysis of resting‑state functional magnetic resonance imaging (rs-fMRI) studies, and to explore the functional brain activity features associated with depressive symptoms.

METHODS: Systematic searches were conducted in PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), and Wanfang Data from database inception to September 2026 to identify cross-sectional studies comparing rs-fMRI-derived differences in functional brain activity between patients with temporal lobe epilepsy comorbid with depressive disorder (TLE-D) and those without depressive disorder (TLE-ND). Eligible rs-fMRI metrics included regional brain activity indices and functional connectivity indices. A meta-analysis of studies reporting regional brain activity indices was performed using anisotropic effect-size signed differential mapping (AES-SDM). Due to their limited number, studies reporting functional connectivity indices were only described narratively. Study selection and data extraction were then completed, and a voxel-based meta-analysis of the included studies was performed with AES-SDM.

RESULTS: A total of six studies yielding nine datasets met the inclusion criteria, involving 100 patients with TLE-D and 108 patients with TLE-ND. Meta-analysis showed that, compared with the TLE-ND group, the TLE-D group had significantly increased spontaneous brain activity in the right precuneus, right angular gyrus, right superior frontal gyrus, left middle frontal gyrus, and left cerebellum (analyzed via AES-SDM with an initial exploratory threshold of uncorrected voxel-level P < 0.005 and cluster size ≥10 voxels, and validated by leave-one-out sensitivity analysis). No brain regions with significantly decreased spontaneous brain activity were detected.

CONCLUSION: These exploratory findings suggest that, compared with patients with TLE-ND, patients with TLE-D show distinct patterns of functional brain activity in multiple key nodes of the default mode network, including the precuneus and angular gyrus, as well as in prefrontal-related regions. These differences may provide preliminary neuroimaging evidence for understanding the neural mechanisms underlying depressive symptoms associated with temporal lobe epilepsy.

PMID:42927711 | DOI:10.1016/j.yebeh.2026.111322

Res Sq [Preprint]. 2026 Oct 6:rs.3.rs-11132707. doi: 10.21203/rs.3.rs-11132707/v1.

ABSTRACT

The Alzheimer's Disease Neuroimaging Initiative (ADNI) provides a comprehensive multimodal neuroimaging resource for studying aging and Alzheimer's disease (AD). However, its resting-state functional MRI (rs-fMRI) data remain underutilized, in part due to challenges with data processing driven by considerable variability in acquisition protocols, inconsistent organization, missing or incomplete imaging sessions, and frequency of data quality issues due to participant motion and aging-related factors. To facilitate widespread use of ADNI rs-fMRI data, we developed an open-source pipeline encompassing the download and organization of imaging and clinical data, conversion to Brain Imaging Data Structure (BIDS), preprocessing with fMRIPrep, and automated quality control (QC). Our QC considers acquisition parameters and 16 structural and functional MRIQC image-quality metrics, flagging scans that fall outside acceptable ranges based on expert input and robust outlier detection techniques. Processed imaging sessions are matched to temporally aligned clinical assessments to produce an analysis-ready dataset. Applying the pipeline to more than 2,800 sessions from ADNI GO, ADNI 2, and ADNI 3 yielded 2,086 quality-checked functional and structural MRI sessions from 935 unique participants. Exclusions occurred at every processing stage and were driven primarily by BIDS conversion errors, image quality flags, and preprocessing- or motion-related failures. The open-source pipeline described in this work produces one of the largest pre-processed, quality controlled, and analysis-ready functional and structural MRI datasets yet available for studying aging and AD. It lowers barriers to large-cohort and longitudinal neuroimaging research and supports large-scale neuroimaging biomarker discovery in AD.

PMID:42926671 | PMC:PMC13692585 | DOI:10.21203/rs.3.rs-11132707/v1

Res Sq [Preprint]. 2026 Oct 6:rs.3.rs-10092045. doi: 10.21203/rs.3.rs-10092045/v1.

ABSTRACT

Childhood maltreatment affects 25% of the U.S. population and increases risk for psychopathology, including anxiety disorders, across generations. Before postnatal exposures, offspring with a mother who has a history of childhood maltreatment are born with greater functional connectivity in amygdala-prefrontal stress circuits. Similarly, maternal stress during pregnancy associates with both greater positive and greater inverse amygdala-prefrontal connectivity in infants in a sex-specific manner. Altered newborn amygdala-prefrontal circuits that support stress processing may reflect accelerated neural maturation. Prior studies on associations between maternal history of childhood maltreatment and newborn amygdala connectivity adjust for prenatal maternal stress yet have not examined whether these associations are mediated by prenatal maternal stress. Because history of childhood maltreatment strongly correlates with maternal mental health problems during pregnancy, including stress, depression, sleep problems, and pregnancy specific distress, we test whether these problems mediate the association between maternal history of childhood maltreatment and altered newborn amygdala-prefrontal connectivity. Participants (N = 59) report their history of childhood maltreatment and mental health symptoms in the 3rd trimester. We measure resting state functional connectivity using fMRI in infants (mean age = 3.15 ± 1.42 weeks). Prenatal maternal sleep problems mediate associations between maternal history of childhood maltreatment and infant's amygdala connectivity in both sexes. Pregnancy specific distress mediates the associations in males. Overall, females show greater positive connectivity, whereas males show greater inverse connectivity; mediation findings are more consistent in males. Our study provides evidence that prenatal maternal mental health problems - particularly sleep problems and pregnancy specific distress - link maternal history of childhood maltreatment to newborn amygdala connectivity. These findings highlight modifiable prenatal factors for trauma-responsive intervention.

PMID:42926657 | PMC:PMC13692590 | DOI:10.21203/rs.3.rs-10092045/v1

bioRxiv [Preprint]. 2026 Oct 6:2026.10.05.756754. doi: 10.64898/2026.10.05.756754.

ABSTRACT

BACKGROUND: Auditory verbal hallucinations (AVH) are among the most disabling symptoms of schizophrenia, yet the network-level mechanisms linking auditory dysfunction to hallucination severity remain poorly characterized, limiting targeted therapeutic development.

METHODS: Using resting-state fMRI and high-resolution surface-based parcellation (HCP-MMP), we examined auditory-language functional connectivity and mesoscale network organization in 56 patients with schizophrenia and 22 healthy controls (primary dataset, N=78). Pairwise auditory-language connectivity associations with hallucination severity (PANSS P3) were examined alongside auditory network community structure, assortativity, hub organization, and routing efficiency. To further characterize these parcel-level findings at the vertex level, we applied a region-growing approach to identify auditory-frontal connectivity patterns maximally associated with severity. In silico perturbation analyses tested the causal role of belt cortex connectivity. Key findings were independently replicated in 93 patients from the Human Connectome Project for Early Psychosis (HCP-EP), for a combined total of 171 participants.

RESULTS: Auditory-language connectivity disruptions were concentrated in belt cortex and specifically implicated ventral what-stream connections, with a vertex-wise analysis converging on the same anatomy. Auditory network segregation scaled with hallucination severity, with belt cortex emerging as the primary integrative hub governing auditory-to-language routing efficiency. Perturbation analyses showed that strengthening earlier-hierarchy auditory regions reduced network segregation more than strengthening later-hierarchy regions. Reduced belt cortex coupling and elevated network segregation replicated independently in the HCP-EP sample.

CONCLUSIONS: Auditory network disorganization scales with hallucination severity and replicates across independent samples, with belt cortex as the critical locus of connectivity disruption and network integration failure, identifying it as a candidate neuromodulatory target.

PMID:42926541 | PMC:PMC13692089 | DOI:10.64898/2026.10.05.756754

Psychiatry Res Neuroimaging. 2026 Oct 22;364:112359. doi: 10.1016/j.pscychresns.2026.112359. Online ahead of print.

ABSTRACT

Major depressive disorder (MDD) is increasingly characterized as a disorder of brain dynamics, but the temporal scale on which resting-state activity differs from healthy controls remains unclear. We analyzed resting-state fMRI data from 71 participants (51 MDD, 20 controls; OpenNeuro ds002748) using bilateral grid-extracted left-right difference signals projected into a control-defined latent space. Across 30 analysis configurations spanning five denoising pipelines, three latent dimensionalities, and two left-right correction settings, MDD showed reduced mean lag-1 autocorrelation in 24 of 30 configurations (integrated β = -0.0321, p = 0.036) and reduced AR(1) gain φ in 24 of 30 (β = -0.0316, p = 0.037), both robust to adjustment for pipeline, age, sex, and head motion. The broader autocorrelation area under lags 1-10 was not significantly reduced (β = -0.0099, p = 0.22), and lag-by-lag analysis localized the group difference specifically to lag 1. A model-comparison analysis identified AR-gain reduction as one of three competing candidate generative transformations rather than the unique winner. MDD is thus associated with a focal short-lag autoregressive carry-over reduction, a candidate latent-dynamical phenotype rather than a fully identified mechanism.

PMID:42925650 | DOI:10.1016/j.pscychresns.2026.112359

Res Sq [Preprint]. 2026 Sep 2:rs.3.rs-10581799. doi: 10.21203/rs.3.rs-10581799/v1.

ABSTRACT

In aging, tau pathology can develop in the medial temporal lobe (MTL), but generally only progresses to the cortex in the context of amyloidosis, driving neurodegeneration and Alzheimer's disease (AD) dementia. Functional connectivity shapes this cortical tau expansion, supporting trans-neuronal tau spreading. However, it is unclear whether MTL tau accumulation itself follows within-MTL connections - particularly those of the transentorhinal (Brodmann area 35 [A35]) and entorhinal cortex (ErC), the earliest cortical sites of tau accumulation in AD and variably affected in aging. To address this, we assessed three-dimensional neurofibrillary tangle (NFT) burden across 14 MTL subregions using post-mortem quantitative histopathology in 25 individuals ( n = 4 amyloid-β negative; n = 21 amyloid-β positive) on the AD continuum. These data were combined with high-resolution 7T resting-state functional MRI-based functional connectivity among the same 14 subregions obtained from 30 young healthy controls. We examined covariance in NFT burden across MTL subregions and tested associations with functional connectivity strength. We then applied seed-based connectivity analyses to identify which MTL subregion's connectivity profile best predicted MTL NFT patterns. NFT levels were highest and comparable across A35 (0.62 ± 0.40), posterior cornu ammonis 1 (CA1; 0.61 ± 0.46), anterolateral ErC (alErC; 0.60 ± 0.39), and anterior CA1 (0.57 ± 0.43). We found a significant positive association between MTL connectivity and covariance in MTL NFTs ( β = 0.49, p < 0.001), with closely connected MTL regions showing similar NFT levels. When assessing seed-based connectivity as a predictor of NFT patterns, alErC ( ρ = 0.66, p < 0.001), A36 ( ρ = 0.64, p < 0.001), and posteromedial ErC (pmErC; ρ = 0.59, p < 0.001) connectivity showed the strongest, comparable correspondence with MTL NFT deposition. This pattern was consistent within low (Braak 0-II) and high (Braak III-VI) NFT burden groups. These results suggest that within-MTL tau propagation is shaped by intrinsic network organization, highlighting entorhinal and perirhinal connectivity profiles as potential drivers of MTL tau progression and as candidate targets for therapeutic interventions.

PMID:42922881 | PMC:PMC13684788 | DOI:10.21203/rs.3.rs-10581799/v1

Front Neurol. 2026 Oct 8;17:1943343. doi: 10.3389/fneur.2026.1943343. eCollection 2026.

ABSTRACT

OBJECTIVE: This study combined independent component analysis (ICA)-derived dynamic functional connectivity (dFNC) with dynamic graph theory analysis methods to analyze the changes in dFNC and dynamic graph theoretic indicators in different motor subtypes of Parkinson's disease (PD)-tremor-dominant (TD) subtype and postural instability/gait difficulty (PIGD) subtype-and healthy controls (HC). We aimed to explore the neural circuitry abnormal mechanisms and differences between the two subtypes.

METHODS: Using a prospective observational study design, from January 2021 to May 2024 at Northern Jiangsu People's Hospital, we enrolled 36 diagnosed PD patients according to inclusion criteria-19 patients with PIGD subtype and 17 patients with TD subtype-along with 19 healthy subjects matched for age, sex, and education level. Resting-state functional magnetic resonance imaging (rs-fMRI), demographic information, and clinical motor function assessment data were collected from all participants. The ICA and dynamic functional network connectivity (dFNC) analysis were performed using the GIFT toolbox platform based on MATLAB. Combined with dynamic graph theory analysis, features such as characteristic path length, clustering coefficient, and node degree were extracted. The dFNC and dynamic graph theoretic indicators of the PIGD group, TD group, and HC group were compared horizontally to clarify the common and specific dynamic abnormalities of brain networks between the two subtypes.

RESULTS: Nine functional brain networks were identified through ICA. Significant differences among the three groups were observed in five brain networks: auditory network, left frontoparietal network, right frontoparietal network, ventral attention network, and sensorimotor network. Based on network-to-network functional connectivity analysis using these nine functional brain networks, after strict FDR correction, only inter-network coupling strength between the auditory network and sensorimotor network showed significant group differences (T = 7.548, FDR-corrected p = 0.00137). Four recurring functional connectivity states were identified through dFNC analysis. Across all participants, State 2 and State 3 accounted for 38 and 23% of total time, respectively. PIGD patients tended to spend more time in these two low-connectivity states. In terms of temporal properties, only the occurrence frequency of state 4 showed significant differences among the three groups (F = 4.855, FDR-corrected p = 0.047). Post-hoc test results showed that HC groups were significantly higher than PIGD groups and presented a trend higher than TD groups, while there was no statistically significant difference between the two PD subtypes. One-way analysis of variance was performed on whole-brain node-to-node functional connectivity and graph theoretic attributes of the three groups; no significant differences were found after FDR correction.

CONCLUSION: Compared with the HC group, PD patients (both TD and PIGD groups) exhibited spatial distribution abnormalities in multiple brain networks. Nominally significant alterations suggestive of compensatory activation of the motor cortex were observed at the uncorrected statistical level, alongside weakened functional connectivity in specific networks.

PMID:42922813 | PMC:PMC13686844 | DOI:10.3389/fneur.2026.1943343

Front Neurol. 2026 Oct 9;17:1967078. doi: 10.3389/fneur.2026.1967078. eCollection 2026.

ABSTRACT

BACKGROUND: Chronic motor-complete spinal cord injury (SCI) results in profound neurological disability with minimal prospects for functional recovery using conventional rehabilitation strategies. Emerging evidence suggests that epidural spinal cord stimulation (eSCS) can activate dormant spinal locomotor networks and restore volitional and autonomic functions when combined with intensive activity-based training. However, systematic evaluation of multimodal neuromodulation approaches integrating advanced rehabilitation and computational neurophysiology remains limited.

METHODS: The RESTORES trial (RESToration Of Rehabilitative function with Epidural spinal Stimulation) is a prospective, single-arm Phase II feasibility study enrolling 15 adults with chronic (≥1 year) motor-complete SCI (American Spinal Injury Association Impairment scale (AIS) A or B) between C5 and T12. Participants will undergo implantation of an epidural spinal cord stimulator followed by a 24-week program of structured stimulation-coupled personalised neurorehabilitation (five sessions per week). Clinical outcomes will be evaluated using standardized neurological and functional measures including the AIS motor score, Spinal Cord Independence Measure version III (SCIM-III), Walking Index for Spinal Cord Injury II (WISCI-II), and Trunk Assessment Scale (TASS). Autonomic function and quality of life will also be assessed. Multimodal neurophysiological measurements-including surface electromyography (sEMG), electroencephalography (EEG), resting-state functional magnetic resonance imaging (rs-fMRI), and computer-vision-based movement analysis-will be performed to investigate neural recovery mechanisms and inform the development of adaptive neuromodulation systems.

STUDY OUTCOMES: The primary outcome is the safety of epidural spinal cord stimulation implantation, defined as the absence of device explantation for safety-related reasons within 6 months following implantation. Secondary outcomes include changes in AIS motor score, functional outcomes (SCIM, WISCI-II, TASS), autonomic function, quality of life, and neurophysiological biomarkers.

DISCUSSION: This study integrates neuromodulation, advanced rehabilitation technologies, and multimodal computational neurophysiology to evaluate both clinical efficacy and neural mechanisms of recovery following chronic SCI. Findings from the RESTORES trial will provide critical safety and feasibility data to inform future multicenter trials and the development of closed-loop spinal cord stimulation systems.

CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, Identifier NCT05644171.

PMID:42921395 | PMC:PMC13692923 | DOI:10.3389/fneur.2026.1967078

Front Neurol. 2026 Oct 9;17:1933104. doi: 10.3389/fneur.2026.1933104. eCollection 2026.

ABSTRACT

INTRODUCTION: Most ischemic stroke survivors experience motor deficits, yet the underlying patterns of spontaneous brain activity change remain unclear. Individual rs-fMRI studies on this population have yielded contradictory findings, likely due to small sample sizes and between-study differences in lesion profiles, stroke stage, rehabilitation history, and imaging pipelines. These inconsistencies have not been resolved by existing reviews, many of which combine ischemic and hemorrhagic stroke, pool conceptually distinct rs-fMRI metrics without sufficient stratification, or focus on functional connectivity rather than local spontaneous activity. This protocol plans a coordinate-based meta-analysis restricted to ischemic stroke and local rs-fMRI metrics to address that gap.

METHODS AND ANALYSIS: This study will systematically identify and synthesise whole-brain rs-fMRI studies that compared ALFF, fALFF, or ReHo between adult ischemic stroke patients with motor dysfunction and healthy controls. We will search PubMed, Embase, Web of Science, and the Cochrane Library up to 6 February 2026. To be included, a study must report whole-brain voxel-wise group comparisons and provide stereotactic peak coordinates in MNI or Talairach space. Studies will be excluded if they are non-original reports, case reports or case series, use task-state fMRI or ROI-only analyses, lack extractable standard-space coordinates, involve duplicate or overlapping datasets, include hemorrhagic or mixed stroke without separable ischemic-stroke data, or do not provide clearly extractable motor dysfunction-related data. Two reviewers will independently screen, extract, and assess methodological quality. Using anisotropic effect-size seed-based d mapping (AES-SDM), the quantitative synthesis will pool coordinates to detect convergent patterns of both increased and decreased regional spontaneous activity. Where data allow, we will conduct subgroup analyses, jackknife sensitivity testing, heterogeneity assessment, and meta-regression. The protocol follows the PRISMA-P statement, and the completed review will adhere to PRISMA 2020.

CONCLUSION: This protocol outlines a systematic review and AES-SDM coordinate-based meta-analysis aimed at synthesizing regional spontaneous activity abnormalities in ischemic stroke patients with motor dysfunction. The results should identify convergent areas of local functional alteration, generating testable predictions for future research on post-stroke motor-network reorganization and rehabilitation.

CLINICAL TRIAL REGISTRATION: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261359426, identifier CRD420261359426.

PMID:42921345 | PMC:PMC13692926 | DOI:10.3389/fneur.2026.1933104

Transl Psychiatry. 2026 Jul 27;16(1):581. doi: 10.1038/s41398-026-04234-9.

ABSTRACT

Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its neural basis and biomarkers remain elusive. In this study, we combined neuroimaging, transcriptomics, proteomics, and machine learning to bridge large-scale brain network dysfunction with peripheral molecular signatures. Resting-state functional magnetic resonance imaging (fMRI) from 544 MDD patients and 569 healthy controls (HC) revealed altered network topology involving thalamic, fronto-striatal, and parietal regions. Connectome-transcriptomic association analysis of these network alterations, in conjunction with differential gene expression analysis, identified 24 candidate genes, with FKBP5, PTX3, and APCDD1 prioritized by machine learning. Plasma proteomics further validated altered protein expression of the three prioritized genes in two independent cohorts (adults: 162 MDD patients and 103 HC; adolescents: 71 MDD patients and 39 HC). Protein-based diagnostic models achieved accuracies of 69.6% in adults and 83.1% in adolescents, while protein levels were significantly higher in adolescents with MDD than in HC (all P < 0.05). These findings suggest that PTX3, APCDD1, and FKBP5 may serve as candidate peripheral biomarkers associated with MDD-related brain network alterations.

PMID:42918767 | DOI:10.1038/s41398-026-04234-9

Biol Psychiatry Cogn Neurosci Neuroimaging. 2026 Oct 23:S2451-9022(26)00312-5. doi: 10.1016/j.bpsc.2026.10.007. Online ahead of print.

ABSTRACT

BACKGROUND: Early caregiving may shape neonatal limbic circuit organization, yet whether microanalytically coded interaction quality relates to neonatal limbic-prefrontal connectivity is unknown. We tested associations between infant and maternal affect during mother-infant interaction and neonatal limbic-prefrontal cortex (PFC) connectivity.

METHODS: At approximately 30 days postnatal, 143 mother-infant dyads from the Healthy MiNDS cohort (São Paulo, Brazil) completed a video-recorded interaction coded with the Coding Interactive Behavior (CIB) system; infant negative affect was the percentage of interaction time in distress. Neonates underwent resting-state fMRI; limbic-PFC connectivity was quantified by principal component analysis of amygdala and hippocampus seed-to-ROI maps. Covariate-adjusted regressions tested associations.

RESULTS: Infant negative affect was associated with right amygdala-PFC (β = -0.247, p = .003) and right hippocampus-PFC connectivity (β = -0.202, p = .021), both surviving FDR correction and robust across multiple analytic approaches. The amygdala association was limited to infant distress-related behaviors, whereas maternal positive expressiveness showed an independent, opposing association (β = 0.202, p = .019); no other CIB measure was significant. Exploratorily, connectivity was associated with sleep problems at 18-24 months in females (r = -.324, p = .030).

CONCLUSIONS: The emotional quality of early caregiving is associated with neonatal limbic circuit organization: infant distress is selectively associated with weaker amygdala-PFC connectivity, whereas maternal positive affect shows an independent opposing association. These findings identify the mother-infant relationship as a modifiable input to neonatal brain development.

PMID:42918449 | DOI:10.1016/j.bpsc.2026.10.007

J Affect Disord. 2026 Oct 23:122662. doi: 10.1016/j.jad.2026.122662. Online ahead of print.

ABSTRACT

BACKGROUND: The spatial organization of insular abnormalities across connectional-architecture-defined subregions in panic disorder (PD) remains unclear. We examined structural and resting-state functional measures using the Brainnetome Atlas.

METHODS: Forty-nine medication-naïve patients with PD and Fifty healthy controls underwent structural and resting-state MRI. Gray matter volume (GMV), amplitude of low-frequency fluctuation (ALFF), and regional homogeneity (ReHo) were assessed across six insular subregions. Four prespecified functional connections were examined, together with exploratory Granger causality analysis between dIg and S1 and an AAL3 whole-insula comparison.

RESULTS: dIg-S1 functional connectivity was reduced in PD (β = -0.148, 95% CI [-0.248, -0.048], pFDR = 0.017). ALFF showed a Group × Subregion interaction (F(5,578) = 4.162, p = 0.001). Only the ventral agranular insula (vIa) showed significantly higher ALFF after false discovery rate (FDR) correction (pFDR = 0.016), with a larger group effect than other subregions. The interaction persisted after temporal signal-to-noise ratio (tSNR) adjustment (F(5,577) = 2.582, p = 0.025), but the vIa-specific effect was nonsignificant in a separate vIa-only tSNR-adjusted model (p = 0.194). ReHo was directionally lower across all six subregions, but no contrast survived FDR correction. No robust subregional GMV differences or significant group differences in exploratory Granger causality were detected. Adjusted AAL3 whole-insula differences were nonsignificant.

CONCLUSIONS: PD showed measure-dependent insular functional alterations, including reduced dIg-S1 coupling and vIa-predominant ALFF differences, with the latter sensitive to signal quality and spatial smoothing.

PMID:42918353 | DOI:10.1016/j.jad.2026.122662

Behav Brain Res. 2026 Oct 23:116546. doi: 10.1016/j.bbr.2026.116546. Online ahead of print.

ABSTRACT

Autism Spectrum Disorder (ASD) encompasses diverse behavioral, cognitive, and neural profiles that vary widely across individuals. Because diagnosis remains predominantly behavior-based, clinically meaningful within-spectrum differences are often missed. Recent advances in neuroimaging analysis have created opportunities for the identification of distinct neural profiles within ASD. These new avenues provide ways to examine intra-ASD heterogeneity directly, identifying person-specific brain-behavior patterns that group-level comparisons fail to capture. The present systematic review focused on neuroimaging methods (i.e., resting-state fMRI; rs-fMRI, cortical morphology) that emphasized heterogeneity-informed outcomes based on normative modeling, data-driven subtyping, clustering analysis and similar analytic choices. For rs-fMRI, findings showed that differences in connectivity within the default mode and salience networks were linked to social-communication and language impairments, with subtype-specific patterns emerging across samples. In cortical thickness and surface area, studies identified distinct developmental trajectories and individual deviation profiles, with prefrontal and temporal regions often tied to repetitive behaviors and social-communication difficulties. Voxel-based analyses revealed subgroup-specific gray matter alterations, including cerebellar and cortical differences, that aligned with variation in repetitive behaviors and social difficulties. Collectively, this emerging evidence supports the notion that neural heterogeneity in autism is a core feature rather than a limitation. Embracing individual variability can provide crucial insight into the inconsistencies and contradictions of earlier case-control and group-level findings. Moving forward, autism research must prioritize heterogeneity-based methods to establish reproducible subtypes and individualized brain-behavior links.

PMID:42918308 | DOI:10.1016/j.bbr.2026.116546