Most recent paper

Neuropsychiatr Dis Treat. 2026 Jul 14;22:585990. doi: 10.2147/NDT.S585990. eCollection 2026.

ABSTRACT

BACKGROUND: This preliminary study aimed to evaluate the clinical utility of resting-state functional magnetic resonance imaging (rs-fMRI) as an individualized tool for localizing core language areas in patients undergoing epilepsy surgery.

METHODS: A retrospective analysis was conducted on 31 patients with drug-resistant epilepsy who underwent rs-fMRI-based language localization and stereo-electroencephalography (SEEG). The rs-fMRI data were processed using seed-based correlation analysis. Two neurosurgeons independently reviewed the data and reached a consensus on the rs-fMRI localization results. Language function outcomes derived from electrical stimulation of language-related electrodes during SEEG were independently analyzed and documented by two additional physicians. The consistency rate between rs-fMRI-identified language regions and the effects observed during electrical stimulation was subsequently calculated to compare the two techniques.

RESULTS: In the Broca area, left- and right-hemisphere dominance occurred in equal proportions, with an asymmetric subregional distribution (predominantly pars triangularis on the left and pars opercularis on the right). Lateralization in the Wernicke area was less clear, with similar proportions of left, right, and bilateral representation. SEEG validation showed that when rs-fMRI indicated unilateral localization, it reliably identified SEEG stimulation-negative regions (specificity ≥ 94%), but its sensitivity was low (33%-50%), meaning that it frequently missed SEEG stimulation-positive areas. When rs-fMRI showed bilateral Wernicke localization, its diagnostic performance was poor (specificity only 27.3%, with a negative AC1).

CONCLUSION: Resting-state fMRI identified language reorganization in 54.8% broca and 64.5% wernicke patients with drug-resistant epilepsy, suggesting atypical or non-left-dominant language lateralization. Before surgery involving critical language areas, rs-fMRI scanning can be considered as an auxiliary tool to localize core language regions. When rs-fMRI shows unilateral localization and the area is non-core, it might reduce the need for implanting SEEG electrodes for language mapping in that region. However, in cases of bilateral Wernicke core localization, additional language mapping methods should be combined. These preliminary findings require validation in larger prospective cohorts.

PMID:42519505 | PMC:PMC13381330 | DOI:10.2147/NDT.S585990

Psychoradiology. 2026 Jul 6;6:kkag025. doi: 10.1093/psyrad/kkag025. eCollection 2026.

ABSTRACT

BACKGROUND: Adolescence is a critical period for brain network remodeling and the onset of major depressive disorder (MDD); however, white matter (WM) functional topology in adolescent MDD remains underexplored. Given that WM functional signals reflect meaningful neural activity and are disrupted in psychiatric disorders, this study aimed to characterize WM functional connectome alterations in adolescents with MDD and examine their clinical associations.

METHODS: Resting-state fMRI data were obtained from a cohort of adolescents with MDD (n = 320) and healthy controls (HCs, n = 144), as well as from an independent replication cohort. Following the construction of thresholded WM functional networks, graph-theoretical analyses were used to calculate global topological properties. Canonical correlation analysis (CCA) was used to examine associations between topology and clinical symptoms, while exploratory classification assessed their discriminative information and generalizability. Furthermore, subgroup analyses were conducted to evaluate the effects of a history of suicide attempt, non-suicidal self-injury, childhood trauma, and sex.

RESULTS: Compared with HCs, adolescent MDD exhibited significant reductions in the clustering coefficient, characteristic path length, and local efficiency. CCA identified distinct covariation patterns: reduced global integration was linked to severe suicidal ideation and depressed mood, while impaired local segregation was associated with vegetative symptoms such as weight loss and insomnia. Subgroup analyses revealed significant sexual dimorphism, with male patients demonstrating more severe topological impairments than females. A similar pattern was observed in the independent replication cohort. The classification analysis achieved above-chance accuracy (69.6 and 60% in the two cohorts).

CONCLUSIONS: Our results reveal a topologically shifted WM functional connectome structure in adolescent MDD, providing new clues to aid in understanding the pathophysiology of its pathophysiology.

PMID:42518885 | PMC:PMC13384069 | DOI:10.1093/psyrad/kkag025

Biol Psychiatry Glob Open Sci. 2026 May 12;6(5):100753. doi: 10.1016/j.bpsgos.2026.100753. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Depression is a prevalent and debilitating affective disorder characterized by the dominance and persistence of depressive rumination. Mindfulness-based cognitive therapy (MBCT) is an effective treatment for recurrent depression developed specifically to target rumination and recurrence risk by training metacognitive awareness and adaptive attention, emotion, and self-regulation skills. However, the underlying mechanisms by which mindfulness training impacts maladaptive depressive rumination are not well understood, and a deeper understanding of its effects on the complex brain dynamics during depressive rumination is needed.

METHODS: In a randomized controlled functional magnetic resonance imaging (fMRI) study (N = 80), we examined dynamic neural changes during resting-state fMRI of an experimentally induced rumination state before and after treatment with MBCT (n = 27) for recurrent depression in addition to treatment as usual (TAU) or TAU alone (n = 21). More specifically, we characterized the changes during a depressive rumination state as a repertoire of metastable substates, each with an occurrence frequency (fractional occupancy) and stability (lifetimes).

RESULTS: We found that MBCT training compared with TAU altered the fractional occupancy of a salience-somatomotor metastable substate during the depressive rumination state. These dynamic network changes in turn were associated with reduced trait rumination posttreatment and reduced depressive symptoms at the 3-month follow-up.

CONCLUSIONS: In a ruminative state, changes in the dynamics of the somatosensory-salience network following mindfulness training was associated with improved clinical outcomes and reduced trait rumination, which may provide insight into candidate brain mechanisms or markers of treatment response to MBCT.

PMID:42518781 | PMC:PMC13382308 | DOI:10.1016/j.bpsgos.2026.100753

Front Hum Neurosci. 2026 Jul 6;20:1839961. doi: 10.3389/fnhum.2026.1839961. eCollection 2026.

ABSTRACT

Behaviors arise from coordinated neural activity across diverse spatial and temporal scales. Prior work has linked better task performance and cognitive functioning to patterns of global network connectivity requiring minimal reconfiguration when switching between task demands. This metric indexing similarity in functional connectivity across task and rest has been termed "neural efficiency." Here we assess stability of neural efficiency over approximately 3 years in adolescence, specificity across two task-rest combinations and associations with anxiety. At approximately age 16 and/or 19, 95 participants completed a resting state scan alongside a cognitive control and/or threat task. Neural efficiency was quantified as partial correlations between intrinsic and task-related functional connectivity patterns across the whole brain. We tested temporal stability across the three-year interval, as well as associations with task performance and anxiety across the two task-rest combinations at the two time points. Neural efficiency values remained relatively stable from mid to late adolescence (ICC[3,1] = 0.51-0.58). The cognitive control task showed higher values than the threat task. Across tasks, neural efficiency was associated with better performance (i.e., reduced interference), although not consistently (r = -0.19, p = 0.26 - r = -0.37, p = 0.021). These effects did not survive correction for multiple testing. No associations were found between neural efficiency and self/parent-reported anxiety. In sum, the metric shows moderate developmental stability and associations with task performance. Task features impact neural efficiency. Given small sample sizes, findings need to be interpreted cautiously.

PMID:42518775 | PMC:PMC13381436 | DOI:10.3389/fnhum.2026.1839961

Neuroimage Rep. 2026 Jul 13;6(3):100383. doi: 10.1016/j.ynirp.2026.100383. eCollection 2026 Sep.

ABSTRACT

Resting-state functional connectivity (rsFC) has shown widespread changes in intrinsic functional brain networks in individuals with chronic low back pain (CLBP). However, less is known about rsFC between task-evoked brain networks (i.e., networks formed by regions that are activated to tasks) implicated in cognitive reappraisal and attention regulation in this population. This cross-sectional study analyzed resting-state fMRI and behavioral data from a separate pain regulation task in 184 individuals with CLBP to investigate whether rsFC among ROIs defined from task-based meta-analyses of cognitive reappraisal and attention regulation networks was associated with pain regulation success. We hypothesized that increased rsFC within and between task-based networks would be associated with greater pain regulation success, and that trait cognitive reappraisal and mindfulness would mediate these relationships. Results indicated that increased rsFC between ROIs in the task-based cognitive reappraisal network, including the left ventrolateral prefrontal cortex (vlPFC) and left middle temporal gyrus (MTG), was associated with reduced pain regulation success using either cognitive reappraisal or attention regulation. Conversely, increased rsFC between ROIs in the task-based cognitive reappraisal network left vlFPC and attention regulation network right middle frontal gyrus (MFG) was associated with increased pain regulation success using attention regulation. Examining the relationship between rsFC and self-reported measures of pain, cognition, and emotion, we found that increased rsFC between the task-based cognitive reappraisal network left MTG and attention regulation network right inferior frontal gyrus (IFG) was associated with increased self-reported cognitive distortions. In contrast, increased rsFC between the task-based attention regulation network bilateral vlPFC and left posterior cingulate cortex (PCC) was associated with more habitual use of cognitive reappraisal, lower pain catastrophizing, and lower depression. In a formal mediation analysis, neither trait cognitive reappraisal nor trait mindfulness mediated the relationship between rsFC and pain regulation success. Together, our findings suggest that rsFC between brain regions in task-based cognitive reappraisal and attention regulation networks is related to behavioral outcomes in a separate evoked pain regulation task and may underlie cognition and emotion regulation success in individuals with CLBP.

PMID:42518330 | PMC:PMC13382298 | DOI:10.1016/j.ynirp.2026.100383

Sleep. 2026 Jul 28:zsag205. doi: 10.1093/sleep/zsag205. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Sleep is fundamental to brain health, yet the mechanisms by which habitual sleep quality shapes large-scale neural dynamics during wakefulness remain unclear. This work aims at determining whether habitual sleep quality is associated with systematic alterations in regional and cross-regional temporal complexity of spontaneous neural activity.

METHODS: Regional brain entropy (BEN) and cross-regional brain entropy (CRBEN) were estimated from resting-state fMRI data of the UK Biobank, with replication in the Human Connectome Project (HCP) and in a randomized total sleep deprivation experiment. Temporal complexity of spontaneous neural activity was correlated to self-reported habitual sleep quality and sleep amount in observational cohorts and experimental total sleep deprivation in the laboratory study.

RESULTS: Better sleep quality was associated with increased BEN in sensory and sensorimotor cortices and decreased BEN in frontoparietal control regions. High-quality sleep enhanced differentiation of temporal complexity among sensory networks while strengthening coordination within higher-order control systems. In the independent HCP cohort, sleep amount predicted increased BEN in visual and somatomotor regions. Moreover, the strength of the association between sleep measures and BEN was strongly and negatively correlated with the major cortical functional gradient. Exploratory results suggest convergent effects following total sleep deprivation. Habitual sleep quality is associated with systematic reconfiguration of the brain's temporal complexity architecture at both regional and network levels.

CONCLUSION: These findings position sleep as a fundamental determinant of the brain's dynamic operating regime and identify temporal complexity as a mechanistically informative neural signature linking sleep health to cognitive function and neuropsychiatric vulnerability.

PMID:42518224 | DOI:10.1093/sleep/zsag205

Exp Biol Med (Maywood). 2026 Jul 13;251:10948. doi: 10.3389/ebm.2026.10948. eCollection 2026.

ABSTRACT

Intrinsic brain networks are crucial for post-stroke recovery, but the causal relationships between specific networks and domain-specific recovery outcomes, as well as the role of lipid metabolism, remain unclear. This study leveraged Mendelian randomization (MR) to evaluate 191 resting-state functional magnetic resonance imaging (rs-fMRI) BOLD-derived phenotypes in relation to post-stroke recovery after nondisabling ischemic stroke. Genetic instruments for rs-fMRI phenotypes were derived from a UK Biobank genome-wide association study (n = 34,691). Outcomes included motor, cognitive, and global recovery after nondisabling ischemic stroke, assessed using longitudinal National Institutes of Health Stroke Scale subscales over 2 years (n = 1,270). Primary analyses used the multiplicative random-effects inverse-variance weighted method. A two-step MR analysis investigated whether brain networks mediate the effects of lipids on post-stroke outcomes. Higher BOLD-derived functional connectivity within the triple network (default mode network, central executive network, and salience network) was associated with better motor and cognitive outcomes. Higher genetically predicted orbitofrontal node amplitude in the limbic network correlated with better motor recovery, while stronger parieto-frontal connectivity was associated with cognitive recovery. Genetically proxied higher low-density lipoprotein cholesterol (LDL-C) was associated with poorer cognitive recovery, with evidence suggesting partial mediation through differences in BOLD-derived triple-network connectivity. This MR study supports a potential causal role of BOLD-derived functional network phenotypes, particularly the triple network, in motor and cognitive recovery, and further suggests that differences in triple-network connectivity act as a partial mediator linking elevated LDL-C liability to impaired cognitive recovery. These findings provide hypothesis-generating evidence for future mechanistic studies and for exploring whether specific brain network-targeted interventions could have a role in stroke recovery.

PMID:42516175 | PMC:PMC13402224 | DOI:10.3389/ebm.2026.10948

Hum Brain Mapp. 2026 Aug;47(11):e70610. doi: 10.1002/hbm.70610.

ABSTRACT

Understanding neurovascular coupling (NVC) is essential for interpreting functional MRI (fMRI) data, particularly in task-based paradigms. BOLD-ASL coupling studies, where simultaneously collected blood oxygenation dependent (BOLD) and arterial spin labeling (ASL) signals are correlated, have shown widespread coupling during the resting state. While prior work has demonstrated widespread BOLD-ASL coupling at rest, less is known about how this coupling behaves during tasks and whether nonlinear dependencies contribute to NVC. This study investigates BOLD-ASL coupling during a visual checkerboard task and a finger-tapping motor task. Coupling was evaluated at zero lag and at the lag of maximum dependence. Spatial correspondence with task activation was quantified using Dice coefficients within Yeo 17-network regions. Coupling was evaluated using traditional Pearson correlation (corr) and mutual information (MI), a model-free approach capable of detecting both linear and nonlinear dependencies. Results showed strong spatial correspondence between task activation and BOLD-ASL coupling for both tasks, particularly in expected visual, sensory, and motor regions. Notably, MI showed more overlap with traditional GLM-based task activation models compared to corr. This suggests that MI may provide additional insights into the complexity of NVC beyond traditional linear methods. These findings reinforce the importance of using multimodal fMRI approaches to characterize NVC more comprehensively.

PMID:42515826 | DOI:10.1002/hbm.70610

Biomedicines. 2026 Jun 26;14(7):1449. doi: 10.3390/biomedicines14071449.

ABSTRACT

Background: Accurate presurgical localization of eloquent cortex and subcortical pathways is essential in neurosurgery, guiding the balance between maximal safe resection and preservation of neurological function. This narrative review compares the clinical utility of task-based functional magnetic resonance imaging (tb-fMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) in neurosurgical populations, with emphasis on brain tumors and epilepsy. Methods: This narrative review was based on a non-systematic literature search of PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar from database inception to March 2026. The review focused on tb-fMRI and rs-fMRI for presurgical functional mapping in neurosurgical populations, including clinical utility, feasibility, validation, limitations, and workflow integration. Results: Tb-fMRI remains the most established noninvasive modality for motor and language mapping and language lateralization because of its task-specific activation maps and established role in clinical workflows. However, its use is limited by dependence on patient cooperation, task performance, and intact neurovascular coupling; thus, aphasia, cognitive impairment, fatigue, paresis, pediatric age, sedation, and tumor-related neurovascular uncoupling may render tb-fMRI inconclusive or misleading. Rs-fMRI offers a task-free alternative based on intrinsic functional connectivity, enabling simultaneous mapping of multiple resting-state networks from a single acquisition and providing particular value in non-cooperative, cognitively impaired, aphasic, pediatric, or sedated patients. Evidence indicates that rs-fMRI is most robust for sensorimotor mapping, with reported agreement with tb-fMRI and intraoperative direct electrical stimulation, whereas language mapping remains less consistent and more dependent on analytical methodology. Neither modality replaces intraoperative stimulation, which remains the reference standard. Conclusions: Current evidence supports a multimodal presurgical strategy in which tb-fMRI is used first-line in cooperative patients; rs-fMRI is added when task-based mapping is limited or infeasible, and both are interpreted alongside tractography, neuronavigation, and intraoperative mapping.

PMID:42511924 | DOI:10.3390/biomedicines14071449

Curr Neuropharmacol. 2026 Jul 21. doi: 10.2174/011570159X470892260706231913. Online ahead of print.

ABSTRACT

INTRODUCTION: Alzheimer's disease (AD) spectrum disorders are characterized by progressive cognitive decline, with white matter degeneration and disrupted cortico-cortical connectivity as early features. Cortico-white matter functional coupling integrates neuronal activity with axonal conduction, yet its natural trajectory across the AD spectrum and ability to be modulated by repetitive transcranial magnetic stimulation (rTMS) remain unclear.

METHODS: Longitudinal resting-state fMRI from the ADNI cohort (n = 160: 59 cognitively normal, CN; 65 mild cognitive impairment, MCI; 36 AD) was used to assess baseline and 1-year changes in mean Fisher's z-transformed coupling between 82 cortical seeds (AAL-90 atlas, excluding subcortical nuclei) and a probabilistic group white matter mask. Specifically, 54 patients with amnestic MCI (aMCI) from the rTMS cohort were allocated to active (n = 40) or sham (n = 14) groups and received four weeks of neuronavigated rTMS targeting the left angular gyrus. Cortico-white matter functional coupling was calculated identically in both cohorts. Changes in coupling strength and their associations with changes in neuropsychological performance were examined across all cortical seeds.

RESULTS: At baseline, mean cortico-white matter functional coupling followed a nonlinear pattern (MCI > AD and CN). One-year follow-up revealed that the CN group exhibited a slight decrease in coupling, and the MCI and AD groups showed a pathological increase. Compared with the sham group, active rTMS significantly attenuated this increase in coupling. After adjusting for covariates, coupling changes were strongly correlated with cognitive decline. The AD group demonstrated the most significant associations (n = 104), whereas the active rTMS group showed 71 associations, predominantly linked to objective memory improvement.

DISCUSSION: This abnormal overcoupling, leading to compensation and decompensation, is associated with the progression of Alzheimer's disease. rTMS effectively moderates this pathological surge by enhancing neural efficiency and stabilizing large-scale network integration. Our findings position cortico-white matter functional coupling as an effective indicator of disease intensity and a measurable link in the chain of rTMS effectiveness for early-stage AD.

CONCLUSION: Overall, cortico-white matter functional coupling may serve as a novel scan-based biomarker for tracking AD progression and evaluating rTMS treatment efficacy in patients with MCI.

PMID:42509708 | DOI:10.2174/011570159X470892260706231913

Prog Neuropsychopharmacol Biol Psychiatry. 2026 Jul 27:111863. doi: 10.1016/j.pnpbp.2026.111863. Online ahead of print.

ABSTRACT

Schizophrenia is a severe psychiatric disorder marked by widespread brain abnormalities. Recent studies suggest that pathological changes may originate from focal 'epicenter' regions and subsequently spread to other brain areas strongly connected to them. Investigating drug-naïve first-episode schizophrenia (dn-FES) patients may help characterize early-stage regional functional abnormalities and their potential neurochemical underpinnings. Resting-state functional magnetic resonance imaging data were acquired from 50 dn-FES patients and 50 age- and sex-matched healthy controls (HCs). Static regional homogeneity (sReHo) and dynamic ReHo (dReHo) were compared between groups, and correlations with psychotic symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS). We further used the JuSpace toolbox to test whether spatial patterns of ReHo alterations were associated with specific neurotransmitter receptor/transporter densities. Compared with HCs, dn-FES patients showed reduced sReHo in the bilateral postcentral/precentral gyri, bilateral paracentral lobules and right supplementary motor area, and increased dReHo in the left lingual gyrus. sReHo in the right postcentral gyrus was inversely correlated with PANSS positive scores, whereas dReHo in the left lingual gyrus was negatively correlated with PANSS general scores. Schizophrenia-related sReHo alterations showed significant spatial associations with serotonergic, dopaminergic, noradrenergic and cholinergic systems, whereas dReHo alterations were associated with serotonergic, dopaminergic, cannabinoid and opioid systems. Taken together, this study identifies abnormal static and dynamic local functional connectivity in sensorimotor and visual regions in drug-naïve first-episode schizophrenia, and the spatial correspondence between these alterations and receptor/transporter distributions may offer insight into the molecular substrates associated with these functional abnormalities.

PMID:42508630 | DOI:10.1016/j.pnpbp.2026.111863

Dev Cogn Neurosci. 2026 Jul 24;81:101789. doi: 10.1016/j.dcn.2026.101789. Online ahead of print.

ABSTRACT

There is growing interest in identifying brain function underlying adolescent cognition, personality, and psychopathology. One promising approach is Precision Functional Mapping (PFM) of MRI functional connectivity, a data-intensive method for characterizing individualized brain networks. Foundational studies suggest that PFM can detect stable, task-responsive, and clinically relevant networks. Studies demonstrate that both functional connectivity reliability and network stability improve with increasing data quantity, although benchmark estimates vary across populations, preprocessing pipelines, and MRI acquisition approaches. Accordingly, it is important to understand how PFM performs in adolescent populations and with multi-echo fMRI acquisition. In a case study of eight youth (ages 10-17), we applied PFM to 80 minutes of combined resting-state and task-based fMRI. The resulting networks were highly modular, consistent with adult templates, and without evidence of structural registration artifacts. Functional connectivity reliability compared favorably to prior single-echo studies, with multivariate similarity and ICC estimates showing early stabilization around 10-15 min despite continued improvement with additional data. Trait-like stability increased gradually with acquisition time, and a Bayesian algorithm (MS-HBM) demonstrated higher stability than Infomap. Across algorithms, stability was greatest in the somatosensory, auditory, visual, and parietal networks. Furthermore, when evaluating task-based responses to threat and attention paradigms, only the auditory network consistently benefited from individualized mapping over group template networks. These findings suggest that, with constrained scanning time, PFM is especially effective for characterizing sensory and perceptual networks in adolescents. Bridging the methodological divide between deeply sampled individual cases and large-scale developmental studies will require further innovation and validation.

PMID:42508279 | DOI:10.1016/j.dcn.2026.101789

Psychiatry Res Neuroimaging. 2026 Jul 20;362:112288. doi: 10.1016/j.pscychresns.2026.112288. Online ahead of print.

ABSTRACT

BACKGROUND: Functional connectivity MRI studies have identified widespread dysconnectivity in schizophrenia and bipolar disorder. However, most approaches rely on group-defined atlases that assume fixed network boundaries, potentially obscuring effects due to inter-individual variability in network organization. Here, we examined topographic abnormalities using individualized functional mapping.

METHODS: Resting-state fMRI data (1 h acquisition) were obtained from 56 healthy controls (HC), 45 bipolar disorder (BP), and 31 schizophrenia (SZ) participants (ages 18-33). Individualized functional networks were derived using template matching. Topographic Abnormality Index (TAI) quantified network-specific spatial deviations relative to normative boundaries, while Vertexwise Functional Deviation Index (VFDI) reflected global deviation across all cortical vertices. Group differences were assessed using ANOVA and ANCOVA (covarying age, sex, and motion), with false discovery rate correction. Clinical correlations were examined within BP and SZ.

RESULTS: Significant group effects were observed across multiple networks, including temporo-insular (TIN), cingulo-opercular (CON), sensorimotor, dorsal attention (DAN), language (LAN), and default mode (DMN) networks (q < 0.05). BP showed prominent abnormalities in sensorimotor and perceptual networks, whereas SZ exhibited greater involvement of higher-order associative networks. Global metrics demonstrated robust group discrimination: TAI average (F = 9.01, p = 2 × 10⁻4) and VFDI (F = 11.06, p = 3.7 × 10⁻⁵), with both BP and SZ elevated relative to HC. Mania severity correlated with sensorimotor (body) network TAI (q = 0.002). Global metrics were not related to symptom severity.

CONCLUSIONS: Schizophrenia and bipolar disorder are characterized by widespread but distinct disruptions in functional network topography. Global measures, particularly VFDI, provide sensitive indices of cross-network abnormality and may offer utility for biomarker development beyond traditional network-specific approaches.

PMID:42508239 | DOI:10.1016/j.pscychresns.2026.112288

J Neurophysiol. 2026 Jul 27. doi: 10.1152/jn.00178.2026. Online ahead of print.

ABSTRACT

We investigated local synchronization in three nuclei of the human striatum (nucleus accumbens, caudate nucleus, putamen; N = 1055 participants) by computing, for each nucleus, the zero-lag crosscorrelations (CC0) between prewhitened resting-state BOLD fMRI time series recorded from voxels 2-12 mm apart (2, 4, 6, 8, 10, 12 mm bins). CC0 was strongest at the shortest distance (2 mm) and decreased with distance in a power (log-log) fit, reaching a plateau at 8 mm. CC0 was highest in accumbens where it decreased more sharply (by ~1.4x) with distance than in the caudate and putamen. These results document a distinct difference in synchronization in accumbens as compared to caudate and putamen, where this synchronization was very similar. Given that the cellular layout is fairly comparable in all 3 nuclei, our findings could be reasonably attributed to a different neuromodulatory environment between accumbens and caudate/putamen, a hypothesis supported by the findings of differential neuromodulatory distributions in humans using positron emission tomography (PET). The role of local synchronization and its different strength among striatal nuclei, on their overall function and relations to behavior remain to be elucidated.

PMID:42507821 | DOI:10.1152/jn.00178.2026

Neurol Int. 2026 Jul 7;18(7):129. doi: 10.3390/neurolint18070129.

ABSTRACT

Background/Objectives: Epilepsy is a chronic brain disease characterized by recurrent epileptic seizures. It affects roughly 50 million people worldwide and around one third of the patients have drug-resistant epilepsy (DRE). The current study aimed to find differences in the whole-brain functional connectivity (FC) in patients with DRE compared to patients with well-controlled epilepsy (WCE) and healthy controls (HCs). Methods: This explorative, cross-sectional study included 92 participants (nDRE = 30; nWCE = 30; nHC = 32) who underwent resting-state functional magnetic resonance imaging (fMRI). The CONN Toolbox was used to process and analyze the FC changes among the three groups. Results: There was a statistically significant increase of the FC between the left lateral prefrontal cortex, left inferior temporal gyrus (temporo-occipital), left lobules IV and V of the cerebellum and multiple cortical and subcortical structures in patients with DRE as opposed to WCE and HC. On the other hand, decreased FC was observed between three seeds (the posterior cingulate cortex, precuneus cortex, the right planum polare) and different frontal, temporal and occipital regions. Interestingly, the right nucleus accumbens (r_NAc) showed increased FC with the inferior frontal gyrus in DRE compared to WCE, whereas the r_NAc-left precentral gyrus FC was reduced in DRE as opposed to HC. Conclusions: The acquired information offers valuable insights into the neuronal networks associated with DRE. These data could be used for advancing diagnostic accuracy and future therapeutic strategies.

PMID:42506051 | DOI:10.3390/neurolint18070129

Biomimetics (Basel). 2026 Jul 9;11(7):481. doi: 10.3390/biomimetics11070481.

ABSTRACT

The topology of spiking neural networks (SNNs) plays an important role in determining their dynamic representation ability, recognition performance, and biological interpretability in speech recognition. However, most existing SNN reservoirs are constructed using random, regular, or manually designed connectivity patterns, which may not reflect the functional organization of the human brain during speech perception. In this study, we propose a task-state fMRI-constrained SNN framework for speech recognition. Human fMRI data acquired during naturalistic English audiobook listening are used offline to derive a task-state whole-brain functional topology, which serves as a biologically inspired structural prior for the recurrent connectivity of the SNN reservoir. Because the fMRI and downstream isolated-digit recognition tasks use different speech paradigms, this topology is interpreted as a general speech-listening prior rather than a digit-specific neural representation. The Schaefer-400 cortical parcellation is used to define 400 whole-brain functional nodes, all of which are retained to preserve distributed cortical interactions during speech listening. Within this topology, 7 SomMotB_Aud parcels are identified as auditory core nodes and analyzed as an embedded auditory circuit. Compared with resting-state fMRI, task-state fMRI shows enhanced functional connectivity among these auditory nodes, indicating task-related auditory-circuit activation. The resulting 400-node task-state topology is mapped onto the recurrent connectivity of the SNN reservoir. This mapping is regarded as a topology-constrained computational abstraction rather than a direct model of biological information transmission. During recognition, speech spike trains are the only external input, while fMRI data are used only for offline topology construction. Experimental comparisons with baseline SNNs show that the proposed topology improves recognition performance and biological interpretability. Resting-state topology comparison, auditory-core contribution analysis, threshold-sensitivity analysis, and statistical testing are further used to evaluate robustness. These findings suggest that speech-evoked whole-brain functional organization may provide an effective topology prior for biologically inspired speech recognition models.

PMID:42505514 | DOI:10.3390/biomimetics11070481

Biol Psychiatry Glob Open Sci. 2026 Jun 10;6(5):100768. doi: 10.1016/j.bpsgos.2026.100768. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Disrupted maturation of functional brain networks has been increasingly linked to elevated risk of psychosis, but the spatiotemporal characteristics of these deviations remain unclear. We used longitudinal connectome fingerprinting and jointly analyzed the functional connectivity (FC) and intraclass correlation coefficient (ICC) to obtain age-dependent trajectories of functional brain organization in 22q11.2 deletion syndrome (22q11DS), a high-risk model for psychosis.

METHODS: Resting-state functional magnetic resonance imaging from 62 individuals with 22q11DS and 63 control participants (ages 8-30 years, 2-5 visits) were analyzed. Patients were stratified by the presence or absence of positive psychotic symptoms (PPSs) [PPS(+), PPS(-)]. The FC and ICC characterization of connectome fingerprints were projected onto a joint principal component (PC) space, yielding 3 orthogonal axes of maturation: PC1 (sensory-association axis), PC2 (emotional-cognitive balance), and PC3 (executive-sensory control). Longitudinal trajectories along these axes characterized the directionality and coordination of connectome maturation.

RESULTS: Control participants showed a clear decrease in identifiability and stability during adolescence, followed by recovery into adulthood, reflecting coordinated, direct maturation along all 3 axes. PPS(-) individuals exhibited a partial decrease and subsequent recovery, preserving adaptive reorganization along PC3. In contrast, PPS(+) participants displayed disorganized and irregular trajectories in the PC space and a decline in PC3, indicating disrupted temporal coordination of network maturation and fragmented executive-sensory integration.

CONCLUSIONS: Loss of developmental synchrony in FC was associated with psychosis vulnerability in 22q11DS. PC analysis-based multiaxis mapping revealed that resilience and vulnerability are determined by the direction and synchrony of brain maturation rather than by stability alone, highlighting a novel marker for tracking neurodevelopmental risk across psychiatric disorders.

PMID:42502641 | PMC:PMC13400943 | DOI:10.1016/j.bpsgos.2026.100768

J Mood Anxiety Disord. 2026 Jul 10;15:100192. doi: 10.1016/j.xjmad.2026.100192. eCollection 2026 Sep.

ABSTRACT

BACKGROUND: Individuals with bipolar disorder spend significantly more time depressed than manic, and treatment alternatives for treatment-resistant patients are greatly needed. Although the Stanford Accelerated Intelligent Neuromodulation Therapy (SAINT) intermittent theta-burst stimulation (iTBS) protocol has shown efficacy in unipolar depression, its utility in bipolar depression remains largely unexplored. This study aims to assess the feasibility and safety of SAINT in patients with bipolar I depression that have failed to respond to a first-line treatment and examine underlying neural mechanisms of treatment response.

METHODS: Ten participants with bipolar I disorder underwent a modified SAINT protocol in this open-label study. Depressive and manic symptoms were assessed throughout. Personalized left dorsolateral prefrontal cortex (DLPFC) stimulation targets exhibiting negative resting-state connectivity with the subgenual anterior cingulate cortex (sgACC) were generated using resting-state functional MRI. We then investigated changes in resting-state (DLPFC and sgACC) seed-to-whole brain connectivity, and its relationship to treatment response.

RESULTS: Immediately post-treatment, depressive symptoms decreased by an average of 56.7 (SD=19.7%)%. Following treatment, participants exhibited increased connectivity between sgACC and two bilateral frontal pole clusters. Greater reductions in depressive severity were significantly associated with increased negative connectivity between left DLPFC target seed and four clusters in prefrontal and temporal cortices.

CONCLUSION: SAINT iTBS was well-tolerated in a bipolar I depression sample and associated with sgACC functional connectivity changes. Increased negative connectivity between the DLPFC target and prefrontal/temporal cortex was associated with treatment response. Larger, sham-controlled studies are needed to confirm these findings and explore predictors of treatment response in bipolar depression.

PMID:42502622 | PMC:PMC13400662 | DOI:10.1016/j.xjmad.2026.100192

Brain Stimul. 2026 Jul 25:103173. doi: 10.1016/j.brs.2026.103173. Online ahead of print.

ABSTRACT

BACKGROUND: Targeting methods for repetitive transcranial magnetic stimulation (rTMS) in patients with depression now include individual functional magnetic resonance imaging (fMRI) scans to target specific functional connectivity (FC) patterns. Potential biomarkers of rTMS response include target FC with the subgenual anterior cingulate cortex (SGC) or the causal depression circuit (CDC), each of which may be candidates for individualized functional targets (iFTs). We retrospectively assessed the relationship of these two approaches to outcomes in secondary analyses of two large rTMS clinical trials.

METHODS: 501 subjects with moderate to severe depression underwent 4-6 weeks of daily rTMS to the left dorsolateral prefrontal cortex (DLPFC), targeted using neuronavigation to an optimized DLPFC-SGC-FC group-based functional target. Baseline resting-state scans were used to retrospectively compute iFTs using either SGC-DLPFC or CDC-DLPFC FC. Proximity (Euclidean distance) of the stimulated target to iFTs were correlated with outcomes. Electric field magnitude at iFTs was computed to capture non-linear stimulation propagation.

RESULTS: Most iFTs were within 2cm of their group-target. Proximity to either an SGC- or CDC-iFT was not associated with better outcomes. Sensitivity analyses accounting for treatment target FC, methodology, data quality, or treatment parameters did not change results. Electric field-based measures were highly similar to Euclidean distance and likewise showed no association with outcomes.

CONCLUSIONS: Under the specific fMRI acquisition parameters used, proximity to optimized DLPFC-SGC-iFTs was not associated with better outcomes in patients receiving neuronavigated rTMS to an optimized DLPFC-SGC group-target. Prospective randomized clinical trials definitively assessing the clinical utility of iFTs are warranted. .

PMID:42501968 | DOI:10.1016/j.brs.2026.103173

Brain Topogr. 2026 Jul 25;39(5):84. doi: 10.1007/s10548-026-01239-x.

ABSTRACT

The amygdala is a central hub for emotional processing, whose interactions with large-scale brain networks have been implicated in the pathophysiology of depression. Investigating how amygdala-centered connectivity relates to depression in a community-based sample, rather than focusing exclusively on patients with major depressive disorder, may provide broader insights into depression vulnerability. To this end, functional connectivity (via cross-correlation) and effective connectivity (via Granger causality) were computed using resting-state functional magnetic resonance imaging (fMRI) data from 161 adults obtained from the Nathan Kline Institute (NKI)/Rockland community sample. Subsequently, a behavior-guided windowed association analysis identified connectivity indicators correlated with depression severity (Beck Depression Inventory scores), whose contributions to depression prediction were subsequently ranked using machine learning based on a support vector machine. Specifically, higher Beck Depression Inventory (BDI) scores were associated with increased amygdala functional connectivity with the salience/ventral attention system and the dmPFC component of the default mode network, together with decreased connectivity involving dorsal attention, sensorimotor, and visual regions. Granger causality analyses further revealed predominantly reduced directional influences both to and from the amygdala, particularly between the amygdala and distributed default mode, salience/ventral attention, visual, and subcortical regions, suggesting weakened large-scale information exchange. Machine learning analyses identified amygdala-centered connectivity features, especially those involving the default mode and salience-related systems, as among the most informative predictors of depression severity. Overall, these findings delineate an amygdala-centered multi-system network pathology underlying depressive vulnerability, providing quantifiable neural signatures for early detection and potential targets for intervention.

PMID:42501214 | DOI:10.1007/s10548-026-01239-x