Most recent paper

Brain Struct Funct. 2025 Nov 4;230(8):168. doi: 10.1007/s00429-025-03041-0.

NO ABSTRACT

PMID:41186746 | DOI:10.1007/s00429-025-03041-0

Nat Neurosci. 2025 Nov 3. doi: 10.1038/s41593-025-02099-7. Online ahead of print.

ABSTRACT

High-amplitude coactivation patterns are sparsely present during resting-state functional magnetic resonance imaging (fMRI), yet they drive functional connectivity and resemble task activation patterns. However, little research has characterized the remaining majority of the resting-state signal. Here, we introduce caricaturing, a method for projecting resting-state data onto a subspace orthogonal to a manifold of coactivation patterns estimated from task fMRI data. This removes linear combinations of these coactivation patterns from resting-state data to create caricatured connectomes. We used task data from two large-scale neuroimaging datasets to construct a manifold of task coactivation patterns and created caricatured connectomes. These connectomes exhibit lower between-individual similarity and higher identifiability and could be used to predict phenotypic measures, representing individual differences in behavior, often to a greater degree than standard connectomes. Our results show that there is a useful signal beyond the dominant coactivations that drive resting-state functional connectivity, which may better characterize the brain's intrinsic functional architecture.

PMID:41184631 | DOI:10.1038/s41593-025-02099-7

J Neurotrauma. 2025 Oct 23. doi: 10.1177/08977151251377469. Online ahead of print.

ABSTRACT

Predicting outcome for patients with acute severe traumatic brain injury (TBI) is imprecise, relying on neurological examination, structural neuroimaging, and resting-state electroencephalography (EEG) to serve as proxies for brain function. We implemented a multimodal assessment protocol to determine whether detection of consciousness using advanced tools, including standardized behavioral evaluation, advanced EEG, and functional magnetic resonance imaging (fMRI), is associated with functional outcome in patients with acute severe TBI admitted to the intensive care unit (ICU). We tested the association between 6-month Disability Rating Scale (DRS) scores and acute level of consciousness on the Coma Recovery Scale-Revised (CRS-R); responses to active-motor-imagery and passive-language EEG and fMRI; and resting-state fMRI default mode network (DMN) connectivity. We consecutively enrolled 55 patients with acute severe TBI. Six-month outcome was available in 45 (45.2 ± 20.7 years old, 70% male), of whom 10 died, all due to withdrawal of life-sustaining treatment (WLST). All deaths occurred in participants who were not behaviorally following commands. Lower (i.e., better) 6-month DRS scores were observed in participants who were younger (ρ = 0.401; 95% confidence interval [CI: 0.078, 0.649]; p = 0.006]) and who were conscious (median DRS score difference [95% CI]: -11 [-20, -2]; p = 0.003) or following commands (-9 [-20, -1]; p = 0.011) on CRS-R assessment in the ICU. Evidence of command-following on EEG or fMRI did not strengthen this relationship. In participants without command-following on the CRS-R, we detected responses to active-motor-imagery (i.e., cognitive motor dissociation [CMD]) in 6/34 (18%) of participants on EEG and 8/24 (33%) participants on fMRI. We detected responses to passive-language stimuli (i.e., covert cortical processing [CCP]) in 30/33 (91%) of participants on EEG and 18/24 (75%) on fMRI. However, neither CMD nor CCP was associated with outcome on the DRS or several secondary outcome measures (e.g., dichotomous DRS, Glasgow Outcome Scale-Extended), an unexpected result that may reflect the modest sample size and high rate of WLST. In exploratory analyses, an intact DMN and the magnitude of DMN connectivity were associated with 6-month outcome on secondary outcome measures. Collectively, our results suggest that the level of consciousness in the ICU, assessed with a standardized behavioral measure, may predict recovery from severe TBI. Further research, conducted at multiple sites and with larger samples, is required to determine whether integrating behavioral, EEG, and fMRI biomarkers of consciousness is more predictive than behavioral assessment alone.

PMID:41182259 | DOI:10.1177/08977151251377469

Brain Commun. 2025 Oct 15;7(6):fcaf404. doi: 10.1093/braincomms/fcaf404. eCollection 2025.

ABSTRACT

There have been reports of altered functional connectivity in Alzheimer's disease, which is associated with the buildup of pathogenic proteins in the brain, including neurofibrillary tau tangles and amyloid-beta plaques. It is believed that the tau aggregates are the main driver of functional disconnection and resulted in cognitive decline in Alzheimer's disease. Tau propagates through connected neurons, a phenomenon often described as the 'prion-like' properties of tau, which can locally result in functional connectivity disruption. Apolipoprotein E gene allele 4 status and amyloid-beta are accelerating factors for tau-related pathological changes in Alzheimer's disease. However, the potential role of apolipoprotein E gene allele 4 and amyloid-beta in mediating the tau-related functional disconnection is not clear. I aimed to investigate the mediating effect of apolipoprotein E gene allele 4 and amyloid-beta on the local association of tau spreading on functional connections. I analysed follow-up resting-state functional MRI (fMRI) (non-baseline visit) and longitudinal tau-PET data from 211 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 138 healthy elderly individuals from the Harvard Aging Brain Study (HABS). The follow-up resting-state fMRI (non-baseline visit) was studied in order to study the time needed effect of tau pathology. The top 10 regions with the highest probability-weighted SUVR values using Gaussian mixture models were selected as individual-level tau-PET epicentres. I looked at how the relationship between functional connectivity to epicentres and individualized connectivity-related tau spreading was mediated by amyloid-beta status and the apolipoprotein E gene allele 4 genotype. Higher rates of tau aggregation accumulation were seen in areas with stronger connectedness (shorter distance-based connectivity) to the baseline-defined tau epicentres. Moreover, the association between functional connectivity to epicentres and tau spreading through functional connections was mediated by apolipoprotein E gene allele 4 and amyloid-beta status in both dataset's participants. Tau aggregates spread through functional connections and locally disrupt connectivity between tau epicentre and non-epicentre regions, which is mediated in apolipoprotein E gene allele 4 carriers and amyloid-beta-positive participants. These findings have implications for trial designs, proposing that apolipoprotein E gene allele 4 carriers and amyloid-beta-positive participants might need earlier intervention to attenuate tau spreading and tau relative functional disconnection.

PMID:41180953 | PMC:PMC12576542 | DOI:10.1093/braincomms/fcaf404

Front Neurol. 2025 Oct 17;16:1683552. doi: 10.3389/fneur.2025.1683552. eCollection 2025.

ABSTRACT

BACKGROUND: Current evidence suggests that repetitive transcranial magnetic stimulation (rTMS), repetitive peripheral magnetic stimulation (rPMS), and their combined application can all enhance upper limb functional recovery after stroke. However, their comparative therapeutic profiles, including relative advantages and limitations, have not been systematically characterized.

OBJECTIVES: To compare rTMS, rPMS, and combined protocols for post-stroke upper limb recovery, analyzing both functional outcomes and neural mechanisms to guide therapeutic selection.

METHODS: Fifty-one stroke patients were randomly divided into an rTMS group, rPMS group, or a combined group. Before and after 3 weeks of intervention, all patients were assessed with the Fugl-Meyer assessment for the upper limb (FMA-UL), the Thumb Localizing Test (TLT), modified Barthel index (MBI), and resting-state functional magnetic resonance imaging (rs-fMRI).

RESULTS: The ΔFMA-UL and ΔMBI scores of the combined group were significantly better than the rTMS group and rPMS group. The ΔTLT scores of the combined group and rPMS were significantly better than the rTMS group, but there was no statistically significant difference in ΔTLT scores between rPMS and the combined group. Compared to the rTMS group, the rPMS group showed increased amplitude of low-frequency fluctuation (ALFF) in the ipsilesional superior frontal gyrus, cerebellum_8 area, and contralesional cerebellum_crus1; the combined group showed increased ALFF in the ipsilesional cerebellum_8 area, superior medial frontal gyrus, and contralesional cerebellum_crus2 area. Compared with the rPMS group, the combined group showed increased ALFF in the ipsilesional paracentral lobule, supplementary motor area, precentral gyrus, and superior medial frontal gyrus.

CONCLUSION: Compared with rTMS, rPMS has certain advantages in improving proprioception after stroke, and combination therapy improves both motor and proprioception. Therefore, combination therapy is recommended to better promote the recovery of brain and limb function.

CLINICAL TRIAL REGISTRATION: http://chictr.org.cn, Identifier ChiCTR2200065871.

PMID:41180535 | PMC:PMC12576412 | DOI:10.3389/fneur.2025.1683552

Front Comput Neurosci. 2025 Oct 16;19:1616472. doi: 10.3389/fncom.2025.1616472. eCollection 2025.

ABSTRACT

INTRODUCTION: Understanding the cognitive process of thinking as a neural phenomenon remains a central challenge in neuroscience and computational modeling. This study addresses this challenge by presenting a biologically grounded framework that simulates adaptive decision making across cognitive states.

METHODS: The model integrates neuronal synchronization, metabolic energy consumption, and reinforcement learning. Neural synchronization is simulated using Kuramoto oscillators, while energy dynamics are constrained by multimodal activity profiles. Reinforcement learning agents-Q-learning and Deep Q-Network (DQN)-modulate external inputs to maintain optimal synchrony with minimal energy cost. The model is validated using real EEG and fMRI data, comparing simulated and empirical outputs across spectral power, phase synchrony, and BOLD activity.

RESULTS: The DQN agent achieved rapid convergence, stabilizing cumulative rewards within 200 episodes and reducing mean synchronization error by over 40%, outperforming Q-learning in speed and generalization. The model successfully reproduced canonical brain states-focused attention, multitasking, and rest. Simulated EEG showed dominant alpha-band power (3.2 × 10-4 a.u.), while real EEG exhibited beta-dominance (3.2 × 10-4 a.u.), indicating accurate modeling of resting states and tunability for active tasks. Phase Locking Value (PLV) ranged from 0.9806 to 0.9926, with the focused condition yielding the lowest circular variance (0.0456) and a near significant phase shift compared to rest (t = -2.15, p = 0.075). Cross-modal validation revealed moderate correlation between simulated and real BOLD signals (r = 0.30, resting condition), with delayed inputs improving temporal alignment. General Linear Model (GLM) analysis of simulated BOLD data showed high region-specific prediction accuracy (R 2 = 0.973-0.993, p < 0.001), particularly in prefrontal, parietal, and anterior cingulate cortices. Voxel-wise correlation and ICA decomposition confirmed structured network dynamics.

DISCUSSION: These findings demonstrate that the framework captures both electrophysiological and spatial aspects of brain activity, respects neuroenergetic constraints, and adaptively regulates brain-like states through reinforcement learning. The model offers a scalable platform for simulating cognition and developing biologically inspired neuroadaptive systems.

CONCLUSION: This work provides a novel and testable approach to modeling thinking as a biologically constrained control problem and lays the groundwork for future applications in cognitive modeling and brain-computer interfaces.

PMID:41180117 | PMC:PMC12571814 | DOI:10.3389/fncom.2025.1616472

Front Med (Lausanne). 2025 Oct 17;12:1657241. doi: 10.3389/fmed.2025.1657241. eCollection 2025.

ABSTRACT

OBJECTIVES: Non-specific low back pain (NSLBP) is a prevalent disorder with significant global health impacts. This systematic review and meta-analysis assessed acupuncture's clinical effectiveness for NSLBP and explored its brain mechanisms using fMRI.

METHODS: A comprehensive search of multiple databases (PubMed, Embase, Cochrane Library, Web of Science, Science Direct, China National Knowledge Infrastructure, Wanfang Data, Chinese Technical Periodicals Database, and Chinese Biomedical Literature Database) was conducted from inception to July 11th, 2024. We included randomized controlled trials (RCTs) or non-RCTs resting-state functional magnetic resonance imaging to observe the effect of acupuncture on NSLBP. GingerALE 3.0.2 was used as the meta-analysis tool, and meta-analysis was performed in the Montreal Neurological Institute coordinate space.

RESULTS: The review synthesized evidence from ten studies involving 358 participants. Subgroup analyses indicated that acupuncture significantly reduced pain scores compared to sham acupuncture in both acute NSLBP (WMD = -1.04, 95% CI: -1.72 to -0.36, p = 0.003) and chronic NSLBP (WMD = -0.78, 95% CI: -1.25 to -0.31, p < 0.001). Neuroimaging analyses revealed distinct brain activation patterns: acute NSLBP showed positive activation in the right sub-lobar insula, inferior parietal lobule, medial frontal gyrus, and cingulate gyrus, while chronic NSLBP demonstrated positive activation in bilateral sub-lobar insula and negative activation in motor and prefrontal regions.

CONCLUSION: Acupuncture shows significant efficacy for NSLBP, modulating pain processing through the insula and limbic system. While these results suggest therapeutic potential for both acute and chronic NSLBP, higher-quality research is needed to validate these mechanisms.

SYSTEMATIC REVIEW REGISTRATION: Prospero registration number: CRD42022342438, URL: https://www.crd.york.ac.uk/PROSPERO/view/CRD42022342438.

PMID:41179904 | PMC:PMC12575243 | DOI:10.3389/fmed.2025.1657241

Front Hum Neurosci. 2025 Oct 17;19:1624489. doi: 10.3389/fnhum.2025.1624489. eCollection 2025.

ABSTRACT

BACKGROUND: Functional constipation (FCon) is frequently accompanied by psychological disorders, implicating the interaction between the gastrointestinal symptom and brain dysfunction in FCon. Recent studies combining electrogastrogram and resting-state functional magnetic resonance imaging (fMRI) have reported a novel gastric network. Besides, the fMRI activity of the gastric network was also coupled with the insular fMRI signal. However, little is known about the connection between the gastric network and the insula in FCon.

METHODS: Based on rs-fMRI, functional connectivity (FC) using a large sample of 652 healthy subjects identified the insular cortex as the most closely linked to the gastric network. Then, seed-based FC and dynamic functional connectivity of the gastric network and the gastric-related insular cortex were calculated and compared in 35 patients with FCon and 36 healthy controls. Constipation symptoms were measured using the Patient Assessment of Constipation Symptom Scale (PAC-SYM) and the Wexner Constipation Scale. Their relationships with alterations in the gastric network-insula subregion were investigated.

RESULTS: The posterior insular cortex presented a strong connection with the gastric network with large-scale resting-state fMRI data sets of healthy participants. FCon patients had significantly decreased FC (t = -2.19, p = 0.032) in the left posterior insula and gastric network compared to healthy controls and were significantly negatively correlated with PAC-SYM (r = -0.407, p = 0.015) and Wexner Constipation Scale (r = -0.483, p = 0.003) scores.

CONCLUSION: The abnormality of the connection between the posterior insula and the gastric network may be the prominent neuroimaging feature on FCon, which sheds light on a new perspective on the pathophysiology of FCon.

PMID:41179259 | PMC:PMC12575236 | DOI:10.3389/fnhum.2025.1624489

Imaging Neurosci (Camb). 2025 Oct 30;3:IMAG.a.969. doi: 10.1162/IMAG.a.969. eCollection 2025.

ABSTRACT

Each heartbeat generates a cardiac pressure wave that propagates through the brain and travels from large arteries through cerebrospinal fluid and brain tissue, compressing the venous sinuses and producing venous blood pulsatility. The delay between arterial and venous pulsation (A-V delay) is an insightful marker of intracranial compliance and the intracranial mechanical environment. We developed a novel approach to extract A-V delay from conventional resting-state functional MRI (fMRI) scans, leveraging fMRI's sensitivity to vessel pulsations in large cerebral arteries and the superior sagittal sinus (SSS). This fully automated method was applied to the Human Connectome Project - Aging dataset to analyze 578 participants aged 35 to 90 years. The mean A-V delay was 78 ± 32 msec; it shortened by 4 msec for every decade of aging and was 12 msec faster in men than women, highlighting age-related and sex-specific differences. We also identified a within-SSS pattern of pulsations, characterized by an earlier posterior pulsation and a later anterior pulsation. This pattern opposes the direction of blood flow, supporting that the SSS is passively compressed and tied to a distinct intracranial pulse transmission. Overall, this work demonstrates the feasibility of extracting an fMRI-based A-V delay, uncovering a previously unexplored capability of fMRI. This approach broadens the potential applications of fMRI by adding a biomechanical dimension to fMRI's established roles in evaluating neuronal and hemodynamic function. Given the widespread availability of fMRI, this approach can be applied in future studies to investigate biomechanical changes in various disease conditions.

PMID:41178936 | PMC:PMC12576844 | DOI:10.1162/IMAG.a.969

BMC Psychiatry. 2025 Oct 31;25(1):1044. doi: 10.1186/s12888-025-07486-9.

ABSTRACT

BACKGROUND: This study utilized resting-state functional magnetic resonance imaging (rs-fMRI) combined with default mode network (DMN) region-of-interest (ROI)-based functional connectivity (FC) analysis to examine adolescents with depression complicated by obesity. Correlation analyses were conducted between the functional connectivity of distinct brain regions in the depression-with-obesity cohort and scores from the Adolescent Self-Rating Life Events Checklist (ASLEC) to examine potential associations. This study aimed to elucidate the underlying pathogenesis of depression complicated by obesity and identify potential imaging biomarkers for early diagnosis in this population.

METHODS: We analysed rs-fMRI data from 37 adolescents with depression complicated by obesity (OMDD group, n = 37), 38 patients with depression (MDD group, n = 38), and 35 healthy controls (HCs group, n = 35). DMN FC was compared with whole-brain connectivity during rs-fMRI. Imaging data from the three groups were collected and analysed using one-way analysis of variance (ANOVA). Group differences in FC values were assessed, and correlations were examined between these values and clinical scale scores across patient groups.

RESULTS: Compared with the MDD group, the OMDD group demonstrated significantly increased FC between the left parahippocampal gyrus (left PHG) and the right precuneus. Compared with the HCs, both the OMDD and MDD patients presented reduced FC between the left PHG and the left putamen, right putamen, and opercular part of the right inferior frontal gyrus. All findings were corrected using Gaussian random field (GRF) theory at a voxel-level threshold of P < 0.001 and a cluster-level threshold of P < 0.05 (minimum cluster size > 30 voxels). Analyses revealed significant negative correlations between the FC values of the right putamen in the OMDD group and the “interpersonal relationship” scores (r = − 0.373, P = 0.023).

CONCLUSION: Compared with healthy controls, adolescents with depression complicated by obesity demonstrated significant alterations in functional integration within the DMN. Specifically, the OMDD group exhibited aberrant FC between the left PHG and the right precuneus. This aberrant FC may underlie the pathophysiology of this disorder. These findings offer novel insight into the neural mechanisms of depression comorbid with obesity, enhancing our understanding of its pathogenesis.

PMID:41174601 | PMC:PMC12577443 | DOI:10.1186/s12888-025-07486-9

Clin Neurophysiol. 2025 Oct 28;180:2111410. doi: 10.1016/j.clinph.2025.2111410. Online ahead of print.

NO ABSTRACT

PMID:41175466 | DOI:10.1016/j.clinph.2025.2111410

Neuropsychopharmacology. 2025 Oct 31. doi: 10.1038/s41386-025-02270-5. Online ahead of print.

ABSTRACT

Lysergic acid diethylamide (LSD) and 3,4-Methylenedioxymethamphetamine (MDMA) are widely used psychoactive drugs and their potential use in psychiatric medicine is currently generating interest. The mechanism by which these drugs may assist recovery in various disorders such as addiction and post-traumatic stress disorder (PTSD) is still not well understood. Most investigations of the effects of these drugs on brain activity have focused on cortical resting-state networks, however the striatum is a key reward and motivation hub of the brain and aberrant striatal processing may be part of the pathophysiology of these disorders. Consequently, we investigated striatal connectivity following acute MDMA and LSD administration. Resting-state fMRI (rs-fMRI) data were acquired from two separate previous studies, and seed-voxel functional connectivity analyses were used with the striatum subdivided into three seed regions: the associative, limbic, and sensorimotor striatum. Within-network connectivity was measured using group mean network maps and whole-brain connectivity (seed-to-voxel) was also examined. Neither MDMA nor LSD significantly changed within-network connectivity of any of the three striatal seed regions. However, striatal connectivity with other brain regions was significantly altered with both MDMA and LSD. Most notably, MDMA reduced connectivity between the limbic striatum and the amygdala, while LSD increased connectivity between the associative striatum and the frontal, sensorimotor, and visual cortices. Changes in connectivity were mostly observed outside the standard striatal networks, consistent with previous findings that psychedelics reduce network modularity or between-network segregation and increase connectivity across standard networks.

PMID:41174227 | DOI:10.1038/s41386-025-02270-5

Neuroimage. 2025 Oct 29:121562. doi: 10.1016/j.neuroimage.2025.121562. Online ahead of print.

ABSTRACT

Fundamental mechanisms that control the brain's ability to dynamically respond to cognitive demands are poorly understood, especially during periods of accelerated neural and cognitive maturation, such as adolescence. Using a sparsity-promoting feedback control framework we investigated the controllability of the adolescence functional connectome. Critical feedback costs associated with a region's control action on itself and the rest of the brain were estimated using resting-state fMRI data from an early longitudinal sample in the Adolescent Brain Cognitive Development (ABCD) study (n = 1394; median (IQR) age = 10.1 (1.1) years at baseline and 12.1 (1.1) years at follow-up). A highly reproducible, core set of predominantly highly connected regions retained their control action over the connectome under high feedback costs. They included posterior visual areas, retrosplenial cortex, cuneus and precuneus, superior parietal lobule, temporal ventral cortex and dorsolateral and lateral prefrontal cortices, i.e., both developed and developing brain regions. These regions were central to the topological organization of the connectome, consistently engaged during spontaneous coordination of resting-state networks, and overlapped with cognitive and topological brain hubs that play ubiquitous roles in cognitive function and the organization of the connectome. Also, most received (integrated) and distributed approximately equal amounts of neural information. These regions' control action was developmentally stable, i.e., critical feedback costs did not change significantly during puberty, suggesting that, despite ongoing maturation and topological changes in the adolescent brain, fundamental mechanisms of system controllability may be well developed to facilitate information processing and response to cognitive demands.

PMID:41173437 | DOI:10.1016/j.neuroimage.2025.121562

Neuroscience. 2025 Oct 29:S0306-4522(25)01042-5. doi: 10.1016/j.neuroscience.2025.10.044. Online ahead of print.

ABSTRACT

Generalized anxiety disorder (GAD) is a common psychiatric condition characterized by chronic excessive worry and abnormal neural circuitry dynamics, as identified by functional magnetic resonance imaging (fMRI). This study employs regional homogeneity (ReHo) and seed-based functional connectivity (FC) analyses to investigate intrinsic brain activity patterns in GAD, offering new neuroimaging insights into its pathophysiology. We enrolled 36 GAD patients and 33 healthy controls (HCs), who underwent resting-state fMRI and clinical assessments. ReHo differences between groups were analyzed, followed by FC analysis using altered ReHo regions as seeds. Correlations between ReHo/FC metrics, cognitive performance, and clinical parameters were examined. Patients with GAD exhibited decreased ReHo in the right cingulate gyrus and left precentral gyrus. FC analysis revealed increased coupling between the left precentral gyrus and the inferior parietal lobule (An integral component of the default mode network [DMN]), while connectivity between the left precentral and postcentral gyri was diminished. These FC changes were clinically relevant: precentral-postcentral connectivity positively correlated with illness duration, while precentral- inferior parietal lobule connectivity showed a negative association with Hamilton Anxiety Rating Scale scores. Neuroimaging studies reveal that GAD is linked to specific functional abnormalities in the cingulate and precentral gyri, as well as altered connectivity within the sensorimotor network and between the sensorimotor network and inferior parietal lobule (An integral component of the DMN). However, large-scale longitudinal studies incorporating multi-modal neuroimaging approaches are needed to establish whether these neural alterations represent pathophysiological mechanisms underlying GAD.

PMID:41173360 | DOI:10.1016/j.neuroscience.2025.10.044

Magn Reson Imaging. 2025 Oct 29:110554. doi: 10.1016/j.mri.2025.110554. Online ahead of print.

ABSTRACT

Magnetic resonance imaging (MRI) at ultra-high field strengths such as 7 T unlocks new opportunities. Functional MRI (fMRI) is especially able to benefit due to the increase in the inherent blood‑oxygen-level-dependant (BOLD) signal. In order to utilise this, the higher motion sensitivity at 7 T and various motion sources in fMRI protocols, especially task-based ones, need to be mitigated. This motivated the development of a 7 T implementation of the real-time, prospective Multislice Prospective Acquisition Correction (MS-PACE) technique. MS-PACE allows for a sub-TR, higher temporal resolution motion correction without the need for external tracking equipment. We present an echo-planar imaging (EPI) implementation, evaluated in a 7 T task-based fMRI study. The results show that the technique led to significant, consistent reduction in residual motion across the scanned cohort. An analysis of the temporal SNR of the resting-state scans indicated a general increase in this metric when prospective motion correction was activated. Functional analysis of the data showed an apparent reduction of artefactual activations compared to a standard retrospective motion correction algorithm.

PMID:41173218 | DOI:10.1016/j.mri.2025.110554

Dev Neurobiol. 2026 Jan;86(1):e23018. doi: 10.1002/dneu.23018.

ABSTRACT

Establishing a proper balance between neuronal excitation (E) and inhibition (I) is essential for healthy brain development, with alterations in this dynamic linked to neurodevelopmental disorders. Animal models suggest that hippocampal activity rapidly increases in the early postnatal period, believed to support the development and stabilization of E/I neural circuitry. This process has not yet been examined in humans, however. Utilizing longitudinal data from the Developing Human Connectome Project, the present study evaluated the impact of early hippocampal activity and gestational age at birth on later outcomes in a cohort of preterm infants (N = 58). Hippocampal activity was assessed using the amplitude of low-frequency fluctuations (ALFF) derived from resting-state functional magnetic resonance imaging collected at two timepoints in the early postnatal period (prior to 20 weeks following birth). Increases in hippocampal activity during this early postnatal period predicted better cognitive and motor function at 18 months of age. Greater gestational age was associated with greater hippocampal activity increase between timepoints. Interestingly, no significant relationships were found between baseline hippocampal activity and 18-month outcomes, suggesting that dynamic changes rather than static measures may be especially sensitive to preterm birth and subsequent alterations in neurodevelopmental processes. These findings underscore the importance of changes in early hippocampal function and gestational age as key risk factors for future neurodevelopmental concerns.

PMID:41171858 | DOI:10.1002/dneu.23018

Front Neurosci. 2025 Oct 15;19:1639838. doi: 10.3389/fnins.2025.1639838. eCollection 2025.

ABSTRACT

INTRODUCTION: Anodal direct current stimulation (a-tDCS) of the visual cortex is a potential rehabilitation tool for vision disorders such as amblyopia and macular degeneration. However, the underlying neural mechanisms are currently unknown. When applied to the human motor cortex, a-tDCS reduces the concentration of gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter that modulates neuroplasticity. Our primary aim was to assess whether the same a-tDCS paradigm alters local GABA concentration when applied to the healthy primary visual cortex. We also measured the effect of a-tDCS on visual cortex resting-state connectivity and sought to replicate reported observations of an association between visual cortex GABA concentration and the dynamics of binocular rivalry.

METHODS: Fourteen participants with normal vision completed two brain imaging sessions at least 48 hours apart. In each session, binocular rivalry dynamics, primary visual cortex GABA and glutamate-glutamine (Glx) concentrations (via magnetic resonance spectroscopy (MRS)) and resting-state functional connectivity (via task-free fMRI) were measured at baseline. Real or sham a-tDCS (20 min, 2mA) was then applied to the visual cortex in a randomized sequence followed by a second set of MRS and fMRI measurements.

RESULTS: No between-session effects of a-tDCS on GABA or Glx concentration or resting-state functional connectivity were observed. A pre-planned within-session analysis revealed a significant increase in Glx following a-tDCS that did not withstand multiple comparisons correction. No consistent relationships between binocular rivalry dynamics and GABA concentration were apparent.

DISCUSSION: Together, our results suggest that a-tDCS effects on the visual cortex may differ from the GABA-associated mechanism in motor cortex.

PMID:41169746 | PMC:PMC12570334 | DOI:10.3389/fnins.2025.1639838

Brain Commun. 2025 Oct 29;7(5):fcaf343. doi: 10.1093/braincomms/fcaf343. eCollection 2025.

ABSTRACT

The treatment of chronic pain represents a widespread clinical challenge. Current approaches to network-based mapping of the cerebral cortex have the potential to localize chronic pain in the brain. In an effort to further characterize the dynamical brain networks, or the 'dynome' in the setting of chronic pain, we performed a Coordinate-Based Meta-Analysis of resting-state functional Magnetic Resonance Imaging studies on chronic pain to create a multinetwork dynome of chronic pain. A cluster-level analysis generated seven statistically significant activation likelihood estimates (ALEs): one for chronic pain as a whole dynome, three for chronic pain conditions, and three for chronic pain mechanisms. Chronic pain is a complex disease process involving tripartite network dysfunction encompassing the Default Mode Network, Central Executive Network and Salience Network. Chronic visceral pain was distinct from chronic headache and chronic musculoskeletal pain, and chronic pain mechanisms have the potential to share common cortical network rearrangements with their respective chronic pain conditions. Collectively, this work represents the first anatomically specific network-based cortical map of chronic pain, with representation of disease-specific and mechanism-specific disruptions in cortical function.

PMID:41169268 | PMC:PMC12569763 | DOI:10.1093/braincomms/fcaf343

BMC Psychiatry. 2025 Oct 30;25(1):1040. doi: 10.1186/s12888-025-07483-y.

ABSTRACT

BACKGROUND: Suicide thoughts and behaviors (STB), including suicidal ideation (SI) and suicide attempts (SA), are significant concerns in major depressive disorder (MDD), yet their neurobiological mechanisms remain poorly understood. This study aims to identify key regional brain activity and connectivity abnormalities associated with STB in MDD by combining a meta-analysis of regional brain activity comparing MDD patients with STB to non-STB controls (both MDD without STB and healthy controls) and an exploratory functional connectivity (FC) analysis in an independent sample of MDD patients.

METHODS: A meta-analysis employing Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software identified regional brain abnormalities. Studies included were those comparing MDD patients with STB to non-STB controls, employing resting-state fMRI with whole-brain analyses, using ALFF, fALFF, and ReHo metrics. The identified abnormal brain regions were used as regions of interest (ROIs) for FC analyses in 57 first-episode, drug-naive MDD patients.

RESULTS: The meta-analysis included 12 studies (13 datasets) comprising 555 MDD patients with STB and 430 non-STB controls. Compared to non-STB controls, MDD-STB patients showed increased activity in the right middle occipital gyrus (MOG) and right inferior frontal gyrus, triangular part (IFGtriang), while decreased activity in right precuneus. Subgroup analysis of SA revealed increased activity in the left angular gyrus in MDD patients with SA, compared to non-SA controls. SI subgroup analysis and two medication status subgroup analyses showed no significant results. In independent sample, FC analysis yielded two significant FCs after Bonferroni correction. Correlation analysis showed a negative association between right MOG-IFGtriang FC and most severe SI scores measured by the Beck Scale for Suicidal Ideation (P = 0.04), though it was non-significant after correction.

CONCLUSIONS: These findings provide novel insights into the neural mechanisms of STB in MDD, identifying specific brain regions and FC patterns associated with STB. These results align with prior studies, highlighting the role of visual processing and cognitive control regions in STB. By combining a meta-analysis of regional abnormalities with an exploratory FC analysis, this study offers a comprehensive understanding of the brain networks implicated in STB and suggests potential targets for future interventions.

PMID:41168736 | DOI:10.1186/s12888-025-07483-y

Nat Commun. 2025 Oct 30;16(1):9359. doi: 10.1038/s41467-025-64988-6.

ABSTRACT

The microbiome-gut-brain-axis plays a critical role in mental health. However, research linking the microbiome to brain function is limited, particularly during development, when tremendous plasticity occurs and many mental health issues, like depression and anxiety, initially manifest. Further complicating attempts to understand interactions between the brain and microbiome is the complex and multidimensional nature of both systems. In the current observational study (N = 55), we use sparse partial least squares to identify linear combinations of brain networks (brain signatures) derived from resting state fMRI scans at age 6 years that maximally covary with internalizing symptoms at age 7.5 years, before identifying microbe abundances (microbial profiles) derived from 16S rRNA sequencing of stool samples at age 2 years that maximally covary with those brain signatures. Finally, we test whether any early microbial profiles are indirectly associated with later internalizing symptoms via the brain signatures, highlighting potential microbial programming effects. We find that microbes in the Clostridiales order and Lachnospiraceae family are associated with internalizing symptoms in middle childhood through connectivity alterations within emotion-related brain networks.

PMID:41168153 | DOI:10.1038/s41467-025-64988-6