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Brain Res Bull. 2025 Dec 9:111681. doi: 10.1016/j.brainresbull.2025.111681. Online ahead of print.

ABSTRACT

BACKGROUND: Neuropsychological tests provide standardized cognitive assessment but have limited ecological validity. Virtual reality (VR) creates immersive environments, better reflecting real-world cognitive performance. Although impaired VR performance correlates with early cognitive decline, its neural mechanisms remain unclear in non-demented elders. This study investigates fMRI biomarkers linked to VR performance to identify neural predictors of cognitive decline.

METHODS: 24 non-demented older adults, including cognitively normal (CN) and mild cognitive impairment (MCI), completed baseline resting-state fMRI and immersive VR tasks combining physical and cognitive demands (dog walking, mountain climbing, drone protection). VR performance score (VRS) was quantified via entropy weight method. We analyzed relationships between VRS, neuropsychological scores, and resting-state functional connectivity (FC).

RESULTS: VRS significantly correlated with MoCA visuospatial/executive scores (p = 0.015). Whole-brain FC analysis revealed a strong association between VRS and FC between the left anterior cingulate cortex (ACC) and left paracentral lobule (PCL) in the overall sample (adjusted p = 1.94 × 10⁻⁶), present in CN but absent in MCI. Stepwise regression confirmed this FC as the significant VRS predictor in CN (R² = 0.599, p < 0.001).

CONCLUSION: Immersive VR performance reflects visuospatial/executive function and is predicted by left ACC-PCL connectivity, serving as a neuroimaging biomarker for real-world cognition that complements traditional assessments. Practically, this biomarker requires validation in larger longitudinal cohorts.

PMID:41380786 | DOI:10.1016/j.brainresbull.2025.111681

Brain Res Bull. 2025 Dec 9:111682. doi: 10.1016/j.brainresbull.2025.111682. Online ahead of print.

ABSTRACT

The heterogeneity of basal ganglia (BG) atrophy in temporal lobe epilepsy (TLE) has not been fully elucidated. This study employed a multimodal fusion framework to examine the potential heterogeneity of BG atrophy among TLE patients. 89 patients diagnosed with TLE were recruited. Structural magnetic resonance imaging (sMRI), resting - state functional magnetic resonance imaging (fMRI), consensus clustering (CC), and neuroimaging - transcriptomic approaches were integrated to explore the structural and functional alterations in the BG and their molecular mechanisms. Canonical correlation analysis (CCA) was employed to investigate the associations between MRI features and clinical characteristics. An individualized prediction model was constructed to facilitate clinical decision-making. CC identified a significant subgroups of BG atrophy in TLE: widespread BG atrophy (TLE-Cluster1, TLE-C1). In TLE-C1, the functional connectivity between the BG and cortical regions associated with sensation, emotion, and memory was notably enhanced. These patients additionally exhibited more severe cognitive impairment as well as higher degrees of anxiety and depression. Transcriptomic analysis established a connection between the heterogeneity of BG atrophy and specific gene expression patterns that were enriched in biological processes such as synaptic function, neurostructural development, and learning and memory. Further analyses uncovered a positive correlation between the gray matter volume of BG and cognitive performance. A classifier based on a Neural Network (NNET) predicted cognitive function with an area under curve (AUC) of 0.983. This study characterizes BG atrophy heterogeneity in TLE, its molecular mechanisms, and clinical relevance, offering insights for personalized diagnosis and management.

PMID:41380785 | DOI:10.1016/j.brainresbull.2025.111682

Front Neurosci. 2025 Nov 25;19:1675610. doi: 10.3389/fnins.2025.1675610. eCollection 2025.

ABSTRACT

OBJECTIVE: This study aims to utilize multimodal neuroimaging techniques to simultaneously analyze global topological properties of white matter structural networks and resting-state functional networks in aMCI patients, comparing them with healthy controls. By conducting independent and integrative analyses of topological impairments in both networks, we seek to systematically characterize the multimodal network disruption patterns in aMCI.

METHODS: 45 aMCI patients and 42 healthy adults from the First Affiliated Hospital of Heilongjiang University of Chinese Medicine in Harbin, Heilongjiang Province, China, were enrolled. A case-control cross-sectional study was conducted. DTI and rs-fMRI data were collected for all participants. Global topological properties of structural and functional networks were constructed using PANDA and dpabi software and were calculated via graph-theoretical analysis in GRETNA software, followed by statistical comparisons between groups.

RESULTS: In patients with aMCI, the small-world (C p , aC p , Lambda, aLambda) of the WM structural network were significantly higher than those in the HC group; Rich-club nodes showed redistribution, and the Rich-club coefficient was decreased; aE loc was significantly increased; the Assortativity index (r < 0) indicated disassortativity; the Hierarchy index (b > 0) exhibited a significant decrease in b within the sparsity range of 0.39∼0.4; the synchronization coefficient (s) was significantly reduced at sparsity levels ranging from 0.28 to 0.30. For the functional network, the small-world index aL p in the aMCI group was significantly lower than that in the HC group; Rich-club nodes showed redistribution, and the Rich-club coefficient was increased within a certain Degree range; aE g was significantly increased; the Assortativity index (r > 0) indicated assortativity; the Hierarchy index (b > 0) was observed within a specific sparsity range.

CONCLUSION: We identified a "structure-function dissociation" in aMCI, where the structural network suffers from fragmentation and hub disruption, while the functional network compensates through rigid, hyper-localized reorganization with elevated local efficiency. This divergence reveals a core pathological mechanism of the disease.

PMID:41378344 | PMC:PMC12685844 | DOI:10.3389/fnins.2025.1675610

bioRxiv [Preprint]. 2025 Dec 1:2025.11.26.690831. doi: 10.1101/2025.11.26.690831.

ABSTRACT

The Risk Reduction for Alzheimer's Disease (rrAD) trial included 513 cognitively normal, sedentary, hypertensive older adults (aged 60 to 85 years) with dementia risk factors. We utilized 420 high-quality baseline resting-state functional MRI (rs-fMRI) scans from this cohort to develop a functional atlas tailored for aging populations. Typical rs-fMRI atlases derived from healthy young adults do not account for age-related changes, such as cortical atrophy, enlarged ventricles, and altered connectivity. To address this gap, we created a cohort-specific MNI-adjacent anatomical template, rrAD420, using SPM12's DARTEL registration. In this space, we derived a comprehensive functional atlas using both group independent component analysis (GICA) and probabilistic functional mode decomposition (PROFUMO). The rrAD420 atlas offers detailed representations of Resting-State Network (RSN) connectivity, encompassing unique configurations and overlapping interactions. It features two Default-Mode Network (DMN)-specific seed-based maps (DMN24 with cerebellum, DMN18 without) and data-driven components resembling the major RSNs. Furthermore, PROFUMO allowed for the identification of multimodal and combinatory networks, capturing connections within and between RSNs. While optimized for hypertensive older adults, the rrAD420 atlas serves as a versatile tool for broader aging populations, aiding in the study of neurodegenerative processes and biomarker discovery.

PMID:41377509 | PMC:PMC12687787 | DOI:10.1101/2025.11.26.690831

Front Neurol. 2025 Nov 25;16:1675066. doi: 10.3389/fneur.2025.1675066. eCollection 2025.

ABSTRACT

OBJECTIVE: Temporal lobe epilepsy (TLE) is a common form of drug-resistant epilepsy often treated with surgical interventions, including laser interstitial thermal therapy (LITT). However, patient-specific factors influencing LITT outcomes remain unclear. This retrospective study aimed to identify pre-operative resting-state functional MRI (rs-fMRI) patterns associated with seizure freedom following LITT in mesial TLE.

METHODS: We analyzed rs-fMRI data from 28 patients with mesial TLE who underwent LITT, classifying them into seizure-free (SF) and not seizure-free (NSF) groups based on 12-month post-operative outcomes. Independent component analysis (ICA) was used to identify subject-specific brain networks, and generalized linear models (GLM) were employed to assess associations between pre-operative spatial patterns of ICA-derived functional connectivity (FC) and surgical outcomes, controlling for clinical variables.

RESULTS: Significant differences in brain ICA-derived FC patterns were observed between SF and NSF groups, with SF exhibiting more locally distributed ICA-derived FC patterns around the mesial temporal lobe, including the posterior orbitofrontal cortex (OFC) and anterior parahippocampal gyrus (PHG). In contrast, NSF demonstrated more diffusely distributed ICA-derived FC patterns encompassing the insula and thalami.

SIGNIFICANCE: These findings highlight the potential of pre-operative rs-fMRI as a prognostic tool for identifying TLE patients more likely to benefit from LITT. Further validation in larger cohorts is warranted to confirm these results and optimize patient selection for surgical interventions.

PMID:41376770 | PMC:PMC12685642 | DOI:10.3389/fneur.2025.1675066

Neuroimage Clin. 2025 Nov 30;49:103919. doi: 10.1016/j.nicl.2025.103919. Online ahead of print.

ABSTRACT

Alterations in brain network centrality are key features of Alzheimer's disease (AD) and may offer insights into the disruption of network organization underlying cognitive decline. We introduce a novel centrality metric, DomiRank, to characterize dominance-driven connectivity patterns in the human brain network, using a multi-center MRI dataset comprising 809 participants. Compared with conventional metrics, DomiRank centrality showed greater sensitivity in detecting AD-related network disruptions, particularly within the cingulate gyrus, precuneus, and subcortical hubs such as the basal ganglia-regions critical for cognition. Regional DomiRank alterations were significantly correlated with clinical cognitive scores, indicating their potential relevance to disease severity. Gene enrichment analysis revealed that areas with reduced DomiRank centrality were enriched for genes involved in synaptic signaling and neuronal communication, suggesting molecular mechanisms underlying network vulnerability. These findings highlight DomiRank centrality as a promising biomarker for characterizing network disorganization in AD, linking changes in brain connectivity with underlying molecular processes.

PMID:41371028 | DOI:10.1016/j.nicl.2025.103919

Age Ageing. 2025 Nov 28;54(12):afaf353. doi: 10.1093/ageing/afaf353.

ABSTRACT

BACKGROUND: Although cerebrovascular reactivity (CVR) correlates with cognitive performance in neurodegenerative conditions, the age-related spatial patterns of CVR alterations and their relationships with grey matter (GM) atrophy and cognition are underexplored.

METHODS: In this cross-sectional study, 301 cognitively unimpaired participants (181 younger, 18-34 years; 120 older: 60-89 years) underwent multi-echo resting-state functional magnetic resonance imaging (fMRI) for CVR measurement. Voxel-wise t-tests compared regional CVR between age groups, with significant clusters defined as regions of interest (ROIs). Mediation analyses examined regional GM atrophy as a mediator of the ageing-CVR relationships within ROIs. Multivariable linear regression and restricted cubic spline analyses evaluated the association between ROI-CVR and cognition in older adults.

RESULTS: Compared with younger adults, older adults showed lower CVR primarily in the temporal, basal ganglia, cingulate, brainstem and cerebellum regions, while higher CVR in the frontal, parietal, occipitotemporal, thalamus and caudate regions. Regional GM atrophy partially mediated age-related CVR increases in the right frontal pole (P = .004) and fusiform/lingual gyrus (P = .001), as well as age-related CVR reduction in bilateral brainstem/cerebellum vermis 45 (P < .001). The proportions mediated were 55.9%, 56.6% and 79.2%, respectively. Among older adults, six ROI-CVRs were associated with executive function, exhibiting linear or nonlinear relationships.

CONCLUSIONS: Resting-state CVR demonstrated regionally heterogeneous age-related decreases or increases, partly mediated by GM atrophy. In older adults, CVR in age-sensitive regions was selectively associated with executive function through linear and nonlinear patterns. Cerebrovascular ageing may involve region-specific vascular adaptations and macrostructural-microvascular (GM-CVR) interactions. Region- and range-dependent CVR could serve as a biomarker for executive function changes.

PMID:41370625 | DOI:10.1093/ageing/afaf353

J Psychiatry Neurosci. 2025 Dec 1;50(6):E337-E350. doi: 10.1139/jpn-25-0063.

ABSTRACT

BACKGROUND: Brain network dynamics are responsive to task induced fluctuations, but such responsivity may not hold in schizophrenia (SCZ). We introduce and implement Centrality Dynamics (CD), a method developed specifically to capture task-driven dynamic changes in graph theoretic measures of centrality. We applied CD to functional MRI (fMRI) data in SCZ and Healthy Controls (HC) acquired during associative learning.

METHODS: fMRI (3T Siemens Verio) was acquired in 88 participants (49 SCZ). Time series were extracted from 246 functionally defined cerebral nodes. We applied a dynamic windowing technique to estimate 280 partially overlapping connectomes (with 30 135 unique region-pairs per connectome). In each connectome, we calculated every node's Betweenness Centrality (BC) following which we built 246 unique time series from a node's BC in successive connectomes (where each such time series represents a node's CD). Next, in each group similarities in CD were used to cluster nodes.

RESULTS: Clustering revealed fewer sub-networks in SCZ, and these sub-networks were formed by nodes with greater functional heterogeneity. The averaged CD of nodes in these sub-networks also showed greater Approximate Entropy (ApEn) (indicating greater stochasticity) but lower amplitude variability (suggesting less adaptability to task-induced dynamics). Finally, higher ApEn was associated with worse clinical symptoms and poorer task performance.

LIMITATIONS: Centrality Dynamics is a new method for network discovery in health and schizophrenia. Further extensions to other task-driven and resting data in other psychiatric conditions will provide fuller understanding of its promise.

CONCLUSION: The brain's functional connectome under task-driven conditions is not static. Characterizing these task-driven dynamics will provide new insight on the dysconnection syndrome that is schizophrenia. Centrality Dynamics provides novel characterization of task-induced changes in the brain's connectome and shows that in the schizophrenia brain, learning-evoked sub-network dynamics were (a) less responsive to learning evoked changes and (b) showed greater stochasticity.

PMID:41369098 | DOI:10.1139/jpn-25-0063

Quant Imaging Med Surg. 2025 Dec 1;15(12):12707-12720. doi: 10.21037/qims-2025-317. Epub 2025 Nov 21.

ABSTRACT

BACKGROUND: Ischemic stroke affecting the basal ganglia disrupts motor, cognitive, and emotional functions, yet the underlying neural network mechanisms remain poorly understood. This study aimed to investigate alterations in brain network topology in patients with acute basal ganglia ischemic stroke (BGIS) through use of resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory analysis (GTA).

METHODS: We constructed whole-brain functional networks and analyzed global and local topological properties in 82 patients with acute BGIS and compared them those in 83 healthy controls (HCs) using the Dosenbach atlas.

RESULTS: Both groups retained small-world attributes (Sigma >1). However, patients with BGIS exhibited significantly lower normalized clustering coefficient (Gamma, P=0.016), small-worldness (Sigma, P=0.021), and modularity (P=0.025), indicating disrupted local network organization. Local centrality analyses revealed significantly higher degree centrality (DC) (false-discovery rate-corrected Q <0.05), betweenness centrality (Q <0.05), and eigenvector centrality (Q <0.05) in the right precentral gyrus (a motor hub) in patients with BGIS. Conversely, lower centrality was observed in cognitive and emotional hubs, including the left ventral prefrontal cortex (Q <0.05 for DC, betweenness centrality, and eigenvector centrality) and the right dorsolateral superior frontal gyrus (Q <0.05 for DC). Global efficiency and assortativity were preserved (P>0.05). No direct associations between these network alterations and clinical scales persistent in the multiple comparisons.

CONCLUSIONS: This study identified a BGIS-induced reconfiguration of brain network topology, characterized by a tendency toward randomization, compensatory hyperconnectivity in motor regions, and impaired integration in cognitive networks. The findings indicated the right precentral gyrus to be a pivotal hub for poststroke recovery and offers novel insights into network-level mechanisms and potential targets for neuromodulatory interventions.

PMID:41367755 | PMC:PMC12682516 | DOI:10.21037/qims-2025-317

Quant Imaging Med Surg. 2025 Dec 1;15(12):12361-12371. doi: 10.21037/qims-2025-1062. Epub 2025 Nov 21.

ABSTRACT

BACKGROUND: Pituitary adenomas (PA) frequently compress the optic chiasm, leading to visual field defects (VFDs) and potentially affecting the function of brain networks. This cross-sectional study aimed to investigate alterations in brain networks in PA patients with chiasmal compression using resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: In this study, 35 PA patients with chiasmal compression and 33 healthy controls (HCs) were enrolled and underwent rs-fMRI scanning. Network-Based Statistic (NBS) and large-scale network analyses were performed. Additionally, correlations were analyzed between altered functional connectivity (FC) and suprasellar extension distance, duration of VFDs, as well as mean deviation (MD), reflecting the degree of VFDs.

RESULTS: Combining NBS and large-scale network analyses, we found that PA patients with chiasmal compression mainly showed significantly decreased intra- and inter-network connectivity, including the visual network (VN), dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN), frontoparietal network (FPN), somatosensory-motor network (SMN), and subcortical network (SCN). Moreover, the decreased mean FC values within VN and between VN-VAN were negatively correlated with suprasellar extension distance, and the decreased mean FC within VN was positively correlated with MD.

CONCLUSIONS: This study highlights the widespread dysfunction of brain networks in PA patients with chiasmal compression. These findings offer new insights into the brain dysfunction in PA patients with chiasmal compression and could also aid in the evaluation of therapeutic efficacy for the disease.

PMID:41367739 | PMC:PMC12682495 | DOI:10.21037/qims-2025-1062

Sci Data. 2025 Dec 9. doi: 10.1038/s41597-025-06398-3. Online ahead of print.

ABSTRACT

This dataset supports research on neuroplasticity and motor adaptation in motor learning and rehabilitation. It includes multimodal longitudinal data from 46 healthy adults performing motor imagery and physical training of a backward glide shot put task. Participants received one of three interventions: function-specific repetitive transcranial magnetic stimulation (rTMS) guided by task-based functional magnetic resonance imaging (fMRI), rTMS targeting hand motor hotspots, or motor training alone. The dataset contains resting-state and task-based fMRI, individualized stimulation coordinates, and daily kinematic parameters collected before and after intervention. These data enable analysis of brain network plasticity, motor performance changes, and the effects of targeted neuromodulation, providing a reproducible resource for advancing studies on precise brain stimulation and motor rehabilitation.

PMID:41365922 | DOI:10.1038/s41597-025-06398-3

Neuroimage. 2025 Dec 7:121636. doi: 10.1016/j.neuroimage.2025.121636. Online ahead of print.

ABSTRACT

BACKGROUND: Disruptions in synaptic plasticity and alterations in effective connectivity (EC) involving the hippocampus and amygdala are hallmarks of early Alzheimer's disease (AD). However, the interplay between these neurophysiological changes and their relationships with cognitive functions in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains poorly understood.

METHODS: Transcranial magnetic stimulation (TMS) and resting-state functional magnetic resonance imaging (rs-fMRI) were used to assess long-term potentiation (LTP)-like plasticity and EC involving the amygdala and hippocampus in 34 individuals with SCD, 27 with MCI, and 35 healthy controls (HC). Between-group differences in cognitive performance, EC alterations, and LTP-like plasticity were examined and their relationships were assessed via correlation and mediation analyses.

RESULTS: Both SCD and MCI groups exhibited disrupted EC between the amygdala/hippocampus and the inferior occipital gyrus, inferior parietal lobule (IPL), medial frontal lobe (MFL), and precuneus. Also, both LTP-5min and LTP-10min were significantly reduced in MCI group compared to SCD and HC groups. Importantly, EC from the left hippocampus to the IPL and from the IPL, MFL, and precuneus to the hippocampus was correlated with memory and executive functions. Moreover, precuneus-to-hippocampus EC was positively correlated with LTP-10min and mediated the relationship between LTP-like plasticity and cognitive performance.

CONCLUSIONS: This study provides novel evidence that precuneus-to-hippocampus EC mediates the link between synaptic plasticity and cognitive function in SCD and MCI, suggesting the precuneus-hippocampus pathway as a promising target for early diagnosis and intervention.

PMID:41365452 | DOI:10.1016/j.neuroimage.2025.121636

Schizophr Res. 2025 Dec 8;287:113-121. doi: 10.1016/j.schres.2025.12.002. Online ahead of print.

ABSTRACT

BACKGROUND: This study examined topological features and network resilience in schizophrenia spectrum disorders (SSDs), other specified schizophrenia spectrum and other psychotic disorder (OSSO), and healthy controls (HC) with resting-state functional MRI (rs-fMRI) and graph theoretical analysis. Associations between topological metrics, resilience, and symptom severity were also explored.

METHODS: rs-fMRI data from SSDs (n = 77), OSSO (n = 86), and HC (n = 83) were analyzed for global efficiency (Eg), characteristic path length (Lp), nodal local efficiency (NLe), nodal clustering coefficient (NCp), and resilience derived from k-shell decomposition and targeted-attack simulations. Symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS).

RESULTS: Both patient groups showed reduced Eg and increased Lp compared with HC, indicating disrupted global integration. At the nodal level, the fusiform gyrus exhibited decreased NLe and NCp in both groups. In OSSO, these nodal metrics correlated with PANSS general and total scores. SSDs displayed pronounced reductions in k-core and maximum-core resilience, whereas OSSO largely retained network stability. k-Shell resilience was most impaired in SSDs, with OSSO showing intermediate deficits. Notably, k-shell resilience in the right superior occipital gyrus significantly differed between OSSO and SSDs.

CONCLUSION: This study presents the first investigation of OSSO-specific neuroimaging signatures using network resilience analysis. OSSO showed partial preservation of k-core resilience and intermediate k-shell resilience between SSDs and HC, suggesting distinct neurobiological organization within the psychosis spectrum. k-Shell resilience in the superior occipital gyrus may serve as a potential neuroimaging marker distinguishing OSSO from SSDs.

PMID:41365234 | DOI:10.1016/j.schres.2025.12.002

Psychiatry Res Neuroimaging. 2025 Nov 20;356:112093. doi: 10.1016/j.pscychresns.2025.112093. Online ahead of print.

ABSTRACT

Schizophrenia spectrum disorders (SSD) are marked by working memory impairments associated with abnormal functional brain connectivity. Although transcranial magnetic stimulation (TMS) shows promise in modulating dysconnectivity patterns and improving cognitive symptoms, current protocols often lack target personalization, overlooking significant variability in functional network topography between individuals. Twenty-two individuals with SSD and cognitive deficits underwent 20Hz repetitive TMS to the left lateral prefrontal cortex. Personalized TMS targeted regions with the strongest central executive-default mode network (CEN-DMN) antagonism, while standardized TMS focused on the EEG F3 site. Resting-state fMRI scans were conducted pre- and post-TMS sessions to evaluate changes in CEN-DMN connectivity, and working memory performance was assessed after the post-TMS fMRI scan. Both TMS protocols failed to significantly alter CEN-DMN connectivity or improve cognitive function, which may be due to the low reliability of the biomarker used for personalized targeting. However, stronger DMN intra-network connectivity at the stimulation site was positively correlated with a reduction in CEN-DMN connectivity and improved working memory performance. These findings highlight the need for more extensive fMRI data for better target determination, and suggest that targeting left prefrontal areas with higher DMN connectivity could more effectively modulate functional connectivity and improve working memory performance through TMS.

PMID:41364985 | DOI:10.1016/j.pscychresns.2025.112093

Addict Behav. 2025 Nov 27;174:108575. doi: 10.1016/j.addbeh.2025.108575. Online ahead of print.

ABSTRACT

Problematic smartphone use (PSU) has been associated with withdrawal-like symptoms and altered intrinsic neural activity (INA). While previous studies suggest that PSU affects brain function, little is known about how INA is modulated by smartphone restriction. This longitudinal fMRI study investigated group- and time-dependent changes in resting-state INA following short-term smartphone deprivation. 36 participants (aged 18-29; 22 female) were categorized into PSU (n = 19) and non-PSU (n = 17) groups using the Smartphone Addiction Scale-Short Version (SAS-SV). Resting-state fMRI scans were obtained before and after a 72-hour period of smartphone restriction. Psychometric measures included the Mannheim Craving Scale (MaCS) and the Smartphone Addiction Inventory (SPAI). A significant group-by-time interaction revealed INA changes in the left inferior frontal gyrus, bilateral posterior cingulate cortex, right middle frontal and precentral gyri, and left calcarine cortex. INA increased over time in the non-PSU group but decreased in the PSU group in prefrontal and cingulate areas. In contrast, sensorimotor and occipital regions showed increased INA over time in PSU individuals. Associations between neural activity and MaCS scores indicated that greater craving was linked to reduced INA in the posterior cingulate cortex. Within the PSU group, higher smartphone-use severity, as measured by the SPAI, was associated with altered INA in occipital, parietal, and cerebellar regions. These findings suggest PSU is linked to distinct and state-dependent neurofunctional alterations that may reflect withdrawal-related processes and maladaptive reward and cognitive control mechanisms.

PMID:41364954 | DOI:10.1016/j.addbeh.2025.108575

Cereb Cortex. 2025 Nov 27;35(12):bhaf330. doi: 10.1093/cercor/bhaf330.

ABSTRACT

Adequately responding towards a threat is a crucial mechanism for survival. Adapting this response when a threat-associated stimulus or situation has become safe requires extinction learning and formation of an extinction memory. Functional magnetic resonance imaging (fMRI) affords to longitudinally monitor network activity, yet, in the rodent, still suffers from significant variability of results and practical restrictions, mainly related to the different approaches of subject immobilization. Physical restraint of awake animals permits only short scanning times, while anesthesia can induce uncontrolled brain states with limited stimulus responsiveness and processing. Here, we implement a paradigm where light medetomidine sedation permits long scanning times in a stable brain state with functional characteristics comparable to the human resting state. We observe responsiveness of the brain to visual stimulation and large-scale resting-state network activity with small-world connectivity features. After visual fear conditioning outside the MRI scanner, rats exposed to the unreinforced visual conditioned stimulus in this stable persistent activity state inside the scanner (extinction) exhibit a significantly lower conditioned fear response when re-exposed to the conditioned stimulus days after scanning (test). We present a brain state-informed paradigm easily adaptable for future studies involving invasive neural manipulations to causally investigate extinction and its memory consolidation.

PMID:41364669 | DOI:10.1093/cercor/bhaf330

Cereb Cortex. 2025 Nov 27;35(12):bhaf327. doi: 10.1093/cercor/bhaf327.

ABSTRACT

The hippocampus, in both children and adults, has shown functional specialization along its long axis, with the anterior region associated with emotional processing and the posterior region with spatial memory and navigation. This specialization is also reflected in separate patterns of functional connectivity, but it is unclear whether it is present before birth. Here, we collected resting-state fMRI data in 51 healthy third-trimester fetuses to examine long-axis functional specialization in utero. Using structural regions of interest in the anterior and posterior hippocampus, a seed-based connectivity analysis was performed. We identified distinct networks of functional organization for the anterior and posterior hippocampus. These patterns showed spatial organization and anticorrelation consistent with long-axis specialization. While less mature than those observed in postnatal human and preclinical models, the fetal patterns suggest that the foundation for hippocampal functional differentiation supporting early affective and cognitive processing is already present before birth. Key points We used resting-state fMRI in the third trimester fetal brain to examine the functional projections of the anterior and posterior hippocampus. We identified distinct networks of functional organization that were independently related to the anterior and posterior hippocampus. The groundwork for the specificity of the hippocampus is being laid in utero, with functional anticorrelation contributing to the separation between long-axis segments.

PMID:41364666 | DOI:10.1093/cercor/bhaf327

Cereb Cortex. 2025 Nov 27;35(12):bhaf322. doi: 10.1093/cercor/bhaf322.

ABSTRACT

Choice consistency denotes the capacity to maintain stable, coherent preferences across diverse contexts-a cornerstone of rational decision-making. However, real-world decisions frequently diverge from normative models, marked by inconsistencies and irrationalities. Memory processes may underlie this variability, influencing the formation and maintenance of choice consistency. Yet, the interplay between memory and choice consistency, particularly their shared neural substrates, remains poorly understood. To address these gaps, we developed a novel behavioral paradigm integrating memory retrieval and food-based decision tasks. Resting-state and task functional magnetic resonance imaging data were acquired from 44 healthy young adults (age range: 18 to 27 years). Behaviorally, remembered food items exhibited significantly faster choice reaction times compared to forgotten items. Leveraging data-driven connectome-based predictive modeling of resting-state functional connectivity, we identified distinct neural predictors: intra-default mode network connectivity and default mode network-memory network connectivity positively predicted memory accuracy, whereas default mode network-frontoparietal control network connectivity negatively predicted memory accuracy. Furthermore, intra-default mode network connectivity and default mode network-frontoparietal control network connectivity positively predicted choice consistency. These findings advance our understanding of memory-decision interactions, highlighting the default mode network and frontoparietal control network as critical neural substrates that bridge mnemonically modulated value signals and choice consistency.

PMID:41364664 | DOI:10.1093/cercor/bhaf322

Neuroimage Rep. 2025 Nov 20;5(4):100300. doi: 10.1016/j.ynirp.2025.100300. eCollection 2025 Dec.

ABSTRACT

The ability to complete activities of daily living (ADLs) is an important part of daily life and can promote well-being and independence. There is currently limited knowledge of brain activity during ADLs (e.g. dressing tasks). Previous studies explored brain activity during dressing using functional magnetic resonance imaging (fMRI); however, the supine position during fMRI is not a natural dressing posture and may impact findings. Functional near-infrared spectroscopy (fNIRS) is a promising method of data collection as it can investigate brain activity in a natural state (sitting) during dressing. In this study, to understand brain activity during buttoning in unimpaired adults, twenty participants (25-65 years) completed an upper extremity task of buttoning in three 20 s repetitions with 15 s rest in between each activity block. Brain activation patterns were recorded using fNIRS over the prefrontal, premotor, supplementary motor, sensorimotor, and posterior parietal cortices. Compared to the resting period, significantly higher activation during the activity block was observed in all recorded regions but the posterior parietal cortex. Understanding brain activity in unimpaired adults during the performance of activities of daily living is a critical first-step for investigating brain activation in different clinical populations.

PMID:41362878 | PMC:PMC12681552 | DOI:10.1016/j.ynirp.2025.100300

Depress Anxiety. 2025 Nov 30;2025:4530547. doi: 10.1155/da/4530547. eCollection 2025.

ABSTRACT

OBJECTIVE: This study aimed to investigate the relationship between alterations in lymphocyte subsets and resting-state functional magnetic resonance imaging (rs-fMRI) patterns in patients with comorbid major depressive disorder (MDD) and insomnia disorder (ID).

METHODS: A total of 114 patients with MDD, 108 with ID, 126 with comorbid MDD and ID, and 168 healthy controls (HCs) were recruited, all experiencing their first episode. Emotional and sleep quality were assessed using the 17-item Hamilton Depression Rating Scale (HAMD-17), self-rating depression scale (SDS), Hamilton Anxiety Scale, self-rating anxiety scale (SAS), Pittsburgh Sleep Quality Index (PSQI), and Insomnia Severity Index (ISI). rs-fMRI data and lymphocyte subsets were analyzed. Multivariate prediction models were constructed using correlation analysis, least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation, and logistic regression. Model performance was evaluated with calibration curves and receiver operating characteristic (ROC) analysis.

RESULTS: No significant differences were observed in age (p=0.552), sex distribution (p=0.248), education level, or anxiety scores among the four groups, whereas depression and insomnia scores differed significantly (all p < 0.0001). The MDD with comorbid insomnia (iMDD) group exhibited lower fractional amplitude of low-frequency fluctuations (fALFFs) in the right lingual gyrus and fusiform gyrus compared to the MDD, ID, and HC groups. Additionally, compared with HCs, CD3+ and CD4+ T cell percentages were elevated, while natural killer (NK) cell percentage was reduced, with the most pronounced alterations in the iMDD group. fALFF values were negatively correlated with CD3+ and CD4+ T cell percentages, but positively correlated with NK cell percentage. The fALFF in the right lingual gyrus, CD4+ T and NK cell percentage, SDS score, and ISI score were identified as key risk predictors. Multivariable prediction models for ID, MDD, and iMDD demonstrated robust calibration (e.g., calibration degree = 0.502), high discrimination (AUC for iMDD vs. HC = 0.991; MDD vs. ID = 0.821), and good clinical applicability.

CONCLUSIONS: The identified risk predictors might facilitate individualized clinical decision-making for iMDD patients. While the multivariable prediction model demonstrated strong internal diagnostic accuracy, further external validation using independent cohorts is needed to confirm its generalizability.

PMID:41362845 | PMC:PMC12682451 | DOI:10.1155/da/4530547