Most recent paper

PLoS One. 2025 Mar 18;20(3):e0319746. doi: 10.1371/journal.pone.0319746. eCollection 2025.

ABSTRACT

Functional connectomics is a popular approach to investigate the neural underpinnings of developmental disorders of which attention deficit hyperactivity disorder (ADHD) is one of the most prevalent. Nonetheless, neuronal mechanisms driving the aberrant functional connectivity resulting in ADHD symptoms remain largely unclear. Whereas resting state activity reflecting intrinsic tonic background activity is only vaguely connected to behavioral effects, naturalistic neuroscience has provided means to measure phasic brain dynamics associated with overt manifestation of the symptoms. Here we collected functional magnetic resonance imaging (fMRI) data in three experimental conditions, an active virtual reality (VR) task where the participants execute goal-directed behaviors, a passive naturalistic Video Viewing task, and a standard Resting State condition. Thirty-nine children with ADHD and thirty-seven typically developing (TD) children participated in this preregistered study. Functional connectivity was examined with network-based statistics (NBS) and graph theoretical metrics. During the naturalistic VR task, the ADHD group showed weaker task performance and stronger functional connectivity than the TD group. Group differences in functional connectivity were observed in widespread brain networks: particularly subcortical areas showed hyperconnectivity in ADHD. More restricted group differences in functional connectivity were observed during the Video Viewing, and there were no group differences in functional connectivity in the Resting State condition. These observations were consistent across NBS and graph theoretical analyses, although NBS revealed more pronounced group differences. Furthermore, during the VR task and Video Viewing, functional connectivity in TD controls was associated with task performance during the measurement, while Resting State activity in TD controls was correlated with ADHD symptoms rated over six months. We conclude that overt expression of the symptoms is correlated with aberrant brain connectivity in ADHD. Furthermore, naturalistic paradigms where clinical markers can be coupled with simultaneously occurring brain activity may further increase the interpretability of psychiatric neuroimaging findings.

PMID:40100891 | DOI:10.1371/journal.pone.0319746

Front Aging Neurosci. 2025 Mar 3;17:1499262. doi: 10.3389/fnagi.2025.1499262. eCollection 2025.

ABSTRACT

BACKGROUND: Chronic pain is a common non-motor symptom of Parkinson's disease (PD) that significantly impacts patients' quality of life, but its neural mechanisms remain poorly understood. This study investigated changes in spontaneous neuronal activity and functional connectivity (FC) associated with chronic pain in PD patients.

METHODS: The study included 41 PD patients with chronic pain (PDP), 41 PD patients without pain (nPDP), and 29 healthy controls. Pain severity was assessed using the visual analog scale (VAS). Resting-state fMRI images were used to measure the amplitude of low-frequency fluctuations (ALFF) as an indicator of regional brain activity. Subsequently, FC analysis was performed to evaluate synchronization between ALFF-identified regions and the entire brain.

RESULTS: Compared to nPDP patients, PDP patients exhibited decreased ALFF in the right putamen, and increased ALFF in motor regions, including the right superior frontal gyrus/supplementary motor area and the left paracentral lobule/primary motor cortex. Additionally, PDP patients exhibited diminished right putamen-based FC in the midbrain, anterior cingulate cortex, orbitofrontal cortex, middle frontal gyrus, middle temporal gyrus, and posterior cerebellar lobe. The correlation analysis revealed that ALFF values in the right putamen were negatively associated with VAS scores in PDP patients.

CONCLUSION: This study demonstrates that chronic pain in PD is associated with reduced ALFF in the putamen and disrupted FC with brain regions involved in pain perception and modulation, highlighting the critical role of dopaminergic degeneration in the development and maintenance of pain in PD.

PMID:40099248 | PMC:PMC11911387 | DOI:10.3389/fnagi.2025.1499262

Ann Gen Psychiatry. 2025 Mar 17;24(1):14. doi: 10.1186/s12991-025-00553-1.

ABSTRACT

BACKGROUND: The growing popularity of internet gaming among adolescents and young adults has driven an increase in both casual and excessive gaming behavior. Nevertheless, it remains unclear how progressive increases in internet gaming engagement led to changes within and between brain networks. This study aims to investigate these connectivity alterations across varying levels of gaming involvement.

METHODS: In this cross-sectional study, 231 participants were recruited and classified into three groups according to Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria for Internet Gaming Disorder (IGD): IGD group, highly engaged gaming(HEG) group, and lowly engaged gaming (LEG) group. Resting-state fMRI data from 217 participants (143 males, 74 females) were included in the final analysis. Independent component analysis was used to examine differences in intra- and inter-network functional connectivity (FC)across the three groups.

RESULTS: No significant differences were found in intra-network FC across the three groups. However, significant inter-network differences between the dorsal attention network(dAN)and the visual network (VN) among the three groups were observed. The HEG group exhibited significantly higher dAN-VN functional network connectivity (FNC) compared to the LEG group. Linear correlation analyses showed no significant correlation between the dAN-VN FNC values and IGD-20T scores.

CONCLUSION: Throughout the development of IGD, increasing levels of engagement are associated with a rise and subsequent decline in FNC of DAN-VN. This pattern may reflect top-down attentional regulation in the early stages of addiction, followed by attentional bias as addiction progresses.

PMID:40098002 | DOI:10.1186/s12991-025-00553-1

Transl Psychiatry. 2025 Mar 17;15(1):86. doi: 10.1038/s41398-025-03265-y.

ABSTRACT

Major depressive disorder (MDD) is a common psychiatric condition associated with aberrant functional connectivity in large-scale brain networks. However, it is unclear how the network dysfunction is characterized by imbalance or derangement of network modular interaction in MDD patients and whether this disruption is associated with gene expression profiles. We included 262 MDD patients and 297 healthy controls, embarking on a comprehensive analysis of intrinsic brain activity using resting-state functional magnetic resonance imaging (R-fMRI). We assessed brain network integration by calculating the Participation Coefficient (PC) and conducted an analysis of intra- and inter-modular connections to reveal the dysconnectivity patterns underlying abnormal PC manifestations. Besides, we explored the potential relationship between the above graph theory measures and clinical symptoms severity in MDD. Finally, we sought to uncover the association between aberrant graph theory measures and postmortem gene expression data sourced from the Allen Human Brain Atlas (AHBA). Relative to the controls, alterations in systemic functional connectivity were observed in MDD patients. Specifically, increased PC within the bilateral visual network (VIS) was found, accompanied by elevated functional connectivities (FCs) between VIS and both higher-order networks and Limbic network (Limbic), contrasted by diminished FCs within the VIS and between the VIS and the sensorimotor network (SMN). The clinical correlations indicated positive associations between inter-VIS FCs and depression symptom, whereas negative correlations were noted between intra-VIS FCs with depression symptom and cognitive disfunction. The transcriptional profiles explained 21-23.5% variance of the altered brain network system dysconnectivity pattern, with the most correlated genes enriched in trans-synaptic signaling and ion transport regulation. These results highlight the modular connectome dysfunctions characteristic of MDD and its linkage with gene expression profiles and clinical symptomatology, providing insight into the neurobiological underpinnings and holding potential implications for clinical management and therapeutic interventions in MDD.

PMID:40097427 | DOI:10.1038/s41398-025-03265-y

Cold Spring Harb Perspect Med. 2025 Mar 17:a041841. doi: 10.1101/cshperspect.a041841. Online ahead of print.

ABSTRACT

Functional neuroimaging techniques are increasingly being used to advance the diagnosis and management of Parkinson's disease (PD). Methods such as [18F]-fluorodeoxyglucose positron emission tomography (FDG PET), resting-state functional magnetic resonance imaging (rs-fMRI), arterial spin labeling (ASL) MRI, and single-photon emission computed tomography (SPECT) enable the identification of disease-specific patterns like the PD-related pattern (PDRP) and PD cognition-related pattern (PDCP), which correlate with motor and cognitive symptoms. Network analysis using graph theory further elucidates the alterations in brain connectivity associated with PD, providing insights into disease progression and response to treatment. Moreover, these neuroimaging patterns assist in distinguishing PD from atypical parkinsonian syndromes, enhancing diagnostic accuracy. Understanding the impact of genetic variants like LRRK2 and GBA1 on functional connectivity highlights the potential for precision medicine in PD. As neuroimaging technologies evolve, their integration into clinical practice will be pivotal in the personalized management of PD, offering improved diagnostic precision and targeted therapeutic interventions.

PMID:40097189 | DOI:10.1101/cshperspect.a041841

Hum Brain Mapp. 2025 Apr 1;46(5):e70193. doi: 10.1002/hbm.70193.

ABSTRACT

Delineating the functional organization of mesoscale cortical columnar structure is essential for understanding brain function. We have previously demonstrated a high spatial correspondence between BOLD fMRI and LFP responses to tactile stimuli in the primary somatosensory cortex area 3b of nonhuman primates. This study aims to explore how 2D spatial profiles of the functional column vary across cortical layers (defined by three cortical depths) in both tactile stimulation and resting states using fMRI. At 9.4 T, we acquired submillimeter-resolution oblique fMRI data from cortical areas 3b and 1 of anesthetized squirrel monkeys and obtained fMRI signals from three cortical layers. In both areas 3b and 1, the tactile stimulus-evoked fMRI activation foci were fitted with point spread functions (PSFs), from which shape parameters, including full width at half maximum (FWHM), were derived. Seed-based resting-state fMRI data analysis was then performed to measure the spatial profiles of resting-state connectivity within and between areas 3b and 1. We found that the tactile-evoked fMRI response and local resting-state functional connectivity were elongated at the superficial layer, with the major axes oriented in lateral to medial (from digit 1 to digit 5) direction. This elongation was significantly reduced in the deeper (middle and bottom) layers. To assess the robustness of these spatial profiles in distinguishing cortical layers, shape parameters describing the spatial extents of activation and resting-state connectivity profiles were used to classify the layers via self-organizing maps (SOM). A minimal overall classification error (~13%) was achieved, effectively classifying the layers into two groups: the superficial layer exhibited distinct features from the two deeper layers in the rsfMRI data. Our results support distinct 2D spatial profiles for superficial versus deeper cortical layers and reveal similarities between stimulus-evoked and resting-state configurations.

PMID:40095731 | DOI:10.1002/hbm.70193

J Alzheimers Dis. 2025 Mar 17:13872877251317489. doi: 10.1177/13872877251317489. Online ahead of print.

ABSTRACT

BackgroundGenetic susceptibility is a primary factor contributing to etiology of late-onset Alzheimer's disease (LOAD). The exact mechanisms and timeline through which APOE/PICALM influence brain functions and contribute to LOAD remain unidentified. This includes their effects on individuals prior to the development of the disease.ObjectiveTo investigate the effects of APOE and PICALM risk genes on brain health and function in non-demented individuals. This study aims to differentiate the combined risk effects of both genes from the risk associated solely with APOE, and to examine how PICALM alleles influence the risk linked to APOE.MethodsAPOE/PICALM alleles were assessed to determine the genetic risk of LOAD in 79 healthy, middle-aged participants who underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings. The resting-state signal was analyzed to estimate relative spectral power, complexity (Higuchi's algorithm), and connectivity (coherence in EEG and independent component analysis-based connectivity in fMRI).ResultsThe main findings indicated that individuals at risk for LOAD exhibited reduced signal complexity and the so-called "slowing of EEG" which are well-known EEG markers of Alzheimer's disease. Additionally, these individuals showed altered functional connectivity in fMRI (within attention-related areas).ConclusionsRisk alleles of APOE/PICALM may affect brain integrity and function prior to the clinical onset of the disease.

PMID:40095677 | DOI:10.1177/13872877251317489

medRxiv [Preprint]. 2025 Mar 3:2025.02.27.25322899. doi: 10.1101/2025.02.27.25322899.

ABSTRACT

Resting-state fMRI (rs-fMRI) captures brain activity at rest, it demonstrates information on how different regions interact without explicity task-based influences. This provides insights into both healthy and disordered brain states. However, clinical application of rs-fMRI remains challenging due to the wide variability in functional connectivity across individuals. Traditional data-driven methods like independent component analysis (ICA) struggle to balance these individual differences with broader patterns. Constrained methods, such as constrained ICA (cICA), have been introduced to address this by integrating templates from multiple external datasets to enhance accuracy and consistency. In our study, we analyzed rs-fMRI data from 100,517 individuals from diverse datasets, processed through a robust quality-control dynamic connectivity pipeline established in previous work. Using the resulting brain state templates as cICA priors, we examined the effectiveness of cICA for schizophrenia classification using a combined CNN and LSTM architecture. Results showed stable classification accuracy (87.6% to 86.43%) for the CNN model, while the LSTM model performed less optimally, likely due to sequence processing, yet still yielded comparable results. These findings underscore the potential of group-informed methods and prior data templates in constrained dynamic ICA, offering improved reliability and clinical relevance in rs-fMRI analysis and advancing our understanding of brain function.

PMID:40093229 | PMC:PMC11908281 | DOI:10.1101/2025.02.27.25322899

medRxiv [Preprint]. 2025 Mar 5:2025.03.02.25322248. doi: 10.1101/2025.03.02.25322248.

ABSTRACT

OBJECTIVE: Determine whether acute behavioral, electroencephalography (EEG), and functional MRI (fMRI) biomarkers of consciousness are associated with outcome after severe traumatic brain injury (TBI).

METHODS: Patients with acute severe TBI admitted consecutively to the intensive care unit (ICU) participated in a multimodal battery assessing behavioral level of consciousness (Coma Recovery Scale-Revised [CRS-R]), cognitive motor dissociation (CMD; task-based EEG and fMRI), covert cortical processing (CCP; stimulus-based EEG and fMRI), and default mode network connectivity (DMN; resting-state fMRI). The primary outcome was 6-month Disability Rating Scale (DRS) total scores.

RESULTS: We 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). Behavioral level of consciousness and presence of command-following in the ICU were each associated with lower (i.e., better) DRS scores (p=0.003, p=0.011). EEG and fMRI biomarkers did not strengthen this relationship, but higher DMN connectivity was associated with better recovery on multiple secondary outcome measures. In a subsample of participants without command-following on the CRS-R, CMD (EEG:18%; fMRI:33%) and CCP (EEG:91%; fMRI:79%) were not associated with outcome, an unexpected result that may reflect the high rate of WLST. However, higher DMN connectivity was associated with lower DRS scores (ρ[95%CI]=-0.41[-0.707, -0.027]; p=0.046) in this group.

INTERPRETATION: Standardized behavioral assessment in the ICU may improve prediction of recovery from severe TBI. Further research is required to determine whether integrating behavioral, EEG, and fMRI biomarkers of consciousness is more predictive than behavioral assessment alone.

PMID:40093212 | PMC:PMC11908294 | DOI:10.1101/2025.03.02.25322248

bioRxiv [Preprint]. 2025 Mar 5:2025.03.04.641400. doi: 10.1101/2025.03.04.641400.

ABSTRACT

It is frequently assumed that the phenotypic heterogeneity in autism spectrum disorder reflects underlying pathobiological variation. However, direct evidence in support of this hypothesis is lacking. Here, we leverage cross-species functional neuroimaging to examine whether variability in brain functional connectivity reflects distinct biological mechanisms. We find that fMRI connectivity alterations in 20 distinct mouse models of autism (n=549 individual mice) can be clustered into two prominent hypo- and hyperconnectivity subtypes. We show that these connectivity profiles are linked to distinct signaling pathways, with hypoconnectivity being associated with synaptic dysfunction, and hyperconnectivity reflecting transcriptional and immune-related alterations. Extending these findings to humans, we identify analogous hypo- and hyperconnectivity subtypes in a large, multicenter resting state fMRI dataset of n=940 autistic and n=1036 neurotypical individuals. Remarkably, hypo- and hyperconnectivity autism subtypes are replicable across independent cohorts (accounting for 25.1% of all autism data), exhibit distinct functional network architecture, are behaviorally dissociable, and recapitulate synaptic and immune mechanisms identified in corresponding mouse subtypes. Our cross-species investigation, thus, decodes the heterogeneity of fMRI connectivity in autism into distinct pathway-specific etiologies, offering a new empirical framework for targeted subtyping of autism.

PMID:40093106 | PMC:PMC11908180 | DOI:10.1101/2025.03.04.641400

Psychol Med. 2025 Mar 17;55:e88. doi: 10.1017/S0033291725000510.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD) is marked by significant changes to the local synchrony of spontaneous neural activity across various brain regions. However, many methods for assessing this local connectivity use fixed or arbitrary neighborhood sizes, resulting in a decreased capacity to capture smooth changes to the spatial gradient of local correlations. A newly developed method sensitive to classical anatomo-functional boundaries, Iso-Distant Average Correlation (IDAC), was therefore used to examine depression associated alterations to the local functional connectivity of the brain.

METHOD: One-hundred and forty-seven adolescents and young adults with MDD and 94 healthy controls underwent a resting-state functional magnetic resonance imaging (fMRI) scan. Whole-brain functional connectivity maps of intracortical neural activity within iso-distant local areas (5-10, 15-20, and 25-30 mm) were generated to characterize local fMRI signal similarities.

RESULTS: Across all spatial distances, MDD participants demonstrated greater local functional connectivity of the bilateral posterior hippocampus, retrosplenial cortex, dorsal insula, fusiform gyrus, and supplementary motor area. Local connectivity alterations in short and medium distances (5-10 and 15-20 mm) in the mid insula cortex were additionally associated with expressive suppression use, independent of depressive symptom severity.

CONCLUSIONS: Our study identified increased synchrony of the neural activity in several regions commonly implicated in the neurobiology of depression. These effects were relatively consistent across the three distances examined. Longitudinal investigation of this altered local connectivity will clarify whether these differences are also found in other age groups and if this relationship is modified by increased disease chronicity.

PMID:40091390 | DOI:10.1017/S0033291725000510

Commun Biol. 2025 Mar 16;8(1):447. doi: 10.1038/s42003-025-07889-0.

ABSTRACT

Resting-state functional magnetic resonance imaging (fMRI) is used to derive functional connectivity (FC) between brain regions. Typically, blood oxygen level-dependent (BOLD) contrast is used. However, BOLD's reliance on neurovascular coupling poses challenges in reflecting brain activity accurately, leading to reduced sensitivity in white matter (WM). WM BOLD signals have long been considered physiological noise, although recent evidence shows that both stimulus-evoked and resting-state WM BOLD signals resemble those in gray matter (GM), albeit smaller in amplitude. We introduce apparent diffusion coefficient fMRI (ADC-fMRI) as a promising functional contrast for GM and WM FC, capturing activity-driven neuromorphological fluctuations. Our study compares BOLD-fMRI and ADC-fMRI FC in GM and WM, showing that ADC-fMRI mirrors BOLD-fMRI connectivity in GM, while capturing more robust FC in WM. ADC-fMRI displays higher average clustering and average node strength in WM, and higher inter-subject similarity, compared to BOLD. Taken together, this suggests that ADC-fMRI is a reliable tool for exploring FC that incorporates gray and white matter nodes in a novel way.

PMID:40091123 | DOI:10.1038/s42003-025-07889-0

Neurosci Biobehav Rev. 2025 Mar 14:106106. doi: 10.1016/j.neubiorev.2025.106106. Online ahead of print.

ABSTRACT

Metastability is proposed as the mechanism supporting our adaptive responses to the environment. While extensive research has characterized brain metastability during rest and task performance, prior studies have mainly focused on understanding underlying mechanisms, with limited exploration of its application in mental processes and behaviors. This scoping review offers an overview of the existing empirical literature in this area. Through a systematic search that included 36 articles, our results reveal a predominance of resting-state fMRI studies, variability in how metastability is defined, and a lack of consideration for common confounds in neuroimaging data. The review concludes with suggestions for future research directions to address crucial unresolved issues in the field.

PMID:40090532 | DOI:10.1016/j.neubiorev.2025.106106

J Psychiatr Res. 2025 Mar 6;184:395-404. doi: 10.1016/j.jpsychires.2025.02.055. Online ahead of print.

ABSTRACT

In Body Integrity Dysphoria (BID) a profound incongruity between the physical body and the desired, i.e., amputated body, often leads to a desire for limb amputation. Virtual reality (VR) and multisensory stimulation paradigms provide powerful tools to create the experience of being embodied in an amputated body. Here we investigate the impact of such an experience on neural and subjective responses in 18 individuals with BID and 18 controls. We used both task-based and resting-state MRI before and after participants played an immersive virtual game in an amputated body corresponding to their desired bodily shape and mimicking their movements. The task-based fMRI assessed neural activity when viewing images of the body in the desired versus the undesired state. Individuals with BID reported higher sense of ownership and control over the virtual body. Task-based fMRI showed increased pre-VR activity in the right superior parietal lobule (rSPL), right angular gyrus, and right supplementary motor area in the BID group, normalizing after VR exposure. Resting-state fMRI showed reduced connectivity in the rSPL, visuo-occipital areas, fronto-parietal, and fronto-striatal mirror and limb system networks, also normalizing post-VR. Additionally, there was a normalization in the pattern of increased connectivity of cortico-striatal tracts connecting the rSPL and the pars orbitalis of the right inferior frontal gyrus with the nucleus accumbens. Our findings suggest that virtual embodiment effectively modulates BID-related neural networks, offering a safe, cost-effective intervention for BID and highlights VR's potential in exploring the complex interaction between body and self, with potential implications for similar psychiatric conditions.

PMID:40090220 | DOI:10.1016/j.jpsychires.2025.02.055

Transl Psychiatry. 2025 Mar 15;15(1):81. doi: 10.1038/s41398-025-03303-9.

ABSTRACT

Noninvasive brain stimulation (NIBS) has emerged as a promising therapeutic approach for attention-deficit/hyperactivity disorder (ADHD), yet the inaccurate selection of stimulation sites may constrain its efficacy. This study aimed to identify novel NIBS targets for ADHD by integrating meta-analytic findings with cross-dataset validation of functional connectivity patterns. A meta-analysis including 124 functional magnetic resonance imaging (fMRI) studies was first conducted to delineate critical brain regions associated with ADHD, which were defined as regions of interest (ROIs). Subsequently, functional connectivity (FC) analysis was performed using resting-state fMRI data from two independent databases comprising 116 patients with ADHD. Surface brain regions exhibiting consistent FC patterns with the ADHD-related ROIs across both datasets were identified as candidate NIBS targets. These targets were then translated to scalp-level stimulation sites using the 10-20 system and continuous proportional coordinates (CPC). Key regions mapped to the scalp included the bilateral dorsolateral prefrontal cortex, right inferior frontal gyrus, bilateral inferior parietal lobule, supplementary motor area (SMA), and pre-SMA. These findings propose a set of precise stimulation location for NIBS interventions in ADHD, potentially broadening the scope of neuromodulation strategies for this disorder. The study emphasized the utility of cross-dataset functional connectivity analysis in refining NIBS target selection and highlights novel brain targets that warrant further investigation in clinical trials.

PMID:40089469 | DOI:10.1038/s41398-025-03303-9

Neuropsychologia. 2025 Mar 13:109124. doi: 10.1016/j.neuropsychologia.2025.109124. Online ahead of print.

ABSTRACT

Virtual reality (VR) technology has received considerable attention over the last few years, with applications in many performance domains including training of sports-related mental and motor skills. The exact psychological and neurobiological mechanisms underlying potential VR training effects in athletes, however, remain largely unknown. The present longitudinal functional magnetic resonance imaging (fMRI) case study reports behavioral and neuroanatomical effects of VR soccer (a.k.a. football) heading training in a male adult amateur player. The study was conducted over 8 weeks, starting with a pre-test, followed by a 4-week VR training phase, during which weekly fMRI assessments and the first behavioral post-test were conducted. After an additional 4-week retention phase, the final fMRI assessment and the second behavioral post-test were conducted. Substantial improvement in real-life heading performance was accompanied by both structural and functional neuroanatomical changes. The comparison of the T1-weighted images revealed an increase in GM volume in the left thalamus and an increase in WM volume in the bilateral cerebellum. Furthermore, the analysis of the surface images showed an increase in cortical thickness in the right insula, left inferior temporal gyrus, left parahippocampal gyrus, left lingual gyrus, left posterior cingulate cortex, and bilateral anterior cingulate and medial prefrontal cortex. The seed-based correlation analyses of the resting-state fMRI data revealed manifold increases in functional connectivity within and between important brain networks. This study contributes to the growing literature on VR training in athletes and provides the world's first evidence on fundamental neurobiological mechanisms underlying neuroplasticity related to VR training effects in sports.

PMID:40089102 | DOI:10.1016/j.neuropsychologia.2025.109124

Sci Rep. 2025 Mar 14;15(1):8853. doi: 10.1038/s41598-025-92849-1.

ABSTRACT

Major depressive disorder (MDD) is a highly heterogeneous psychiatric disorder characterized with considerable individual variability in clinical manifestations which may correspond to brain alterations including the default mode network (DMN). This study analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from 796 MDD patients and 823 healthy controls (HC) to investigate individual variability in functional connectivity (IVFC) between the DMN and 108 non-DMN regions. We aimed to identify MDD-related IVFC abnormalities and their clinical relevance, alongside exploring gene expression correlations. The results revealed similar spatial patterns of IVFC within the DMN in both groups, yet significantly increased IVFC values in MDD patients were observed in regions such as the ventromedial prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, fusiform gyrus, and occipital cortex. Notably, the mean IVFC in the DMN and fusiform gyrus was positively correlated with Hamilton Rating Scale for Depression (HAMD) scores in MDD patients. Gene expression analyses explained 47.0% of the variance in MDD-related IVFC alterations, with the most associated genes enriched in processes including membrane potential regulation, head development, synaptic transmission, and dopaminergic synapse. These findings highlight the clinical importance of IVFC variability in the DMN and suggest its potential role as a biomarker in MDD.

PMID:40087380 | DOI:10.1038/s41598-025-92849-1

Prog Neuropsychopharmacol Biol Psychiatry. 2025 Mar 12:111326. doi: 10.1016/j.pnpbp.2025.111326. Online ahead of print.

ABSTRACT

Maladaptive brain plasticity has been reported in chronic pain (CP) conditions, though it remains unclear if there are common alterations across pathologies. Therefore, we systematically synthesized literature comparing resting-state functional magnetic resonance imaging (rs-fMRI) in CP patients and healthy controls (HC), and meta-analyzed data whenever applicable. Separate meta-analyses were performed for each method - (fractional) amplitude of low-frequency fluctuations (fALFF, ALFF), regional homogeneity (ReHo), seed-based connectivity (according to the seed) and independent component analysis (according to the network). In qualitative synthesis, sensory-discriminative pain processing - thalamus, insula, temporal and sensory cortices - and cognitive and emotional processing - cingulate, prefrontal and parietal cortices and precuneus - regions concentrated CP/HC differences. Meta-analyses revealed decreased ALFF and increased ReHo in the precuneus, increased fALFF in the left posterior insula and disrupted within- and cross-network connectivity of default mode network (DMN) nodes, as well as altered connectivity in top-down pain modulation pathways. Specifically, it showed decreased anterior and increased posterior components' representation within DMN, enhanced connectivity between the medial prefrontal cortex (mPFC, part of the DMN) and anterior insula (part of the salience network), and decreased mPFC connectivity with the periaqueductal gray matter (PAG). Collectively, results suggest that CP disrupts the natural functional organization of the brain, particularly impacting DMN nodes (mPFC and precuneus), insula and top-town pain modulation circuits.

PMID:40086716 | DOI:10.1016/j.pnpbp.2025.111326

Dev Cogn Neurosci. 2025 Mar 4;73:101541. doi: 10.1016/j.dcn.2025.101541. Online ahead of print.

ABSTRACT

Adolescence is a key period for the maturation of cognitive control during which cortical circuitry is refined through processes such as synaptic pruning, but how these refinements modulate local functional dynamics to support cognition remains only partially characterized. Here, we used data from a longitudinal, adolescent cohort (N = 134 individuals ages 10-31 years, N = 202 total sessions) that completed MRI scans at ultra-high field (7 Tesla). We used resting state fMRI data to compute surface-based regional homogeneity (ReHo)-a measure of time-dependent correlations in fMRI activity between a vertex and its immediate neighbors-as an index of local functional connectivity across the cortex. We found widespread decreases in ReHo, suggesting increasing heterogeneity and specialization of functional circuits through adolescence. Decreases in ReHo included a spatial component which overlapped with sensorimotor and cingulo-opercular networks, in which ReHo decreases were associated with developmental stabilization of working memory performance. We show that decreases in ReHo are associated with higher intrinsic coding dimensionality, demonstrating how functional specialization of these circuits may confer computational benefits by facilitating increased capacity for encoding information. These results suggest a remodeling of cortical activity in adolescence through which local functional circuits become increasingly specialized, higher-dimensional, and more capable of supporting adult-like cognitive functioning.

PMID:40086409 | DOI:10.1016/j.dcn.2025.101541

Imaging Neurosci (Camb). 2024 May 10;2:1-20. doi: 10.1162/imag_a_00165. eCollection 2024 May 1.

ABSTRACT

The precise network topology of functional brain systems is highly specific to individuals and undergoes dramatic changes during critical periods of development. Large amounts of high-quality resting state data are required to investigate these individual differences, but are difficult to obtain in early infancy. Using the template matching method, we generated a set of infant network templates to use as priors for individualized functional resting-state network mapping in two independent neonatal datasets with extended acquisition of resting-state functional MRI (fMRI) data. We show that template matching detects all major adult resting-state networks in individual infants and that the topology of these resting-state network maps is individual-specific. Interestingly, there was no plateau in within-subject network map similarity with up to 25 minutes of resting-state data, suggesting that the amount and/or quality of infant data required to achieve stable or high-precision network maps is higher than adults. These findings are a critical step towards personalized precision functional brain mapping in infants, which opens new avenues for clinical applicability of resting-state fMRI and potential for robust prediction of how early functional connectivity patterns relate to subsequent behavioral phenotypes and health outcomes.

PMID:40083644 | PMC:PMC11899874 | DOI:10.1162/imag_a_00165