Most recent paper

Front Neurosci. 2025 Mar 14;19:1549172. doi: 10.3389/fnins.2025.1549172. eCollection 2025.

ABSTRACT

This study aimed to directly compare electroencephalography (EEG) whole-brain patterns of neural dynamics with concurrently measured fMRI BOLD data. To achieve this, we aim to derive EEG patterns based on a spatio-spectral decomposition of band-limited EEG power in the source-reconstructed space. In a large dataset of 72 subjects undergoing resting-state hdEEG-fMRI, we demonstrated that the proposed approach is reliable in terms of both the extracted patterns as well as their spatial BOLD signatures. The five most robust EEG spatio-spectral patterns not only include the well-known occipital alpha power dynamics, ensuring consistency with established findings, but also reveal additional patterns, uncovering new insights into brain activity. We report and interpret the most reproducible source-space EEG-fMRI patterns, along with the corresponding EEG electrode-space patterns, which are better known from the literature. The EEG spatio-spectral patterns show weak, yet statistically significant spatial similarity to their functional magnetic resonance imaging (fMRI) blood oxygenation level-dependent (BOLD) signatures, particularly in the patterns that exhibit stronger temporal synchronization with BOLD. However, we did not observe a statistically significant relationship between the EEG spatio-spectral patterns and the classical fMRI BOLD resting-state networks (as identified through independent component analysis), tested as the similarity between their temporal synchronization and spatial overlap. This provides evidence that both EEG (frequency-specific) power and the BOLD signal capture reproducible spatio-temporal patterns of neural dynamics. Instead of being mutually redundant, these only partially overlap, providing largely complementary information regarding the underlying low-frequency dynamics.

PMID:40161575 | PMC:PMC11949981 | DOI:10.3389/fnins.2025.1549172

Front Neural Circuits. 2025 Mar 14;19:1500227. doi: 10.3389/fncir.2025.1500227. eCollection 2025.

ABSTRACT

The spatiotemporal dynamics of resting-state brain activity can be characterized by switching between multiple brain states, and numerous techniques have been developed to extract such dynamic features from resting-state functional magnetic resonance imaging (fMRI) data. However, many of these techniques are based on momentary temporal correlation and co-activation patterns and merely reflect linear features of the data, suggesting that the dynamic features, such as state-switching, extracted by these techniques may be misinterpreted. To examine whether such misinterpretations occur when using techniques that are not based on momentary temporal correlation or co-activation patterns, we addressed Energy Landscape Analysis (ELA) based on pairwise-maximum entropy model (PMEM), a statistical physics-inspired method that was designed to extract multiple brain states and dynamics of resting-state fMRI data. We found that the shape of the energy landscape and the first-order transition probability derived from ELA were similar between real data and surrogate data suggesting that these features were largely accounted for by stationary and linear properties of the real data without requiring state-switching among locally stable states. To confirm that surrogate data were distinct from the real data, we replicated a previous finding that some topological properties of resting-state fMRI data differed between the real and surrogate data. Overall, we found that linear models largely reproduced the first order ELA-derived features (i.e., energy landscape and transition probability) with some notable differences.

PMID:40160867 | PMC:PMC11949950 | DOI:10.3389/fncir.2025.1500227

Quant Imaging Med Surg. 2025 Mar 3;15(3):1834-1844. doi: 10.21037/qims-24-1684. Epub 2025 Feb 26.

ABSTRACT

BACKGROUND: Alopecia areata (AA) is a nonscarring chronic inflammatory hair loss disease with a complex etiology. Psychological stress and dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis have been strongly linked to the etiology of AA, but the associated changes in intrinsic brain activity remain unknown. We hypothesized that patients with AA exhibit altered hypothalamic activity that is linked to psychological stress. This study aimed to characterize the altered hypothalamic activity in patients with AA and its relationship to psychological stress.

METHODS: A total of 102 patients with AA and 84 age- and sex-matched healthy controls (HCs) were recruited. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) to assess brain activity and completed neuropsychological evaluations, including the Hamilton Anxiety Rating Scale (HAM-A) score and the Hamilton Depression Rating Scale (HAM-D). Additionally, patients with AA were assessed using the Dermatology Life Quality Index (DLQI), and blood samples were obtained to measure total serum immunoglobulin E (IgE) levels. We chose the hypothalamus as the region of interest (ROI) to compare alterations in hypothalamic of amplitude of low-frequency fluctuation (ALFF) and whole-brain functional connectivity (FC) between patients with AA and HCs. Analyses of the correlation of brain activity and clinical data were conducted, including neuropsychological tests, DLQI, and blood samples.

RESULTS: The HAM-A score, the HAM-D score, and the altered ALFF in the hypothalamus showed a statistically significant difference between patients with AA and HCs (P<0.05). Patients with AA exhibited increased FC between the hypothalamus, the left postcentral gyrus, and right inferior temporal gyrus (Gaussian random field-corrected: voxel <0.001 and cluster <0.05). Moreover, increased FC between the hypothalamus and left postcentral gyrus was positively correlated with HAM-D score (r=0.296; P=0.020), while increased FC between the hypothalamus and the right inferior temporal gyrus was negatively correlated with both DLQI (r=-0.256; P=0.012) and total serum IgE (r=-0.203; P=0.048).

CONCLUSIONS: Patients with AA exhibited altered hypothalamus activity and connectivity. These alterations may underlie the neurophysiological basis of psychological stress experienced by patients with AA.

PMID:40160661 | PMC:PMC11948389 | DOI:10.21037/qims-24-1684

Quant Imaging Med Surg. 2025 Mar 3;15(3):2362-2375. doi: 10.21037/qims-24-2062. Epub 2025 Feb 26.

ABSTRACT

BACKGROUND: Nonarteritic anterior ischemic optic neuropathy (NAION) is often accompanied by degeneration of optic nerve axons and ganglion cell apoptosis, but the mechanism of its effects on the cerebral cortex and visual centers is not clear. Graph theory analysis, as a quantitative tool for complex networks, has made it possible to characterize the topological alterations of brain networks in patients with NAION. The objective of this pilot study was to investigate the topological characteristics of functional brain networks in patients with NAION and to analyze their potential correlation with visual dysfunction.

METHODS: This prospective, cross-sectional study recruited 25 patients with NAION and 24 matched healthy controls (HCs) from Dongfang Hospital, Beijing University of Chinese Medicine. Following resting-state functional magnetic resonance imaging (rs-fMRI) scans, large-scale functional connectivity matrices of 90 regions were constructed. Graph theory was then used to compare global and local network parameters. Subsequently, network-based statistics (NBS) analysis was employed to detect differences in functional connectivity across the brain. Finally, correlations were assessed between the network topological properties and clinical variables.

RESULTS: Individuals with NAION, as compared to controls, exhibited significant decreases in normalized clustering coefficient (gamma; P=0.021), small-worldness (sigma; P=0.043), and local efficiency (Eloc; P=0.030), as well as a significant increase in the size of the largest connected component (LCC; P=0.039) of the network. Additionally, the LCC showed a negative association with gamma, sigma and global efficiency (Eg) but a positive correlation with the normalized characteristic path length (lambda) of the two groups (all P values <0.05). Regionally, patients exhibited changes in nodal centralities, particularly affecting the attention, visual, and salience networks. NBS analysis identified an interconnected subnetwork consisting of 49 nodes and 77 edges (P<0.001, NBS-corrected) that showed significantly higher connectivity in patients with NAION. The mean connectivity of this subnetwork was negatively correlated with the global topological parameters gamma, sigma, and Eg in the NAION group and gamma and sigma in the HCs but positively correlated with the LCC in both groups (all P values <0.05). Moreover, the nodal betweenness centrality of the left dorsolateral superior frontal gyrus exhibited a significant positive correlation with the visual field (VF) mean deviation (MD) in the NAION group (P<0.001).

CONCLUSIONS: This study initially identified aberrant topological and connectivity changes in the functional brain networks associated with visual impairment in patients with NAION, thus expanding our existing understanding of the neurobiological mechanisms of NAION.

PMID:40160619 | PMC:PMC11948378 | DOI:10.21037/qims-24-2062

Mach Learn Clin Neuroimaging (2024). 2025;15266:145-154. doi: 10.1007/978-3-031-78761-4_14. Epub 2024 Dec 6.

ABSTRACT

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that encompasses a wide variety of symptoms and degrees of impairment, which makes the diagnosis and treatment challenging. Functional magnetic resonance imaging (fMRI) has been extensively used to study brain activity in ASD, and machine learning methods have been applied to analyze resting state fMRI (rs-fMRI) data. However, fewer studies have explored the recent transformer-based models on rs-fMRI data. Given the superiority of transformer models in capturing long-range dependencies in sequence data, we have developed a transformer-based self-supervised framework that directly analyzes time-series fMRI data without computing functional connectivity. To address over-fitting in small datasets and enhance the model performance, we propose self-supervised pre-training tasks to reconstruct the randomly masked fMRI time-series data, investigating the effects of various masking strategies. We then fine-tune the model for the ASD classification task and evaluate it using two public datasets and five-fold cross-validation with different amounts of training data. The experiments show that randomly masking entire ROIs gives better model performance than randomly masking time points in the pre-training step, resulting in an average improvement of 10.8% for AUC and 9.3% for subject accuracy compared with the transformer model trained from scratch across different levels of training data availability. Our code is available on GitHub .

PMID:40160559 | PMC:PMC11951341 | DOI:10.1007/978-3-031-78761-4_14

Soc Cogn Affect Neurosci. 2025 Mar 31:nsaf025. doi: 10.1093/scan/nsaf025. Online ahead of print.

ABSTRACT

Previous work suggests blood pressure (BP) relates to social algesia, where those with higher BP are more tolerant of social pain. The neural correlates of this association, however, are unknown. Based on findings suggesting neural regions involved in physical pain are activated during social pain, the current study explores whether BP relates to subjective and neural responses to social pain, apart from emotional responding. BP was measured, after which participants completed emotional processing and social exclusion fMRI paradigms. Results replicated previous findings, with higher systolic BP related to lower trait sensitivity to social pain. However, there were no associations between BP and reported social pain sensitivity during social exclusion. Moreover, after accounting for adiposity, we found no association between BP and anterior insula (AI) or dorsal anterior cingulate cortex (dACC) activity to exclusion. Finally, there were no reliable associations between BP and reported valence or arousal, or AI and dACC activity to emotional images. Findings partly replicate and extend prior findings on BP and emotional responding to social pain; however, they appear inconsistent with predictions at the neural level. Future experimental manipulation of BP may allow for causal inferences and adjudication of conceptual perspectives on cardiovascular contributions to social algesia.

PMID:40160022 | DOI:10.1093/scan/nsaf025

Sci Rep. 2025 Mar 29;15(1):10888. doi: 10.1038/s41598-025-95190-9.

ABSTRACT

Network modeling are widely using in resting-state functional magnetic resonance imaging (rs-fMRI) for Alzheimer's disease (AD) research. Typically, Pearson correlation coefficient (PCC) was widely applied to construct brain connectivity network from BOLD signals of regions of interest. However, it often results in significant intra-group variability and complicates the identification of disease-specific functional connectivity patterns. To address this issue, we propose a novel brain network construction strategy, called SNBG, which uses aggregated information from the control group to derive a single-sample network. We compare SNBG and the PCC based method on a dataset from an Alzheimer's Disease Neuroimaging Initiative (ADNI) study. SNBG method captures more stable connections between regions of interest (ROIs) and increases classification accuracy from 89.24% of PCC based method to 97.13%. In addition, in AD-related local networks, such as default mode network (DMN), medial frontal network (MFN) and frontoparietal network (FPN), SNBG demonstrates lower intra-group heterogeneity than the PCC based method.

PMID:40157941 | DOI:10.1038/s41598-025-95190-9

Neuroimage. 2025 Mar 27:121177. doi: 10.1016/j.neuroimage.2025.121177. Online ahead of print.

ABSTRACT

Naturalistic stimuli have become an effective tool to uncover the dynamic functional brain networks triggered by cognitive and emotional real-life experiences through multimodal and dynamic stimuli. However, current research predominantly focused on exploring dynamic functional connectivity generated via chosen templates under resting-state paradigm, with relatively limited investigation into the dynamic functional interactions among large-scale brain networks. Moreover, these studies might overlook the longer time-scale adaptability and information transmission that occur over extended periods during naturalistic stimuli. In this study, we introduced an unsupervised deep recursive autoencoder (DRAE) model combined with a sliding window approach, effectively capturing the brain's long-term temporal dependencies, as measured in functional magnetic resonance imaging (fMRI), when subjects viewing a long-duration and emotional film. The experimental results revealed that naturalistic stimuli can induce dynamic large-scale brain networks, of which functional interactions covary with the development of the film's narrative. Furthermore, the dynamic interactions among brain networks were temporally synchronized with specific features of the movie, especially with the emotional arousal and valence. Our study provided novel insight to the underlying neural mechanisms of dynamic functional interactions among brain regions in an ecologically valid sensory experience.

PMID:40157466 | DOI:10.1016/j.neuroimage.2025.121177

Psychiatry Res Neuroimaging. 2025 Mar 25;349:111986. doi: 10.1016/j.pscychresns.2025.111986. Online ahead of print.

ABSTRACT

Numerous studies have revealed that patients with major depressive disorder (MDD) suffer from insomnia symptoms. However, the dysfunction pattern in specific insomnia symptoms in patients with MDD remains unclear. The present study aimed to examine the regional brain neuroimaging activity features of difficulty falling asleep (DFA) and early awakening (EA) in patients with MDD. The resting-fMRI by applying the amplitude of low-frequency fluctuation (ALFF) method was estimated in 50 MDD patients with DFA, 36 patients with EA, 46 patients without insomnia symptoms, and 60 matched healthy controls. The Pearson correlation analysis was used among the ALFF with significant difference brain regions, the 17-item Hamilton Depression Rating Scale factor scores, and the Pittsburgh Sleep Quality Index scores. Patients with DFA showed lower ALFF values in the left precentral gyrus than those with EA and higher ALFF values in the left insula than those without insomnia symptoms. Patients with EA showed higher ALFF values in the left precentral gyrus than those without insomnia symptoms. This study revealed distinct neural mechanisms underlying specific insomnia symptoms, identifying the left insula as a potential pathological region in DFA patients and the left precentral gyrus as a characteristic neuropathological region in EA patients.

PMID:40156942 | DOI:10.1016/j.pscychresns.2025.111986

Sleep. 2025 Mar 29:zsaf088. doi: 10.1093/sleep/zsaf088. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Adolescents often do not sleep as much as recommended by most national guidelines, which may impact their brain development. The current study aims to evaluate the relationship between objective assessment of sleep duration measured with actigraphy, and brain network connectivity on functional magnetic resonance imaging (fMRI).

METHODS: We used data from the two-year follow-up of the Adolescent Brain Cognitive Development (ABCD) study comprising 3,799 adolescents, ages 10 to 13 years old, to assess the relationship between sleep duration, measured by two weeks of Fitbit-derived actigraphy, and brain network connectivity derived from resting-state fMRI, using linear regression models. Linear regression analysis was also used to investigate the interaction between participant sex and sleep duration on brain network connectivity.

RESULTS: We identified both positive and negative correlations between mean sleep duration and 6 within brain network and 30 between-network pairs. These included networks involved in attention (Dorsal and Ventral Attention networks), executive control (Cingulo-Opercular and Default Mode networks), memory (Retrosplenial Temporal network), and sensory function (Auditory and Sensorimotor networks). We also identified sex-specific effects in three network pairs (Auditory - Retrosplenial Temporal, Retrosplenial Temporal - Sensorimotor, and Visual - Visual) and sex differences in functional connectivity across 23 distinct within- and between-network connections.

CONCLUSIONS: Sleep duration is associated with the functional network connectivity in attentional, executive control, memory, and sensory networks during early adolescence. The identification of sex-specific effects in select network pairs underscores the importance of sex as a biological variable in studies of adolescent sleep and brain development.

PMID:40156904 | DOI:10.1093/sleep/zsaf088

J Headache Pain. 2025 Mar 28;26(1):60. doi: 10.1186/s10194-025-02004-4.

ABSTRACT

BACKGROUND: Sleep deprivation can trigger acute headache attacks in individuals with migraine; however, the underlying mechanism remains poorly understood. The aim of this study was to investigate the effects of acute sleep deprivation (ASD) on brain function in individuals with migraine without aura (MWoA) via functional magnetic resonance imaging (fMRI).

METHODS: Twenty three MWoA individuals and 23 healthy controls (HCs) were fairly included in this study. All participants underwent two MRI scans: one at baseline (prior to sleep deprivation) and another following 24 h of ASD. Images were obtained with blood-oxygen-level-dependent and T1-weighted sequences on a Siemens 7.0 T MRI scanner. We conducted analyses of changes in the low-frequency fluctuations (ALFF) values and functional connectivity (FC) between brain networks and within network before and after ASD in both MWoA group and HC group. Additionally, we investigated the relationship between the changes in ALFF before and after ASD and the clinical features (VAS and monthly headache days).

RESULTS: In the HC group, ASD led to a significant increase in ALFF values in the left parahippocampal gyrus compared to baseline (p-FDR = 0.01). In the MWoA group, ALFF values were significantly greater in 64 brain regions after ASD than at baseline. The most significant change in ALFF before and after ASD in the MWoA group was detected in the right medial pulvinar of the thalamus (p-FDR = 0.017), which showed a significant negative correlation with monthly headache days. Moreover, seed-based connectivity (SBC) analysis using the right medial pulvinar of the thalamus as the seed point revealed significantly increased connectivity with the cerebellar vermis (p-FWE = 0.035) after ASD in individuals with MWoA, whereas connectivity with the right postcentral gyrus was significantly decreased (p-FWE = 0.048). Furthermore, we performed analyses of between-network connectivity (BNC) and within-network connectivity across 17 brain networks, utilizing the Yeo-17 atlas. Both MWoA individuals and HCs showed no significant changes in BNC after ASD compared to baseline. However, our analysis in within-network revealed that MWoA individuals exhibited a reduced within-network FC in dorsal attention network (DAN) after ASD compared to baseline (p-FDR = 0.031), whereas HCs showed no significant differences in within-network FC across all networks before and after ASD.

CONCLUSIONS: In comparison to HCs, MWoA individuals exhibited significant alterations in brain function after ASD, particularly within the thalamus, and MWoA individuals exhibited a reduced within-network FC in DAN after ASD compared to baseline. Brain regions and networks in MWoA individuals were more susceptible to the effects of ASD.

PMID:40155843 | DOI:10.1186/s10194-025-02004-4

J Neurosurg. 2025 Mar 28:1-9. doi: 10.3171/2024.11.JNS241935. Online ahead of print.

ABSTRACT

OBJECTIVE: Increasing evidence suggests that primary trigeminal neuralgia (TN), including classical TN (CTN) and idiopathic TN (ITN), share biological, neuropsychological, and clinical features, despite differing diagnostic criteria. Neuroimaging studies have shown neurovascular compression (NVC) differences in these disorders. However, changes in brain dynamics across these two TN subtypes remain unknown.

METHODS: The authors aimed to examine the functional connectivity differences in CTN, ITN, and pain-free controls. A total of 93 subjects, 50 TN patients and 43 pain-free controls, underwent resting-state functional magnetic resonance imaging (rs-fMRI). All TN patients underwent surgery, and the NVC type was verified. Functional connectivity and spontaneous brain activity were analyzed, and the significant alterations in rs-fMRI indices were selected to train classification models.

RESULTS: The patients with TN showed increased connectivity between several brain regions, such as the medial prefrontal cortex (mPFC) and left planum temporale and decreased connectivity between the mPFC and left superior frontal gyrus. CTN patients exhibited a further reduction in connectivity between the left insular lobe and left occipital pole. Compared to controls, TN patients had heightened neural activity in the frontal regions. The CTN patients showed reduced activity in the right temporal pole compared to that in the ITN patients. These patterns effectively distinguished TN patients from controls, with an accuracy of 74.19% and an area under the receiver operating characteristic curve of 0.80.

CONCLUSIONS: This study revealed alterations in rs-fMRI metrics in TN patients compared to those in controls and is the first to show differences between CTN and ITN. The support vector machine model of rs-fMRI indices exhibited moderate performance on discriminating TN patients from controls. These findings have unveiled potential biomarkers for TN and its subtypes, which can be used for additional investigation of the pathophysiology of the disease.

PMID:40153851 | DOI:10.3171/2024.11.JNS241935

Neuroscience. 2025 Mar 26:S0306-4522(25)00261-1. doi: 10.1016/j.neuroscience.2025.03.059. Online ahead of print.

ABSTRACT

Schizophrenia has been identified to exhibit significant abnormalities in brain functional networks, which are likely to underpin the cognitive and functional impairments observed in patients. Graph theoretical analysis revealed the disrupted modularity in schizophrenia, however, the dynamic network abnormalities in schizophrenia remains unclear. We collected the resting-state functional magnetic resonance imaging data from 82 first-episode schizophrenia (FES) patients and 55 healthy control (HC) subjects. Dynamic functional connectivity matrices were constructed and a multilayer network model was employed to run the dynamic modularity analysis. We also performed correlation analyses to investigate the relationship between flexibility, cognitive function and clinical symptoms. Our findings indicate that FES patients exhibit higher multilayer modularity. The node flexibility of FES patients were found elevated in several brain regions, which were included in the default mode network, fronto-parietal network, salience network and visual network. The node flexibility metrics in aberrant brain regions were found to demonstrate significant correlations with cognitive function and negative symptoms in patients with FES. These findings suggest a pathological imbalance in brain network dynamics, where abnormal modular organization might contribute to the cognitive impairment and functional deficits in schizophrenia.

PMID:40154938 | DOI:10.1016/j.neuroscience.2025.03.059

J Tradit Chin Med. 2025 Apr;45(2):450-457. doi: 10.19852/j.cnki.jtcm.2025.02.011.

ABSTRACT

OBJECTIVE: To examine the variations in brain regions among individuals with decreasing ovarian reserve (DOR) compared to healthy controls using resting-state functional magnetic resonance imaging (rs-fMRI), and to assess the immediate effects of acupuncture stimulation on these brain regions in DOR patients.

METHODS: Twenty patients diagnosed with DOR (DOR group) and twenty healthy controls (HC group) who underwent rs-fMRI scans were included. The DOR group received acupuncture and underwent a subsequent rs-fMRI scan. Amplitude of low-frequency fluctuations (ALFF) analysis was utilized to identify disparities in brain regions between DOR and HC groups, and to evaluate the immediate effects of acupuncture on DOR patients' brain regions. Common brain regions were identified as seed points for functional connectivity (FC) analysis.

RESULTS: In this study, a total of 20 HCs and 20 patients with DOR were initially enrolled. However, due to incomplete personal information, three participants were removed from the HC group. Additionally, two DOR patients experienced symptoms such as physical discomfort and shortness of breath during the MRI scan, leading to their exclusion due to excessive head movement parameters. Consequently, 17 HCs and 16 DOR patients completed the entire study protocol. Comparative analysis revealed that DOR patients exhibited increased ALFF values in the left inferior temporal gyrus (ITG) and middle temporal gyrus (MTG), while ALFF values in the bilateral superior frontal gyrus (SFG), middle frontal gyrus (MFG), and left inferior frontal gyrus (IFG) were decreased compared to HCs. Following acupuncture intervention, ALFF values in the left SFG, MFG, and supplementary motor area (SMA) of DOR patients increased. Furthermore, functional connectivity (FC) analysis demonstrated increased connectivity of the left SFG with the bilateral calcarine sulcus and lingual gyrus post-acupuncture.

CONCLUSION: This study highlights abnormal neural activity in the SFG, MFG, IFG, and ACC in DOR patients compared to HCs. Acupuncture was found to regulate the activity of the SFG, bringing it closer to normal levels, and enhancing its functional connectivity with the bilateral calcarine sulcus and lingual gyrus.

PMID:40151132 | DOI:10.19852/j.cnki.jtcm.2025.02.011

Brain Sci. 2025 Mar 18;15(3):317. doi: 10.3390/brainsci15030317.

ABSTRACT

Background: Modulating spontaneous neuronal activity is critical for understanding and potentially treating neurological disorders, yet the comparative effects of different non-invasive brain stimulation techniques remain underexplored. Objective: This study aimed to systematically compare the effects of temporal interference (TI) stimulation and high-definition transcranial direct current stimulation (HD-tDCS) on spontaneous neuronal activity in the primary motor cortex. Methods: In a randomized, crossover design, forty right-handed participants underwent two 20 min sessions of either TI or HD-tDCS. Resting-state fMRI data were collected at four stages: pre-stimulus baseline (S1), first half of stimulation (S2), second half of stimulation (S3), and post-stimulation (S4). We analyzed changes in regional homogeneity (ReHo), dynamic ReHo (dReHo), fractional amplitude of low-frequency fluctuations (fALFFs), and dynamic fALFFs (dfALFFs) to assess the impact on spontaneous neuronal activity. Results: The analysis revealed that TI had a more significant impact on ReHo, especially in the left superior temporal gyrus and postcentral gyrus, compared with HD-tDCS. Both stimulation methods exhibited their strongest effects during the second half of the stimulation period, but only TI maintained significant activity in the post-stimulation phase. Additionally, both TI and HD-tDCS enhanced fALFFs in real-time, with TI showing more pronounced effects in sensorimotor regions. Conclusions: These findings suggest that TI exerts a more potent and sustained influence on spontaneous neuronal activity than HD-tDCS. This enhanced understanding of their differential effects provides valuable insights for optimizing non-invasive brain stimulation protocols for therapeutic applications.

PMID:40149838 | DOI:10.3390/brainsci15030317

Brain Sci. 2025 Mar 16;15(3):313. doi: 10.3390/brainsci15030313.

ABSTRACT

BACKGROUND/OBJECTIVES: Schizophrenia is a severe psychiatric disorder characterized by deficits in perception and advanced cognitive functions. Prior studies have reported abnormal lateralization in cortical morphology and functional connectivity in schizophrenia. However, it remains unclear whether schizophrenia affects hemispheric asymmetry in the hierarchical organization of functional connectome.

METHODS: Here, we apply a gradient mapping framework to the hemispheric functional connectome to estimate the first three gradients, which characterize unimodal-to-transmodal, visual-to-somatomotor, and somatomotor/default mode-to-multiple demand hierarchy axes. We then assess between-group differences in intra- and inter-hemispheric asymmetries of these three functional gradients.

RESULTS: We find that, compared to healthy controls, patients with schizophrenia exhibit significantly altered hemispheric asymmetry in functional gradient across multiple networks, including the dorsal attention, ventral attention, visual, and control networks. Region-level analyses further reveal that patients with schizophrenia show significantly abnormal hemispheric gradient asymmetries in several cortical regions in the dorsal prefrontal gyrus, medial superior frontal gyrus, and somatomotor areas. Lastly, we find that hemispheric asymmetries in functional gradients can differentiate between patients and healthy controls and predict the severity of positive symptoms in schizophrenia.

CONCLUSIONS: Collectively, these findings suggest that schizophrenia is associated with altered hemispheric asymmetry in functional hierarchy, providing novel perspectives for understanding the atypical brain lateralization in schizophrenia.

PMID:40149834 | DOI:10.3390/brainsci15030313

Brain Sci. 2025 Mar 7;15(3):285. doi: 10.3390/brainsci15030285.

ABSTRACT

BACKGROUND/OBJECTIVES: Advancements in biomedical imaging technologies over the past few decades have made it increasingly possible to measure the long-term effects of exercise on the central nervous system. This study aims to compare the brain morphology and functional connectivity of wrestlers and handball players, exploring sport-specific neural adaptations.

METHODS: Here, we examined 26 elite male athletes (13 wrestlers and 13 handball players) using anatomical and resting-state functional magnetic resonance imaging (fMRI) measurements. Connectivity maps are derived using the seed-based correlation analysis of resting-state fMRI, while voxel-based morphometry (VBM) is employed to identify anatomical differences. Additionally, the cortical thickness and global volumetric values of the segmented images are examined to determine the distinctions between elite wrestlers and handball players using non-parametric statistical tests.

RESULTS: Wrestlers exhibited greater grey matter volume (GMV) in the right middle temporal gyrus, left middle frontal gyrus, and right posterior cingulate gyrus (uncorr., p < 0.001). On the other hand, wrestlers showed increased functional connectivity in the left superior temporal gyrus, left parahippocampal gyrus, the left anterior orbital gyrus, and right superior frontal gyrus-medial frontal region (P(FWE) < 0.05). In addition, wrestlers showed greater cortical thickness in several brain regions.

CONCLUSIONS: The increased GMV, cortical thickness, and functional connectivity observed in wrestlers highlight the presence of sport-specific neural adaptations. While this research provides valuable insights into the neuroplastic effects of various athletic disciplines, further studies involving additional sports and control groups are needed for a more comprehensive understanding.

PMID:40149806 | DOI:10.3390/brainsci15030285

Brain Sci. 2025 Feb 28;15(3):264. doi: 10.3390/brainsci15030264.

ABSTRACT

BACKGROUND/OBJECTIVES: Research on pleasant tactile perception has primarily focused on C-tactile fibers found in hairy skin, with the forearm and face as common study sites. Recent findings of these fibers in hairless skin, such as the palms, have sparked interest in tactile stimulation on the hands. While studies have examined comfort and brain activity in passive touch, active touch remains underexplored. This study aimed to investigate differences in pleasant sensation and brain activity during active touch with stress balls of varying hardness.

METHODS: Forty healthy women participated. Using functional magnetic resonance imaging (fMRI), brain activity was measured as participants alternated between gripping stress balls of soft, medium, and hard hardness and resting without a ball. Participants rated hardness and comfort on a 9-point scale.

RESULTS: Soft stress balls were perceived as soft and comfortable, activating the thalamus and left insular cortex while reducing activity in the right insular cortex. Medium stress balls elicited similar perceptions and thalamic activation but with reduced right insular cortex activity. Hard stress balls caused discomfort, activating the insular cortex, thalamus, and amygdala while reducing anterior cingulate cortex activity.

CONCLUSIONS: Soft stress balls may reduce aversive stimuli through perceived comfort, while hard stress balls may induce discomfort and are unlikely to alleviate stress.

PMID:40149784 | DOI:10.3390/brainsci15030264

Brain Sci. 2025 Feb 28;15(3):263. doi: 10.3390/brainsci15030263.

ABSTRACT

Background/Objectives: Cocaine use disorder (CUD) poses a worldwide health challenge, with severe consequences for brain function. However, the phase dynamics underlying CUD and the transitions between CUD and health remain poorly understood. Methods: Here, we used resting-state functional magnetic resonance imaging (fMRI) data from 43 CUD patients and 45 healthy controls (HCT). We performed empirical analysis to identify phase-coherence states and compared their probabilities of occurrence between conditions. To further explore the underlying mechanism, we employed computational modeling to replicate the observed state probabilities for each condition. These generated whole-brain models enabled us to simulate external perturbations and identify optimal brain regions mediating transitions between HCT and CUD. Results: We found that CUD was associated with a reduced occurrence probability of the state dominated by the default mode network (DMN). Perturbing the nucleus accumbens, thalamus, and specific regions within the default mode, limbic and frontoparietal networks drives transitions from HCT to CUD, while perturbing the hippocampus and specific regions within the visual, dorsal attention, and DMN facilitates a return from CUD to HCT. Conclusions: This study revealed altered DMN-related dynamics in CUD from the phase perspective and provides potential regions critical for state transitions. The results contribute to understanding the pathogenesis of CUD and the development of therapeutic stimulation strategies.

PMID:40149783 | DOI:10.3390/brainsci15030263

Brain Imaging Behav. 2025 Mar 28. doi: 10.1007/s11682-025-00977-z. Online ahead of print.

ABSTRACT

This study aims to unravel the consistent abnormalities in functional connectivity (FC) with the primary motor cortex (M1) for post-stroke motor dysfunctions and the dynamic shifts of FC across distinct phases (acute/subacute/chronic) following stroke onset. Eleven studies with 269 stroke patients and 257 healthy controls (HCs) were included after screening articles in PubMed, Web of Science, and Embase. Voxel-wise meta-analysis and subgroup analysis on three phases after stroke onset were applied using the anisotropic effect size-signed differential mapping toolbox. Additionally, a M1-seeded FC analysis from an independent dataset with 29 stroke patients and 40 HCs was applied to validate the results of the meta-analyses. The abnormal connectivity with M1 in patients with post-stroke motor dysfunctions extended beyond motor-related regions to non-motor domains. A consistent interhemispheric connectivity reduction between M1 and motor-related regions emerged as a hallmark, persisting across different phases after stroke onset. These alterations were largely replicable through validation analysis. Our findings indicated the imbalance of connectivity in patients with post-stroke motor dysfunctions.

PMID:40148720 | DOI:10.1007/s11682-025-00977-z