Brain Sciences

24 pages, 4573 KB

Open AccessArticle

How Personality Traits Affect the Perception of Facial and Vocal Attractiveness

by Lingyun Xiang, Werner Sommer, Siqi Yue, Jingyu Liao, Meng Liu and Weijun Li

Brain Sci. 2025, 15(11), 1143; https://doi.org/10.3390/brainsci15111143 (registering DOI) - 25 Oct 2025

Background: Previous research has found an association between attractiveness and personality traits, but the neural mechanisms are largely unknown. Method: We used a Stroop-like paradigm combined with EEG recordings to investigate how personality traits affect the perception of facial and vocal attractiveness. Twenty-three [...] Read more.

Background: Previous research has found an association between attractiveness and personality traits, but the neural mechanisms are largely unknown. Method: We used a Stroop-like paradigm combined with EEG recordings to investigate how personality traits affect the perception of facial and vocal attractiveness. Twenty-three female participants classified the attractiveness of male faces and male voices paired with positive or negative personality trait words. Results: The behavioral results indicate that personality trait words that are semantically congruent with attractiveness levels facilitate the perception of attractiveness, whereas incongruent trait information produces the opposite effect. Event-related potentials revealed that the influence of personality trait words on facial attractiveness was primarily related to motivated attention as indicated by the late positive component. In the voice task, personality trait words impacted vocal attractiveness processing first during semantic integration (N400 component) and then modulated motivated attention. Conclusions: These results suggest that alleged personality traits modify attractiveness processing in faces and voices in relatively late and partially modality-specific stages. Full article

(This article belongs to the Section Sensory and Motor Neuroscience)

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17 pages, 1328 KB

Open AccessArticle

Relationships Between Sleep Quality, Anxiety and Depression in University Students: Stable Trends over Time and a Pronounced Concern for Sleep Initiation

by Jonathan P. Whitehead and Caroline L. Horton

Brain Sci. 2025, 15(11), 1142; https://doi.org/10.3390/brainsci15111142 (registering DOI) - 24 Oct 2025

Abstract

Background/Objectives: Relationships between sleep quality, anxiety and depression are well-documented across the lifespan. Here we investigated relationships between sleep, mental health and markers of obesity and cardiovascular health in Higher Education students (young adults, 18–28 years) using repeated cross-sectional sampling. Methods: [...] Read more.

Background/Objectives: Relationships between sleep quality, anxiety and depression are well-documented across the lifespan. Here we investigated relationships between sleep, mental health and markers of obesity and cardiovascular health in Higher Education students (young adults, 18–28 years) using repeated cross-sectional sampling. Methods: Students (n = 486) participated at one of four timepoints across 2020–2023. The PSQI (sleep quality), GAD7 (anxiety) and PHQ8 (depression) were completed online. Measurements of obesity (Body Mass Index (BMI), body fat percent (BF%) and waist–hip ratio (WHR)) and cardiovascular function (heart rate (HR), diastolic and systolic blood pressure (DP and SP)) were determined. Changes over time, differences between sexes, and correlations between parameters were examined. Results: All measures were stable over the 4-year period. GAD7 (p < 0.0001) and PHQ8 (p = 0.0014) scores were significantly higher in females than males. There were significant, moderate to strong correlations between PSQI, GAD7 and PHQ8 scores for both sexes (r = 0.34–0.71). Only 18.1% of females and 23% of males reported both good quality sleep and no or low levels of anxiety and depression. Significant sex-specific differences were observed across markers of obesity and cardiovascular function (for BF%, WHR, HR and SP—all p ≤ 0.01), which showed weak to moderate correlations with sleep and mental health. Impaired sleep latency (C2) was identified as a potential key contributing factor. Conclusions: These observations provide evidence of multiple established, interlinked chronic challenges affecting sleep, mental and physical health in students. Identification of a key role for impaired sleep latency provides a foundation for targeted intervention, focusing upon improving sleep initiation, to improve mental health outcomes. Full article

(This article belongs to the Special Issue Relationships Between Disordered Sleep and Mental Health)

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15 pages, 641 KB

Open AccessArticle

Menstrual Cycle Modulation of Verbal Performance and Hemispheric Asymmetry

by Ivana Hromatko and Meri Tadinac

Brain Sci. 2025, 15(11), 1141; https://doi.org/10.3390/brainsci15111141 (registering DOI) - 24 Oct 2025

Abstract

Background/Objectives: It has been postulated that sex differences in certain types of verbal abilities arise from sex-dimorphic patterns of hemispheric activation, and that these patterns might be modulated by circulating levels of sex hormones. The aim of this study was to explore [...] Read more.

Background/Objectives: It has been postulated that sex differences in certain types of verbal abilities arise from sex-dimorphic patterns of hemispheric activation, and that these patterns might be modulated by circulating levels of sex hormones. The aim of this study was to explore the activational effects of sex hormones (throughout the menstrual cycle) on both verbal performance and functional hemispheric asymmetries (qEEG laterality) in three types of verbal tasks: sex-differentiated (verbal fluency and semantic decision) vs. sex-neutral (verbal reasoning) tasks. Methods: A group (n = 32) of healthy young women was tested twice, once during the mid-luteal (high levels of circulating sex hormones) and once during the early follicular (low levels of sex hormones) phases of the menstrual cycle. A comparable group of healthy young men (n = 32) was tested once. EEG was continuously recorded. The differences in alpha power on homologous sites of the left and right hemispheres were then calculated. Results: We found a clear congruence between performance on a task and laterality score: for sex-differentiated tasks, the activational effects of sex hormones were observed in both performance and laterality scores, while there were neither performance nor laterality scores shifts throughout the menstrual cycle for the sex-neutral task. Interestingly, measures of functional asymmetry were higher in the luteal compared to the menstrual phase. Conclusions: These findings suggest that sex hormones modulate verbal performance through their influence on hemispheric asymmetry. Full article

(This article belongs to the Special Issue Language Perception and Processing)

13 pages, 1194 KB

Open AccessArticle

No Association Between Face Recognition and Spatial Navigation: Evidence from Developmental Prosopagnosia and Super-Recognizers

by Alejandro J. Estudillo, Olivia Dark, Jan M. Wiener and Sarah Bate

Brain Sci. 2025, 15(11), 1140; https://doi.org/10.3390/brainsci15111140 (registering DOI) - 24 Oct 2025

Abstract

Background/Objectives: Previous studies have reported associations between prosopagnosia and spatial navigation, but it remains unclear whether this link is merely coincidental (i.e., observable only in prosopagnosia) or genuinely interdependent (i.e., such that variation in one ability predicts variation in the other across the [...] Read more.

Background/Objectives: Previous studies have reported associations between prosopagnosia and spatial navigation, but it remains unclear whether this link is merely coincidental (i.e., observable only in prosopagnosia) or genuinely interdependent (i.e., such that variation in one ability predicts variation in the other across the full spectrum of face-recognition abilities). This study aimed to directly test this possibility by examining the relationship between face recognition and navigational skills in developmental prosopagnosics (DPs), super-recognizers (SRs), and control participants. Methods: Eighteen DPs, sixteen SRs, and twenty-eight control participants were tested in a recently validated route-learning task, in which they were asked to memorize a route from a first-person perspective. In the subsequent test stages, both route repetition and route retracing were assessed. Results: Group analyses showed comparable performance in route repetition and retracing across the three groups. Single-case analyses confirmed these findings and indicated that only two DPs and two SRs performed worse than control participants in route retracing. Conclusions: These findings suggest that spatial navigation and face recognition are not directly associated and therefore appear to be different skills. Full article

(This article belongs to the Special Issue Advances in Face Perception and How Disorders Affect Face Perception)

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22 pages, 2233 KB

Open AccessArticle

Strengthening the Aging Brain: Functional Connectivity Changes After a Language-Based Cognitive Program

by Anne-Sophie Beaumier, Ana Paula Bastos, Bárbara Malcorra, Bárbara Rusch da Rocha, Vanessa Bisol, Fernanda Souza Espinosa Borges, Erica dos Santos Rodrigues, Maria Teresa Carthery-Goulart, Lucas Porcello Schilling, Karine Marcotte and Lilian Cristine Hübner

Brain Sci. 2025, 15(11), 1139; https://doi.org/10.3390/brainsci15111139 (registering DOI) - 24 Oct 2025

Abstract

Background/Objectives: Accumulating evidence suggests that cognitive training can induce functional reorganization of intrinsic connectivity networks involved in higher-order cognitive processes. However, few interventions have specifically targeted language, an essential domain tightly interwoven with memory, attention, and executive functions. Given their foundational role in [...] Read more.

Background/Objectives: Accumulating evidence suggests that cognitive training can induce functional reorganization of intrinsic connectivity networks involved in higher-order cognitive processes. However, few interventions have specifically targeted language, an essential domain tightly interwoven with memory, attention, and executive functions. Given their foundational role in communication, reasoning, and knowledge acquisition, enhancing language-related abilities may yield widespread cognitive benefits. This study investigated the neural impact of a new structured, language-based cognitive training program on neurotypical older adults. Methods: Twenty Brazilian Portuguese-speaking women (aged 63–77 years; schooling 9–20 years; low-to-medium socioeconomic status) participated in linguistic activities designed to engage language and general cognitive processing. Behavioral testing and resting-state functional Magnetic Resonance Imaging (fMRI) were conducted before and after the intervention. Results: Functional connectivity analyses revealed significant post-intervention increases in connectivity within the frontoparietal network, critical for language processing, and the ventral attentional network, associated with attentional control. Conclusions: The observed neural enhancements indicate substantial plasticity in cognitive networks among older adults, highlighting the effectiveness of linguistic interventions in modulating critical cognitive functions. These findings provide a foundation for future research on targeted cognitive interventions to promote healthy aging and sustain cognitive vitality. Full article

(This article belongs to the Special Issue Advances in Speech and Language Research for Cognitive Well-Being in Aging)

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14 pages, 3288 KB

Open AccessArticle

CT Morphometric Analysis of Ossification Centres in the Fetal Th12 Vertebra

by Magdalena Grzonkowska, Michał Kułakowski, Zofia Dzięcioł-Anikiej, Agnieszka Rogalska, Beata Zwierko, Sara Kierońska-Siwak, Karol Elster, Stanisław Orkisz and Mariusz Baumgart

Brain Sci. 2025, 15(11), 1138; https://doi.org/10.3390/brainsci15111138 (registering DOI) - 24 Oct 2025

Abstract

Objectives: The present study aimed to determine the growth dynamics of the ossification centers of the twelfth thoracic vertebra in the human fetus, focusing on detailed linear, surface, and volumetric parameters of both the vertebral body and neural processes. Methods: The investigation was [...] Read more.

Objectives: The present study aimed to determine the growth dynamics of the ossification centers of the twelfth thoracic vertebra in the human fetus, focusing on detailed linear, surface, and volumetric parameters of both the vertebral body and neural processes. Methods: The investigation was based on 55 human fetuses (27 males, 28 females) aged 17–30 weeks of gestation. High-resolution low-dose computed tomography, three-dimensional reconstruction, digital image analysis and appropriate statistical modeling were used to obtain detailed morphometric measurements. Results: All measured morphometric parameters of the Th12 vertebral body ossification center—transverse and sagittal diameters, cross-sectional area, and volume—increased linearly with gestational age (R² = 0.94–0.97). A similar linear growth pattern was demonstrated for the length, width, cross-sectional area, and volume of the right and left neural process ossification centers (R² = 0.97–0.98). No statistically significant sex-related or side-related differences were found, allowing the establishment of single normative growth curves for each parameter. Conclusions: This study provides the first comprehensive CT-based normative data for the ossification centers of the fetal Th12 vertebra in the second and early third trimesters. The presented linear growth models and reference values may assist anatomists, radiologists, obstetricians, and pediatric spine surgeons in estimating fetal age, and in the prenatal and postnatal assessment of congenital spinal anomalies, especially at the thoracolumbar junction. Further research on larger and broader gestational cohorts is warranted to validate and extend these findings. Full article

(This article belongs to the Special Issue Translational Neuroanatomy: Recent Updates and Future Perspectives—2nd Edition)

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12 pages, 324 KB

Open AccessArticle

Evaluation of Inflammatory and Oxidative Markers and Their Diagnostic Value in Schizophrenia

by Mehmet Güneş, Betül Uyar, Süleyman Dönmezdil and İbrahim Kaplan

Brain Sci. 2025, 15(11), 1137; https://doi.org/10.3390/brainsci15111137 - 23 Oct 2025

Abstract

Objective: Schizophrenia is a chronic psychiatric disorder associated with increased oxidative stress. We aimed to investigate serum myeloperoxidase (MPO), catalase (CAT), and malondialdehyde (MDA) levels and their diagnostic value in schizophrenia. Methods: Sixty patients with schizophrenia, diagnosed according to DSM-V criteria, and 65 [...] Read more.

Objective: Schizophrenia is a chronic psychiatric disorder associated with increased oxidative stress. We aimed to investigate serum myeloperoxidase (MPO), catalase (CAT), and malondialdehyde (MDA) levels and their diagnostic value in schizophrenia. Methods: Sixty patients with schizophrenia, diagnosed according to DSM-V criteria, and 65 age- and sex-matched healthy controls were enrolled. Clinical severity was assessed with the Positive and Negative Syndrome Scale (PANSS) and Clinical Global Impression (CGI). Serum MPO and CAT were measured using ELISA, and MDA levels were determined spectrophotometrically. Receiver operating characteristic (ROC) analysis was performed to assess diagnostic performance. Results: Compared with controls, schizophrenia patients demonstrated significantly higher serum MDA (5.64 vs. 3.42 pg/mL, p < 0.001), MPO (77.25 vs. 31.42 ng/mL, p < 0.001), and CAT (22.06 vs. 6.58 ng/mL, p < 0.001) levels. Subgroup analysis revealed consistently increased values across patients receiving typical, atypical, or combined antipsychotics. ROC analysis indicated good diagnostic accuracy: AUC = 0.884 for MDA (cut-off: 3.79 pg/mL), AUC = 0.882 for MPO (cut-off: 34.56 ng/mL), and AUC = 0.875 for CAT (cut-off: 9.38 ng/mL), all p < 0.001. Combined analysis of MPO, CAT, and MDA yielded superior diagnostic performance (AUC = 0.995; sensitivity = 98.3%). MPO was positively correlated with PANSS-N scores (r = 0.275, p = 0.033), and both MPO and CAT were correlated with CGI severity scores. Conclusions: Elevated MPO, CAT, and MDA levels indicate increased oxidative stress in schizophrenia. MPO may also be associated with negative symptom severity. These findings suggest potential utility of oxidative stress biomarkers as adjunctive diagnostic tools, although results should be considered preliminary and validated in larger, drug-naïve, and longitudinal samples. Full article

(This article belongs to the Section Neuropsychiatry)

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22 pages, 10534 KB

Open AccessArticle

M³ASD: Integrating Multi-Atlas and Multi-Center Data via Multi-View Low-Rank Graph Structure Learning for Autism Spectrum Disorder Diagnosis

by Shuo Yang, Zuohao Yin, Yue Ma, Meiling Wang, Shuo Huang and Li Zhang

Brain Sci. 2025, 15(11), 1136; https://doi.org/10.3390/brainsci15111136 - 23 Oct 2025

Abstract

Background: Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental condition for which accurate and automated diagnosis is crucial to enable timely intervention. Resting-state functional magnetic resonance imaging (rs-fMRI) serves as one of the key modalities for diagnosing ASD and elucidating its underlying [...] Read more.

Background: Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental condition for which accurate and automated diagnosis is crucial to enable timely intervention. Resting-state functional magnetic resonance imaging (rs-fMRI) serves as one of the key modalities for diagnosing ASD and elucidating its underlying mechanisms. Numerous existing studies using rs-fMRI data have achieved accurate diagnostic performance. However, these methods often rely on a single brain atlas for constructing brain networks and overlook the data heterogeneity caused by variations in imaging devices, acquisition parameters, and processing pipelines across multiple centers. Methods: To address these limitations, this paper proposes a multi-view, low-rank subspace graph structure learning method to integrate multi-atlas and multi-center data for automated ASD diagnosis, termed M³ASD. The proposed framework first constructs functional connectivity matrices from multi-center neuroimaging data using multiple brain atlases. Edge weight filtering is then applied to build multiple brain networks with diverse topological properties, forming several complementary views. Samples from different classes are separately projected into low-rank subspaces within each view to mitigate data heterogeneity. Multi-view consistency regularization is further incorporated to extract more consistent and discriminative features from the low-rank subspaces across views. Results: Experimental results on the ABIDE-I dataset demonstrate that our model achieves an accuracy of 83.21%, outperforming most existing methods and confirming its effectiveness. Conclusions: The proposed method was validated using the publicly available Autism Brain Imaging Data Exchange (ABIDE) dataset. Experimental results demonstrate that the M³ASD method not only improves ASD diagnostic accuracy but also identifies common functional brain connections across atlases, thereby enhancing the interpretability of the method. Full article

(This article belongs to the Special Issue Biomarker Development in the Early Identification of Autism Spectrum Disorders)

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8 pages, 498 KB

Open AccessCommunication

Correction of Vitamin D Deficiency Improves PTSD Symptoms in Gulf War Veterans

by Chandrasekhar Kesavan, Donna D. Strong and Richard M. Strong

Brain Sci. 2025, 15(11), 1135; https://doi.org/10.3390/brainsci15111135 - 23 Oct 2025

Abstract

Gulf War Veterans (GWVs) presenting with irritable bowel syndrome-diarrhea (IBS-D) often exhibit concurrent post-traumatic stress disorder (PTSD) or traumatic brain injury (TBI). All Veterans’ Affair physicians are required to assess symptoms of depression, anxiety, and suicide ideation by maintaining yearly training. In a [...] Read more.

Gulf War Veterans (GWVs) presenting with irritable bowel syndrome-diarrhea (IBS-D) often exhibit concurrent post-traumatic stress disorder (PTSD) or traumatic brain injury (TBI). All Veterans’ Affair physicians are required to assess symptoms of depression, anxiety, and suicide ideation by maintaining yearly training. In a previous study for IBS-D (3), we identified significant vitamin D deficiency (VDD), with an average level of 19 ng/mL. This includes those with and without PTSD, TBI, showing depression and anxiety symptoms. Since VDD is associated with PTSD, and all veterans not on supplementation were found to be VDD (>90%) at our facility, we investigated a possible association between VDD and these neuropsychological conditions. While age and body mass index (BMI), seasons, and demographic locations are known to affect vitamin D levels, we found no correlation between these factors and VDD in the PTSD group and those with IBS-D. In the TBI group, VDD did correlate with BMI. Multiple deployments appeared to have a minor negative effect on vitamin D levels (a 11–13% contribution) in veterans with either PTSD or TBI. Although these veterans showed signs of inflammation with elevated minor C-reactive protein (CRP) levels (4.7 mg/L), there was a negative correlation between CRP and vitamin D to suggest that inflammation is not the primary cause of PTSD or TBI. Following daily vitamin D treatment, vitamin D levels returned to a normal average of 30 ng/mL (less than 30 ng/mL is abnormal). Treatment had no effect on serum calcium levels, but did lead to a resolution of depression, anxiety, TBI, and PTSD symptoms in the majority of patients. These findings suggest that correcting VDD in GWVs visiting GI clinics with co-occurring PTSD and TBI had reduced psychological symptoms. Replacing vitamin D is a simple strategy to implement, rather than increasing neurotrophic medications in some patients. Full article

(This article belongs to the Special Issue Traumatic Stress and Dissociative Disorder)

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22 pages, 2124 KB

Open AccessArticle

The Effect of 5G Mobile Phone Electromagnetic Exposure on Corticospinal and Intracortical Excitability in Healthy Adults: A Randomized Controlled Pilot Study

by Azadeh Torkan, Maryam Zoghi, Negin Foroughimehr and Shapour Jaberzadeh

Brain Sci. 2025, 15(11), 1134; https://doi.org/10.3390/brainsci15111134 - 22 Oct 2025

Abstract

Background: Research on the impact of 5G mobile phone electromagnetic exposure on corticospinal excitability and intracortical mechanisms is still poorly understood. Objective: This randomized controlled pilot study explored the effects of 5G mobile phone exposure at 3.6 GHz (power density: 0.0030 W/m² [...] Read more.

Background: Research on the impact of 5G mobile phone electromagnetic exposure on corticospinal excitability and intracortical mechanisms is still poorly understood. Objective: This randomized controlled pilot study explored the effects of 5G mobile phone exposure at 3.6 GHz (power density: 0.0030 W/m²) on corticospinal excitability and intracortical mechanisms in healthy adults. Methods: Nineteen healthy participants (mean age: 36.5 years) were exposed to 5G mobile phone exposure for 5 and 20 min, approximating the typical duration of a phone call. Corticospinal excitability, intracortical facilitation, short intracortical inhibition, and long intracortical inhibition using single- and paired-pulse transcranial magnetic stimulation assessed before and immediately after exposure were performed. Results: A two-way repeated-measures ANOVA revealed no significant interactions between exposure condition (5 min, 20 min, sham) and time (pre vs. post) for CSE, ICF, SICI, or LICI (all p > 0.15). Bayesian analyses yielded Bayes factors close to 1, indicating inconclusive evidence for both the null and alternative hypotheses. Conclusion: Short-term exposure to 5G mobile phone electromagnetic fields did not produce detectable changes in corticospinal or intracortical excitability. Bayesian evidence was similarly inconclusive (Bayes factors ≈ 1), suggesting that the data provide limited support for either the presence or absence of a detectable effect. Any potential influence of 5G exposure on neural function is therefore likely to be subtle with the present methods. As a pilot study, these findings should be interpreted cautiously and underscore the need for further research using more sensitive outcome measures, extended exposure durations, and vulnerable populations. Full article

(This article belongs to the Section Neurotechnology and Neuroimaging)

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23 pages, 3402 KB

Open AccessArticle

Resting-State and Task-Based Functional Connectivity Reveal Distinct mPFC and Hippocampal Network Alterations in Major Depressive Disorder

by Ekaete Ekpo, Lysianne Beynel, Bruce Luber, Zhi-De Deng, Timothy J. Strauman and Sarah H. Lisanby

Brain Sci. 2025, 15(11), 1133; https://doi.org/10.3390/brainsci15111133 - 22 Oct 2025

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Abstract

Background: Resting-state functional connectivity (RSFC) is widely used to identify abnormal brain function associated with depression. Resting-state functional magnetic resonance imaging (fMRI) scans have many potential confounds, and task-based FC might provide complementary information leading to better insight on brain function. Methods: We [...] Read more.

Background: Resting-state functional connectivity (RSFC) is widely used to identify abnormal brain function associated with depression. Resting-state functional magnetic resonance imaging (fMRI) scans have many potential confounds, and task-based FC might provide complementary information leading to better insight on brain function. Methods: We used MATLAB’s (version 2024b) CONN toolbox (version 22a) to evaluate FC in 40 adults with and without major depressive disorder (MDD) (n_MDD = 23, n_HC = 17). fMRI acquisition was performed while participants were at rest and while performing the Selves Task, an individualized goal priming task. Seed-based analyses were performed using two seeds: medial prefrontal cortex (mPFC) and left hippocampus. Results: Both groups showed strong positive RSFC between the mPFC and other DMN regions, including the anterior cingulate cortex and precuneus, which had more focal positive FC to the mPFC during the task in both groups. Additionally, the MDD group had significantly lower RSFC between the mPFC and several regions, including the right inferior temporal gyrus. The left hippocampus seed-based analysis revealed a pattern of hypoconnectivity to multiple brain regions in MDD, including the cerebellum, which was present at rest and during the task. Conclusions: Our results indicated multiple FC differences between adults with and without MDD, as well as distinct FC patterns and contrast results in resting state and task-based analyses, including differential FC between mPFC–cerebellum and hippocampus–cerebellum. These results emphasize that resting-state and task-based fMRI capture distinct patterns of brain connectivity. Further investigation into combining resting-state and task-based FC could inform future neuroimaging research. Full article

(This article belongs to the Special Issue Applications of fMRI (Functional Magnetic Resonance Imaging) in Neuropsychiatry and Neurological Disease)

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21 pages, 3685 KB

Open AccessArticle

MSRLNet: A Multi-Source Fusion and Feedback Network for EEG Feature Recognition in ADHD

by Qiulei Han, Ze Song, Hongbiao Ye, Yan Sun, Jian Zhao, Lijuan Shi and Zhejun Kuang

Brain Sci. 2025, 15(11), 1132; https://doi.org/10.3390/brainsci15111132 - 22 Oct 2025

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Abstract

Background: Electroencephalography (EEG) has been widely used in Attention Deficit Hyperactivity Disorder (ADHD) recognition, but existing methods still suffer from limitations in dynamic modeling, small-sample adaptability, and training stability. This study proposes a Multi-Source Fusion and Feedback Network (MSRLNet) to enhance EEG-based ADHD [...] Read more.

Background: Electroencephalography (EEG) has been widely used in Attention Deficit Hyperactivity Disorder (ADHD) recognition, but existing methods still suffer from limitations in dynamic modeling, small-sample adaptability, and training stability. This study proposes a Multi-Source Fusion and Feedback Network (MSRLNet) to enhance EEG-based ADHD recognition. Methods: MSRLNet comprises three modules: (1) Multi-Source Feature Fusion (MSFF), combining microstate and statistical features to improve interpretability; (2) a CNN-GRU Parallel Module (CGPM) for multi-scale temporal modeling; and (3) Performance Feedback–driven Parameter Optimization (PFPO) to enhance training stability. Feature-level data augmentation is introduced to alleviate overfitting in small-sample scenarios. Results: On a public dataset, MSRLNet achieved an accuracy of 98.90%, an F1-score of 98.98%, and a kappa of 0.979, all exceeding comparative approaches. Conclusions: MSRLNet shows high accuracy and robustness in ADHD EEG feature recognition, verifying its potential application value in clinical auxiliary diagnosis. Full article

(This article belongs to the Section Computational Neuroscience, Neuroinformatics, and Neurocomputing)

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17 pages, 1174 KB

Open AccessArticle

Pauses as a Quantitative Measure of Linguistic Planning Challenges in Parkinson’s Disease

by Sara D’Ascanio, Fabrizio Piras, Caterina Spada, Clelia Pellicano and Federica Piras

Brain Sci. 2025, 15(11), 1131; https://doi.org/10.3390/brainsci15111131 - 22 Oct 2025

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Abstract

Background/Objectives: Pausing is a multifaceted phenomenon relevant to motor and cognitive disorders, particularly Parkinson’s Disease (PD). Thus, examining pauses as a metric for linguistic planning and motor speech difficulties in PD patients has gained significant attention. Here, we examined the production of [...] Read more.

Background/Objectives: Pausing is a multifaceted phenomenon relevant to motor and cognitive disorders, particularly Parkinson’s Disease (PD). Thus, examining pauses as a metric for linguistic planning and motor speech difficulties in PD patients has gained significant attention. Here, we examined the production of silent and filled pauses (indexing difficulties at various linguistic processing levels) during narrative tasks to investigate the interplay between pausing behavior and informativeness/productivity measures. Methods: Individuals’ pausing patterns during narratives were analyzed relative to their syntactic context (within and between sentences expressing motor and non-motor related content), in 29 patients in the mild-to-moderate stage of PD, and 29 age-matched healthy speakers. The interaction between communicative metrics (informativeness and productivity), motor symptoms, cognitive capabilities, and pausing behavior was explored to characterize the mechanisms underlying pause production and its influence on discourse content. Results: PD patients’ pausing profile was characterized by an overall reduced number of pauses, longer silent pauses and fewer/shorter filled pauses, particularly before words that extend or specify the semantic content of sentences. Contrary to what was observed in healthy speakers, both the duration of silent pauses and the total number and duration of filled pauses could explain a significant proportion of variance in informativeness measures. Silent pause duration significantly correlated with measures of lexical access, indicating that cognitive processes influence pause production, while motor speech and cognitive challenges may also interact. Conclusions: Current results have significant implications for understanding discourse difficulties linked to PD and for formulating intervention strategies to improve communication efficacy. Full article

(This article belongs to the Section Neurolinguistics)

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Brain Sci., Volume 15, Issue 11 (November 2025) – 13 articles

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