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Brain Sci., Volume 15, Issue 6 (June 2025) – 111 articles

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23 pages, 1109 KiB  
Review
Shaping the Future of Psychiatric Neurosurgery: From Connectomic Precision to Technological Integration
by Cristina V. Torres Díaz, Marta Navas García, Paloma Pulido Rivas, Mónica Lara Almunia and José Antonio Fernández Alén
Brain Sci. 2025, 15(6), 647; https://doi.org/10.3390/brainsci15060647 - 16 Jun 2025
Abstract
Psychiatric neurosurgery is undergoing a profound transformation, propelled by advances in neurotechnology, connectomics, and personalized medicine. Once controversial, surgical interventions are now guided by detailed functional brain mapping and precise neuromodulation techniques, such as deep brain stimulation (DBS), which offer therapeutic options for [...] Read more.
Psychiatric neurosurgery is undergoing a profound transformation, propelled by advances in neurotechnology, connectomics, and personalized medicine. Once controversial, surgical interventions are now guided by detailed functional brain mapping and precise neuromodulation techniques, such as deep brain stimulation (DBS), which offer therapeutic options for patients with severe, treatment-resistant psychiatric disorders. This manuscript reviews the current techniques, including lesion-based procedures and DBS, and explores their mechanisms of action, from synaptic plasticity to large-scale network modulation. It highlights recent progress in neuroimaging, connectomic targeting, and artificial intelligence applications for surgical planning and the prediction of treatment responses. Ethical considerations—including informed consent, identity, and long-term follow-up—are critically examined in light of these advances. Furthermore, the growing role of minimally invasive procedures and wearable integrated neurotechnologies is discussed as part of a shift toward dynamic and adaptive interventions. Although still investigational, psychiatric neurosurgery is emerging as a technologically sophisticated field that demands rigorous clinical evaluation, ethical accountability, and an individualized approach to restoring function and autonomy in some of the most disabling mental illnesses. Full article
19 pages, 1732 KiB  
Article
Pain Hypersensitivity and Increased Urinary Tetrahydrobiopterin Levels in Mice Submitted to High-Fat Diet
by Tuany Eichwald, Débora da Luz Scheffer, Leonardo Barros, Alexandre Solano, Vivian De Souza Menegassi, Ananda Christina Staats Pires, Camila Sartor Spivakoski, Rodrigo A. Da Silva, Joana M. Gaspar, Marcelo Fernando Ronsoni and Alexandra Latini
Brain Sci. 2025, 15(6), 646; https://doi.org/10.3390/brainsci15060646 - 16 Jun 2025
Abstract
Objective: This study aimed to examine the impact of high-fat-diet(HFD)-induced obesity on pain sensitivity and tetrahydrobiopterin (BH4) levels. The effect of moderate-intensity physical exercise, an anti-inflammatory non-pharmacological intervention, on pain scores was also investigated. Methods: Adult male C57BL/J6 mice were fed standard [...] Read more.
Objective: This study aimed to examine the impact of high-fat-diet(HFD)-induced obesity on pain sensitivity and tetrahydrobiopterin (BH4) levels. The effect of moderate-intensity physical exercise, an anti-inflammatory non-pharmacological intervention, on pain scores was also investigated. Methods: Adult male C57BL/J6 mice were fed standard or an HFD for eight weeks. Their total body weight, food intake, locomotor and motivational behavior, and pain reflexes were measured. A subgroup of animals underwent physical exercise for five days per week over six weeks. Blood was collected for glucose tolerance testing and levels of lactate. Urine samples were collected to measure BH4 levels. Results: We showed that the HFD increased weight gain, epididymal white adipose tissue, and the percentage of body weight as epididymal fat. These anthropometric alterations were characterized by impaired glucose tolerance at four and eight weeks of the dietary intervention. It was also observed that reduced locomotor activity and higher pain scores in the HFD-fed mice were prevented by a physical exercise intervention. The HFD also induced an increase in urinary BH4 levels at four and eight weeks of intervention. Conclusions: The HFD increased scores of chemical and mechanical hyperalgesias, as well as urinary BH4 levels. Urinary BH4 can be proposed as a potential easy-to-access, sensitive, and reliable biomarker of pain development, and a promising target for the control of pain hypersensitivity in obesity. Full article
(This article belongs to the Special Issue Novel Insights into Neuroinflammation and Brain Disease)
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19 pages, 966 KiB  
Article
Sensitivity to Instruction Strategies in Motor Learning Is Predicted by Anterior–Posterior TMS Motor Thresholds
by Michael L. Perrier, Kylee R. Graham, Jessica E. Vander Vaart, W. Richard Staines and Sean K. Meehan
Brain Sci. 2025, 15(6), 645; https://doi.org/10.3390/brainsci15060645 - 16 Jun 2025
Abstract
Background: The impact of exogenous explicit knowledge on early motor learning is highly variable and may be influenced by excitability within the procedural sensorimotor network. Recent transcranial magnetic stimulation (TMS) studies suggest that variability in interneuron recruitment by anterior–posterior (AP) currents is linked [...] Read more.
Background: The impact of exogenous explicit knowledge on early motor learning is highly variable and may be influenced by excitability within the procedural sensorimotor network. Recent transcranial magnetic stimulation (TMS) studies suggest that variability in interneuron recruitment by anterior–posterior (AP) currents is linked to differences in functional connectivity between premotor and motor regions. Objectives: This study used controllable pulse parameter TMS (cTMS) to assess how AP-sensitive interneuron excitability interacts with explicit knowledge to influence motor learning. Methods: Seventy-two participants were grouped as AP-positive (n = 36) and AP-negative groups (n = 36) based on whether an AP threshold could be obtained before reaching maximal stimulator output. A narrow (30 µs) stimulus was employed to target the longest latency corticospinal inputs selectively. Participants then practiced a continuous visuomotor tracking task and completed a delayed retention test. Half of each group received explicit knowledge of a repeated sequence embedded between random sequences. Random sequence tracking performance assessed general sensorimotor efficiency; repeated sequence performance assessed sequence-specific learning. Results: Both AP30-positive participants, with and without explicit knowledge, and the AP30-negative without explicit knowledge demonstrated similar improvements in sensorimotor efficiency driven by offline consolidation. However, AP30-negative participants given explicit instruction exhibited significantly reduced improvement in sensorimotor efficiency, primarily due to impaired offline consolidation. Conclusions: These findings suggest that individuals with low excitability in long-latency AP-sensitive inputs may be more vulnerable to interference from explicit instruction. The current results highlight the importance of accounting for individual differences in interneuron excitability when developing instructional strategies for motor learning. Full article
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17 pages, 1891 KiB  
Article
Exploring the Impact of Robotic Hand Rehabilitation on Functional Recovery in Parkinson’s Disease: A Randomized Controlled Trial
by Loredana Raciti, Desiree Latella, Gianfranco Raciti, Chiara Sorbera, Mirjam Bonanno, Laura Ciatto, Giuseppe Andronaco, Angelo Quartarone, Giuseppe Di Lorenzo and Rocco Salvatore Calabrò
Brain Sci. 2025, 15(6), 644; https://doi.org/10.3390/brainsci15060644 - 15 Jun 2025
Abstract
Background/Objective: Parkinson’s disease (PD) is characterized by motor and cognitive impairments that significantly affect quality of life. Robotic-assisted therapies, such as the AMADEO® system, have shown potential in rehabilitating upper limb function but are underexplored in PD. This study aimed to assess [...] Read more.
Background/Objective: Parkinson’s disease (PD) is characterized by motor and cognitive impairments that significantly affect quality of life. Robotic-assisted therapies, such as the AMADEO® system, have shown potential in rehabilitating upper limb function but are underexplored in PD. This study aimed to assess the effects of Robotic-Assisted Therapy (RAT) compared to Conventional Physical Therapy (CPT) on cognitive, motor, and functional outcomes in PD patients. Methods: A single-blind, randomized controlled trial was conducted with PD patients allocated to RAT or CPT. Participants were assessed at baseline (T0) and post-intervention (T1) using measures including MoCA, FAB, UPDRS-III, 9-Hole Peg Test, FMA-UE, FIM, and PDQ-39. Statistical analyses included ANCOVA and regression models. Results: RAT led to significant improvements in global cognition (MoCA, p < 0.001) and executive functioning (FAB, p = 0.0002) compared to CPT. Motor function improved, particularly in wrist and hand control (FMA-UE), whereas changes in fine motor dexterity (9-Hole Peg Test) were less consistent and did not reach robust significance. No significant improvements were observed in broader quality of life domains, depressive symptoms, or memory-related cognitive measures. However, quality of life improved significantly in the stigma subdomain of the PDQ-39 (p = 0.0075). Regression analyses showed that baseline motor impairment predicted cognitive outcomes. Conclusions: RAT demonstrated superior cognitive and motor benefits in PD patients compared to CPT. These results support the integration of robotic rehabilitation into PD management. Further studies with larger sample sizes and long-term follow-up are needed to validate these findings and assess their sustainability. Full article
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20 pages, 1885 KiB  
Review
Hypoxia’s Impact on Hippocampal Functional Connectivity: Insights from Resting-State fMRI Studies
by Julia Micaux, Abir Troudi Habibi, Franck Mauconduit and Marion Noulhiane
Brain Sci. 2025, 15(6), 643; https://doi.org/10.3390/brainsci15060643 - 14 Jun 2025
Abstract
The hippocampus is one of the brain’s most vulnerable structures to hypoxia, playing a crucial role in memory and spatial navigation. This sensitivity makes it a key region for understanding the effects of hypoxia on brain connectivity. This review examines the effects of [...] Read more.
The hippocampus is one of the brain’s most vulnerable structures to hypoxia, playing a crucial role in memory and spatial navigation. This sensitivity makes it a key region for understanding the effects of hypoxia on brain connectivity. This review examines the effects of both acute and chronic hypoxia on resting-state networks (RSNs) that contribute to hippocampal functional connectivity (FC). Hypoxia, characterized by a reduced oxygen supply to the brain, can result from environmental factors (such as high-altitude exposure) or hypoxia-induced pathological conditions (including obstructive sleep apnea and hypoxic–ischemic encephalopathy). The hippocampus’s susceptibility to hypoxic damage significantly impairs brain connectivity. This review examines through rs-fMRI studies how hypoxia alters hippocampal FC, focusing on its effects on RSNs involved in hippocampal functions, and compares acute and chronic hypoxic states. We seek to determine whether distinct or shared patterns of FC changes exist between acute and chronic hypoxia, and how hypoxia indirectly changes hippocampal FC, given the challenges of studying it in isolation. By addressing these questions, this review aims to deepen our understanding of hypoxia-induced changes in hippocampal FC and provide insights into potential therapeutic strategies to mitigate its effects on cognitive functions. Full article
(This article belongs to the Special Issue Brain Network Connectivity Analysis in Neuroscience)
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15 pages, 2337 KiB  
Article
Is It About Speech or About Prediction? Testing Between Two Accounts of the Rhythm–Reading Link
by Susana Silva, Ana Rita Batista, Nathércia Lima Torres, José Sousa, Aikaterini Liapi, Styliani Bairami and Vasiliki Folia
Brain Sci. 2025, 15(6), 642; https://doi.org/10.3390/brainsci15060642 - 14 Jun 2025
Abstract
Background/Objectives: The mechanisms underlying the positive association between reading and rhythmic skills remain unclear. Our goal was to systematically test between two major explanations: the Temporal Sampling Framework (TSF), which highlights the relation between rhythm and speech encoding, and a competing explanation based [...] Read more.
Background/Objectives: The mechanisms underlying the positive association between reading and rhythmic skills remain unclear. Our goal was to systematically test between two major explanations: the Temporal Sampling Framework (TSF), which highlights the relation between rhythm and speech encoding, and a competing explanation based on rhythm’s role in enhancing prediction within visual and auditory sequences. Methods: We compared beat versus duration perception for their associations with encoding and sequence learning (prediction-related) tasks, using both visual and auditory sequences. We also compared these associations for Portuguese vs. Greek participants, since Portuguese stress-timed rhythm is more compatible with music-like beats lasting around 500 ms, in contrast to the syllable-timed rhythm of Greek. If rhythm acts via speech encoding, its effects should be more salient in Portuguese. Results: Consistent with the TSF’s predictions, we found a significant association between beat perception and auditory encoding in Portuguese but not in Greek participants. Correlations between time perception and sequence learning in both modalities were either null or insufficiently supported in both groups. Conclusions: Altogether, the evidence supported the TSF-related predictions in detriment of the Rhythm-as-Predictor (RaP) hypothesis. Full article
(This article belongs to the Section Neurolinguistics)
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31 pages, 3880 KiB  
Review
Sleep Deprivation and Alzheimer’s Disease: A Review of the Bidirectional Interactions and Therapeutic Potential of Omega-3
by Nasar Ullah Khan Niazi, Jiahui Jiang, Haiyan Ou, Ruiye Chen and Zhiyou Yang
Brain Sci. 2025, 15(6), 641; https://doi.org/10.3390/brainsci15060641 - 14 Jun 2025
Abstract
Sleep is essential for physical and mental health, playing a critical role in memory consolidation, behavioral stability, and the regulation of immune and metabolic functions. The incidence of sleep disorders, particularly sleep deprivation (SD), increases with age and is prevalent in neurodegenerative and [...] Read more.
Sleep is essential for physical and mental health, playing a critical role in memory consolidation, behavioral stability, and the regulation of immune and metabolic functions. The incidence of sleep disorders, particularly sleep deprivation (SD), increases with age and is prevalent in neurodegenerative and psychiatric disorders such as Alzheimer’s disease (AD). Nearly 40% of AD patients experience significant chronic sleep impairments. The clinical distinction between late-life sleep disorders and AD is often challenging due to overlapping symptoms, including cognitive decline and behavioral impairments. Although the exact causal relationship between SD and AD remains complex and multifaceted, strong evidence suggests a bidirectional link, with AD patients frequently exhibiting disrupted sleep architecture, reduced slow-wave activity, and shorter total sleep duration. On a pathophysiological level, SD contributes to neuroinflammation, amyloid-β plaque deposition, and tau tangles, which are key features of AD. Current treatments, such as sedatives and antidepressants, often have limitations, including inconsistent efficacy, dependency risks, and poor long-term outcomes/recurrence, highlighting the need for safer and more effective alternatives. This review examines the interplay between SD and AD and proposes omega (n)-3 fatty acids (FAs) as a potential therapeutic intervention. Preclinical and clinical studies suggest that n-3 supplementation may improve sleep onset/quality, reduce neuroinflammation, support synaptic function, and decrease amyloid-β aggregation, thereby alleviating early AD-related neurological changes. Given their safety profile and neuroprotective effects, n-3 FAs represent a promising strategy for managing the comorbidity of sleep disorders in AD. Full article
(This article belongs to the Special Issue What Impact Does Lack of Sleep Have on Mental Health?)
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34 pages, 1488 KiB  
Review
Self, Me, or I? Unravelling the Triumvirate of Selfhood in Pathological Consciousness
by Alexander A. Fingelkurts and Andrew A. Fingelkurts
Brain Sci. 2025, 15(6), 640; https://doi.org/10.3390/brainsci15060640 - 13 Jun 2025
Viewed by 24
Abstract
In this conceptual review, we explore how alterations in the configuration and expression of the three core aspects of experiential Selfhood—‘Self,’ ‘Me’, and ‘I’—both reflect and shape an individual’s susceptibility to neuropsychopathology. Drawing on empirical neurophenomenological evidence and theoretical insights, we examine a [...] Read more.
In this conceptual review, we explore how alterations in the configuration and expression of the three core aspects of experiential Selfhood—‘Self,’ ‘Me’, and ‘I’—both reflect and shape an individual’s susceptibility to neuropsychopathology. Drawing on empirical neurophenomenological evidence and theoretical insights, we examine a range of psychiatric and neurological disorders through the lens of the Selfhood triumvirate. Our findings indicate that, despite variations in the expression of Selfhood aspects across different pathologies, their proportional configuration remains remarkably stable in most conditions, with the ‘Self’ aspect consistently dominant, followed by the ‘Me’ aspect, and finally the ‘I’ aspect. This stability suggests a fundamental neurophenomenological hierarchy in Selfhood organization, which seems to be disrupted only in extreme cases such as vegetative (unresponsive) states and also schizophrenia. Ultimately, we propose that all neuropsychopathologies are best understood as disorders of Selfhood, where disruptions in the dynamic balance and configuration of the ‘Self’, ‘Me’, and ‘I’ aspects accompany neurophenomenological manifestations in distinct dysfunctions and pathologies. Full article
(This article belongs to the Section Neuropsychiatry)
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18 pages, 1102 KiB  
Article
Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance
by Federica Aracri, Maria Giovanna Bianco, Andrea Quattrone and Alessia Sarica
Brain Sci. 2025, 15(6), 639; https://doi.org/10.3390/brainsci15060639 - 13 Jun 2025
Viewed by 23
Abstract
Background/Objectives: Missing data is a common challenge in neuroscience and neuroimaging studies, especially in the context of neurodegenerative disorders such as Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Inadequate handling of missing values can compromise the performance and interpretability of machine learning [...] Read more.
Background/Objectives: Missing data is a common challenge in neuroscience and neuroimaging studies, especially in the context of neurodegenerative disorders such as Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Inadequate handling of missing values can compromise the performance and interpretability of machine learning (ML) models. This study aimed to systematically compare the impacts of five imputation methods on classification performance using multimodal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Methods: We analyzed a dataset including clinical, cognitive, and neuroimaging features from ADNI participants diagnosed with MCI or AD. Five imputation techniques—mean, median, k-Nearest Neighbors (kNNs), Multiple Imputation by Chained Equations (MICE), and missForest (MF)—were applied. Classification tasks were performed using Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). Models were trained on the imputed datasets and evaluated on a test set without missing values. The statistical significance of performance differences was assessed using McNemar’s test. Results: On the test set, MICE imputation yielded the highest accuracy for both RF (0.76) and LR (0.81), while SVM performed best with median imputation (0.81). McNemar’s test revealed significant differences between RF and both LR and SVM (p < 0.01), but not between LR and SVM. Simpler methods like mean and median performed adequately but were generally outperformed by MICE. The performance of kNNs and MF was less consistent. Conclusions: Overall, the choice of imputation method significantly affects classification accuracy. Selecting strategies tailored to both data structure and classifier is essential for robust predictive modeling in clinical neuroscience. Full article
18 pages, 1771 KiB  
Article
Analysis of Early EEG Changes After Tocilizumab Treatment in New-Onset Refractory Status Epilepticus
by Yong-Won Shin, Sang Bin Hong and Sang Kun Lee
Brain Sci. 2025, 15(6), 638; https://doi.org/10.3390/brainsci15060638 - 13 Jun 2025
Viewed by 52
Abstract
Background/Objectives: New-onset refractory status epilepticus (NORSE) is a rare neurologic emergency that often requires immunotherapy despite an unclear etiology and poor response to standard treatments. Tocilizumab, an anti-interleukin-6 monoclonal antibody, has shown promise in case reports; however, objective early biomarkers of treatment [...] Read more.
Background/Objectives: New-onset refractory status epilepticus (NORSE) is a rare neurologic emergency that often requires immunotherapy despite an unclear etiology and poor response to standard treatments. Tocilizumab, an anti-interleukin-6 monoclonal antibody, has shown promise in case reports; however, objective early biomarkers of treatment response remain lacking. We investigated early electroencephalography (EEG) changes following tocilizumab administration in NORSE patients using both quantitative and qualitative analyses. Methods: We retrospectively analyzed six NORSE patients who received tocilizumab and underwent continuous EEG monitoring during the period of its administration, following the failure of first- and second-line immunotherapies. Clinical characteristics, treatment history, and EEG recordings were collected. EEG features were analyzed from 2 h before to 1 day after tocilizumab treatment. Quantitative EEG metrics included relative band power, spectral ratios, permutation and spectral entropy, and connectivity metrics (coherence, weighted phase lag index [wPLI]). Temporal EEG trajectories were clustered to identify distinct response patterns. Results: Changes in spectral power and band ratios were heterogeneous and not statistically significant. Among entropy metrics, spectral entropy in the theta band showed a significant reduction at 1 day post-treatment. Connectivity metrics, particularly wPLI, demonstrated a consistent decline after treatment. Clustering of subject–channel trajectories revealed distinct patterns including monotonic changes, indicating individual variation in response. Visual EEG review corroborated qualitative improvements in all cases. Conclusions: Tocilizumab was associated with measurable early EEG changes in NORSE, supported by visually noticeable EEG changes. Quantitative EEG may serve as a useful early biomarker for treatment response in NORSE and assist in monitoring the critical phase. Further validation in larger cohorts and standardized protocols is warranted to confirm these findings and refine EEG-based biomarkers. Full article
(This article belongs to the Section Neurotechnology and Neuroimaging)
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19 pages, 5014 KiB  
Article
Integrated Workflow for Drug Repurposing in Glioblastoma: Computational Prediction and Preclinical Validation of Therapeutic Candidates
by Nazareno Gonzalez, Melanie Pérez Küper, Matías Garcia Fallit, Jorge A. Peña Agudelo, Alejandro Nicola Candia, Maicol Suarez Velandia, Ana Clara Romero, Guillermo Videla Richardson and Marianela Candolfi
Brain Sci. 2025, 15(6), 637; https://doi.org/10.3390/brainsci15060637 - 13 Jun 2025
Viewed by 132
Abstract
Background: Glioblastoma (GBM) remains a significant challenge in oncology due to its resistance to standard treatments including temozolomide. This study aimed to develop and validate an integrated model for predicting GBM sensitivity to alternative chemotherapeutics and identifying new drugs and combinations with therapeutic [...] Read more.
Background: Glioblastoma (GBM) remains a significant challenge in oncology due to its resistance to standard treatments including temozolomide. This study aimed to develop and validate an integrated model for predicting GBM sensitivity to alternative chemotherapeutics and identifying new drugs and combinations with therapeutic potential. Research Design and Methods: We analyzed drug sensitivity data for 272 compounds from CancerRxTissue and employed in silico algorithms to assess blood-brain barrier permeability. The model was used to predict GBM sensitivity to various drugs, which was then validated using GBM cellular models. Alternative drugs targeting overexpressed and negative prognostic biomarkers in GBM were experimentally validated. Results: The model predicted that GBM is more sensitive to Etoposide and Cisplatin compared to Temozolomide, which was confirmed by experimental validation in GBM cells. We also identified novel drugs with high predicted sensitivity in GBM. Daporinad, a NAMPT inhibitor that permeates the blood-brain barrier was selected for further preclinical evaluation. This evaluation supported the in silico predictions of high potential efficacy and safety in GBM. Conclusions: Our findings using different cellular models suggest that this computational prediction model could constitute a valuable tool for drug repurposing in GBM and potentially in other tumors, which could accelerate the development of more effective cancer treatments. Full article
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20 pages, 3404 KiB  
Article
Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease
by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng and Jiyang Dong
Brain Sci. 2025, 15(6), 636; https://doi.org/10.3390/brainsci15060636 - 12 Jun 2025
Viewed by 116
Abstract
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms [...] Read more.
Background: Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder characterized by progressive neurodegeneration and connectivity deterioration. While resting-state functional magnetic resonance imaging (fMRI) provides critical insights into brain network abnormalities, traditional mutual information-based methods exhibit inherent limitations in characterizing the dynamic synergistic mechanisms between cerebral regions. Method: This study pioneered the application of an Integrated Information Decomposition (ΦID) framework in AD brain network analysis, constructing single-sample network models based on ΦID-derived synergy metrics to systematically compare their differences with mutual information-based methods in pathological sensitivity, computational robustness, and network representation capability, while detecting brain regions with declining dynamic synergy during AD progression through intergroup t-tests. Result: The key finding are as follows: (1) synergy metrics exhibited lower intra-group coefficient of variation than mutual information metrics, indicating higher computational stability; (2) single-sample reconstruction significantly enhanced the statistical power in intergroup difference detection; (3) synergy metrics captured brain network features that are undetectable by traditional mutual information methods, with more pronounced differences between networks; (4) key node analysis demonstrated spatiotemporal degradation patterns progressing from initial dysfunction in orbitofrontal–striatal–temporoparietal pathways accompanied by multi-regional impairments during prodromal stages, through moderate-phase decline located in the right middle frontal and postcentral gyri, to advanced-stage degeneration of the right supramarginal gyrus and left inferior parietal lobule. ΦID-driven dynamic synergy network analysis provides novel information integration theory-based biomarkers for AD progression diagnosis and potentially lays the foundation for pathological understanding and subsequent targeted therapy development. Full article
(This article belongs to the Special Issue Using Neuroimaging to Explore Neurodegenerative Diseases)
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24 pages, 3394 KiB  
Article
Resilience of Neural Networks Underlying the Stroop Effect in the Aftermath of Severe COVID-19: fMRI Pilot Study
by Valérie Beaud, Nicolas Farron, Eleonora Fornari, Vincent Dunet, Sonia Crottaz-Herbette and Stephanie Clarke
Brain Sci. 2025, 15(6), 635; https://doi.org/10.3390/brainsci15060635 - 12 Jun 2025
Viewed by 124
Abstract
Background: Alterations in resting-state functional connectivity and in activation patterns elicited during cognitive tasks were reported in acute to chronic stages of mild, moderate and critical SARS-CoV-2 infection, suggesting the dysregulation of specialised neural networks. In this pilot study, we report on activation [...] Read more.
Background: Alterations in resting-state functional connectivity and in activation patterns elicited during cognitive tasks were reported in acute to chronic stages of mild, moderate and critical SARS-CoV-2 infection, suggesting the dysregulation of specialised neural networks. In this pilot study, we report on activation patterns elicited by the colour–word Stroop task in patients who suffered from severe COVID-19 requiring Intensive Care Unit hospitalisation but who had no prior or COVID-19-related brain damage. Methods: Neural activity elicited during a 16 min long colour–word Stroop task was investigated with 3T fMRI 9 months after severe SARS-CoV-2 infection in six patients and in twenty-four control subjects. Results: Patients’ performance in the Stroop task was within normal limits, with the exception of one (out of six) response time in one patient and one (out of six) accuracy measure in another patient. Activation elicited by the Stroop effect, i.e., the contrasting Incongruent vs. Congruent condition, differed between the first and second parts of the task. In controls, the Stroop effect yielded an increase in activity in prefrontal, cingulate and parieto-temporal clusters as well as in the nucleus accumbens during the first part, and the activity receded during the second part in most regions. Two distinct response profiles were found among patients: (i) a Stroop effect-linked increase during the first part followed by a partial decrease during the second part, as in healthy subjects; and (ii) a weak or absent Stroop effect increase during the first part followed by a partial increase during the second part. Conclusions: The normal performance presented by patients on the Stroop task was associated with two distinct activation patterns. They may represent different resilience profiles of the corresponding neural networks and be indicative of propensity for further recovery and/or susceptibility to therapeutic interventions. Full article
(This article belongs to the Section Neurorehabilitation)
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16 pages, 4024 KiB  
Systematic Review
Epileptic Seizure Detection Using Machine Learning: A Systematic Review and Meta-Analysis
by Lin Bai, Gerhard Litscher and Xiaoning Li
Brain Sci. 2025, 15(6), 634; https://doi.org/10.3390/brainsci15060634 - 12 Jun 2025
Viewed by 221
Abstract
Background/Objectives: Epileptic seizures significantly impact patients’ lives due to their unpredictability, making early and accurate detection crucial for effective treatment. Machine learning (ML) models based on electroencephalogram (EEG) signals have been explored for automated seizure detection. This meta-analysis reviews the performance of ML [...] Read more.
Background/Objectives: Epileptic seizures significantly impact patients’ lives due to their unpredictability, making early and accurate detection crucial for effective treatment. Machine learning (ML) models based on electroencephalogram (EEG) signals have been explored for automated seizure detection. This meta-analysis reviews the performance of ML models in seizure detection and analyzes factors such as the model type (deep learning vs. traditional ML), data preprocessing methods, and dataset types. Aim: This study aims to provide an evidence-based foundation for the future development of intelligent tools by evaluating the performance of ML models in detecting epileptic seizures through a meta-analysis. Methods: A systematic search of multiple databases up to April 2025 identified 60 studies and 93 datasets. The pooled sensitivity, specificity, and area under the curve (AUC) were calculated using Stata 17.0. Subgroup analyses were performed to identify sources of heterogeneity. Publication bias was assessed using Deek’s test and funnel plots. Results: The pooled sensitivity, specificity, and AUC were 0.96 (95% CI 0.95–0.97), 0.97 (95% CI 0.96–0.98), and 0.99 (95% CI 0.98–1.00), respectively, indicating a good performance of ML in seizure detection. Subgroup analyses revealed that the model type, data preprocessing methods, and dataset type contributed to heterogeneity. Conclusions: ML shows a strong potential for EEG-based seizure detection. Imaging devices integrating ML may serve as effective tools for early epilepsy diagnosis. However, larger, multicenter clinical studies are needed to validate these algorithms and enhance their interpretability, safety, and applicability in real-world clinical settings. Full article
(This article belongs to the Section Neurotechnology and Neuroimaging)
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22 pages, 5809 KiB  
Article
Non-Target Suppression Supports the Formation of Representational Prioritization Under High Working Memory Load
by Yaya Zhang, Gongao Li, Xuezhu Hu, Peng Zhang and Jinhong Ding
Brain Sci. 2025, 15(6), 633; https://doi.org/10.3390/brainsci15060633 - 12 Jun 2025
Viewed by 153
Abstract
Background: Target enhancement and non-target suppression are two critical mechanisms underlying representational prioritization in visual working memory (VWM). However, it remains unclear how VWM load modulates these prioritization mechanisms. Methods: Using EEG combined with a retro-cue paradigm, this study investigated how representational prioritization [...] Read more.
Background: Target enhancement and non-target suppression are two critical mechanisms underlying representational prioritization in visual working memory (VWM). However, it remains unclear how VWM load modulates these prioritization mechanisms. Methods: Using EEG combined with a retro-cue paradigm, this study investigated how representational prioritization emerges under low (Experiment 1) and high (Experiment 2) memory load conditions. Methods: Behavioral results showed that under low load, both target and non-target items benefited from retro-cue. ERP analyses revealed significantly larger P2 and P3b amplitudes in response to valid compared to neutral retro-cues, whereas no significant contralateral delay activity (CDA) component was observed. Under high load, cueing benefits were restricted to target items, whereas non-target items suffered impaired performance. ERP analyses again showed enhanced P2 and P3b amplitudes for valid compared to neutral retro-cues, but a significant CDA component was also observed. Time–frequency analyses further revealed frontal theta synchronization (ERS) and posterior alpha desynchronization (ERD) under both load conditions. Notably, theta–alpha phase–amplitude coupling (PAC) was significantly stronger for valid than neutral retro-cues under low load, whereas under high load, PAC did not significantly differ between cue conditions. Conclusions: Together, these findings suggest that target enhancement serves as a stable mechanism for representational prioritization, whereas non-target suppression critically depends on resource availability. VWM load systematically shapes representational prioritization through modulation of oscillatory timing characteristics and inter-regional neural coordination. Full article
(This article belongs to the Section Cognitive, Social and Affective Neuroscience)
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20 pages, 831 KiB  
Article
Adoption of Technology in Older Adults in Mexico City: An Approach from the Technology Acceptance Model
by Itzel Julieta De la Peña-López and Elizabeth Acosta-Gonzaga
Brain Sci. 2025, 15(6), 632; https://doi.org/10.3390/brainsci15060632 - 12 Jun 2025
Viewed by 197
Abstract
Background/Objectives: Currently, older adults face significant digital exclusion due to a lack of technological skills, which limits their access to essential services and their social participation in an environment increasingly dependent on technology. This study aimed to analyze how technological anxiety and social [...] Read more.
Background/Objectives: Currently, older adults face significant digital exclusion due to a lack of technological skills, which limits their access to essential services and their social participation in an environment increasingly dependent on technology. This study aimed to analyze how technological anxiety and social influence affect the perceived usefulness, perceived ease of use, and adoption intention of technological tools among older adults in Mexico City using the Technology Acceptance Model (TAM). Methods: A survey was conducted with 70 older adults attending an event in Mexico City. Results: The findings confirm that, although perceived usefulness and ease of use remain pillars of technology use intention, technology anxiety acts as a critical barrier limiting adoption. At the same time, social influence has a dual effect: on the one hand, it facilitates the perception of ease of use; on the other, it diminishes the perception of usefulness when support becomes pressuring or impatient. Conclusions: These results underscore the need to design interventions that reduce anxiety, strengthen digital literacy, and promote empathetic and motivating social support, thereby effectively enhancing technology adoption among older adults. Full article
(This article belongs to the Special Issue Advances in Cognitive and Psychometric Evaluation)
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14 pages, 1469 KiB  
Article
Exercise Improves Alzheimer’s Disease Phenotype in the TgF344-AD Rat, a Behavioral Time Course Study of Males and Females
by Stephanie E. Hall, Zachary J. White, Troy T. Rohn, Keshari H. Sudasinghe and Michael E. Young
Brain Sci. 2025, 15(6), 631; https://doi.org/10.3390/brainsci15060631 - 12 Jun 2025
Viewed by 190
Abstract
Alzheimer’s disease (AD) is the third leading cause of death among older adults with nearly 6 million diagnosed annually. In the race for a cure, one thing is certain—exercise can reduce your risk. However, the mechanisms responsible for this reduced risk are unknown. [...] Read more.
Alzheimer’s disease (AD) is the third leading cause of death among older adults with nearly 6 million diagnosed annually. In the race for a cure, one thing is certain—exercise can reduce your risk. However, the mechanisms responsible for this reduced risk are unknown. Several studies have linked exercise to improved memory, reduced amyloid beta plaques, and tau hyperphosphorylation in AD. Background/Objectives: By utilizing a novel rat model of AD, TgF344-AD, we evaluated the time course of behavioral shifts as well as the protective effect of exercise. Methods: TgF344-AD animals (61 total, 31 females and 30 males) were assessed every 3 months from 3 to 12 months of age and then assessments were increased to monthly until they reached 18 months of age. A progressive treadmill protocol was administered at 12 months of age and continued until 18 months. Pre-intervention and post-intervention data were analyzed. Results: Females had greater grip strength relative to body mass compared to males and exercise attenuated the age-related and AD-induced decline. Also, female AD-impaired memory was rescued with exercise, while males had no exercise-induced improvements. Conclusions: There is a sex difference present in the TgF344-AD rat model of Alzheimer’s disease and this should be studied further; in addition, sex differences across all models of AD and the human pathology need to be evaluated. Exercise neuroprotection, while more prominent in females, is an important factor in AD research, and further work to understand the mechanisms of neuroprotection is warranted. Full article
(This article belongs to the Section Neurodegenerative Diseases)
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13 pages, 361 KiB  
Article
Nucleus Basalis of Meynert Volume and Cognitive Impairment in Parkinson’s Disease Before and After Deep Brain Stimulation of the Subthalamic Nucleus
by Vibuthi Sisodia, Yarit Wiggerts, Anouk A. Boogaard, Arthur W. G. Buijink, Rozemarije A. Holewijn, Bart E. K. S. Swinnen, Gert J. Geurtsen, Rick Schuurman and Rob M. A. de Bie
Brain Sci. 2025, 15(6), 630; https://doi.org/10.3390/brainsci15060630 - 11 Jun 2025
Viewed by 219
Abstract
Objectives: To investigate whether a smaller volume of the nucleus basalis of Meynert (NBM) is associated with (1) preoperative cognitive impairment and (2) cognitive decline six months after deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson’s disease (PD), [...] Read more.
Objectives: To investigate whether a smaller volume of the nucleus basalis of Meynert (NBM) is associated with (1) preoperative cognitive impairment and (2) cognitive decline six months after deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson’s disease (PD), using detailed neuropsychological assessment (NPA). Methods: PD patients from the GALAXY and DBS-MODE study were included if they had a preoperative MRI and NPA. NBM volume was measured using voxel-based morphometry. Regression analyses were conducted to assess associations between NBM volume and (1) global NPA scores at baseline, (2) baseline cognitive categories (i.e., normal cognition, mild cognitive impairment (MCI) and Parkinson’s disease dementia (PDD)), (3) change in NPA score and (4) cognitive decline based on the reliability change index six months after STN DBS. Results: For 129 patients, NBM volume was significantly associated with baseline cognitive categories (χ2 = 42.4, p < 0.001). However, smaller NBM volume appeared to be associated only with PDD (B = −2.2, p = 0.036), not with MCI. In 103 patients, no association was found between NBM volume and NPA score at baseline, change in NPA score nor cognitive decline six months after STN DBS. Conclusions: Smaller NBM volume appears to be associated with PDD at baseline, but not with cognitive decline six months after STN DBS. Full article
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10 pages, 659 KiB  
Article
Flow-Diverting Stents During Mechanical Thrombectomy for Carotid Artery Dissection-Related Stroke: Analysis from a Multicentre Cohort
by Osama Elshafei, Jonathan Cortese, Nidhal Ben Achour, Eimad Shotar, Jildaz Caroff, Léon Ikka, Cristian Mihalea, Vanessa Chalumeau, Maria Fernanda Rodriguez Erazu, Mariana Sarov, Nicolas Legris, Jean-Christophe Gentric, Frederic Clarençon and Laurent Spelle
Brain Sci. 2025, 15(6), 629; https://doi.org/10.3390/brainsci15060629 - 11 Jun 2025
Viewed by 214
Abstract
Background and Purpose: Mechanical thrombectomy in the context of internal carotid artery dissection (ICA-D) lesions is an undesirable procedure that may necessitate carotid stenting. Flow-diverting stents (FDSs) are promising devices with numerous advantages, particularly in cases involving tortuous anatomy. Here, we investigate the [...] Read more.
Background and Purpose: Mechanical thrombectomy in the context of internal carotid artery dissection (ICA-D) lesions is an undesirable procedure that may necessitate carotid stenting. Flow-diverting stents (FDSs) are promising devices with numerous advantages, particularly in cases involving tortuous anatomy. Here, we investigate the use of FDSs in the acute management of carotid dissection during mechanical thrombectomy procedures in patients with dissection-related strokes. Materials and Methods: This was a multicentric retrospective observational study of consecutive patients admitted for mechanical thrombectomy due to acute ischaemic stroke with ICA-D and treated with an FDS in the acute setting between July 2018 and February 2023. Patient records, procedural details, and post-procedural outcomes, including follow-up data, were reviewed. Results: A total of 11 patients (10 patients with unilateral ICA-D and one patient with bilateral ICA-D) were included, 10 of whom were male, with a median age of 54 years (range: 35–85 years) and NIHSS scores at admission ranging from 3 to 32 (median 13). Eight cases (73%) involved intracranial occlusion (tandem stroke), with the intracranial occlusion managed first each time. An FDS was selected when the dissection was long and/or the ICA was tortuous, and successful deployment was achieved in all patients with a favourable angiographic outcome (TICI 2B-3). A favourable outcome (modified Rankin scale 0–2 at 90 days) was observed in five patients (45%), with four patients (36%) experiencing symptomatic ICH and three patients having stent occlusion out of the 12 treated ICA-D cases. Conclusions: The use of FDSs for acute stenting in ICA-D-related stroke can be performed efficiently, resulting in excellent angiographic outcomes and an acceptable rate of favourable outcomes specific to the pathology. Larger prospective studies are still needed to confirm the potential benefits of FDSs in acute situations. Full article
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13 pages, 4782 KiB  
Case Report
Anti-Ri Paraneoplastic Neurological Syndrome Presenting with Ocular Flutter in a Patient with Breast Cancer
by Francesca Cascone, Federica Stella, Christian Barbato, Antonio Minni and Giuseppe Attanasio
Brain Sci. 2025, 15(6), 628; https://doi.org/10.3390/brainsci15060628 - 11 Jun 2025
Viewed by 218
Abstract
Ocular flutter is an uncommon ophthalmic finding that may indicate paraneoplastic phenomena, and it is clinically characterized by intermittent bursts of conjugate, horizontal saccades without an intersaccadic interval. Ocular flutter must be differentiated from opsoclonus, which, although also characteristic of certain paraneoplastic syndromes, [...] Read more.
Ocular flutter is an uncommon ophthalmic finding that may indicate paraneoplastic phenomena, and it is clinically characterized by intermittent bursts of conjugate, horizontal saccades without an intersaccadic interval. Ocular flutter must be differentiated from opsoclonus, which, although also characteristic of certain paraneoplastic syndromes, is instead defined by multidirectional saccades on both the horizontal and vertical planes. This report describes a very rare presentation of anti-Ri syndrome in a patient with an undiagnosed breast cancer, presenting with ocular flutter, dizziness, blurred vision, photophobia, and vomiting. Comprehensive evaluations, including contrast-enhanced brain Magnetic Resonance Imaging (MRI), brain Computed Tomography (CT) scan, ophthalmological assessment, viral serology, complete blood count and thyroid, renal coagulation, hepatic function assessments, vitamin D and B12 levels, were all normal. Upon excluding other potential etiologies for the neurological symptoms, a paraneoplastic origin was considered. Serological tests confirmed the presence of anti-Ri onconeural antibodies, and a whole-body CT scan identified nodules in the right breast. Despite surgical excision of the primary tumor and subsequent medical therapy, there was no improvement in the neurological symptoms. Follow-up evaluations at 2 months, 6 months, 1 year and 2 years revealed persistent vestibular and neurological symptoms, with serum tests remaining positive for anti-Ri antibodies and no clinical or radiological evidence of neoplastic recurrence. Full article
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1 pages, 139 KiB  
Correction
Correction: Liu et al. Relationships between Grey Matter Volume in the Bilateral Superior Frontal Gyrus and Reactive Aggression Varied by Level of Traditional Masculinity. Brain Sci. 2024, 14, 605
by Weijun Liu, Cody Ding, Ziang Li and Hong Chen
Brain Sci. 2025, 15(6), 627; https://doi.org/10.3390/brainsci15060627 - 11 Jun 2025
Viewed by 123
Abstract
There is a typographical error in the description of participant demographics in the original publication [...] Full article
27 pages, 612 KiB  
Systematic Review
Cocaine Cues Used in Experimental Research: A Systematic Review
by Eileen Brobbin, Natalie Lowry, Matteo Cella, Alex Copello, Simon Coulton, Jerome Di Pietro, Colin Drummond, Steven Glautier, Ceyda Kiyak, Thomas Phillips, Daniel Stahl, Shelley Starr, Lucia Valmaggia, Colin Williams and Paolo Deluca
Brain Sci. 2025, 15(6), 626; https://doi.org/10.3390/brainsci15060626 - 10 Jun 2025
Viewed by 409
Abstract
Aims: Cue exposure therapy (CET) is a promising treatment approach for cocaine substance use disorder (SUD). CET specifically targets the psychological and physiological responses elicited by drug-related cues, aiming to reduce their motivational impact. To advance understanding of CET for cocaine treatment, [...] Read more.
Aims: Cue exposure therapy (CET) is a promising treatment approach for cocaine substance use disorder (SUD). CET specifically targets the psychological and physiological responses elicited by drug-related cues, aiming to reduce their motivational impact. To advance understanding of CET for cocaine treatment, this systematic review aims to categorise the range of cocaine cues used in research. Methods: A systematic review of the existing literature with searches conducted on PubMed and Web of Science bibliographic databases with no time constraints in August 2024 (PROSPERO: CRD42024554361). Three reviewers were independently involved in the screening, review and data extraction process, in line with PRISMA guidelines. Data extracted included participant demographics, study design, data on the cocaine cue task, and examples (if provided). Each study was appraised and received a quality score. The secondary outcome was to summarise examples for each category type identified. The data are presented as a narrative synthesis. Results: 3600 articles were identified and screened. 235 articles were included in the analysis. Cues identified included images, paraphernalia, drug-related words, cocaine smell, auditory stimuli presented via audiotapes, video recordings, scripts, and virtual reality environments, often combining multiple modalities. Included studies recruited cocaine-dependent individuals, recreational users, polydrug users, and non-cocaine-using controls. The sample sizes of the studies ranged from a single case study to a study including 1974 participants. Conclusions: This review found that studies employed a wide range of cue categories, but detailed examples were often lacking, limiting replication. The number and combination of cues varied: some studies used only cocaine-related images, while others included images, videos, physical items, and audiotapes. The level of immersion and personalisation also differed considerably. All studies used cocaine-specific cues, most commonly images or representations of cocaine substance, cocaine use or drug paraphernalia, drug preparation items, or conversations of cocaine use and its effects. The overall quality of the included studies was deemed good, with all adhering to standard research norms. While this review highlights the breath of cue types used in the literature, further research should focus on enhancing cue exposure techniques by incorporating more immersive and personalised stimuli, and by providing clearer documentation of cue characteristics to support replication and clinical translation. Full article
(This article belongs to the Special Issue Psychiatry and Addiction: A Multi-Faceted Issue)
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13 pages, 6124 KiB  
Article
Neuroradiological Evaluation of Anatomo-Morphometric Arcuate Fascicle Modifications According to Different Brain Tumor Histotypes: An Italian Multicentric Study
by Roberto Altieri, Andrea Bianconi, Stefano Caneva, Giovanni Cirillo, Fabio Cofano, Sergio Corvino, Oreste de Divitiis, Giuseppe Maria Della Pepa, Ciro De Luca, Pietro Fiaschi, Gianluca Galieri, Diego Garbossa, Giuseppe La Rocca, Salvatore Marino, Edoardo Mazzucchi, Grazia Menna, Antonio Mezzogiorno, Alberto Morello, Alessandro Olivi, Michele Papa, Daniela Pacella, Rosellina Russo, Giovanni Sabatino, Giovanna Sepe, Assunta Virtuoso, Giovanni Vitale, Rocco Vitale, Gianluigi Zona and Manlio Barbarisiadd Show full author list remove Hide full author list
Brain Sci. 2025, 15(6), 625; https://doi.org/10.3390/brainsci15060625 - 10 Jun 2025
Viewed by 224
Abstract
Background: The arcuate fasciculus (AF) is a critical white matter (WM) tract that connects key cortical language-processing regions, including the so-called Broca’s and Wernicke’s areas. The aim of the present study was to quantitatively assess its radiological–anatomical–morphometric modifications according to different brain tumor [...] Read more.
Background: The arcuate fasciculus (AF) is a critical white matter (WM) tract that connects key cortical language-processing regions, including the so-called Broca’s and Wernicke’s areas. The aim of the present study was to quantitatively assess its radiological–anatomical–morphometric modifications according to different brain tumor histotypes. Methods: A retrospective multicentric Italian study was conducted. AF reconstructions were calculated for both hemispheres for each patient diagnosed with glioblastoma (GBM), low-grade glioma (LGG), brain metastasis, and meningioma using Elements Fibertracking 2.0 software (Brainlab AG, Munich, Germany). A 3D object of each fascicle was evaluated for its volume, average fractional anisotropy (FA), and length. The cerebral healthy hemisphere was compared to the pathological contralateral in different tumor histotypes. Results: In total, 1294 patients were evaluated. A total of 156 met the inclusion criteria. We found a significant difference between healthy hemisphere and the contralateral for AF mean length and volume (p = 0.01 and p < 0.001, respectively). Considering separately the different tumor histotypes, the GBM subgroup (98, 63%) confirmed the results for mean FA and volume (p-value < 0.001); LGG patients (26, 17%) showed no significant difference between healthy and pathological hemisphere for AF mean length, mean FA, and volume (p-value 0.5, p-value 0.3, p-value <0.1, respectively). In patients affected by brain metastasis (18, 12%), Student’s t-test showed a significant difference for FA (p-value 0.003). No differences were found in patients affected by meningiomas (14, 9%) (14). Conclusions: Thorough knowledge of the microscopic anatomy and function of the arcuate fasciculus, as well as the pattern of growth of the different brain tumor histotypes, along with a careful preoperative neuroradiological assessment are mandatory to plan a tailored surgical strategy and perform a safe and effective surgical technique. The AF could be displaced and infiltrated/destructed by the solid component and peritumoral edema, respectively, of GBM. LGG shows a prevalent infiltrative pattern. Metastases account for AF dislocation due to peritumoral edema. Meningiomas do not affect WM anatomy. Full article
(This article belongs to the Special Issue Current Research in Neurosurgery)
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16 pages, 2457 KiB  
Article
Neural Correlates of Cognitive Disengagement Syndrome Symptoms in Children: A Magnetoencephalography Study
by Xiaoqian Yu, Jing Xiang, Jeffery N. Epstein, Leanne Tamm, Josalyn A. Foster and Stephen P. Becker
Brain Sci. 2025, 15(6), 624; https://doi.org/10.3390/brainsci15060624 - 10 Jun 2025
Viewed by 222
Abstract
Background/Objectives: Despite the growing recognition of cognitive disengagement syndrome (CDS), previously termed sluggish cognitive tempo, as a distinct dimension of psychopathology, the neural correlates of CDS remain largely unknown. We investigated the neural correlates of CDS in children using whole-head magnetoencephalography (MEG). Methods [...] Read more.
Background/Objectives: Despite the growing recognition of cognitive disengagement syndrome (CDS), previously termed sluggish cognitive tempo, as a distinct dimension of psychopathology, the neural correlates of CDS remain largely unknown. We investigated the neural correlates of CDS in children using whole-head magnetoencephalography (MEG). Methods: A community-based sample of children (N = 43, ages 8–12 years) was recruited and completed self-report ratings of CDS. MEG was recorded while the children completed an adapted version of the attention network test (ANT). Results: The results indicated that higher levels of self-reported CDS symptoms were associated with larger changes in the root-mean square (ΔRMS) (incongruent—congruent trials) in M2 and M3, suggesting children with higher levels of CDS symptoms might require greater mental effort to overcome distractors during incongruent trials. The source localization analysis initially revealed a negative correlation between child self-reported CDS symptoms and ΔM2 power (incongruent—congruent trials) in the medial prefrontal cortex (mPFC), suggesting insufficient power allocation in a region critical for attentional processing. However, this association was no longer significant after controlling for ADHD status. No significant correlation was found between self-reported CDS symptoms and alerting or orienting. Conclusions: These findings provide initial evidence of the disrupted attentional processing associated with CDS in children. Further replication and extension with larger samples are warranted. Full article
(This article belongs to the Section Cognitive, Social and Affective Neuroscience)
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23 pages, 9130 KiB  
Article
Individual Differences in the Neurocognitive Effect of Movement During Executive Functioning in Children with ADHD: Impact of Subtype, Severity, and Gender
by Beverly-Ann Hoy, Maya Feehely, Michelle Bi, Matthew Lam, Androu Abdalmalak and Barbara Fenesi
Brain Sci. 2025, 15(6), 623; https://doi.org/10.3390/brainsci15060623 - 9 Jun 2025
Viewed by 260
Abstract
Background/Objectives: Attention-Deficit Hyperactivity Disorder (ADHD) is an immensely heterogeneous developmental disorder, uniquely impacting each individual. Physical movement is a promising adjunct behavioral treatment that can promote executive functioning in children with ADHD. The current study used neuroimaging and behavioral techniques to investigate the [...] Read more.
Background/Objectives: Attention-Deficit Hyperactivity Disorder (ADHD) is an immensely heterogeneous developmental disorder, uniquely impacting each individual. Physical movement is a promising adjunct behavioral treatment that can promote executive functioning in children with ADHD. The current study used neuroimaging and behavioral techniques to investigate the impact of movement during executive functioning on dorsolateral prefrontal cortical (DLPFC) activity and inhibitory control in children with ADHD, with particular focus on key individual difference factors in ADHD, such as subtype, severity, and gender. Methods: Twenty-eight children with ADHD completed a Stroop task while remaining stationary (stationary condition) and while desk cycling (movement condition). Simultaneous functional near-infrared spectroscopy (fNIRS) recorded oxygenated and deoxygenated changes in hemoglobin within the left DLPFC. Participants were categorized into ADHD subtype (hyperactive/impulsive, inattention, combined), ADHD severity (low, moderate, high), and gender (male, female). Results: Those with the hyperactive and combined ADHD subtypes, those with high ADHD severity, and males with ADHD showed greater DLPFC activation when engaging in movement during executive functioning compared to remaining stationary. In contrast, those with the inattentive ADHD subtype, those with low-to-moderate ADHD severity, and females with ADHD showed greater DLPFC activation when remaining stationary during executive functioning compared to engaging in movement. Inhibitory control improved in the stationary condition for females who were predominantly inattentive. Conclusions: This work underscores the importance of considering individual difference factors in ADHD when designing physical activity interventions, as treatment efficacy may vary. Full article
(This article belongs to the Section Behavioral Neuroscience)
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17 pages, 4298 KiB  
Article
The Rapid Sense of Direction (R-SOD) Scale: A Brief Self-Report Tool to Identify Developmental Topographical Disorientation (DTD)
by Tejdeep Jaswal, Ford Burles and Giuseppe Iaria
Brain Sci. 2025, 15(6), 622; https://doi.org/10.3390/brainsci15060622 - 9 Jun 2025
Viewed by 169
Abstract
Background/Objectives: Developmental Topographical Disorientation (DTD) refers to a condition in which individuals report getting lost in very familiar surroundings, since childhood, with no other cognitive complaints, and no brain injuries or neurological disorders. While the cognitive and neurological mechanisms underlying DTD are being [...] Read more.
Background/Objectives: Developmental Topographical Disorientation (DTD) refers to a condition in which individuals report getting lost in very familiar surroundings, since childhood, with no other cognitive complaints, and no brain injuries or neurological disorders. While the cognitive and neurological mechanisms underlying DTD are being investigated, to date, there is no tool available to the public and health practitioners for identifying this lifelong condition. Methods: Here, we used a decade of data (N = 3794) collected in healthy and DTD individuals to produce a short and reliable measure of self-reported sense of direction that could point to the presence of DTD. Results: We adopted a measure of internal consistency (Cronbach’s alpha) and identified four items of the well-known Santa Barbara Sense of Direction (SBSOD) Scale that retain its original strong internal consistency. These four items remain sensitive to the well-known effects of sex on spatial orientation and, importantly, to the presence of DTD, while maintaining the same pattern of association with a cognitive battery of computerized tasks measuring different spatial abilities. Conclusions: This four-item measure could be of practical use to obtain a rapid assessment of an individual’s self-reported sense of direction and help to identify the presence of DTD in the general population. Full article
(This article belongs to the Section Sensory and Motor Neuroscience)
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4 pages, 145 KiB  
Editorial
Advancing Our Understanding of Executive Functioning Development—Measurements and Promotion in Naturalistic Contexts
by Andrea Paula Goldin, Marcos Luis Pietto and Juan Esteban Kamienkowski
Brain Sci. 2025, 15(6), 621; https://doi.org/10.3390/brainsci15060621 - 9 Jun 2025
Viewed by 170
Abstract
The collection of eight articles featured in this Special Issue of Brain Sciences highlights the multifaceted nature of executive functioning (EF), spanning early childhood to adulthood and encompassing diverse contexts—including typical development, clinical populations, and various cultural settings [...] Full article
9 pages, 222 KiB  
Article
Simple and Complex Phonic Tics in Tourette Syndrome
by José Fidel Baizabal-Carvallo and Joseph Jankovic
Brain Sci. 2025, 15(6), 620; https://doi.org/10.3390/brainsci15060620 - 8 Jun 2025
Viewed by 262
Abstract
Tourette syndrome (TS) is the most common cause of tics. Tics are classified as motor and phonic tics. The latter (previously also referred to as “vocal tics”) are manifested by simple sounds (simple phonic tics) or complex, often semantically meaningful utterances (complex phonic [...] Read more.
Tourette syndrome (TS) is the most common cause of tics. Tics are classified as motor and phonic tics. The latter (previously also referred to as “vocal tics”) are manifested by simple sounds (simple phonic tics) or complex, often semantically meaningful utterances (complex phonic tics). Methods: We compared the clinical and demographic features of consecutive patients with TS who exhibited simple and complex phonic tics. Results: There were 149 patients, 117 (78.5%) of whom were males; the mean age at evaluation was 19.61 ± 12.97 years. In total, 35 (23.5%) of these manifested complex phonic tics, and 26 (17.4%) had verbalizations. No statistically significant differences were observed between TS patients with simple versus complex phonic tics with respect to sex, age at onset, age at presentation, or comorbid attention-deficit/hyperactivity disorder or obsessive–compulsive disorder. Patients with complex phonic tics more frequently had trunk tics (p = 0.002), complex motor tics (p < 0.001), copropraxia (p = 0.002), a wider variety of phonic tics (p < 0.001) and greater tic severity (p = 0.001). The multivariate regression analysis showed an independent association between trunk tics and complex phonic tics. Conclusions: Complex phonic tics seem to be part of a more widely distributed, severe, and complex presentation of TS, likely representing a continuum within the spectrum of motor and phonic tics. Full article
(This article belongs to the Special Issue Clinical Research on Tourette Syndrome: Advances and Challenges)
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Article
Movement Impairments May Not Preclude Visuomotor Adaptation After Stroke
by Robert Taylor Moore, Mark Andrew Piitz, Nishita Singh, Sean Peter Dukelow and Tyler Cluff
Brain Sci. 2025, 15(6), 619; https://doi.org/10.3390/brainsci15060619 - 8 Jun 2025
Viewed by 252
Abstract
Purpose: Many individuals with stroke partake in rehabilitation to improve their movements. Rehabilitation operates on the assumption that individuals with stroke can use visual feedback from their movements or visual cues from a therapist to improve their movements through practice. However, this type [...] Read more.
Purpose: Many individuals with stroke partake in rehabilitation to improve their movements. Rehabilitation operates on the assumption that individuals with stroke can use visual feedback from their movements or visual cues from a therapist to improve their movements through practice. However, this type of visuomotor learning can be impaired after stroke. It is unclear whether and how learning impairments relate to impairments in movement. Here, we examined the relationship between learning and movement impairments after stroke. Methods: We recruited adults with first-time unilateral stroke and controls matched for overall age and sex. The participants performed a visuomotor learning task in a Kinarm exoskeleton robot. The task assessed how they adapted their reaching movements to a systematic visual disturbance that altered the relationship between the observed and actual motion of their hand. Learning was quantified as the extent to which the participants adapted their movements to the visual disturbance. A separate visually-guided reaching task was used to assess the straightness, direction, smoothness, and duration of their movements. The relationships between visuomotor adaptation and movement were analyzed using Spearman’s correlations. Control data were used to identify impairments in visuomotor adaptation and movement. The independence of these impairments was examined using Fisher’s exact tests. Results: Impairments in visuomotor adaptation (46.3%) and movement (73.2%) were common in participants with stroke (n = 41). We observed weak–moderate correlations between continuous measures of adaptation and movement performance (rho range: −0.44–0.58). Adaptation and movement impairments, identified using the range of performance in the control participants, were statistically independent (all p > 0.05). Conclusions: Movement impairments accounted for 34% of the variance in visuomotor adaptation at best. Our findings suggest that factors other than movement impairments may influence visuomotor adaptation after stroke. Full article
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17 pages, 3021 KiB  
Article
Prediction of Alzheimer’s Disease Based on Multi-Modal Domain Adaptation
by Binbin Fu, Changsong Shen, Shuzu Liao, Fangxiang Wu and Bo Liao
Brain Sci. 2025, 15(6), 618; https://doi.org/10.3390/brainsci15060618 - 7 Jun 2025
Viewed by 363
Abstract
Background/Objectives: Structural magnetic resonance imaging (MRI) and 18-fluoro-deoxy-glucose positron emission tomography (PET) reveal the structural and functional information of the brain from different dimensions, demonstrating considerable clinical and practical value in the computer-aided diagnosis of Alzheimer’s disease (AD). However, the structure and semantics [...] Read more.
Background/Objectives: Structural magnetic resonance imaging (MRI) and 18-fluoro-deoxy-glucose positron emission tomography (PET) reveal the structural and functional information of the brain from different dimensions, demonstrating considerable clinical and practical value in the computer-aided diagnosis of Alzheimer’s disease (AD). However, the structure and semantics of different modal data are different, and the distribution between different datasets is prone to the problem of domain shift. Most of the existing methods start from the single-modal data and assume that different datasets meet the same distribution, but they fail to fully consider the complementary information between the multi-modal data and fail to effectively solve the problem of domain distribution difference. Methods: In this study, we propose a multi-modal deep domain adaptation (MM-DDA) model that integrates MRI and PET modal data, which aims to maximize the utilization of the complementarity of the multi-modal data and narrow the differences in domain distribution to boost the accuracy of AD classification. Specifically, MM-DDA comprises three primary modules: (1) the feature encoding module, which employs convolutional neural networks (CNNs) to capture detailed and abstract feature representations from MRI and PET images; (2) the multi-head attention feature fusion module, which is used to fuse MRI and PET features, that is, to capture rich semantic information between modes from multiple angles by dynamically adjusting weights, so as to achieve more flexible and efficient feature fusion; and (3) the domain transfer module, which reduces the distributional discrepancies between the source and target domains by employing adversarial learning training. Results: We selected 639 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and considered two transfer learning settings. In ADNI1→ADNI2, the accuracies of the four experimental groups, AD vs. CN, pMCI vs. sMCI, AD vs. MCI, and MCI vs. CN, reached 92.40%, 81.81%, 81.13%, and 85.45%, respectively. In ADNI2→ADNI1, the accuracies of the four experimental groups, AD vs. CN, pMCI vs. sMCI, AD vs. MCI, and MCI vs. CN, reached 94.73%, 81.48%, 85.48%, and 81.69%, respectively. Conclusions: MM-DDA is compared with other deep learning methods on two kinds of transfer learning, and the performance comparison results confirmed the superiority of the proposed method in AD prediction tasks. Full article
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