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16 pages, 1134 KiB  
Article
Neural Correlates of Loudness Coding in Two Types of Cochlear Implants—A Model Study
by Ilja M. Venema, Savine S. M. Martens, Randy K. Kalkman, Jeroen J. Briaire and Johan H. M. Frijns
Technologies 2025, 13(8), 331; https://doi.org/10.3390/technologies13080331 - 1 Aug 2025
Viewed by 131
Abstract
Many speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a ‘virtual’ patient, [...] Read more.
Many speech coding strategies have been developed over the years, but comparing them has been convoluted due to the difficulty in disentangling brand-specific and patient-specific factors from strategy-specific factors that contribute to speech understanding. Here, we present a comparison with a ‘virtual’ patient, by comparing two strategies from two different manufacturers, Advanced Combination Encoder (ACE) versus HiResolution Fidelity 120 (F120), running on two different implant systems in a computational model with the same anatomy and neural properties. We fitted both strategies to an expected T-level and C- or M-level based on the spike rate for each electrode contact’s allocated frequency (center electrode frequency) of the respective array. This paper highlights neural and electrical differences due to brand-specific characteristics such as pulse rate/channel, recruitment of adjacent electrodes, and presence of subthreshold pulses or interphase gaps. These differences lead to considerably different recruitment patterns of nerve fibers, while achieving the same total spike rates, i.e., loudness percepts. Also, loudness growth curves differ significantly between brands. The model is able to demonstrate considerable electrical and neural differences in the way loudness growth is achieved in CIs from different manufacturers. Full article
(This article belongs to the Special Issue The Challenges and Prospects in Cochlear Implantation)
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17 pages, 2003 KiB  
Article
Effect of Caffeinated Chewing Gum on Maximal Strength, Muscular Power, and Muscle Recruitment During Bench Press and Back Squat Exercises
by Li Ding, Jue Liu, Yixuan Ma, Tze-Huan Lei, Mathew Barnes, Li Guo, Bin Chen, Yinhang Cao and Olivier Girard
Nutrients 2025, 17(15), 2455; https://doi.org/10.3390/nu17152455 - 28 Jul 2025
Viewed by 414
Abstract
Background/Objectives: This study aims to investigate the effects of caffeinated chewing gum on maximal strength, muscular power, and neural drive to the prime movers during bench press and back squat in resistance-trained men. Methods: Sixteen resistance-trained males participated in a double-blind, [...] Read more.
Background/Objectives: This study aims to investigate the effects of caffeinated chewing gum on maximal strength, muscular power, and neural drive to the prime movers during bench press and back squat in resistance-trained men. Methods: Sixteen resistance-trained males participated in a double-blind, randomized trial, chewing either caffeinated gum (4 mg/kg) or placebo gum on two separate occasions, seven days apart. After chewing for 5 min, participants performed a maximal strength test followed by muscular power assessments at 25%, 50%, 75%, and 90% of their one-repetition maximum (1RM), completing with 3, 2, 1, and 1 repetition (s), respectively, for bench press and back squat. Surface electromyography data were recorded for each repetition. Results: Caffeinated gum did not significantly improve one-repetition maximum (1RM) for bench press (p > 0.05), but increased mean frequency (MF) and median frequency (MDF) in anterior deltoid, pectoralis major, and biceps brachii (all p < 0.05) compared to placebo. For back squat, 1RM increased with caffeinated gum, along with higher MF and MDF in vastus medialis (all p < 0.05). Caffeinated gum also improved mean and peak velocities, and mean and peak power outputs at 25–75% 1RM during the bench press (all p < 0.05), along with elevated MDF in pectoralis major and biceps brachii (all p < 0.05). Similar improvements were seen in mean and peak velocities during the back squat at 25–90% 1RM (all p < 0.05), along with higher MF and MDF in vastus medialis and increased normalized root mean square activity in gluteus maximus (all p < 0.05). Conclusions: Caffeinated chewing gum (4 mg/kg) enhanced muscular power (25–75% 1RM) in the bench press and improved maximal strength and muscular power (25–90% 1RM) in the back squat by increasing muscle recruitment in resistance-trained men. Full article
(This article belongs to the Special Issue Energy Drink Effectiveness on Human Health and Exercise Performance)
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24 pages, 1540 KiB  
Review
The Search for Disease Modification in Parkinson’s Disease—A Review of the Literature
by Daniel Barber, Tissa Wijeratne, Lakshman Singh, Kevin Barnham and Colin L. Masters
Life 2025, 15(8), 1169; https://doi.org/10.3390/life15081169 - 23 Jul 2025
Viewed by 427
Abstract
Sporadic Parkinson’s Disease (PD) affects 3% of people over 65 years of age. People are living longer, thanks in large part to improvements in global health technology and health access for non-neurological diseases. Consequently, neurological diseases of senescence, such as PD, are representing [...] Read more.
Sporadic Parkinson’s Disease (PD) affects 3% of people over 65 years of age. People are living longer, thanks in large part to improvements in global health technology and health access for non-neurological diseases. Consequently, neurological diseases of senescence, such as PD, are representing an ever-increasing share of global disease burden. There is an intensifying research focus on the processes that underlie these conditions in the hope that neurological decay may be arrested at the earliest time point. The concept of neuronal death linked to ageing- neural senescence- first emerged in the 1800s. By the late 20th century, it was recognized that neurodegeneration was common to all ageing human brains, but in most cases, this process did not lead to clinical disease during life. Conditions such as PD are the result of accelerated neurodegeneration in particular brain foci. In the case of PD, degeneration of the substantia nigra pars compacta (SNpc) is especially implicated. Why neural degeneration accelerates in these particular regions remains a point of contention, though current evidence implicates a complex interplay between a vast array of neuronal cell functions, bioenergetic failure, and a dysfunctional brain immunological response. Their complexity is a considerable barrier to disease modification trials, which seek to intercept these maladaptive cell processes. This paper reviews current evidence in the domain of neurodegeneration in Parkinson’s disease, focusing on alpha-synuclein accumulation and deposition and the role of oxidative stress and inflammation in progressive brain changes. Recent approaches to disease modification are discussed, including the prevention or reversal of alpha-synuclein accumulation and deposition, modification of oxidative stress, alteration of maladaptive innate immune processes and reactive cascades, and regeneration of lost neurons using stem cells and growth factors. The limitations of past research methodologies are interrogated, including the difficulty of recruiting patients in the clinically quiescent prodromal phase of sporadic Parkinson’s disease. Recommendations are provided for future studies seeking to identify novel therapeutics with disease-modifying properties. Full article
(This article belongs to the Section Life Sciences)
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15 pages, 802 KiB  
Article
Differential Cortical Activations Among Young Adults Who Fall Versus Those Who Recover Successfully Following an Unexpected Slip During Walking
by Rudri Purohit, Shuaijie Wang and Tanvi Bhatt
Brain Sci. 2025, 15(7), 765; https://doi.org/10.3390/brainsci15070765 - 18 Jul 2025
Viewed by 281
Abstract
Background: Biomechanical and neuromuscular differences between falls and recoveries have been well-studied; however, the cortical correlations remain unclear. Using mobile brain imaging via electroencephalography (EEG), we examined differences in sensorimotor beta frequencies between falls and recoveries during an unpredicted slip in walking. Methods [...] Read more.
Background: Biomechanical and neuromuscular differences between falls and recoveries have been well-studied; however, the cortical correlations remain unclear. Using mobile brain imaging via electroencephalography (EEG), we examined differences in sensorimotor beta frequencies between falls and recoveries during an unpredicted slip in walking. Methods: We recruited 22 young adults (15 female; 18–35 years) who experienced a slip (65 cm) during walking. Raw EEG signals were band-pass filtered, and independent component analysis was performed to remove non-neural sources, eventually three participants were excluded due to excessive artifacts. Peak beta power was extracted from three time-bins: 400 milliseconds pre-, 0–150 milliseconds post and 150–300 milliseconds post-perturbation from the midline (Cz) electrode. A 2 × 3 Analysis of Covariance assessed the interaction between time-bins and group on beta power, followed by Independent and Paired t-tests for between and within-group post hoc comparisons. Results: All participants (n = 19) experienced a balance loss, seven experienced a fall. There was a time × group interaction on beta power (p < 0.05). With no group differences pre-perturbation, participants who experienced a fall exhibited higher beta power during 0–150 milliseconds post-perturbation than those who recovered (p < 0.001). However, there were no group differences in beta power during 150–300 milliseconds post-perturbation. Conclusions: Young adults exhibiting a greater increase in beta power during the early post-perturbation period experienced a fall, suggesting a higher cortical error detection due to a larger mismatch in the expected and ongoing postural state and greater cortical dependence for sensorimotor processing. Our study results provide an overview of the possible cortical governance to modulate slip-fall/recovery outcomes. Full article
(This article belongs to the Section Behavioral Neuroscience)
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20 pages, 547 KiB  
Article
Fine-Grained Semantics-Enhanced Graph Neural Network Model for Person-Job Fit
by Xia Xue, Jingwen Wang, Bo Ma, Jing Ren, Wujie Zhang, Shuling Gao, Miao Tian, Yue Chang, Chunhong Wang and Hongyu Wang
Entropy 2025, 27(7), 703; https://doi.org/10.3390/e27070703 - 30 Jun 2025
Viewed by 411
Abstract
Online recruitment platforms are transforming talent acquisition paradigms, where a precise person-job fit plays a pivotal role in intelligent recruitment systems. However, current methodologies predominantly rely on coarse-grained semantic analysis, failing to address the textual structural dependencies and noise inherent in resumes and [...] Read more.
Online recruitment platforms are transforming talent acquisition paradigms, where a precise person-job fit plays a pivotal role in intelligent recruitment systems. However, current methodologies predominantly rely on coarse-grained semantic analysis, failing to address the textual structural dependencies and noise inherent in resumes and job descriptions. To bridge this gap, the novel fine-grained semantics-enhanced graph neural network for person-job fit (FSEGNN-PJF) framework is proposed. First, graph topologies are constructed by modeling word co-occurrence relationships through pointwise mutual information and sliding windows, followed by graph attention networks to learn graph structural semantics. Second, to mitigate textual noise and focus on critical features, a differential transformer and self-attention mechanism are introduced to semantically encode resumes and job requirements. Then, a novel fine-grained semantic matching strategy is designed, using the enhanced feature fusion strategy to fuse the semantic features of resumes and job positions. Extensive experiments on real-world recruitment datasets demonstrate the effectiveness and robustness of FSEGNN-PJF. Full article
(This article belongs to the Section Multidisciplinary Applications)
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25 pages, 937 KiB  
Review
T-Cadherin (CDH13) and Non-Coding RNAs: The Crosstalk Between Health and Disease
by Kseniya Rubina, Artem Maier, Polina Klimovich, Veronika Sysoeva, Daniil Romashin, Ekaterina Semina and Vsevolod Tkachuk
Int. J. Mol. Sci. 2025, 26(13), 6127; https://doi.org/10.3390/ijms26136127 - 26 Jun 2025
Viewed by 628
Abstract
T-cadherin (CDH13) is an atypical, glycosyl-phosphatidylinositol-anchored cadherin with functions ranging from axon guidance and vascular patterning to adipokine signaling and cell-fate specification. Originally identified as a homophilic cue for migrating neural crest cells, projecting axons, and growing blood vessels, it later [...] Read more.
T-cadherin (CDH13) is an atypical, glycosyl-phosphatidylinositol-anchored cadherin with functions ranging from axon guidance and vascular patterning to adipokine signaling and cell-fate specification. Originally identified as a homophilic cue for migrating neural crest cells, projecting axons, and growing blood vessels, it later emerged as a dual metabolic receptor for cardioprotective high-molecular-weight adiponectin and atherogenic low-density lipoproteins. We recently showed that mesenchymal stem/stromal cells lacking T-cadherin are predisposed to adipogenesis, underscoring its role in lineage choice. Emerging evidence indicates that CDH13 expression and function are fine-tuned by non-coding RNAs (ncRNAs). MiR-199b-5p, miR-377-3p, miR-23a/27a/24-2, and the miR-142 family directly bind CDH13 3′-UTR or its epigenetic regulators, affecting transcription or accelerating decay. Long non-coding RNAs (lncRNAs), including antisense transcripts CDH13-AS1/AS2, brain-restricted FEDORA, and context-dependent LINC00707 and UPAT, either sponge these miRNAs or recruit DNMT/TET enzymes to the CDH13 promoter. Circular RNAs (circRNAs), i.e.circCDH13 and circ_0000119, can add a third level of complexity by sequestering miRNA repressors or boosting DNMT1. Collectively, this ncRNA circuitry regulates T-cadherin across cardiovascular, metabolic, oncogenic, and neurodegenerative conditions. This review integrates both experimentally validated data and in silico predictions to map the ncRNA-CDH13 crosstalk between health and disease, opening new avenues for biomarker discovery and RNA-based therapeutics. Full article
(This article belongs to the Special Issue Regulation by Non-Coding RNAs 2025)
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27 pages, 903 KiB  
Systematic Review
Neurosustainability: A Scoping Review on the Neuro-Cognitive Bases of Sustainable Decision-Making
by Letizia Richelli, Maria Arioli and Nicola Canessa
Brain Sci. 2025, 15(7), 678; https://doi.org/10.3390/brainsci15070678 - 25 Jun 2025
Viewed by 635
Abstract
As climate change continues to endanger a sustainable global condition, a growing literature investigates how to pursue green practices to fight its effects. Individuals are the essential starting point for such bottom-up attempts, with their attitudes towards sustainability driving pro-environmental behaviors (PEBs). Objectives [...] Read more.
As climate change continues to endanger a sustainable global condition, a growing literature investigates how to pursue green practices to fight its effects. Individuals are the essential starting point for such bottom-up attempts, with their attitudes towards sustainability driving pro-environmental behaviors (PEBs). Objectives: Based on the available relevant literature, this scoping review aims to delve into the processes underlying people’s sustainable decision-making (SDM) associated with PEBs. Methods: A scientific literature search was performed through (a) an active database search and (b) the identification of studies via reference and citation tracking. Results were screened and selected in Rayyan. Results: Included articles (n = 30) heterogeneously reported cognitive and neural aspects of SDM shaping PEBs. These proved to (a) recruit brain areas involved in mentalizing and moral cognition (likely because of their role in processing the interplay between personal and contextual factors rather than moral considerations in themselves); (b) undergo the same modulatory influences shaping other kinds of prosocial/cooperative behaviors; and (c) include brain areas involved in attentional/monitoring and emotional/motivational processes, alongside those consistently associated with decision-making processes. Conclusions: These results help interpret the available evidence on the neuro-cognitive bases of SDM while focusing on potential interventions to foster better practices and mitigate the adverse repercussions of climate change on human and global health. Full article
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12 pages, 2716 KiB  
Article
A Novel Machine Learning Model for the Automated Diagnosis of Nasal Pathology in Canine Patients
by Andreea Istrate, Radu Constantinescu, Lithicka Anandavel, Shraddha Rajeshkumar Tandel, Simon Dye and Charlotte Dye
Animals 2025, 15(12), 1718; https://doi.org/10.3390/ani15121718 - 10 Jun 2025
Viewed by 444
Abstract
Computed tomography (CT) is the imaging method of choice for evaluating the canine nasal cavity, being invaluable in determining disease extent, guiding sampling, and planning treatment. While predictions of pathology type can be made, there is significant overlap between CT changes noted in [...] Read more.
Computed tomography (CT) is the imaging method of choice for evaluating the canine nasal cavity, being invaluable in determining disease extent, guiding sampling, and planning treatment. While predictions of pathology type can be made, there is significant overlap between CT changes noted in neoplastic, inflammatory, and infectious nasal disease. Recent years have seen remarkable advancement in computer-aided detection systems in human medicine, with machine and deep learning techniques being successfully applied for the identification and accurate classification of intranasal pathology. This study aimed to develop a neural network pipeline for differentiating nasal pathology in dogs using CT studies of the head. A total of 80 CT studies were recruited for training and testing purposes. Studies falling into one of the three groups (normal nasal anatomy, fungal rhinitis, and intranasal neoplasia) were manually segmented and used to train a suite of neural networks. Standard accuracy metrics assessed performance during training and testing. The machine learning algorithm showed reasonable accuracy (86%) in classifying the diagnosis from an isolated scan slice but high accuracy (99%) when aggregating over slices taken from a full scan. These results suggest that machine learning programmes can accurately discriminate between intranasal pathologies based on canine computed tomography. Full article
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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 599
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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18 pages, 4366 KiB  
Article
sEMG-Based Gesture Recognition Using Sigimg-GADF-MTF and Multi-Stream Convolutional Neural Network
by Ming Zhang, Leyi Qu, Weibiao Wu, Gujing Han and Wenqiang Zhu
Sensors 2025, 25(11), 3506; https://doi.org/10.3390/s25113506 - 2 Jun 2025
Viewed by 567
Abstract
To comprehensively leverage the temporal, static, and dynamic information features of multi-channel surface electromyography (sEMG) signals for gesture recognition, considering the sensitive temporal characteristics of sEMG signals to action amplitude and muscle recruitment patterns, an sEMG-based gesture recognition algorithm is innovatively proposed using [...] Read more.
To comprehensively leverage the temporal, static, and dynamic information features of multi-channel surface electromyography (sEMG) signals for gesture recognition, considering the sensitive temporal characteristics of sEMG signals to action amplitude and muscle recruitment patterns, an sEMG-based gesture recognition algorithm is innovatively proposed using Sigimg-GADF-MTF and multi-stream convolutional neural network (MSCNN) by introducing the Sigimg, GADF, and MTF data processing methods and combining them with a multi-stream fusion strategy. Firstly, a sliding window is used to rearrange the multi-channel original sEMG signals through channels to generate a two-dimensional image (named Sigimg method). Meanwhile, each channel signal is respectively transformed into two-dimensional subimages using Gram angular difference field (GADF) and Markov transition field (MTF) methods. Then, the GADF and MTF images are obtained using a horizontal stitching method to splice these subimages, respectively. The Sigimg, GADF, and MTF images are used to construct a training and testing dataset, which is then imported into the constructed MSCNN model for experimental testing. The fully connected layer fusion method is utilized for multi-stream feature fusion, and the gesture recognition results are output. Through comparative experiments, an average accuracy of 88.4% is achieved using the Sigimg-GADF-MTF-MSCNN algorithm on the Ninapro DBl dataset, higher than most mainstream models. At the same time, the effectiveness of the proposed algorithm is fully verified through generalization testing of data obtained from the self-developed sEMG signal acquisition platform with an average accuracy of 82.4%. Full article
(This article belongs to the Section Biomedical Sensors)
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28 pages, 5257 KiB  
Article
Comparative Evaluation of Sequential Neural Network (GRU, LSTM, Transformer) Within Siamese Networks for Enhanced Job–Candidate Matching in Applied Recruitment Systems
by Mateusz Łępicki, Tomasz Latkowski, Izabella Antoniuk, Michał Bukowski, Bartosz Świderski, Grzegorz Baranik, Bogusz Nowak, Robert Zakowicz, Łukasz Dobrakowski, Bogdan Act and Jarosław Kurek
Appl. Sci. 2025, 15(11), 5988; https://doi.org/10.3390/app15115988 - 26 May 2025
Viewed by 794
Abstract
Job–candidate matching is pivotal in recruitment, yet traditional manual or keyword-based methods can be laborious and prone to missing qualified candidates. In this study, we introduce the first Siamese framework that systematically contrasts GRU, LSTM, and Transformer sequential heads on top of a [...] Read more.
Job–candidate matching is pivotal in recruitment, yet traditional manual or keyword-based methods can be laborious and prone to missing qualified candidates. In this study, we introduce the first Siamese framework that systematically contrasts GRU, LSTM, and Transformer sequential heads on top of a multilingual Sentence Transformer backbone, which is trained end-to-end with triplet loss on real-world recruitment data. This combination captures both long-range dependencies across document segments and global semantics, representing a substantial advance over approaches that rely solely on static embeddings. We compare the three heads using ranking metrics such as Top-K accuracy and Mean Reciprocal Rank (MRR). The Transformer-based model yields the best overall performance, with an MRR of 0.979 and a Top-100 accuracy of 87.20% on the test set. Visualization of learned embeddings (t-SNE) shows that self-attention more effectively clusters matching texts and separates them from irrelevant ones. These findings underscore the potential of combining multilingual base embeddings with specialized sequential layers to reduce manual screening efforts and improve recruitment efficiency. Full article
(This article belongs to the Special Issue Innovations in Artificial Neural Network Applications)
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17 pages, 913 KiB  
Article
The Individual and Combined Effects of Prenatal Micronutrient Supplementations on Neurobehavioral Developmental Disorders in Preschool Children
by Liwen Ding, Esben Strodl, Maolin Zhang and Weiqing Chen
Children 2025, 12(5), 602; https://doi.org/10.3390/children12050602 - 5 May 2025
Viewed by 735
Abstract
Background: Neurobehavioral developmental disorders significantly affect children’s future well-being and contribute to the global disease burden. While prenatal micronutrient supplementation is crucial for fetal neural development, their individual and combined effects on subsequent neurobehavioral outcomes in childhood remain poorly understood. This study aimed [...] Read more.
Background: Neurobehavioral developmental disorders significantly affect children’s future well-being and contribute to the global disease burden. While prenatal micronutrient supplementation is crucial for fetal neural development, their individual and combined effects on subsequent neurobehavioral outcomes in childhood remain poorly understood. This study aimed to examine the individual and combined effects of prenatal micronutrient supplementation on neurobehavioral developmental disorders in preschool children, and to explore their effects across specific developmental domains. Methods: 15,636 mother-child dyads were recruited from the 2022 children’s survey in Shenzhen, China. Mothers provided information on prenatal supplementation of calcium, folic acid, iron, and multivitamins. Five domains of children’s neurobehavioral functioning were assessed using the Ages and Stages Questionnaire-Third Edition (communication, gross motor, fine motor, problem-solving, and personal-social status). Logistic regression models were used to estimate the effect of micronutrient supplementations on NDDs across crude, adjusted, and full-inclusion models. Combined effects were assessed by multiplicative and additive interactions calculated from crossover analysis. Results: 11.7% of preschool children were identified as at risk for neurobehavioral developmental disorders, with the highest prevalence in the gross motor domain. Prenatal multivitamin supplementation showed a protective effect against neurobehavioral developmental disorders (OR = 0.73, 95% CI = 0.66–0.81). Interaction analysis revealed that the combination of iron and multivitamins further enhanced this protection, with both multiplicative (IOR = 1.26, 95% CI = 1.02–1.57) and additive interactions (RERI = 0.18, 95% CI = 0.02–0.35). The problem-solving domain consistently showed the greatest benefit from the supplementation of these micronutrients individually and in combination. Conclusions: Prenatal multivitamin supplementation reduces the risk of neurobehavioral developmental disorders, especially when combined with iron supplementation. These findings highlight the potential benefits of prenatal co-supplementation strategies to improve neurobehavioral outcomes in offspring. Further studies are recommended to confirm these findings and explore underlying mechanisms. Full article
(This article belongs to the Special Issue Cognitive Development in Children)
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11 pages, 578 KiB  
Article
Abnormal Gyrus Rectus Asymmetry in Alzheimer’s Disease: An MRI-Based Parcellation Method
by Ömür Karaca, Ahmet Arman Kibar, Burcu Aslantekin and Nermin Tepe
Brain Sci. 2025, 15(5), 452; https://doi.org/10.3390/brainsci15050452 - 26 Apr 2025
Viewed by 602
Abstract
Background: The gyrus rectus is a key brain region with neural connections to the entorhinal cortex and hippocampus, both of which are among the earliest areas affected in Alzheimer’s disease (AD). Investigating volumetric differences and asymmetry in this region may provide insights into [...] Read more.
Background: The gyrus rectus is a key brain region with neural connections to the entorhinal cortex and hippocampus, both of which are among the earliest areas affected in Alzheimer’s disease (AD). Investigating volumetric differences and asymmetry in this region may provide insights into disease progression. This study aimed to assess gyrus rectus volume and asymmetry in AD patients using an MRI-based parcellation method. Methods: This cross-sectional volumetric study included 25 cognitively healthy adults and 25 AD patients recruited from the Neurology Clinic of Balıkesir University Hospital. Brain MRI scans were obtained using a 1.5 Tesla MRI scanner. Volumetric measurements were computed using MRIStudio, an atlas-based image analysis program. Group differences in brain volume and asymmetry index were examined, and their correlations with Mini-Mental State Examination (MMSE) scores were evaluated. Results: AD patients exhibited significantly greater rightward volumetric asymmetry of the gyrus rectus volume than healthy controls (p < 0.05). Additionally, a positive correlation was observed between gyrus rectus volume and MMSE scores (p < 0.05). Conclusions: These results suggest that rightward volumetric asymmetry of the gyrus rectus may represent a promising biomarker for tracking the progression of Alzheimer’s disease. Detecting asymmetry in brain structures could improve understanding of AD pathology and aid clinical evaluation. Full article
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21 pages, 1890 KiB  
Article
Musical Expertise Reshapes Cross-Domain Semantic Integration: ERP Evidence from Language and Music Processing
by Xing Wang and Tao Zeng
Brain Sci. 2025, 15(4), 401; https://doi.org/10.3390/brainsci15040401 - 16 Apr 2025
Viewed by 634
Abstract
Background/Objectives: Both language and music are capable of encoding and communicating semantic concepts, suggesting a potential overlap in neurocognitive mechanisms. Moreover, music training not only enhances domain-specific musical processing but also facilitates cross-domain language processing. However, existing research has predominantly focused on Indo-European [...] Read more.
Background/Objectives: Both language and music are capable of encoding and communicating semantic concepts, suggesting a potential overlap in neurocognitive mechanisms. Moreover, music training not only enhances domain-specific musical processing but also facilitates cross-domain language processing. However, existing research has predominantly focused on Indo-European languages, with limited evidence from paratactic languages such as Mandarin Chinese. In addition, the impact of variations in musical expertise on these shared processing mechanisms remains unclear, leaving a critical gap in our understanding of the shared neural bases for semantic processing in language and music. This event-related potential (ERP) study investigated whether Chinese sentences and musical chord sequences share semantic processing mechanisms and how musical expertise modulates these mechanisms. Methods: This study recruited 46 college students (22 musicians and 24 non-musicians). Participants read Chinese sentences presented word-by-word visually, while chord sequences were delivered auditorily, with each word temporally aligned to one chord. Sentences included semantically acceptable or unacceptable classifier–noun pairs and chord sequences ended with in-key or out-of-key chords. Participants were instructed to focus on reading sentences while ignoring the concurrent music. ERP signals were recorded, and time-locked to final words to capture neural dynamics during semantic integration. Results: The behavioral results showed that musicians were influenced by musical regularity when reading (acceptable: F(1, 44) = 25.70, p < 0.001, ηp2 = 0.38; unacceptable: F(1, 44) = 11.45, p = 0.002, ηp2 = 0.21), but such effect was absent in non-musicians (ps > 0.05). ERP results showed that musical semantic processing had a substantial impact on both P200 (F(1, 44) = 9.95, p = 0.003, ηp2 = 0.18), N400 (musicians: F(1, 44) = 15.80, p < 0.001, ηp2 = 0.26; non-musicians: F(1, 44) = 4.34, p = 0.043, ηp2 = 0.09), and P600 (musicians: F(1, 44) = 5.55, p = 0.023, ηp2 = 0.11; non-musicians: F(1, 44) = 8.68, p = 0.005, ηp2 = 0.17) components. Furthermore, musical expertise exerted modulatory effects during later stages, as evidenced by divergent N400 and P600 latency patterns between musicians and non-musicians. Specifically, ERP amplitudes exhibited opposing trends: musicians showed an enhanced N400 and diminished P600, while non-musicians displayed a weaker N400 and stronger P600. Conclusions: Our findings provide novel evidence that Mandarin Chinese and chord sequences engage partially overlapping neural mechanisms for semantic processing both in the early (P200) and the late (N400 and P600) stages. Crucially, this study is the first to demonstrate that musical expertise may gradually reorganize these shared mechanisms, enabling two initially independent but functionally analogous semantic mechanisms into a domain-general processing system. These insights deepen our understanding of the neurocognitive mechanisms underlying linguistic and musical semantic processing and highlight how expertise shapes the neural architecture of cross-domain mechanisms. Full article
(This article belongs to the Section Neurolinguistics)
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29 pages, 1918 KiB  
Study Protocol
Rehabilitation with and Without Robot and Allied Digital Technologies (RADTs) in Stroke Patients: A Study Protocol for a Multicentre Randomised Controlled Trial on the Effectiveness, Acceptability, Usability, and Economic-Organisational Sustainability of RADTs from Subacute to Chronic Phase (STROKEFIT4)
by Irene Giovanna Aprile, Marco Germanotta, Alessio Fasano, Mariacristina Siotto, Maria Cristina Mauro, Arianna Pavan, Giovanna Nicora, Giuseppina Sgandurra, Alberto Malovini, Letizia Oreni, Nevio Dubbini, Enea Parimbelli, Giovanni Comandè, Christian Lunetta, Pietro Fiore, Roberto De Icco, Carlo Trompetto, Leopoldo Trieste, Giuseppe Turchetti, Silvana Quaglini and Cristina Messaadd Show full author list remove Hide full author list
J. Clin. Med. 2025, 14(8), 2692; https://doi.org/10.3390/jcm14082692 - 15 Apr 2025
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Abstract
Background: Rehabilitation after stroke often employs Robots and Allied Digital Technologies (RADTs). However, evidence of their effectiveness remains inconclusive due to study heterogeneity and limited sample sizes. Methods: This is a protocol of a pragmatic multicentre, multimodal, randomised, controlled, parallel-group (1:1) [...] Read more.
Background: Rehabilitation after stroke often employs Robots and Allied Digital Technologies (RADTs). However, evidence of their effectiveness remains inconclusive due to study heterogeneity and limited sample sizes. Methods: This is a protocol of a pragmatic multicentre, multimodal, randomised, controlled, parallel-group (1:1) interventional study with blinded assessors aimed at assessing the effectiveness and sustainability of RADT-mediated rehabilitation compared to traditional rehabilitation. The trial will recruit 596 adult subacute post-stroke patients. Participants will be randomised into either the experimental group (using RADTs and two therapists supervising four to six patients) or the control group (individual traditional rehabilitation). Patients in both groups will undergo a comprehensive rehabilitation treatment, targeting (a) upper limb sensorimotor abilities; (b) lower limb sensorimotor abilities and gait; (c) balance; and (d) cognitive abilities. Patients will undergo 25 sessions, each lasting 45 min, with a frequency of 5 (inpatients) or 3 (outpatients) times a week. The primary endpoint is the non-inferiority of RADTs in the recovery of the activities of daily living (ADL) using the modified Barthel Index. If non-inferiority is established, the study will evaluate the superiority. Secondary endpoints will analyse the improvements in the aforementioned domains, as well as changes in neural plasticity and biochemical aspects. Upper limb dexterity and gait recovery rates during treatment will be monitored. The study will also evaluate ADL and quality of life during a six-month follow-up period. Acceptability and usability of integrated RADTs-based rehabilitation for patients, families, and healthcare providers, along with economic and organisational sustainability for patients, payers, and society, will also be assessed. Conclusions: This study aims to establish stronger evidence on the effectiveness of RADTs in post-stroke patients. Trial registration number: NCT06547827. Full article
(This article belongs to the Section Clinical Neurology)
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