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Brain Sci., Volume 14, Issue 8 (August 2024) – 112 articles

Cover Story (view full-size image): The distinct clinical and radiological characteristics of right temporal variant FTD have only been recently recognized. Methods: Eight patients with right temporal variant FTD were prospectively recruited and underwent a standardized neuropsychological assessment, clinical MRI, and quantitative neuroimaging. Results: Our voxel-wise gray analyses captured bilateral anterior and mesial temporal gray matter atrophy with a clear right-sided predominance. Bilateral hippocampal involvement was also observed, as well as disease burden in the right insular and opercula regions. White matter integrity alterations were also bilateral in anterior temporal and sub-insular regions with a clear right-hemispheric predominance. Extra-temporal white matter alterations have also been observed in orbitofrontal and parietal regions. View this paper
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17 pages, 5367 KiB  
Article
Detection of Anxiety-Based Epileptic Seizures in EEG Signals Using Fuzzy Features and Parrot Optimization-Tuned LSTM
by Kamini Kamakshi Palanisamy and Arthi Rengaraj
Brain Sci. 2024, 14(8), 848; https://doi.org/10.3390/brainsci14080848 - 22 Aug 2024
Viewed by 886
Abstract
In humans, epilepsy is diagnosed through electroencephalography (EEG) signals. Epileptic seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging for radiologists, and there is a limited availability of anxiety-based EEG signals. Data augmentation methods are required to increase the [...] Read more.
In humans, epilepsy is diagnosed through electroencephalography (EEG) signals. Epileptic seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging for radiologists, and there is a limited availability of anxiety-based EEG signals. Data augmentation methods are required to increase the number of novel samples. An epileptic seizure arises due to anxiety, which manifests as variations in EEG signal patterns consisting of changes in the size and shape of the signal. In this study, anxiety EEG signals were synthesized by applying data augmentation methods such as random data augmentation (RDA) to existing epileptic seizure signals from the Bonn EEG dataset. The data-augmented anxiety seizure signals were processed using three algorithms—(i) fuzzy C-means–particle swarm optimization–long short-term memory (FCM-PS-LSTM), (ii) particle swarm optimization–long short-term memory (PS-LSTM), and (iii) parrot optimization LSTM (PO-LSTM)—for the detection of anxiety ESs via EEG signals. The predicted accuracies of detecting ESs through EEG signals using the proposed algorithms—namely, (i) FCM-PS-LSTM, (ii) PS-LSTM, and (iii) PO-LSTM—were about 98%, 98.5%, and 96%, respectively. Full article
(This article belongs to the Section Neurotechnology and Neuroimaging)
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12 pages, 1338 KiB  
Article
Flow Diversion for Cerebral Aneurysms: A Decade-Long Experience with Improved Outcomes and Predictors of Success
by Tae Keun Jee, Je Young Yeon, Keon Ha Kim, Jong-Soo Kim and Pyoung Jeon
Brain Sci. 2024, 14(8), 847; https://doi.org/10.3390/brainsci14080847 - 22 Aug 2024
Viewed by 709
Abstract
Background: Flow diversion has significantly improved the management of cerebral aneurysms. Technological advancements and increased clinical experience over the past decade have led to better outcomes and fewer complications. This study provides updated results and examines the factors that influence the success of [...] Read more.
Background: Flow diversion has significantly improved the management of cerebral aneurysms. Technological advancements and increased clinical experience over the past decade have led to better outcomes and fewer complications. This study provides updated results and examines the factors that influence the success of flow diversion. Methods: We reviewed records of 115 patients with 121 intracranial aneurysms treated from July 2014 to August 2023. All patients had unruptured aneurysms in the anterior and posterior circulation. Results: Complete aneurysm occlusion was achieved in 72.7% of cases, with a complication rate of 9.1%. Significant predictors of complete occlusion included aneurysm diameter (OR = 0.89, 95% CI 0.82–0.97, p = 0.009) and the presence of incorporated branches (OR = 0.22, 95% CI 0.08–0.59, p = 0.003). Cox analysis identified neck diameter (HR = 0.92, 95% CI 0.87–0.98, p = 0.009) and incorporated branch (HR = 0.40, 95% CI 0.24–0.69, p = 0.001) as significant for occlusion. Multivariable analysis identified aneurysm diameter (OR = 1.21, 95% CI 1.09–1.37, p = 0.001) as significant for safety outcomes. Improved outcomes were observed in recent treatments, with higher occlusion rates (79.7% vs. 61.7%, p = 0.050) and lower complication rates (4.1% vs. 14.9%, p = 0.011). Conclusions: Enhanced technical proficiency, better devices, and refined patient selection have significantly improved the efficacy and safety of flow diversion for cerebral aneurysms. Identifying significant predictors for treatment success and safety outcomes can inform clinical practice, aiding in patient selection. Full article
(This article belongs to the Special Issue Advanced Clinical Technologies in Treating Neurosurgical Diseases)
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16 pages, 664 KiB  
Article
Evaluation of Different Visual Feedback Methods for Brain—Computer Interfaces (BCI) Based on Code-Modulated Visual Evoked Potentials (cVEP)
by Milán András Fodor, Hannah Herschel, Atilla Cantürk, Gernot Heisenberg and Ivan Volosyak
Brain Sci. 2024, 14(8), 846; https://doi.org/10.3390/brainsci14080846 - 22 Aug 2024
Viewed by 786
Abstract
Brain–computer interfaces (BCIs) enable direct communication between the brain and external devices using electroencephalography (EEG) signals. BCIs based on code-modulated visual evoked potentials (cVEPs) are based on visual stimuli, thus appropriate visual feedback on the interface is crucial for an effective BCI system. [...] Read more.
Brain–computer interfaces (BCIs) enable direct communication between the brain and external devices using electroencephalography (EEG) signals. BCIs based on code-modulated visual evoked potentials (cVEPs) are based on visual stimuli, thus appropriate visual feedback on the interface is crucial for an effective BCI system. Many previous studies have demonstrated that implementing visual feedback can improve information transfer rate (ITR) and reduce fatigue. This research compares a dynamic interface, where target boxes change their sizes based on detection certainty, with a threshold bar interface in a three-step cVEP speller. In this study, we found that both interfaces perform well, with slight variations in accuracy, ITR, and output characters per minute (OCM). Notably, some participants showed significant performance improvements with the dynamic interface and found it less distracting compared to the threshold bars. These results suggest that while average performance metrics are similar, the dynamic interface can provide significant benefits for certain users. This study underscores the potential for personalized interface choices to enhance BCI user experience and performance. By improving user friendliness, performance, and reducing distraction, dynamic visual feedback could optimize BCI technology for a broader range of users. Full article
(This article belongs to the Section Computational Neuroscience and Neuroinformatics)
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14 pages, 1753 KiB  
Article
Functional Network Connectivity for Components of Depression-Related Psychological Fragility
by Ian D. Evans, Christopher F. Sharpley, Vicki Bitsika, Kirstan A. Vessey, Emmanuel Jesulola and Linda L. Agnew
Brain Sci. 2024, 14(8), 845; https://doi.org/10.3390/brainsci14080845 - 22 Aug 2024
Viewed by 769
Abstract
Psychological resilience (PR) is known to be inversely associated with depression. While there is a growing body of research examining how depression alters activity across multiple functional neural networks, how differences in PR affect these networks is largely unexplored. This study examines the [...] Read more.
Psychological resilience (PR) is known to be inversely associated with depression. While there is a growing body of research examining how depression alters activity across multiple functional neural networks, how differences in PR affect these networks is largely unexplored. This study examines the relationship between PR and functional connectivity in the alpha and beta bands within (and between) eighteen established cortical nodes in the default mode network, the central executive network, and the salience network. Resting-state EEG data from 99 adult participants (32 depressed, 67 non-depressed) were used to measure the correlation between the five factors of PR sourced from the Connor–Davidson Resilience Scale and eLORETA-based measures of coherence and phase synchronisation. Distinct functional connectivity patterns were seen across each resilience factor, with a notable absence of overlapping positive results across the depressed and non-depressed samples. These results indicate that depression may modulate how resilience is expressed in terms of fundamental neural activity. Full article
(This article belongs to the Section Psychiatric Diseases)
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12 pages, 250 KiB  
Article
The Association between Attention-Deficit–Hyperactivity Disorder and Autistic Traits with Psychotic-like Experiences in Sample of Youths Who Were Referred to a Psychiatric Outpatient Service
by Laura Fusar-Poli, Chiara Avanzato, Giuliana Maccarone, Elide Di Martino, Gabriele Avincola, Stefania Grasso, Giovanni Rapisarda, Francesco Guarnieri and Maria Salvina Signorelli
Brain Sci. 2024, 14(8), 844; https://doi.org/10.3390/brainsci14080844 - 22 Aug 2024
Viewed by 924
Abstract
The aim of this study is to identify autism spectrum disorder (ASD) and attention-deficit–hyperactivity disorder (ADHD) traits in adolescents who experience psychotic-like experiences (PLEs), often ignored in clinical practice but widely prevalent in the general population. A total of 57 adolescents and young [...] Read more.
The aim of this study is to identify autism spectrum disorder (ASD) and attention-deficit–hyperactivity disorder (ADHD) traits in adolescents who experience psychotic-like experiences (PLEs), often ignored in clinical practice but widely prevalent in the general population. A total of 57 adolescents and young adults (aged between 16 and 24 years old) were recruited consecutively in the outpatient services. A total of 37 were females (64.9%), 18 were males (31.6%), and two participants (3.5%) were non-binary or gender non-conforming, with a mean age at referral of 18.26 ± 2.06. To investigate these symptoms, three sets of standardized questionnaires were used, as follows: the Autism Spectrum Quotient–short form (AQ-10), the Community Assessment of Psychic Experiences (CAPE-42), and the Adult ADHD Self-Report Scale (ASRS). We found significant associations between the ASRS and AQ-10 total scores and all CAPE scales. The model which explained the highest variance was CAPE Score’s Total Frequency score (p < 0.001). Our findings underline the importance of investigating the presence of subthreshold ASD and ADHD symptoms in clinical populations, particularly in the period of adolescence and young adulthood, to promptly identify the presence of PLEs and, thus, prevent the onset of a frank psychotic disorder, particularly in the presence of a comorbid psychopathological condition, leading to better diagnosis and treatment for individuals with two or more of these conditions. Full article
(This article belongs to the Special Issue Exploring the Mental Health of People with Autism)
7 pages, 666 KiB  
Brief Report
Effects of Electroencephalogram Neurofeedback Intervention on Blood C-Reactive Protein Levels in Astronauts Attending 2-Week Long Analog Moon Mission
by Jakub Hinca and Marcin Dornowski
Brain Sci. 2024, 14(8), 843; https://doi.org/10.3390/brainsci14080843 - 22 Aug 2024
Viewed by 647
Abstract
The human organism is affected by multiple stressors every single day, especially during extremely demanding activities. It needs a method to regulate itself better. One of the stressors that is affecting humans is social isolation. The state of prolonged isolation happens during space [...] Read more.
The human organism is affected by multiple stressors every single day, especially during extremely demanding activities. It needs a method to regulate itself better. One of the stressors that is affecting humans is social isolation. The state of prolonged isolation happens during space missions. In this study, 40 analog astronauts attended a two-week-long mission. The experimental group had EEG neurofeedback training intervention performed on a daily basis, while the control group remained isolated without neurofeedback. The results let us take this non-invasive intervention under consideration, while debating the methods to lower the physiological stress reaction in humans that are exposed to extremely hard circumstances. Although not statistically significant, the trends observed give us direction towards other research to confirm EEG neurofeedback as a method to lower cell stress response levels. Full article
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25 pages, 803 KiB  
Review
Cognitive Stimulation with Music in Older Adults with Cognitive Impairment: A Scoping Review
by Alfredo Raglio, Camilla Figini, Alice Bencivenni, Federica Grossi, Federica Boschetti and Marina Rita Manera
Brain Sci. 2024, 14(8), 842; https://doi.org/10.3390/brainsci14080842 - 22 Aug 2024
Viewed by 1385
Abstract
Background: The use of music in cognitive interventions represents a possibility with potential worthy of further investigation in the field of aging, both in terms of prevention from dementia, in the phase of mild cognitive impairment, and in the treatment of overt dementia. [...] Read more.
Background: The use of music in cognitive interventions represents a possibility with potential worthy of further investigation in the field of aging, both in terms of prevention from dementia, in the phase of mild cognitive impairment, and in the treatment of overt dementia. Objectives: Currently, the types of music-based interventions proposed in the literature are characterized by wide heterogeneity, which is why it is necessary to clarify which interventions present more evidence of effectiveness in stimulating different cognitive domains. Method: The study was conducted in accordance with PRISMA guidelines for scoping reviews. By searching two different databases, PubMed and the Web of Science, all studies evaluating the cognitive effects of music-based interventions on people at early stages of cognitive decline (MCI or mild-to-moderate dementia) were selected. Results: The study selection included a total of 28 studies involving n = 1612 participants (mean age ranged from 69.45 to 85.3 years old). Most of the studies analyzed agree with the observation of an improvement, or at least maintenance, of global cognitive conditions (mainly represented by the results of the MMSE test) following music-based interventions, together with a series of other positive effects on verbal fluency, memory, and executive processes. Conclusions: The results of this review suggest the introduction of music-based interventions as complementary approaches to usual cognitive treatments. Also, the use of standardized and well-defined protocols, in addition to strong methodological research approaches, is suggested. Music-based interventions are recommended in the early stages of dementia, in MCI, and in a preventive sense in healthy older adults. Full article
(This article belongs to the Special Issue New Insights into Cognitive and Behavioral Neurology)
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11 pages, 279 KiB  
Perspective
The Absence of Items Addressing Increased Appetite or Weight in Depressive-Symptom Questionnaires: Implications for Understanding the Link between Major Depressive Disorder, Antidepressants, and Obesity
by Andrés M. Treviño-Alvarez, Marci E. Gluck, Susan L. McElroy and Alfredo B. Cuellar-Barboza
Brain Sci. 2024, 14(8), 841; https://doi.org/10.3390/brainsci14080841 - 21 Aug 2024
Viewed by 1439
Abstract
Major depressive disorder (MDD) and obesity have a complex bidirectional relationship. However, most studies do not assess increased appetite or weight as a depressive symptom due to limitations in rating scales. Here we aimed to analyze frequently employed depressive-symptom scales and discuss the [...] Read more.
Major depressive disorder (MDD) and obesity have a complex bidirectional relationship. However, most studies do not assess increased appetite or weight as a depressive symptom due to limitations in rating scales. Here we aimed to analyze frequently employed depressive-symptom scales and discuss the relevance of weight and appetite assessment items. To elaborate this perspective, we searched for validated questionnaires and scales evaluating depressive symptoms in English. We analyzed appetite and weight items from 20 depressive-symptoms rating scales. Only 8 of 20 rating scales assessed for increased weight or appetite. The scales reported in the literature as the most employed in antidepressants efficacy trials do not assess increased appetite or weight. The current use of rating scales limits our understanding of the relationship between MDD, antidepressants, and obesity. It is necessary to improve our weight and appetite measurements in MDD to clarify the respective impact of depressive symptoms and antidepressants on weight change. Full article
(This article belongs to the Special Issue Clinical Research on Mood Disorders: Opportunities and Challenges)
17 pages, 1564 KiB  
Article
Decline in Sensory Integration in Old Age and Its Related Functional Brain Connectivity Correlates Observed during a Virtual Reality Task
by Satoru Inagaki, Hirokazu Matsuura, Kazuki Sakurai, Ludovico Minati and Natsue Yoshimura
Brain Sci. 2024, 14(8), 840; https://doi.org/10.3390/brainsci14080840 - 21 Aug 2024
Viewed by 781
Abstract
Sensory integration is an essential human function whose decline impacts quality of life, particularly in older adults. Herein, we propose an arm-reaching task based on a virtual reality head-mounted display system to assess sensory integration in daily life, and we examined whether reaching [...] Read more.
Sensory integration is an essential human function whose decline impacts quality of life, particularly in older adults. Herein, we propose an arm-reaching task based on a virtual reality head-mounted display system to assess sensory integration in daily life, and we examined whether reaching task performance was associated with resting-state functional connectivity (rsFC) between the brain regions involved in sensory integration. We hypothesized that declining sensory integration would affect performance during a reaching task with multiple cognitive loads. Using a task in which a young/middle-aged group showed only small individual differences, older adults showed large individual differences in the gap angle between the reaching hand and the target position, which was used to assess sensory integration function. Additionally, rsfMRI data were used to identify correlations between rsFC and performance in older adults, showing that performance was correlated with connectivity between the primary motor area and the left inferior temporal gyrus and temporo-occipital region. Connectivity between areas is related to visuomotor integration; thus, the results suggest the involvement of visuomotor integration in the decline of sensory integration function and the validity of the gap angle during this VR reaching task as an index of functional decline. Full article
(This article belongs to the Section Sensory and Motor Neuroscience)
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15 pages, 3476 KiB  
Article
EEG-Based Seizure Prediction Using Hybrid DenseNet–ViT Network with Attention Fusion
by Shasha Yuan, Kuiting Yan, Shihan Wang, Jin-Xing Liu and Juan Wang
Brain Sci. 2024, 14(8), 839; https://doi.org/10.3390/brainsci14080839 - 21 Aug 2024
Viewed by 1020
Abstract
Epilepsy seizure prediction is vital for enhancing the quality of life for individuals with epilepsy. In this study, we introduce a novel hybrid deep learning architecture, merging DenseNet and Vision Transformer (ViT) with an attention fusion layer for seizure prediction. DenseNet captures hierarchical [...] Read more.
Epilepsy seizure prediction is vital for enhancing the quality of life for individuals with epilepsy. In this study, we introduce a novel hybrid deep learning architecture, merging DenseNet and Vision Transformer (ViT) with an attention fusion layer for seizure prediction. DenseNet captures hierarchical features and ensures efficient parameter usage, while ViT offers self-attention mechanisms and global feature representation. The attention fusion layer effectively amalgamates features from both networks, guaranteeing the most relevant information is harnessed for seizure prediction. The raw EEG signals were preprocessed using the short-time Fourier transform (STFT) to implement time–frequency analysis and convert EEG signals into time–frequency matrices. Then, they were fed into the proposed hybrid DenseNet–ViT network model to achieve end-to-end seizure prediction. The CHB-MIT dataset, including data from 24 patients, was used for evaluation and the leave-one-out cross-validation method was utilized to evaluate the performance of the proposed model. Our results demonstrate superior performance in seizure prediction, exhibiting high accuracy and low redundancy, which suggests that combining DenseNet, ViT, and the attention mechanism can significantly enhance prediction capabilities and facilitate more precise therapeutic interventions. Full article
(This article belongs to the Section Computational Neuroscience and Neuroinformatics)
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12 pages, 1900 KiB  
Article
Spontaneously Hypertensive Rats Present Exacerbated Focal Stroke Behavioral Outcomes
by João Victor Matos e Moreira, Luis Pedro Bernardi, Fernanda Cardoso Teixeira, Jerônimo Paniago, Luciele Varaschini Teixeira, Felippo Bifi, Diogo Onofre Souza and Francieli Rohden
Brain Sci. 2024, 14(8), 838; https://doi.org/10.3390/brainsci14080838 - 21 Aug 2024
Viewed by 611
Abstract
This study aimed to analyze the effects of systemic arterial hypertension (SAH) in a model of permanent ischemic stroke (focal ischemia due to thermocoagulation of pial vessels) on sensorimotor function (cylinder test and patch removal test), behavioral tasks (novelty habituation memory open field [...] Read more.
This study aimed to analyze the effects of systemic arterial hypertension (SAH) in a model of permanent ischemic stroke (focal ischemia due to thermocoagulation of pial vessels) on sensorimotor function (cylinder test and patch removal test), behavioral tasks (novelty habituation memory open field task) and cerebral infarct size in adult male spontaneously hypertensive rats (SHR) and normotensive Wistar Kyoto rats (WKY) for 42 days after the occurrence of a stroke. We observed that the stroke caused asymmetry in the front paws and delayed adhesive removal. These effects were spontaneously reduced in WKY rats, but not in SHR. Short- and long-term novelty habituation memories were abolished by stroke in WYK and SHR. On the 3rd day after stroke, the size of the focal cerebral infarct was the same in WKY and SHR. However, on the 7th day, the infarct size decreased in WKY rats, but not SHR. These results suggested that SAH impairment of sensorimotor recovery in rats subjected to cerebral ischemia could be related to augmented focal cerebral infarct size. Moreover, the behavioral tasks used in this study were unaffected by Systemic Arterial Hypertension. Our results highlight the need for animal models of comorbidities in stroke research. Full article
(This article belongs to the Section Behavioral Neuroscience)
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34 pages, 1134 KiB  
Review
From Infancy to Childhood: A Comprehensive Review of Event- and Task-Related Brain Oscillations
by Esra Ünsal, Rümeysa Duygun, İrem Yemeniciler, Elifnur Bingöl, Ömer Ceran and Bahar Güntekin
Brain Sci. 2024, 14(8), 837; https://doi.org/10.3390/brainsci14080837 - 20 Aug 2024
Viewed by 2418
Abstract
Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, [...] Read more.
Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications. Full article
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17 pages, 1193 KiB  
Article
An Intrinsically Explainable Method to Decode P300 Waveforms from EEG Signal Plots Based on Convolutional Neural Networks
by Brian Ezequiel Ail, Rodrigo Ramele, Juliana Gambini and Juan Miguel Santos
Brain Sci. 2024, 14(8), 836; https://doi.org/10.3390/brainsci14080836 - 20 Aug 2024
Viewed by 1223
Abstract
This work proposes an intrinsically explainable, straightforward method to decode P300 waveforms from electroencephalography (EEG) signals, overcoming the black box nature of deep learning techniques. The proposed method allows convolutional neural networks to decode information from images, an area where they have achieved [...] Read more.
This work proposes an intrinsically explainable, straightforward method to decode P300 waveforms from electroencephalography (EEG) signals, overcoming the black box nature of deep learning techniques. The proposed method allows convolutional neural networks to decode information from images, an area where they have achieved astonishing performance. By plotting the EEG signal as an image, it can be both visually interpreted by physicians and technicians and detected by the network, offering a straightforward way of explaining the decision. The identification of this pattern is used to implement a P300-based speller device, which can serve as an alternative communication channel for persons affected by amyotrophic lateral sclerosis (ALS). This method is validated by identifying this signal by performing a brain–computer interface simulation on a public dataset from ALS patients. Letter identification rates from the speller on the dataset show that this method can identify the P300 signature on the set of 8 patients. The proposed approach achieves similar performance to other state-of-the-art proposals while providing clinically relevant explainability (XAI). Full article
(This article belongs to the Special Issue Emerging Topics in Brain-Computer Interface)
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10 pages, 2184 KiB  
Case Report
Characteristics of Intracranial Kinetic Loads When Sports-Related Concussion Occurs in Men’s Rhythmic Gymnastics
by Shunya Otsubo, Yutaka Shigemori, Sena Endo, Hiroshi Fukushima, Muneyuki Tachihara, Kyosuke Goto, Rino Tsurusaki, Nana Otsuka, Kentaro Masuda and Yuelin Zhang
Brain Sci. 2024, 14(8), 835; https://doi.org/10.3390/brainsci14080835 - 20 Aug 2024
Viewed by 729
Abstract
This study aimed to clarify the differences between the previously reported mechanisms of sports-related concussion (SRC) injuries without a loss of consciousness in contact and collision sports and the mechanisms of SRC injuries in our cases. Based on two videos of SRC injuries [...] Read more.
This study aimed to clarify the differences between the previously reported mechanisms of sports-related concussion (SRC) injuries without a loss of consciousness in contact and collision sports and the mechanisms of SRC injuries in our cases. Based on two videos of SRC injuries occurring during a men’s rhythmic gymnastics competition (three people were injured), the risk of SRC occurrence was estimated from various parameters using a multibody analysis and eight brain injury evaluation criteria. In the present study, the three SRC impacts that occurred in men’s rhythmic gymnastics showed significant characteristics in duration compared to previously reported cases in the contact sports. This suggests that the occurrence of SRC may have been caused by a different type of impact from that which causes SRC in contact sports (e.g., tackling). In addition, calculation of the strain indicating the rate of brain deformation suggested a risk of nerve swelling in all cases involving type 2 axonal injuries. Therefore, when reexamining sports-related head injuries, it is important to recognize the characteristics and mechanisms of SRC that occur in each different sport, as well as the symptoms and course of SRC after injury. Full article
(This article belongs to the Section Neurosurgery and Neuroanatomy)
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25 pages, 4163 KiB  
Systematic Review
The Effectiveness of Overground Robot Exoskeleton Gait Training on Gait Outcomes, Balance, and Motor Function in Patients with Stroke: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
by Myoung-Ho Lee, Ming-Yu Tian and Myoung-Kwon Kim
Brain Sci. 2024, 14(8), 834; https://doi.org/10.3390/brainsci14080834 - 19 Aug 2024
Viewed by 1063
Abstract
Objective: This study aimed to investigate the effects of overground robot exoskeleton gait training on gait outcomes, balance, and motor function in patients with stroke. Methods: Following the PRISMA guidelines, literature searches were performed in the PubMed, EMBASE, Cochrane Central Register of Controlled [...] Read more.
Objective: This study aimed to investigate the effects of overground robot exoskeleton gait training on gait outcomes, balance, and motor function in patients with stroke. Methods: Following the PRISMA guidelines, literature searches were performed in the PubMed, EMBASE, Cochrane Central Register of Controlled Trials, SCOPUS, Ovid-LWW, and RISS databases. A total of 504 articles were identified, of which 19 were included for analysis after application of the inclusion and exclusion criteria. The included literature was qualitatively evaluated using the PEDro scale, while the Egger’s regression, funnel plot, and trim-and-fill methods were applied to assess and adjust for publication bias. Results: The averaged PEDro score was 6.21 points, indicating a high level of methodological quality. In the analysis based on dependent variables, higher effect sizes were observed in the following ascending order: gait speed (g = 0.26), motor function (g = 0.21), gait ability (g = 0.18), Timed Up and Go Test (g = −0.15), gait endurance (g = 0.11), and Berg Balance Scale (g = 0.05). Subgroup analyses further revealed significant differences in Asian populations (g = 0.26), sessions lasting longer than 30 min (g = 0.37), training frequency of three times per week or less (g = 0.38), and training duration of four weeks or less (g = 0.25). Overall, the results of this study indicate that overground robot exoskeleton gait training is effective at improving gait speed in patients with stroke, particularly when the sessions exceed 30 min, are conducted three times or less per week, and last for four weeks or less. Conclusion: our results suggest that training is an effective intervention for patients with stroke, provided that appropriate goal-setting and intensity and overground robot exoskeleton gait are applied. Full article
(This article belongs to the Section Neurorehabilitation)
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18 pages, 4625 KiB  
Article
Genetically Predicted Association of 91 Circulating Inflammatory Proteins with Multiple Sclerosis: A Mendelian Randomization Study
by Xin’ai Li, Zhiguo Ding, Shuo Qi, Peng Wang, Junhui Wang and Jingwei Zhou
Brain Sci. 2024, 14(8), 833; https://doi.org/10.3390/brainsci14080833 - 19 Aug 2024
Viewed by 909
Abstract
Previous studies have validated a close association between inflammatory factors and multiple sclerosis (MS), but their causal relationship is not fully profiled yet. This study used Mendelian randomization (MR) to investigate the causal effect of circulating inflammatory proteins on MS. Data from a [...] Read more.
Previous studies have validated a close association between inflammatory factors and multiple sclerosis (MS), but their causal relationship is not fully profiled yet. This study used Mendelian randomization (MR) to investigate the causal effect of circulating inflammatory proteins on MS. Data from a large-scale genome-wide association study (GWAS) were analyzed using a two-sample MR method to explore the relationship between 91 circulating inflammatory proteins and MS. The inverse-variance-weighted (IVW) analysis was employed as the main method for evaluating exposures and outcomes. Furthermore, series of the methods of MR Egger, weighted median, simple mode, and weighted mode were used to fortify the final results. The results of the IVW method were corrected with Bonferroni (bon) and false discovery rate (fdr) for validating the robustness of results and ensuring the absence of heterogeneity and horizontal pleiotropy. The sensitivity analysis was also performed. The results of the forward MR analysis showed that higher levels of CCL25 were found to be associated with an increased risk of MS according to IVW results, OR: 1.085, 95% CI (1.011, 1.165), p = 2.42 × 10−2, adjusted p_adj_bon = 1, p_adj_fdr = 0.307. Similarly, higher levels of CXCL10 were found to be associated with an increased risk of MS, OR: 1.231, 95% CI (1.057, 1.433), p = 7.49 × 10−3, adjusted p_adj_bon = 0.682, p_adj_fdr = 0.227. In contrast, elevated levels of neurturin (NRTN) were associated with a decreased risk of MS, OR: 0.815, 95% CI (0.689, 0.964), p = 1.68 × 10−2, adjusted p_adj_bon = 1, p_adj_fdr = 0.307. Reverse MR analysis showed no causal relationship between MS and the identified circulating inflammatory cytokines. The effects of heterogeneity and level pleiotropy were further excluded by sensitivity analysis. This study provides new insights into the relationship between circulating inflammatory proteins and MS and brings up a new possibility of using these cytokines as potential biomarkers and therapeutic targets. The data in this study show that there are only weak associations between inflammatory molecules and MS risk, which did not survive bon and fdr correction, and the obtained p-values are quite low. Therefore, further studies on larger samples are needed. Full article
(This article belongs to the Special Issue Advances in Neuroinflammation)
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16 pages, 3993 KiB  
Article
The Role of Interoceptive Sensitivity and Hypnotizability in Motor Imagery
by Eleonora Malloggi, Žan Zelič and Enrica Laura Santarcangelo
Brain Sci. 2024, 14(8), 832; https://doi.org/10.3390/brainsci14080832 - 19 Aug 2024
Viewed by 907
Abstract
Motor imagery (MI) requires the mental representation of the body, obtained by integrating exteroceptive and interoceptive information. This study aimed to investigate the role of interoceptive sensitivity (IS) in MI performed through visual and kinesthetic modalities by participants with low (lows, N = [...] Read more.
Motor imagery (MI) requires the mental representation of the body, obtained by integrating exteroceptive and interoceptive information. This study aimed to investigate the role of interoceptive sensitivity (IS) in MI performed through visual and kinesthetic modalities by participants with low (lows, N = 26; SHSS: A, M + SD: 1.00 + 1.52), medium (mediums, N = 11; SHSS: A, 6.00 + 0.77) and high hypnotizability scores (highs, N = 16; SHSS:A, 9.75 + 1.24), as measured by the Stanford Hypnotic Susceptibility Scale: Form A. The three groups displayed different MI abilities and IS levels. The efficacy of MI was measured using the chronometric index and self-reported experience, while IS was measured using the Multidimensional Assessment of Interoceptive Awareness (MAIA) questionnaire. Alpha and beta power spectrum densities (PSDs) were extracted from the EEG signals acquired during baseline, actual movement and visually and kinesthetically imagined movements. The chronometric indices do not reveal significant differences between groups and imagery modalities. The self-report MI efficacy indicates better kinesthetic imagery in highs and mediums than in lows, and no modality difference among lows. The MAIA dimensions sustain the differences in subjective experience and almost all the EEG differences. The latter are slightly different in highs, mediums and lows. This is the first report of the major role played by IS in MI and strongly supports the theory of embodied cognition. Full article
(This article belongs to the Section Behavioral Neuroscience)
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33 pages, 720 KiB  
Perspective
Leveraging Artificial Intelligence to Optimize Transcranial Direct Current Stimulation for Long COVID Management: A Forward-Looking Perspective
by Thorsten Rudroff, Oona Rainio and Riku Klén
Brain Sci. 2024, 14(8), 831; https://doi.org/10.3390/brainsci14080831 - 19 Aug 2024
Viewed by 872
Abstract
Long COVID (Coronavirus disease), affecting millions globally, presents unprecedented challenges to healthcare systems due to its complex, multifaceted nature and the lack of effective treatments. This perspective review explores the potential of artificial intelligence (AI)-guided transcranial direct current stimulation (tDCS) as an innovative [...] Read more.
Long COVID (Coronavirus disease), affecting millions globally, presents unprecedented challenges to healthcare systems due to its complex, multifaceted nature and the lack of effective treatments. This perspective review explores the potential of artificial intelligence (AI)-guided transcranial direct current stimulation (tDCS) as an innovative approach to address the urgent need for effective Long COVID management. The authors examine how AI could optimize tDCS protocols, enhance clinical trial design, and facilitate personalized treatment for the heterogeneous manifestations of Long COVID. Key areas discussed include AI-driven personalization of tDCS parameters based on individual patient characteristics and real-time symptom fluctuations, the use of machine learning for patient stratification, and the development of more sensitive outcome measures in clinical trials. This perspective addresses ethical considerations surrounding data privacy, algorithmic bias, and equitable access to AI-enhanced treatments. It also explores challenges and opportunities for implementing AI-guided tDCS across diverse healthcare settings globally. Future research directions are outlined, including the need for large-scale validation studies and investigations of long-term efficacy and safety. The authors argue that while AI-guided tDCS shows promise for addressing the complex nature of Long COVID, significant technical, ethical, and practical challenges remain. They emphasize the importance of interdisciplinary collaboration, patient-centered approaches, and a commitment to global health equity in realizing the potential of this technology. This perspective article provides a roadmap for researchers, clinicians, and policymakers involved in developing and implementing AI-guided neuromodulation therapies for Long COVID and potentially other neurological and psychiatric conditions. Full article
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11 pages, 7955 KiB  
Article
FluoAnalysis: An Open-Source MATLAB Toolbox for Analysis of Calcium Imaging Measurements of Oscillatory Astrocytic and Neuronal Networks
by Márton Péter and László Héja
Brain Sci. 2024, 14(8), 830; https://doi.org/10.3390/brainsci14080830 - 19 Aug 2024
Viewed by 1080
Abstract
Calcium imaging, especially two-photon imaging, has become essential in neuroscience for studying neuronal and astrocytic activity under in vivo and in vitro conditions. Current advances in the development of calcium sensors as well as imaging hardware enable high-frequency measurements of calcium signals in [...] Read more.
Calcium imaging, especially two-photon imaging, has become essential in neuroscience for studying neuronal and astrocytic activity under in vivo and in vitro conditions. Current advances in the development of calcium sensors as well as imaging hardware enable high-frequency measurements of calcium signals in hundreds of cells simultaneously. The analysis of these large datasets requires special tools and usually a certain level of programming experience. Despite advancements in calcium imaging analysis software development, significant gaps remain, particularly for data acquired at a high sampling rate that would allow for the spectral analysis of calcium signals. The FluoAnalysis MATLAB toolbox addresses these gaps by offering a comprehensive solution for analyzing simultaneously measured calcium imaging and electrophysiological data. It features both GUI-based and command-line approaches, emphasizing frequency domain analysis to reveal network-level oscillatory signals linked to single-cell activity. In addition, the toolbox puts special emphasis on differentiating between astrocytes and neurons, revealing the interactions between the network activity of the two major cell types of the brain. It facilitates a streamlined workflow for data loading, ROI identification, cell classification, fluorescence intensity calculation, spectral analysis, and report generation, supporting both manual and automated high-throughput analysis. This versatile platform enables the comprehensive analysis of large imaging datasets. In conclusion, the FluoAnalysis MATLAB toolbox provides a robust and versatile platform for the integrated analysis of calcium imaging and electrophysiological data, supporting diverse neuroscience research applications. Full article
(This article belongs to the Section Computational Neuroscience and Neuroinformatics)
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18 pages, 2752 KiB  
Systematic Review
Comparison between Single-Dose and Two-Dose Psilocybin Administration in the Treatment of Major Depression: A Systematic Review and Meta-Analysis of Current Clinical Trials
by Gianmarco Salvetti, Daniele Saccenti, Andrea Stefano Moro, Jacopo Lamanna and Mattia Ferro
Brain Sci. 2024, 14(8), 829; https://doi.org/10.3390/brainsci14080829 - 18 Aug 2024
Viewed by 2080
Abstract
Current pharmacological treatments for major depressive disorder (MDD) are often only partially effective, with many patients experiencing no significant benefit, leading to treatment-resistant depression (TRD). Psilocybin, a classical serotonergic psychedelic, has emerged as a notable emerging treatment for such disorders. The aim of [...] Read more.
Current pharmacological treatments for major depressive disorder (MDD) are often only partially effective, with many patients experiencing no significant benefit, leading to treatment-resistant depression (TRD). Psilocybin, a classical serotonergic psychedelic, has emerged as a notable emerging treatment for such disorders. The aim of this systematic review and meta-analysis is to summarize and discuss the most recent evidence about the therapeutic effects of single-dose and two-dose psilocybin administration on the severity of depressive symptoms, as well as compare the efficacy of these interventions among patients with a primary diagnosis of MDD or TRD. Articles were collected from EBSCOhost and PubMed following the PRISMA guidelines, yielding 425 articles with 138 duplicates. After screening 287 records, 12 studies met the eligibility criteria and were included in the review. A quantitative analysis of the studies indicates that psilocybin is highly effective in reducing depressive symptoms severity among patients with primary MDD or TRD. Both single-dose and two-dose psilocybin treatments significantly reduced depressive symptoms severity, with two-dose administration sometimes yielding more pronounced and lasting effects. However, it is unclear if this was solely due to dosage or other factors. Future research should include standardized trials comparing these dosing strategies to better inform clinical practice. Full article
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16 pages, 4019 KiB  
Article
Improving the Sensitivity of Task-Based Multi-Echo Functional Magnetic Resonance Imaging via T2* Mapping Using Synthetic Data-Driven Deep Learning
by Yinghe Zhao, Qinqin Yang, Shiting Qian, Jiyang Dong, Shuhui Cai, Zhong Chen and Congbo Cai
Brain Sci. 2024, 14(8), 828; https://doi.org/10.3390/brainsci14080828 - 17 Aug 2024
Viewed by 865
Abstract
(1) Background: Functional magnetic resonance imaging (fMRI) utilizing multi-echo gradient echo-planar imaging (ME-GE-EPI) has demonstrated higher sensitivity and stability compared to utilizing single-echo gradient echo-planar imaging (SE-GE-EPI). The direct derivation of T2* maps from fitting multi-echo data enables accurate recording of [...] Read more.
(1) Background: Functional magnetic resonance imaging (fMRI) utilizing multi-echo gradient echo-planar imaging (ME-GE-EPI) has demonstrated higher sensitivity and stability compared to utilizing single-echo gradient echo-planar imaging (SE-GE-EPI). The direct derivation of T2* maps from fitting multi-echo data enables accurate recording of dynamic functional changes in the brain, exhibiting higher sensitivity than echo combination maps. However, the widely employed voxel-wise log-linear fitting is susceptible to inevitable noise accumulation during image acquisition. (2) Methods: This work introduced a synthetic data-driven deep learning (SD-DL) method to obtain T2* maps for multi-echo (ME) fMRI analysis. (3) Results: The experimental results showed the efficient enhancement of the temporal signal-to-noise ratio (tSNR), improved task-based blood oxygen level-dependent (BOLD) percentage signal change, and enhanced performance in multi-echo independent component analysis (MEICA) using the proposed method. (4) Conclusion: T2* maps derived from ME-fMRI data using the proposed SD-DL method exhibit enhanced BOLD sensitivity in comparison to T2* maps derived from the LLF method. Full article
(This article belongs to the Section Computational Neuroscience and Neuroinformatics)
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9 pages, 261 KiB  
Article
Epidemiology of Sports-Related Concussion in Japanese University Soccer Players
by Hiroshi Fukushima, Yutaka Shigemori, Shunya Otsubo, Kyosuke Goto, Koki Terada, Muneyuki Tachihara, Tatsuma Kurosaki, Keita Yamaguchi, Nana Otsuka, Kentaro Masuda, Rino Tsurusaki and Masahiro Inui
Brain Sci. 2024, 14(8), 827; https://doi.org/10.3390/brainsci14080827 - 17 Aug 2024
Viewed by 838
Abstract
In recent years, sports-related concussion (SRC) in soccer has been extensively researched worldwide. However, there have been no reports of large-scale SRC studies among soccer players in Japan. The purpose of this study is to investigate the epidemiology of SRC among university soccer [...] Read more.
In recent years, sports-related concussion (SRC) in soccer has been extensively researched worldwide. However, there have been no reports of large-scale SRC studies among soccer players in Japan. The purpose of this study is to investigate the epidemiology of SRC among university soccer players in Japan. This descriptive epidemiological study collected data on the history of SRC and details of SRC injuries during soccer. The participants were university male soccer players belonging to the Japan University Football Association. SRC rates were calculated per 1000 athlete-exposures (AEs). A total of 5953 students participated in this study. The SRC rate was 0.10/1000 AE during total activities. The SRC rate during competition (0.42/1000 AE) was higher than in practice (0.04/1000 AE). The most frequent mechanism of SRC was “head-to-head” (26.9%), followed by “head-to-ball” (24.2%). During competition, the most frequent mechanism was “head-to-head” (30.8%), followed by “head-to-ground” (23.8%), and “head-to-ball” (19.3%) followed, while in practice, it was “head-to-ball” (34.8%), followed by “head-to-ground” (23.8%), and “head-to-head” (17.2%). Thus, there was a difference in the mechanism of injury between competition and practice. In this study, among Japanese university soccer players, the SRC rate was to be approximately ten times higher in competition than in practice. Full article
(This article belongs to the Section Neurosurgery and Neuroanatomy)
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7 pages, 598 KiB  
Brief Report
Sleep, Diet, and Exercise: How Much Dementia Caregivers Are Affected?
by Angeliki Tsapanou, Panagiota Zoi and Paraskeui Sakka
Brain Sci. 2024, 14(8), 826; https://doi.org/10.3390/brainsci14080826 - 17 Aug 2024
Viewed by 865
Abstract
The current descriptive study reports the sleep, diet, and exercise patterns among 114 dementia caregivers, whose mean age was 55.7 (SD: 10.4) years, with 83 (72.8%) being women. The results indicate significant sleep dysfunction: 37.2% of caregivers reported rarely or never feeling rested [...] Read more.
The current descriptive study reports the sleep, diet, and exercise patterns among 114 dementia caregivers, whose mean age was 55.7 (SD: 10.4) years, with 83 (72.8%) being women. The results indicate significant sleep dysfunction: 37.2% of caregivers reported rarely or never feeling rested upon waking, and 46.5% did not get enough sleep, with 45.6% sleeping only 5 to 5.5 h on average. Sleep latency was also prevalent, as 33.3% required 16 to 30 min to fall asleep. Dietary habits showed reliance on coffee, with 69.4% consuming it daily. Meat consumption was reported by 75%, and 60.9% ate pasta, indicating common dietary preferences. While 86.2% had one to three meals per day, 100% of the caregivers supplemented their diets with vitamins. The physical activity level was low, with 62.3% of respondents reporting no exercise in the past week. These findings underscore significant health concerns among dementia caregivers, including sleep deprivation, inadequate nutrition, and physical inactivity. The report emphasizes the need for targeted interventions to promote self-care practices that can enhance caregivers’ health, including better sleep hygiene, balanced nutrition, and regular exercise. Full article
(This article belongs to the Section Sleep and Circadian Neuroscience)
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10 pages, 265 KiB  
Article
Validation of the Fatigue Impact Scale in Multiple Sclerosis Patients in Serbia
by Olivera Tamaš, Marija Kovačević, Aleksandra Dobrodolac, Nada Rašuo Bosnić, Žužana Tot Šari, Livija Despenić, László Vécsei, Krisztina Bencsik, Tatjana Pekmezović and Jelena Drulović
Brain Sci. 2024, 14(8), 825; https://doi.org/10.3390/brainsci14080825 - 17 Aug 2024
Viewed by 665
Abstract
Fatigue is one of the most frequent complaints of patients with multiple sclerosis (MS). The Fatigue Impact Scale (FIS), one of the 30 available fatigue questionnaires, is commonly applied because it evaluates multidimensional aspects of fatigue. The chief objectives of this study were [...] Read more.
Fatigue is one of the most frequent complaints of patients with multiple sclerosis (MS). The Fatigue Impact Scale (FIS), one of the 30 available fatigue questionnaires, is commonly applied because it evaluates multidimensional aspects of fatigue. The chief objectives of this study were to validate FIS and evaluate the psychometric properties of MS patients in Serbia. One hundred and twenty-one (121) MS patients and one hundred and twenty-two (122) age-, gender- and education-matched healthy control (HC) subjects completed the FIS and the Beck Depression Inventory. Internal consistency of the FIS subscales was determined using Cronbach’s Alpha Coefficient. Test/retest reliability with an intra-class correlation coefficient (ICC) for each FIS subscale was performed. The total FIS score and subscale scores showed statistically significant differences between the MS patients and the HC subjects in both FIS sessions. Cronbach’s Alpha was 0.966. All ICCs were statistically significant (p < 0.05). The Serbian version of this instrument may be useful as a clinical measure for fatigue and functionality in patients with MS. Full article
(This article belongs to the Section Behavioral Neuroscience)
3 pages, 143 KiB  
Editorial
From Editorial Board of Special Issue Entitled “Post-Stroke Rehabilitation”
by Noureddin Nakhostin Ansari, Gholamreza Hassanzadeh and Ardalan Shariat
Brain Sci. 2024, 14(8), 824; https://doi.org/10.3390/brainsci14080824 - 16 Aug 2024
Viewed by 621
Abstract
Diseases affecting the nervous system are diverse [...] Full article
(This article belongs to the Special Issue Post-stroke Rehabilitation)
9 pages, 956 KiB  
Article
Exploratory Study of Biomechanical Properties and Pain Sensitivity at Back-Shu Points
by Heeyoung Moon, Seoyoung Lee, Da-Eun Yoon, In-Seon Lee and Younbyoung Chae
Brain Sci. 2024, 14(8), 823; https://doi.org/10.3390/brainsci14080823 - 16 Aug 2024
Cited by 1 | Viewed by 784
Abstract
Objectives: Hypersensitive acupoints in specific body areas are associated with corresponding internal or visceral disorders. Back-shu points are clinically significant for the diagnosis of visceral organ disease, according to the biomechanical characteristics of the acupoints. In this study, we assessed the biomechanical characteristics [...] Read more.
Objectives: Hypersensitive acupoints in specific body areas are associated with corresponding internal or visceral disorders. Back-shu points are clinically significant for the diagnosis of visceral organ disease, according to the biomechanical characteristics of the acupoints. In this study, we assessed the biomechanical characteristics and pain sensitivities of five back-shu points linked to five visceral organs in healthy participants. Methods: The study included 48 volunteer participants. A myotonometry was used to assess muscle tone and muscle stiffness at five back-shu points associated with visceral organs. Pressure was monitored using a microcontroller and a force sensor. Pain sensitivity was assessed in response to deep pressure pain produced by a constant force. Results: Substantial differences in muscle tone and stiffness were observed at the five back-shu points; muscle tone was highest at BL15, whereas muscle tone and muscle stiffness were lowest at BL23. Moreover, pain sensitivity was significantly different among the acupoints; pain sensitivity was highest at BL23. There was a significant negative correlation between muscle tone and pain sensitivity. Conclusions: We found significant differences in muscle tone, muscle stiffness, and pain sensitivity among five back-shu points associated with visceral organs, which may be attributable to anatomical variations at each point. Our findings suggest that differences at back-shu points should be considered to ensure the accurate diagnosis of visceral disease. Full article
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7 pages, 262 KiB  
Brief Report
Neurological Damage Measured by S-100b and Neuron-Specific Enolase in Patients Treated with Electroconvulsive Therapy
by Ángel A. Ruiz-Chow, Carlos J. López-Cruz, Daniel Crail-Meléndez, Jesús Ramírez-Bermúdez, José Santos-Zambrano and Laura A. Luz-Escamilla
Brain Sci. 2024, 14(8), 822; https://doi.org/10.3390/brainsci14080822 - 16 Aug 2024
Viewed by 972
Abstract
Electroconvulsive therapy (ECT) is considered one of the most effective treatments for psychiatric disorders. ECT has proven effective in the treatment of depression, mania, catatonia and psychosis. It is presumed that seizures induced during ECT administration cause toxicity and potentially neuronal and glial [...] Read more.
Electroconvulsive therapy (ECT) is considered one of the most effective treatments for psychiatric disorders. ECT has proven effective in the treatment of depression, mania, catatonia and psychosis. It is presumed that seizures induced during ECT administration cause toxicity and potentially neuronal and glial cell death. A broad range of neurological disorders increase cerebrospinal fluid and serum levels of neuron-specific enolase (NSE) and S-100b protein. This study aims to investigate the effect of ECT on NSE and S-100b levels, which, together, serve as a proxy for neuronal cell damage. Serum concentrations of S-100b and NSE of adult patients who received ECT were measured by immunoluminometric analysis before and after treatment. A two-way ANOVA test was used to estimate the statistical differences in marker concentrations between the subgroups of the study population. Results: A total of 55 patients were included in the analysis: 52.73% (n = 29) were diagnosed with depression, 21.82% (n = 12) with schizophrenia or other psychosis, 16.36% (n = 9) with mania and 9.09% (n = 5) with catatonia. There were no statistically significant changes in NSE (p = 0.288) and S-100b (p = 0.243) levels. We found no evidence that ECT induced neuronal damage based on NSE and S-100b protein levels measured in the serum of patients before and after treatment. Full article
(This article belongs to the Special Issue Clinical and Biological Characterization of Psychiatric Disorders)
14 pages, 913 KiB  
Systematic Review
Understanding Quality of Life for People with Motor Neurone Disease Who Use Tracheostomy Ventilation and Family Members: A Scoping Review
by Nicola Turner, Christina Faull, Jonathan Palmer, Alison Armstrong, Jennifer Bedford, Martin R. Turner and Eleanor Wilson
Brain Sci. 2024, 14(8), 821; https://doi.org/10.3390/brainsci14080821 - 16 Aug 2024
Viewed by 839
Abstract
Tracheostomy ventilation (TV) can increase survival time for people living with motor neurone disease (MND); however, the use of TV varies between countries. Concerns regarding anticipated quality of life (QoL) are among the reasons given by healthcare professionals for not recommending this intervention, [...] Read more.
Tracheostomy ventilation (TV) can increase survival time for people living with motor neurone disease (MND); however, the use of TV varies between countries. Concerns regarding anticipated quality of life (QoL) are among the reasons given by healthcare professionals for not recommending this intervention, yet little is known about QoL in this context. This scoping review was conducted to examine the evidence on QoL for those with MND who use TV and family members involved in their care. Using the methodological guidance of the Joanna Briggs Institute, 23 papers were identified for inclusion, and findings were inductively analysed to identify key themes. We found that people living with MND tend to rate QoL post TV more positively than anticipated by healthcare professionals or family members. QoL was found to be related to positive relationships and activities the person could maintain. Feeling able to make a choice and an adequate level of financial resources were also important factors. Family members tended to experience lower QoL, associated with the uncertainty surrounding an emergency procedure and the complexity of subsequently required care. More evidence on QoL from the perspectives of people with MND who use TV is needed to support decision making and inform guidance. Full article
(This article belongs to the Section Neuromuscular and Movement Disorders)
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17 pages, 3956 KiB  
Article
EEG–fNIRS-Based Emotion Recognition Using Graph Convolution and Capsule Attention Network
by Guijun Chen, Yue Liu and Xueying Zhang
Brain Sci. 2024, 14(8), 820; https://doi.org/10.3390/brainsci14080820 - 16 Aug 2024
Cited by 1 | Viewed by 1452
Abstract
Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) can objectively reflect a person’s emotional state and have been widely studied in emotion recognition. However, the effective feature fusion and discriminative feature learning from EEG–fNIRS data is challenging. In order to improve the accuracy of [...] Read more.
Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) can objectively reflect a person’s emotional state and have been widely studied in emotion recognition. However, the effective feature fusion and discriminative feature learning from EEG–fNIRS data is challenging. In order to improve the accuracy of emotion recognition, a graph convolution and capsule attention network model (GCN-CA-CapsNet) is proposed. Firstly, EEG–fNIRS signals are collected from 50 subjects induced by emotional video clips. And then, the features of the EEG and fNIRS are extracted; the EEG–fNIRS features are fused to generate higher-quality primary capsules by graph convolution with the Pearson correlation adjacency matrix. Finally, the capsule attention module is introduced to assign different weights to the primary capsules, and higher-quality primary capsules are selected to generate better classification capsules in the dynamic routing mechanism. We validate the efficacy of the proposed method on our emotional EEG–fNIRS dataset with an ablation study. Extensive experiments demonstrate that the proposed GCN-CA-CapsNet method achieves a more satisfactory performance against the state-of-the-art methods, and the average accuracy can increase by 3–11%. Full article
(This article belongs to the Section Cognitive, Social and Affective Neuroscience)
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7 pages, 521 KiB  
Communication
The Relationship between Clinical and Psychophysical Assessments of Visual Perceptual Disturbances in Individuals at Clinical High Risk for Psychosis: A Preliminary Study
by Chloe Ifrah, Shaynna N. Herrera, Steven M. Silverstein, Cheryl M. Corcoran, James Gordon, Pamela D. Butler and Vance Zemon
Brain Sci. 2024, 14(8), 819; https://doi.org/10.3390/brainsci14080819 - 16 Aug 2024
Viewed by 893
Abstract
This study investigated relations between a measure of early-stage visual function and self-reported visual anomalies in individuals at clinical high risk for psychosis (CHR-P). Eleven individuals at CHR identified via the Structured Interview for Psychosis-Risk Syndromes (SIPS) were recruited from a CHR-P research [...] Read more.
This study investigated relations between a measure of early-stage visual function and self-reported visual anomalies in individuals at clinical high risk for psychosis (CHR-P). Eleven individuals at CHR identified via the Structured Interview for Psychosis-Risk Syndromes (SIPS) were recruited from a CHR-P research program in NYC. The sample was ~36% female, ranging from 16 to 33 years old (M = 23.90, SD = 6.14). Participants completed a contrast sensitivity task on an iPad with five spatial frequencies (0.41–13 cycles/degree) and completed the self-report Audio-Visual Abnormalities Questionnaire. Higher contrast sensitivity (better performance) to low spatial frequencies was associated with higher perceptual (r = 0.616, p = 0.044) and visual disturbances (r = 0.667, p = 0.025); lower contrast sensitivity to a middle spatial frequency was also associated with higher perceptual (r = −0.604, p = 0.049) and visual disturbances (r = −0.606, p = 0.048). This relation between the questionnaire and contrast sensitivity to low spatial frequency may be indicative of a reduction in lateral inhibition and “flooding” of environmental stimuli. The association with middle spatial frequencies, which play a critical role in face processing, may result in a range of perceptual abnormalities. These findings demonstrate that self-reported perceptual anomalies occur in these individuals and are linked to performance on a measure of early visual processing. Full article
(This article belongs to the Section Psychiatric Diseases)
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