Journal Description
Brain Sciences
Brain Sciences
is an international, peer-reviewed, open access journal on neuroscience published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, PSYNDEX, CAPlus / SciFinder, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.6 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.3 (2022);
5-Year Impact Factor:
3.4 (2022)
Latest Articles
Motor Imagery Classification Using Effective Channel Selection of Multichannel EEG
Brain Sci. 2024, 14(5), 462; https://doi.org/10.3390/brainsci14050462 - 03 May 2024
Abstract
Electroencephalography (EEG) is effectively employed to describe cognitive patterns corresponding to different tasks of motor functions for brain–computer interface (BCI) implementation. Explicit information processing is necessary to reduce the computational complexity of practical BCI systems. This paper presents an entropy-based approach to select
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Electroencephalography (EEG) is effectively employed to describe cognitive patterns corresponding to different tasks of motor functions for brain–computer interface (BCI) implementation. Explicit information processing is necessary to reduce the computational complexity of practical BCI systems. This paper presents an entropy-based approach to select effective EEG channels for motor imagery (MI) classification in brain–computer interface (BCI) systems. The method identifies channels with higher entropy scores, which is an indication of greater information content. It discards redundant or noisy channels leading to reduced computational complexity and improved classification accuracy. High entropy means a more disordered pattern, whereas low entropy means a less disordered pattern with less information. The entropy of each channel for individual trials is calculated. The weight of each channel is represented by the mean entropy of the channel over all the trials. A set of channels with higher mean entropy are selected as effective channels for MI classification. A limited number of sub-band signals are created by decomposing the selected channels. To extract the spatial features, the common spatial pattern (CSP) is applied to each sub-band space of EEG signals. The CSP-based features are used to classify the right-hand and right-foot MI tasks using a support vector machine (SVM). The effectiveness of the proposed approach is validated using two publicly available EEG datasets, known as BCI competition III–IV(A) and BCI competition IV–I. The experimental results demonstrate that the proposed approach surpasses cutting-edge techniques.
Full article
(This article belongs to the Special Issue EEG and Event-Related Potentials)
Open AccessArticle
Two Sides of Theory of Mind: Mental State Attribution to Moving Shapes in Paranoid Schizophrenia Is Independent of the Severity of Positive Symptoms
by
Christina Fuchs, Sarita Silveira, Thomas Meindl, Richard Musil, Kim Laura Austerschmidt, Dirk W. Eilert, Norbert Müller, Hans-Jürgen Möller, Rolf Engel, Maximilian Reiser, Martin Driessen, Thomas Beblo and Kristina Hennig-Fast
Brain Sci. 2024, 14(5), 461; https://doi.org/10.3390/brainsci14050461 - 02 May 2024
Abstract
Background: Theory of Mind (ToM) impairment has repeatedly been found in paranoid schizophrenia. The current study aims at investigating whether this is related to a deficit in ToM (undermentalizing) or an increased ToM ability to hyperattribute others’ mental states (overmentalizing). Methods: Mental state
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Background: Theory of Mind (ToM) impairment has repeatedly been found in paranoid schizophrenia. The current study aims at investigating whether this is related to a deficit in ToM (undermentalizing) or an increased ToM ability to hyperattribute others’ mental states (overmentalizing). Methods: Mental state attribution was examined in 24 patients diagnosed with schizophrenia (12 acute paranoid (APS) and 12 post-acute paranoid (PPS)) with regard to positive symptoms as well as matched healthy persons using a moving shapes paradigm. We used 3-T-functional magnetic resonance imaging (fMRI) to provide insights into the neural underpinnings of ToM due to attributional processes in different states of paranoid schizophrenia. Results: In the condition that makes demands on theory of mind skills (ToM condition), in patients with diagnosed schizophrenia less appropriate mental state descriptions have been used, and they attributed mental states less often to the moving shapes than healthy persons. On a neural level, patients suffering from schizophrenia exhibited within the ToM network hypoactivity in the medial prefrontal cortex (MPFC) and hyperactivity in the temporo-parietal junction (TPJ) as compared to the healthy sample. Conclusions: Our results indicate both undermentalizing and hypoactivity in the MPFC and increased overattribution related to hyperactivity in the TPJ in paranoid schizophrenia, providing new implications for understanding ToM in paranoid schizophrenia.
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(This article belongs to the Special Issue Cognitive Dysfunction in Schizophrenia)
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Open AccessEditorial
Advances in Social Cognitive and Affective Neuroscience: Ten Highly Cited Articles Published in Brain Sciences in 2022–2023
by
Yang Zhang
Brain Sci. 2024, 14(5), 460; https://doi.org/10.3390/brainsci14050460 - 02 May 2024
Abstract
In the realm of Social Cognitive and Affective Neuroscience, researchers employ a variety of methods to address theoretical and practical questions that focus on the intricate interplay between social perception, cognition, and emotion across diverse populations and contexts [...]
Full article
(This article belongs to the Section Social Cognitive and Affective Neuroscience)
Open AccessEditorial
Brain Sciences Special Issue “Neuromodulation of Cortical Networks in Neurological and Neuropsychiatric Disorders: Potential Clinical Indications and the Biophysiological Impact of Stimulation”
by
Maja Rogić Vidaković, Joško Šoda and Joshua Elan Kuluva
Brain Sci. 2024, 14(5), 459; https://doi.org/10.3390/brainsci14050459 - 01 May 2024
Abstract
Individuals with neurological and neuropsychiatric disorders face a variety of difficulties that can significantly impact their daily lives [...]
Full article
(This article belongs to the Special Issue Neuromodulation of Cortical Networks in Neurological and Neuropsychiatric Disorders: Potential Clinical Indications and the Biophysiological Impact of Stimulation)
Open AccessReview
A Review of Childhood Developmental Changes in Attention as Indexed in the Electrical Activity of the Brain
by
Sirel Karakaş
Brain Sci. 2024, 14(5), 458; https://doi.org/10.3390/brainsci14050458 - 01 May 2024
Abstract
This review aims to present age-related changes in the neuroelectric responses of typically developing children (TDC) who are presumed to meet developmental stages appropriately. The review is based on findings from the frequently used neuropsychological tasks of active attention, where attention is deliberately
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This review aims to present age-related changes in the neuroelectric responses of typically developing children (TDC) who are presumed to meet developmental stages appropriately. The review is based on findings from the frequently used neuropsychological tasks of active attention, where attention is deliberately focused versus passive attention where attention is drawn to a stimulus, facilitatory attention, which enhances the processing of a stimulus versus inhibitory attention, which suppresses the processing of a stimulus. The review discusses the early and late stages of attentional selectivity that correspond to early and late information processing. Age-related changes in early attentional selectivity were quantitatively represented in latencies of the event-related potential (ERP) components. Age-related changes in late attentional selectivity are also qualitatively represented by structural and functional reorganization of attentional processing and the brain areas involved. The purely bottom-up or top-down processing is challenged with age-related findings on difficult tasks that ensure a high cognitive load. TDC findings on brain oscillatory activity are enriched by findings from attention deficit hyperactivity disorder (ADHD). The transition from the low to fast oscillations in TDC and ADHD confirmed the maturational lag hypothesis. The deviant topographical localization of the oscillations confirmed the maturational deviance model. The gamma-based match and utilization model integrates all levels of attentional processing. According to these findings and theoretical formulations, brain oscillations can potentially display the human brain’s wholistic–integrative functions.
Full article
(This article belongs to the Special Issue Human Brain Responses and Functional Brain Networks across the Lifespan)
Open AccessArticle
Temporal Dynamics of Adverse Effects across Five Sessions of Transcranial Direct Current Stimulation
by
Miguel Delicado-Miralles, Laura Flix-Diez, Francisco Gurdiel-Álvarez, Enrique Velasco, María Galán-Calle and Sergio Lerma Lara
Brain Sci. 2024, 14(5), 457; https://doi.org/10.3390/brainsci14050457 - 30 Apr 2024
Abstract
(1) Background: Transcranial direct current stimulation (tDCS) is a safe intervention, only producing mild and transient adverse effects (AEs). However, there is no detailed analysis of the pattern of adverse effects in an application transferable to the clinic. Therefore, our objective is to
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(1) Background: Transcranial direct current stimulation (tDCS) is a safe intervention, only producing mild and transient adverse effects (AEs). However, there is no detailed analysis of the pattern of adverse effects in an application transferable to the clinic. Therefore, our objective is to describe the AEs produced by tDCS and its temporal evolution. (2) Methods: A total of 33 young volunteers were randomized into a tDCS or sham group. Participants performed a hand dexterity task while receiving the tDCS or sham intervention (20 min and 1 mA), for five consecutive days. AEs were assessed daily after each intervention and classified as somatosensory, pain, or other effects. (3) Results: The number of AEs was generally increased by tDCS intervention. Specifically, tDCS led to more frequent somatosensory discomfort, characterized by sensations like itching and tingling, alongside painful sensations such as burning, compared to the sham intervention. Additionally, certain adverse events, including neck and arm pain, as well as dizziness and blurry vision, were exclusive to the tDCS group. Interestingly, tDCS produced similar AEs across the days; meanwhile, the somatosensory AEs in the sham group showed a trend to decrease. (4) Conclusions: tDCS produces mild and temporary somatosensory and pain AEs during and across sessions. The different evolution of the AEs between the tDCS and sham protocol could unmask the blinding protocol most used in tDCS studies. Potential solutions for improving blinding protocols for future studies are discussed.
Full article
(This article belongs to the Section Sensory and Motor Neuroscience)
Open AccessArticle
The Use of Generative Adversarial Network and Graph Convolution Network for Neuroimaging-Based Diagnostic Classification
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Nguyen Huynh, Da Yan, Yueen Ma, Shengbin Wu, Cheng Long, Mirza Tanzim Sami, Abdullateef Almudaifer, Zhe Jiang, Haiquan Chen, Michael N. Dretsch, Thomas S. Denney, Rangaprakash Deshpande and Gopikrishna Deshpande
Brain Sci. 2024, 14(5), 456; https://doi.org/10.3390/brainsci14050456 - 30 Apr 2024
Abstract
Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative
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Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases.
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(This article belongs to the Special Issue Advances of AI in Neuroimaging)
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Open AccessArticle
In-Hospital Mortality in Patients with and without Dementia across Age Groups, Clinical Departments, and Primary Admission Diagnoses
by
Karel Kostev, Bernhard Michalowsky and Jens Bohlken
Brain Sci. 2024, 14(5), 455; https://doi.org/10.3390/brainsci14050455 - 30 Apr 2024
Abstract
Background: Studies have reported higher in-hospital mortality rates in patients living with dementia (PlwD) with limited evidence across age groups, clinical departments, and admission diagnoses. The aim of this study was to compare the in-hospital mortality rate of PlwD with patients without dementia
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Background: Studies have reported higher in-hospital mortality rates in patients living with dementia (PlwD) with limited evidence across age groups, clinical departments, and admission diagnoses. The aim of this study was to compare the in-hospital mortality rate of PlwD with patients without dementia across groups, clinical departments, and admission diagnoses. Methods: This case-control study included patients aged ≥ 60 years hospitalized in 1 of 14 German hospitals between January 2019 and July 2023. PlwD were matched to patients without dementia. The associations between dementia and in-hospital mortality across groups were assessed using univariable logistic regression analyses. Results: 15,956 patients with and 15,956 without dementia were included (mean age: 83.9 years, 60.7% female). PlwD had a significantly higher in-hospital mortality rate (14.0% vs. 11.7%; OR 1.24, 95% CI: 1.16–1.32) than non-dementia controls. The highest excess mortality rate was observed in the youngest age group (60–70 years: 10.9% vs. 5.7%; OR: 2.05, 95% CI: 1.30–3.24), decreased with age, and became non-significant in the oldest age group (≥90 years: 16.2% vs. 17.3%; OR: 0.93, 95% CI: 0.80–1.08). Significant differences were found for digestive system disorders (OR: 1.59; 95% CI: 1.15–1.89), cardiovascular and cerebrovascular disorders (OR: 1.51; 95% CI: 1.30–1.75), endocrine, nutritional, and metabolic diseases (OR: 1.42; 95% CI: 1.06–1.90), and pneumonia (OR: 1.20; 95% CI: 1.04–1.37), as well as for all clinic departments except for geriatric departments. Conclusion: The excess mortality rate was highest in younger age groups, where the general mortality and complication rate is relatively low in the general population. Appropriate approaches are needed, especially in non-geriatric wards.
Full article
(This article belongs to the Section Neurodegenerative Diseases)
Open AccessReview
Central Causation of Autism/ASDs via Excessive [Ca2+]i Impacting Six Mechanisms Controlling Synaptogenesis during the Perinatal Period: The Role of Electromagnetic Fields and Chemicals and the NO/ONOO(-) Cycle, as Well as Specific Mutations
by
Martin L. Pall
Brain Sci. 2024, 14(5), 454; https://doi.org/10.3390/brainsci14050454 - 30 Apr 2024
Abstract
The roles of perinatal development, intracellular calcium [Ca2+]i, and synaptogenesis disruption are not novel in the autism/ASD literature. The focus on six mechanisms controlling synaptogenesis, each regulated by [Ca2+]i, and each aberrant in ASDs is novel. The model presented
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The roles of perinatal development, intracellular calcium [Ca2+]i, and synaptogenesis disruption are not novel in the autism/ASD literature. The focus on six mechanisms controlling synaptogenesis, each regulated by [Ca2+]i, and each aberrant in ASDs is novel. The model presented here predicts that autism epidemic causation involves central roles of both electromagnetic fields (EMFs) and chemicals. EMFs act via voltage-gated calcium channel (VGCC) activation and [Ca2+]i elevation. A total of 15 autism-implicated chemical classes each act to produce [Ca2+]i elevation, 12 acting via NMDA receptor activation, and three acting via other mechanisms. The chronic nature of ASDs is explained via NO/ONOO(-) vicious cycle elevation and MeCP2 epigenetic dysfunction. Genetic causation often also involves [Ca2+]i elevation or other impacts on synaptogenesis. The literature examining each of these steps is systematically examined and found to be consistent with predictions. Approaches that may be sed for ASD prevention or treatment are discussed in connection with this special issue: The current situation and prospects for children with ASDs. Such approaches include EMF, chemical avoidance, and using nutrients and other agents to raise the levels of Nrf2. An enriched environment, vitamin D, magnesium, and omega-3s in fish oil may also be helpful.
Full article
(This article belongs to the Special Issue Children with Autism Spectrum Disorders: Current Situation and Prospects)
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Open AccessReview
A Narrative Review of the Efficacy of Interventions for Emotional Dysregulation, and Underlying Bio–Psycho–Social Factors
by
Thomas Easdale-Cheele, Valeria Parlatini, Samuele Cortese and Alessio Bellato
Brain Sci. 2024, 14(5), 453; https://doi.org/10.3390/brainsci14050453 - 30 Apr 2024
Abstract
In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint,
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In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint, we discuss the factors commonly associated with emotion regulation, including neurobiological and neuropsychological mechanisms, and the role of childhood adverse experiences and psycho–social factors in the onset of emotion dysregulation. We then present evidence about pharmacological and non-pharmacological interventions aiming at improving emotion dysregulation and promoting emotion regulation across the lifespan. Although our review was not intended as a traditional systematic review, and the search was only restricted to systematic reviews and meta-analyses, we highlighted important implications and provided recommendations for clinical practice and future research in this field.
Full article
(This article belongs to the Special Issue Clinical and Biological Correlates of Emotional Dysregulation in Children and Adolescents: A Transdiagnostic Approach to Developmental Psychopathology)
Open AccessSystematic Review
Deep Brain Stimulation for Primary Refractory Tinnitus: A Systematic Review
by
Landon Basner, Jasper V. Smit, Daniel M. Zeitler, Seth R. Schwartz, Katie Krause, Aiyush Bansal and Farrokh Farrokhi
Brain Sci. 2024, 14(5), 452; https://doi.org/10.3390/brainsci14050452 - 30 Apr 2024
Abstract
Background: tinnitus is a common and often debilitating condition with limited evidence-based treatment options. Deep brain stimulation (DBS) is an approved treatment modality for certain neurological conditions; its experimental use as a treatment modality for severe tinnitus is novel and beginning to show
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Background: tinnitus is a common and often debilitating condition with limited evidence-based treatment options. Deep brain stimulation (DBS) is an approved treatment modality for certain neurological conditions; its experimental use as a treatment modality for severe tinnitus is novel and beginning to show promise. This systematic review focuses on the current evidence for the safety and efficacy of DBS for treatment of refractory tinnitus. Methods: a systematic search in PubMed and EMBASE was performed to identify peer-reviewed studies on DBS of non-cortical structures for the primary indication of tinnitus treatment. Three studies were identified as meeting these criteria, one of which had two related sub-studies. Results: seven patients with available data who underwent DBS for tinnitus were identified. DBS targets included nucleus accumbens (NAc), ventral anterior limb of the internal capsule (vALIC), caudate nucleus, and the medial geniculate body (MGB) of the thalamus. All studies used the Tinnitus Functional Index (TFI) as a primary outcome measure. DBS of the caudate was most commonly reported (n = 5), with a mean TFI improvement of 23.3 points. Only one subject underwent DBS targeting the NAc/vALIC (extrapolated TFI improvement 46.8) and one subject underwent DBS targeting the MGB (TFI improvement 59 points). Conclusions: DBS is a promising treatment option for refractory subjective tinnitus, with early data, from small patient cohorts in multiple studies, suggesting its safety and efficacy. Further studies with a larger patient population are needed to support this safety and efficacy before implementing this treatment to daily practice.
Full article
(This article belongs to the Special Issue Central Aspects of Tinnitus: Advances in Mechanisms and Neuromodulation)
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Open AccessArticle
Incorporating Evidence-Based Gamification and Machine Learning to Assess Preschool Executive Function: A Feasibility Study
by
Cassondra M. Eng, Aria Tsegai-Moore and Anna V. Fisher
Brain Sci. 2024, 14(5), 451; https://doi.org/10.3390/brainsci14050451 - 30 Apr 2024
Abstract
Computerized assessments and digital games have become more prevalent in childhood, necessitating a systematic investigation of the effects of gamified executive function assessments on performance and engagement. This study examined the feasibility of incorporating gamification and a machine learning algorithm that adapts task
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Computerized assessments and digital games have become more prevalent in childhood, necessitating a systematic investigation of the effects of gamified executive function assessments on performance and engagement. This study examined the feasibility of incorporating gamification and a machine learning algorithm that adapts task difficulty to individual children’s performance into a traditional executive function task (i.e., Flanker Task) with children ages 3–5. The results demonstrated that performance on a gamified version of the Flanker Task was associated with performance on the traditional version of the task and standardized academic achievement outcomes. Furthermore, gamification grounded in learning science and developmental psychology theories applied to a traditional executive function measure increased children’s task enjoyment while preserving psychometric properties of the Flanker Task. Overall, this feasibility study indicates that gamification and adaptive machine learning algorithms can be successfully incorporated into executive function assessments with young children to increase enjoyment and reduce data loss with developmentally appropriate and intentional practices.
Full article
(This article belongs to the Special Issue Executive Functioning Development—Measurements and Promotion in Naturalistic Setups)
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Open AccessArticle
Investigating Descending Pain Regulation in Fibromyalgia and the Link to Altered Autonomic Regulation by Means of Functional MRI Data
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Shima Hassanpour, Hannan Algitami, Maya Umraw, Jessica Merletti, Brieana Keast and Patrick W. Stroman
Brain Sci. 2024, 14(5), 450; https://doi.org/10.3390/brainsci14050450 - 30 Apr 2024
Abstract
Fibromyalgia syndrome (FM) is a chronic pain condition that affects a significant portion of the population; yet, this condition is still poorly understood. Prior research has suggested that individuals with FM display a heightened sensitivity to pain and signs of autonomic dysfunction. Recent
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Fibromyalgia syndrome (FM) is a chronic pain condition that affects a significant portion of the population; yet, this condition is still poorly understood. Prior research has suggested that individuals with FM display a heightened sensitivity to pain and signs of autonomic dysfunction. Recent advances in functional MRI analysis methods to model blood-oxygenation-level-dependent (BOLD) responses across networks of regions, and structural and physiological modeling (SAPM) have shown the potential to provide more detailed information about altered neural activity than was previously possible. Therefore, this study aimed to apply novel analysis methods to investigate altered neural processes underlying pain sensitivity in FM in functional magnetic resonance imaging (fMRI) data from the brainstem and spinal cord. Prior fMRI studies have shown evidence of functional differences in fibromyalgia (FM) within brain regions associated with pain’s motivational aspects, as well as differences in neural activity related to pain regulation, arousal, and autonomic homeostatic regulation within the brainstem and spinal cord regions. We, therefore, hypothesized that nociceptive processing is altered in FM compared to healthy controls (HCs) in the brainstem and spinal cord areas linked to autonomic function and descending pain regulation, including the parabrachial nuclei (PBN) and nucleus tractus solitarius (NTS). We expected that new details of this altered neural signaling would be revealed with SAPM. The results provide new evidence of altered neural signaling in FM related to arousal and autonomic homeostatic regulation. This further advances our understanding of the altered neural processing that occurs in women with FM.
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(This article belongs to the Special Issue New Perspectives in Chronic Pain Research: Focus on Neuroimaging)
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Open AccessArticle
Substance Addiction in Adolescents: Influence of Parenting and Personality Traits
by
Irene Escamilla, Nerea Juan, Ana Benito, Francisca Castellano-García, Francesc Rodríguez-Ruiz and Gonzalo Haro
Brain Sci. 2024, 14(5), 449; https://doi.org/10.3390/brainsci14050449 - 30 Apr 2024
Abstract
Background: Substance use in adolescents has been separately related to personality traits and parental socialization styles; in this study, our objective was to study these variables in an integrated way. Methods: A cross-sectional observational study was conducted in five institutes in a final
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Background: Substance use in adolescents has been separately related to personality traits and parental socialization styles; in this study, our objective was to study these variables in an integrated way. Methods: A cross-sectional observational study was conducted in five institutes in a final sample of 331 students, excluding those with gaming disorder. The sample was stratified into three subgroups: ‘no addiction’, ‘low risk’, and ‘high risk’ of Substance Use Disorders (SUD). Results: 12.9% of the adolescents presented a low risk of SUD, while 18.3% showed a high risk, with both being older (F = 9.16; p < 0.001) than the no addiction group. Adolescents with high risk scored lower in control and structure variables and higher in maternal and paternal indifference factors. Non-addicted subjects presented higher scores in conscientiousness, extraversion, and agreeableness and lower scores in neuroticism. The probability of SUD increased with age (OR = 2.187; p = 0.022), sensation seeking (OR = 1.084; p < 0.001), and neuroticism (OR = 1.049; p = 0.042), while conscientiousness was a protective factor (OR = 0.930; p = 0.008). Conclusions: These results reflect that personality traits are directly related to the development of substance abuse in adolescents.
Full article
(This article belongs to the Section Behavioral Neuroscience)
Open AccessArticle
Research on Brain Networks of Human Balance Based on Phase Estimation Synchronization
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Yifei Qiu and Zhizeng Luo
Brain Sci. 2024, 14(5), 448; https://doi.org/10.3390/brainsci14050448 - 29 Apr 2024
Abstract
Phase synchronization serves as an effective method for analyzing the synchronization of electroencephalogram (EEG) signals among brain regions and the dynamic changes of the brain. The purpose of this paper is to study the construction of the functional brain network (FBN) based on
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Phase synchronization serves as an effective method for analyzing the synchronization of electroencephalogram (EEG) signals among brain regions and the dynamic changes of the brain. The purpose of this paper is to study the construction of the functional brain network (FBN) based on phase synchronization, with a special focus on neural processes related to human balance regulation. This paper designed four balance paradigms of different difficulty by blocking vision or proprioception and collected 19-channel EEG signals. Firstly, the EEG sequences are segmented by sliding windows. The phase-locking value (PLV) of core node pairs serves as the phase-screening index to extract the valid data segments, which are recombined into new EEG sequences. Subsequently, the multichannel weighted phase lag index (wPLI) is calculated based on the new EEG sequences to construct the FBN. The experimental results show that due to the randomness of the time points of body balance adjustment, the degree of phase synchronization of the datasets screened by PLV is more obvious, improving the effective information expression of the subsequent EEG data segments. The FBN topological structures of the wPLI show that the connectivity of various brain regions changes structurally as the difficulty of human balance tasks increases. The frontal lobe area is the core brain region for information integration. When vision or proprioception is obstructed, the EEG synchronization level of the corresponding occipital lobe area or central area decreases. The synchronization level of the frontal lobe area increases, which strengthens the synergistic effect among the brain regions and compensates for the imbalanced response caused by the lack of sensory information. These results show the brain regional characteristics of the process of human balance regulation under different balance paradigms, providing new insights into endogenous neural mechanisms of standing balance and methods of constructing brain networks.
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(This article belongs to the Special Issue The Impact of Posture and Movement on Intrinsic Brain Activity)
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Open AccessArticle
Comparison of Depressive Symptoms between International and Domestic Students in a Japanese University: Pre- and Post-COVID-19 Pandemic
by
Yuki Shiratori, Takafumi Ogawa, Miho Ota, Noriko Sodeyama, Tetsuaki Arai and Hirokazu Tachikawa
Brain Sci. 2024, 14(5), 447; https://doi.org/10.3390/brainsci14050447 - 29 Apr 2024
Abstract
Background: The COVID-19 pandemic led to significant lifestyle changes and uncertainties, triggering a secondary wave of mental health issues in society. University students are especially susceptible to mental disorders. International students are considered more vulnerable due to limited emotional and financial support from
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Background: The COVID-19 pandemic led to significant lifestyle changes and uncertainties, triggering a secondary wave of mental health issues in society. University students are especially susceptible to mental disorders. International students are considered more vulnerable due to limited emotional and financial support from their families and difficulties accessing community support. Hence, we conducted a longitudinal analysis to compare depressive symptoms among international students before and during the pandemic. Methods: Data from depression screenings conducted at the University of Tsukuba in 2019 and 2020 were utilized. We included all students enrolled in 2019 who underwent health check-ups in both 2019 and 2020. Participants completed the Patient Health Questionnaire-9 (PHQ-9), enabling a comparison of item scores between domestic and international students. Psychopathological network analysis was employed to examine relationships among the items. Results: Prior to the pandemic, international students generally exhibited relatively good mental health compared with domestic students. During the 2020 pandemic, no significant difference was observed, but international students tended to demonstrate better mental health. However, network analysis revealed intergroup variations in the relationships among PHQ-9 items, with concentration problems and suicidal thoughts being more prominent among international students. Conclusion: This study’s findings suggest that young people studying abroad experience mental health crises similar to their domestic counterparts. Nevertheless, the patterns of these crises may differ between the two groups.
Full article
(This article belongs to the Special Issue The Effect of COVID-19 on Youth Mental Health)
Open AccessArticle
Revisiting Cognitive Deficits in Outpatients with Psychotic Disorders: A Transdiagnostic Comparison of Cognitive Performance While Accounting for Putative Confounding Factors
by
Mathias Konstantin Kammerer, Ulrike Nowak, Tania M. Lincoln and Katarina Krkovic
Brain Sci. 2024, 14(5), 446; https://doi.org/10.3390/brainsci14050446 - 29 Apr 2024
Abstract
Recent research suggests that cognitive deficits in individuals with psychotic disorders could be overestimated because poor cognitive test performance is partly attributable to non-cognitive factors. To further test this, we included non-hospitalized individuals with psychotic disorders (PSY, n = 38), individuals with attenuated
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Recent research suggests that cognitive deficits in individuals with psychotic disorders could be overestimated because poor cognitive test performance is partly attributable to non-cognitive factors. To further test this, we included non-hospitalized individuals with psychotic disorders (PSY, n = 38), individuals with attenuated psychotic symptoms (n = 40), individuals with obsessive-compulsive disorders (n = 39), and healthy controls (n = 38). Relevant cognitive domains were assessed using the MATRICS Consensus Cognitive Battery. Putative confounding non-cognitive factors—heart rate, self-reported stress, negative affect, performance-related beliefs, and actigraphy-derived sleep—were assessed before cognitive testing. A multivariate analysis of covariance was calculated to examine group differences in cognitive performance while controlling for non-cognitive factors. PSY showed decreased test performance in graphomotor speed, attention, and verbal tasks compared to the other groups, whereas non-verbal/visual-spatial tasks were unimpaired. After accounting for non-cognitive factors, group differences diminished in verbal learning, whereas differences in the other domains remained significant. Against our hypotheses, the present findings indicate that some cognitive deficits in PSY cannot be attributed to momentary confounding factors.
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(This article belongs to the Special Issue Cognitive Dysfunction in Schizophrenia)
Open AccessReview
CNS Germ Cell Tumors: Molecular Advances, Significance in Risk Stratification and Future Directions
by
Jiajun Zhou, Chenxing Wu and Shouwei Li
Brain Sci. 2024, 14(5), 445; https://doi.org/10.3390/brainsci14050445 - 29 Apr 2024
Abstract
Central Nervous System Germ Cell Tumors (CNS GCTs) represent a subtype of intracranial malignant tumors characterized by highly heterogeneous histology. Current diagnostic methods in clinical practice have notable limitations, and treatment strategies struggle to achieve personalized therapy based on patient risk stratification. Advances
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Central Nervous System Germ Cell Tumors (CNS GCTs) represent a subtype of intracranial malignant tumors characterized by highly heterogeneous histology. Current diagnostic methods in clinical practice have notable limitations, and treatment strategies struggle to achieve personalized therapy based on patient risk stratification. Advances in molecular genetics, biology, epigenetics, and understanding of the tumor microenvironment suggest the diagnostic potential of associated molecular alterations, aiding risk subgroup identification at diagnosis. Furthermore, they suggest the existence of novel therapeutic approaches targeting chromosomal alterations, mutated genes and altered signaling pathways, methylation changes, microRNAs, and immune checkpoints. Moving forward, further research is imperative to explore the pathogenesis of CNS GCTs and unravel the intricate interactions among various molecular alterations. Additionally, these findings require validation in clinical cohorts to assess their role in the diagnosis, risk stratification, and treatment of patients.
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(This article belongs to the Special Issue Innovation in Brain Tumor Treatment)
Open AccessArticle
DysDiTect: Dyslexia Identification Using CNN-Positional-LSTM-Attention Modeling with Chinese Dictation Task
by
Hey Wing Liu, Shuo Wang and Shelley Xiuli Tong
Brain Sci. 2024, 14(5), 444; https://doi.org/10.3390/brainsci14050444 - 29 Apr 2024
Abstract
Handwriting difficulty is a defining feature of Chinese developmental dyslexia (DD) due to the complex structure and dense information contained within compound characters. Despite previous attempts to use deep neural network models to extract handwriting features, the temporal property of writing characters in
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Handwriting difficulty is a defining feature of Chinese developmental dyslexia (DD) due to the complex structure and dense information contained within compound characters. Despite previous attempts to use deep neural network models to extract handwriting features, the temporal property of writing characters in sequential order during dictation tasks has been neglected. By combining transfer learning of convolutional neural network (CNN) and positional encoding with the temporal-sequential encoding of long short-term memory (LSTM) and attention mechanism, we trained and tested the model with handwriting images of 100,000 Chinese characters from 1064 children in Grades 2–6 (DD = 483; Typically Developing [TD] = 581). Using handwriting features only, the best model reached 83.2% accuracy, 79.2% sensitivity, 86.4% specificity, and 91.2% AUC. With grade information, the best model achieved 85.0% classification accuracy, 83.3% sensitivity, 86.4% specificity, and 89.7% AUC. These findings suggest the potential of utilizing machine learning technology to identify children at risk for dyslexia at an early age.
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(This article belongs to the Special Issue Statistical Learning and Machine Learning: Advances in Neurobiological and Computational Approaches)
Open AccessArticle
Enhanced Cognitive Inhibition in Table Tennis Athletes: Insights from Color-Word and Spatial Stroop Tasks
by
Qin Huang, Xuechen Mao, Jilong Shi, Jun Pan and Anmin Li
Brain Sci. 2024, 14(5), 443; https://doi.org/10.3390/brainsci14050443 - 29 Apr 2024
Abstract
The ability to inhibit conflicting information is pivotal in the dynamic and high-speed context of fast-ball sports. However, the behavioral and electrophysiological characteristics underlying the cognitive inhibition processes associated with table tennis expertise remain unexplored. This study aims to bridge these research gaps
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The ability to inhibit conflicting information is pivotal in the dynamic and high-speed context of fast-ball sports. However, the behavioral and electrophysiological characteristics underlying the cognitive inhibition processes associated with table tennis expertise remain unexplored. This study aims to bridge these research gaps by utilizing the color-word Stroop task and the spatial Stroop task alongside event-related potential (ERP) measurements to investigate domain-general and domain-specific cognitive inhibition among table tennis athletes. The study involved a total of 40 participants, including 20 table tennis athletes (11 males and 9 females; mean age 20.75 years) and 20 nonathletes (9 males and 11 females; mean age 19.80 years). The group differences in the Stroop effect on behavioral outcomes and ERP amplitudes were compared within each task, respectively. In the color-word Stroop tasks, athletes exhibited smaller incongruent-related negative potential amplitudes (Ninc; 300–400 ms; p = 0.036) and a diminished Stroop effect on late sustained potential amplitudes (LSP; 500–650 ms; p = 0.028) than nonathletes, although no significant differences were observed in behavioral outcomes (p > 0.05). Conversely, in the spatial Stroop tasks, athletes not only responded more swiftly but also exhibited reduced Stroop effects on both LSP amplitudes (350–500 ms; p = 0.004) and reaction times (p = 0.002) relative to nonathletes. These findings suggest that table tennis athletes excel in cognitive inhibition in the context of both domain-general and domain-specific tasks, particularly exhibiting enhanced performance in tasks that are closely aligned with the demands of their sport. Our results support the neural efficiency hypothesis and improve our understanding of the interactions between cognitive functions and table tennis expertise.
Full article
(This article belongs to the Special Issue Research on Executive Functions by EEG and fMRI)
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