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
Subtle Patterns of Altered Responsiveness to Delayed Auditory Feedback during Finger Tapping in People Who Stutter
Brain Sci. 2024, 14(5), 472; https://doi.org/10.3390/brainsci14050472 (registering DOI) - 07 May 2024
Abstract
Differences in sensorimotor integration mechanisms have been observed between people who stutter (PWS) and controls who do not. Delayed auditory feedback (DAF) introduces timing discrepancies between perception and action, disrupting sequence production in verbal and non-verbal domains. While DAF consistently enhances speech fluency
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Differences in sensorimotor integration mechanisms have been observed between people who stutter (PWS) and controls who do not. Delayed auditory feedback (DAF) introduces timing discrepancies between perception and action, disrupting sequence production in verbal and non-verbal domains. While DAF consistently enhances speech fluency in PWS, its impact on non-verbal sensorimotor synchronization abilities remains unexplored. A total of 11 PWS and 13 matched controls completed five tasks: (1) unpaced tapping; (2) synchronization-continuation task (SCT) without auditory feedback; (3) SCT with DAF, with instruction either to align the sound in time with the metronome; or (4) to ignore the sound and align their physical tap to the metronome. Additionally, we measured participants’ sensitivity to detecting delayed feedback using a (5) delay discrimination task. Results showed that DAF significantly affected performance in controls as a function of delay duration, despite being irrelevant to the task. Conversely, PWS performance remained stable across delays. When auditory feedback was absent, no differences were found between PWS and controls. Moreover, PWS were less able to detect delays in speech and tapping tasks. These findings show subtle differences in non-verbal sensorimotor performance between PWS and controls, specifically when action–perception loops are disrupted by delays, contributing to models of sensorimotor integration in stuttering.
Full article
(This article belongs to the Special Issue Behavioral and Neural Mechanisms Underlying Sensory–Motor Integration)
Open AccessReview
Nanoplastics and Neurodegeneration in ALS
by
Andrew Eisen, Erik P. Pioro, Stephen A. Goutman and Matthew C. Kiernan
Brain Sci. 2024, 14(5), 471; https://doi.org/10.3390/brainsci14050471 (registering DOI) - 07 May 2024
Abstract
Plastic production, which exceeds one million tons per year, is of global concern. The constituent low-density polymers enable spread over large distances and micro/nano particles (MNPLs) induce organ toxicity via digestion, inhalation, and skin contact. Particles have been documented in all human tissues
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Plastic production, which exceeds one million tons per year, is of global concern. The constituent low-density polymers enable spread over large distances and micro/nano particles (MNPLs) induce organ toxicity via digestion, inhalation, and skin contact. Particles have been documented in all human tissues including breast milk. MNPLs, especially weathered particles, can breach the blood–brain barrier, inducing neurotoxicity. This has been documented in non-human species, and in human-induced pluripotent stem cell lines. Within the brain, MNPLs initiate an inflammatory response with pro-inflammatory cytokine production, oxidative stress with generation of reactive oxygen species, and mitochondrial dysfunction. Glutamate and GABA neurotransmitter dysfunction also ensues with alteration of excitatory/inhibitory balance in favor of reduced inhibition and resultant neuro-excitation. Inflammation and cortical hyperexcitability are key abnormalities involved in the pathogenic cascade of amyotrophic lateral sclerosis (ALS) and are intricately related to the mislocalization and aggregation of TDP-43, a hallmark of ALS. Water and many foods contain MNPLs and in humans, ingestion is the main form of exposure. Digestion of plastics within the gut can alter their properties, rendering them more toxic, and they cause gut microbiome dysbiosis and a dysfunctional gut–brain axis. This is recognized as a trigger and/or aggravating factor for ALS. ALS is associated with a long (years or decades) preclinical period and neonates and infants are exposed to MNPLs through breast milk, milk substitutes, and toys. This endangers a time of intense neurogenesis and establishment of neuronal circuitry, setting the stage for development of neurodegeneration in later life. MNPL neurotoxicity should be considered as a yet unrecognized risk factor for ALS and related diseases.
Full article
(This article belongs to the Special Issue Amyotrophic Lateral Sclerosis: Recent Considerations for Diagnosis, Pathogenesis and Therapy)
Open AccessArticle
Biomarkers of Immersion in Virtual Reality Based on Features Extracted from the EEG Signals: A Machine Learning Approach
by
Hamed Tadayyoni, Michael S. Ramirez Campos, Alvaro Joffre Uribe Quevedo and Bernadette A. Murphy
Brain Sci. 2024, 14(5), 470; https://doi.org/10.3390/brainsci14050470 - 07 May 2024
Abstract
Virtual reality (VR) enables the development of virtual training frameworks suitable for various domains, especially when real-world conditions may be hazardous or impossible to replicate because of unique additional resources (e.g., equipment, infrastructure, people, locations). Although VR technology has significantly advanced in recent
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Virtual reality (VR) enables the development of virtual training frameworks suitable for various domains, especially when real-world conditions may be hazardous or impossible to replicate because of unique additional resources (e.g., equipment, infrastructure, people, locations). Although VR technology has significantly advanced in recent years, methods for evaluating immersion (i.e., the extent to which the user is engaged with the sensory information from the virtual environment or is invested in the intended task) continue to rely on self-reported questionnaires, which are often administered after using the virtual scenario. Having an objective method to measure immersion is particularly important when using VR for training, education, and applications that promote the development, fine-tuning, or maintenance of skills. The level of immersion may impact performance and the translation of knowledge and skills to the real-world. This is particularly important in tasks where motor skills are combined with complex decision making, such as surgical procedures. Efforts to better measure immersion have included the use of physiological measurements including heart rate and skin response, but so far they do not offer robust metrics that provide the sensitivity to discriminate different states (idle, easy, and hard), which is critical when using VR for training to determine how successful the training is in engaging the user’s senses and challenging their cognitive capabilities. In this study, electroencephalography (EEG) data were collected from 14 participants who completed VR jigsaw puzzles with two different levels of task difficulty. Machine learning was able to accurately classify the EEG data collected during three different states, obtaining accuracy rates of 86% and 97% for differentiating easy versus hard difficulty states and baseline vs. VR states. Building on these results may enable the identification of robust biomarkers of immersion in VR, enabling real-time recognition of the level of immersion that can be used to design more effective and translative VR-based training. This method has the potential to adjust aspects of VR related to task difficulty to ensure that participants are immersed in VR.
Full article
(This article belongs to the Special Issue Advances of AI in Neuroimaging)
Open AccessArticle
Electroencephalogram-Based ConvMixer Architecture for Recognizing Attention Deficit Hyperactivity Disorder in Children
by
Min Feng and Juncai Xu
Brain Sci. 2024, 14(5), 469; https://doi.org/10.3390/brainsci14050469 - 07 May 2024
Abstract
Attention deficit hyperactivity disorder (ADHD) is a neuro-developmental disorder that affects approximately 5–10% of school-aged children worldwide. Early diagnosis and intervention are essential to improve the quality of life of patients and their families. In this study, we propose ConvMixer-ECA, a novel deep
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Attention deficit hyperactivity disorder (ADHD) is a neuro-developmental disorder that affects approximately 5–10% of school-aged children worldwide. Early diagnosis and intervention are essential to improve the quality of life of patients and their families. In this study, we propose ConvMixer-ECA, a novel deep learning architecture that combines ConvMixer with efficient channel attention (ECA) blocks for the accurate diagnosis of ADHD using electroencephalogram (EEG) signals. The model was trained and evaluated using EEG recordings from 60 healthy children and 61 children with ADHD. A series of experiments were conducted to evaluate the performance of the ConvMixer-ECA. The results showed that the ConvMixer-ECA performed well in ADHD recognition with 94.52% accuracy. The incorporation of attentional mechanisms, in particular ECA, improved the performance of ConvMixer; it outperformed other attention-based variants. In addition, ConvMixer-ECA outperformed state-of-the-art deep learning models including EEGNet, CNN, RNN, LSTM, and GRU. t-SNE visualization of the output of this model layer validated the effectiveness of ConvMixer-ECA in capturing the underlying patterns and features that separate ADHD from typically developing individuals through hierarchical feature learning. These outcomes demonstrate the potential of ConvMixer-ECA as a valuable tool to assist clinicians in the early diagnosis and intervention of ADHD in children.
Full article
(This article belongs to the Special Issue Diagnosis and Prediction of Neurological Diseases: Application of EEG-Based Technology)
Open AccessArticle
Error Function Optimization to Compare Neural Activity and Train Blended Rhythmic Networks
by
Jassem Bourahmah, Akira Sakurai and Andrey L. Shilnikov
Brain Sci. 2024, 14(5), 468; https://doi.org/10.3390/brainsci14050468 - 07 May 2024
Abstract
We present a novel set of quantitative measures for “likeness” (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of their mathematical models. Our innovative “blended” system approach offers an objective,
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We present a novel set of quantitative measures for “likeness” (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of their mathematical models. Our innovative “blended” system approach offers an objective, high-throughput, and computationally efficient method for comparing biological and mathematical models. This approach involves using voltage recordings of biological neurons to drive and train mathematical models, facilitating the derivation of the error function for further parameter optimization. Our calibration process incorporates measurements such as action potential (AP) frequency, voltage moving average, voltage envelopes, and the probability of post-synaptic channels. To assess the effectiveness of our method, we utilized the sea slug Melibe leonina swim central pattern generator (CPG) as our model circuit and conducted electrophysiological experiments with TTX to isolate CPG interneurons. During the comparison of biological recordings and mathematically simulated neurons, we performed a grid search of inhibitory and excitatory synapse conductance. Our findings indicate that a weighted sum of simple functions is essential for comprehensively capturing a neuron’s rhythmic activity. Overall, our study suggests that our blended system approach holds promise for enabling objective and high-throughput comparisons between biological and mathematical models, offering significant potential for advancing research in neural circuitry and related fields.
Full article
(This article belongs to the Special Issue Recent Advances in Neuroinformatics)
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Open AccessArticle
B355252 Suppresses LPS-Induced Neuroinflammation in the Mouse Brain
by
Qingping He, Qi Qi, Gordon C. Ibeanu and P. Andy Li
Brain Sci. 2024, 14(5), 467; https://doi.org/10.3390/brainsci14050467 - 07 May 2024
Abstract
B355252 is a small molecular compound known for potentiating neural growth factor and protecting against neuronal cell death induced by glutamate in vitro and cerebral ischemia in vivo. However, its other biological functions remain unclear. This study aims to investigate whether B355252 suppresses
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B355252 is a small molecular compound known for potentiating neural growth factor and protecting against neuronal cell death induced by glutamate in vitro and cerebral ischemia in vivo. However, its other biological functions remain unclear. This study aims to investigate whether B355252 suppresses neuroinflammatory responses and cell death in the brain. C57BL/6j mice were intraperitoneally injected with a single dosage of lipopolysaccharide (LPS, 1 mg/kg) to induce inflammation. B355252 (1 mg/kg) intervention was started two days prior to the LPS injection. The animal behavioral changes were assessed pre- and post-LPS injections. The animal brains were harvested at 4 and 24 h post-LPS injection, and histological, biochemical, and cytokine array outcomes were examined. Results showed that B355252 improved LPS-induced behavioral deterioration, mitigated brain tissue damage, and suppressed the activation of microglial and astrocytes. Furthermore, B355252 reduced the protein levels of key pyroptotic markers TLR4, NLRP3, and caspase-1 and inhibited the LPS-induced increases in IL-1β, IL-18, and cytokines. In conclusion, B355252 demonstrates a potent anti-neuroinflammatory effect in vivo, suggesting that its potential therapeutic value warrants further investigation.
Full article
(This article belongs to the Section Molecular and Cellular Neuroscience)
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Open AccessArticle
A Methodological Approach to Quantifying Silent Pauses, Speech Rate, and Articulation Rate across Distinct Narrative Tasks: Introducing the Connected Speech Analysis Protocol (CSAP)
by
Georgia Angelopoulou, Dimitrios Kasselimis, Dionysios Goutsos and Constantin Potagas
Brain Sci. 2024, 14(5), 466; https://doi.org/10.3390/brainsci14050466 - 07 May 2024
Abstract
The examination of connected speech may serve as a valuable tool for exploring speech output in both healthy speakers and individuals with language disorders. Numerous studies incorporate various fluency and silence measures into their analyses to investigate speech output patterns in different populations,
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The examination of connected speech may serve as a valuable tool for exploring speech output in both healthy speakers and individuals with language disorders. Numerous studies incorporate various fluency and silence measures into their analyses to investigate speech output patterns in different populations, along with the underlying cognitive processes that occur while speaking. However, methodological inconsistencies across existing studies pose challenges in comparing their results. In the current study, we introduce CSAP (Connected Speech Analysis Protocol), which is a specific methodological approach to investigate fluency metrics, such as articulation rate and speech rate, as well as silence measures, including silent pauses’ frequency and duration. We emphasize the importance of employing a comprehensive set of measures within a specific methodological framework to better understand speech output patterns. Additionally, we advocate for the use of distinct narrative tasks for a thorough investigation of speech output in different conditions. We provide an example of data on which we implement CSAP to showcase the proposed pipeline. In conclusion, CSAP offers a comprehensive framework for investigating speech output patterns, incorporating fluency metrics and silence measures in distinct narrative tasks, thus allowing a detailed quantification of connected speech in both healthy and clinical populations. We emphasize the significance of adopting a unified methodological approach in connected speech studies, enabling the integration of results for more robust and generalizable conclusions.
Full article
(This article belongs to the Special Issue Artificial Intelligence Methods for Assessing Speech, Language, and Communication Functioning)
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Open AccessArticle
ChatGPT for Tinnitus Information and Support: Response Accuracy and Retest after Three and Six Months
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W. Wiktor Jedrzejczak, Piotr H. Skarzynski, Danuta Raj-Koziak, Milaine Dominici Sanfins, Stavros Hatzopoulos and Krzysztof Kochanek
Brain Sci. 2024, 14(5), 465; https://doi.org/10.3390/brainsci14050465 - 07 May 2024
Abstract
Testing of ChatGPT has recently been performed over a diverse range of topics. However, most of these assessments have been based on broad domains of knowledge. Here, we test ChatGPT’s knowledge of tinnitus, an important but specialized aspect of audiology and otolaryngology. Testing
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Testing of ChatGPT has recently been performed over a diverse range of topics. However, most of these assessments have been based on broad domains of knowledge. Here, we test ChatGPT’s knowledge of tinnitus, an important but specialized aspect of audiology and otolaryngology. Testing involved evaluating ChatGPT’s answers to a defined set of 10 questions on tinnitus. Furthermore, given the technology is advancing quickly, we re-evaluated the responses to the same 10 questions 3 and 6 months later. The accuracy of the responses was rated by 6 experts (the authors) using a Likert scale ranging from 1 to 5. Most of ChatGPT’s responses were rated as satisfactory or better. However, we did detect a few instances where the responses were not accurate and might be considered somewhat misleading. Over the first 3 months, the ratings generally improved, but there was no more significant improvement at 6 months. In our judgment, ChatGPT provided unexpectedly good responses, given that the questions were quite specific. Although no potentially harmful errors were identified, some mistakes could be seen as somewhat misleading. ChatGPT shows great potential if further developed by experts in specific areas, but for now, it is not yet ready for serious application.
Full article
(This article belongs to the Special Issue Advances in Tinnitus and Hearing Disorders)
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Open AccessArticle
Interactions between Lateral Hypothalamic Orexin and Dorsal Raphe Circuitry in Energy Balance
by
Vijayakumar Mavanji, Brianna L. Pomonis, Laurie Shekels and Catherine M. Kotz
Brain Sci. 2024, 14(5), 464; https://doi.org/10.3390/brainsci14050464 - 07 May 2024
Abstract
Orexin/hypocretin terminals innervate the dorsal raphe nucleus (DRN), which projects to motor control areas important for spontaneous physical activity (SPA) and energy expenditure (EE). Orexin receptors are expressed in the DRN, and obesity-resistant (OR) rats show higher expression of these receptors in the
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Orexin/hypocretin terminals innervate the dorsal raphe nucleus (DRN), which projects to motor control areas important for spontaneous physical activity (SPA) and energy expenditure (EE). Orexin receptors are expressed in the DRN, and obesity-resistant (OR) rats show higher expression of these receptors in the DRN and elevated SPA/EE. We hypothesized that orexin-A in the DRN enhances SPA/EE and that DRN-GABA modulates the effect of orexin-A on SPA/EE. We manipulated orexin tone in the DRN either through direct injection of orexin-A or through the chemogenetic activation of lateral-hypothalamic (LH) orexin neurons. In the orexin neuron activation experiment, fifteen minutes prior to the chemogenetic activation of orexin neurons, the mice received either the GABA-agonist muscimol or antagonist bicuculline injected into the DRN, and SPA/EE was monitored for 24 h. In a separate experiment, orexin-A was injected into the DRN to study the direct effect of DRN orexin on SPA/EE. We found that the activation of orexin neurons elevates SPA/EE, and manipulation of GABA in the DRN does not alter the SPA response to orexin neuron activation. Similarly, intra-DRN orexin-A enhanced SPA and EE in the mice. These results suggest that orexin-A in the DRN facilitates negative energy balance by increasing physical activity-induced EE, and that modulation of DRN orexin-A is a potential strategy to promote SPA and EE.
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(This article belongs to the Section Molecular and Cellular Neuroscience)
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Open AccessArticle
Assessment of Suicide Risk in Patients with Depressive Episodes Due to Affective Disorders and Borderline Personality Disorder: A Pilot Comparative Study
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Elena Rudolfovna Isaeva, Daria Maksimovna Ryzhova, Anna Vladimirovna Stepanova and Ivo Nestorov Mitrev
Brain Sci. 2024, 14(5), 463; https://doi.org/10.3390/brainsci14050463 - 06 May 2024
Abstract
This study assessed suicidal risk in patients suffering from non-psychotic depressive disorders within various clinical and nosological forms (F31–F34 mood disorders and F60.31—emotionally unstable personality disorder). Clinical and psychological features were presented, as well as predictors of suicidal risk in patients of these
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This study assessed suicidal risk in patients suffering from non-psychotic depressive disorders within various clinical and nosological forms (F31–F34 mood disorders and F60.31—emotionally unstable personality disorder). Clinical and psychological features were presented, as well as predictors of suicidal risk in patients of these groups. We performed a comparative analysis of the anxiety and depression level, the level of mental pain, fear of death and the severity of anti-suicidal motives in patients with affective disorders and borderline personality disorder (BPD). Based on the results, 100% of patients in these clinical nosological groups were found to have a high level of suicidal risk. Patients with affective disorders have weak anti-suicidal motives and are not fully aware of the consequences of their own death. Patients with BPD have a higher suicidal risk than patients with affective disorders; they are characterized by less pronounced social orientation, demonstrativeness, self-centeredness, less pronounced levels of anxiety and fear of death.
Full article
(This article belongs to the Special Issue Anxious Brain: Stress Influence on the Nervous System)
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Open AccessArticle
Motor Imagery Classification Using Effective Channel Selection of Multichannel EEG
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Abdullah Al Shiam, Kazi Mahmudul Hassan, Md. Rabiul Islam, Ahmed M. M. Almassri, Hiroaki Wagatsuma and Md. Khademul Islam Molla
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.
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(This article belongs to the Special Issue EEG and Event-Related Potentials)
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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
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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 [...]
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(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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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.
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(This article belongs to the Section Neurodegenerative Diseases)
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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.
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(This article belongs to the Special Issue Children with Autism Spectrum Disorders: Current Situation and Prospects)
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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.
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(This article belongs to the Special Issue Clinical and Biological Correlates of Emotional Dysregulation in Children and Adolescents: A Transdiagnostic Approach to Developmental Psychopathology)
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