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
A New Framework Combining Diffusion Models and the Convolution Classifier for Generating Images from EEG Signals
Brain Sci. 2024, 14(5), 478; https://doi.org/10.3390/brainsci14050478 - 8 May 2024
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The generation of images from electroencephalography (EEG) signals has become a popular research topic in recent research because it can bridge the gap between brain signals and visual stimuli and has wide application prospects in neuroscience and computer vision. However, due to the
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The generation of images from electroencephalography (EEG) signals has become a popular research topic in recent research because it can bridge the gap between brain signals and visual stimuli and has wide application prospects in neuroscience and computer vision. However, due to the high complexity of EEG signals, the reconstruction of visual stimuli through EEG signals continues to pose a challenge. In this work, we propose an EEG-ConDiffusion framework that involves three stages: feature extraction, fine-tuning of the pretrained model, and image generation. In the EEG-ConDiffusion framework, classification features of EEG signals are first obtained through the feature extraction block. Then, the classification features are taken as conditions to fine-tune the stable diffusion model in the image generation block to generate images with corresponding semantics. This framework combines EEG classification and image generation means to enhance the quality of generated images. Our proposed framework was tested on an EEG-based visual classification dataset. The performance of our framework is measured by classification accuracy, 50-way top-k accuracy, and inception score. The results indicate that the proposed EEG-Condiffusion framework can extract effective classification features and generate high-quality images from EEG signals to realize EEG-to-image conversion.
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Open AccessArticle
The Effect of Brain Anodal and Cathodal Transcranial Direct Current Stimulation on Psychological Refractory Period at Different Stimulus-Onset Asynchrony in Non-Fatigue and Mental Fatigue Conditions
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Somayeh Hafezi, Mohammadreza Doustan and Esmaeel Saemi
Brain Sci. 2024, 14(5), 477; https://doi.org/10.3390/brainsci14050477 - 8 May 2024
Abstract
The psychological refractory period (PRP) effect occurs when two stimuli that require separate responses are presented sequentially, particularly with a short and variable time interval between them. Fatigue is a suboptimal psycho-physiological state that leads to changes in strategies. In recent years, numerous
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The psychological refractory period (PRP) effect occurs when two stimuli that require separate responses are presented sequentially, particularly with a short and variable time interval between them. Fatigue is a suboptimal psycho-physiological state that leads to changes in strategies. In recent years, numerous studies have investigated the effects of transcranial direct current stimulation (tDCS) on motor control. The present study aimed to investigate the effects of two tDCS methods, anodal and cathodal, on PRP in ten different conditions of stimulus-onset asynchronies (SOAs) under non-fatigue and mental fatigue conditions. The participants involved 39 male university students aged 19 to 25 years. In the pre-test, they were assessed using the PRP measurement tool under both non-fatigue and mental fatigue conditions. The mental fatigue was induced by a 30-min Stroop task. The test consisted of two stimuli with different SOAs (50, 75, 100, 150, 300, 400, 600, 900, 1200, and 1500 ms). The first was a visual stimulus with three choices (letters A, B, and C). After a random SOA, the second stimulus, a visual stimulus with three choices (colors red, yellow, and blue), was presented. Subsequently, participants were randomly assigned to the anodal, cathodal, and sham stimulation groups and underwent four consecutive sessions of tDCS stimulation. In the anodal and cathodal stimulation groups, 20 min of tDCS stimulation were applied to the PLPFC area in each session, while in the sham group, the stimulation was artificially applied. All participants were assessed using the same measurement tools as in the pre-test phase, in a post-test phase one day after the last stimulation session, and in a follow-up phase four days after that. Inferential statistics include mixed ANOVA, one-way ANOVA, independent, and dependent t-tests. The findings indicated that the response time to the second stimulus was longer at lower SOAs. However, there was no significant difference between the groups in this regard. Additionally, there was no significant difference in response time to the second stimulus between the fatigue and non-fatigue conditions, or between the groups. Therefore, tDCS had no significant effect. There was a significant difference between mental fatigue and non-fatigue conditions in the psychological refractory period. Moreover, at lower SOAs, the PRP was longer than at higher SOAs. In conditions of fatigue, the active stimulation groups (anodal and cathodal) performed better than the sham stimulation group at higher SOAs. Considering the difference in response to both stimuli at different SOAs, some central aspects of the response can be simultaneously parallel. Fatigue also affects parallel processing. This study supports the response integration phenomenon in PRP, which predicts that there will be an increase in response time to the first stimulus as the interval between the presentation of the two stimuli increases. This finding contradicts the bottleneck model. In this study, the effectiveness of cathodal and anodal tDCS on response time to the second stimulus and PRP was found to be very small.
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(This article belongs to the Section Sensory and Motor Neuroscience)
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Ultrastructural Changes of Neuroendocrine Pheochromocytoma Cell Line PC-12 Exposed In Vitro to Rotenone
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Manuel Belli, Mario Cristina, Valeria Calabrese, Marta Russo, Marisa Granato, Matteo Antonio Russo and Luigi Sansone
Brain Sci. 2024, 14(5), 476; https://doi.org/10.3390/brainsci14050476 - 8 May 2024
Abstract
Rotenone is a pesticide used in research for its ability to induce changes similar, in vivo and in vitro, to those observed in Parkinson’s disease (PD). This includes a selective death of dopaminergic neurons in the substantia nigra. Nonetheless, the precise mechanism through
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Rotenone is a pesticide used in research for its ability to induce changes similar, in vivo and in vitro, to those observed in Parkinson’s disease (PD). This includes a selective death of dopaminergic neurons in the substantia nigra. Nonetheless, the precise mechanism through which rotenone modifies structure and function of neurons remains unclear. The PC12 cells closely resemble dopamine terminal neurons. This makes it a preferred model for studying the morphology of central dopamine neurons and predicting neurotoxicity. In this paper, we investigated the effects of 0.5 µM rotenone for 24–48 h on PC12 cell viability and ultrastructure (TEM), trying to identify primary and more evident alterations that can be related to neuronal damages similar to that seen in animal PD models. Cell viability decreased after 24 h rotenone treatment, with a further decrease after 48 h. Ultrastructural changes included vacuolar degeneration, mitochondrial mild swelling, decrease in the number of neuropeptide granules, and the loss of cell-to-cell adhesion. These findings are in agreement with previous research suggesting that rotenone, by inhibiting energy production and increasing ROS generation, is responsible for significant alterations of the ultrastructure and cell death of PC12 cells. Our data confirm the link between rotenone exposure, neuronal damage, and changes in dopamine metabolism, suggesting its role in the pathogenesis of PD.
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(This article belongs to the Special Issue Advanced Studies of the Neuron Model of Neurodegenerative Diseases)
Open AccessCorrection
Correction: Horne et al. White Matter Correlates of Domain-Specific Working Memory. Brain Sci. 2023, 13, 19
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Autumn Horne, Junhua Ding, Tatiana T. Schnur and Randi C. Martin
Brain Sci. 2024, 14(5), 475; https://doi.org/10.3390/brainsci14050475 - 8 May 2024
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Open AccessArticle
Gaze Orienting in the Social World: An Exploration of the Role Played by Caregiving Vocal and Tactile Behaviors in Infants with Visual Impairment and in Sighted Controls
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Serena Grumi, Elena Capelli, Federica Morelli, Luisa Vercellino, Eleonora Mascherpa, Chiara Ghiberti, Laura Carraro, Sabrina Signorini and Livio Provenzi
Brain Sci. 2024, 14(5), 474; https://doi.org/10.3390/brainsci14050474 - 8 May 2024
Abstract
Infant attention is a cognitive function that underlines sensory–motor integration processes at the interface between the baby and the surrounding physical and socio-relational environment, mainly with the caregivers. The investigation of the role of non-visual inputs (i.e., vocal and tactile) provided by the
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Infant attention is a cognitive function that underlines sensory–motor integration processes at the interface between the baby and the surrounding physical and socio-relational environment, mainly with the caregivers. The investigation of the role of non-visual inputs (i.e., vocal and tactile) provided by the caregivers in shaping infants’ attention in the context of visual impairment is relevant from both a theoretical and clinical point of view. This study investigated the social attention (i.e., gaze orientation) skills in a group of visually impaired (VI) and age-matched sighted controls (SCs) between 9 and 12 months of age. Moreover, the role of VI severity and maternal vocalizations and touch in shaping the social attention were investigated. Overall, 45 infants and their mothers participated in a video-recorded 4 min interaction procedure, including a play and a still-face episode. The infants’ gaze orientation (i.e., mother-directed, object-directed, or unfocused) and the types of maternal vocalizations and touch (i.e., socio-cognitive, affective) were micro-analytically coded. Maternal vocalizations and touch were found to influence gaze orientation differently in VI infants compared SCs. Moreover, the group comparisons during the play episode showed that controls were predominantly oriented to the mothers, while VI infants were less socially oriented. Visual impairment severity did not emerge as linked with social attention. These findings contribute to our understanding of socio-cognitive developmental trajectories in VI infants and highlight the need for tailored interventions to promote optimal outcomes for VI populations.
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(This article belongs to the Special Issue Behavioral and Neural Mechanisms Underlying Sensory–Motor Integration)
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Open AccessReview
Seizure-Related Head Injuries: A Narrative Review
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Sebastian Piwowarczyk, Paweł Obłój, Łukasz Janicki, Kornelia Kowalik, Adam Łukaszuk and Mariusz Siemiński
Brain Sci. 2024, 14(5), 473; https://doi.org/10.3390/brainsci14050473 - 8 May 2024
Abstract
Epilepsy is one of the most common neurological diseases. Epileptic seizures very often result in head injuries that may lead to many adverse consequences, both acute and chronic. They contribute to the need for hospitalization, modification of treatment, and a general decline in
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Epilepsy is one of the most common neurological diseases. Epileptic seizures very often result in head injuries that may lead to many adverse consequences, both acute and chronic. They contribute to the need for hospitalization, modification of treatment, and a general decline in social productivity. The objective of our review is to characterize and assess management aspects of seizure-related head injuries (SRHIs) as an important and frequent clinical problem present in emergency department settings. PubMed and other relevant databases and websites were systematically searched for articles on traumatic brain injuries connected with the occurrence of seizures published from inception to 9 April 2024; then, we reviewed the available literature. Our review showed that SRHIs can lead to various acute complications, in some cases requiring hospitalization and neurosurgical intervention. Long-term complications and cognitive decline after injury might be present, eventually implying a negative impact on a patient’s quality of life. Despite being frequent and clinically important, there are still no widely accepted, uniform recommendations for the management of patients with SRHIs. As such, a concise and standardized protocol for the management of seizure-related head injuries in emergency departments is worth consideration.
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(This article belongs to the Section Neuropharmacology and Neuropathology)
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Subtle Patterns of Altered Responsiveness to Delayed Auditory Feedback during Finger Tapping in People Who Stutter
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Giorgio Lazzari, Robert van de Vorst, Floris T. van Vugt and Carlotta Lega
Brain Sci. 2024, 14(5), 472; https://doi.org/10.3390/brainsci14050472 - 7 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.
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(This article belongs to the Special Issue Behavioral and Neural Mechanisms Underlying Sensory–Motor Integration)
Open AccessReview
Nanoplastics and Neurodegeneration in ALS
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Andrew Eisen, Erik P. Pioro, Stephen A. Goutman and Matthew C. Kiernan
Brain Sci. 2024, 14(5), 471; https://doi.org/10.3390/brainsci14050471 - 7 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.
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(This article belongs to the Special Issue Amyotrophic Lateral Sclerosis: Recent Considerations for Diagnosis, Pathogenesis and Therapy)
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Biomarkers of Immersion in Virtual Reality Based on Features Extracted from the EEG Signals: A Machine Learning Approach
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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 - 7 May 2024
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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
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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.
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(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
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Min Feng and Juncai Xu
Brain Sci. 2024, 14(5), 469; https://doi.org/10.3390/brainsci14050469 - 7 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.
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(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
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Jassem Bourahmah, Akira Sakurai and Andrey L. Shilnikov
Brain Sci. 2024, 14(5), 468; https://doi.org/10.3390/brainsci14050468 - 7 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.
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(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
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Qingping He, Qi Qi, Gordon C. Ibeanu and P. Andy Li
Brain Sci. 2024, 14(5), 467; https://doi.org/10.3390/brainsci14050467 - 7 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.
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(This article belongs to the Section Molecular and Cellular Neuroscience)
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A Methodological Approach to Quantifying Silent Pauses, Speech Rate, and Articulation Rate across Distinct Narrative Tasks: Introducing the Connected Speech Analysis Protocol (CSAP)
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Georgia Angelopoulou, Dimitrios Kasselimis, Dionysios Goutsos and Constantin Potagas
Brain Sci. 2024, 14(5), 466; https://doi.org/10.3390/brainsci14050466 - 7 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.
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(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 - 7 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.
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(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
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Vijayakumar Mavanji, Brianna L. Pomonis, Laurie Shekels and Catherine M. Kotz
Brain Sci. 2024, 14(5), 464; https://doi.org/10.3390/brainsci14050464 - 7 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 - 6 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
by
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 - 3 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
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 - 2 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 - 2 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 - 1 May 2024
Abstract
Individuals with neurological and neuropsychiatric disorders face a variety of difficulties that can significantly impact their daily lives [...]
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(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)
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