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 12.9 days after submission; acceptance to publication is undertaken in 2.5 days (median values for papers published in this journal in the first half of 2024).
- 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:
2.7 (2023);
5-Year Impact Factor:
3.0 (2023)
Latest Articles
Early Diagnosis of CNS Virus Infections from Neurological Autoimmune Diseases: A Cross-Sectional Study from China in ER Setting
Brain Sci. 2024, 14(9), 888; https://doi.org/10.3390/brainsci14090888 (registering DOI) - 30 Aug 2024
Abstract
It is challenging to differentiate between central nervous system (CNS) virus infections and neurological autoimmune diseases in the emergency department. Considering their different pathogenesis, we assume they differ in neuropsychiatric symptoms and laboratory results. A total of 80 patients were included in this
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It is challenging to differentiate between central nervous system (CNS) virus infections and neurological autoimmune diseases in the emergency department. Considering their different pathogenesis, we assume they differ in neuropsychiatric symptoms and laboratory results. A total of 80 patients were included in this study, 50 with CNS virus infections and 30 with CNS autoimmune diseases, confirmed by a polymerase chain reaction (PCR) of cerebrospinal fluid (CSF). A binary logistic regression model and receiver operating characteristic (ROC) curve were employed to examine the discrimination between the two types of diseases based on neuropsychiatric symptoms and laboratory results. Compared to patients with neurological autoimmune diseases, patients with CNS virus infections had a higher incidence of abnormal behavior (p = 0.026) and abnormal sensation/thought (p = 0.029); higher total (p = 0.005), direct (p = 0.004), and indirect bilirubin (p = 0.004); and increased CSF cell (p = 0.01) and CSF white cell counts (p = 0.01). Patients with disturbance of consciousness and abnormal sensation/thought were 7.79-fold and 5.07-fold more likely to be diagnosed with CNS virus infections (OR = 7.79, p = 0.008; OR = 5.07, p = 0.032). Each unit increase in blood indirect bilirubin concentration and CSF white cell counts increased the risk of developing CNS virus infections by 1.25-fold and 1.01-fold (OR = 1.25, p = 0.016; OR = 1.01, p = 0.011). ROC analysis showed that the area under the curve was 88.0% (p < 0.001). Our study found that patients with CNS viral infections tend to have higher blood indirect bilirubin concentration, CSF leukocyte count, frequency of disorders of consciousness, and abnormal sensation and thought, which may help differentiate them from those with neurological autoimmune diseases.
Full article
(This article belongs to the Special Issue New Advances in Neuroimmunology and Neuroinflammation)
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Open AccessArticle
Comparative Analysis of Brain Coping Mechanisms in Small Left-Hemisphere Lesions: Incidental vs. Symptomatic Gliomas
by
Elisa Cargnelutti, Tamara Ius, Marta Maieron, Serena D’Agostini, Miran Skrap and Barbara Tomasino
Brain Sci. 2024, 14(9), 887; https://doi.org/10.3390/brainsci14090887 - 30 Aug 2024
Abstract
Background. Incidentally discovered low-grade gliomas (iLGGs) are very rare and little is still known about their associated functional imaging activation patterns, white-matter status, and plasticity potential. Recent studies shed light on several clinical factors responsible for the good clinical status observed in these
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Background. Incidentally discovered low-grade gliomas (iLGGs) are very rare and little is still known about their associated functional imaging activation patterns, white-matter status, and plasticity potential. Recent studies shed light on several clinical factors responsible for the good clinical status observed in these patients versus those with their symptomatic counterpart (sLGGs), including small volume. Comparisons were typically carried out by comparing iLGGs with the wider and more heterogeneous sLGG group. In this study, we investigated whether iLGGs affect the brain differently from comparably small sLGGs. Method. Starting from a sample of 13 patients with iLGG, in the current comparative cross-sectional study, we identified a group of patients with sLGGs, primarily matched by lesion volume. We looked for potential differences between the two groups in language-related functional and structural parameters (the fMRI network associated with naming and white-matter fascicles). Results. The t-test did not show significant differences in the fMRI network, but these emerged when performing masking. No significant differences were observed at the white-matter level. Conclusions. Given that small volumes characterized both groups and that demographic variables were comparable, too, we hypothesized that differences between the two groups could be attributed to alternative lesion-related parameters. We discussed these findings from clinical and neurosurgical perspectives.
Full article
(This article belongs to the Section Neuropsychology)
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Open AccessEditorial
From Bench to Bedside: Motor–Cognitive Interactions
by
Daniele Corbo
Brain Sci. 2024, 14(9), 886; https://doi.org/10.3390/brainsci14090886 - 30 Aug 2024
Abstract
The capacity of humans to learn new motor abilities is known as motor learning, which is often understood as increasing movement precision over time and space through repetition [...]
Full article
(This article belongs to the Special Issue From Bench to Bedside: Motor-Cognitive Interactions)
Open AccessArticle
Involvement of Subinsular Territory Stroke as Predictor of Outcome after Successful Endovascular Recanalization of Left Middle Cerebral Artery Occlusion
by
Yasuyuki Yoshida, Tatsushi Mutoh, Yasuko Tatewaki, Yasuyuki Taki, Junta Moroi and Tatsuya Ishikawa
Brain Sci. 2024, 14(9), 885; https://doi.org/10.3390/brainsci14090885 - 30 Aug 2024
Abstract
Subinsular stroke (subIS) can occur between the penetrating middle cerebral artery (MCA) branches, which clinical and radiological findings sometimes encounter in patients after the recanalization of left proximal MCA occlusion. However, no supportive data are available to clarify this relationship. This study investigated
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Subinsular stroke (subIS) can occur between the penetrating middle cerebral artery (MCA) branches, which clinical and radiological findings sometimes encounter in patients after the recanalization of left proximal MCA occlusion. However, no supportive data are available to clarify this relationship. This study investigated whether the involvement of subIS can impact outcomes after successful reperfusion therapy. Data from 152 consecutive patients who underwent endovascular thrombectomy between 2019 and 2023 were collected. A 3-month functional independence defined as a modified Rankin Scale 0–2 (primary outcome) and influencing factors were analyzed retrospectively. Recanalization was achieved in 35 patients, of whom 11 (31%) developed subIS. Patients with subIS were older in age (81 vs. 75; p < 0.05), had lower apparent diffusion coefficient (ADC) values on admission (0.52 vs. 0.62; p < 0.001), and higher modified Rankin Scale (mRS) scores (4 vs. 2; p < 0.001) than those without subIS. In a multivariate analysis, subIS was independently associated with a worse functional outcome (odds ratio: 10.5, p = 0.02). The cut-off value of the ADCs was 0.52 with a sensitivity and specificity of 70% and 64%, respectively. Subinsular ischemic lesions contribute to poor functional independence in patients after the successful recanalization of left MCA occlusion. The attenuation of the ADC value in these territories could be a valuable predictor of the outcome.
Full article
(This article belongs to the Special Issue Initial Assessment and Management of Acute Stroke)
Open AccessArticle
Gender Differences in Prefrontal Cortex Response to Negative Emotional Stimuli in Drivers
by
Ferran Balada, Anton Aluja, Óscar García, Neus Aymamí and Luis F. García
Brain Sci. 2024, 14(9), 884; https://doi.org/10.3390/brainsci14090884 - 30 Aug 2024
Abstract
Background: Road safety improvement is a governmental priority due to driver-caused accidents. Driving style variation affects safety, with emotional regulation being pivotal. However, functional near-infrared spectroscopy (fNIRS) studies show inconsistent prefrontal cortex activity during emotion processing. This study examines prefrontal cortex response to
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Background: Road safety improvement is a governmental priority due to driver-caused accidents. Driving style variation affects safety, with emotional regulation being pivotal. However, functional near-infrared spectroscopy (fNIRS) studies show inconsistent prefrontal cortex activity during emotion processing. This study examines prefrontal cortex response to negative emotional stimuli, particularly traffic accident images, across drivers diverse in age and gender. Method: The study involved 118 healthy males (44.38 ± 12.98 years) and 84 females (38.89 ± 10.60 years). The Multidimensional Driving Style Inventory (MDSI) was used to assess driving behavior alongside fNIRS recordings. Participants viewed traffic accident and neutral images while prefrontal oxygenation was monitored. Results: Women rated traffic accidents (t-test = 2.43; p < 0.016) and neutral images (t-test = 2.19; p < 0.030) lower in valence than men. Arousal differences were significant for traffic accident images (t-test = −3.06; p < 0.002). correlational analysis found an inverse relationship between Dissociative scale scores and oxygenation (all p-values ≤ 0.013). Greater prefrontal oxygenation occurred with neutral images compared to traffic accidents. Left hemisphere differences (t-test = 3.23; p < 0.001) exceeded right hemisphere differences (t-test = 2.46; p < 0.015). Subgroup analysis showed male participants to be driving these disparities. Among adaptive drivers, significant oxygenation differences between neutral and accident images were evident in both hemispheres (left: t-test = 2.72, p < 0.009; right: t-test = 2.22, p < 0.030). Conclusions: Male drivers with maladaptive driving styles, particularly dissociative ones, exhibit reduced prefrontal oxygenation when exposed to neutral and traffic accident images. This response was absent in female drivers, with no notable age-related differences.
Full article
(This article belongs to the Section Neuropsychology)
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Open AccessArticle
Ongoing Dynamics of Peak Alpha Frequency Characterize Hypnotic Induction in Highly Hypnotic-Susceptible Individuals
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Mathieu Landry, Jason da Silva Castanheira, Floriane Rousseaux, Pierre Rainville, David Ogez and Karim Jerbi
Brain Sci. 2024, 14(9), 883; https://doi.org/10.3390/brainsci14090883 - 30 Aug 2024
Abstract
Hypnotic phenomena exhibit significant inter-individual variability, with some individuals consistently demonstrating efficient responses to hypnotic suggestions, while others show limited susceptibility. Recent neurophysiological studies have added to a growing body of research that shows variability in hypnotic susceptibility is linked to distinct neural
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Hypnotic phenomena exhibit significant inter-individual variability, with some individuals consistently demonstrating efficient responses to hypnotic suggestions, while others show limited susceptibility. Recent neurophysiological studies have added to a growing body of research that shows variability in hypnotic susceptibility is linked to distinct neural characteristics. Building on this foundation, our previous work identified that individuals with high and low hypnotic susceptibility can be differentiated based on the arrhythmic activity observed in resting-state electrophysiology (rs-EEG) outside of hypnosis. However, because previous work has largely focused on mean spectral characteristics, our understanding of the variability over time of these features, and how they relate to hypnotic susceptibility, is still limited. Here we address this gap using a time-resolved assessment of rhythmic alpha peaks and arrhythmic components of the EEG spectrum both prior to and following hypnotic induction. Using multivariate pattern classification, we investigated whether these neural features differ between individuals with high and low susceptibility to hypnosis. Specifically, we used multivariate pattern classification to investigate whether these non-stationary neural features could distinguish between individuals with high and low susceptibility to hypnosis before and after a hypnotic induction. Our analytical approach focused on time-resolved spectral decomposition to capture the intricate dynamics of neural oscillations and their non-oscillatory counterpart, as well as Lempel–Ziv complexity. Our results show that variations in the alpha center frequency are indicative of hypnotic susceptibility, but this discrimination is only evident during hypnosis. Highly hypnotic-susceptible individuals exhibit higher variability in alpha peak center frequency. These findings underscore how dynamic changes in neural states related to alpha peak frequency represent a central neurophysiological feature of hypnosis and hypnotic susceptibility.
Full article
(This article belongs to the Special Issue Brain Mechanism of Hypnosis)
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Open AccessCase Report
Emergency Carotid Thrombo-Endarterectomy after Failed Endovascular Recanalization for Acute Complete Carotid Occlusion: A Case Report
by
Abdullah Keles, Zeynep Arzum Uyaniker, Beverly Aagaard-Kienitz and Mustafa K. Baskaya
Brain Sci. 2024, 14(9), 882; https://doi.org/10.3390/brainsci14090882 - 30 Aug 2024
Abstract
Rapid identification of the type and origin of a stroke is crucial for prompt and appropriate treatment, which can significantly influences patient outcomes. We report a multidisciplinary management case involving a 76-year-old man who presented with left-sided weakness and mild dysarthria. Imaging revealed
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Rapid identification of the type and origin of a stroke is crucial for prompt and appropriate treatment, which can significantly influences patient outcomes. We report a multidisciplinary management case involving a 76-year-old man who presented with left-sided weakness and mild dysarthria. Imaging revealed a completely occluded right internal carotid artery. Despite multiple endovascular recanalization attempts, adequate flow could not be achieved, leading to the decision to perform an open thrombo-endarterectomy. The patient underwent carotid endarterectomy with microsurgical techniques under general anesthesia. The atheroma plaque and central thrombus were removed, which reestablished flow. Continuous intraoperative neuromonitoring was utilized to ensure patient safety. The patient woke up without new deficits and was discharged for rehabilitation. Follow-up imaging confirmed arterial patency, and the patient eventually made an excellent recovery, including being independent over one and a half years. Emergent recanalization with carotid endarterectomy following a failed endovascular recanalization is both safe and feasible, emphasizing the need for collaboration between different treatment providers to ensure optimal patient outcomes. Our report highlights the importance of a multidisciplinary approach and the advantages of a hybrid operating room in the treatment of acute complete carotid artery occlusion.
Full article
(This article belongs to the Special Issue Valuable Experience in Clinical Neurology and Neurosurgery)
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Open AccessArticle
Comprehensive Analysis of Age- and Sex-Related Expression of the Chaperone Protein Sigma-1R in the Mouse Brain
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Khadija Tarmoun, Véronik Lachance, Victoria Le Corvec, Sara-Maude Bélanger, Guillaume Beaucaire and Saïd Kourrich
Brain Sci. 2024, 14(9), 881; https://doi.org/10.3390/brainsci14090881 - 30 Aug 2024
Abstract
Sigma-1R (S1R) is a ubiquitously distributed protein highly expressed in the brain and liver. It acts as a ligand-inducible chaperone protein localized at the endoplasmic reticulum. S1R participates in several signaling pathways that oversee diverse cellular and neurological functions, such as calcium and
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Sigma-1R (S1R) is a ubiquitously distributed protein highly expressed in the brain and liver. It acts as a ligand-inducible chaperone protein localized at the endoplasmic reticulum. S1R participates in several signaling pathways that oversee diverse cellular and neurological functions, such as calcium and proteome homeostasis, neuronal activity, memory, and emotional regulation. Despite its crucial functions, S1R expression profile in the brain with respect to age and sex remains elusive. To shed light on this matter, we assessed S1R distribution in the mouse brain across different developmental stages, including juvenile, early adult, and middle-aged mice. Using immunohistochemistry, we found that S1R is predominantly expressed in the hippocampus in juvenile mice, particularly in CA1 and CA3 regions. Notably, S1R is not expressed in the subgranular layer of the dentate gyrus of juvenile mice. We observed dynamic changes in S1R levels during development, with most brain regions showing either an abrupt or gradual decline as mice transition from juveniles to adults. Sexual dimorphism is observed before puberty in the hippocampus and hypothalamus and during adulthood in the hippocampus and cortex.
Full article
(This article belongs to the Section Molecular and Cellular Neuroscience)
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Open AccessArticle
Classifying Unconscious, Psychedelic, and Neuropsychiatric Brain States with Functional Connectivity, Graph Theory, and Cortical Gradient Analysis
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Hyunwoo Jang, Rui Dai, George A. Mashour, Anthony G. Hudetz and Zirui Huang
Brain Sci. 2024, 14(9), 880; https://doi.org/10.3390/brainsci14090880 - 30 Aug 2024
Abstract
Accurate and generalizable classification of brain states is essential for understanding their neural underpinnings and improving clinical diagnostics. Traditionally, functional connectivity patterns and graph-theoretic metrics have been utilized. However, cortical gradient features, which reflect global brain organization, offer a complementary approach. We hypothesized
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Accurate and generalizable classification of brain states is essential for understanding their neural underpinnings and improving clinical diagnostics. Traditionally, functional connectivity patterns and graph-theoretic metrics have been utilized. However, cortical gradient features, which reflect global brain organization, offer a complementary approach. We hypothesized that a machine learning model integrating these three feature sets would effectively discriminate between baseline and atypical brain states across a wide spectrum of conditions, even though the underlying neural mechanisms vary. To test this, we extracted features from brain states associated with three meta-conditions including unconsciousness (NREM2 sleep, propofol deep sedation, and propofol general anesthesia), psychedelic states induced by hallucinogens (subanesthetic ketamine, lysergic acid diethylamide, and nitrous oxide), and neuropsychiatric disorders (attention-deficit hyperactivity disorder, bipolar disorder, and schizophrenia). We used support vector machine with nested cross-validation to construct our models. The soft voting ensemble model marked the average balanced accuracy (average of specificity and sensitivity) of 79% (62–98% across all conditions), outperforming individual base models (70–76%). Notably, our models exhibited varying degrees of transferability across different datasets, with performance being dependent on the specific brain states and feature sets used. Feature importance analysis across meta-conditions suggests that the underlying neural mechanisms vary significantly, necessitating tailored approaches for accurate classification of specific brain states. This finding underscores the value of our feature-integrated ensemble models, which leverage the strengths of multiple feature types to achieve robust performance across a broader range of brain states. While our approach offers valuable insights into the neural signatures of different brain states, future work is needed to develop and validate even more generalizable models that can accurately classify brain states across a wider array of conditions.
Full article
(This article belongs to the Special Issue Deep into the Brain: Artificial Intelligence in Brain Diseases—2nd Edition)
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Open AccessArticle
Effectiveness and Tolerability of Anti-Calcitonin Gene-Related Peptide Therapy for Migraine and Other Chronic Headaches in Adolescents and Young Adults: A Retrospective Study in the USA
by
Anjaneya Shankar Madhav Bandatmakur, Pooja Dave, Melissa Kerr, Colin Brunick, Sijin Wen and Nicholas Hansen
Brain Sci. 2024, 14(9), 879; https://doi.org/10.3390/brainsci14090879 - 30 Aug 2024
Abstract
This retrospective study assesses the efficacy and tolerability of anti-calcitonin gene-related peptide (anti-CGRP) therapy in adolescents and young adults (ages 12–21) with migraine and chronic daily headaches unresponsive to standard treatments. Migraines in this demographic significantly impair school performance, self-esteem, psychological well-being, and
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This retrospective study assesses the efficacy and tolerability of anti-calcitonin gene-related peptide (anti-CGRP) therapy in adolescents and young adults (ages 12–21) with migraine and chronic daily headaches unresponsive to standard treatments. Migraines in this demographic significantly impair school performance, self-esteem, psychological well-being, and cognitive health. These young patients are also particularly sensitive to the side effects of conventional medications, which are often prescribed off-label and come with high insurance denial rates. Medication overuse, including analgesics, triptans, and NSAIDs, is prevalent due to treatment failures. Elevated plasma CGRP levels observed during migraines suggest that anti-CGRP therapies, successful in adult populations, may also benefit this younger age group. Over a three-year period, patients at a specialized pediatric headache center were evaluated for the impact of anti-CGRP treatments, including monoclonal antibodies (erenumab, fremanezumab, and galcanezumab) and small-molecule CGRP receptor antagonists (ubrogepant, rimegepant, and atogepant), administered either alone or in combination with OnabotulinumtoxinA. Data were extracted from the hospital’s electronic medical records, and patient progress was consistently documented using a structured template for each clinic visit. Additional patient satisfaction data were collected via telephone follow-ups and patient message reviews. The study included 23 patients, primarily treated for chronic migraine (CM) (78.3%), with a smaller subset addressing episodic migraine (EM), new daily persistent headaches (NDPHs), and post-traumatic headaches (PTHs). Comprehensive demographic and clinical data, including age, treatment duration, history of preventive treatment failures, and comorbidities like psychiatric conditions and sleep disorders, were collected. Anti-CGRP therapies, particularly when combined with traditional treatments or OnabotulinumtoxinA, resulted in significant improvements: 91.3% of patients experienced reduced migraine duration and intensity, 82.6% reported improvements in other bothersome symptoms, and 73.9% saw an improved response to rescue medications. Additionally, 78.3% of patients reported a reduction in their use of rescue medications per week by more than 50%, and emergency room visits were reduced for 56.5% of patients. Significant reductions in headache days were observed in 82.6% of patients after one month and 87% after three months, with nearly 40% experiencing more than a 50% reduction in both periods. The greatest benefits were observed in patients treated for more than six months. Adverse effects were minimal, with 95.7% of patients reporting no side effects, and patient satisfaction was high, with 69.6% opting to continue treatment. Overall, this study highlights the substantial potential of anti-CGRP therapy in improving outcomes for adolescents and young adults with CM and EM, offering a promising approach for a demographic that faces considerable challenges with conventional treatment options. However, further research is needed to confirm these findings and expand clinical applications in this age group.
Full article
(This article belongs to the Section Neuroscience of Pain)
Open AccessReview
Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review
by
Jing Ling Tay, Kyawt Kyawt Htun and Kang Sim
Brain Sci. 2024, 14(9), 878; https://doi.org/10.3390/brainsci14090878 - 29 Aug 2024
Abstract
Background: Psychotic disorders are major psychiatric disorders that can impact multiple domains including physical, social, and psychological functioning within individuals with these conditions. Being able to better predict the outcomes of psychotic disorders will allow clinicians to identify illness subgroups and optimize treatment
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Background: Psychotic disorders are major psychiatric disorders that can impact multiple domains including physical, social, and psychological functioning within individuals with these conditions. Being able to better predict the outcomes of psychotic disorders will allow clinicians to identify illness subgroups and optimize treatment strategies in a timely manner. Objective: In this scoping review, we aimed to examine the accuracy of the use of artificial intelligence (AI) methods in predicting the clinical outcomes of patients with psychotic disorders as well as determine the relevant predictors of these outcomes. Methods: This review was guided by the PRISMA Guidelines for Scoping Reviews. Seven electronic databases were searched for relevant published articles in English until 1 February 2024. Results: Thirty articles were included in this review. These studies were mainly conducted in the West (63%) and Asia (37%) and published within the last 5 years (83.3%). The clinical outcomes included symptomatic improvements, illness course, and social functioning. The machine learning models utilized data from various sources including clinical, cognitive, and biological variables such as genetic, neuroimaging measures. In terms of main machine learning models used, the most common approaches were support vector machine, random forest, logistic regression, and linear regression models. No specific machine learning approach outperformed the other approaches consistently across the studies, and an overall range of predictive accuracy was observed with an AUC from 0.58 to 0.95. Specific predictors of clinical outcomes included demographic characteristics (gender, socioeconomic status, accommodation, education, and employment); social factors (activity level and interpersonal relationships); illness features (number of relapses, duration of relapses, hospitalization rates, cognitive impairments, and negative and disorganization symptoms); treatment (prescription of first-generation antipsychotics, high antipsychotic doses, clozapine, use of electroconvulsive therapy, and presence of metabolic syndrome); and structural and functional neuroimaging abnormalities, especially involving the temporal and frontal brain regions. Conclusions: The current review highlights the potential and need to further refine AI and machine learning models in parsing out the complex interplay of specific variables that contribute to the clinical outcome prediction of psychotic disorders.
Full article
(This article belongs to the Special Issue Clinical and Biological Characterization of Psychiatric Disorders)
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Open AccessArticle
Therapeutic Cerebral Fluid Puncture in Patients with Idiopathic Intracranial Hypertension: No Short-Term Effect on Neurocognitive Function
by
Cem Thunstedt, Dilan Aydemir, Julian Conrad, Elisabeth Wlasich, Sandra V. Loosli, Florian Schöberl, Andreas Straube and Ozan E. Eren
Brain Sci. 2024, 14(9), 877; https://doi.org/10.3390/brainsci14090877 - 29 Aug 2024
Abstract
Background: Idiopathic intracranial hypertension (IIH) is typically characterized by headaches and vision loss. However, neurocognitive deficits are also described. Our study aimed to test the influence of therapeutic lumbar puncture on the latter. Methods: A total of 15 patients with IIH were tested
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Background: Idiopathic intracranial hypertension (IIH) is typically characterized by headaches and vision loss. However, neurocognitive deficits are also described. Our study aimed to test the influence of therapeutic lumbar puncture on the latter. Methods: A total of 15 patients with IIH were tested with a battery of neurocognitive tests at baseline and after therapeutic lumbar drainage. Hereby, Logical Memory of the Wechsler Memory Scale—Revised Edition (WMS-R), the California Verbal Learning Test Short Version (CVLT), alertness, selective attention, and word fluency were used. Changes in cognitive functioning in the course of CSF pressure lowering were analysed and compared with age, sex, and education-matched healthy controls. Results: Before intervention, scores of Logical Memory, the RWT, and the HADS-D were significantly lower in IIH patients compared to matched controls. After short-term normalization of CSF pressure, the RWT improved significantly. Additionally, significant positive correlations were found between headache intensity and subjective impairment, as well as between BMI and CSF opening pressure. Conclusions: Our findings confirm lower performance in terms of long-term verbal memory and word fluency compared to controls, as well as depressive symptoms in IIH patients. Significant improvement after short-term normalization of intracranial pressure by means of CSF drainage was seen only for word fluency. This indicates that short-term normalization of CSF pressure is not sufficient to normalize observed neurocognitive deficits.
Full article
(This article belongs to the Section Cognitive Social and Affective Neuroscience)
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Open AccessArticle
Betahistine’s Neuroprotective Actions against Lipopolysaccharide-Induced Neurotoxicity: Insights from Experimental and Computational Studies
by
Vasudevan Mani and Minhajul Arfeen
Brain Sci. 2024, 14(9), 876; https://doi.org/10.3390/brainsci14090876 - 29 Aug 2024
Abstract
Histamine H3 receptor (H3R) antagonists, such as betahistine (BHTE), have shown significant potential in treating central nervous system (CNS) disorders due to their neuroprotective properties. This study investigated BHTE’s effects on lipopolysaccharide (LPS)-induced neurotoxicity, which is associated with neuroinflammation and
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Histamine H3 receptor (H3R) antagonists, such as betahistine (BHTE), have shown significant potential in treating central nervous system (CNS) disorders due to their neuroprotective properties. This study investigated BHTE’s effects on lipopolysaccharide (LPS)-induced neurotoxicity, which is associated with neuroinflammation and neurodegeneration. Rats were divided into groups and pre-treated with BHTE (5 or 10 mg/kg, p.o.) for 30 days, followed by LPS administration (1 mg/kg, i.p.) for 4 consecutive days to induce neurotoxicity. LPS exposure resulted in cognitive impairment, as evidenced by performance deficits in maze tests, and a significant reduction in brain acetylcholine (ACh) levels. Additionally, LPS led to increased neuroinflammation, oxidative stress, mitochondrial dysfunction, and apoptosis. Pre-treatment with BHTE effectively counteracted these effects, improving cognitive performance and restoring ACh levels. BHTE significantly reduced LPS-induced increases in pro-inflammatory markers (COX-2, TNF-α, and IL-6) while enhancing anti-inflammatory cytokines (IL-10 and TGF-β1). Furthermore, BHTE improved mitochondrial function by increasing enzyme levels (MRCC-I, II, and IV) and boosted anti-apoptotic (Bcl-2) and antioxidant defenses (GSH and catalase). BHTE also reduced apoptosis markers, including pro-apoptotic protein caspase-3, and oxidative stress marker malondialdehyde (MDA). Molecular modeling studies revealed that BHTE effectively binds to key enzymes involved in neuroinflammation and apoptosis (AChE, COX-2, and caspase-3), with binding free energies between 4 and 5 kcal/mol, interacting with critical residues. These findings underscore BHTE’s multifaceted neuroprotective effects against LPS-induced neurotoxicity, offering potential therapeutic avenues for managing neuroinflammation and related neurodegenerative disorders.
Full article
(This article belongs to the Special Issue Neuropharmacology and Neuroinflammation)
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Open AccessArticle
Impact of Stimulation Duration in taVNS—Exploring Multiple Physiological and Cognitive Outcomes
by
Till Bömmer, Luisa M. Schmidt, Katharina Meier, Julius Kricheldorff, Heiko Stecher, Christoph S. Herrmann, Christiane M. Thiel, Kathrin Janitzky and Karsten Witt
Brain Sci. 2024, 14(9), 875; https://doi.org/10.3390/brainsci14090875 - 29 Aug 2024
Abstract
Transcutaneous auricular vagus nerve stimulation (taVNS) is a non-invasive neuromodulation technique that modulates the noradrenergic activity of the locus coeruleus (LC). Yet, there is still uncertainty about the most effective stimulation and reliable outcome parameters. In a double blind, sham-controlled study including a
[...] Read more.
Transcutaneous auricular vagus nerve stimulation (taVNS) is a non-invasive neuromodulation technique that modulates the noradrenergic activity of the locus coeruleus (LC). Yet, there is still uncertainty about the most effective stimulation and reliable outcome parameters. In a double blind, sham-controlled study including a sample of healthy young individuals (N = 29), we compared a shorter (3.4 s) and a longer (30 s) stimulation duration and investigated the effects of taVNS (real vs. sham) on saliva samples (alpha amylase and cortisol concentration), pupil (pupillary light reflex and pupil size at rest) and EEG data (alpha and theta activity at rest, ERPs for No-Go signals), and cognitive tasks (Go/No-Go and Stop Signal Tasks). Salivary alpha amylase concentration was significantly increased in the real as compared to sham stimulation for the 30 s stimulation condition. In the 3.4 s stimulation condition, we found prolonged reaction times and increased error rates in the Go/No-Go task and increased maximum acceleration in the pupillary light reflex. For the other outcomes, no significant differences were found. Our results show that prolonged stimulation increases salivary alpha-amylase, which was expected from the functional properties of the LC. The finding of longer response times to short taVNS stimulation was not expected and cannot be explained by an increase in LC activity. We also discuss the difficulties in assessing pupil size as an expression of taVNS-mediated LC functional changes.
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(This article belongs to the Special Issue Application of Nerve Stimulation: Current Status and Future Directions)
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Open AccessArticle
Reward History and Statistical Learning Independently Impact Attention Search: An ERP Study
by
Guang Zhao, Rongtao Wu, Huijun Wang, Jiahuan Chen, Shiyi Li, Qiang Wang and Hong-Jin Sun
Brain Sci. 2024, 14(9), 874; https://doi.org/10.3390/brainsci14090874 - 29 Aug 2024
Abstract
Selection history is widely accepted as a vital source in attention control. Reward history indicates that a learned association captures attention even when the reward is no longer presented, while statistical learning indicates that a learned probability exerts its influence on attentional control
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Selection history is widely accepted as a vital source in attention control. Reward history indicates that a learned association captures attention even when the reward is no longer presented, while statistical learning indicates that a learned probability exerts its influence on attentional control (facilitation or inhibition). Existing research has shown that the effects of the reward history and statistical learning are additive, suggesting that these two components influence attention priority through different pathways. In the current study, leveraging the temporal resolution advantages of EEG, we explored whether these two components represent independent sources of attentional bias. The results revealed faster responses to the target at the high-probability location compared to low-probability locations. Both the target and distractor at high-probability locations elicited larger early Pd (50–150 ms) and Pd (150–250 ms) components. The reward distractor slowed the target search and elicited a larger N2pc (180–350 ms). Further, no interaction between statistical learning and the reward history was observed in RTs or N2pc. The different types of temporal progression in attention control indicate that statistical learning and the reward history independently modulate the attention priority map.
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(This article belongs to the Section Neurotechnology and Neuroimaging)
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Open AccessArticle
High Accuracy of Three-Dimensional Navigated Kirschner-Wire-Less Single-Step Pedicle Screw System (SSPSS) in Lumbar Fusions: Comparison of Intraoperatively Planned versus Final Screw Position
by
Mateusz Bielecki, Blake I. Boadi, Yizhou Xie, Chibuikem A. Ikwuegbuenyi, Minaam Farooq, Jessica Berger, Alan Hernández-Hernández, Ibrahim Hussain and Roger Härtl
Brain Sci. 2024, 14(9), 873; https://doi.org/10.3390/brainsci14090873 - 29 Aug 2024
Abstract
(1) Background: Our team has previously introduced the Single-Step Pedicle Screw System (SSPSS), which eliminates the need for K-wires, as a safe and effective method for percutaneous minimally invasive spine (MIS) pedicle screw placement. Despite this, there are ongoing concerns about the reliability
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(1) Background: Our team has previously introduced the Single-Step Pedicle Screw System (SSPSS), which eliminates the need for K-wires, as a safe and effective method for percutaneous minimally invasive spine (MIS) pedicle screw placement. Despite this, there are ongoing concerns about the reliability and accuracy of screw placement in MIS procedures without traditional tools like K-wires and Jamshidi needles. To address these concerns, we evaluated the accuracy of the SSPSS workflow by comparing the planned intraoperative screw trajectories with the final screw positions. Traditionally, screw placement accuracy has been assessed by grading the final screw position using postoperative CT scans. (2) Methods: We conducted a retrospective review of patients who underwent lumbar interbody fusion, using intraoperative 3D navigation for screw placement. The planned screw trajectories were saved in the navigation system during each procedure, and postoperative CT scans were used to evaluate the implanted screws. Accuracy was assessed by comparing the Gertzbein and Robbins classification scores of the planned trajectories and the final screw positions. Accuracy was defined as a final screw position matching the classification of the planned trajectory. (3) Results: Out of 206 screws, 196 (95%) were accurately placed, with no recorded complications. (4) Conclusions: The SSPSS workflow, even without K-wires and other traditional instruments, facilitates accurate and reliable pedicle screw placement.
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(This article belongs to the Special Issue Advanced Clinical Technologies in Treating Neurosurgical Diseases)
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Open AccessArticle
On Metacognition: Overconfidence in Word Recall Prediction and Its Association with Psychotic Symptoms in Patients with Schizophrenia
by
Yvonne Flores-Medina, Regina Ávila Bretherton, Jesús Ramírez-Bermudez, Ricardo Saracco-Alvarez and Monica Flores-Ramos
Brain Sci. 2024, 14(9), 872; https://doi.org/10.3390/brainsci14090872 - 29 Aug 2024
Abstract
A two-factor account has been proposed as an explanatory model for the formation and maintenance of delusions. The first factor refers to a neurocognitive process leading to a significant change in subjective experience; the second factor has been regarded as a failure in
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A two-factor account has been proposed as an explanatory model for the formation and maintenance of delusions. The first factor refers to a neurocognitive process leading to a significant change in subjective experience; the second factor has been regarded as a failure in hypothesis evaluation characterized by an impairment in metacognitive ability. This study was focused on the assessment of metacognition in patients with schizophrenia. The aims of the study were to measure the overconfidence in metacognitive judgments through the prediction of word list recall and to analyze the correlation between basic neurocognition (memory and executive function) and metacognition through a metamemory test and the severity of psychotic symptoms. Method: Fifty-one participants with a diagnosis of schizophrenia were evaluated. The Positive and Negative Syndrome Scale (PANSS) was used to assess the severity of psychiatric symptoms, and the subtest of metamemory included in the Executive Functions and Frontal Lobe-2 battery (BANFE-2) was used to evaluate overconfidence and underestimation errors, intrusion and perseverative response, total volume of recall, and Brief Functioning Assessment Scale (FAST) for social functioning. Results: The strongest correlation is observed between overconfidence errors and the positive factor of the PANSS (r = 0.774, p < 0.001). For the enter model in the multiple linear regression (r = 0.78, r2 = 0.61; F = 24.57, p < 0.001), the only significant predictor was overconfidence errors. Conclusion: Our results highlight the relevance of a metacognitive bias of overconfidence, strongly correlated with psychotic symptoms, and support the hypothesis that metacognitive defects contribute to the failure to reject contradictory evidence. From our perspective, these findings align with current mechanistic models of schizophrenia that focus on the role of the prefrontal cortex.
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(This article belongs to the Special Issue Cognitive Dysfunction in Schizophrenia)
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Open AccessArticle
Machine Learning Predicts Phenoconversion from Polysomnography in Isolated REM Sleep Behavior Disorder
by
Matteo Cesari, Andrea Portscher, Ambra Stefani, Raphael Angerbauer, Abubaker Ibrahim, Elisabeth Brandauer, Simon Feuerstein, Kristin Egger, Birgit Högl and Antonio Rodriguez-Sanchez
Brain Sci. 2024, 14(9), 871; https://doi.org/10.3390/brainsci14090871 - 28 Aug 2024
Abstract
Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of alpha-synucleinopathies. This study aimed at developing a fully-automated machine learning framework for the prediction of phenoconversion in patients with iRBD by using data recorded during polysomnography (PSG). A total
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Isolated rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of alpha-synucleinopathies. This study aimed at developing a fully-automated machine learning framework for the prediction of phenoconversion in patients with iRBD by using data recorded during polysomnography (PSG). A total of 66 patients with iRBD were included, of whom 18 converted to an overt alpha-synucleinopathy within 2.7 ± 1.0 years. For each patient, a baseline PSG was available. Sleep stages were scored automatically, and time and frequency domain features were derived from electromyography (EMG) and electroencephalography (EEG) signals in REM and non-REM sleep. Random survival forest was employed to predict the time to phenoconversion, using a four-fold cross-validation scheme and by testing several combinations of features. The best test performances were obtained when considering EEG features in REM sleep only (Harrel’s C-index: 0.723 ± 0.113; Uno’s C-index: 0.741 ± 0.11; integrated Brier score: 0.174 ± 0.06). Features describing EEG slowing had high importance for the machine learning model. This is the first study employing machine learning applied to PSG to predict phenoconversion in patients with iRBD. If confirmed in larger cohorts, these findings might contribute to improving the design of clinical trials for neuroprotective treatments.
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(This article belongs to the Special Issue Artificial Intelligence in Sleep Medicine)
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Open AccessBrief Report
Epilepsy and Myasthenia Gravis: A Case Series
by
Iñigo Oyarzun, Guillermo Hernández, Jacint Sala-Padró, Francisco Morandeira, Carlos Casasnovas and Mercè Falip
Brain Sci. 2024, 14(9), 870; https://doi.org/10.3390/brainsci14090870 - 28 Aug 2024
Abstract
The association between epilepsy and myasthenia gravis has rarely been reported, and when it has been reported, it has only been in a small case series. The aim of the present study was to report the frequency of epilepsy and myasthenia gravis and
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The association between epilepsy and myasthenia gravis has rarely been reported, and when it has been reported, it has only been in a small case series. The aim of the present study was to report the frequency of epilepsy and myasthenia gravis and to describe a case series of patients with myasthenia gravis and epilepsy, focusing on their clinical characteristics and searching for a possible physiopathological mechanism. A retrospective, observational, adult center study was conducted in 2022. Patients were recruited from the database of the outpatient clinic of the Myasthenia Gravis and Epilepsy Unit of the Neurology Service, Hospital Universitari de Bellvitge. Five patients were included. The frequency of epilepsy in the myasthenia gravis cohort was 5/469 (1.1%), and the frequency of myasthenia gravis in the epilepsy cohort was 5/1432 (0.35%). All patients suffered from focal epilepsy, mainly temporo-central, which was drug-resistant in 3/5 Myasthenia gravis, which was generalized and with exacerbations in 3/5. Three patients were thymectomized (anatomopathology: thymic hyperplasia). Other autoimmune diseases were found in two (40%). Epilepsy onset preceded myasthenia gravis onset in all patients. Both diseases were considered autoimmune-related in 3/5, related to genetic predisposition due to altered innate immune system in 1/5, and due to chance or to treatment in 1/5. Epilepsy and myasthenia gravis are only infrequently associated. In adult patients, epilepsy onset precedes myasthenia onset in most cases. In some cases, epilepsy has an autoimmune etiology and coexists with other autoimmune conditions.
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(This article belongs to the Section Behavioral Neuroscience)
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Open AccessArticle
Electroacupuncture Reduced Fibromyalgia-Pain-like Behavior through Inactivating Transient Receptor Potential V1 and Interleukin-17 in Intermittent Cold Stress Mice Model
by
Yu-An Yeh, Hsien-Yin Liao, I-Han Hsiao, Hsin-Cheng Hsu and Yi-Wen Lin
Brain Sci. 2024, 14(9), 869; https://doi.org/10.3390/brainsci14090869 - 28 Aug 2024
Abstract
Fibromyalgia (FM) is a widespread musculoskeletal pain associated with psychological disturbances, the etiopathogenesis of which is still not clear. One hypothesis implicates inflammatory cytokines in increasing central and peripheral sensitization along with neuroinflammation, leading to an elevation in pro-inflammatory cytokines, e.g., interleukin-17A (IL-17A),
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Fibromyalgia (FM) is a widespread musculoskeletal pain associated with psychological disturbances, the etiopathogenesis of which is still not clear. One hypothesis implicates inflammatory cytokines in increasing central and peripheral sensitization along with neuroinflammation, leading to an elevation in pro-inflammatory cytokines, e.g., interleukin-17A (IL-17A), enhanced in FM patients and animal models. The intermittent cold stress (ICS)-induced FM-like model in C57BL/6 mice has been developed since 2008 and proved to have features which mimic the clinical pattern in FM patients such as mechanical allodynia, hyperalgesia, and female predominance of pain. Electroacupuncture (EA) is an effective treatment for relieving pain in FM patients, but its mechanism is not totally clear. It was reported as attenuating pain-like behaviors in the ICS mice model through the transient receptor potential vanilloid 1 (TRPV1) pathway. Limited information indicates that TRPV1-positive neurons trigger IL-17A-mediated inflammation. Therefore, we hypothesized that the IL-17A would be inactivated by EA and TRPV1 deletion in the ICS-induced FM-like model in mice. We distributed mice into a control (CON) group, ICS-induced FM model (FM) group, FM model with EA treatment (EA) group, FM model with sham EA treatment (Sham) group, and TRPV1 gene deletion (Trpv1−/−) group. In the result, ICS-induced mechanical and thermal hyperalgesia increased pro-inflammatory cytokines including IL-6, IL-17, TNFα, and IFNγ in the plasma, as well as TRPV1, IL-17RA, pPI3K, pAkt, pERK, pp38, pJNK, and NF-κB in the somatosensory cortex (SSC) and cerebellum (CB) lobes V, VI, and VII. Moreover, EA and Trpv1−/− but not sham EA countered these effects significantly. The molecular mechanism may involve the pro-inflammatory cytokines, including IL-6, IL-17, TNFα, and IFNγ. IL-17A–IL-17RA play a crucial role in peripheral and central sensitization as well as neuroinflammation and cannot be activated without TRPV1 in the ICS mice model. EA alleviated FM-pain-like behaviors, possibly by abolishing the TRPV1- and IL-17A-related pathways. It suggests that EA is an effective and potential therapeutic strategy in FM.
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(This article belongs to the Special Issue Application of Nerve Stimulation: Current Status and Future Directions)
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