Frontiers in Neuroscience

Alzheimer’s Disease (AD) is the most prevalent type of dementia and is characterized by the presence of senile plaques and neurofibrillary tangles. There are various theories concerning the causes of AD, but the connection between viral and bacterial infections and their potential role in the pathogenesis of AD has become a fascinating area of research for the field. Various viruses such as Herpes simplex virus 1 (HSV-1), Epstein–Barr virus (EBV), Cytomegalovirus (CMV), influenza viruses, and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as well as bacteria such as Chlamydia pneumoniae (CP), Helicobacter pylori (HP), Porphyromonas gingivalis ( P. gingivalis ), Spirochetes and eukaryotic unicellular parasites (e.g., Toxoplasma gondii ), have been linked to AD due to their ability to activate the immune system, induce inflammation and increase oxidative stress, thereby leading to cognitive decline and AD. In addition, microRNAs (miRNAs) might play a crucial role in the pathogenesis mechanisms of these pathogens since they are utilized to target various protein-coding genes, allowing for immune evasion, maintaining latency, and suppressing cellular signaling molecules. Also, they can regulate gene expression in human cells. This article provides an overview of the association between AD and various infectious agents, with a focus on the mechanisms by which these pathogens may be related to the pathogenesis of AD. These findings suggest important areas for further research to be explored in future studies.

Introduction The study of attention has been pivotal in advancing our comprehension of cognition. The goal of this study is to investigate which EEG data representations or features are most closely linked to attention, and to what extent they can handle the cross-subject variability. Methods We explore the features obtained from the univariate time series from a single EEG channel, such as time domain features and recurrence plots, as well as representations obtained directly from the multivariate time series, such as global field power or functional brain networks. To address the cross-subject variability in EEG data, we also investigate persistent homology features that are robust to different types of noise. The performance of the different EEG representations is evaluated with the Support Vector Machine (SVM) accuracy on the WithMe data derived from a modified digit span experiment, and is benchmarked against baseline EEG-specific models, including a deep learning architecture known for effectively learning task-specific features. Results The raw EEG time series outperform each of the considered data representations, but can fall short in comparison with the black-box deep learning approach that learns the best features. Discussion The findings are limited to the WithMe experimental paradigm, highlighting the need for further studies on diverse tasks to provide a more comprehensive understanding of their utility in the analysis of EEG data.

Background Acupoint catgut embedding (ACE) is a traditional Chinese medicine technique commonly used for managing various disorders, including chronic inflammatory pain and allergic asthma. Despite its growing use, the neuroimmunological mechanisms underlying ACE treatment effects remain unclear. Methods This study investigated the roles and potential mechanisms of the effects of ACE in treating experimental autoimmune encephalomyelitis (EAE), a frequently used animal model of autoimmune neuroinflammation. The effects of ACE treatment were evaluated by monitoring body weight and EAE severity scores. Behavioral tests, histopathological analysis, ELISA, and flow cytometry were conducted to assess the therapeutic efficacy of ACE. RNA sequencing was performed to uncover ACE-associated transcriptional signatures in the spinal cords of EAE mice. Results The results were validated through western blotting, qRT-PCR, and immunofluorescence (IF) staining. In ACE-treated mice, EAE disease severity was significantly ameliorated, along with improvements in anxiety-like behaviors and reduced inflammation and demyelination. The ACE treatment restored immune imbalance in the EAE mice by decreasing Th17 and Th1 cells, while increasing Treg cells in peripheral immune organs and reducing serum inflammatory cytokine levels. RNA sequencing revealed significant suppression of the genes and pathways associated with reactive microglial and astrocytic activation, corroborated by IF studies. Additionally, ACE treatment could suppress the ERK and JNK signaling pathways at both RNA and protein levels. Conclusion These findings confirm the protective role of ACE in mitigating EAE symptoms by modulating microglial and astrocytic activity and regulating inflammatory cytokines.

Introduction Amyotrophic lateral sclerosis (ALS) is a rare, devastating neurodegenerative disease that affects upper and lower motor neurons, resulting in muscle atrophy, spasticity, hyperreflexia, and paralysis. Inflammation plays an important role in the development of ALS, and associated with rapid disease progression. Current observational studies indicate the thinning of cortical thickness in patients with ALS is associated with rapid disease progression and cognitive changes. However, the effects of inflammatory cytokines on cortical thickness in patients with ALS are unclear. Here, we investigated the relationship between inflammatory cytokines and cortical thickness in patients with ALS. Methods We evaluated 51 patients with ALS for inflammatory cytokines including interleukin (IL)-4, interferon (IFN)-α, IL-1β, IL-2, IL-5, IL-12, tumor necrosis factor (TNF)-α, IL-6, IL-10, IL-8, IL-17, and IFN-γ and analyzed the correlation between these indicators and the ALS functional rating scale-revised (ALSFRS-R) score or disease progression rate (ΔFS score). Twenty-six patients with ALS and 26 controls were studied using whole-cortex analysis, and post-hoc analyses were performed to examine the correlation between brain cortical thickness and ALSFRS-R or ΔFS scores. Results IL-4, IFN-α, IL-1β, and IL-2 levels were significantly correlated with ALSFRS-R scores, and the IL-2 level was significantly correlated with ΔFS scores. After controlling for age and sex, the ALS group had thinner cortexes in multiple clusters across the brain than the control group. Further analyses revealed that cortical thickness in the right superior temporal and lingual gyrus regions was inversely correlated with ΔFS scores. There was a significant positive correlation between the clusters in the right lingual cortex and IL-2 level. Conclusion These results suggest cortical thickness was reduced in patients with ALS in motor and non-motor cortical areas. Inflammatory factors (especially IL-2) were correlated with cortical thickness, and both were related to the disease progression rate, suggesting IL-2 plays an important role in ALS.

Neurodegenerative diseases represent a group of disorders characterized by progressive degeneration of neurons in the central nervous system, leading to a range of cognitive, motor, and sensory impairments. In recent years, there has been growing interest in the association between neurodegenerative diseases and olfactory dysfunction (OD). Characterized by a decline in the ability to detect or identify odors, OD has been observed in various conditions, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and Amyotrophic Lateral Sclerosis (ALS). This phenomenon often precedes the onset of other clinical symptoms, suggesting its potential utility as an early marker or prodromal symptom of neurodegenerative diseases. This review provides a vast literature overview on the current knowledge of OD in PD, AD, ALS, and HD in order to evaluate its potential as a biomarker, particularly in the early and prodromal stages of these diseases. We summarize the most common methods used to measure olfactory function and delve into neuropathological correlations and the alterations in neurotransmitter systems associated with OD in those neurodegenerative diseases, including differences in genetic variants if applicable, and cater to current pitfalls and shortcomings in the research.

Purpose Tinnitus is considered a neurological disorder affecting both auditory and nonauditory networks. This study aimed to investigate the structural brain covariance network in tinnitus patients and analyze its altered topological properties. Materials Fifty three primary tinnitus patients and 67 age- and sex-matched healthy controls (HCs) were included. Gray matter volume (GMV) of each participant was extracted using voxel-based morphometry, a group-level structural covariance network (SCN) was constructed based on the GMV of each participant, and graph theoretic analyses were performed using graph analysis toolbox (GAT). The differences in the topological properties of SCN between both groups were compared and analyzed. Results Both groups exhibited small-world attributes. Compared with HCs, tinnitus patients had significantly higher characteristic path length, lambda, transitivity, and assortativity ( p < 0.05), and significantly lower global efficiency ( p < 0.05). Tinnitus patients had higher clustering coefficient and reduced gamma and modularity, but neither was remarkable. The hubs in tinnitus network focused on the temporal lobe. In addition, the tinnitus network was found to be reduced in robustness to targeted attacks compared with HCs. Besides, a significant negative correlation between Tinnitus Handicap Inventory (THI) score and GMV in the left angular gyrus ( r = −0.283, p = 0.040) as well as left superior temporal pole ( r = −0.282, p = 0.041) were identified. Conclusion Tinnitus patients showed reduced small-world properties, altered hub nodes, and reduced ability to respond to targeted attacks in brain network. The GMV in the left angular gyrus and left superior temporal pole showed significant negative correlation with tinnitus distress (THI score), indicating potential therapeutic target.

Introduction Transcranial magnetic stimulation (TMS) is widely used for the noninvasive activation of neurons in the human brain. It utilizes a pulsed magnetic field to induce electric pulses that act on the central nervous system, altering the membrane potential of nerve cells in the cerebral cortex to treat certain mental diseases. However, the effectiveness of TMS can be compromised by significant heat generation and the clicking noise produced by the pulse in the TMS coil. This study proposes a novel, non-resonant, high-frequency switching design controlled by high-frequency pulse-width modulation (PWM) voltage excitation to achieve ideal pulse-current waveforms that minimize both clicking noise and heat generation from the TMS coil. Method First, a particle swarm optimization algorithm was used to optimize the pulse-current waveform, minimizing both the resistance loss and clicking noise (vibration energy) generated by the TMS coils. Next, the pulse-current waveform was modeled based on the principles of programmable transcranial magnetic stimulation circuits. The relationships between the parameters of the pulse-current waveform, vibration energy, and ohmic resistance loss in the TMS coil were explored, ensuring the necessary depolarization of the nerve membrane potential. Finally, four insulated-gate bipolar transistors, controlled by a series of PWM pulse sequences, generated the desired pulse-current duration and direction in the H-bridge circuit. The duration and slope of the rising and falling segments of the current waveform were adjusted by the PWM pulse duration. Results The optimized current waveform, represented by three segmented functions, reduces heat loss and noise while inducing a greater change in neural membrane potential compared with those obtained with conventional symmetric waveforms. Spectral analysis further confirmed that the noise spectrum of the optimized current waveform, particularly the peak spectrum, is significantly lower than that of the conventional triangular symmetric waveform. Conclusion The study provide a method and new ideas for low energy consumption and low-noise transcranial magnetic stimulation by using TMS circuit design techniques as well as waveform optimization.

Introduction In the field of medical listening assessments,accurate transcription and effective cognitive load management are critical for enhancing healthcare delivery. Traditional speech recognition systems, while successful in general applications often struggle in medical contexts where the cognitive state of the listener plays a significant role. These conventional methods typically rely on audio–only inputs and lack the ability to account for the listener's cognitive load, leading to reduced accuracy and effectiveness in complex medical environments. Methods To address these limitations, this study introduces ClinClip, a novel multimodal model that integrates EEG signals with audio data through a transformer-based architecture. ClinClip is designed to dynamically adjust to the cognitive state of the listener, thereby improving transcription accuracy and robustness in medical settings. The model leverages cognitive-enhanced strategies, including EEG-based modulation and hierarchical fusion of multimodal data, to overcome the challenges faced by traditional methods. Results and discussion Experiments conducted on four datasets–EEGEyeNet, DEAP, PhyAAt, and eSports Sensors–demonstrate that ClinClip significantly outperforms six state-of-the-art models in both Word Error Rate (WER) and Cognitive Modulation Efficiency (CME). These results underscore the model's effectiveness in handling complex medical audio scenarios and highlight its potential to improve the accuracy of medical listening assessments. By addressing the cognitive aspects of the listening process. ClinClip contributes to more reliable and effective healthcare delivery, offering a substantial advancement over traditional speech recognition approaches.

Introduction DYRK1A , a protein kinase located on human chromosome 21, plays a role in postembryonic neuronal development and degeneration. Alterations to DYRK1A have been consistently associated with cognitive functioning and neurodevelopmental disorders (e.g., autism, intellectual disability). However, the broader cognitive and behavioral phenotype of DYRK1A syndrome requires further characterization. Specifically, executive functioning, or cognitive processes that are necessary for goal-directed behavior, has not yet been characterized in this population. Methods Individuals with DYRK1A variants ( n = 29; ages 4 to 21 years) were assessed with a standardized protocol with multiple measures of executive functioning: Delis-Kaplan Executive Function Schedule, and chronologically age-appropriate caregiver-report forms of the Behavior Rating Inventory of Executive Function (BRIEF) and Achenbach System of Empirically Based Assessment (ASEBA). We first examined the feasibility and appropriateness of established executive functioning measures among participants with DYRK1A syndrome to inform selection of executive functioning tools in future research. We then characterized executive functioning among the group, including associations with other phenotypic features. Results Neurocognitive assessments of executive functioning were deemed infeasible due to cognitive and verbal functioning. Caregiver-report revealed elevated executive functioning concerns related to self-monitoring, working memory, and planning/organization on the BRIEF, and attention and ADHD on the CBCL. Only two participants had existing ADHD diagnoses; however, 5 participants (out of 10 participants with data) exceeded the cutoff on the BRIEF, 13 individuals (out of 27 with data) exceeded the cutoff on the ASEBA ADHD subscale, and 18 exceeded the cutoff on the ASEBA attention subscale. There was concordance between ADHD diagnosis and the ASEBA, but not BRIEF. Executive functioning was correlated with nonverbal IQ and autism traits. Discussion Objective measures of executive functioning are needed for individuals with intellectual disability who are nonverbal and/or have motor limitations. Diagnostic overshadowing, or the tendency to attribute all problems to intellectual disability and to leave other co-existing conditions, such as executive functioning challenges or ADHD, undiagnosed, is common. Phenotypic characterization of executive functioning is therefore important for our understanding of DYRK1A syndrome and for ensuring that caregivers’ concerns are addressed, and individuals receive the clinical services that best meet their needs.

Introduction Posttraumatic stress disorder (PTSD) is a debilitating disorder characterized by intrusive memories, avoidance, negative thoughts and moods, and heightened arousal. Many patients also report gastrointestinal symptoms. Cognitive behavioral therapy (CBT) is an evidence-based treatment approach for PTSD that successfully reduces symptoms. However, many patients still meet criteria for PTSD after treatment or continue to have symptoms indicating the need for new treatment strategies for PTSD. Patients with PTSD have a disrupted intestinal microbiome (i.e., dysbiosis) which can promote neuroinflammation; thus, modulation of the microbiome could be an alternative or adjunct treatment approach for PTSD. Methods The current study was a 12-week, double-blind, placebo-controlled trial seeking to understand if CBT combined with a microbiota-modifying, prebiotic fiber intervention would beneficially impact clinical outcomes in veterans with PTSD ( n = 70). This proof-of-concept, pilot trial was designed to assess: (1) the relationship between severity of PTSD symptoms and microbiota composition and SCFA levels (i.e., acetate, propionate, butyrate), (2) if CBT treatment with a concomitant prebiotic fiber intervention would beneficially impact clinical outcomes in veterans with PTSD, (3) evaluate the feasibility and acceptability of a prebiotic intervention as an adjunct treatment to CBT, and (4) assess the impact of treatment on the intestinal microbiota and stool SCFA (i.e., mechanism). Results This study found that PTSD severity may be associated with reduced abundance of taxa capable of producing the SCFA propionate, and that a subset of individuals with PTSD may benefit from a microbiota-modifying prebiotic intervention. Conclusion This study suggests that targeting the intestinal microbiome through prebiotic supplementation could represent a promising avenue for enhancing treatment outcomes in some individuals with PTSD. Clinical trial registration https://clinicaltrials.gov/ , identifier NCT05424146.

Background It is known that illicit and prescribed drugs impact pupil size, eye movement and function. Still, comprehensive quantitative evaluations under known ambient light conditions are lacking, when smartphones are used for monitoring. Methods In this clinical study (NCT05731999), four medicinal products with addiction risks were administered to 48 subjects (18–70 years old, all with informed consent, 12 subjects per drug). Videos captured by smartphones at ~50 lux and ~ 500 lux documented the eye’s reaction before and after controlled intake of single doses of oral oxycodone (20 mg), lorazepam (2 mg), lisdexamphetamine (70 mg) and inhaled cannabis flos (65 mg with 22% THC) over a 5-h test period. Data from three observational tests, non-convergence (NC, ability to cross the eyes), nystagmus (NY), and pupillary light reflex (PLR) were converted into 24 key features that represent different eye characteristics. Results Of the acquired data, 87–97% produced key features. At peak drug plasma concentration, oxycodone constricted pupils ( p < 0.001); lorazepam induced non-convergence ( p < 0.001); lisdexamphetamine induced dilated pupils ( p < 0.001), irrespective of ambient light conditions. Inhaled cannabis induced miosis ( p = 0.05 at ~50 lux, p = 0.10 at ~500 lux), a reduced light-induced amplitude ( p = 0.003 at ~50 lux, p = 0.3 at ~500 lux) and redness of the sclerae ( p = 0.14 at ~50 lux, p = 0.007 at ~500 lux). The drug effect lasted at least 5 h ( p < 0.005) except for inhaled cannabis (2–3 h, p < 0.05). Conclusion The ocular response to oxycodone, lorazepam, lisdexamphetamine and cannabis, as measured under controlled light conditions using a smartphone-based assessment, demonstrated distinct and readily distinguishable patterns for each substance. Clinical trial registration Identifier, NTC05731999.

We report a patient with autonomic dysfunction following acute SARS-CoV-2 infection, presenting progressively worsening severe orthostatic hypotension to the point where she could no longer sit or stand. The patient experienced a delay in diagnosis after an initial misdiagnosis of a functional neurological disorder. Persistent orthostatic symptoms prompted us to re-examine the diagnosis and explore other diagnostic tools, which ultimately allowed us to identify and treat severe immune-mediated orthostatic hypotension (OH). We identified autoantibodies (AAB) targeting the autonomic nervous system. Intravascular immunoglobulin therapy, along with early, specific multi-disciplinary rehabilitation, completely resolved the symptoms. Hard-to-assess patients are often penalized by suboptimal care due to the lack of a comprehensive patient history and physical examination, resulting in unnecessary and costly ancillary examinations that lead to delays in diagnosis or misdiagnoses. Furthermore, a lack of awareness of rare complications with new diseases may also hamper proper patient care. In the present case, this includes the wide range of SARS-CoV-2 infection manifestations, including immune-mediated autonomic complications.

In the ventricular-subventricular-zone (V-SVZ) of the postnatal mammalian brain, immature neurons (neuroblasts) are generated from neural stem cells throughout their lifetime. These V-SVZ-derived neuroblasts normally migrate to the olfactory bulb through the rostral migratory stream, differentiate into interneurons, and are integrated into the preexisting olfactory circuit. When the brain is injured, some neuroblasts initiate migration toward the lesion and attempt to repair the damaged neuronal circuitry, but their low regeneration efficiency prevents functional recovery. Elucidation of the molecular basis of neuroblast migration toward lesions is expected to lead to the development of new therapeutic strategies for brain regenerative medicine. Here, we show gene expression profiles of neuroblasts migrating in the peri-injured cortex compared with those migrating in the V-SVZ using photo-isolation chemistry, a method for spatial transcriptome analysis. Differentially expressed gene analysis showed that the expression levels of 215 genes (97 upregulated and 118 downregulated genes) were significantly different in neuroblasts migrating in the peri-injured cortex from those migrating in the V-SVZ. Gene Ontology analysis revealed that in neuroblasts migrating in the peri-injured cortex, expression of genes involved in regulating migration direction and preventing cell death was upregulated, while the expression of genes involved in cell proliferation and maintenance of the immature state was downregulated. Indeed, neuroblasts migrating in the peri-injured cortex had significantly lower Cyclin D2 mRNA and Ki67 protein expression levels than those in the V-SVZ. In the injured brain, amoeboid microglia/macrophages expressed transforming growth factor- β (TGF- β ), and neuroblasts migrating in the peri-injured cortex expressed TGF- β receptors. Experiments using primary cultured neuroblasts showed that application of TGF- β significantly decreased proliferating cells labeled with BrdU. These data suggest that the proliferative activity of neuroblasts migrating toward lesions is suppressed by TGF- β secreted from cells surrounding the lesion. This is the first comprehensive study characterizing the gene expression profiles of neuroblasts migrating in the peri-injured cortex.

Objective To assist in the rapid clinical identification of brain tumor types while achieving segmentation detection, this study investigates the feasibility of applying the deep learning YOLOv5s algorithm model to the segmentation of brain tumor magnetic resonance images and optimizes and upgrades it on this basis. Methods The research institute utilized two public datasets of meningioma and glioma magnetic resonance imaging from Kaggle. Dataset 1 contains a total of 3,223 images, and Dataset 2 contains 216 images. From Dataset 1, we randomly selected 3,000 images and used the Labelimg tool to annotate the cancerous regions within the images. These images were then divided into training and validation sets in a 7:3 ratio. The remaining 223 images, along with Dataset 2, were ultimately used as the internal test set and external test set, respectively, to evaluate the model’s segmentation effect. A series of optimizations were made to the original YOLOv5 algorithm, introducing the Atrous Spatial Pyramid Pooling (ASPP), Convolutional Block Attention Module (CBAM), Coordinate Attention (CA) for structural improvement, resulting in several optimized versions, namely YOLOv5s-ASPP, YOLOv5s-CBAM, YOLOv5s-CA, YOLOv5s-ASPP-CBAM, and YOLOv5s-ASPP-CA. The training and validation sets were input into the original YOLOv5s model, five optimized models, and the YOLOv8s model for 100 rounds of iterative training. The best weight file of the model with the best evaluation index in the six trained models was used for the final test of the test set. Results After iterative training, the seven models can segment and recognize brain tumor magnetic resonance images. Their precision rates on the validation set are 92.5, 93.5, 91.2, 91.8, 89.6, 90.8, and 93.1%, respectively. The corresponding recall rates are 84, 85.3, 85.4, 84.7, 87.3, 85.4, and 91.9%. The best weight file of the model with the best evaluation index among the six trained models was tested on the test set, and the improved model significantly enhanced the image segmentation ability compared to the original model. Conclusion Compared with the original YOLOv5s model, among the five improved models, the improved YOLOv5s-ASPP model significantly enhanced the segmentation ability of brain tumor magnetic resonance images, which is helpful in assisting clinical diagnosis and treatment planning.

Mild cognitive impairment in Parkinson’s disease (PD-MCI) as an independent risk factor for dementia in Parkinson’s disease has prognostic value in predicting dementia in PD patients. It was found that the calculation of cognitive function decision-making could better evaluate the cognitive function of PD-MCI. Therefore, this study explored deficits in decision-making cognitive function in PD-MCI population, and mined novel digital biomarkers for recognizing early cognitive decline in PD-MCI through an independently designed maze decision-making digital assessment paradigm. This study included 30 healthy controls 37 PD with normal cognition (PD-NC) and 40 PD-MCI patients. Through difference comparison and stepwise regression analysis, two digital decision-making biomarkers, total decision time and performance average acceleration, were screened, and their joint area under curve for the ability to discriminate between PD-MCI and PD-NC was 0.909, and for the ability to discriminate between PD-MCI and NC was 0.942. In addition, it was found that maze digital decision-making biomarkers had greater early warning efficacy in men than in women. Unlike traditional methods, this study used digital dynamic assessment to reveal possible decision-making cognitive deficits in the PD-MCI populations, which provides new ideas for effective screening for PD-MCI.

Adolescence is characterized by heightened sleep disturbances (e.g., poor sleep quality and irregular/insufficient sleep) and sensitivity to social feedback that may exacerbate suicidal ideation (SI). Victimization experiences (e.g., bullying, humiliation) can contribute to sleep disturbances and SI, particularly among minoritized youth (e.g., sexual/gender, racial/ethnic minorities). However, sensitivity to social reward, despite social challenges, may buffer against the effects of victimization on sleep and SI. In a diverse sample of youth at varying suicide risk, we examined sleep disturbance as a mediator of victimization and SI, and if neural response to social reward moderated the link between victimization and sleep disturbance. Ninety eight youth (14–22 years old; 50% sexual and/or racial/ethnic minority) with varying SI severity provided self-report data on past-six-month identity-related victimization, past-week sleep disturbance, and past-month SI. Seventy four youth completed an fMRI task involving receipt of social feedback. Region-of-interest analyses examined ventral striatum (VS) activity during positive feedback. Mediation and moderation effects were examined using linear regressions. Sleep disturbance mediated the association between identity-related victimization and SI: higher victimization was associated with worse sleep disturbance, predicting more severe SI. Moderation analyses revealed a positive association between victimization and sleep disturbance at lower but not higher levels of VS response to social reward. Sleep disturbance occurring in the context of social stress heightens vulnerability for SI, particularly among minoritized youth. Greater neural sensitivity to social reward buffers against the effects of victimization on sleep, with implications for mitigating SI. Findings suggest potential mechanisms and individual difference factors underlying minority health disparities.

Background Electrically evoked compound action potential (ECAP) can be used to measure the auditory nerve’s response to electrical stimulation in cochlear implant (CI) users. In the Nurotron CI system, extracting the ECAP waveform from the stimulus artifact is time-consuming. Method We developed a new paradigm (“FastCAP”) for use with Nurotron CI devices. In electrically evoked compound action potential in fast mode (FastCAP), N recordings are averaged directly on the CI hardware before data transmission, significantly reducing data transmission time. FastCAPs and ECAPs were measured across five electrodes and four stimulation levels per electrode. The FastCAP stimulation rate (33.3 Hz) is also faster than the ECAP rate (2.5 Hz). Results Results showed strong correlations between ECAPs and FastCAPs for N1 latency ( r = 0.84, p < 0.001) and N1 amplitude ( r = 0.97, p < 0.001). Test-retest reliability for FastCAPs was also high, with intraclass correlation coefficients of r = 0.87 for N1 latency ( p < 0.001) and r = 0.96 for N1 amplitude ( p < 0.001). The mean test time was 46.9 ± 1.4 s for the FastCAP and 340.3 ± 6.3 s for the ECAP. The FastCAP measurement time was significantly shorter than the ECAP measurement time ( W = −210.0, p < 0.001). FastCAP thresholds were significantly correlated with behavioral thresholds in 7/20 participants and with comfortable loudness levels in 11/20 participants. The time required to measure FastCAPs was significantly lower than that for ECAPs. The FastCAP paradigm maintained the accuracy and reliability the ECAP measurements while offering a significant reduction in time requirements. Conclusion This preliminary evaluation suggests that the FastCAP could be an effective clinical tool to optimize CI processor settings (e.g., threshold stimulation levels) in users of the Nurotron CI device.

Purpose To investigate the changes in cerebral hemispheric functional connections in patients with acute acquired concomitant esotropia (AACE) and their relationship with clinical manifestations, utilizing voxel-mirrored homotopic connectivity (VMHC). Methods A prospective, observational study was conducted involving 32 AACE patients and 31 age-, sex-, and education-matched healthy controls (HC). The resting-state functional magnetic resonance imaging (rs-fMRI) signals, binocular vision function, and psychometric scale scores were collected rs-fMRI data and structural image data were analyzed for VMHC, and a two-sample t -test was used to analyze the differences in VMHC between groups. Spearman correlation analysis evaluated the relationship between fMRI indicators and clinical features. Results There was no statistical difference between the two groups concerning sex, age, height and weight. VMHC levels in the superior frontal gyrus and anterior cingulate were significantly lower in the AACE group ( p < 0.05). In the AACE group, the VMHC values of the left caudate positively correlated with near vision work duration ( r = 0.381, p = 0.034), the deviation angles at near ( r = 0.428, p = 0.015) and at distance ( r = 0.416, p = 0.018). The VMHC values in the bilateral olfactory cortex also positively correlated with the near vision work duration (Right: r = 0.389, p = 0.031; Left: r = 0.372, p = 0.039) while Beck Depression Inventory (BDI) scores negatively correlated with the VMHC values of the left olfactory cortex ( r = −0.359, p = 0.048). Conclusion The dysfunction of the medial frontal gyrus and anterior cingulate gyrus is the underlying neuropathological mechanism of AACE, and these dysfunctions may be related to poor eye habits and the severity of deviation.

Background Ischemic stroke is the second leading cause of death and the third leading cause of combined disability and mortality globally. While reperfusion therapies play a critical role in the management of acute ischemic stroke (AIS), their applicability is limited, leaving many patients with significant neurological deficits and poor prognoses. Neuroprotective agents have garnered attention for their potential as adjunct therapies; however, their relative efficacy remains unclear. This study utilized a network meta-analysis (NMA) to systematically compare the efficacy of neuroprotective agents in improving neurological function and prognosis in stroke patients. Methods This study adhered to PRISMA guidelines and the Cochrane Handbook for systematic reviews. Randomized controlled trials (RCTs) were identified through comprehensive searches of the PubMed, Embase, and Cochrane Library databases. Two independent reviewers conducted the selection process, data extraction, and quality assessment. Outcomes included 90-day modified Rankin Scale (90d-mRS), change of National Institutes of Health Stroke Scale score from baseline to 90-day/14-day/7-day (90d/14d/7d-NIHSS) and 90-day/14-day Barthel Index (90d/14d-BI). Data analyses were performed using RevMan 5.4 and Stata 14.0. Results A total of 42 RCTs involving 12,210 participants were included in this analysis. The interventions assessed included Cerebrolysin, Citicoline, Edaravone, Edaravone Dextranol, Human urinary kallidinogenase, Minocycline, Nerinetide, Butylphthalide, Vinpocetine, and Control. The NMA results demonstrated that NBP ranked highest for the 90d-mRS, 90d-NIHSS, 14d-NIHSS, and 14d-BI outcomes. Edaravone was found to be the most effective intervention for the 7d-NIHSS and 90d-BI outcomes. Conclusion The findings of this study indicate that different neuroprotective agents exhibit distinct advantages at specific stages of recovery. NBP showed outstanding performance in improving 90d-mRS and 90d-NIHSS, underscoring its potential in long-term rehabilitation. Edaravone demonstrated significant superiority in 7d-NIHSS scores, highlighting its role in early neuroprotection. These results provide valuable insights for individualized clinical treatment. To further validate the efficacy and safety of neuroprotective agents, future studies should involve larger sample sizes and conduct multicenter, large-scale randomized controlled trials. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=601346 , identifier CRD42024601346.

Learning tactile Braille reading leverages cross-modal plasticity, emphasizing the brain’s ability to reallocate functions across sensory domains. This neuroplasticity engages motor and somatosensory areas and reaches language and cognitive centers like the visual word form area (VWFA), even in sighted subjects following training. No study has employed a complex reading task to monitor neural activity during the first weeks of Braille training. Since neuroplasticity can occur within days, understanding neural reorganization during early learning stages is critical. Moreover, such activation was not tested in visual and tactile domains using comparable tasks. Furthermore, implicit reading has not been studied in tactile Braille. Although visual reading in the native script occurs automatically, it remains uncertain whether the same applies to tactile reading. An implicit reading task could extend the knowledge of linguistic processing in Braille. Our study involved 17 sighted adults who learned Braille for 7 months and 19 controls. The experimental group participated in 7 testing sessions (1 week before the course, on the first day, after 1 and 6 weeks, after 3 and 7 months, and after 3 month-long hiatus). Using the fMRI Lexical Decision Task, we observed increased activity within the reading network, including the inferior frontal and supramarginal gyri, 1 week into learning in tactile and visual Braille. Interestingly, VWFA activation was observed after 1 week in the visual domain but only after 6 weeks in the tactile domain. This suggests that skill level in tactile reading influences the onset of involvement of VWFA. Once this activation was achieved, the peak level of VWFA engagement remained stable, even after the follow-up. Furthermore, an implicit reading task revealed increased activity within the reading network, including the VWFA, among participants learning Braille compared to the passive controls. Possibly, implicit reading occurs during non-reading tactile tasks where the Braille alphabet is present. We showed that the VWFA activity peak occurs faster in the visual domain compared to the tactile domain. We also showed that sighted subjects can process tactile Braille implicitly. These results enrich our understanding of neural adaptation mechanisms and the interplay between sensory modalities during complex, cross-modal learning.

Objective To investigate differences in the microstructure of the spinothalamic tract (STT) white matter in people with chronic neck and shoulder pain (CNSP) using diffusion tensor imaging, and to assess its correlation with pain intensity and duration of the pain. Materials and methods A 3.0T MRI scanner was used to perform diffusion tensor imaging scans on 31 people with CNSP and 24 healthy controls (HCs), employing the Automatic Fiber Segmentation and Quantification (AFQ) method to extract the STT and quantitatively analyze the fractional anisotropy (FA) and mean diffusivity (MD), reflecting the microstructural integrity of nerve fibers. Correlations of these differences with duration of pain and visual analog scale (VAS) scores were analyzed. Results No significant differences in the mean FA or MD values of the bilateral STT were observed between people with CNSP and HCs ( p > 0.05), as indicated by the two-sample t test. Further point-by-point comparison along 100 equidistant nodes within the STT pathway revealed significant reductions in FA values in the left (segments 12–18, 81–89) and right (segments 9–19, 76–80) STT in the CNSP group compared to HCs; significant increases in MD values were observed in the left (segments 1–13, 26–30, 71–91) and right (segments 8–17, 76–91) STT ( p < 0.05, FWE corrected). Partial correlation analysis indicates that in people with CNSP, the FA values of the STT in regions with damaged white matter structure show a negative correlation with VAS scores and duration of pain, whereas MD values show a positive correlation with VAS scores and duration of pain. Conclusion This study found that people with CNSP exhibit white matter microstructural abnormalities in the specific segments of STT. These abnormalities are associated with the patient’s pain intensity and disease duration. The findings offer a new neuroimaging perspective on the pathophysiological basis of chronic pain in the ascending conduction process and its potential role in developing targeted intervention strategies. However, due to the limited sample size and the lack of statistical significance when analyzing the entire spinothalamic tract, these conclusions should be interpreted with caution. Further research with larger cohorts is necessary to validate these results.

The circadian clock regulates physiological and biochemical processes in nearly every species. Sexual and reproductive behaviors are two processes controlled by the circadian timing system. Evidence supporting the importance of proper clock function on fertility comes from several lines of work demonstrating that misalignment of biological rhythms or disrupted function of the body’s master clock, such as occurs from repeated shift work or chronic jet lag, negatively impacts reproduction by interfering with both male and female fertility. Along these lines, dysregulation of clock genes leads to impairments in fertility within mammals, and disruption of circadian clock timing negatively impacts sex hormone levels and semen quality in males, and it leads to ovulatory deficiencies in females. Here, we review the current understanding of the circadian modulation of both male and female reproductive hormones—from animal models to humans. Further, we discuss neural circuits within the hypothalamus that may regulate circadian changes in mammalian sexual behavior and reproduction, and we explore how knowledge of such circuits in animal models may help to improve human sexual function, fertility, and reproduction.

The use of submillimeter resolution functional magnetic resonance imaging (fMRI) is increasing in popularity due to the prospect of studying human brain activation non-invasively at the scale of cortical layers and columns. This method, known as laminar fMRI, is inherently signal-to-noise ratio (SNR)-limited, especially at lower field strengths, with the dominant noise source being of thermal origin. Furthermore, laminar fMRI is challenged with signal displacements due to draining vein effects in conventional gradient-echo blood oxygen level-dependent (BOLD) imaging contrasts. fMRI contrasts such as cerebral blood volume (CBV)-sensitive vascular space occupancy (VASO) sequences have the potential to mitigate draining vein effects. However, VASO comes along with another reduction in detection sensitivity. NOise Reduction with DIstribution Corrected (NORDIC) PCA (principal component analysis) is a denoising technique specifically aimed at suppressing thermal noise, which has proven useful for increasing the SNR of high-resolution functional data. While NORDIC has been examined for BOLD acquisitions, its application to VASO data has been limited, which was the focus of the present study. We present a preliminary analysis to evaluate NORDIC’s capability to suppress thermal noise while preserving the VASO signal across a wide parameter space at 3T. For the data presented here, with a proper set of parameters, NORDIC reduced thermal noise with minimal bias on the underlying signal and preserved spatial resolution. Denoising performance was found to vary with different implementation strategies and parameter choices, for which we provide recommendations. We conclude that when applied properly, NORDIC has the potential to overcome the sensitivity limitations of laminar-specific VASO fMRI. Since very few groups currently have 3T VASO data, by sharing our analysis and code, we can compile and compare the effects of NORDIC across a broader range of acquisition parameters and study designs. Such a communal effort will help develop robust recommendations that will increase the utility of laminar fMRI at lower field strengths.

Purpose of the report Adults with Down Syndrome (DS) have a substantially increased risk for Alzheimer’s disease (AD) due to the triplicated amyloid-precursor-protein gene on chromosome 21, resulting in amyloid and tau accumulation. However, tau PET assessments are not sufficiently implemented in DS-AD research or clinical work-up, and second-generation tau tracers such as [ ¹⁸ F]PI-2620 have not been thoroughly characterized in adults with DS. We aim at illustrating feasibility and potential diagnostic value of tau PET imaging with [ ¹⁸ F]PI-2620 for the diagnosis of DS-AD. Materials and methods Five adults with DS (40% female, aged 43–62) and cognitive decline underwent clinical assessments, neuropsychological testing, lumbar puncture and multimodal neuroimaging. All underwent [ ¹⁸ F]PI-2620 tau PET. Visual read of tau PET scans was performed by three blinded raters, assessing increased tracer uptake in brain areas corresponding to the six Braak stage regions and basal ganglia. Results Visual read of tau burden revealed three tau-positive individuals which corresponded to their clinical decline while two cognitively stable individuals were rated as negative. Rating showed high inter-rater reliability for all Braak stages. Conclusion Tau PET imaging is a feasible and important biomarker assessment in the differential diagnosis of cognitive decline in adults with DS at risk of developing AD.