Search Results (379)

Sertraline, a selective serotonin reuptake inhibitor (SSRI), is commonly used to treat various psychiatric disorders such as depression and anxiety due to its ability to increase serotonin availability in the brain. Recent findings suggest that sertraline may also influence the expression of genes related to synaptic plasticity and neuronal signaling pathways. Alternative splicing, a process that allows a single gene to produce multiple protein isoforms, plays a crucial role in the regulation of neuronal functions and plasticity. Dysregulation of alternative splicing events has been linked to various neurodevelopmental and neurodegenerative diseases. This study aims to explore the effects of sertraline on alternative splicing events, including exon inclusion, exon exclusion, and mutually exclusive splicing events, in genes associated with neuronal function in Drosophila melanogaster and to use this model to investigate the molecular impacts of SSRIs on gene regulation in the nervous system. RNA sequencing (RNA-seq) was performed on central nervous system samples from Drosophila melanogaster adults exposed to sertraline for 24 h when they were third instar larvae. Alternative splicing events were analyzed to identify changes in exon inclusion and exclusion, as well as intron retention. Sertraline treatment significantly altered alternative splicing patterns in key genes related to neuronal stability and function. Specifically, sertraline promoted the inclusion of long Ank2 isoforms, suggesting enhanced axonal stability, and favored long ATPalpha isoforms, which support Na⁺/K⁺ ATPase activity essential for ionic balance and neuronal excitability. Intron retention in the yuri gene suggests that cytoskeletal reorganization could impact neuronal morphology. Additionally, splicing alterations in sxc and Atg18a indicate a potential influence of sertraline on epigenetic regulation and autophagy processes, fundamental aspects for neuronal plasticity and cellular homeostasis. These findings suggest that sertraline influences alternative splicing in the central nervous system of Drosophila melanogaster, potentially contributing to its therapeutic effects by modulating neuronal stability and adaptability. Full article

The neuroscience of language processing in the human brain has a long history. Strings of letters that form meaningful words trigger lexical and semantic processing, which in turn lead to conscious awareness of what the words mean. However, it is still unclear how the brain processes normal words differently from number words and, more interestingly, how the brain processes number words differently from digits, both of which are meant to trigger quantity processing. While much of the literature deals with this topic, the time course of the respective differences in brain activity has been largely ignored. This may be because most studies have used functional magnetic resonance imaging (fMRI), which is known to have limited temporal resolution. This study used electroencephalography (EEG), more specifically event-related potentials (ERPs), to investigate brain potential differences between visual presentations of words, non-words, number words and digits. This approach made it possible to describe the time course of brain activity evoked by these four stimulus categories. Starting at about 200 ms post-stimulus, digits elicited the strongest negative ERP in the right occipito-parietal cortical region. Peaking at around 300 ms after stimulus onset, number words elicited the most negative going ERP in the left occipito-parietal area. Finally, starting at about 400 ms after stimulus onset, digits elicited by far the most negative ERP in the left inferior fronto-temporal area. All of these findings are supported by analytical statistics across all study participants. It is noteworthy that the last effect in the left inferior fronto-temporal area can also be seen for number words, but it is much smaller and not statistically significant. In summary, we found clear differences between brain activity related to the processing of words, non-words, number words, and digits, providing evidence that the left inferior fronto-temporal cortical area is specialised for the processing of quantities. Furthermore, it can be concluded that digits are better symbols for mediating quantity processing in the human brain than number words. Full article

Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field. Being a multidisciplinary field, neuroeducation requires expertise in various fields such as education, neuroinformatics, psychology, cognitive science, and neuroscience. The need for a comprehensive guide where various important issues are presented and examples of their application in neuroeducation research projects are given is apparent. This paper presents an overview of the current hardware and software options, discusses methodological issues, and gives examples of best practices as found in the recent literature. These were selected by applying the PRISMA statement to results returned by searching PubMed, Scopus, and Google Scholar with the keywords “EEG and neuroeducation” for projects published in the last six years (2018–2024). Apart from the basic background knowledge, two research questions regarding methodological aspects (experimental settings and hardware and software used) and the subject of the research and type of information used from the EEG signals are addressed and discussed. Full article

Background: Olfactory dysfunction (OD) is an underestimated symptom in multiple sclerosis (MS). Multiple factors may play a role in the OD reported by MS patients, such as ongoing inflammation in the central nervous system (CNS), damage to the olfactory bulbs due to demyelination, and the presence of plaques in brain areas associated with the olfactory system. Indeed, neuroimaging studies in MS have shown a clear association of the OD with the number and activity of MS-related plaques in frontal and temporal brain regions. However, these studies have used only psychophysical tests to evaluate the OD in MS patients. Olfactory Event-Related Potentials (OERPs) are a method to assess olfaction with the clear advantage of its objectivity in comparison with psychophysical tests. The aim of this study was to investigate the association between the parameters of OERP components (latency and amplitude) and the lesion load of the brain regions which are involved in olfaction in a cohort of relapsing-remitting (RR) MS patients. Methods: In this cross-sectional study, we enrolled 30 RRMS patients and 30 healthy controls. The parameters of OERP components and magnetic resonance imaging data (lesions in the CNS) were analyzed in RRMS patients. Results: The association found between the RRMS patient groups with and without OERPs and the number of lesions in the frontal area as well as the correlation between the lesion load in the temporal area and OERP parameters suggest how brain alterations may impact on olfactory performance in MS. In addition, the predictive value of the number of lesions in the frontal and parietal areas for P2 amplitude also highlights the potential for OERP measures to serve as markers for disease progression in MS. Conclusions: This approach to assess the olfaction in MS could improve our understanding of the disease’s neurological impact and contribute to the development of new targeted interventions to mitigate olfactory sensory deficits. Full article

Background: Chronic hypoperfusion is a risk factor for neurodegenerative diseases. However, the sequence of events driving ischemia-induced functional changes in a cell-specific manner is unclear. Methods: To address this gap in knowledge, we used the bilateral common carotid artery stenosis (BCAS) mouse model, and evaluated progressive functional changes to neurons, arterioles, astrocytes, and microglial cells at 14 and 28 days post-BCAS surgery. To assess the neuro-glio-vascular response to an acute ischemic insult, brain slices were superfused with low O₂ conditions. Using whole-cell patch-clamp electrophysiology, we measured basic membrane properties (e.g., resting membrane potential, capacitance, input resistance) in cortical pyramidal neurons. The activity of astrocytes was evaluated by monitoring Ca²⁺ from Aldh1l1-CreERT2; R26-lsl-GCaMP6f mice. Vascular reactivity to low O₂ from the BCAS mice was also assessed ex vivo. Results: Our data showed no changes to the basic membrane properties of cortical pyramidal neurons. On the other hand, astrocyte activity was characterized by a progressive increase in the resting Ca²⁺. Notably, at 14 and 28 days post-BCAS, there was an increased expression of anti-inflammatory-related markers (IL-10, S100A10, TRPA1, and Nrf2). These data suggest that, in young mice, BCAS-induced increases in resting Ca²⁺ were associated with the expression of neuroprotective signals. Contrary to observations in glial cells, vascular function was impaired post-BCAS surgery, as shown by a blunted vasodilatory response to low O₂ and the vasodilatory signal, adenosine. Conclusions: Together, these data suggest that, in young mice, BCAS leads to vascular dysfunction (e.g., impaired vasodilation in parenchymal arterioles), and in the absence of neuronal dysfunction, mild ischemia is associated with the activation of glial-derived neuroprotective signals. Full article

Traditional tactile brain–computer interfaces (BCIs), particularly those based on steady-state somatosensory–evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contrast, using transient electrical stimuli offers a promising alternative for generating tactile BCI control signals: somatosensory event-related potentials (sERPs). This study aimed to optimize the performance of a novel electrotactile BCI by employing advanced feature extraction and machine learning techniques on sERP signals for the classification of users’ selective tactile attention. The experimental protocol involved ten healthy subjects performing a tactile attention task, with EEG signals recorded from five EEG channels over the sensory–motor cortex. We employed sequential forward selection (SFS) of features from temporal sERP waveforms of all EEG channels. We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. We explored the effects of the number of stimuli required to obtain sERP features for classification and their influence on accuracy and information transfer rate. Our approach indicated significant improvements in classification accuracy compared to previous studies. We demonstrated that the number of stimuli for sERP generation can be reduced while increasing the information transfer rate without a statistically significant decrease in classification accuracy. In the case of the support vector machine classifier, we achieved a mean accuracy over 90% for 10 electrical stimuli, while for 6 stimuli, the accuracy decreased by less than 7%, and the information transfer rate increased by 60%. This research advances methods for tactile BCI control based on event-related potentials. This work is significant since tactile stimulation is an understudied modality for BCI control, and electrically induced sERPs are the least studied control signals in reactive BCIs. Exploring and optimizing the parameters of sERP elicitation, as well as feature extraction and classification methods, is crucial for addressing the accuracy versus speed trade-off in various assistive BCI applications where the tactile modality may have added value. Full article

Background: Auditory–tactile integration is an important research area in multisensory integration. Especially in special environments (e.g., traffic noise and complex work environments), auditory–tactile integration is crucial for human response and decision making. We investigated the influence of attention on the temporal course and spatial distribution of auditory–tactile integration. Methods: Participants received auditory stimuli alone, tactile stimuli alone, and simultaneous auditory and tactile stimuli, which were randomly presented on the left or right side. For each block, participants attended to all stimuli on the designated side and detected uncommon target stimuli while ignoring all stimuli on the other side. Event-related potentials (ERPs) were recorded via 64 scalp electrodes. Integration was quantified by comparing the response to the combined stimulus to the sum of the responses to the auditory and tactile stimuli presented separately. Results: The results demonstrated that compared to the unattended condition, integration occurred earlier and involved more brain regions in the attended condition when the stimulus was presented in the left hemispace. The unattended condition involved a more extensive range of brain regions and occurred earlier than the attended condition when the stimulus was presented in the right hemispace. Conclusions: Attention can modulate auditory–tactile integration and show systematic differences between the left and right hemispaces. These findings contribute to the understanding of the mechanisms of auditory–tactile information processing in the human brain. Full article

The purpose of this longitudinal pilot study was to add to the body of research relating to head kinematics/vibration in sport and their potential to cause short-term alterations in brain function. In horseracing, due to the horse’s movement, repeated low-level accelerations are transmitted to the jockey’s head. To measure this, professional jockeys (2 male, 2 female) wore an inertial measurement unit (IMU) to record their head kinematics while riding out. In addition, a short battery of tests (Stroop, Trail Making Test B, choice reaction time, manual dexterity, and visual function) was completed immediately before and after riding. Pre- and post-outcome measures from the cognitive test battery were compared using descriptive statistics. The average head kinematics measured across all jockeys and days were at a low level: resultant linear acceleration peak = 5.82 ± 1.08 g, mean = 1.02 ± 0.01 g; resultant rotational velocity peak = 10.37 ± 3.23 rad/s, mean = 0.85 ± 0.15 rad/s; and resultant rotational acceleration peak = 1495 ± 532.75 rad/s², mean = 86.58 ± 15.54 rad/s². The duration of an acceleration event was on average 127.04 ± 17.22 ms for linear accelerations and 89.42 ± 19.74 ms for rotational accelerations. This was longer than those noted in many impact and non-impact sports. Jockeys experienced high counts of linear and rotational head accelerations above 3 g and 400 rad/s², which are considered normal daily living levels (average 300 linear and 445 rotational accelerations per hour of riding). No measurable decline in executive function or dexterity was found after riding; however, a deterioration in visual function (near point convergence and accommodation) was seen. This work lays the foundation for future large-scale research to monitor the head kinematics of riders, measure the effects and understand variables that might influence them. Full article

Schizophrenia is a complex neuropsychiatric disorder characterized by disruptions in brain connectivity and cognitive functioning. Continuous monitoring of neural activity is essential, as it allows for the detection of subtle changes in brain connectivity patterns, which could provide early warnings of cognitive decline or symptom exacerbation, ultimately facilitating timely therapeutic interventions. This paper proposes a novel approach for detecting schizophrenia-related abnormalities using deep learning (DL) techniques applied to electroencephalogram (EEG) data. Using an openly available EEG dataset on schizophrenia, the focus is on preprocessed event-related potentials (ERPs) from key electrode sites and applied transfer entropy (TE) analysis to quantify the directional flow of information between brain regions. TE matrices were generated to capture neural connectivity patterns, which were then used as input for a hybrid DL model, combining convolutional neural networks (CNNs) and Bidirectional Long Short-Term Memory (BiLSTM) networks. The model achieved a performant accuracy of 99.94% in classifying schizophrenia-related abnormalities, demonstrating its potential for real-time mental health monitoring. The generated TE matrices revealed significant differences in connectivity between the two groups, particularly in frontal and central brain regions, which are critical for cognitive processing. These findings were further validated by correlating the results with EEG data obtained from the Muse 2 headband, emphasizing the potential for portable, non-invasive monitoring of schizophrenia in real-world settings. The final model, integrated into the NeuroPredict platform, offers a scalable solution for continuous mental health monitoring. By incorporating EEG data, heart rate, sleep patterns, and environmental metrics, NeuroPredict facilitates early detection and personalized interventions for schizophrenia patients. Full article

Objectives: Naturally, there are several challenges, such as muscular artifacts, ocular movements and electrical interferences that depend on precise diagnosis and classification, which hamper exact epileptic seizure detection. This study has been conducted to improve seizure detection accuracy in epilepsy patients using an advanced preprocessing technique that could remove such noxious artifacts. Methods: In the frame of this paper, the core tool in the area of epilepsy, EEG, will be applied to record and analyze the electrical patterns of the brain. The dataset includes recordings of seven epilepsy patients taken by the Unit of Neurology and Neurophysiology, University of Siena. The preprocessing techniques employed include advanced artifact removal and signal enhancement methods. We introduced Peak-to-Peak Amplitude Fluctuation (PPAF) to assess amplitude variability within Event-Related Potential (ERP) waveforms. This approach was applied to data from patients experiencing 3–5 seizures, categorized into three distinct groups. Results: The results indicated that the frontal and parietal regions, particularly the electrode areas Cz, Pz and Fp2, are the main contributors to epileptic seizures. Additionally, the implementation of the PPAF metric enhanced the effectiveness of seizure detection and classification algorithms, achieving accuracy rates of 99%, 98% and 95% for datasets with three, four and five seizures, respectively. Conclusions: The present research extends the epilepsy diagnosis with clues on brain activity during seizures and further demonstrates the effectiveness of advanced preprocessing techniques. The introduction of PPAF as a metric could have promising potential in improving both the accuracy and reliability of epilepsy seizure detection algorithms. These observations provide important implications for control and treatment both in focal and in generalized epilepsy. Full article

Background: Anti-phospholipid syndrome (APS) has emerged as a significant issue in autoimmune diseases over recent decades. Its hallmark feature is thromboembolic events, potentially affecting any vascularized area including the microcirculation of the inner ear. Since the first case report of APS-related audiovestibular dysfunction described in 1993, numerous reports have explored the association between APS-related antibodies and audiovestibular dysfunction. These studies indicate a higher prevalence of APS-related antibodies in patients with sensorineural hearing loss compared to healthy controls. Unlike other idiopathic hearing loss disorders, audiovestibular dysfunction associated with APS may respond to appropriate treatments, highlighting the importance of timely recognition by clinicians to potentially achieve favorable outcomes. Therefore, this systematic review aims to consolidate current evidence on the characteristics, pathophysiology, assessment, and management of audiovestibular dysfunction linked to APS. Methods: This systematic review utilized electronic searches of the PubMed, Embase, ClinicalKey, Web of Science, and ScienceDirect online platforms. The initial search was performed on 27 January 2024, with the final update search completed on 20 June 2024. Results: Based on theoretical pathophysiology, anticoagulation emerges as a pivotal treatment strategy. Additionally, drawing from our preliminary data, we propose a modified protocol combining anticoagulants, steroids, and non-invasive brain stimulation to offer clinicians a novel therapeutic approach for managing these symptoms. Conclusions: Clinicians are encouraged to remain vigilant about the possibility of APS and its complex audiovestibular manifestations, as prompt intervention could stabilize audiovestibular function effectively. Full article

Objectives: Teachers’ intention understanding ability reflects their professional insight, which is the basis for effective classroom teaching activities. However, the cognitive process and brain mechanism of how teachers understand students’ action intention in class are still unclear. Methods: This study used event-related potential (ERP) technology to explore the cognitive neural differences in intention understanding ability among teachers with different levels of knowledge and experience. The experiment used the comic strips paradigm to examine the ability of expert and novice teachers to understand students’ normative and non-normative classroom actions under different text prompts (“how” and “why”). Results: The results revealed that in the late time window, expert teachers induced larger P300 and LPC amplitudes when they understood students’ classroom action intentions, while the N250 amplitudes induced by novice teachers in the early time window were significantly larger. In addition, for both types of teachers, when understanding the intentions behind students’ normative actions, the N250 amplitude was the most significant, while the P300 and LPC amplitudes were more significant for non-normative actions. Conclusions: This study found that teachers at varying professional development stages had different time processing processes in intention understanding ability, which supported teachers’ brain electrophysiological activities related to social ability. Full article

Background: Many studies have demonstrated the benefits of long-term music training (i.e., musicianship) on the neural processing of sound, including simple tones and speech. However, the effects of musicianship on the encoding of simultaneously presented pitches, in the form of complex musical chords, is less well established. Presumably, musicians’ stronger familiarity and active experience with tonal music might enhance harmonic pitch representations, perhaps in an attention-dependent manner. Additionally, attention might influence chordal encoding differently across the auditory system. To this end, we explored the effects of long-term music training and attention on the processing of musical chords at the brainstem and cortical levels. Method: Young adult participants were separated into musician and nonmusician groups based on the extent of formal music training. While recording EEG, listeners heard isolated musical triads that differed only in the chordal third: major, minor, and detuned (4% sharper third from major). Participants were asked to correctly identify chords via key press during active stimulus blocks and watched a silent movie during passive blocks. We logged behavioral identification accuracy and reaction times and calculated information transfer based on the behavioral chord confusion patterns. EEG data were analyzed separately to distinguish between cortical (event-related potential, ERP) and subcortical (frequency-following response, FFR) evoked responses. Results: We found musicians were (expectedly) more accurate, though not faster, than nonmusicians in chordal identification. For subcortical FFRs, responses showed stimulus chord effects but no group differences. However, for cortical ERPs, whereas musicians displayed P2 (~150 ms) responses that were invariant to attention, nonmusicians displayed reduced P2 during passive listening. Listeners’ degree of behavioral information transfer (i.e., success in distinguishing chords) was also better in musicians and correlated with their neural differentiation of chords in the ERPs (but not high-frequency FFRs). Conclusions: Our preliminary results suggest long-term music training strengthens even the passive cortical processing of musical sounds, supporting more automated brain processing of musical chords with less reliance on attention. Our results also suggest that the degree to which listeners can behaviorally distinguish chordal triads is directly related to their neural specificity to musical sounds primarily at cortical rather than subcortical levels. FFR attention effects were likely not observed due to the use of high-frequency stimuli (>220 Hz), which restrict FFRs to brainstem sources. Full article

Multiciliated cells (MCCs) serve many important functions, including fluid propulsion and chemo- and mechanosensing. Diseases ranging from rare conditions to the recent COVID-19 global health pandemic have been linked to MCC defects. In recent years, the zebrafish has emerged as a model to investigate the biology of MCCs. Here, we review the major events in MCC formation including centriole biogenesis and basal body docking. Then, we discuss studies on the role of MCCs in diseases of the brain, respiratory, kidney and reproductive systems, as well as recent findings about the link between MCCs and SARS-CoV-2. Next, we explore why the zebrafish is a useful model to study MCCs and provide a comprehensive overview of previous studies of genetic components essential for MCC development and motility across three major tissues in the zebrafish: the pronephros, brain ependymal cells and nasal placode. Taken together, here we provide a cohesive summary of MCC research using the zebrafish and its future potential for expanding our understanding of MCC-related disease states. Full article

Background: The evaluation of evidence, which frequently takes the form of scientific evidence, necessitates the input of experts in relevant fields. The results are presented as expert opinions or expert evaluations, which are generally accepted as a reliable representation of the facts. A further issue that remains unresolved though is the process of evaluating the expertise and knowledge of an expert in the first instance. In general, earned certificates, grades and other objective criteria are typically regarded as representative documentation to substantiate an expert status. However, there is a possibility that these may not always be sufficiently representative. Objectives: The goal of the present study was to provide evidence that the neural processing of law-relevant and law-irrelevant terms varies significantly between participants who have received training in the field of law (experts) and those who have not (novices). Methods: To this end, changes in brain activity were recorded via electroencephalography (EEG) during visual presentations of terms belonging to five different categories (fake right, democracy, filler word, basic right and rule of law). Event-related potentials (ERPs) were subsequently averaged for each category and subjected to statistical analysis. Results: The results clearly demonstrate that participants trained in law processed fake rights and filler words in a similar manner. Furthermore, both of these conditions elicited different levels of brain activity compared to all law-relevant terms. This was not the case in participants who had not received legal training. The brains of untrained participants processed all five term categories in a strikingly similar manner. In light of prior knowledge regarding language processing, the primary focus was on two distinct electrode locations: one in the left posterior region, and the other in the left frontal region. In both locations, the most prominent differences in brain activity elicited by the aforementioned term categories in law-trained participants occurred approximately 450 milliseconds after stimulus onset. The results were further corroborated by a repeated-measures ANOVA and subsequent t-tests, which also demonstrated the absence of this effect in law-untrained participants. Conclusions: The findings of this study provide empirical evidence that brain activity measurements, in particular ERPs, can be used to distinguish between experts trained in a specific field of expertise and novices in that field. Such findings have the potential to facilitate objective assessments of expertise, enabling comparisons between experts and novices that extend beyond traditional criteria such as qualifications and experience. Instead, individuals can be evaluated based on their cognitive processes, as observed through brain activity. Full article