Search Results (89)

This article presents the development of a serious game designed to help individuals improve their ability to relax and self-regulate, with a particular focus on children. Additionally, the game has the potential to become an effective tool for intervention in individuals with Attention Deficit Hyperactivity Disorder (ADHD) due to its integration of critical elements for measuring attention levels. These include omission errors, commission errors, response times, standard deviations of response times, and other relevant variables. The game allows control through electroencephalographic (EEG) signals, using alpha wave modulation and blinking as interaction methods. The amplification of alpha wave amplitude is associated with states of relaxation and mental tranquility, indicating that their modulation could potentially mitigate anxiety and enhance emotional self-regulation. The game’s primary objective is to encourage participants to attain relaxing mental states by overcoming challenges as they progress. In order to achieve this, the game’s development necessitated a comprehensive understanding of EEG signal processing, a crucial aspect meticulously explored in this article. In addition, this paper presents the results of alpha wave and flicker detection, along with a performance analysis that demonstrates satisfactory results. Subsequently, the game was assessed with children to evaluate its effectiveness, facilitating a comprehensive analysis of various performance parameters. The findings indicate that the game facilitates the gradual improvement of participants’ skills with each iteration, notably enhancing their capacity to achieve a state of relaxation. Full article

Background: The utility of single-pulse TMS (transcranial magnetic stimulation)-evoked EEG (electroencephalograph) potentials (TEPs) has been extensively studied in the past three decades. TEPs have been shown to provide insights into features of cortical excitability and connectivity, reflecting mechanisms of excitatory/inhibitory balance, in various neurological and psychiatric conditions. In the present study, we sought to review and summarize the most studied neurological and psychiatric clinical indications utilizing single-pulse TEP and describe its promise as an informative novel tool for the evaluation of brain physiology. Methods: A thorough search of PubMed, Embase, and Google Scholar for original research utilizing single-pulse TMS-EEG and the measurement of TEP was conducted. Our review focused on the indications and outcomes most clinically relevant, commonly studied, and well-supported scientifically. Results: We included a total of 55 publications and summarized them by clinical application. We categorized these publications into seven sub-sections: healthy aging, Alzheimer’s disease (AD), disorders of consciousness (DOCs), stroke rehabilitation and recovery, major depressive disorder (MDD), Parkinson’s disease (PD), as well as prediction and monitoring of treatment response. Conclusions: TEP is a useful measurement of mechanisms underlying neuronal networks. It may be utilized in several clinical applications. Its most prominent uses include monitoring of consciousness levels in DOCs, monitoring and prediction of treatment response in MDD, and diagnosis of AD. Additional applications including the monitoring of stroke rehabilitation and recovery, as well as a diagnostic aid for PD, have also shown encouraging results but require further evidence from randomized controlled trials (RCTs). Full article

The use of eye tracking technology, together with other physiological measurements such as psychogalvanic skin response (GSR) and electroencephalographic (EEG) recordings, provides researchers with information about users’ physiological behavioural responses during their learning process in different types of tasks. These devices produce a large volume of data. However, in order to analyse these records, researchers have to process and analyse them using complex statistical and/or machine learning techniques (supervised or unsupervised) that are usually not incorporated into the devices. The objectives of this study were (1) to propose a procedure for processing the extracted data; (2) to address the potential technical challenges and difficulties in processing logs in integrated multichannel technology; and (3) to offer solutions for automating data processing and analysis. A Notebook in Jupyter is proposed with the steps for importing and processing data, as well as for using supervised and unsupervised machine learning algorithms. Full article

Background. Pain is known to negatively impact attention, but its influence on more complex cognitive abilities, such as logical reasoning, remains inconsistent. This may be due to compensatory mechanisms (e.g., investing additional resources), which might not be detectable at the behavioral level but can be observed through psychophysiological measures. In this study, we investigated whether experimentally induced pain affects logical reasoning and underlying attentional mechanisms, using both behavioral and electroencephalographic (EEG) measures. Methods. A total of 98 female participants were divided into a pain-free control group (N = 47) and a pain group (N = 51). Both groups completed the Advanced Progressive Matrices (APM) task, with EEG recordings capturing task-related power (TRP) changes in the upper alpha frequency band (10–12 Hz). We used a mixed design where all participants completed half of the APM task in a pain-free state (control condition); the second half was completed under pain induction by the pain group but not the pain-free group (experimental condition). Results. Logical reasoning performance, as measured by APM scores and response times, declined during the experimental condition, compared to the control condition for both groups, indicating that the second part of the APM was more difficult than the first part. However, no significant differences were found between the pain and pain-free groups, suggesting that pain did not impair cognitive performance at the behavioral level. In contrast, EEG measures revealed significant differences in upper alpha band power, particularly at fronto-central sites. In the pain group, the decrease in TRP during the experimental condition was significantly smaller compared to both the control condition and the pain-free group. Conclusions. Pain did not impair task performance at the behavioral level but reduced attentional resources, as reflected by changes in upper alpha band activity. This underscores the importance of incorporating more sensitive psychophysiological measures alongside behavioral measures to better understand the impact of pain on cognitive processes. Full article

Background/Objectives: Given the importance of emotion recognition for communication purposes, and the impairment for such skill in CI users despite impressive language performances, the aim of the present study was to investigate the neural correlates of emotion recognition skills, apart from language, in adult unilateral CI (UCI) users during a music in noise (happy/sad) recognition task. Furthermore, asymmetry was investigated through electroencephalographic (EEG) rhythm, given the traditional concept of hemispheric lateralization for emotional processing, and the intrinsic asymmetry due to the clinical UCI condition. Methods: Twenty adult UCI users and eight normal hearing (NH) controls were recruited. EEG gamma and alpha band power was assessed as there is evidence of a relationship between gamma and emotional response and between alpha asymmetry and tendency to approach or withdraw from stimuli. The TAS-20 questionnaire (alexithymia) was completed by the participants. Results: The results showed no effect of background noise, while supporting that gamma activity related to emotion processing shows alterations in the UCI group compared to the NH group, and that these alterations are also modulated by the etiology of deafness. In particular, relative higher gamma activity in the CI side corresponds to positive processes, correlated with higher emotion recognition abilities, whereas gamma activity in the non-CI side may be related to positive processes inversely correlated with alexithymia and also inversely correlated with age; a correlation between TAS-20 scores and age was found only in the NH group. Conclusions: EEG gamma activity appears to be fundamental to the processing of the emotional aspect of music and also to the psychocognitive emotion-related component in adults with CI. Full article

The neural basis of tactile processing in humans has been extensively studied; however, the neurophysiological basis of human width discrimination remains relatively unexplored. In particular, the changes that occur in neural networks underlying active tactile width discrimination learning have yet to be described. Here, it is hypothesized that subjects learning to perform the active version of the width discrimination task would present changes in behavioral data and in the neurophysiological activity, specifically in networks of electrodes relevant for tactile and motor processing. The specific hypotheses tested here were that the performance and response latency of subjects would change between the first and the second blocks; the power of the different frequency bands would change between the first and the second blocks; electrode F4 would encode task performance and response latency through changes in the power of the delta, theta, alpha, beta, and low-gamma frequency bands; the relative power in the alpha and beta frequency bands in electrodes C3 and C4 (Interhemispheric Spectral Difference—ISD) would change because of learning between the first and the second blocks. To test this hypothesis, we recorded and analyzed electroencephalographic (EEG) activity while subjects performed a session where they were tested twice (i.e., two different blocks) in an active tactile width discrimination task using their right index finger. Subjects (n = 18) presented high performances (high discrimination accuracy) already in their first block, and therefore no significant improvements were found in the second block. Meanwhile, a reduction in response latency was observed between the two blocks. EEG recordings revealed an increase in power for the low-gamma frequency band (30–45 Hz) for electrodes F3 and C3 from the first to the second block. This change was correlated with neither performance nor latency. Analysis of the neural activity in electrode F4 revealed that the beta frequency band encoded the subjects’ performance. Meanwhile, the delta frequency band in the same electrode revealed a complex pattern where blocks appeared clustered in two different patterns: an Upper Pattern (UP), where power and latency were highly correlated (Rho = 0.950), and a sparser and more uncorrelated Lower Pattern (LP). Blocks belonging to the UP or LP patterns did not differ in performance and were not specific to the first or the second block. However, blocks belonging to the LP presented an increase in response latency, increased variability in performance, and an increased ISD in alpha and beta frequency bands for the pair of electrodes C3–C4, suggesting that the LP may reflect a state related to increased cognitive load or task difficulty. These results suggest that changes in performance and latency in an active tactile width discrimination task are encoded in the delta, alpha, beta, and low-gamma frequency bands in a fronto-central network. The main contribution of this study is therefore related to the description of neural dynamics in frontal and central networks involved in the learning process of active tactile width discrimination. Full article

This study explores the potential of using a Siamese Network as a biomarker for assessing the effectiveness of Dolphin-Assisted Therapy (DAT) in children with Spastic Cerebral Palsy (SCP). The problem statement revolves around the need for objective measures to evaluate the impact of DAT on patients with SCP, considering the subjective nature of traditional assessment methods. The methodology involves training a Siamese network, a type of neural network designed to compare similarities between inputs, using data collected from SCP patients undergoing DAT sessions. The study employed Event-Related Potential (ERP) and Fast Fourier Transform (FFT) analyses to examine cerebral activity and brain rhythms, proposing the use of SNN to compare electroencephalographic (EEG) signals of children with cerebral palsy before and after Dolphin-Assisted Therapy. Testing on samples from four children yielded a high average similarity index of 0.9150, indicating consistent similarity metrics before and after therapy. The network is trained to learn patterns and similarities between pre- and post-therapy evaluations, in order to identify biomarkers indicative of therapy effectiveness. Notably, the Siamese Network’s architecture ensures that comparisons are made within the same feature space, allowing for more accurate assessments. The results of the study demonstrate promising findings, indicating different patterns in the output of the Siamese Network that correlate with improvements in symptoms of SCP post-DAT. Confirming these observations will require large, longitudinal studies but such findings would suggest that the Siamese Network could have utility as a biomarker in monitoring treatment responses for children with SCP who undergo DAT and offer them more objective as well as quantifiable manners of assessing therapeutic interventions. Great discrepancies in neuronal voltage perturbations, 7.9825 dB on average at the specific samples compared to the whole dataset (6.2838 dB), imply a noted deviation from resting activity. These findings indicate that Dolphin-Assisted Therapy activates particular brain regions specifically during the intervention. Full article

This study investigates the feasibility of a novel brain–computer interface (BCI) device designed for sensory training following stroke. The BCI system administers electrotactile stimuli to the user’s forearm, mirroring classical sensory training interventions. Concurrently, selective attention tasks are employed to modulate electrophysiological brain responses (somatosensory event-related potentials—sERPs), reflecting cortical excitability in related sensorimotor areas. The BCI identifies attention-induced changes in the brain’s reactions to stimulation in an online manner. The study protocol assesses the feasibility of online binary classification of selective attention focus in ten subacute stroke patients. Each experimental session includes a BCI training phase for data collection and classifier training, followed by a BCI test phase to evaluate online classification of selective tactile attention based on sERP. During online classification tests, patients complete 20 repetitions of selective attention tasks with feedback on attention focus recognition. Using a single electroencephalographic channel, attention classification accuracy ranges from 70% to 100% across all patients. The significance of this novel BCI paradigm lies in its ability to quantitatively measure selective tactile attention resources throughout the therapy session, introducing a top-down approach to classical sensory training interventions based on repeated neuromuscular electrical stimulation. Full article

Lennox–Gastaut syndrome (LGS) is a severe developmental and epileptic encephalopathy characterized by drug-resistant seizures, cognitive impairments, and abnormal electroencephalographic patterns. Vagus nerve stimulation (VNS) is a widely used neuromodulation therapy for LGS, but its effects on seizure outcomes, different seizure types, non-seizure outcomes, and adverse events in this population have not been comprehensively reviewed. To conduct a scoping review on the use of VNS in LGS, a literature search was performed in PubMed, OVID, Web of Science, and Embase from inception to 9 June 2024, using relevant keywords and without restrictions on study design. The search yielded forty eligible studies (twenty-four retrospective cohorts, fourteen prospective cohorts, and two registry analyses) comprising 1400 LGS patients treated with VNS. No randomized controlled trials were identified. Across studies, the median seizure reduction ranged from 20.6% to 65%, with 0% to 100% of patients achieving a ≥50% seizure reduction. No consistent preoperative biomarker of VNS responsiveness was identified in LGS. Although inconsistent among different studies, tonic, atonic, and tonic–clonic seizures responded best, while focal seizures responded worst. Improvements in seizure severity, alertness, and quality of life were reported in some studies, but cognitive and adaptive functioning generally remained unchanged. Adverse events were mostly mild and transient, including hoarseness, cough, and paresthesia. Device-related complications and infections were uncommon. In conclusion, further research is needed to better understand VNS’s position in the evolving LGS treatment landscape and its cost effectiveness. Full article

Individuals grappling with severe central nervous system injuries often face significant challenges related to sensorimotor function and communication abilities. In response, brain–computer interface (BCI) technology has emerged as a promising solution by offering innovative interaction methods and intelligent rehabilitation training. By leveraging electroencephalographic (EEG) signals, BCIs unlock intriguing possibilities in patient care and neurological rehabilitation. Recent research has utilized covariance matrices as signal descriptors. In this study, we introduce two methodologies for covariance matrix analysis: multiple tangent space projections (M-TSPs) and Cholesky decomposition. Both approaches incorporate a classifier that integrates linear and nonlinear features, resulting in a significant enhancement in classification accuracy, as evidenced by meticulous experimental evaluations. The M-TSP method demonstrates superior performance with an average accuracy improvement of 6.79% over Cholesky decomposition. Additionally, a gender-based analysis reveals a preference for men in the obtained results, with an average improvement of 9.16% over women. These findings underscore the potential of our methodologies to improve BCI performance and highlight gender-specific performance differences to be examined further in our future studies. Full article

Purpose: A growing body of evidence has shown that electroencephalography (EEG) is an interesting method of assessing the underlying brain physiology associated with disordered eating. Using EEG, we sought to evaluate brain reactivity to hyper-palatable food cues in undergraduate students with disordered eating behavior (DEB). Methods: After assessing the eating behaviors of twenty-six undergraduate students using the Eating Attitudes Test (EAT-26), electroencephalographic signals were recorded while the participants were presented with pictures of hyper-palatable food. The current study used a temporospatial principal component analysis (PCA) approach to identify event-related potential (ERP) responses that differed between DEB and non-DEB individuals. Results: A temporospatial PCA applied to the ERPs identified a positivity with a maximum amplitude at 347 ms at the occipital–temporal electrodes in response to pictures of hyper-palatable food. This positivity was correlated with the EAT-26 scores. Participants with DEB showed reduced positivities in this component compared with those without DEB. Conclusion: Our findings may reflect greater motivated attention toward hyper-palatable food cues in undergraduate students with DEB. These results are an important step toward obtaining a more refined understanding of specific abnormalities related to reactivity to food cues in this population. Full article

This study explored the role of sensorimotor simulation in modulating the stress response in individuals exposed to stressful digital simulated interviews. Participants were assigned to two different versions of a Digital Social Stress Test: a simulated version with a dynamic–realistic examining committee (Dyn-DSST) and a version with a static examining committee (Stat-DSST). During interview preparation, behavioral indices reflecting stress regulation and resistance, response times, and electroencephalographic (EEG) and autonomic indices were collected. Higher regulation scores were found for the Stat-DSST group compared to the Dyn-DSST group, probably induced by the presence of limited external sensory input in time and space, perceived as less stressful. The EEG results revealed a distinct contribution of the low- and high-frequency bands for both groups. Dyn-DSST required greater cognitive regulation effort due to the presence of a continuous flow of information, which can enhance sensory and motor activation in the brain. The SCR increased in the Dyn-DSST group compared to the Stat-DSST group, reflecting greater emotional involvement in the Dyn-DSST group and reduced sensory stimulation in the static version. In conclusion, the results suggest that sensorimotor simulation impacts the stress response differently in dynamic interviews compared to static ones, with distinct profiles based on behavioral, EEG, and autonomic measures. Full article

Objective: The present pilot study aimed to propose an innovative scale-independent measure based on electroencephalographic (EEG) signals for the identification and quantification of the magnitude of chronic pain. Methods: EEG data were collected from three groups of participants at rest: seven healthy participants with pain, 15 healthy participants submitted to thermal pain, and 66 participants living with chronic pain. Every 30 s, the pain intensity score felt by the participant was also recorded. Electrodes positioned in the contralateral motor region were of interest. After EEG preprocessing, a complex analytical signal was obtained using Hilbert transform, and the upper envelope of the EEG signal was extracted. The average coefficient of variation of the upper envelope of the signal was then calculated for the beta (13–30 Hz) band and proposed as a new EEG-based indicator, namely Piq_β, to identify and quantify pain. Main results: The main results are as follows: (1) A Piq_β threshold at 10%, that is, Piq_β ≥ 10%, indicates the presence of pain, and (2) the higher the Piq_β (%), the higher the extent of pain. Conclusions: This finding indicates that Piq_β can objectively identify and quantify pain in a population living with chronic pain. This new EEG-based indicator can be used for objective pain assessment based on the neurophysiological body response to pain. Significance: Objective pain assessment is a valuable decision-making aid and an important contribution to pain management and monitoring. Full article

Recent research in architectural neuroscience has found that visual exposure to biophilic design may help reduce occupant physiological stress responses. However, there are still significant gaps in our understanding of the complex ways in which biophilic design impacts on building occupant neurophysiology. The relationship between visual exposure to biophilic design and neurophysiological responses such as neuroinflammation have yet to be directly investigated. This paper examines the results of a pilot study that was established to investigate the relationship between visual exposure to biophilic design and neuroinflammation, as mediated by physiological stress responses. The pilot study utilised a 32-channel quantitative electroencephalograph (qEEG) to assess the relative changes in neuroinflammatory markers (relative alpha and relative delta power band activity) of 10 participants while they were exposed to 2D digital images of buildings that visually expressed varying degrees of biophilic design. Participants exhibited a decrease in relative delta power when exposed to higher levels of biophilic design. No statistically significant changes in relative alpha power were observed. These findings suggest that exposure to buildings with higher degrees of biophilia may result in decreased neuroinflammatory activity. In doing so, this research works to further develop our understanding of the complex ways in which the built environment impacts on occupant neuroinflammation and physiological stress. Full article

The nociceptive withdrawal reflex (NWR) is a physiological, polysynaptic spinal reflex occurring in response to noxious stimulations. Continuous NWR threshold (NWRt) tracking has been shown to be possibly useful in the depth of anesthesia assessment. The primary aim of this study was to describe how propofol modulates the NWRt over time in pigs. Five juvenile pigs (anesthetized three times) were included. An intravenous (IV) infusion of propofol (20 mg/kg/h) was started, and boli were administered to effect until intubation. Afterwards, the infusion was increased every ten minutes by 6 mg/kg/h, together with an IV bolus of 0.5 mg/kg, until reaching an electroencephalographic suppression ratio (SR) of between 10% and 30%. The NWRt was continuously monitored. For data analysis, the time span between 15 min following intubation and the end of propofol infusion was considered. Individual durations of propofol administration were divided into five equal time intervals for each pig (TI1–TI5). A linear regression between NWRt and TI was performed for each pig. Moreover, the baseline NWRt and slopes of the linear regression (b1) were compared among days using a Friedman Repeated Measures Analysis of Variance on Ranks. The NWRt always increased with the propofol dose (b1 = 4.71 ± 3.23; mean ± standard deviation). No significant differences were found between the baseline NWRt and the b1 values. Our results suggest that the NWRt may complement the depth of anesthesia assessment in pigs receiving propofol. Full article