Frontiers in Human Neuroscience最新文献

Introduction: Global Visual Selective Attention (VSA) is the ability to integrate multiple visual elements of a scene to achieve visual overview. This is essential for navigating crowded environments and recognizing objects or faces. Clinical pediatric research on global VSA deficits primarily focuses on autism spectrum disorder (ASD). However, in children with cerebral visual impairment (CVI) and other neurodevelopmental disorders (ADHD, dyslexia) similar deficits are reported. The aim of this study was to investigate global VSA performance in children with CVI, ADHD, dyslexia and neurotypical children by combing gaze-based measures with conventional neuropsychological tasks.

Methods: We included children aged 6-12 years with CVI (n = 20), ADHD (n = 30), dyslexia (n = 34) and neurotypical development (n = 37), all with normal verbal IQ. Eye tracking measurements were stepwise introduced within three global VSA tasks: Gestalt Closure (no eye tracking), Navon stimuli (eye tracking-based qualitative analysis) and Kanizsa Illusory Contours (KIC; eye tracking-based quantitative analysis). Verbal responses were compared with non-verbal gaze behavior.

Results: Children with CVI had significantly lower success rates on Gestalt Closure recognition, prolonged verbal response times on Navon stimuli, and decreased verbal and gaze performance on the KIC task compared to all other groups, irrespective of visual acuity. Children with ADHD and dyslexia performed similar to neurotypical children on all tasks.

Discussion: The results suggest а distinct global VSA deficit in children with CVI, which aligns with clinical observations of symptoms in daily life. Incorporating gaze-based analyses provided new information about search strategies beyond verbal answers and made the KIC task more inclusive for children with language and motor disabilities. Assessing global VSA within clinical CVI assessments could improve the differential diagnostic evaluations among children with CVI, ADHD and dyslexia, leading to more personalized treatment approaches.

Objectives: We assessed the modulation of allostatic load (AL) by engagement in healthy habits and life stressors, mediated through resilience and the perceived influence of the stressors. Sleep was included as third mediator given extensive evidence associating to all the analysed factors.

Methods: Structural equation models to assess the modulation of AL by either traumatic or psychosocial stressors and healthy habits were generated with data from 620 mid-life adults (age 51.3 ± 5.48 years). Model 1 included self-reported life stressors, engagement in cognitive and physical activities, resilience and a pyramid score for diet. In Model 2, self-reported sleep quality was included in the mediation analysis between resilience and perceived stress on AL.

Results: Direct effects of sports and diet on AL, and on resilience by sports were found in all the evaluated models. The modulation of AL by both types of stressors was only revealed in model 2, through indirect effects of perceived influence via sleep quality. An effect of sport habits on AL via resilience was found to be mediated by sleep, and equivalent but opposed effects of perceived influence of stressors and resilience on sleep quality emerged as critical factor for AL modulation.

Conclusion: Our results suggest that sleep plays a pivotal role in the modulation of AL by both life stressors and sport habits, balancing the harmful and protective effects of perceived stress and resilience. The relative weight of one over the other to worsen or improve sleep quality will determine the resulting level of AL.

Introduction: Galvanic vestibular stimulation (GVS) is a simple, safe, and noninvasive method of neurostimulation that can be used to improve body balance. Several central nervous system diseases cause alterations in body balance, including HTLV-1-associated myelopathy (HAM).

Objective: To test GVS as a balance rehabilitation strategy for HAM.

Methods: This study is a quasi-experimental clinical trial in which postural balance was compared before and after a GVS rehabilitation protocol applied to 20 patients with HAM, 12 women and 8 men, average age of 78 and 79 years, respectively. They were followed for nine months after the end of the GVS protocol, which consisted of one GVS session per week for 12 consecutive weeks. The GVS current intensity was progressively increased from 1.0 milliamperes (mA) to 3.5 mA until the third session and maintained at 3.5 mA until the 12th session. The electrical stimulation time progressively increased from 9 min in the first session to 18 min in the second session and maintained at 30 min from the third session onwards. Postural balance was assessed by Time up and go test (TUG), Berg balance scale (BBS) and posturography that were performed before the beginning of the intervention, during the intervention (6th week), at the end of the intervention (12th week) and after 9 months of follow-up without electrical stimulation.

Results: In a blind comparison, in the 12th week of stimulation, improvement was observed in all the tests. In TUG, time in seconds changed from 28 before to 18 after GVS (p < 0,001). In BBS, the score changed from 29.00 before to 41.00 points after GVS. In posturography, the stability limit improved after the intervention (p < 0.05). However, after nine months without stimulation, the gain was lost for TUG, for BBS and for stability limit.

Conclusion: GVS was an effective method to improve postural instability of patients with HAM in the short term, but the gain in postural stability was not maintained in the long term. A device for home use may be an option for long-term use.

Introduction: Cognitive deficits are common in psychiatric and mental health disorders, making the assessment of cognitive function in mental health treatment an important area of research. Cognitive Function Development Therapy (CFDT) is a novel therapeutic modality designed to enhance cognitive function and regulate the autonomic nervous system through targeted exercises and activities focused on attention networks and memory systems. The therapy is tracked and based on Primary Cognitive Function (PCF) scores.

Methods: This retrospective, observational study analyzed real world data from 183 children and adults undergoing CFDT to evaluate changes in cognition over time, incorporating both cognitive performance measures and an exploratory analysis of neurophysiological function. Objective neurophysiological measures in the form of the brain vital signs framework, based in event-related potentials (ERPs), were measured in a small subset of clients to explore the frameworks use in CFDT.

Results: Our findings indicate that CFDT holds promise for improving cognitive performance, as evidenced by increased PCF scores at the group level compared to pre-treatment levels [F (5, 173) = 7.087, p < 0.001, η_p ² = 0.170]. Additionally, a weak effect of age [Spearman's Rho range: -0.301 to -0.340, p < 0.001] was found to influence the degree of cognitive improvement, suggesting the importance of early intervention for maximizing cognitive gains. The exploratory analysis suggested that CFDT may affect neurophysiological measures of information processing, particularly in basic attention, as reflected in increased amplitude in P300 measures.

Discussion: While these initial findings are encouraging, caution is warranted due to the retrospective nature of the study, though overall, the results suggest a positive impact of CFDT on cognitive function.

Introduction: The combination of magnetic and focused ultrasonic fields generates focused electric fields at depth entirely noninvasively. This noninvasive method may find particularly important applications in targeted treatments of the deep brain circuits involved in mental and neurological disorders. Due to the novelty of this method, it is nonetheless unknown which parameters modulate neural activity effectively.

Methods: We have investigated this issue by applying the combination of magnetic and focused ultrasonic fields to deep brain visual circuits in two non-human primates, quantifying the electroencephalographic gamma activity evoked in the visual cortex. We hypothesized that the pulse repetition frequency of the ultrasonic stimulation should be a key factor in modulating the responses, predicting that lower frequencies should elicit inhibitory effects and higher frequencies excitatory effects.

Results: We replicated the results of a previous study, finding an inhibition of the evoked gamma responses by a strong magnetic field. This inhibition was only observed for the lowest frequency tested (5 Hz), and not for the higher frequencies (10 kHz and 50 kHz). These neuromodulatory effects were transient and no safety issues were noted.

Discussion: We conclude that this new method can be used to transiently inhibit evoked neural activity in deep brain regions of primates, and that delivering the ultrasonic pulses at low pulse repetition frequencies maximizes the effect.

Postural control is a multisensory adaptive system performing predictive (anticipatory) and/or reactive (compensatory) actions, with varying degrees of accuracy, to maintain balance in a changing environmental context. Common instrumentation to evaluate balance includes static and dynamic force platforms; added sway-referenced perturbations on the dynamic platform constitute its main advantage. Clinical applications notwithstanding, normative data are needed for interpretation in clinical settings. Posturography norms are used to compare a reference group (healthy individuals) and a specific patient population. This work, to the best of our knowledge, represents the first attempt to synthesize the literature on normative data for computerized posturography using a combined mixed method. The search strategy resulted in the retrieval of 1,244 articles from PubMed, Web of Science, and Science Direct. After deduplication, 689 articles were screened based on title and abstract. One hundred and seven articles met the criteria after the first screening. In-depth, full-text screening resulted in the inclusion of 44 studies for the systematic review and 17 studies for the meta-analyses. The main findings of the systematic review are (1) extensive heterogeneity was found in methodological characteristics, (2) there was insufficient risk of bias mitigation, (3) the majority of tasks evaluated less than four components of the systems framework for postural control (SFPC), and (4) studies mostly used distance domain sway parameters and did not report the influence of other variables on postural sway. Based on the multilevel meta-analyses, females appeared to outperform males in eyes closed (EC) conditions significantly. Based on the network meta-analyses, we found that younger children swayed more than those aged between 8 and 14 years both in eyes open (EO) conditions and EC conditions significantly. The results also revealed a significant difference in sway between individuals of age range between 50 and 79 years old and younger individuals, with more instability observed in older participants both in EO conditions and in EC conditions. Thus, future studies need to ensure that enough information about participants is provided. Standardization of experimental conditions and sway parameters harmonization are still needed to ensure high-quality assessment (QA). Finally, evidence-based postural impairment management requires both age- and sex-related normative data. Systematic review registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023378144, identifier PROSPERO 2023 CRD42023378144.

Introduction: Motor Imagery (MI) Electroencephalography (EEG) signals are non-stationary and dynamic physiological signals which have low signal-to-noise ratio. Hence, it is difficult to achieve high classification accuracy. Although various machine learning methods have already proven useful to that effect, the use of many features and ineffective EEG channels often leads to a complex structure of classifier algorithms. State-of-the-art studies were interested in improving classification performance with complex feature extraction and classification methods by neglecting detailed EEG channel and feature investigation in predicting MI tasks from EEGs. Here, we investigate the effects of the statistically significant feature selection method on four different feature domains (time-domain, frequency-domain, time-frequency domain, and non-linear domain) and their two different combinations to reduce the number of features and classify MI-EEG features by comparing low-dimensional matrices with well-known machine learning algorithms.

Methods: Our main goal is not to find the best classifier performance but to perform feature and channel investigation in MI task classification. Therefore, the detailed investigation of the effect of EEG channels and features is implemented using a statistically significant feature distribution on 22 EEG channels for each feature set separately. We used the BCI Competition IV Dataset IIa and 288 samples per person. A total of 1,364 MI-EEG features were analyzed in this study. We tested nine distinct classifiers: Decision tree, Discriminant analysis, Logistic regression, Naive Bayes, Support vector machine, k-Nearest neighbor, Ensemble learning, Neural networks, and Kernel approximation.

Results: Among all feature sets considered, classifications performed with non-linear and combined feature sets resulted in a maximum accuracy of 63.04% and 47.36% for binary and multiple MI task predictions, respectively. The ensemble learning classifier achieved the maximum accuracy in almost all feature sets for binary and multiple MI task classifications.

Discussion: Our research thus shows that the statistically significant feature-based feature selection method significantly improves the classification performance with fewer features in almost all feature sets, enabling detailed and effective EEG channel and feature investigation.