Lateralization difference in functional activity during Stroop tasks: a functional near-infrared spectroscopy and EEG simultaneous study

Effect of Specific mode electroacupuncture stimulation combined with NGF during the ischaemic stroke: Study protocol for a randomized controlled trial

BACKGROUND

The emergence of the Nerve Growth Factor (NGF) has promoted the development of neuroprotective therapy; however, it has little effect on cerebral ischemia because of its poor Blood-Brain Barrier (BBB) permeability. Specific Mode Electroacupuncture Stimulation (SMES) can open BBB safely and effectively; however, it has shown inconclusive clinical effects and indirect clinical evidence in the recovery phase. Hence, the authors conducted a multicentre, randomized, placebo-controlled, assessor-blinded clinical trial to assess the effectiveness and safety of SMES combined with NGF treatment used during ischaemic stroke recovery.

METHODS

A total of 288 stroke patients from three hospitals will be recruited and randomly allocated to four groups: acupuncture + placebo, acupuncture + NGF, SMES + placebo, and SMES + NGF, in a 1:1:1:1 ratio. Assessment data will be collected at baseline, 2-weeks, and 4-weeks during the treatment period, as well as at the 4-week and 8-week follow-up after treatment completion. The primary outcome measure will be the basic cure rate. The secondary outcome measures include the simplified Modified Barthel Index, Timed Up and Go Test, Fugl-Meyer Assessment of Motor Function Score, Tinetti Performance Oriented Mobility Assessment, Montreal Cognitive Assessment, and Loewenstein Occupational Therapy Cognitive Assessment. Moreover, resting-state functional magnetic resonance imaging and Functional near-infrared spectroscopy can detect changes in cerebral blood flow and brain function and investigate the relationship between the clinical efficacy and mechanism of the prescribed interventions.

CONCLUSION

This study will provide clinical evidence for the efficacy and safety of SMES combined with NGF in the treatment of stroke patients.

Effects of Cognitive and Physical Load of Acute Exercise on Inhibitory Control and Prefrontal Cortex Hemodynamics in Children

INTRODUCTION

Evidence suggests that acute exercise benefits inhibitory control, but it remains unclear how physical and cognitive load influence this ability in preadolescent children, when faced with different types of distractors. We examined their moderating effects along with changes in prefrontal cortex hemodynamics.

METHODS

Using a crossover design, 29 participants completed 10 min of exercise (with an interactive training wall) at 1) low physical and low cognitive load, 2) low physical and high cognitive load, 3) high physical and low cognitive load, and 4) high physical and high cognitive load in a randomized order. Before and after each condition, they performed a Standard and Affective Stroop task. During both tasks, the lateral oxygenation difference in the prefrontal cortex was measured by using functional near-infrared spectroscopy.

RESULTS

For the Standard Stroop task, there was no effect of physical and cognitive load on performance. In contrast, exercise with low compared with high cognitive load was associated with a greater reduction of reaction time and increase in accuracy on the Affective Stroop task. This was accompanied by a decrease in lateral oxygenation difference on trials with low inhibitory control demands.

CONCLUSIONS

Acute exercise with low compared with high cognitive demand benefits the ability to resolve emotional conflict, but the control over inhibition of nonemotional information remains unaffected. This effect of cognitive load is complemented by an increased efficiency of the left prefrontal cortex, when no emotional conflict resolution is required.

An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations. The dataset combines standard event-related potential and microstate analyses with state-of-the-art decoding approaches of four scenarios: spontaneous/instructed truth-telling and lying. This demonstrates game-based methods' efficacy in studying deception and sets a benchmark for future research. Overall, our dataset represents a unique resource with applications in cognitive neuroscience and related fields for studying deception, competitive behavior, decision-making, inter-brain synchrony, and benchmarking of decoding frameworks in a difficult, high-level cognitive task.

EEG and fNIRS datasets based on Stroop task during two weeks of high-altitude exposure in new immigrants

Maintaining sufficient cerebral oxygen metabolism is crucial for human survival, especially in challenging conditions such as high-altitudes. Human cognitive neural activity is sensitive to fluctuations in oxygen levels. However, there is a lack of publicly available datasets on human behavioural responses and cerebral dynamics assessments during the execution of conflicting tasks in natural hypoxic environments. We recruited 80 healthy new immigrant volunteers (males, aged 20 ± 2 years) and employed the Stroop cognitive conflict paradigm. After a two-week exposure to both high and low-altitudes, the behavioural performance, prefrontal oxygen levels, and electroencephalography (EEG) signals were recorded. Comparative analyses were conducted on the behavioural reaction times and accuracy during Stroop tasks, and statistical analyses of participants' prefrontal oxygen levels and EEG signals were performed. We anticipate that our open-access dataset will contribute to the development of monitoring devices and algorithms, designed specifically for measuring cerebral oxygen and EEG dynamics in populations exposed to extreme environments, particularly among individuals suffering from oxygen deficiency.

Frontal P300 asymmetry and congruence judgment: Retroactive switching is impaired during school day mornings in female adolescents

Investigating frontal EEG asymmetry as a possible biomarker of cognitive control abilities is especially important in ecological contexts such as school and work. We used a novel approach combining judgment performance and hemispheric frontal event-related potential (ERP) P300 asymmetry (fP3As) to evaluate aspects of cognitive control (i.e., repetition and switching) in adolescent females over a two-week ordinary school period. While undergoing electroencephalographic recording, students performed a word-colour "Stroop-like" congruence judgment task during morning and afternoon sessions, on Mondays and Wednesdays. Proportion of incongruence and congruence trials was 75% and 25%, respectively. ERP analysis revealed larger "novelty" right hemispheric fP3As amplitude for infrequent congruence but equivalent or significantly smaller than left hemispheric fP3As amplitude for frequent incongruence. RTs increased with extent of right fP3As shift. Behaviorally, repeat trial pairs (i.e., congruent followed by congruent, incongruent followed by incongruent) generally did not differ by time or day and were associated with near-ceiling accuracy. In contrast, switch trial pairs (i.e., congruent followed by incongruent, incongruent followed by congruent) in the afternoon were slower and associated with lower accuracy at the expected 75% criterion rate (i.e., judging incongruence by default), dropping significantly below 75% in the mornings. Crucially, compared to afternoon, morning fP3As patterns did not change adaptively with switch trial pairs. Although retroactive switching during congruence judgment was affected at all testing times, we conclude it was most impaired in the mornings of both early and mid school weeks, supporting misalignment between adolescent circadian cycle and school start time. We discuss some implications for optimal learning of adolescents at school.

Evaluation of the learning state of online video courses based on functional near infrared spectroscopy

Studying brain activity during online learning will help to improve research on brain function based on real online learning situations, and will also promote the scientific evaluation of online education. Existing research focuses on enhancing learning effects and evaluating the learning process associated with online learning from an attentional perspective. We aimed to comparatively analyze the differences in prefrontal cortex (PFC) activity during resting, studying, and question-answering states in online learning and to establish a classification model of the learning state that would be useful for the evaluation of online learning. Nineteen university students performed experiments using functional near-infrared spectroscopy (fNIRS) to monitor the prefrontal lobes. The resting time at the start of the experiment was the resting state, watching 13 videos was the learning state, and answering questions after the video was the answering state. Differences in student activity between these three states were analyzed using a general linear model, 1s fNIRS data clips, and features, including averages from the three states, were classified using machine learning classification models such as support vector machines and k-nearest neighbor. The results show that the resting state is more active than learning in the dorsolateral prefrontal cortex, while answering questions is the most active of the three states in the entire PFC, and k-nearest neighbor achieves 98.5% classification accuracy for 1s fNIRS data. The results clarify the differences in PFC activity between resting, learning, and question-answering states in online learning scenarios and support the feasibility of developing an online learning assessment system using fNIRS and machine learning techniques.

A Novel Approach to Evaluating Crosstalk for Near-Infrared Spectrometers

Multi-channel and multi-parameter near-infrared spectroscopy (NIRS) has gradually become a new research direction and hot spot due to its ability to provide real-time, continuous, comprehensive indicators of multiple parameters. However, multi-channel and multi-parameter detection may lead to crosstalk between signals. There is still a lack of benchmarks for the evaluation of the reliability, sensitivity, stability and response consistency of the NIRS instruments. In this study, a set of test methods (a human blood model test, ink drop test, multi-channel crosstalk test and multi-parameter crosstalk test) for analyzing crosstalk and verifying the reliability of NIRS was conducted to test experimental verification on a multi-channel (8-channel), multi-parameter (4-parameter) NIRS instrument independently developed by our team. Results show that these tests can be used to analyze the signal crosstalk and verify the reliability, sensitivity, stability and response consistency of the NIRS instrument. This study contributes to the establishment of benchmarks for the NIRS instrument crosstalk and reliability testing. These novel tests have the potential to become the benchmark for NIRS instrument reliability testing.