Real-World Spatial Synchronization of Event-CMOS Cameras through Deep Learning: A Novel CNN-DGCNN Approach.

This paper presents a new deep-learning architecture designed to enhance the spatial synchronization between CMOS and event cameras by harnessing their complementary characteristics. While CMOS cameras produce high-quality imagery, they struggle in rapidly changing environments-a limitation that event cameras overcome due to their superior temporal resolution and motion clarity. However, effective integration of these two technologies relies on achieving precise spatial alignment, a challenge unaddressed by current algorithms.

Neurophysiological insights into sequential decision-making: exploring the secretary problem through ERPs and TBR dynamics.

Decision-making under uncertainty, a cornerstone of human cognition, is encapsulated by the "secretary problem" in optimal stopping theory. Our study examines this decision-making challenge, where participants are required to sequentially evaluate and make irreversible choices under conditions that simulate cognitive overload. We probed neurophysiological responses by engaging 27 students in a secretary problem simulation while undergoing EEG monitoring, focusing on Event-Related Potentials (ERPs) P200 and P400, and Theta to Beta Ratio (TBR) dynamics.

Corrigendum: Attachment style, emotional feedback, and neural processing: investigating the influence of attachment on the P200 and P400 components of event-related potentials.

[This corrects the article DOI: 10.3389/fnhum.2023.

Comparative analysis of ROCKET-driven and classic EEG features in predicting attachment styles.

Predicting attachment styles using AI algorithms remains relatively unexplored in scientific literature. This study addresses this gap by employing EEG data to evaluate the effectiveness of ROCKET-driven features versus classic features, both analyzed using the XGBoost machine learning algorithm, for classifying 'secure' or 'insecure' attachment styles.Participants, fourth-year engineering students aged 20-35, first completed the ECR-R questionnaire.

Enhancing EEG-based attachment style prediction: unveiling the impact of feature domains.

Introduction: Attachment styles are crucial in human relationships and have been explored through neurophysiological responses and EEG data analysis. This study investigates the potential of EEG data in predicting and differentiating secure and insecure attachment styles, contributing to the understanding of the neural basis of interpersonal dynamics.

Methods: We engaged 27 participants in our study, employing an XGBoost classifier to analyze EEG data across various feature domains, including time-domain, complexity-based, and frequency-based attributes.

Predicting Tacit Coordination Success Using Electroencephalogram Trajectories: The Impact of Task Difficulty.

In this study, we aim to develop a machine learning model to predict the level of coordination between two players in tacit coordination games by analyzing the similarity of their spatial EEG features. We present an analysis, demonstrating the model's sensitivity, which was assessed through three conventional measures (precision, recall, and f1 score) based on the EEG patterns. These measures are evaluated in relation to the coordination task difficulty, as determined by the coordination index (CI).

Attachment style, emotional feedback, and neural processing: investigating the influence of attachment on the P200 and P400 components of event-related potentials.

Understanding the interplay between attachment style, emotional processing, and neural responses is crucial for comprehending the diverse ways individuals function socially and emotionally. While previous research has contributed to our knowledge of how attachment style influences emotional processing, there is still a gap in the literature when it comes to investigating emotional feedback using event-related potentials (ERPs) within a cognitive framework. This study aims to address this gap by examining the effects of attachment style and feedback valence on ERP components, specifically focusing on the P200 and P400.

Offline EEG hyper-scanning using anonymous walk embeddings in tacit coordination games.

In this paper we present a method to examine the synchrony between brains without the need to carry out simultaneous recordings of EEG signals from two people which is the essence of hyper-scanning studies. We used anonymous random walks to spatially encode the entire graph structure without relying on data at the level of individual nodes. Anonymous random walks enabled us to encapsulate the structure of a graph regardless of the specific node labels.

Electrophysiological Features to Aid in the Construction of Predictive Models of Human-Agent Collaboration in Smart Environments.

Achieving successful human-agent collaboration in the context of smart environments requires the modeling of human behavior for predicting people's decisions. The goal of the current study was to utilize the TBR and the Alpha band as electrophysiological features that will discriminate between different tasks, each associated with a different depth of reasoning. To that end, we monitored the modulations of the TBR and Alpha, while participants were engaged in performing two cognitive tasks: picking and coordination.

Modeling and predicting individual tacit coordination ability.

Background: Previous experiments in tacit coordination games hinted that some people are more successful in achieving coordination than others, although the variability in this ability has not yet been examined before. With that in mind, the overarching aim of our study is to model and describe the variability in human decision-making behavior in the context of tacit coordination games.

Methods: In this study, we conducted a large-scale experiment to collect behavioral data, characterized the distribution of tacit coordination ability, and modeled the decision-making behavior of players.

An Electrophysiological Model for Assessing Cognitive Load in Tacit Coordination Games.

Previously, it was shown that some people are better coordinators than others; however, the relative weight of intuitive (system 1) versus deliberate (system 2) modes of thinking in tacit coordination tasks is still not resolved. To address this question, we have extracted an electrophysiological index, the theta-beta ratio (TBR), from the Electroencephalography (EEG) recorded from participants while they were engaged in a semantic coordination task. Results have shown that individual coordination ability, game difficulty and response time are each positively correlated with cognitive load.

Level-K Classification from EEG Signals Using Transfer Learning.

Tacit coordination games are games in which communication between the players is not allowed or not possible. In these games, the more salient solutions, that are often perceived as more prominent, are referred to as The level-k model states that players' decisions in tacit coordination games are a consequence of applying different decision rules at different depths of reasoning (level-k). A player at Lk=0 will randomly pick a solution, whereas a Lk≥1 player will apply their strategy based on their beliefs regarding the actions of the other players.

Using a Stochastic Agent Model to Optimize Performance in Divergent Interest Tacit Coordination Games.

In recent years collaborative robots have become major market drivers in industry 5.0, which aims to incorporate them alongside humans in a wide array of settings ranging from welding to rehabilitation. Improving human-machine collaboration entails using computational algorithms that will save processing as well as communication cost.

Collectivism-individualism: Strategic behavior in tacit coordination games.

The effect of culture on strategic interaction has been widely explored. However, the effect of the cultural background on focal point selection in tacit coordination games has not yet been examined. To accomplish this goal, in this study we have focused on the individual level of analysis.

Relationship Between Kinematic and Physiological Indices During Braking Events of Different Intensities.

Objective To study the relationship between physiological indices and kinematic indices during braking events of different intensities. Background Based on mental workload theory, driving and other task demands may generate changes in physiological indices, such as the driver's heart rate and skin conductance. However, no attempts were made to associate changes in physiological indices with changes in vehicle kinematics that result from the driver attempts to meet task demands.

Brain Network Activation as a Novel Biomarker for the Return-to-Play Pathway Following Sport-Related Brain Injury.

Children and adolescent athletes are at a higher risk for concussion than adults, and also experience longer recovery times and increased associated symptoms. It has also recently been demonstrated that multiple, seemingly mild concussions may result in exacerbated and prolonged neurological deficits. Objective assessments and return-to-play criteria are needed to reduce risk and morbidity associated with concussive events in these populations.

Clinically Effective Treatment of Fibromyalgia Pain With High-Definition Transcranial Direct Current Stimulation: Phase II Open-Label Dose Optimization.

Unlabelled: Despite promising preliminary results in treating fibromyalgia (FM) pain, no neuromodulation technique has been adopted in clinical practice because of limited efficacy, low response rate, or poor tolerability. This phase II open-label trial aims to define a methodology for a clinically effective treatment of pain in FM by establishing treatment protocols and screening procedures to maximize efficacy and response rate. High-definition transcranial direct current stimulation (HD-tDCS) provides targeted subthreshold brain stimulation, combining tolerability with specificity.

Preliminary evidence of reduced brain network activation in patients with post-traumatic migraine following concussion.

Post-traumatic migraine (PTM) (i.e., headache, nausea, light and/or noise sensitivity) is an emerging risk factor for prolonged recovery following concussion.

Brain Network Activation (BNA) reveals scopolamine-induced impairment of visual working memory.

The overarching goal of this event-related potential (ERP) study was to examine the effects of scopolamine on the dynamics of brain network activation using a novel ERP network analysis method known as Brain Network Activation (BNA). BNA was used for extracting group-common stimulus-activated network patterns elicited to matching probe stimuli in the context of a delayed matching-to-sample task following placebo and scopolamine treatments administered to healthy participants. The BNA extracted networks revealed the existence of two pathophysiological mechanisms following scopolamine, disconnection, and compensation.

Dissociation between the activity of the right middle frontal gyrus and the middle temporal gyrus in processing semantic priming.

The aim of this event-related functional magnetic resonance imaging (fMRI) study was to test whether the right middle frontal gyrus (MFG) and middle temporal gyrus (MTG) would show differential sensitivity to the effect of prime-target association strength on repetition priming. In the experimental condition (RP), the target occurred after repetitive presentation of the prime within an oddball design. In the control condition (CTR), the target followed a single presentation of the prime with equal probability of the target as in RP.

Comparator and non-comparator mechanisms of change detection in the context of speech--an ERP study.

Automatic change detection reflects a cognitive memory-based comparison mechanism as well as a sensorial non-comparator mechanism based on differential states of refractoriness. The purpose of this study was to examine whether the comparator mechanism of the mismatch negativity component (MMN) is differentially affected by the lexical status of the deviant. Event-related potential (ERP) data was collected during an "oddball" paradigm designed to elicit the MMN from 15 healthy subjects that were involved in a counting task.

An EEG (electroencephalogram) recording system with carbon wire electrodes for simultaneous EEG-fMRI (functional magnetic resonance imaging) recording.

Simultaneous EEG-fMRI (Electroencephalography-functional Magnetic Resonance Imaging) recording provides a means for acquiring high temporal resolution electrophysiological data and high spatial resolution metabolic data of the brain in the same experimental runs. Carbon wire electrodes (not metallic EEG electrodes with carbon wire leads) are suitable for simultaneous EEG-fMRI recording, because they cause less RF (radio-frequency) heating and susceptibility artifacts than metallic electrodes. These characteristics are especially desirable for recording the EEG in high field MRI scanners.

Sensory and cognitive mechanisms of change detection in the context of speech.

The aim of this study was to dissociate the contributions of memory-based (cognitive) and adaptation-based (sensory) mechanisms underlying deviance detection in the context of natural speech. Twenty healthy right-handed native speakers of English participated in an event-related design scan in which natural speech stimuli, /de:/ ("deh") and /deI/ ("day"); (/te:/ ("teh") and /teI/ ("tay") served as standards and deviants within functional magnetic resonance imaging event-related "oddball" paradigm designed to elicit the mismatch negativity component. Thus, "oddball" blocks could involve either a word deviant ("day") resulting in a "word advantage" effect, or a non-word deviant ("deh" or "tay").

Time course of auditory cortex activation during speech processing.

The purpose of the studies summarized in this report was to determine the time course of auditory cortex involvement in speech and language processing in the context of auditory object formation. Forty-one subjects took part in the three studies summarized in this report. In all three studies, subjects performed a choice-reaction task that required their pressing an appropriate button in response to auditory stimuli (speech/non-speech, good/worse fused phonemes, first/second language words) presented through earphones.