Applied human neuroscience: Fostering and designing inclusive environments with the 3E-Cognition perspective.

The conventional medical paradigm often focuses on deficits and impairments, failing to capture the rich tapestry of experiences and abilities inherent in neurodiversity conditions. In this article, we introduce the 3E-Cognition perspective, offering a paradigm shift by emphasizing the dynamic interplay between the brain, body, and environment in shaping cognitive processes. The perspective fosters a more inclusive and supportive understanding of neurodiversity, with potential applications across various domains such as education, workplace, and healthcare. We begin by introducing the 3E-Cognition principles: embodied, environmentally scaffolded, and enactive. Then, we explore how the 3E-Cognition perspective can be applied to create inclusive environments and experiences for neurodiverse individuals. We provide examples in the realms of education, workplace, and healthcare. In all of these domains, spaces, methodologies, epistemologies, and roles that cater to diverse needs and strengths can be designed using the 3E principles. Finally, we discuss the challenges and benefits of implementing the 3E-Cognition perspective. We focus on the need for technological advancements and research in complex real-world scenarios; we suggest mobile brain/body imaging is a possible solution. We furthermore highlight the importance of recognizing and valuing the diverse manners of experiencing and interacting with the world, the promotion of diverse well-being, and the facilitation of innovation and creativity. Thus, we conclude that the 3E-Cognition perspective offers a groundbreaking approach to understanding and supporting neurodiversity: by embracing the inherent interconnectedness of the brain, body, and environment, we can create a more inclusive and supportive world.

A Personalized User Authentication System Based on EEG Signals.

Conventional biometrics have been employed in high-security user-authentication systems for over 20 years now. However, some of these modalities face low-security issues in common practice. Brainwave-based user authentication has emerged as a promising alternative method, as it overcomes some of these drawbacks and allows for continuous user authentication. In the present study, we address the problem of individual user variability, by proposing a data-driven Electroencephalography (EEG)-based authentication method. We introduce machine learning techniques, in order to reveal the optimal classification algorithm that best fits the data of each individual user, in a fast and efficient manner. A set of 15 power spectral features (delta, theta, lower alpha, higher alpha, and alpha) is extracted from three EEG channels. The results show that our approach can reliably grant or deny access to the user (mean accuracy of 95.6%), while at the same time poses a viable option for real-time applications, as the total time of the training procedure was kept under one minute.

Incorporating Brain Explanations in Psychoanalysis: Tennessee Williams as a Case Study.

Despite Tennessee Williams's genius as a playwright who could represent his inner emotional struggles in his art, psychoanalysis was unable to free him from the powerful "blue devils" within him. Williams's inability to engage with psychoanalysis presents an opportunity to discuss ways that contemporary thinking about brain structure and function might guide our understanding and treatment of patients such as Williams. One of the core defensive behaviors that made analysis difficult for Williams was his avoidance of painful emotions through compulsive writing, sex, alcohol, and drug-addictive behaviors. These pre-mentalized reactions became Williams's habitual procedural body response, which occurs below the level of the self-reflective brain. Within a relatively traditional ego psychological frame, Lawrence Kubie, Williams's analyst in 1957, attempted to prohibit the compulsive behaviors to be able to process the underlying painful affects in the analysis. However, given that this level of mind and brain functions was Williams's chief means of regulation, Williams could not engage in the psychoanalytic process and left the treatment after one year. I propose that Williams was operating in brain circuits below the level of "higher" reflection or interpretation-receptive circuits and therefore he was unable to make use of a traditional ego psychological model. A review of these brain circuits seeks to encourage therapists to utilize simplified brain explanations for patients, which can destigmatize the pathologic behaviors and enhance engagement in the treatment process.

Introduction: An overview of NIMH (Klecany, CZ) scientific activities.

An overview of research activities of National Institute of Mental Health (NIMH) in Klecany, Czech republic. The institute was funded by EU operational project Research and Development for Innovation and started working in 2015. NIMH activities are organized in eight research programs including the neurobiology of the serious mental disorders, social psychiatry, brain imaging and use of information technologies in psychiatric research, epidemiology of addictions, sleep laboratory and chronobiology, electrophysiology, clinical research, and transfer of technologies. The equipment and expertise ranks NIMH Klecany among top neuroscience research institutions in central and eastern Europe.

Impressions on the current state of cognitive neuroscience in occupational measurement.

Cognitive neuroscience is currently finding itself as a marketing trend in occupational science, particularly in terms of workplace assessment and measurement. However, the field has historically had little to do with occupational applications and has generally remained focused on the clinical and academic relevance of its research. We will explore several frontiers where research methods and theory established in cognitive neuroscience are beginning to produce meaningful applications in the workplace. Given that this application is likely to be unfamiliar with many in brain research, we look to outline concepts that should be perceived as key considerations when applying innovative measures to the workplace. Relating to these key considerations are several challenges that currently stand in the way of cognitive neuroscience progressing beyond a marketing trend into a steadfast perspective in occupational science.

Digging Deeper: An Object Relations Couple Therapy Update.

Over the past two decades, neurobiology research has added clarity to the process of emotional and behavioral change. In turn, this has led to endorsement of interventions that appear to be most helpful in individual and couple therapy. In addition to research on emotional dysregulation, contemporary studies have focused on the construction of meaning and its relevance to interpersonal relationships. According to Lisa Barrett, Richard Lane, and others, the brain references concepts to rapidly arrive at the most probable conclusions. Encoded experience and memory fragments guide this process and are vital in understanding partners' emotional responses. These findings support an object relations perspective that emphasizes the importance of past relational experiences that inform the present. This is particularly relevant in work with couples, as each individual's beliefs, expectations, and capacity for intimacy are invariably tied to earlier relationships. Research findings on memory reconstruction provide a basis for interventions that can add to the existing treatment approach, as it is suggested that working in a specific way with emotionally based memories has the potential to modify and reduce their predictive power and ability to unleash beliefs and behaviors that work against intimacy. The therapist who is informed by emerging neuroscience research can better uncover and actively work with memories that may be compromising a couple's relationship.

Durante las últimas dos décadas, la investigación sobre neurobiología ha aclarado el proceso de cambio emocional y conductual. A su vez, esto ha conducido a la aprobación de intervenciones que parecen ser más útiles en la terapia individual y de pareja. Además de la investigación sobre la desregulación emocional, algunos estudios contemporáneos se han centrado en la construcción de significado y su relevancia para las relaciones interpersonales. De acuerdo con Barrett (2018), Lane (2015) y otros, el cerebro nombra conceptos para llegar rápidamente a las conclusiones más probables. La experiencia codificada y los fragmentos de recuerdos guían este proceso y son fundamentales para comprender las respuestas emocionales de las parejas. Estos hallazgos respaldan una perspectiva de la relación de objetos que enfatiza la importancia de las experiencias relacionales anteriores que respaldan el presente. Esto es particularmente relevante en el trabajo con parejas, ya que las creencias, las expectativas y la capacidad de intimidad de cada persona están invariablemente ligadas a relaciones anteriores. Los resultados de las investigaciones sobre la reconstrucción de la memoria ofrecen una base para las intervenciones que puede potenciar el método de tratamiento existente, ya que se sugiere que trabajar de una forma específica con recuerdos basados en las emociones tiene el potencial de modificar y reducir su poder predictivo y su capacidad de desatar creencias y conductas que funcionan en contra de la intimidad. El terapeuta que se base en la investigación emergente sobre neurociencia podrá descubrir mejor y trabajar activamente con recuerdos que pueden estar comprometiendo una relación de pareja.

Assessing Feedback Response With a Wearable Electroencephalography System.

Background: Event related potential (ERP) components, such as P3, N2, and FRN, are potential metrics for assessing feedback response as a form of performance monitoring. Most research studies investigate these ERP components using clinical or research-grade electroencephalography (EEG) systems. Wearable EEGs, which are an affordable alternative, have the potential to assess feedback response using ERPs but have not been sufficiently evaluated. Feedback-related ERPs also have not been scientifically evaluated in interactive settings that are similar to daily computer use. In this study, a consumer-grade wearable EEG system was assessed for its feasibility to collect feedback-related ERPs through an interactive software module that provided an environment in which users were permitted to navigate freely within the program to make decisions. Methods: The recording hardware, which costs < $1,500 in total, incorporated the OpenBCI Cyton Board with Daisy chain, a consumer-grade EEG system that costs $949 USD. Seventeen participants interacted with an oddball paradigm and an interactive module designed to elicit feedback-related ERPs. The features of interests for the oddball paradigm were the P3 and N2 components. The features of interests for the interactive module were the P3, N2, and FRN components elicited in response to positive, neutral, and two types of negative feedback. The FRN was calculated by subtracting the positive feedback response from the negative feedback responses. Results: The P3 and N2 components of the oddball paradigm indicated statistically significant differences between infrequent targets and frequent targets which is in line with current literature. The P3 and N2 components elicited in the interactive module indicated statistically significant differences between positive, neutral, and negative feedback responses. There were no significant differences between the FRN types and significant interactions with channel group and FRN type. Conclusion: The OpenBCI Cyton, after some modifications, shows potential for eliciting and assessing P3, N2, and FRN components, which are important indicators for performance monitoring, in an interactive setting.

Willingness-to-Pay-Associated Right Prefrontal Activation During a Single, Real Use of Cosmetics as Revealed by Functional Near-Infrared Spectroscopy.

Use of applied neuroscience to complement traditional methods of consumer research is increasing. Previously, fMRI has shown that prefrontal activity contains information relating to willingness-to-pay (WTP). The aim of the present study was to determine if functional near infrared spectroscopy (fNIRS) can record WTP-related brain activation in the dorsolateral prefrontal cortex (DLPFC) during a single, real use of cosmetic products. Thirty female participants, were divided into two groups (one low frequency users of foundation and one high frequency users of foundation), asked to apply different foundations to their face and then record how much money they were willing to pay. The oxyhemoglobin time series was analyzed with the GLM and the correlation between the beta scores for the foundations and their respective WTP values conducted for each participant. These subject level correlations were then converted to z scores and averaged for each group. The results revealed a significant mean correlation for the high but not low frequency group. In other words, the brain activity in right hemisphere dorsolateral PFC (RH-DLPFC) during single, real use of foundations correlated with their respective WTP values for the high frequency but not low frequency group. The difference between groups may reflect the importance of learning and automation on activity in RH-DLPFC. Our research provides further evidence supporting the use of fNIRS to complement traditional consumer research in a commercial setting and to extend neuroscience research into more naturalistic environments.

BCI to Potentially Enhance Streaming Images to a VR Headset by Predicting Head Rotation.

While numerous studies show that brain signals contain information about an individual's current state that are potentially valuable for smoothing man-machine interfaces, this has not yet lead to the use of brain computer interfaces (BCI) in daily life. One of the main challenges is the common requirement of personal data that is correctly labeled concerning the state of interest in order to train a model, where this trained model is not guaranteed to generalize across time and context. Another challenge is the requirement to wear electrodes on the head. We here propose a BCI that can tackle these issues and may be a promising case for BCI research and application in everyday life. The BCI uses EEG signals to predict head rotation in order to improve images presented in a virtual reality (VR) headset. When presenting a 360° video to a headset, field-of-view approaches only stream the content that is in the current field of view and leave out the rest. When the user rotates the head, other content parts need to be made available soon enough to go unnoticed by the user, which is problematic given the available bandwidth. By predicting head rotation, the content parts adjacent to the currently viewed part could be retrieved in time for display when the rotation actually takes place. We here studied whether head rotations can be predicted on the basis of EEG sensor data and if so, whether application of such predictions could be applied to improve display of streaming images. Eleven participants generated left- and rightward head rotations while head movements were recorded using the headsets motion sensing system and EEG. We trained neural network models to distinguish EEG epochs preceding rightward, leftward, and no rotation. Applying these models to streaming EEG data that was withheld from the training showed that 400 ms before rotation onset, the probability "no rotation" started to decrease and the probabilities of an upcoming right- or leftward rotation started to diverge in the correct direction. In the proposed BCI scenario, users already wear a device on their head allowing for integrated EEG sensors. Moreover, it is possible to acquire accurately labeled training data on the fly, and continuously monitor and improve the model's performance. The BCI can be harnessed if it will improve imagery and therewith enhance immersive experience.

Using neurophysiological signals that reflect cognitive or affective state: six recommendations to avoid common pitfalls.

Estimating cognitive or affective state from neurophysiological signals and designing applications that make use of this information requires expertise in many disciplines such as neurophysiology, machine learning, experimental psychology, and human factors. This makes it difficult to perform research that is strong in all its aspects as well as to judge a study or application on its merits. On the occasion of the special topic "Using neurophysiological signals that reflect cognitive or affective state" we here summarize often occurring pitfalls and recommendations on how to avoid them, both for authors (researchers) and readers. They relate to defining the state of interest, the neurophysiological processes that are expected to be involved in the state of interest, confounding factors, inadvertently "cheating" with classification analyses, insight on what underlies successful state estimation, and finally, the added value of neurophysiological measures in the context of an application. We hope that this paper will support the community in producing high quality studies and well-validated, useful applications.