Neurophysiological correlates underlying social behavioural adjustment of conformity

[eng] Conformity is the act of changing one’s behaviour to adjust to other human beings. It is a crucial social adaptation that happens when people cooperate, where one sacrifices their own perception, expectations, or beliefs to reach convergence with another person. The aim of the present study was to increase the understanding of the neurophysiological underpinnings regarding the social behavioural adjustment of conformity. We start by introducing cooperation and how it is ingrained in human behaviour. Then we explore the different processes that the brain requires for the social behavioural adjustment of conformity. To engage in this social adaptation, a person needs a self-referenced learning mechanism based on a predictive model that helps them track the prediction errors from unexpected events. Also, the brain uses its monitoring and control systems to encode different value functions used in action selection. The use of different learning models in neuroscience, such as reinforcement learning (RL) algorithms, has been a success story identifying learning systems by means of the mapped activity of different regions in the brain. Importantly, experimental paradigms which has been used to study conformity have not been based in a social interaction setting and, hence, the results, cannot be used to explain an inherently social phenomenon. The main goal of the present thesis is to study the neurophysiological mechanisms underlying the social behavioural adjustment of conformity and its modulation with repeated interaction. To reach this goal, we have first designed a new experimental task where conformity appears spontaneously between two persons and in a reiterative way. This design exposes learning acquisition processes, which require iterative loops, as well as other cognitive control mechanisms such as feedback processing, value-based decision making and attention. The first study shows that people who previously cooperate increase their level of convergence and report a significantly more satisfying overall experience. In addition, participants learning on their counterparts’ behaviour can be explained using a RL algorithm as opposed to when they do not have previously cooperated. In the second study, we have studied the event-related potentials (ERP) and oscillatory power underlying conformity. ERP results show different levels of cognitive engagement that are associated to distinct levels of conformity. Also, time-frequency analysis shows evidence in theta, alpha and beta related to different functions such as cognitive control, attention and, also, reward processing, supporting the idea that convergence between dyads acts as a social reward. Finally, in the third study, we explored the intra- and inter- oscillatory connectivity between electrodes related to behavioural convergence. In intra-brain oscillatory connectivity coherence, we have found two different dynamics related to attention and executive functions in alpha. Also, we have found that the learning about peer’s behaviour as computed using a RL is mediated by theta oscillatory connectivity. Consequently, combined evidence from Study 2 and Study 3 suggests that both cognitive control and learning computations happening in the social behavioural adaptation of conformity are signalled in theta frequency band. The present work is one of the first studies describing, with credible evidence, that conformity, when this occurs willingly and spontaneously rather than induced, engages different brain activity underlying reward-guided learning, cognitive control, and attention.[spa] La conformidad es el acto de cambiar el comportamiento de uno a favor de ajustarnos a otros seres humanos. Se trata de una adaptación crucial que ocurre cuando la gente coopera, donde uno sacrifica su propia percepción, expectativas o creencias en aras de conseguir una convergencia con la otra persona. El objetivo del presente estudio ha sido tratar de aportar a la comprensión de las estructuras neurofisiológicas que soportan un ajuste social como el de la conformidad. En la primera parte de esta tesis comenzamos hablando de la cooperación y lo profundamente arraigada que está en nuestro comportamiento. Más tarde exploramos diferentes procesos que el cerebro requiere en el ajuste social de la conformidad. Así pues, para involucrarse en esta adaptación social, una persona requiere de un mecanismo de aprendizaje auto-referenciado basado en un modelo predictivo que le ayude a seguir el rastro de los errores de predicción que acompañan a los eventos inesperados. Además, el cerebro usa sus sistemas de control y predicción para codificar diferentes funciones de valor usadas en la selección de acción. El uso de diferentes modelos de aprendizaje en neurociencia, como los algoritmos de aprendizaje por refuerzo (RL), han sido una historia de éxito a la hora de identificar los sistemas de aprendizaje a través del mapeo de la actividad de diferentes regiones del cerebro. Es importante destacar que los paradigmas experimentales que se han usado para estudiar la conformidad no se han basado en entornos de interacción social y que, por lo tanto, sus resultados no pueden usarse para explicar un fenómeno inherentemente social. El objetivo principal de la presente tesis es el estudio de los mecanismos neurofisiológicos que fundamentan el comportamiento de ajuste social de la conformidad y su modulación con la interacción repetida. Para alcanzar este objetivo, primero hemos diseñado una nueva tarea experimental en la que la conformidad aparece de forma espontánea entre dos personas y, además, de forma reiterativa. Este diseño permite exponer tanto los procesos de adquisición del aprendizaje, que requieren de ciclos iterativos, así como otros mecanismos de control cognitivo tales como el procesamiento de la retroalimentación, las tomas de decisiones basadas en procesos valorativos y la atención. El primer estudio nos muestra que la gente que coopera previamente incrementa sus niveles de convergencia y reportan significativamente una experiencia generalmente más satisfactoria en el experimento. Adicionalmente, un modelo de RL nos explica que los participantes tratan de aprender del comportamiento de sus parejas en mayor medida si estos han cooperado previamente. En el segundo estudio, hemos estudiado los potenciales relacionados con eventos (ERP) y el poder de las oscilaciones que sustentan la conformidad. Los estudios de ERP muestran diferentes niveles de implicación cognitiva asociados con diferentes niveles de conformidad. Además, los análisis de tiempo-frecuencia muestran evidencia en theta, alfa y beta relacionados con diferentes funciones como el control cognitivo, la atención, y, también, el procesamiento de la recompensa, apoyando la idea de que la convergencia entre díadas actúa como una recompensa social. Finalmente, en el tercer estudio, exploramos la conectividad oscilatoria intra e inter entre electrodos que se pudieran relacionar con la conducta de convergencia. A propósito de la conectividad oscilatoria coherente intra, hemos hallado dos dinámicas relacionadas con la atención y las funciones ejecutivas en alfa. Asimismo, hemos encontrado que el aprendizaje de la conducta de la pareja computada a través de RL está mediada a través de la conectividad oscilatoria de theta. Consecuentemente, la evidencia combinada entre el estudio 2 y el estudio 3 sugiere que conjuntamente el control cognitivo y las computaciones de aprendizaje que ocurren en la conducta de adaptación social de la conformidad están relacionadas con la actividad de la banda de frecuencia theta. Este trabajo constituye uno de los primeros estudios que describen, con evidencia creíble, que la conformidad, cuando ocurre voluntaria y espontáneamente a diferencia cuando esta es inducida, involucra actividad del cerebro que se fundamenta en el aprendizaje guiado por reforzamiento, el control cognitivo y la atención

Neurophysiological correlates of interpersonal discrepancy and social adjustment in an interactive decision-making task in dyads

IntroductionThe pursuit of convergence and the social behavioral adjustment of conformity are fundamental cooperative behaviors that help people adjust their mental frameworks to reach a common goal. However, while social psychology has extensively studied conformity by its influence context, there is still plenty to investigate about the neural cognitive mechanisms involved in this behavior.MethodsWe proposed a paradigm with two phases, a pre-activation phase to enhance cooperative tendencies and, later, a social decision-making phase in which dyads had to make a perceptual estimation in three consecutive trials and could converge in their decisions without an explicit request or reward to do so. In Study 1, 80 participants were divided in two conditions. In one condition participants did the pre-activation phase alone, while in the other condition the two participants did it with their partners and could interact freely. In Study 2, we registered the electroencephalographical (EEG) activity of 36 participants in the social decision-making phase.ResultsStudy 1 showed behavioral evidence of higher spontaneous convergence in participants who interacted in the pre-activation phase. Event related Potentials (ERP) recorded in Study 2 revealed signal differences in response divergence in different time intervals. Time-frequency analysis showed theta, alpha, and beta evidence related to cognitive control, attention, and reward processing associated with social convergence.DiscussionCurrent results support the spontaneous convergence of behavior in dyads, with increased behavioral adjustment in those participants who have previously cooperated. In addition, neurophysiological components were associated with discrepancy levels between participants, and supported the validity of the experimental paradigm to study spontaneous social behavioral adaptation in experimental settings

Intra- and inter-brain synchrony oscillations underlying social adjustment

Humans naturally synchronize their behavior with other people. However, although it happens almost automatically, adjusting behavior and conformity to others is a complex phenomenon whose neural mechanisms are still yet to be understood entirely. The present experiment aimed to study the oscillatory synchronization mechanisms underlying automatic dyadic convergence in an EEG hyperscanning experiment. Thirty-six people performed a cooperative decision-making task where dyads had to guess the correct position of a point on a line. A reinforcement learning algorithm was used to model different aspects of the participants’ behavior and their expectations of their peers. Intra- and inter-connectivity among electrode sites were assessed using inter-site phase clustering in three main frequency bands (theta, alpha, beta) using a two-level Bayesian mixed-effects modeling approach. The results showed two oscillatory synchronization dynamics related to attention and executive functions in alpha and reinforcement learning in theta. In addition, inter-brain synchrony was mainly driven by beta oscillations. This study contributes preliminary evidence on the phase-coherence mechanism underlying inter-personal behavioral adjustment

La gestión de residuos en la empresa: motivaciones para su implantación y mejoras asociadas

ResumenEntre los problemas medioambientales actuales, la reducción o eliminación de los residuos se ha convertido en una de las principales preocupaciones en los países industrializados y en una prioridad para las empresas. En el presente trabajo se realiza una revisión de los postulados del modelo económico clásico, vigente hasta hace escasas fechas, en relación con la variable medio ambiente y los residuos generados por las empresas. Asimismo, se revisa la literatura existente en torno a la potencialidad de la gestión de residuos y las posibles alternativas para la obtención de ventajas derivadas de un tratamiento eficiente de los mismos. El estudio se completa con el análisis empírico de la gestión de residuos en empresas de la Comunidad Autónoma del País Vasco. Así, se analizan las motivaciones que impulsan a las empresas a implementar un sistema de gestión de residuos y las ventajas o beneficios que de ello se derivan, entre otros factores.AbstractNowadays the reduction or elimination of waste has become a major environmental concern among industrialized countries and a priority for companies. In this work it is carried out a review of the postulates of the classical economic model, existing until a few dates, in connection with the variable environment and waste generated by firms. It is also examined the literature about the potential of the waste management and possible alternatives for obtaining of advantages or benefits derived from an efficient treatment of waste. This paper is completed with an empirical analysis of the waste management in companies of the Basque Autonomous Community. The motivations that drive firms to implement a waste management system and the advantages or benefits which derive from this fact are analyzed among other factors

Neurophysiological correlates of interpersonal discrepancy and social adjustment in an interactive decision-making task in dyads

Introduction: The pursuit of convergence and the social behavioral adjustment of conformity are fundamental cooperative behaviors that help people adjust their mental frameworks to reach a common goal. However, while social psychology has extensively studied conformity by its influence context, there is still plenty to investigate about the neural cognitive mechanisms involved in this behavior. Methods: We proposed a paradigm with two phases, a pre-activation phase to enhance cooperative tendencies and, later, a social decision-making phase in which dyads had to make a perceptual estimation in three consecutive trials and could converge in their decisions without an explicit request or reward to do so. In Study 1, 80 participants were divided in two conditions. In one condition participants did the pre-activation phase alone, while in the other condition the two participants did it with their partners and could interact freely. In Study 2, we registered the electroencephalographical (EEG) activity of 36 participants in the social decision-making phase. Results: Study 1 showed behavioral evidence of higher spontaneous convergence in participants who interacted in the pre-activation phase. Event related Potentials (ERP) recorded in Study 2 revealed signal differences in response divergence in different time intervals. Time-frequency analysis showed theta, alpha, and beta evidence related to cognitive control, attention, and reward processing associated with social convergence. Discussion: Current results support the spontaneous convergence of behavior in dyads, with increased behavioral adjustment in those participants who have previously cooperated. In addition, neurophysiological components were associated with discrepancy levels between participants, and supported the validity of the experimental paradigm to study spontaneous social behavioral adaptation in experimental settings

Vanadium Redox Flow Batteries: A Review Oriented to Fluid-Dynamic Optimization

Large-scale energy storage systems (ESS) are nowadays growing in popularity due to the increase in the energy production by renewable energy sources, which in general have a random intermittent nature. Currently, several redox flow batteries have been presented as an alternative of the classical ESS; the scalability, design flexibility and long life cycle of the vanadium redox flow battery (VRFB) have made it to stand out. In a VRFB cell, which consists of two electrodes and an ion exchange membrane, the electrolyte flows through the electrodes where the electrochemical reactions take place. Computational Fluid Dynamics (CFD) simulations are a very powerful tool to develop feasible numerical models to enhance the performance and lifetime of VRFBs. This review aims to present and discuss the numerical models developed in this field and, particularly, to analyze different types of flow fields and patterns that can be found in the literature. The numerical studies presented in this review are a helpful tool to evaluate several key parameters important to optimize the energy systems based on redox flow technologies.The authors appreciate the support to the government of the Basque Country through research programs Grants N. ELKARTEK 20/71 and ELKARTEK 20/78

Metal Knitting: A New Strategy for Cold Gas Spray Additive Manufacturing

Cold Spray Additive Manufacturing (CSAM) is an emergent technique to produce parts by the additive method, and, like other technologies, it has pros and cons. Some advantages are using oxygen-sensitive materials to make parts, such as Ti alloys, with fast production due to the high deposition rate, and lower harmful residual stress levels. However, the limitation in the range of the parts' geometries is a huge CSAM con. This work presents a new conceptual strategy for CSAM spraying. The controlled manipulation of the robot arm combined with the proper spraying parameters aims to optimize the deposition efficiency and the adhesion of particles on the part sidewalls, resulting in geometries from thin straight walls, less than 5 mm thick, up to large bulks. This new strategy, Metal Knitting, is presented regarding its fundamentals and by comparing the parts' geometries produced by Metal Knitting with the traditional strategy. The Metal Knitting described here made parts with vertical sidewalls, in contrast to the 40 degrees of inclination obtained by the traditional strategy. Their mechanical properties, microstructures, hardness, and porosity are also compared for Cu, Ti, Ti6Al4V, 316L stainless steel, and Al

Validation of LDLr Activity as a Tool to Improve Genetic Diagnosis of Familial Hypercholesterolemia: A Retrospective on Functional Characterization of LDLr Variants

Familial hypercholesterolemia (FH) is an autosomal dominant disorder characterized by high blood-cholesterol levels mostly caused by mutations in the low-density lipoprotein receptor (LDLr). With a prevalence as high as 1/200 in some populations, genetic screening for pathogenic LDLr mutations is a cost-effective approach in families classified as definite' or probable' FH and can help to early diagnosis. However, with over 2000 LDLr variants identified, distinguishing pathogenic mutations from benign mutations is a long-standing challenge in the field. In 1998, the World Health Organization (WHO) highlighted the importance of improving the diagnosis and prognosis of FH patients thus, identifying LDLr pathogenic variants is a longstanding challenge to provide an accurate genetic diagnosis and personalized treatments. In recent years, accessible methodologies have been developed to assess LDLr activity in vitro, providing experimental reproducibility between laboratories all over the world that ensures rigorous analysis of all functional studies. In this review we present a broad spectrum of functionally characterized missense LDLr variants identified in patients with FH, which is mandatory for a definite diagnosis of FH.This work was supported by ELKARTEK 2016 and and the Basque Government (Grupos Consolidados IT849-13). A.B.-V. and S.J. were supported by a grant PIF (2014-2015) and (2018-2021), Gobierno Vasco respectively

Automatic Identification Algorithm of Equivalent Electrochemical Circuit Based on Electroscopic Impedance Data for a Lead Acid Battery

Obtaining tools to analyze and predict the performance of batteries is a non-trivial challenge because it involves non-destructive evaluation procedures. At the research level, the development of sensors to allow cell-level monitoring is an innovative path, and electrochemical impedance spectrometry (EIS) has been identified as one of the most promising tools, as is the generation of advanced multivariable models that integrate environmental and internal-battery information. In this article, we describe an algorithm that automatically identifies a battery-equivalent electrochemical model based on electroscopic impedance data. This algorithm allows in operando monitoring of variations in the equivalent circuit parameters that will be used to further estimate variations in the state of health (SoH) and state of charge (SoC) of the battery based on a correlation with experimental aging data corresponding to states of failure or degradation. In the current work, the authors propose a two-step parameter identification algorithm. The first consists of a rough differential evolution algorithm-based identification. The second is based on the Nelder–Mead Simplex search method, which gives a fine parameter estimation. These algorithm results were compared with those of the commercially available Z-view, an equivalent circuit tool estimation that requires expert human input.Special thanks should also be expressed for the Torres Quevedo (PTQ) 2019 Aid from the State Research Agency, within the framework of the State Program for the Promotion of Talent and its Employability in R + D + i, Ref. PTQ2019-010787 /AEI/10.13039/501100011033