Psychophysiological response to social stressors : relevance of sex and age

Understanding the factors involved in the psychophysiological response of people in acute stressful situations is crucial to the prevention and treatment of stress-related health problems. We aim to integrate the results of studies investigating the role of sex and age in the inter-individual variability in several biomarkers of the stress response Methods: We summarize the main findings of our research group and other laboratories regarding sex and age-related differences in the psychophysiological response to psychosocial stress. Results: Sexrelated differences in the stress response are observed in blood pressure and cortisol, but not in heart rate, heart rate variability, or salivary alphaamylase. Additionally, age may explain differences in cortisol levels and basal sympathetic nervous system activity. Conclusions: The results highlight the importance of taking sex and age into account in order to understand the stress response and its possible negative effects on health. Antecedentes: entender los factores involucrados en la respuesta psicofisiológica ante situaciones de estrés agudo es crucial para prevenir y tratar problemas de salud relacionados con el estrés. El objetivo es integrar los resultados de estudios en humanos relacionados con el papel del sexo y la edad en las diferencias individuales en la respuesta de estrés en diferentes biomarcadores. Metodología: se integran los principales resultados de nuestro grupo de investigación y de otros laboratorios centrados en las diferencias debidas al sexo y la edad en la respuesta psicofisiológica a situaciones de estrés psicosocial. Resultados: se observan diferencias en la respuesta de estrés entre hombres y mujeres en presión sanguínea y en niveles de cortisol, pero no en frecuencia cardíaca, variabilidad de la frecuencia cardíaca y alfa-amilasa. Además, la edad influye en los niveles de cortisol y en la actividad basal del sistema nervioso simpático. Conclusiones: los resultados ponen de manifiesto la importancia de tener en cuenta el sexo y la edad de los participantes para poder entender la respuesta de estrés y sus posibles efectos en salud

A Goal-Directed Bayesian Framework for Categorization

Categorization is a fundamental ability for efficient behavioral control. It allows organisms to remember the correct responses to categorical cues and not for every stimulus encountered (hence eluding computational cost or complexity), and to generalize appropriate responses to novel stimuli dependant on category assignment. Assuming the brain performs Bayesian inference, based on a generative model of the external world and future goals, we propose a computational model of categorization in which important properties emerge. These properties comprise the ability to infer latent causes of sensory experience, a hierarchical organization of latent causes, and an explicit inclusion of context and action representations. Crucially, these aspects derive from considering the environmental statistics that are relevant to achieve goals, and from the fundamental Bayesian principle that any generative model should be preferred over alternative models based on an accuracy-complexity trade-off. Our account is a step toward elucidating computational principles of categorization and its role within the Bayesian brain hypothesis

From extinction learning to anxiety treatment: mind the gap

Laboratory models of extinction learning in animals and humans have the potential to illuminate methods for improving clinical treatment of fear-based clinical disorders. However, such translational research often neglects important differences between threat responses in animals and fear learning in humans, particularly as it relates to the treatment of clinical disorders. Specifically, the conscious experience of fear and anxiety, along with the capacity to deliberately engage top-down cognitive processes to modulate that experience, involves distinct brain circuitry and is measured and manipulated using different methods than typically used in laboratory research. This paper will identify how translational research that investigates methods of enhancing extinction learning can more effectively model such elements of human fear learning, and how doing so will enhance the relevance of this research to the treatment of fear-based psychological disorders.Published versio

Lying takes time : a meta-analysis on reaction time measures of deception

Lie detection techniques are frequently used, but most of them have been criticized for the lack of empirical support for their predictive validity and presumed underlying mechanisms. This situation has led to increased efforts to unravel the cognitive mechanisms underlying deception and to develop a comprehensive theory of deception. A cognitive approach to deception has reinvigorated interest in reaction time (RT) measures to differentiate lies from truths and to investigate whether lying is more cognitively demanding than truth telling. Here, we provide the results of a meta-analysis of 114 studies (n = 3307) using computerized RT paradigms to assess the cognitive cost of lying. Results revealed a large standardized RT difference, even after correction for publication bias (d = 1.049; 95% CI [0.930; 1.169]), with a large heterogeneity amongst effect sizes. Moderator analyses revealed that the RT deception effect was smaller, yet still large, in studies in which participants received instructions to avoid detection. The autobiographical Implicit Association Test produced smaller effects than the Concealed Information Test, the Sheffield Lie Test, and the Differentiation of Deception paradigm. An additional meta-analysis (17 studies, n = 348) showed that, like other deception measures, RT deception measures are susceptible to countermeasures. Whereas our meta-analysis corroborates current cognitive approaches to deception, the observed heterogeneity calls for further research on the boundary conditions of the cognitive cost of deception. RT-based measures of deception may have potential in applied settings, but countermeasures remain an important challenge

Attention modulates the specificity of automatic imitation to human actors

The perception of actions performed by others activates one’s own motor system. Recent studies disagree as to whether this effect is specific to actions performed by other humans, an issue complicated by differences in perceptual salience between human and non-human stimuli. We addressed this issue by examining the automatic imitation of actions stimulated by viewing a virtual, computer generated, hand. This stimulus was held constant across conditions, but participants’ attention to the virtualness of the hand was manipulated by informing some participants during instructions that they would see a “computer-generated model of a hand,” while making no mention of this to others. In spite of this attentional manipulation, participants in both conditions were generally aware of the virtualness of the hand. Nevertheless, automatic imitation of the virtual hand was significantly reduced––but not eliminated––when participants were told they would see a virtual hand. These results demonstrate that attention modulates the “human bias” of automatic imitation to non-human actors