Over the last decade or so, several researchers have considered the predictive processing framework (PPF) to be a useful perspective from which to shed some much-needed light on the mechanisms behind psychosis. Most approaches to psychosis within PPF come down to the idea of the “atypical” brain generating inaccurate hypotheses that the “typical” brain does not generate, either due to a systematic top-down processing bias or more general precision weighting breakdown. Strong at explaining common individual symptoms of psychosis, such approaches (...) face some issues when we look at a more general clinical picture. In this paper, we propose an update on the current accounts of psychosis based on the realization that a neurotypical brain constantly generates non-actual, de-coupled, counterfactual hypotheses as part of healthy cognition. We suggest that what is going on in psychosis, at least in some cases, is not so much a generation of erroneous hypotheses, but rather an inability to correctly use the counterfactual ones. This updated view casts “accurate” cognition as more fragile and delicate, but also closes the gap between psychosis and typical cognition. (shrink)

This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. Our approach can be described as _computational phenomenology_ because it applies methods originally developed in computational modelling to provide a formal model of the descriptions of lived experience in the phenomenological tradition of philosophy (e.g., the work of Edmund Husserl, Maurice Merleau-Ponty, etc.). The first section presents a brief review of the overall project to naturalize phenomenology. The second section presents and evaluates (...) philosophical objections to that project and situates our version of computational phenomenology with respect to these projects. The third section reviews the generative modelling framework. The final section presents our approach in detail. We conclude by discussing how our approach differs from previous attempts to use generative modelling to help understand consciousness. In summary, we describe a version of computational phenomenology which uses generative modelling to construct a computational model of the inferential or interpretive processes that best explain this or that kind of lived experience. (shrink)

Generalized anxiety disorder is among the world’s most prevalent psychiatric disorders and often manifests as persistent and difficult to control apprehension. Despite its prevalence, there is no integrative, formal model of how anxiety and anxiety disorders arise. Here, we offer a perspective derived from the free energy principle; one that shares similarities with established constructs such as learned helplessness. Our account is simple: anxiety can be formalized as learned uncertainty. A biological system, having had persistent uncertainty in its past, will (...) expect uncertainty in its future, irrespective of whether uncertainty truly persists. Despite our account’s intuitive simplicity—which can be illustrated with the mere flip of a coin—it is grounded within the free energy principle and hence situates the formation of anxiety within a broader explanatory framework of biological self-organization and self-evidencing. We conclude that, through conceptualizing anxiety within a framework of working generative models, our perspective might afford novel approaches in the clinical treatment of anxiety and its key symptoms. (shrink)

This exploration aims to solve the problems of imperfect psychological health education system and poor educational effects on college students. Here, ideological and political education is integrated with mental health education to investigate the role of collaborative intervention in guiding college students to resist negative emotions. First, an overview is offered of research on ideological and political education, mental health education, and negative emotions by the literature survey method. Moreover, a comprehensive investigation is also conducted on research objects, through the (...) questionnaire, to understand the current situation of negative emotions of college students. And finally, an intervention experiment is taken on the negative emotions of college students by combining ideological and political education with mental health education. The results show that after 10 weeks of intervention experiment by combining ideological and political education with mental health education, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between the treatment group and the control group. Besides, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between sophomores in the treatment group and the control group. Moreover, there are significant differences in depression, negative emotions, somatization symptoms, and interpersonal problems between male participants in the treatment group and the control group. In summary, ideological and political education integrated with mental health education has a positive guidance effect on the negative emotions of college students, greatly improving the negative emotions of the students, helping the students to regulate their emotions, and benefiting their study and life a lot. The purpose of integrating ideological and political education with mental health education is to provide reference for refining the mental health education system of college students and strengthening the positive guidance of negative emotions of college students. (shrink)