A recent theoretical framework has formalized predictive mechanisms in the sensorimotor system. This “predictive coding,” also called the agent-centered approach, has revealed some dysfunctions of prediction in patients with mental disorders such as schizophrenia. The dynamic and hierarchical nature of prediction could be innately aberrant. Therefore, their representation as a generative model of the self and the world is unclear. The current paper discusses (1) the theoretical controversies in subjective probability in the Bayesian perspective and (2) its application for understanding psychotic symptoms or experiences such as delusions and hallucinations for future empirical work.
Asai (2019) discusses a transformation of the view of reality resulting from the Bayesian theory of inference. The current paper offers philosophical interpretations concerning the significance, scope, and possible development of Asai’s discussion, which are especially based on a phenomenological point of view. Asai’s Bayesian view of reality is closely related to phenomenology. It implies a denial of determinism and naive realism. However, these traits of Asai’s view can signify a more moderate and scientific attitude. What an individual experiences as reality is the effect of certain filters that his or her experience has. Asai calls this effect “attention”; however, it is better described as “consciousness.” His interpretation of reality as mutual interference of waves is convincing and closely matches the quantum theoretical view of reality. Finally, such a transformation of the view of reality can positively affect the view of “mental disorder.” The aim of psychiatric treatment should not be to conform patients to the “only one same reality” (which is illusory), but to gear (or accommodate) different realities to each other.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in which the most prominent symptoms are deficits in social interaction and communication, and restricted and repetitive patterns of behavior, interests, or activities. The latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) has recently included atypical sensory responsiveness (i.e., hyper- or hyporeactivity to sensory input). This review discusses attentional hypotheses and sensory processing as a developmental bias to stimulation processing in social interactions in individuals with ASD. The first section reviews the weak central coherence hypothesis (Happé & Frith, 2006) and reviews the enhanced perceptual functioning hypothesis (Mottron et al., 2006), which is a basic, but not necessarily social, disturbance of the perceptual-cognitive style and focuses on detail-focused processing in ASD. These proposed hypotheses are a framework within which the perceptual characteristics of individuals with ASD can be understood. The second section discusses a possible mechanism between specific sensory processing (e.g., arousal system and interoception) and atypical social interaction (e.g., repetitive and stereotyped interests and behaviors) in ASD, based on the discussion of the predictive coding theory. Individuals with ASD limit the input of information by an attentional focus on a part of the stimulus and/or by restricted and repetitive behavior. These aspects of information processing may contribute to the generation and stabilization of models of the internal or emotional self. Thus, attentional biases such as detail-focused processing in ASD are an adaptive mechanism for managing the overabundance of visual information.
This paper reviews the role of empathy in autism spectrum disorders and psychopathy. Empathy can be subdivided into two categories: cognitive empathy (i.e., the ability to identify the emotions of others) and affective empathy (i.e., the ability to share or match the emotions of the self with those of others). Individuals with autism spectrum disorders lack cognitive empathy, whereas individuals with psychopathy lack emotional empathy. The similarity hypothesis states that people empathize with other people who are similar to themselves in personality and in conditions such as developmental disorders or typical development. The similarity hypothesis predicts that individuals with autism spectrum disorders would emotionally empathize with other people with autism spectrum disorders, and individuals with psychopathy would cognitively empathize with other people with psychopathy. Finally, we attempted to interpret autism spectrum disorders and psychopathy as resulting from the neurodiversity of empathy.
Knowledge and recognition of the significance and strength of various cognitive-behavioural phenotypes, including phenotypes associated with mental and developmental disorders, are increasing but remain limited. With a focus on biological, psychological, and economic concepts such as biodiversity, neurodiversity, and comparative advantage, this paper argues that individuals and society benefit when individuals with different cognitive-behavioural profiles coexist within a society. This paper also discusses the strength of various cognitive-behavioural phenotypes, focusing especially on the autism spectrum. The advantages and strength of diverse cognitive-behavioural phenotypes are emphasised; however, highlighting these positive aspects does not mean neglecting individuals’ need for support: humans are multifaceted and individuals who share a diagnosis are varied as well. Future research must increasingly focus on how we all can take advantage of our strengths through sharing perspectives, including the perspectives of individuals facing disabilities.
Many studies demonstrate attentional bias to threatening stimuli in social anxiety. Several cognitive models of anxiety propose that bottom-up and top-down processing have an important role in threat-related attentional bias. This review summarizes the empirical evidence for attentional bias in social anxiety that supports the cognitive model. Enhanced bottom-up processing (e.g., salience evaluation, stimulus-driven attention, alerting) and impaired top-down processing (e.g., goal-directed orienting, inhibitory control, working memory capacity) underlie facilitated threat-related attention. The present review also explains the role of attentional bias in a developmental framework. Temperamental traits and family environments develop attentional bias and moderate the relationship between attentional bias and social anxiety. The present review concludes by examining attentional bias modification training to reduce social anxiety by reducing attention bias. Several issues remain unresolved in attentional bias modification.
Depression is a highly recognized mental disorder that has been widely studied. However, an essential understanding of depression has not been achieved. We conducted a narrative review to examine the mechanism of depression, based on the perspective of a computational approach. We focused on studies that used the reinforcement learning model. We reviewed the relationship between the parameters of the reinforcement learning model and anhedonia symptoms. The computational approach to depression is a new research field; therefore, we will also propose future topics for study on the basis of our narrative reviews. In particular, we discuss increasing the quality of our findings by using model-based reinforcement learning and the Bayesian inference models, and exploring the mechanisms of psychotherapy.
The transdiagnostic approach to psychopathologies was introduced as a solution to high comorbidity and weak differentiation of psychological disorders. Factor analytic studies have revealed a hierarchical structure with the highest single p-factor (i.e., psychopathology), which parallels the results in the personality studies of general factor of personality over the Big 5 dimensions. The etiology of the single super-factor is considered in the life history strategy in evolutionary psychology. Two strategies to clinically utilize the p-factor are discussed, as follows: (1) setting the p-factor as a predictor to probe the relevant mediators (i.e., endophenotype) of symptoms and (2) moving across the levels of hierarchy to enhance flexible responding. The final topic discussed is the cybernetic principle with goal hierarchy, which will enhance studies on personality, psychopathology, and well-being.
Studies on psychiatric disorders in abnormal psychology have shown several cognitive and affective features of psychiatric patients such as attentional bias, deficits in working memory, deviations in the parameters of reinforcement learning such as learning rate, inverse temperature, and discounting rate. However, causal relationships between such cognitive and affective features and symptoms of the disorders are unclear. The hypothesis of this study is that the dysregulation of homeostasis and allostasis via mechanisms of the predictive coding of interoception may be a critical mediator of the link between cognitive and affective features and psychiatric disorders. In this paper, a computational model combining the predictive coding of interoception and reinforcement learning is proposed to provide suggestions for the hypothesis. Simulations using the model suggested that (1) a reduced learning rate and inverse temperature, which are observed in depressed patients, can lead to unstable decision-making and maintained higher levels of reward predictive errors and (2) can consequently result in dull physiological reactivity and chronically higher levels of autonomic responses. These results provide a perspective that can integrate cognitive and affective features, physiological states, and symptoms of psychiatric disorders.