Ryan Smith

The Laureate Institute for Brain Research (LIBR) / University of Tulsa

Anxiety and depression commonly co-occur, yet the underlying brain and behavioral processes are poorly understood. Here we examined the hypothesis that individuals with comorbid anxiety and depression would show increased fearful reactivity to an aversive interoceptive perturbation relative to depressed-only individuals. One-hundred and eighty anxi...

Introduction: Repetitive negative thinking (RNT) is a cognitive process focusing on self-relevant and negative experiences, leading to a poor prognosis of major depressive disorder (MDD). We previously identified that connectivity between the precuneus/posterior cingulate cortex (PCC) and right temporoparietal junction (rTPJ) was positively correl...

It is unclear at present whether psychopathic tendencies are associated with lower or higher levels of emotional awareness (EA). Given that psychopathy includes a proficiency for manipulating others, one might expect an elevated ability to identify and use information about others’ emotions. On the other hand, empathic deficits in psychopathy could...

Evidence suggests that emotional awareness – the ability to identify and label emotions – may be impaired in schizophrenia and related to positive symptom severity. Exposure to childhood trauma is a risk factor for both low emotional awareness and positive symptoms. The current investigation examines associations between a performance-based measure...

The central nervous system (CNS) exerts a strong regulatory influence over the cardiovascular system in response to environmental demands. Floatation-REST (Reduced Environmental Stimulation Therapy) is an intervention that minimizes stimulation from the environment, yet little is known about the autonomic consequences of reducing external sensory i...

Understanding and promoting subjective wellbeing (SWB) has been the topic of increasing research, due in part to its potential contributions to health and productivity. To date, the conceptualization of SWB has been grounded within social psychology and largely focused on self-report measures. In this paper, we explore the potentially complementary...

Introduction: Multiple measures of decision-making under uncertainty (e.g. jumping to conclusions, bias against disconfirmatory evidence, win-switch behavior, random exploration) have been associated with delusional thinking in independent studies. Yet, it is unknown whether these variables explain shared or unique variance in delusional thinking,...

Background: We have previously reported activation in reward, salience and executive control regions during functional MRI (fMRI) using an approach–avoidance conflict (AAC) decision-making task with healthy adults. Further investigations into how anxiety and depressive disorders relate to differences in neural responses during AAC can inform their...

Mindfulness training (MT) has been shown to influence smoking behavior, yet the involvement of reinforcement learning processes as underlying mechanisms remains unclear. This naturalistic, single-arm study aimed to examine slope trajectories of smoking behavior across uses of our app-based MT craving tool for smoking cessation, and whether this rel...

Computational modelling is a promising approach to parse dysfunctional cognitive processes in substance use disorders (SUDs), but it is unclear how much these processes change during the recovery period. We assessed 1-year follow-up data on a sample of treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, ha...

The active inference framework, and in particular its recent formulation as a partially observable Markov decision process (POMDP), has gained increasing popularity in recent years as a useful approach for modeling neurocognitive processes. This framework is highly general and flexible in its ability to be customized to model any cognitive process,...

Active inference offers a unified theory of perception, learning, and decision-making at computational and neural levels of description. In this article, we address the worry that active inference may be in tension with the belief–desire–intention (BDI) model within folk psychology because it does not include terms for desires (or other conative co...

Cognitive theories of consciousness, such as global workspace theory and higher-order theories, posit that frontoparietal circuits play a crucial role in conscious access. However, recent studies using no-report paradigms have posed a challenge to cognitive theories by demonstrating conscious accessibility in the apparent absence of prefrontal cort...

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 tendency to reflect on the emotions of self and others is a key aspect of emotional awareness (EA)—a trait widely recognized as relevant to mental health. However, the degree to which EA draws on general reflective cognition vs. specialized socio-emotional mechanisms remains unclear. Based on a synthesis of work in neuroscience and psychology,...

Recent theoretical work suggests that emotional awareness (EA) depends on the harshness/predictability of early social interactions—and that low EA may in fact be adaptive in harsh environments that lack predictable interpersonal interactions. In evolutionary psychology, this process of psychological “calibration” to early environments corresponds...

There is a growing body of evidence suggesting that the neural processes underlying perception, learning, and decision-making approximate Bayesian inference. Yet, humans perform poorly when asked to solve explicit probabilistic reasoning problems. In response, some have argued that certain brain processes are Bayesian while others are not; others h...

Anxiety and depression are often associated with strong beliefs that entering specific situations will lead to aversive outcomes – even when these situations are objectively safe and avoiding them reduces well-being. A possible mechanism underlying this maladaptive avoidance behavior is a failure to reflect on: (1) appropriate levels of uncertainty...

(1) Background: Growing evidence indicates that inflammation can induce neural circuit dysfunction and plays a vital role in the pathogenesis of major depressive disorder (MDD). Nevertheless, whether inflammation affects the integrity of white matter pathways is only beginning to be explored. (2) Methods: We computed quantitative anisotropy (QA) fr...

Purpose of Review In this article, we provide a brief review of recent computational modelling studies of substance use disorders (SUDs), with a focus on work published within the last 5 years. While reinforcement learning (RL) approaches are most prominent in recent studies, we also review work from other perspectives that focus on Bayesian (activ...

Computational modelling is a promising approach to parse dysfunctional cognitive processes in substance use disorders (SUDs), but it is unclear how much these processes change during the recovery period. We assessed 1-year follow-up data on a sample of treatment-seeking individuals with one or more SUDs (alcohol, cannabis, sedatives, stimulants, ha...

Introduction: The COVID-19 pandemic has presented a major challenge to mental health and emotional wellbeing. The present study examined whether training in emotional intelligence (EI) skills, provided before the pandemic, would serve as a protective factor for sustaining mental health during the COVID-19 crisis. Methods: Data came from a longit...

Anxiety and depression are often associated with strong beliefs that entering specific situations will lead to aversive outcomes – even when these situations are objectively safe and avoiding them reduces well-being. A possible mechanism underlying this maladaptive avoidance behavior is a failure to reflect on: 1) appropriate levels of uncertainty...

Cognitive theories of consciousness, such as global workspace theory and higher-order theories, posit that frontoparietal circuits play a crucial role in conscious access. However, recent studies using no-report paradigms have posed a challenge to cognitive theories by demonstrating conscious accessibility in the apparent absence of prefrontal cort...

Emotional awareness is the ability to conceptualize and describe one’s own emotions and those of others. Over thirty years ago, a cognitive-developmental theory of emotional awareness patterned after Piaget’s theory of cognitive development was created as well as a performance measure of this ability called the Levels of Emotional Awareness Scale (...

Background and aims Maladaptive eating habits are a major cause of obesity and weight-related illness. The development of empirically-based approaches, such as mindfulness training (MT) that target accurate mechanisms of action to address these behaviors is therefore critical. Two studies were conducted to examine the impact of MT on maladaptive ea...

People often form polarized beliefs about others. In a clinical setting this is referred to as a dichotomous or ‘split’ representation of others, whereby others are not imbued with possessing mixtures of opposing properties. Here, we formalise these accounts as an oversimplified categorical model of others’ internal, intentional, states. We show ho...

Neurocomputational theories have hypothesized that Bayesian inference underlies interoception, which has become a topic of recent experimental work in heartbeat perception. To extend this approach beyond cardiac interoception, we describe the application of a Bayesian computational model to a recently developed gastrointestinal interoception task c...

The tendency to reflect on the emotions of self and others is a key aspect of emotional awareness (EA) – a trait widely recognized as relevant to mental health. However, the degree to which EA draws on general reflective cognition vs. specialized socio-emotional mechanisms remains unclear. Based on a synthesis of work in neuroscience and psychology...

Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty and sensitivity to negative outcomes versus reward (emoti...

Cognitive-behavioral therapy (CBT) leverages interactions between thoughts, feelings, and behaviors. To deepen understanding of these interactions, we present a computational (active inference) model of CBT that allows formal simulations of interactions between cognitive interventions (i.e., cognitive restructuring) and behavioral interventions (i....

Active inference offers a unified theory of perception, learning, and decision-making at computational and neural levels of description. In this article, we address the worry that active inference may be in tension with folk psychology because it does not include terms for desires (or other conative constructs) at the mathematical level of descript...

Recent theoretical work suggests that emotional awareness (EA) depends on the harshness/predictability of early social interactions – and that low EA may actually be adaptive in harsh environments that lack predictable interpersonal interactions. In evolutionary psychology, this process of psychological “calibration” to early environments correspon...

Emotional intelligence (EI) is associated with a range of positive outcomes, and methods to increase EI are greatly needed. The present study tests the effectiveness of an online training program for increasing EI in adults. After an initial design and refinement process, 326 participants were randomly assigned to complete an EI training program or...

This paper presents a version of neurophenomenology based on generative modelling techniques developed in computational neuroscience and biology. We call this approach computational phenomenology because it applies methods originally developed in computational modelling to phenomenology. The first section presents a brief review of the project to n...

Understanding the neural processes governing the human gut-brain connection has been challenging due to the inaccessibility of the body′s interior. Here, we investigated neural responses to gastrointestinal sensation using a minimally invasive mechanosensory probe by quantifying brain, stomach, and perceptual responses following the ingestion of a...

Background Substance use disorders (SUD) with comorbid depression and anxiety are linked to poor treatment outcome and relapse. Although some depressed individuals exhibit elevated blood-based inflammation (interleukin-6 [IL-6] and C reactive protein [CRP]), few studies have examined whether the presence of SUD exacerbates inflammation. Methods Tr...

This study employed a series of heartbeat perception tasks to assess the hypothesis that cardiac interoceptive processing in individuals with depression/anxiety (N = 221), and substance use disorders (N = 136) is less flexible than that of healthy individuals (N = 53) in the context of physiological perturbation. Cardiac interoception was assessed...

The active inference framework, and in particular its recent formulation as a partially observable Markov decision process (POMDP), has gained increasing popularity in recent years as a useful approach for modelling neurocognitive processes. This framework is highly general and flexible in its ability to be customized to model any cognitive process...

This chapter reviews current perspectives on the neural basis of subjective experience. Its primary focus is on the interaction between two broad dimensions of experience: subjective contents (e.g., the conscious experience of seeing a red ball or feeling a sharp pain) and the global brain states that modulate the representation of those contents a...

The aim of this paper is to leverage the free-energy principle and its corollary process theory, active inference, to develop a generic, generalizable model of the representational capacities of living creatures; that is, a theory of phenotypic representation. Given their ubiquity, we are concerned with distributed forms of representation (e.g., po...

Theoretical proposals have previously been put forward regarding the computational basis of interoception. Following on this, we recently reported using an active inference approach to 1) quantitatively simulate interoceptive computation, and 2) fit the model to behavior on a cardiac awareness task. In the present work, we attempted to replicate ou...

Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty and sensitivity to negative outcomes vs. reward (emotiona...

Recent neurocomputational theories have hypothesized that abnormalities in prior beliefs and/or the precision-weighting of afferent interoceptive signals may facilitate the transdiagnostic emergence of psychopathology. Specifically, it has been suggested that, in certain psychiatric disorders, interoceptive processing mechanisms either over-weight...

The positive-negative axis of emotional valence has long been recognized as fundamental to adaptive behavior, but its origin and underlying function have largely eluded formal theorizing and computational modeling. Using deep active inference, a hierarchical inference scheme that rests on inverting a model of how sensory data are generated, we deve...

Anxiety disorders are the most widespread form of mental illness, affecting roughly 34% of the population worldwide. Exposure therapy is a central component of leading cognitive-behavioural treatments, yet they are effective in only 40–60% of individuals, and of these 20% relapse within 1 year. Because exposure is highly aversive, many individuals...

Background: Imbalances in approach-avoidance conflict (AAC) decision-making (e.g., sacrificing rewards to avoid negative outcomes) are considered central to multiple psychiatric disorders. We used computational modelling to examine 2 factors that are often not distinguished in descriptive analyses of AAC: decision uncertainty and sensitivity to neg...

Theoretical proposals have previously been put forward regarding the computational basis of interoception. Following on this, we recently reported using an active inference approach to 1) quantitatively simulate interoceptive computation, and 2) fit the model to behavior on a cardiac awareness task. In the present work, we attempted to replicate ou...

In this paper, we combine sophisticated and deep-parametric active inference to create an agent whose affective states change as a consequence of its Bayesian beliefs about how possible future outcomes will affect future beliefs. To achieve this, we augment Markov Decision Processes with a Bayes-adaptive deep-temporal tree search that is guided by...

The global neuronal workspace (GNW) model has inspired over two decades of hypothesis-driven research on the neural basis of consciousness. However, recent studies have reported findings that are at odds with empirical predictions of the model. Further, the macro-anatomical focus of current GNW research has limited the specificity of predictions af...

Active inference is a normative framework for generating behaviour based upon the free energy principle, a theory of self-organisation. This framework has been successfully used to solve reinforcement learning and stochastic control problems, yet, the formal relation between active inference and reward maximisation has not been fully explicated. In...

Affective agnosia, an impairment in knowing how one feels emotionally, has been described as an extreme deficit in the experience and expression of emotion that may confer heightened risk for adverse medical outcomes. Alexithymia, by contrast, has been proposed as an over-arching construct that includes a spectrum of deficits of varying severity, i...

Theoretical proposals have previously been put forward regarding the computational basis of interoception. Following on this, we recently reported using an active inference approach to 1) quantitatively simulate interoceptive computation, and 2) fit the model to behavior on a cardiac awareness task. In the present work, we attempted to replicate ou...

Research in clinical neuroscience is founded on the idea that a better understanding of brain (dys)function will improve our ability to diagnose and treat neurological and psychiatric disorders. In recent years, neuroscience has converged on the notion that the brain is a ‘prediction machine’—in that it actively predicts the sensory input that it w...

The aim of this paper is to leverage the free-energy principle and its corollary process theory, active inference, to develop a generic, generalizable model of the representational capacities of living creatures; that is, a theory of phenotypic representation. Given their ubiquity, we are concerned with distributed forms of representation (e.g., po...

Background Substance use disorders (SUDs) are a major public health risk. However, mechanisms accounting for continued patterns of poor choices in the face of negative life consequences remain poorly understood. Methods We use a computational (active inference) modeling approach, combined with multiple regression and hierarchical Bayesian group an...

Cognitive-behavioral therapy (CBT) leverages interactions between thoughts, feelings, and actions. In this paper, we use neurocomputational modelling to deepen our understanding of the mechanisms underlying these interactions and how therapeutic interventions can produce behavioral change through different mechanisms in different cases. We describe...

Will man die Neurobiologie von Emotionen erfassen, bietet es sich an, zum besseren Verständnis in mehreren Schritten vorzugehen. Der erste Schritt besteht darin, die umfassende Kategorie der »Emotionen« in eine Reihe von grundlegen-den, miteinander interagierenden Prozessen zu zerlegen. Im zweiten Schritt werden diese elementaren Prozesse dann empi...

Recent neurocomputational theories have hypothesized that abnormalities in prior expectations and/or the precision-weighting of afferent interoceptive signals (i.e. the degree to which afferent bodily signals contribute to interoceptive perceptual inference), may facilitate the transdiagnostic emergence of psychopathology. Specifically, it has been...

The active inference framework offers an attractive starting point for understanding cultural cognition. Here, we argue that affective dynamics are essential to include when constructing this type of theory. We highlight ways in which interactions between emotional responses and the perception of those responses, both within and between individuals...

Within computational neuroscience, the algorithmic and neural basis of structure learning remains poorly understood. Concept learning is one primary example, which requires both a type of internal model expansion process (adding novel hidden states that explain new observations), and a model reduction process (merging different states into one unde...