Scott Alexander examines a theory proposing that depression, anxiety, and trauma are characterized by low precision of sensory evidence, leading to overreliance on negative priors. Longer summary

Scott Alexander discusses a paper by Van der Bergh et al. that proposes a unified theory of negative emotionality, including depression, anxiety, and trauma. The theory suggests that these conditions are characterized by a processing style that assigns unusually low precision to sensory evidence, leading to an overreliance on negative priors. Scott explores the implications of this theory, including its support for various psychotherapies, somatic therapies, and meditation. He also discusses potential pharmacological interventions and how this model ties together various concepts in psychiatry and predictive processing. Shorter summary

Scott Alexander draws parallels between OpenAI's GPT-2 language model and human dreaming, exploring their similarities in process and output quality. Longer summary

Scott Alexander compares OpenAI's GPT-2 language model to human dreaming, noting similarities in their processes and outputs. He explains how GPT-2 works by predicting next words in a sequence, much like the human brain predicts sensory input. The post explores why both GPT-2 and dreams produce narratives that are coherent in broad strokes but often nonsensical in details. Scott discusses theories from neuroscience and machine learning to explain this phenomenon, including ideas about model complexity reduction during sleep and comparisons to AI algorithms like the wake-sleep algorithm. He concludes by suggesting that dream-like outputs might simply be what imperfect prediction machines produce, noting that current AI capabilities might be comparable to a human brain operating at very low capacity. Shorter summary

Scott reviews a paper proposing a computational model of mood and emotions based on predictive processing, discussing its implications for understanding mood disorders. Longer summary

This post discusses a paper by Clark, Watson, and Friston that proposes a computational perspective on mood and emotions. The authors argue that emotions reflect changes in the uncertainty about the somatic consequences of action, while mood corresponds to hyperpriors about emotional states. The theory suggests that depression is a prediction of bad outcomes with high confidence, mania is a prediction of good outcomes with high confidence, and anxiety is a prediction of bad outcomes with low confidence. The post explores how this theory explains various aspects of mood disorders and their symptoms, including learned helplessness and the role of serotonin. The author finds the theory intriguing but notes some inconsistencies, particularly in unifying the concepts of 'prior on bad outcomes' and 'low precision of predictions'. Shorter summary

Scott Alexander attempts to understand and explain Karl Friston's complex 'free energy' principle in neuroscience, exploring its various interpretations and potential implications. Longer summary

Scott Alexander explores Karl Friston's work on 'free energy', a complex concept in neuroscience that has been described as a unified brain theory. The post delves into various interpretations of free energy, from its mathematical origins in Bayesian equations to its application in explaining perception, cognition, homeostasis, and action. Scott struggles to fully grasp the concept, acknowledging its complexity and the widespread difficulty in understanding Friston's work. He presents different perspectives on free energy, including its role in uncertainty reduction, its connection to predictive processing, and its potential to explain biological systems and the origin of life. The post concludes with a tentative synthesis of these ideas and raises questions about the implications of the free energy principle for machine ethics. Shorter summary

Scott Alexander explores the motivational system as described in 'The Hungry Brain', connecting it to dopamine, willpower, and predictive processing theory. Longer summary

Scott Alexander revisits Stephan Guyenet's book 'The Hungry Brain', focusing on its description of the motivational system. He explains how the basal ganglia in lampreys and humans select behaviors from competing 'bids' made by different brain regions. The post then discusses dopamine's role in this system and how disorders like Parkinson's disease and abulia affect motivation. Scott concludes by proposing a theory linking dopamine levels, willpower, and the predictive processing model, suggesting that high dopamine levels may represent confidence in overriding default behaviors with more willpower-intensive actions. Shorter summary

Scott proposes a speculative theory of depression as pathologically low confidence in neural predictions within the predictive processing framework, explaining how this could account for various depressive symptoms. Longer summary

This post explores a potential theory of depression within the predictive processing (PP) framework. Scott starts by noting the lack of a compelling PP account for depression, then proposes that depression might be a state of pathologically low confidence in neural predictions. He explains how this could account for various symptoms of depression, including perceptual changes, psychomotor retardation, and lack of motivation. The post then speculates on why low confidence might cause sadness, suggesting that emotions could be a way of globally adjusting confidence levels based on past success or failure. Scott acknowledges the speculative nature of these ideas and some potential problems with the theory. Shorter summary

Scott Alexander examines the conflict between predictive processing theory and evolutionary psychology claims about innate knowledge, questioning how genes could directly encode complex preferences. Longer summary

Scott Alexander explores the tension between predictive processing (PP) theory and evolutionary psychology claims about innate knowledge. He argues that while PP can accommodate some genetic influences on cognition, it struggles to explain how genes could directly encode high-level concepts like 'attraction to large breasts.' The post questions how such specific preferences could be genetically programmed given the limited number of genes humans have. Scott acknowledges that instincts clearly exist in animals, but suggests that even seemingly innate traits like gender identity may involve some level of inference. He proposes a heuristic for evaluating evolutionary psychology claims, recommending skepticism towards ideas that genes can directly manipulate high-level concepts unless there's a compelling evolutionary reason. Shorter summary

Scott Alexander explores the similarities between Predictive Processing and Perceptual Control Theory, arguing that PCT anticipates many aspects of PP and deserves recognition for its insights. Longer summary

Scott Alexander draws parallels between Predictive Processing (PP) and Perceptual Control Theory (PCT), suggesting that PCT anticipates many aspects of PP. He argues that both theories share the concept of cognitive 'layers' acting at various levels, with upper layers influencing lower layers to produce desired stimuli. Scott notes that PP offers a more refined explanation for higher-level cognitive processes compared to PCT's sometimes overly simplistic model. He concludes by comparing Will Powers, the originator of PCT, to ancient Greek atomists like Epicurus, suggesting that Powers' work deserves recognition for its prescient insights, even if it has been superseded by more advanced theories. Shorter summary

Scott Alexander reviews 'Surfing Uncertainty' by Andy Clark, exploring the predictive processing model of brain function and its wide-ranging explanatory power. Longer summary

Scott Alexander reviews the book 'Surfing Uncertainty' by Andy Clark, which explains the predictive processing model of how the brain works. This model posits that the brain is constantly making predictions about sensory input and updating its models based on prediction errors. Scott explores how this theory can explain various phenomena like attention, imagination, learning, motor behavior, and even psychiatric conditions like autism and schizophrenia. He finds the model compelling and potentially explanatory for a wide range of cognitive and perceptual processes. Shorter summary

The post explores how neurotypical social interactions often involve indirect communication, which can be confusing for autistic individuals, and suggests that conversations may be deliberately designed to be unpredictable. Longer summary

The post discusses the complexity of social interactions, particularly focusing on how neurotypical people often ask indirect questions to initiate conversations or join activities. It explains how this can lead to miscommunication with autistic individuals who may interpret these questions literally. The author explores the concept of 'plausible deniability' in social interactions, where people deliberately skirt the border of incomprehensibility to allow for graceful rejections. The post concludes by suggesting that ordinary conversations might be deliberately designed to be difficult to predict, making them particularly challenging for those who struggle with social cues. Shorter summary