A thread through the archive
Essays tagged “neuroscience”. Follow an idea across the archive.
Scott Alexander explores different types of prediction markets, their uses, limitations, and ethical considerations in decision-making and information gathering.
Scott Alexander explores expert and reader comments on his post about motivated reasoning and reinforcement learning, discussing brain function, threat detection, and the implementation of complex behaviors.
Scott analyzes motivated reasoning as misapplied reinforcement learning, explaining how it might arise from the brain's mixture of reinforceable and non-reinforceable architectures.
Scott Alexander critiques a study claiming cash payments to poor mothers increased infant brain function, highlighting statistical and methodological issues that undermine its positive conclusions.
Scott explores the connection between the Dark Room Problem in neuroscience, meditative jhanas, and theories of beauty, suggesting that intense focus on regular stimuli can produce extreme bliss.
Scott Alexander discusses recent research unifying predictive coding in the brain with backpropagation in machine learning, exploring its implications for AI and neuroscience.
Scott Alexander examines the relationship between handedness, authoritarianism, and cognitive flexibility, finding unexpected results that contradict a recent study.
Scott Alexander proposes a Bayesian theory of willpower as a process of weighing evidence from different mental processes to determine actions.
Scott examines the relationship between sleep, synaptic homeostasis, and depression, exploring how sleep deprivation temporarily alleviates depression symptoms.
Scott Alexander critically examines a new theory on antidepressant mechanisms, expressing skepticism while acknowledging its potential significance if proven true.
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.
Scott Alexander explores the similarities between Wernicke's aphasia and GPT-3's language use, while noting that GPT-3's capabilities likely surpass this neurological comparison.
Scott reviews Julian Jaynes' controversial theory that ancient people lacked consciousness and instead heard hallucinated voices of gods, critiquing some aspects while finding value in the idea of theory of mind as culturally constructed.
Scott examines the bidirectional relationship between depression and sense of smell, exploring potential mechanisms and treatment implications.
Scott Alexander argues that psychiatric diagnoses, while imperfect, are useful tools despite potentially combining multiple conditions with different causes.
The post explores how emotional learning creates hard-to-update mental models, drawing parallels between psychotherapy, psychedelics, and rationality techniques in overcoming these 'mental mountains'.
Scott Alexander examines skeptical and supportive comments on claims of enlightenment, arguing that evidence for such states is comparable to other accepted mental phenomena.
Scott reviews a paper proposing that psychedelics work by relaxing priors in the brain, potentially treating mental illness but also risking side effects.
Scott Alexander explores a theory suggesting that complex features of human biology evolved as defenses against parasite manipulation, discussing its implications for understanding psychiatric medications and biological complexity.
Scott Alexander finds a correlation between animals' cortical neuron count and people's intuitive perception of their moral value, based on a small survey.
The post examines the relationship between neuron count and intelligence across species, challenging traditional brain size measures and exploring implications for AI development.
Scott Alexander argues that Free Energy/Predictive Coding and Perceptual Control Theory are fundamentally the same, and proposes using PCT's more intuitive terminology to help understand FE/PC.
Scott Alexander draws parallels between OpenAI's GPT-2 language model and human dreaming, exploring their similarities in process and output quality.
Scott Alexander presents a 'Grand Unified Chart' showing how different domains of knowledge share a similar structure in interpreting the world, arguing this is due to basic brain algorithms and effective epistemology.
The post explores the diametrical model of autism and schizophrenia, suggesting they represent opposite ends of a spectrum from mechanistic to mentalistic cognition.