The first account of psychopathy seems to be a short text from 1786 by the American physician Benjamin Rush who described a mysterious medical condition that he called anomia – and later moral derangement – where people allegedly lost the ability to distinguish between good and evil. Although his work is highly speculative, it sketched out the idea of ‘the psychopath’ in a way that could be passed on to a scientific audience: as a biological disorder so extreme that it impairs the innate human capacity for moral attitudes and prosocial behaviours.
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Predictive processing has been applied to understanding various mental disorders, such as schizophrenia, autism, and anxiety. For example, in schizophrenia, it is hypothesized that there might be an imbalance in the precision weighting of prediction errors, leading to aberrant predictions and perceptions (such as hallucinations). In autism, there might be an over-reliance on sensory input over predictions, leading to difficulties in processing complex or ambiguous stimuli.
The predictive processing framework has also influenced the field of artificial intelligence (AI), particularly in the development of models that mimic the brain’s predictive capabilities. By incorporating prediction error minimization and hierarchical inference, AI systems can be designed to learn and adapt more effectively, potentially leading to more advanced and human-like cognitive abilities.
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The neurophysiological evidence is incompatible with predictive coding theories. We argue that feedback from higher to lower brain areas tends to enhance the activity of the representation that is predicted, whereas stimuli that are repeated in time and space cause alterations in feedforward processing that reduce the neuronal responses. Only attended stimuli give rise to top-down predictions. These predictions can be matched to only one of the sensory stimuli at any one time.
Jacob A. Westerberg, Pieter R. Roelfsema
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Multilayer network analysis was applied to calculate the network switching rates between brain states. Compared to HCs, schizophrenia patients at baseline showed significantly increased network switching rates.
Ziyang Gao , Yuan Xiao , Fei Zhu , Bo Tao , Qiannan Zhao , Wei Yu , John A Sweeney , Qiyong Gong , Su Lui
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Xanomeline/trospium chloride (Cobenfy) is the first FDA-approved medication for schizophrenia that is not classified as an "antipsychotic" in the traditional sense. Unlike conventional antipsychotics that block dopamine D2 receptors, Cobenfy works through a novel mechanism by targeting muscarinic acetylcholine receptors (M1 and M4) in the brain, indirectly modulating dopamine release without direct D2 blockade.
prevent dopamine from binding
blunt signaling everywhere D2 exists
putting tape over the speaker
modulates the circuit that controls dopamine release
preserves normal D2 signaling capacity
reduces pathological overdrive
turning down the volume at the mixing board
More upstream, more nuanced.
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“Most notably, the World Health Organization twice compared schizophrenia outcomes in the rich countries of the world with outcomes in poor countries, and each time the patients in the poor countries—where drug usage was much less—were doing dramatically better at two‑year and five‑year follow‑ups. … In India, Nigeria and Colombia, where only 16% of patients were maintained continuously on neuroleptics, roughly two‑thirds were doing fairly well at the end of the follow‑up period … In the U.S. and other rich countries, where 61% of the patients were kept on antipsychotic drugs, the ratio of good‑to‑bad outcomes was almost precisely the reverse."
Whitaker: Anatomy of an Epidemic: Magic Bullets, Psychiatric Drugs, and the Astonishing Rise of Mental Illness in America (2010)
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