Errors or Adaptations? A Critical Review of Predictive Processing in Psychiatry
Behavioral Sciences July 3, 2026 DOI: 10.3390/bs16071116 via OpenAlex
Summary
AI-generated from the abstractPredictive processing (PP) accounts often characterize mental illness as maladaptive and epistemically distorting due to mismatches between brain-generated top-down models and bottom-up sensory inputs, but this review identifies exceptions. Hypervigilance in trauma survivors with PTSD or depression may sustain desirable gaps between anticipated problems and actual harms. Depressive slowdowns can be adaptive when physiological problems make activity strenuous. PP researchers introduce tacit normative assumptions, such as stipulating thresholds for predictive model specificity in autism and ADHD, and presupposing Western concepts of self as neurocognitive ideals in schizophrenia interpretations. PP accounts of prediction error can tacitly invoke veridical representation despite claims that cognition evolved for action, not truth-seeking. Greater attention to these exceptions and cultural variability may strengthen the framework's capacity to understand and treat psychiatric conditions.
Study at a glance
| Characteristics | Review Peer reviewed |
|---|---|
| Keywords | Neurocognitive Normative Hypervigilance Schizophrenia object-oriented programming Cognition |
| Key finding | Predictive processing accounts of mental illness often impose normative assumptions and overlook adaptive exceptions, such as hypervigilance in PTSD and depressive slowdowns, but attending to these factors may improve the framework. |
Abstract
Predictive processing (PP) accounts often characterize mental illness as maladaptive and epistemically distorting due to mismatches between brain-generated top-down models and bottom-up sensory inputs, with this review identifying exceptions. First, hypervigilance in trauma survivors with PTSD or depression may sustain desirable gaps between anticipated problems and actual harms that would otherwise occur. Second, PP defenders have argued that depressive slowdowns follow from maladaptive brain-based regulatory models, yet physiological problems may make activity strenuous—in which case slowing down is adaptive. Third, PP researchers introduce tacit normative assumptions. For example, in autism and ADHD, they stipulate thresholds for how specific (hence error-prone) predictive models should be, and PP interpretations of schizophrenia sometimes presuppose Western concepts of self as normative neurocognitive ideals. Fourth, PP accounts of prediction error can tacitly invoke veridical representation, even though advocates regularly claim that cognition evolved primarily for action, not truth-seeking. While criticizing PP for its overreaches, this review also explores how greater attention to these exceptions and factors such as cultural variability may strengthen the framework’s capacity to understand and contribute to the treatment of a range of psychiatric conditions.