Maladaptive Precision: A Channel-Specific Predictive-Processing Framework for the Neurodevelopmental Consequences of Early Life Adversity
Abstract
Early life adversity (ELA) is proposed here to bias precision weighting in specific information channels—up-weighting potential threat and predictable, low-salience input while down-weighting evidence that disconfirms expectations of danger—rather than altering a single global gain. This channel-specific claim distinguishes ELA-related dysregulation from the global precision accounts proposed for autism and is the review’s central, deliberately parsimonious hypothesis. We synthesize two research traditions, predictive processing (PP) and the developmental impact of ELA, treating the brain as a hierarchical inference engine whose precision estimates are calibrated by early experience. We specify the claim in two ways. First, a mapping table links dimensions of early experience—threat, deprivation, environmental unpredictability, rigid invariance, prenatal maternal distress, and supportive caregiving—to predicted precision changes, developmental windows, measurable indices, and observations that would count against each prediction. Second, we propose the anterior cingulate cortex, embedded within macroscale functional gradients, as a key mechanistic locus, arguing that apparently contradictory findings (threat-related hyper-reactivity alongside reduced expected-value and reward-prediction-error encoding) reflect a single biased allocation of gain across channels under a limited precision budget. As a stronger, optional hypothesis, sustained adversity may entrench these biases as maladaptive generative models (priors); much of the developmental data can be accommodated by altered precision alone. The framework is held to a symmetry constraint—supportive input calibrates the same machinery and is predicted to confer faster precision re-tuning, not merely a mirror image of adversity—and yields discriminating, falsifiable predictions. A companion paper (Van den Bergh & Frasch, under review) applies the framework to eleven publications across two prenatal-anxiety cohorts spanning infancy to adulthood; it provides compatibility with, not independent corroboration of, the framework.
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BibTeX
@misc{frasch2026maladaptive,
title = {{Maladaptive Precision: A Channel-Specific Predictive-Processing Framework for the Neurodevelopmental Consequences of Early Life Adversity}},
author = {Martin Gerbert Frasch and Bea Van den Bergh},
howpublished = {PsyArXiv},
year = {2026},
month = sep,
doi = {10.31234/osf.io/zj4bf_v1},
url = {https://osf.io/preprints/psyarxiv/zj4bf_v1/},
note = {CC0},
}
RIS
TY - UNPB
TI - Maladaptive Precision: A Channel-Specific Predictive-Processing Framework for the Neurodevelopmental Consequences of Early Life Adversity
AU - Martin Gerbert Frasch
AU - Bea Van den Bergh
PY - 2026
DA - 2026/09/09
PB - PsyArXiv
DO - 10.31234/osf.io/zj4bf_v1
UR - https://osf.io/preprints/psyarxiv/zj4bf_v1/
AB - Early life adversity (ELA) is proposed here to bias precision weighting in specific information channels—up-weighting potential threat and predictable, low-salience input while down-weighting evidence that disconfirms expectations of danger—rather than altering a single global gain. This channel-specific claim distinguishes ELA-related dysregulation from the global precision accounts proposed for autism and is the review’s central, deliberately parsimonious hypothesis. We synthesize two research traditions, predictive processing (PP) and the developmental impact of ELA, treating the brain as a hierarchical inference engine whose precision estimates are calibrated by early experience. We specify the claim in two ways. First, a mapping table links dimensions of early experience—threat, deprivation, environmental unpredictability, rigid invariance, prenatal maternal distress, and supportive caregiving—to predicted precision changes, developmental windows, measurable indices, and observations that would count against each prediction. Second, we propose the anterior cingulate cortex, embedded within macroscale functional gradients, as a key mechanistic locus, arguing that apparently contradictory findings (threat-related hyper-reactivity alongside reduced expected-value and reward-prediction-error encoding) reflect a single biased allocation of gain across channels under a limited precision budget. As a stronger, optional hypothesis, sustained adversity may entrench these biases as maladaptive generative models (priors); much of the developmental data can be accommodated by altered precision alone. The framework is held to a symmetry constraint—supportive input calibrates the same machinery and is predicted to confer faster precision re-tuning, not merely a mirror image of adversity—and yields discriminating, falsifiable predictions. A companion paper (Van den Bergh & Frasch, under review) applies the framework to eleven publications across two prenatal-anxiety cohorts spanning infancy to adulthood; it provides compatibility with, not independent corroboration of, the framework.
ER -