Evidence and implications of abnormal predictive coding in dementia
Ece Kocagoncu, Anastasia Klimovich-Gray, Laura E Hughes, James B Rowe

TL;DR
This review proposes that abnormal predictive coding in hierarchical neural networks underpins diverse cognitive deficits in dementia, offering a unified framework that links various symptoms and guides future research and therapy.
Contribution
It introduces a predictive coding framework to explain neurodegenerative dementia symptoms, moving beyond traditional localized brain region theories.
Findings
Predictive coding impairments can explain diverse dementia symptoms.
Behavioral and neurophysiological evidence supports the model.
Framework links cognitive and movement disorders.
Abstract
The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasises convergent critical features of pathophysiology, rather than the loss of memory centres or language centres, or singular neurotransmitter systems. Cognitive deficits are interpreted in the light of advances in normative accounts of brain function, based on predictive coding in hierarchical neural networks. The predicting coding rests on Bayesian integration of beliefs and sensory evidence, with hierarchical predictions and prediction errors, for memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, in neurodegenerative dementias. The review…
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