Evidence and implications of abnormal predictive coding in dementia

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 presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The re-formulation of cognitive deficits in dementia in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework, such as linking cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding model may therefore also inform future therapeutic strategies.