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Evidence and implications of abnormal predictive coding in dementia
Kocagoncu E, Klimovich-Gray A, Hughes LE, Rowe JB.. Brain : a journal of neurology, 2021-12-01
Topic: Risk, prevention and care in population studies
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 emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of 'memory centres' or 'language centres', or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns 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 framework may therefore also inform future therapeutic strategies.
Key findings
- The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease.
Why it matters
This review proposes that cognitive deficits in dementias can be understood as aberrant predictive coding in hierarchical neural networks. It is a theoretical framework based on behavioural and neurophysiological studies, not a treatment or prevention finding.
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Study details
- Evidence strengthLow
How this study scored 50/100
Published in a leading specialty journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, so that was left out: it earned 48 of the 96 points we could judge it on, which is 50 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 9 / 10 | Tier 2 — leading specialty journal (Brain : a journal of neurology) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 3 / 5 | 2021 — within 6 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 57 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 8.1 citations a year over 7 year(s) since 2021 |
| Impact for its field and year | 3 / 6 | Cited 5.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 2 / 4 | Cited 32 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author James Benedict Rowe: h-index 101 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of Cambridge: institution h-index 1,973 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 34240109) |
| Free to read | 2 / 2 | Free to read |
| Points | 48 / 96 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 48 of the 96 points we could judge it on is 50 out of 100. |
| Total | 50 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Kocagoncu, E., Klimovich-Gray, A., Hughes, L. E., & Rowe, J. B. (2021). Evidence and implications of abnormal predictive coding in dementia. Brain : a journal of neurology. https://doi.org/10.1093/brain/awab254
Vancouver
Kocagoncu E, Klimovich-Gray A, Hughes LE, Rowe JB. Evidence and implications of abnormal predictive coding in dementia. Brain : a journal of neurology. 2021. doi:10.1093/brain/awab254. PMID: 34240109.
BibTeX
@article{kocagoncu2021-34240109,
author = {Kocagoncu, E. and Klimovich-Gray, A. and Hughes, L. E. and Rowe, J. B.},
title = {{Evidence and implications of abnormal predictive coding in dementia}},
journal = {Brain : a journal of neurology},
year = {2021},
doi = {10.1093/brain/awab254},
pmid = {34240109},
url = {https://doi.org/10.1093/brain/awab254}
}
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