Biological deep learning for simulating the role of SST Interneurons in cognitive resilience

Our findings suggest that SST interneuron loss has a disproportionately large impact on cognitive function, both in artificial and biological systems. The model predicts that this is due to the key role that SST interneurons play in propagating task-error signals throughout the cortex. These results not only support the hypothesis that SST interneurons play a critical role in cognitive resilience, but also provide deeper insight into Alzheimer's disease by linking cortical circuit physiology to cognitive dysfunction. References Gabitto, M. I. et al. Nature Neuroscience (2024). Mathys, H. et al. Cell (2023). Morgan, G. R. & Carlyle, B. C. Scientific Reports (2024). Greedy, W. et al. Advances in neural information processing systems (2022).

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Publication Details

Journal
Alzheimer s & Dementia
Published
2025-12-01
DOI
https://doi.org/10.1002/alz70861_108740
Primary Topic
Amyotrophic Lateral Sclerosis Research
Type
article
Field-Weighted Citation Impact
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article

Biological deep learning for simulating the role of SST Interneurons in cognitive resilience

Becky C. Carlyle, Will Greedy, Rui Ponte Costa, Iris Marmouset‐De La Taille et al.
Alzheimer s & Dementia
Amyotrophic Lateral Sclerosis Research
article

Biological deep learning for simulating the role of SST Interneurons in cognitive resilience

Becky C. Carlyle, Will Greedy, Rui Ponte Costa, Iris Marmouset‐De La Taille, Benjamin Federico Elias Duisberg
article en

Abstract

Our findings suggest that SST interneuron loss has a disproportionately large impact on cognitive function, both in artificial and biological systems. The model predicts that this is due to the key role that SST interneurons play in propagating task-error signals throughout the cortex. These results not only support the hypothesis that SST interneurons play a critical role in cognitive resilience, but also provide deeper insight into Alzheimer's disease by linking cortical circuit physiology to cognitive dysfunction. References Gabitto, M. I. et al. Nature Neuroscience (2024). Mathys, H. et al. Cell (2023). Morgan, G. R. & Carlyle, B. C. Scientific Reports (2024). Greedy, W. et al. Advances in neural information processing systems (2022).

Alzheimer s & DementiaVol. 21(S7)
At Bristol (GB), University of Bristol (GB), University of Oxford (GB)
Openalex Percentile: Top 32%
Amyotrophic Lateral Sclerosis Research
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