Hippocampal granule cells balance energy and function along the Pareto optimal front
- 1ICAR3R Interdisciplinary Centre for 3Rs in Animal Research, Justus-Liebig-University Giessen, 35390 Giessen, Germany
Abstract
The dentate gyrus' principal neuron, the granule cell (GC), plays a key role in pattern separation, transforming similar inputs into dissimilar outputs. We used a new measure based on information theory to evaluate this transformation in an experimentally derived in silico GC model with realistic ion channel distributions across its dendrites. We found that model performance aligned well with current-clamp recordings from mouse brain slices. However, it was also possible to find artificial parameter combinations in the model that functionally outperformed the recorded cells while matching their action potential shapes. Rather than maximising computational power, the biologically realistic GC model balanced energy efficiency against increased functionality in a Pareto optimal way: No possible parameter combination was found to improve one of the objectives without impairing the other. Interestingly, immature GCs adopted a different weighted trade-off with a stronger emphasis on energy efficiency than pattern separation, but they remained Pareto optimal over their putative developmental trajectory. Our results support the idea that evolution favours neurons that can satisfy functional and energetic demands simultaneously.
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BibTeX
@misc{mittag2026hippocampal,
title = {{Hippocampal granule cells balance energy and function along the Pareto optimal front}},
author = {M. Mittag and A. D. Bird and L. A. Mongiat and A. Roth and H. Cuntz and P. Jedlicka},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.29.755037},
url = {https://www.biorxiv.org/content/10.64898/2026.09.29.755037v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Hippocampal granule cells balance energy and function along the Pareto optimal front
AU - M. Mittag
AU - A. D. Bird
AU - L. A. Mongiat
AU - A. Roth
AU - H. Cuntz
AU - P. Jedlicka
PY - 2026
DA - 2026/09/29
PB - bioRxiv
DO - 10.64898/2026.09.29.755037
UR - https://www.biorxiv.org/content/10.64898/2026.09.29.755037v1
AB - The dentate gyrus' principal neuron, the granule cell (GC), plays a key role in pattern separation, transforming similar inputs into dissimilar outputs. We used a new measure based on information theory to evaluate this transformation in an experimentally derived in silico GC model with realistic ion channel distributions across its dendrites. We found that model performance aligned well with current-clamp recordings from mouse brain slices. However, it was also possible to find artificial parameter combinations in the model that functionally outperformed the recorded cells while matching their action potential shapes. Rather than maximising computational power, the biologically realistic GC model balanced energy efficiency against increased functionality in a Pareto optimal way: No possible parameter combination was found to improve one of the objectives without impairing the other. Interestingly, immature GCs adopted a different weighted trade-off with a stronger emphasis on energy efficiency than pattern separation, but they remained Pareto optimal over their putative developmental trajectory. Our results support the idea that evolution favours neurons that can satisfy functional and energetic demands simultaneously.
ER -