ReviewOpen biology2022
Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons.
Review in Open biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- The exact mathematical form of the Pareto principle.Theory in biosciences = Theorie in den Biowissenschaften · 2026Article
- Neuronal excitability and parameter variability in the Hodgkin-Huxley model.PLoS computational biology · 2026Article
- Morphological details contribute to neuronal response variability within the same cell type.Frontiers in cellular neuroscience · 2026Article
- JAXLEY: differentiable simulation enables large-scale training of detailed biophysical models of neural dynamics.Nature methods · 2025Article
- Fundamental Trade-Offs in the Robustness of Biological Systems with Feedback Regulation.ACS synthetic biology · 2025Article
- The emergence of nonlinear evolutionary trade-offs and the maintenance of genetic polymorphisms.Biology letters · 2024Article
- Tetrapod sperm length evolution in relation to body mass is shaped by multiple trade-offs.Nature communications · 2024Article
- The Emergence of Non-Linear Evolutionary Trade-offs and the Maintenance of Genetic Polymorphisms.bioRxiv : the preprint server for biology · 2024Article
- Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus.PLoS computational biology · 2024Article
- Controlling morpho-electrophysiological variability of neurons with detailed biophysical models.iScience · 2023Article
- Biological complexity facilitates tuning of the neuronal parameter space.PLoS computational biology · 2023Article
- Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair.Communications biology · 2023Review
- Homeostatic regulation of neuronal function: importance of degeneracy and pleiotropy.Frontiers in cellular neuroscience · 2023Review
- Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium.Frontiers in cellular neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.