ReviewCurrent opinion in neurobiology2015
Computational models in the age of large datasets.
Review in Current opinion in neurobiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
What it found
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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
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Co-expression of calcium and hERG potassium channels reduces the incidence of proarrhythmic events.Cardiovascular research · 2021Pooled it
- Correcting model error bias in estimations of neuronal dynamics from time series observations.Scientific reports · 2026Article
- Prediction of neural activity in connectome-constrained recurrent networks.Nature neuroscience · 2025Article
- Minding the gap between artificial and biological computing paradigms for biologically loyal AI.Frontiers in systems neuroscience · 2025Article
- Estimation of ionic currents and compensation mechanisms from recursive piecewise assimilation of electrophysiological data.Frontiers in computational neuroscience · 2025Article
- The Problem-Ladenness of Theory.Computational brain & behavior · 2024Article
- Flexible multitask computation in recurrent networks utilizes shared dynamical motifs.Nature neuroscience · 2024Article
- Prediction of neural activity in connectome-constrained recurrent networks.bioRxiv : the preprint server for biology · 2024Article
- Single shot detection of alterations across multiple ionic currents from assimilation of cell membrane dynamics.Scientific reports · 2024Article
- On the scope of scientific hypotheses.Royal Society open science · 2023Article
- Uncovering the organization of neural circuits with Generalized Phase Locking Analysis.PLoS computational biology · 2023Article
- On the Role of Theory and Modeling in Neuroscience.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Heterogeneous off-target impact of ion-channel deletion on intrinsic properties of hippocampal model neurons that self-regulate calcium.Frontiers in cellular neuroscience · 2023Article
- Information geometry for multiparameter models: new perspectives on the origin of simplicity.Reports on progress in physics. Physical Society (Great Britain) · 2022Review
- Energy-efficient network activity from disparate circuit parameters.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets.International journal of molecular sciences · 2022Review
- Reinforcement Learning for Central Pattern Generation in Dynamical Recurrent Neural Networks.Frontiers in computational neuroscience · 2022Article
- Interrogating theoretical models of neural computation with emergent property inference.eLife · 2021Article
- Theoretical principles for illuminating sensorimotor processing with brain-wide neuronal recordings.Current opinion in neurobiology · 2020Review
- Training deep neural density estimators to identify mechanistic models of neural dynamics.eLife · 2020Article
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
Abstract
Technological advances in experimental neuroscience are generating vast quantities of data, from the dynamics of single molecules to the structure and activity patterns of large networks of neurons. How do we make sense of these voluminous, complex, disparate and often incomplete data? How do we find general principles in the morass of detail? Computational models are invaluable and necessary in this task and yield insights that cannot otherwise be obtained. However, building and interpreting good computational models is a substantial challenge, especially so in the era of large datasets. Fitting detailed models to experimental data is difficult and often requires onerous assumptions, while more loosely constrained conceptual models that explore broad hypotheses and principles can yield more useful insights.
Indexed as
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What OpenQuestion 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 OpenQuestion graph.