更正：概率求解器能够直接探索神经科学模型中的数值不确定性。

IF 1.5 4区医学 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY

Journal of Computational Neuroscience Pub Date : 2022-08-01 DOI:10.1007/s10827-023-00856-w

Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, Philipp Berens

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Correction to: Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models.

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来源期刊

Journal of Computational Neuroscience 生物-神经科学

CiteScore

2.00

自引率

8.30%

发文量

审稿时长

3 months

期刊介绍： The Journal of Computational Neuroscience provides a forum for papers that fit the interface between computational and experimental work in the neurosciences. The Journal of Computational Neuroscience publishes full length original papers, rapid communications and review articles describing theoretical and experimental work relevant to computations in the brain and nervous system. Papers that combine theoretical and experimental work are especially encouraged. Primarily theoretical papers should deal with issues of obvious relevance to biological nervous systems. Experimental papers should have implications for the computational function of the nervous system, and may report results using any of a variety of approaches including anatomy, electrophysiology, biophysics, imaging, and molecular biology. Papers investigating the physiological mechanisms underlying pathologies of the nervous system, or papers that report novel technologies of interest to researchers in computational neuroscience, including advances in neural data analysis methods yielding insights into the function of the nervous system, are also welcomed (in this case, methodological papers should include an application of the new method, exemplifying the insights that it yields).It is anticipated that all levels of analysis from cognitive to cellular will be represented in the Journal of Computational Neuroscience.