The Journal of Computational Neuroscience focuses on understanding brain function at the level of neurons and circuits via computational and model-based approaches that are tied to biology and are experimentally testable.
This is a transformative journal, you may have access to funding.
We are showcasing the top articles from Journal of Computational Neuroscience, published in 2020 and 2021. This collection features the highlights of the latest academic research. We hope you enjoy your free reading!
To provide a forum for authors to present new ideas, comment on published material, or re-interpret data, a new article type was set up at this journal: “Perspective”. Articles should be brief and timely, and of wide interest to the computational neuroscience community.
The manuscript should not exceed 3000 words and 1 figure or table, and it should not report any new data, but could re-analyze existing data or propose a new interpretation of published data. A fast publication is expected.
Read the Editors-in-Chief’s Editorial on “Perspectives”.
Submit your paper here.
In this paper, the authors present a novel approach to understanding the organization of spinal circuitry. Rather than taking the viewpoint that the circuitry is hardwired, they consider models in which spinal synaptic organization is learned from descending control signals.
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