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Network Computation in Neural Systems Template

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About the Network Computation in Neural Systems format

Network Computation in Neural Systems is a peer-reviewed journal published by Taylor & Francis, covering Neural dynamics and brain function, Neural Networks and Applications, Visual perception and processing mechanisms.

PublisherTaylor & Francis
Reference styleAuthor–year (Chicago, T&F)
Author–year — (Smith, 2023) in the text
Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Network Computation in Neural Systems 12 (3): 45–58.

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Publishes research inNeural dynamics and brain function Neural Networks and Applications Visual perception and processing mechanisms Advanced Memory and Neural Computing stochastic dynamics and bifurcation
ISSN0954-898X
Citation impact (2-yr)3.6
h-index102
i10-index649
Total citations46,509
Top institutions publishing hereUniversity of Oxford
Journal websitewww.informahealthcare.com
You getA submission-ready PDF and the editable LaTeX source — ready to submit.

Papers published in Network Computation in Neural Systems per year

13
2014
5
2015
13
2016
4
2017
4
2018
7
2019
4
2020
5
2021
12
2022
24
2023
96
2024
40
2025

Citation impact of Network Computation in Neural Systems by publication year

89
2014
81
2015
188
2016
40
2017
23
2018
31
2019
45
2020
118
2021
96
2022
98
2023
403
2024
65
2025

Citations each year’s papers have accumulated so far — the most recent years are still building up.

Most-cited papers in Network Computation in Neural Systems

A review of methods for spike sorting: the detection and classification of neural action potentials

Michael S. Lewicki · 1 Jan 1998

The detection of neural spike activity is a technical challenge that is a prerequisite for studying many types of brain function. Measuring the activity of individual neurons accurately can be difficult due to large amounts of background noise and the difficulty in distinguishing the action potentials of one neuron from those of others in the…

1,256 citations Cite SaveGo to paper →
The statistics of natural images

Daniel Ruderman · 1 Jan 1994

AbstracL Recently there has been a resurgence of interest in the properties of natural images. Their statistics are important not only in image compression but also far the study of sensory processing in biology, which can be viewed as satisfying cettain ‘design criteria’. This review summarizes previous work on image statistics and presents our own…

887 citations Cite SaveGo to paper →
A simple white noise analysis of neuronal light responses

E. J. Chichilnisky · 1 Jan 2001

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes…

851 citations Cite SaveGo to paper →
Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks

David Mackay · 1 Jan 1995

Bayesian probability theory provides a unifying framework for data modelling. In this framework the overall aims are to find models that are well-matched to the data, and to use these models to make optimal predictions. Neural network learning is interpreted as an inference of the most probable parameters for the model, given the training data.…

847 citations Cite SaveGo to paper →
Statistics of natural image categories

Antonio Torralba, Aude Oliva · 1 Jan 2003

In this paper we study the statistical properties of natural images belonging to different categories and their relevance for scene and object categorization tasks. We discuss how second-order statistics are correlated with image categories, scene scale and objects. We propose how scene categorization could be computed in a feedforward manner in order to provide top-down…

798 citations Cite SaveGo to paper →

Network Computation in Neural Systems template — frequently asked questions

How do I write a paper in the Network Computation in Neural Systems format?
In DocuGuru you write your manuscript in a normal editor — no LaTeX setup required — and select the Network Computation in Neural Systems template. When you export, DocuGuru compiles the paper into the official Taylor & Francis format and hands you a submission-ready PDF along with the editable LaTeX source.
What reference style does Network Computation in Neural Systems use?
Network Computation in Neural Systems uses Author–year (Chicago, T&F) references, shown as author–year markers such as (Smith, 2023) in the text. DocuGuru formats every in-text citation and the reference list in this exact style automatically. A reference appears like this: Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Network Computation in Neural Systems 12 (3): 45–58.
Do I need to know LaTeX to submit to Network Computation in Neural Systems?
No. DocuGuru generates the interact LaTeX class and compiles the PDF for you in the background, so you get a Taylor & Francis-ready Network Computation in Neural Systems document without writing any LaTeX. If you do want it, the LaTeX source is included in the export.
Can I import an existing draft into the Network Computation in Neural Systems template?
Yes. Paste or upload your current manuscript — Word, LaTeX, Markdown, or plain text — and DocuGuru reflows it into the Network Computation in Neural Systems format with correct headings, figures, tables, and author–year citations.
Who publishes Network Computation in Neural Systems?
Network Computation in Neural Systems is a multidisciplinary journal published by Taylor & Francis. DocuGuru's Network Computation in Neural Systems template matches Taylor & Francis's official submission format.
Can I export a submission-ready Network Computation in Neural Systems PDF?
Yes — DocuGuru produces a PDF built with the official Network Computation in Neural Systems template (the interact class) that is ready to submit to Taylor & Francis, together with the matching LaTeX source files.
How much does the Network Computation in Neural Systems template cost?
You can start writing in the Network Computation in Neural Systems template for free. Exporting the final submission-ready Network Computation in Neural Systems PDF and LaTeX source is part of DocuGuru's paid plans — see the app for current pricing.
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