Journal of Mathematical Neuroscience

Aims & Scope

The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions.

The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition.

The aim is to publish work that uses advanced mathematical techniques to illuminate these questions.

It publishes full length original papers, rapid communications and review articles.

Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged.

Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.

View Aims & Scope

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Metrics & Ranking

SJR (SCImago Journal Rank)

Year	Value
2024	0.474

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	24

Journal Rank

Year	Value
2024	12125

Journal Citation Indicator

Year	Value
2024	20

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Neuroscience, designed to support cutting-edge academic discovery.

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Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Mathematical Frameworks for Oscillatory Network Dynamics in Neuroscience

  Citation: 229

  Authors: Peter, Stephen, Rachel

• Understanding the dynamics of biological and neural oscillator networks through exact mean-field reductions: a review

  Citation: 224

  Authors: Christian, Marc, Carlo R., Erik A.

• Mean-field description and propagation of chaos in networks of Hodgkin-Huxley and FitzHugh-Nagumo neurons

  Citation: 138

  Authors: Javier, Diego, Olivier, Jonathan

• Wilson–Cowan Equations for Neocortical Dynamics

  Citation: 111

  Authors: Jack D., Jeremy, Wim

• A phenomenological model of seizure initiation suggests network structure may explain seizure frequency in idiopathic generalised epilepsy

  Citation: 89

  Authors: Oscar, Thomas HB, Peter, Krasimira, Fahmida, Mark P, John R

• Phase-Amplitude Descriptions of Neural Oscillator Models

  Citation: 80

  Authors: Kyle CA, Kevin K, Ruediger, Stephen

• Fast–Slow Bursters in the Unfolding of a High Codimension Singularity and the Ultra-slow Transitions of Classes

  Citation: 75

  Authors: Maria Luisa, Andreas, Christophe, Viktor K.

• Parameter-sweeping techniques for temporal dynamics of neuronal systems: case study of Hindmarsh-Rose model

  Citation: 75

  Authors: Roberto, Andrey

• Path Integral Methods for Stochastic Differential Equations

  Citation: 71

  Authors: Carson C., Michael A.

• Analysis of Nonlinear Noisy Integrate&Fire Neuron Models: blow-up and steady states

  Citation: 68

  Authors: María J, José A, Benoît

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