Journal of Computational Neuroscience

Aims & Scope

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.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	2
2024	1.50

Journal Rank

Year	Value
2024	12760

Journal Citation Indicator

Year	Value
2024	138

SJR (SCImago Journal Rank)

Year	Value
2024	0.444

Quartile

Year	Value
2024	Q3

h-index

Year	Value
2024	85

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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
• Web of Science

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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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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.

• Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons

  Citation: 1482

  Authors: Nicolas

• Transfer entropy—a model-free measure of effective connectivity for the neurosciences

  Citation: 805

  Authors: Raul, Michael, Michael, Gordon

• When inhibition not excitation synchronizes neural firing

  Citation: 637

  Authors: Carl, L. F., G.

• Synchronous oscillations in neuronal systems: Mechanisms and functions

  Citation: 626

  Authors: Charles M.

• Effects of Neuromodulation in a Cortical Network Model of Object Working Memory Dominated by Recurrent Inhibition

  Citation: 580

  Authors: Nicolas, Xiao-Jing

• High Frequency Stimulation of the Subthalamic Nucleus Eliminates Pathological Thalamic Rhythmicity in a Computational Model

  Citation: 515

  Authors: Jonathan E., David

• Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism

  Citation: 474

  Authors: Alain, Zachary F., Terrence J.

• Intrinsic and network rhythmogenesis in a reduced traub model for CA3 neurons

  Citation: 454

  Authors: Paul F., John

• Vector reconstruction from firing rates

  Citation: 396

  Authors: Emilio, L. F.

• Synchronization and Oscillatory Dynamics in Heterogeneous, Mutually Inhibited Neurons

  Citation: 344

  Authors: John A., Carson C., Jason, Cristina, Nancy

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