• Record: found
  • Abstract: found
  • Article: found
Is Open Access

NeuroMatic: An Integrated Open-Source Software Toolkit for Acquisition, Analysis and Simulation of Electrophysiological Data

Read this article at

      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


      Acquisition, analysis and simulation of electrophysiological properties of the nervous system require multiple software packages. This makes it difficult to conserve experimental metadata and track the analysis performed. It also complicates certain experimental approaches such as online analysis. To address this, we developed NeuroMatic, an open-source software toolkit that performs data acquisition (episodic, continuous and triggered recordings), data analysis (spike rasters, spontaneous event detection, curve fitting, stationarity) and simulations (stochastic synaptic transmission, synaptic short-term plasticity, integrate-and-fire and Hodgkin-Huxley-like single-compartment models). The merging of a wide range of tools into a single package facilitates a more integrated style of research, from the development of online analysis functions during data acquisition, to the simulation of synaptic conductance trains during dynamic-clamp experiments. Moreover, NeuroMatic has the advantage of working within Igor Pro, a platform-independent environment that includes an extensive library of built-in functions, a history window for reviewing the user's workflow and the ability to produce publication-quality graphics. Since its original release, NeuroMatic has been used in a wide range of scientific studies and its user base has grown considerably. NeuroMatic version 3.0 can be found at and

      Related collections

      Most cited references 62

      • Record: found
      • Abstract: found
      • Article: not found

      The NEURON simulation environment.

      The moment-to-moment processing of information by the nervous system involves the propagation and interaction of electrical and chemical signals that are distributed in space and time. Biologically realistic modeling is needed to test hypotheses about the mechanisms that govern these signals and how nervous system function emerges from the operation of these mechanisms. The NEURON simulation program provides a powerful and flexible environment for implementing such models of individual neurons and small networks of neurons. It is particularly useful when membrane potential is nonuniform and membrane currents are complex. We present the basic ideas that would help informed users make the most efficient use of NEURON.
        • Record: found
        • Abstract: not found
        • Article: not found

        SCIENTIFIC STANDARDS. Promoting an open research culture.

          • Record: found
          • Abstract: not found
          • Article: not found

          A manifesto for reproducible science


            Author and article information

            Department of Neuroscience, Physiology and Pharmacology, University College London , London, United Kingdom
            Author notes

            Edited by: Daniel Gardner, Weill Cornell Medicine, Cornell University, United States

            Reviewed by: Michael Denker, Forschungszentrum Jülich, Germany; John J. Woodward, Medical University of South Carolina, United States

            *Correspondence: Jason S. Rothman j.rothman@
            Front Neuroinform
            Front Neuroinform
            Front. Neuroinform.
            Frontiers in Neuroinformatics
            Frontiers Media S.A.
            04 April 2018
            : 12
            Copyright © 2018 Rothman and Silver.

            This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

            Figures: 15, Tables: 0, Equations: 4, References: 63, Pages: 21, Words: 15785
            Funded by: Wellcome Trust 10.13039/100004440
            Award ID: 095667
            Award ID: 203048
            Award ID: 086699
            Funded by: European Research Council 10.13039/501100000781
            Award ID: 294667
            Funded by: Medical Research Council 10.13039/501100000265
            Award ID: G0400598
            Funded by: European Commission 10.13039/501100000780
            Award ID: LSHM-CT-2005-019055
            Technology Report


            Comment on this article