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

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          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

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          Most cited references 62

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          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.
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            A manifesto for reproducible science

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              SCIENTIFIC STANDARDS. Promoting an open research culture.


                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


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