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A framework for streamlining research workflow in neuroscience and psychology

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A framework for streamlining research workflow in neuroscience and psychology

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Frontiers in Neuroinformatics [ 1662-5196 ] ; 2014.

RBID : PMC:3894454

Abstract

Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of scientific conduct. However, such principles are difficult to enact when researchers continue to resort on ad-hoc workflows and with poorly maintained code base. In this paper I examine the needs of neuroscience and psychology community, and introduce psychopy_ext, a unifying framework that seamlessly integrates popular experiment building, analysis and manuscript preparation tools by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows for automation of multiple tasks, such as generated user interfaces, unit testing, control analyses of stimuli, single-command access to descriptive statistics, and publication quality plotting. Taken together, psychopy_ext opens an exciting possibility for a faster, more robust code development and collaboration for researchers.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3894454

DOI: 10.3389/fninf.2013.00052
PubMed: 24478691
PubMed Central: 3894454

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<author><name sortKey="Kubilius, Jonas" sort="Kubilius, Jonas" uniqKey="Kubilius J" first="Jonas" last="Kubilius">Jonas Kubilius</name>
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<front><div type="abstract" xml:lang="en"><p>Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of scientific conduct. However, such principles are difficult to enact when researchers continue to resort on <italic>ad-hoc</italic>
 workflows and with poorly maintained code base. In this paper I examine the needs of neuroscience and psychology community, and introduce <italic>psychopy_ext</italic>
, a unifying framework that seamlessly integrates popular experiment building, analysis and manuscript preparation tools by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows for automation of multiple tasks, such as generated user interfaces, unit testing, control analyses of stimuli, single-command access to descriptive statistics, and publication quality plotting. Taken together, <italic>psychopy_ext</italic>
 opens an exciting possibility for a faster, more robust code development and collaboration for researchers.</p>
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<pmc article-type="review-article"><pmc-dir>properties open_access</pmc-dir>
  <front><journal-meta><journal-id journal-id-type="nlm-ta">Front Neuroinform</journal-id>
<journal-id journal-id-type="iso-abbrev">Front Neuroinform</journal-id>
<journal-id journal-id-type="publisher-id">Front. Neuroinform.</journal-id>
<journal-title-group><journal-title>Frontiers in Neuroinformatics</journal-title>
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<issn pub-type="epub">1662-5196</issn>
<publisher><publisher-name>Frontiers Media S.A.</publisher-name>
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<article-meta><article-id pub-id-type="pmid">24478691</article-id>
<article-id pub-id-type="pmc">3894454</article-id>
<article-id pub-id-type="doi">10.3389/fninf.2013.00052</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Neuroscience</subject>
<subj-group><subject>Methods Article</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>A framework for streamlining research workflow in neuroscience and psychology</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Kubilius</surname>
<given-names>Jonas</given-names>
</name>
<xref ref-type="author-notes" rid="fn001"><sup>*</sup>
</xref>
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</contrib-group>
<aff><institution>Laboratories of Biological and Experimental Psychology, Faculty of Psychology and Educational Sciences, KU Leuven</institution>
<country>Leuven, Belgium</country>
</aff>
<author-notes><fn fn-type="edited-by"><p>Edited by: Yaroslav O. Halchenko, Dartmouth College, USA</p>
</fn>
<fn fn-type="edited-by"><p>Reviewed by: Michael Hanke, Otto-von-Guericke University, Germany; Fernando Perez, University of California at Berkeley, USA</p>
</fn>
<corresp id="fn001">*Correspondence: Jonas Kubilius, Laboratory of Biological Psychology, Faculty of Psychology and Educational Sciences, KU Leuven, Tiensestraat 102 bus 3711, Leuven e-mail: <email xlink:type="simple">Jonas.Kubilius@ppw.kuleuven.be</email>
</corresp>
<fn fn-type="other" id="fn002"><p>This article was submitted to the journal Frontiers in Neuroinformatics.</p>
</fn>
</author-notes>
<pub-date pub-type="epub"><day>17</day>
<month>1</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="collection"><year>2013</year>
</pub-date>
<volume>7</volume>
<elocation-id>52</elocation-id>
<history><date date-type="received"><day>01</day>
<month>11</month>
<year>2013</year>
</date>
<date date-type="accepted"><day>30</day>
<month>12</month>
<year>2013</year>
</date>
</history>
<permissions><copyright-statement>Copyright © 2014 Kubilius.</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by/3.0/"><license-p>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) or licensor 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.</license-p>
</license>
</permissions>
<abstract><p>Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of scientific conduct. However, such principles are difficult to enact when researchers continue to resort on <italic>ad-hoc</italic>
 workflows and with poorly maintained code base. In this paper I examine the needs of neuroscience and psychology community, and introduce <italic>psychopy_ext</italic>
, a unifying framework that seamlessly integrates popular experiment building, analysis and manuscript preparation tools by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows for automation of multiple tasks, such as generated user interfaces, unit testing, control analyses of stimuli, single-command access to descriptive statistics, and publication quality plotting. Taken together, <italic>psychopy_ext</italic>
 opens an exciting possibility for a faster, more robust code development and collaboration for researchers.</p>
</abstract>
<kwd-group><kwd>python</kwd>
<kwd>neuroscience</kwd>
<kwd>vision</kwd>
<kwd>psychophysics</kwd>
<kwd>fMRI</kwd>
<kwd>MVPA</kwd>
<kwd>reproducibility</kwd>
<kwd>collaboration</kwd>
</kwd-group>
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<equation-count count="0"></equation-count>
<ref-count count="24"></ref-count>
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</article-meta>
</front>
</pmc>
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A framework for streamlining research workflow in neuroscience and psychology

A framework for streamlining research workflow in neuroscience and psychology

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