1 Ocak 2022 Dergi makalesi Açık Erişim

Argunsah, Ali Ozgur; Erdil, Ertunc; Ghani, Muhammad Usman; Ramiro-Cortes, Yazmin; Hobbiss, Anna F.; Karayannis, Theofanis; Cetin, Mujdat; Israely, Inbal; Unay, Devrim

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  <identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/261197</identifier>
  <creators>
    <creator>
      <creatorName>Argunsah, Ali Ozgur</creatorName>
      <givenName>Ali Ozgur</givenName>
      <familyName>Argunsah</familyName>
    </creator>
    <creator>
      <creatorName>Erdil, Ertunc</creatorName>
      <givenName>Ertunc</givenName>
      <familyName>Erdil</familyName>
      <affiliation>Swiss Fed Inst Technol, Comp Vis Lab, Zurich, Switzerland</affiliation>
    </creator>
    <creator>
      <creatorName>Ghani, Muhammad Usman</creatorName>
      <givenName>Muhammad Usman</givenName>
      <familyName>Ghani</familyName>
      <affiliation>Boston Univ, Dept Elect &amp; Comp Engn, Boston, MA 02215 USA</affiliation>
    </creator>
    <creator>
      <creatorName>Ramiro-Cortes, Yazmin</creatorName>
      <givenName>Yazmin</givenName>
      <familyName>Ramiro-Cortes</familyName>
    </creator>
    <creator>
      <creatorName>Hobbiss, Anna F.</creatorName>
      <givenName>Anna F.</givenName>
      <familyName>Hobbiss</familyName>
      <affiliation>Champalimaud Ctr Unknown, Champalimaud Res, P-1400038 Lisbon, Portugal</affiliation>
    </creator>
    <creator>
      <creatorName>Karayannis, Theofanis</creatorName>
      <givenName>Theofanis</givenName>
      <familyName>Karayannis</familyName>
    </creator>
    <creator>
      <creatorName>Cetin, Mujdat</creatorName>
      <givenName>Mujdat</givenName>
      <familyName>Cetin</familyName>
      <affiliation>Univ Rochester, Goergen Inst Data Sci, Dept Elect &amp; Comp Engn, Rochester, NY 14627 USA</affiliation>
    </creator>
    <creator>
      <creatorName>Israely, Inbal</creatorName>
      <givenName>Inbal</givenName>
      <familyName>Israely</familyName>
    </creator>
    <creator>
      <creatorName>Unay, Devrim</creatorName>
      <givenName>Devrim</givenName>
      <familyName>Unay</familyName>
    </creator>
  </creators>
  <titles>
    <title>An Interactive Time Series Image Analysis Software For Dendritic Spines</title>
  </titles>
  <publisher>Aperta</publisher>
  <publicationYear>2022</publicationYear>
  <dates>
    <date dateType="Issued">2022-01-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Journal article</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/261197</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1038/s41598-022-16137-y</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">Live fluorescence imaging has demonstrated the dynamic nature of dendritic spines, with changes in shape occurring both during development and in response to activity. The structure of a dendritic spine correlates with its functional efficacy. Learning and memory studies have shown that a great deal of the information stored by a neuron is contained in the synapses. High precision tracking of synaptic structures can give hints about the dynamic nature of memory and help us understand how memories evolve both in biological and artificial neural networks. Experiments that aim to investigate the dynamics behind the structural changes of dendritic spines require the collection and analysis of large time-series datasets. In this paper, we present an open-source software called SpineS for automatic longitudinal structural analysis of dendritic spines with additional features for manual intervention to ensure optimal analysis. We have tested the algorithm on in-vitro, in-vivo, and simulated datasets to demonstrate its performance in a wide range of possible experimental scenarios.</description>
  </descriptions>
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