<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>30374</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>22</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>articler</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-24</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Beyond Scalar Timing Theory: Integrating Neural Oscillators with Computational Accessibility in Memory</title>
    <abstract language="eng">One of the major challenges for computational models of timing and time perception is to identify a neurobiological plausible implementation that predicts various behavioral properties, including the scalar property and retrospective timing. The available timing models primarily focus on the scalar property and prospective timing, while virtually ignoring the computational accessibility. Here, we first selectively review timing models based on ramping activity, oscillatory pattern, and time cells, and discuss potential challenges for the existing models. We then propose a multifrequency oscilla- tory model that offers computational accessibility, which could account for a much broader range of timing features, including both retrospective and prospective timing.</abstract>
    <parentTitle language="eng">Timing &amp; Time Perception</parentTitle>
    <identifier type="doi">10.1163/22134468-bja10059</identifier>
    <identifier type="issn">2213-4468</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">2 Gesundheit und Lifes Sciences / Health and Life Sciences</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Zhuanghua</firstName>
      <lastName>Shi</lastName>
    </author>
    <submitter>
      <firstName>Stefan</firstName>
      <lastName>Glasauer</lastName>
    </submitter>
    <author>
      <firstName>Bon-Mi</firstName>
      <lastName>Gu</lastName>
    </author>
    <author>
      <firstName>Stefan</firstName>
      <lastName>Glasauer</lastName>
    </author>
    <author>
      <firstName>Warren H.</firstName>
      <lastName>Meck</lastName>
    </author>
    <collection role="institutes" number="1403">FG Computational Neuroscience</collection>
  </doc>
</export-example>
