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            <title xml:lang="en">Distinct inhibitory connectivity motifs could trigger distinct forms of anticipation in the retinal network</title>
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                <forename type="first">Simone</forename>
                <surname>Ebert</surname>
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              <persName>
                <forename type="first">Bruno</forename>
                <surname>Cessac</surname>
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              <email type="md5">1ac24872745bca873456704b40e3f1fd</email>
              <email type="domain">inria.fr</email>
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                <forename>Bruno</forename>
                <surname>Cessac</surname>
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            <funder>This work was supported by the French government through the UCAJEDI project managed by theNational Research Agency (ANR-15- IDEX-01) and, in particular, by the interdisciplinary Institute for Modeling in Neuroscience and Cognition (NeuroMod) of Université Côte d’Azur, which funded S.E. PhD. It was also partially supported by the \href{https://team.inria.fr/biovision/esthetics-exploring-the-functional-structure-of-the-retina-with-closed-loop-stimulation-a-physiological-and-computational-approach/}{ESTHETICS} project - receiving funding from the French government, managed by the National Research Agency under the France 2030 Investment Plan, as part of the Côte d'Azur University Initiative of Excellence, reference ANR-15-IDEX-0001 - and by the Inria associated team \href{https://team.inria.fr/biovision/fusion-functional-structure-of-the-retina-a-physiological-and-computational-approach/}{Fusion}.This work has also been funded by the ERC grant (No 101045253, DEEPRETINA) to Olivier Marre and ERC grant (No 101039115, NextMechMod) to Phillip Berens.</funder>
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            <idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno>
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            <idno type="stamp" n="UNIV-COTEDAZUR">Université Côte d'Azur</idno>
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                <title xml:lang="en">Distinct inhibitory connectivity motifs could trigger distinct forms of anticipation in the retinal network</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Simone</forename>
                    <surname>Ebert</surname>
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                <author role="aut">
                  <persName>
                    <forename type="first">Bruno</forename>
                    <surname>Cessac</surname>
                  </persName>
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                  <email type="domain">inria.fr</email>
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                  <idno type="idhal" notation="numeric">9425</idno>
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                <title level="j">Scientific Reports</title>
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                  <publisher>Nature Publishing Group</publisher>
                  <date type="datePub" subtype="inPress">2026</date>
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              <p>Motion is an important feature of visual scenes and retinal neuronal circuits selectively signal different motion features. It has been shown that the retina can extrapolate the position of a moving object, thereby compensating sensory transmission delays and enabling  signal processing in real-time. Amacrine cells, the inhibitory interneurons of the retina, play essential roles in such computations although their precise function remain unclear. Here, we computationally explore the potential effects of two different inhibitory connectivity motifs on the retina's response to moving objects, in a simplified model of the retina: feed-forward and recurrent feed-back inhibition. In this model, both motifs can account for motion anticipation, with two different mechanisms. Feed-forward inhibition truncates motion responses and shifts peak responses forward via subtractive inhibition, whereas recurrent feed-back coupling evokes excitatory and inhibitory waves with different phases that interfere and shift the response peak. A key difference between the two mechanisms is how the anticipatory peak shift scales with the speed of a moving object. Motion prediction with feed-forward circuits monotonically decreases with increasing speeds, while recurrent feed-back coupling induces tuning curves that exhibit a preferred speed for which motion prediction is maximal.</p>
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          <orgName>Hertie Institute for AI in Brain Health, University of Tuebingen</orgName>
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              <country key="DE"/>
            </address>
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          <idno type="RNSR">201622040S</idno>
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          <orgName>Biologically plausible Integrative mOdels of the Visual system : towards synergIstic Solutions for visually-Impaired people and artificial visiON</orgName>
          <orgName type="acronym">BIOVISION</orgName>
          <date type="start">2016-01-01</date>
          <date type="end">2027-12-31</date>
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            <address>
              <addrLine>2004 route des LuciolesBP 9306902 Sophia Antipolis</addrLine>
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            </address>
            <ref type="url">http://www.inria.fr/equipes/biovision</ref>
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              <addrLine>2004 route des Lucioles BP 93 06902 Sophia Antipolis</addrLine>
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              <addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine>
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          <desc>A perturbative approach to model retinal processing of natural scenes</desc>
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          <idno type="call">ERC-2021-STG</idno>
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          <desc>Next generation mechanistic models of retinal interneurons</desc>
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