<div dir="ltr"><div class="gmail_quote"><div dir="ltr"><div><br></div><div><p class="MsoNormal" align="center" style="text-align:center"><b><u><span lang="ES" style="font-family:arial,sans-serif">SEMINARIOS  DEL
IFLP y DEL DEPARTAMENTO</span></u></b></p>

<p class="MsoNormal" align="center" style="text-align:center"><b><u><span style="font-family:arial,sans-serif">MARTES 2 de MAYO – 10:30 hs<span></span></span></u></b></p>

<p class="MsoNormal" align="center" style="text-align:center"><b><u><span lang="EN-US" style="font-family:arial,sans-serif">AULA CHICA<span></span></span></u></b></p>

<p class="MsoNormal" style="text-align:justify"><br></p>

<p class="MsoNormal"><b><u><span lang="EN-US" style="font-family:arial,sans-serif">TÍTULO</span></u></b><b><span lang="PT-BR" style="font-family:arial,sans-serif">: </span></b><b><span lang="EN-US" style="font-family:arial,sans-serif">"Modelling Higher-order correlations
in multi-neuron inputs and outputs in a population of neurons"</span></b><b><span lang="PT-BR" style="font-family:arial,sans-serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span></span></span></b></p>

<p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span lang="EN-US" style="font-family:arial,sans-serif;color:rgb(69,69,69)"><span> </span></span></p>

<p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><b><u><span lang="EN-US" style="font-family:arial,sans-serif">EXPOSITOR:</span></u></b><b><span lang="EN-US" style="font-family:arial,sans-serif"> </span></b><span class="m_2130190935970305313gmail-Ninguno"><b><span lang="EN-US">Dr Fernando Montani</span></b></span></p><p class="MsoNormal" style="background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><i><span lang="EN-US"><font size="2">IFLYSIB – CONICET/UNLP</font></span></i></p>

<p class="MsoNormal" style="text-align:justify"><b><u><span lang="EN-US" style="font-family:arial,sans-serif"><br></span></u></b></p><p class="MsoNormal" style="text-align:justify"><b><u><span lang="EN-US" style="font-family:arial,sans-serif">Resumen:</span></u></b><span lang="EN-US" style="font-family:arial,sans-serif"> </span><span lang="PT-BR" style="font-family:arial,sans-serif">To
understand how sensory information is processed in the brain, we need to
investigate how information is represented collectively by the activity of a
population of neurons. Information can be carried in spike rate, spike timing,
and spike correlations across neurons. Spike correlations across neurons are
widely found in the brain, and the evidences show that pairwise correlations do
not by themselves account for multineuronal firing patterns. Indeed, the
relationship between noise and signal correlations, when considering higher
order correlations can lead either to redundancy or synergy at population
level. Evidence shows that higher order correlations in the neuronal inputs and
the spiking outputs follow a non-Gaussian statistics suggesting the need of
developing a new theoretical framework taking into account the complexity of
synchronous activity patterns. We analyze how input statistics are transformed
through a threshold process into output statistics, and investigate the
conditions that may lead to higher-order correlations in a neuronal ensemble.
This allows us to define a new scenario for the interplay between pairwise and
higher-than-pairwise interactions.</span><span lang="PT-BR" style="font-size:14pt;font-family:arial,sans-serif;background-image:initial;background-position:initial;background-size:initial;background-repeat:initial;background-origin:initial;background-clip:initial"><span></span></span></p></div></div>
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