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The Spiking Search over Time and Space Model (sSoTS): Simulating Dual Task Experiments and the Temporal Dynamics of Preview Search

  • Eirini Mavritsaki
  • Dietmar Heinke
  • Glyn Humphreys
  • Gustavo Deco
Conference paper
  • 1.2k Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4840)

Abstract

The visual information we receive in the real world is usually prioritized through time as well as space. Evidence presented by Watson and Humphreys [18] supports the view that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this work we present, an explicit computational model of visual marking using biologically plausible activation functions. The ”spiking search over time and space” model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca2  + ] sensitive K +  current. This frequency adaptation current when coupled with a process of active inhibition applied to old items, leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, sSoTS can simulate the temporal dynamics of preview search [13] and dual task experimental results [12] . The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.

Keywords

Visual search over time temporal dynamics of visual marking dual task integrate-and-fire neurons frequency adaptation 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Eirini Mavritsaki
    • 1
  • Dietmar Heinke
    • 1
  • Glyn Humphreys
    • 1
  • Gustavo Deco
    • 2
  1. 1.Behavioural Brain Sciences Centre, School of Psychology, University of Birmingham, Edgbaston, B15 2TTUK
  2. 2.Institucio Catalana de Recerca i Estudis Avancats (ICREA), Universitat Pompeu Fabra, Dept. of Technology, Computational Neuroscience, Passeig de Circumval.lacio, 8 08003 BarcelonaSpain

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