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Rapid categorization of achromatic natural scenes: how robust at very low contrasts?

Authors

  • Marc J.-M. Macé,

    1. Centre de Recherche Cerveau et Cognition (UMR 5549, CNRS-UPS), Faculté de Médecine de Rangueil, 133, route de Narbonne, 31062 Toulouse, France
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  • Simon J. Thorpe,

    1. Centre de Recherche Cerveau et Cognition (UMR 5549, CNRS-UPS), Faculté de Médecine de Rangueil, 133, route de Narbonne, 31062 Toulouse, France
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  • Michèle Fabre-Thorpe

    1. Centre de Recherche Cerveau et Cognition (UMR 5549, CNRS-UPS), Faculté de Médecine de Rangueil, 133, route de Narbonne, 31062 Toulouse, France
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Dr Marc Macé, as above.
E-mail: marc.mace@cerco.ups-tlse.fr

Abstract

The human visual system is remarkably good at categorizing objects even in challenging visual conditions. Here we specifically assessed the robustness of the visual system in the face of large contrast variations in a high-level categorization task using natural images. Human subjects performed a go/no-go animal/nonanimal categorization task with briefly flashed grey level images. Performance was analysed for a large range of contrast conditions randomly presented to the subjects and varying from normal to 3% of initial contrast. Accuracy was very robust and subjects were performing well above chance level (≈ 70% correct) with only 10–12% of initial contrast. Accuracy decreased with contrast reduction but reached chance level only in the most extreme condition (3% of initial contrast). Conversely, the maximal increase in mean reaction time was ≈ 60 ms (at 8% of initial contrast); it then remained stable with further contrast reductions. Associated ERPs recorded on correct target and distractor trials showed a clear differential effect whose amplitude and peak latency were correlated respectively with task accuracy and mean reaction times. These data show the strong robustness of the visual system in object categorization at very low contrast. They suggest that magnocellular information could play a role in ventral stream visual functions such as object recognition. Performance may rely on early object representations which lack the details provided subsequently by the parvocellular system but contain enough information to reach decision in the categorization task.

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