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Philipp Schwedhelm, Florian Kasten, Stefan Treue; Attention field size effects in transparent motion discrimination. Journal of Vision 2013;13(9):148. doi: https://doi.org/10.1167/13.9.148.
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© ARVO (1962-2015); The Authors (2016-present)
The Normalization Model of Attention (NMoA; Reynolds & Heeger, Neuron 2009) provides a parsimonious explanation for many of the diverse effects of attention on neuronal responses in visual cortex. A core prediction of this model is that the relationship between stimulus size and attention field size determines whether attention has a contrast or response gain influence on neuronal activity. This has since been confirmed for spatial attention, but for feature-based attention Herrmann et al. (Vision Research, 2012) found that regardless of the extent of the attention field within the feature dimension orientation, only response gain effects are observed. They argued that this is explained by the NMoA since it predicts contrast gain effects only for very narrow tuning bandwidths. We tested this prediction in a direction discrimination task, which allowed for an increased ratio between tuning bandwidth and attention field size. Subjects viewed random dot patterns containing two directions in transparent motion and compared these with a subsequent single motion, indicating the direction change relative to the closer direction of the transparent motion stimulus. Using an abstract cue with 75% validity, we directed feature-based attention to ranges of either 20° or 110° width for the target direction. We then varied motion coherences and assessed attentional effects on psychophysical performance. In agreement with Herrmann et al. we find that the feature attention field can be modulated by means of a visual cue, and we have first experimental evidence of such a modulation for attention to visual motion. However, our results indicate a combination of contrast and response gain, to a large degree following predictions made by the NMoA. We conclude that the type of neuronal modulation evoked by feature-based attention depends on the relationship between tuning width for the given feature dimension and the width of the attention field in that dimension.
Meeting abstract presented at VSS 2013
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