Data set for the study "Distrctor Volatility and Distractor Suppression"

Authors

Nan Qiu, Fredrik Allenmark, Hermann J. Müller, Zhuanghua Shi

Background

Statistical learning to suppress the location(s) of where a salient distractor is likely (vs. unlikely) to occur can enhance visual search efficiency, an effect termed distractor-location probability cueing. However, whether this effect is influenced by the volatility of distractor occurrence (i.e., of the sequence of distractor-present and -absent events) remains poorly understood. Here, we investigated this question by contrasting two volatility regimens in a distractor-location probability-cueing paradigm: a low-volatility environment ( distractor-present and -absent trials likely streaked) and a high-volatility environment (two trial types changing frequently).

Data structure

  • /csv includes the raw experimental data
  • /figs includes the output figures for the manuscript
  • behavioral_analysis.ipynb is the analysis journal