Attentional selection of feature conjunctions is accomplished by parallel and independent selection of single features

Søren K. Andersen, Matthias M Muller, Steven A Hillyard

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34 Citations (Scopus)
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Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex.
Original languageEnglish
Pages (from-to)9912-9919
Number of pages8
JournalJournal of Neuroscience
Issue number27
Early online date8 Jul 2015
Publication statusPublished - 8 Jul 2015

Bibliographical note

Date of Acceptance: 31/05/2015

This work was supported by Deutsche Forschungsgemeinschaft (AN 841/1-1, MU 972/20-1). We thank Renate Zahn and Norman Forschack for help with data collection. The authors declare no competing financial interests


  • attention
  • EEG
  • feature-based attention
  • frequency tagging
  • steady-state visual evoked potentials
  • visual search


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