Decoding and Reconstructing the Focus of Spatial Attention from the Topography of Alpha-band Oscillations

J Cogn Neurosci. 2016 Aug;28(8):1090-7. doi: 10.1162/jocn_a_00955. Epub 2016 Mar 22.

Abstract

Many aspects of perception and cognition are supported by activity in neural populations that are tuned to different stimulus features (e.g., orientation, spatial location, color). Goal-directed behavior, such as sustained attention, requires a mechanism for the selective prioritization of contextually appropriate representations. A candidate mechanism of sustained spatial attention is neural activity in the alpha band (8-13 Hz), whose power in the human EEG covaries with the focus of covert attention. Here, we applied an inverted encoding model to assess whether spatially selective neural responses could be recovered from the topography of alpha-band oscillations during spatial attention. Participants were cued to covertly attend to one of six spatial locations arranged concentrically around fixation while EEG was recorded. A linear classifier applied to EEG data during sustained attention demonstrated successful classification of the attended location from the topography of alpha power, although not from other frequency bands. We next sought to reconstruct the focus of spatial attention over time by applying inverted encoding models to the topography of alpha power and phase. Alpha power, but not phase, allowed for robust reconstructions of the specific attended location beginning around 450 msec postcue, an onset earlier than previous reports. These results demonstrate that posterior alpha-band oscillations can be used to track activity in feature-selective neural populations with high temporal precision during the deployment of covert spatial attention.

MeSH terms

  • Adolescent
  • Adult
  • Alpha Rhythm*
  • Attention / physiology*
  • Brain / physiology*
  • Electroencephalography
  • Female
  • Humans
  • Linear Models
  • Male
  • Multivariate Analysis
  • Neuropsychological Tests
  • Reaction Time
  • Signal Processing, Computer-Assisted
  • Space Perception / physiology*
  • Young Adult