Decoding of visual attention from LFP signals of macaque MT

PLoS One. 2014 Jun 30;9(6):e100381. doi: 10.1371/journal.pone.0100381. eCollection 2014.


The local field potential (LFP) has recently been widely used in brain computer interfaces (BCI). Here we used power of LFP recorded from area MT of a macaque monkey to decode where the animal covertly attended. Support vector machines (SVM) were used to learn the pattern of power at different frequencies for attention to two possible positions. We found that LFP power at both low (<9 Hz) and high (31-120 Hz) frequencies contains sufficient information to decode the focus of attention. Highest decoding performance was found for gamma frequencies (31-120 Hz) and reached 82%. In contrast low frequencies (<9 Hz) could help the classifier reach a higher decoding performance with a smaller amount of training data. Consequently, we suggest that low frequency LFP can provide fast but coarse information regarding the focus of attention, while higher frequencies of the LFP deliver more accurate but less timely information about the focus of attention.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Animals
  • Attention / physiology*
  • Brain-Computer Interfaces
  • Craniotomy
  • Electroencephalography
  • Evoked Potentials, Visual / physiology*
  • Macaca mulatta / physiology*
  • Male
  • Microelectrodes
  • Photic Stimulation
  • Visual Cortex / anatomy & histology
  • Visual Cortex / physiology*

Grant support

This work was funded by the Institute for Research in Fundamental Sciences (IPM), School of Cognitive Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.