Towards obtaining spatiotemporally precise responses to continuous sensory stimuli in humans: A general linear modeling approach to EEG

Nuno R. Gonçalves, Robert Whelan, John J. Foxe, Edmund C. Lalor

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Noninvasive investigation of human sensory processing with high temporal resolution typically involves repeatedly presenting discrete stimuli and extracting an average event-related response from scalp recorded neuroelectric or neuromagnetic signals. While this approach is and has been extremely useful, it suffers from two drawbacks: a lack of naturalness in terms of the stimulus and a lack of precision in terms of the cortical response generators. Here we show that a linear modeling approach that exploits functional specialization in sensory systems can be used to rapidly obtain spatiotemporally precise responses to complex sensory stimuli using electroencephalography (EEG). We demonstrate the method by example through the controlled modulation of the contrast and coherent motion of visual stimuli. Regressing the data against these modulation signals produces spatially focal, highly temporally resolved response measures that are suggestive of specific activation of visual areas V1 and V6, respectively, based on their onset latency, their topographic distribution and the estimated location of their sources. We discuss our approach by comparing it with fMRI/MRI informed source analysis methods and, in doing so, we provide novel information on the timing of coherent motion processing in human V6. Generalizing such an approach has the potential to facilitate the rapid, inexpensive spatiotemporal localization of higher perceptual functions in behaving humans.

Original languageEnglish (US)
Pages (from-to)196-205
Number of pages10
JournalNeuroImage
Volume97
DOIs
StatePublished - Aug 15 2014

Keywords

  • Dorsal stream
  • EEG
  • Impulse response
  • Motion
  • VEP
  • VESPA

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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