Spontaneous Decoding of the Timing and Content of Human Object Perception from Cortical Surface Recordings Reveals Complementary Information in the Event-Related Potential and Broadband Spectral Change

Abstract

The link between object perception and neural activity in visual cortical areas is a problem of fundamental importance in neuroscience. Here we show that electrical potentials from the ventral temporal cortical surface in humans contain sufficient information for spontaneous and near-instantaneous identification of a subjects perceptual state. Electrocorticographic (ECoG) arrays were placed on the subtemporal cortical surface of seven epilepsy patients. Grayscale images of faces and houses were displayed rapidly in random sequence. We developed a template projection approach to decode the continuous ECoG data stream spontaneously, predicting the occurrence, timing and type of visual stimulus. In this setting, we evaluated the independent and joint use of two well-studied features of brain signals, broadband changes in the frequency power spectrum of the potential and deflections in the raw potential trace (event-related potential; ERP). Our ability to predict both the timing of stimulus onset and the type of image was best when we used a combination of both the broadband response and ERP, suggesting that they capture different and complementary aspects of the subjects perceptual state. Specifically, we were able to predict the timing and type of 96% of all stimuli, with less than 5% false positive rate and a ~20ms error in timing.

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Document Details

Document Type
Technical Report
Publication Date
Jan 28, 2016
Accession Number
AD1094763

Entities

People

  • Dora Hermes
  • Gerwin Schalk
  • Jeffrey G. Ojemann
  • Kia J. Miller
  • Rajesh P.N. Rao

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Brain
  • Cerebral Cortex
  • Computational Science
  • Computer Vision
  • Data Mining
  • Decoding
  • Electrophysiological Phenomena
  • Information Science
  • Machine Learning
  • Neurosciences
  • Power Spectra
  • Three Dimensional
  • Two Dimensional
  • United States
  • Visual Cortex
  • Voltage

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computer Vision.
  • Neuroscience