August 2012
Volume 12, Issue 9
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2012
Can principal component analysis reliably identify the temporal response of cortical area V1?
Author Affiliations
  • Thom Carney
    School of Optometry, Univ. of Calif at Berkeley
  • David Kim
    Bioengineering, Univ. of Calif at Berkeley
  • Justin Ales
    Psychology, Stanford University,
  • Stanley Klein
    School of Optometry, Univ. of Calif at Berkeley
Journal of Vision August 2012, Vol.12, 78. doi:https://doi.org/10.1167/12.9.78
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      Thom Carney, David Kim, Justin Ales, Stanley Klein; Can principal component analysis reliably identify the temporal response of cortical area V1?. Journal of Vision 2012;12(9):78. https://doi.org/10.1167/12.9.78.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

The early CI component and its polarity inversion as a stimulus moves from inferior to superior visual field is the basis for many evoked response potential (ERP) based claims of attention and other perceptual effects involving V1 activation. However, recent results have undermined the validity those criteria. Ales et al. (2010) have shown "polarity inversion is an unreliable diagnostic for activity originating in striate cortex". The fact that the CI is the earliest response peak is also not indicative of a V1 signal since recent ERP source modeling demonstrate that the signals from V1 and V2 begin at about the same time (Ales et al, 2009). With historical ERP measures of V1 activation discredited, does any method offer reliable isolation of the striate cortex response besides inverse source modeling along with fMRI to constrain the solution space?

Zhang and Hood (2004) suggested principal component analysis provides a means of deriving the V1 response when combined with multi-focal stimulation. The change in the first component signal strength with stimulus position was consistent with the cruciform model of V1. However, we now know the cruciform model is flawed, so we revisited the utility of using PCA to isolate V1.

In two subjects, using high density multi-focal stimuli with a 96 electrode recording array we compared the V1 temporal response based on PCA verses inverse source modeling methods. The concordance between the V1 response derived from PCA and fMRI constrained inverse source modeling was high. However, in 21 subjects, simulated ERPs using boundary element forward models and fMRI based source positions corresponding to a 96 patch multi-focal stimulus demonstrated that the first PCA component of simulated ERP's do not always match the V1 source time functions. In conclusion, PCA of the multi-focal ERP does not provide a reliable estimate of an individual's V1 response.

Meeting abstract presented at VSS 2012

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