Abstract

The linear transform model of functional magnetic resonance imaging (fMRI) hypothesizes that fMRI responses are proportional to local average neural activity averaged over a period of time. This work reports results from three empirical tests that support this hypothesis. First, fMRI responses in human primary visual cortex (V1) depend separably on stimulus timing and stimulus contrast. Second, responses to long-duration stimuli can be predicted from responses to shorter duration stimuli. Third, the noise in the fMRI data is independent of stimulus contrast and temporal period. Although these tests can not prove the correctness of the linear transform model, they might have been used to reject the model. Because the linear transform model is consistent with our data, we proceeded to estimate the temporal fMRI impulse–response function and the underlying (presumably neural) contrast–response function of human V1.

Keywords

Functional magnetic resonance imagingStimulus (psychology)Impulse responseVisual cortexGeneral linear modelLinear modelNeurosciencePsychologyContrast (vision)Artificial intelligenceComputer scienceCognitive psychologyMathematicsMachine learning

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Publication Info

Year
1996
Type
article
Volume
16
Issue
13
Pages
4207-4221
Citations
2349
Access
Closed

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Geoffrey M. Boynton, Stephen A. Engel, Gary H. Glover et al. (1996). Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1. Journal of Neuroscience , 16 (13) , 4207-4221. https://doi.org/10.1523/jneurosci.16-13-04207.1996

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DOI
10.1523/jneurosci.16-13-04207.1996