1996/07/01 by Geoffrey M. Boynton, Stephen A. Engel, Gary H. Glover +1 · 12 citations
Neuroscience · Psychology · Mathematics · #Visual perception and processing mechanisms #Neural dynamics and brain function #Functional Brain Connectivity Studies #Functional magnetic resonance imaging #Stimulus (psychology) #Impulse response #Visual cortex #General linear model #Linear model #Neuroscience #Psychology #Contrast (vision) #Artificial intelligence #Computer science #Cognitive psychology #Mathematics #Machine learning
paper · pdf · doi:10.1523/jneurosci.16-13-04207.1996
openalex publication_date 1996/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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.