J Vision
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A fMRI study by Pestilli et al. (2011) established a method for modeling links between attention-related changes in BOLD activation in visual cortex and changes in behavior. The study found that models based on sensory gain and noise reduction could not explain the relationship between attention-related changes in behavior and attention-related additive shifts of the BOLD contrast-response function (CRF). However, a model based on efficient post-sensory read-out successfully linked BOLD modulations and behavior. ⋯ We also observed differences between attention-induced changes in EEG-based CRFs (multiplicative gain) and fMRI-based CRFs (additive shift) within the same group of subjects who performed an identical spatial attention task. These results suggest that attentional modulation of EEG responses interacts with the magnitude of sensory-evoked responses, whereas attentional modulation of fMRI signals is largely stimulus-independent. This raises the intriguing possibility that EEG and fMRI signals provide complementary insights into cortical information processing, and that these complementary signals may help to better constrain quantitative models that link neural activity and behavior.
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Understanding the human neural mechanisms that underly behavioral enhancement due to visual spatial attention requires synthesis of knowledge gained across many different spatial scales of measurement and species. Our lab has focused on the measurement of contrast-response and how it changes with attention in humans. Contrast is a key visual variable in that it controls visibility and measurements from single-units to optical-imaging to fMRI find general consistency in that cortical visual areas respond in monotonically increasing functions to increases in contrast. ⋯ Our work is heavily informed by the physiology literature particularly because some properties of neural response, such as efficiency of synaptic transmission or correlation of activity are difficult if not impossible to determine in humans. Nonetheless, discrepancies across measurements suggests potential difficulties of interpretation of results from any single measurement modality. We will discuss our efforts to address these potential discrepancies by adapting computational models used to explain disparate effects across different single-unit studies to larger spatial-scale population measures such as fMRI.