This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Studies of inferotemporal cortex have looked for the parameter space over which IT neurons are tuned; for example, tuning for color and stimulus size have been tested, along with a plethora of other stimuli. The curious results from these studies is that IT neurons are unpredictable: small changes in a stimulus can sometimes cause huge changes in neural response, while large changes can sometimes cause negligible changes in neural response. Our proposal is that this curiosity can be explained by describing IT neurons as being tuned to the perceptual similarity of stimuli. That is the hypothesis being tested in studies in our laboratory. We have made progress on several fronts. The first is testing a method of assessing the degree of tuning and response similarity that we would expect to untrained stimuli in IT, using image similarity algorithms developed for searching image databases. In that experiment (Allred & Jagadeesh, 2005) we examined the relationship between neural response and perception by recording from IT neurons in monkeys while they viewed realistic images. Images that elicited similar neural responses were ranked as more similar by these algorithms than images that elicited different neural responses, and images ranked as similar by the algorithms elicited similar responses from neurons. The degree to which algorithms for image similarity were correlated with human perception was related to the degree to which algorithms explained the selectivity of IT neurons, providing support for the proposal that the selectivity of IT neurons is related to perceptual similarity of images. In addition to this work, we have developed a demanding discrimination task, and made simultaneous measurements of neural performance. To paraphrase the abstract of this work, we studied the relationship between neural response and behavioral choice by recording from IT neurons while monkeys performed a delayed-match-to sample task with images.
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