The ability to read a page of text or recognize a person’s face depends on category-selective visual regions in ventral temporal cortex (VTC). To understand how these regions mediate word and face recognition, it is necessary to characterize how stimuli are represented and how this representation is used in the execution of a cognitive task. Here, we show that the response of a category-selective region in VTC can be computed as the degree to which the low-level properties of the stimulus match a category template. Moreover, we show that during execution of a task, the bottom-up representation is scaled by the intraparietal sulcus (IPS), and that the level of IPS engagement reflects the cognitive demands of the task. These results provide an account of neural processing in VTC in the form of a model that addresses both bottom-up and top-down effects and quantitatively predicts VTC responses.
Bibliographical noteFunding Information:
We thank K Grill-Spector for providing the face and house stimuli used in the main experiment, R Kiani and N Kriegeskorte for providing the object stimuli used in the retinotopic mapping experiment, A Vu and E Yacoub for collecting pilot data, C Gratton, M Harms, and L Ramsey for scanning assistance, and K Weiner for assistance with ROI definition. We also thank P Elder, C Gratton, S Petersen, A Rokem, A Vogel, and J Winawer for helpful discussions. This work was supported by the McDonnell Center for Systems Neuroscience and Arts and Sciences at Washington University (KNK) and NSF Grant BCS-1551330 (JDY). Computations were performed using the facilities of the Washington University Center for High Performance Computing, which were partially provided through grant NCRR1S10RR022984-01A1. McDonnell Center for Neuroscience Systems Kendrick N Kay. Washington University in St.Louis Kendrick N Kay. National Science Foundation BCS-1551330 Jason D Yeatman. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
© Kay and Yeatman.