Abstract
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.
Highlights
How does visual cortex work? One approach to answering this question consists in building functional models that characterize the computations that are implemented by neurons and their circuitry (Hubel and Wiesel, 1963; Heeger et al, 1996)
We focus on two specific ventral temporal cortex (VTC) regions, the visual word form area (VWFA), which selectively responds to words (Cohen et al, 2000, 2002; Wandell et al, 2012), and the fusiform face area (FFA), which selectively responds to faces (Kanwisher et al, 1997; Grill-Spector and Weiner, 2014)
Building upon the observation that top-down modulation acts as a scaling mechanism on responses in VWFA and FFA and the observation that top-down effects are correlated with the intraparietal sulcus (IPS) signal, we propose that the magnitude of the IPS response to a stimulus indicates the amount of top-down scaling that is applied to bottom-up sensory responses in VTC (Figure 5a)
Summary
One approach to answering this question consists in building functional models that characterize the computations that are implemented by neurons and their circuitry (Hubel and Wiesel, 1963; Heeger et al, 1996) This approach has been fruitful for the front end of the visual system, where relatively simple image computations have been shown to characterize the spiking activity of neurons in the retina, thalamus, and V1 (Carandini et al, 2005; Wu et al, 2006). Models of early visual processing have been able to offer accurate explanations of low-level perceptual functions such as contrast detection (Ress et al, 2000; Ress and Heeger, 2003) and orientation discrimination (Bejjanki et al, 2011) These models are insufficient to explain highlevel perceptual functions such as the ability to read a page of text or recognize a face. These abilities are believed to depend on category-selective regions in ventral temporal cortex (VTC), but the computations that give rise to category-selective responses are poorly understood
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