Past events

The cortical system for processing faces is a model system for studying the functional neuroanatomy of ventral temporal cortex and its role in perception for two reasons. First, the functional organization of the cortical face system is well understood. Second, activations in ventral face-selective regions are causally related to face perception. Here, I will describe recent results from our research elucidating the computations performed by population receptive field (pRFs) in the cortical system for face perception. In contrast to predictions of classical theories, recent data from my lab reveals that computations in face-selective regions in human ventral temporal cortex can be characterized with a computational pRF model, which predicts the location and spatial extent of the visual field that is processed by the neural population in a voxel. Our research characterizes pRF properties of ventral face-selective regions revealing three main findings. First, pRFs illustrate a hierarchical organization within the face system, whereby pRFs become larger and more foveal across the ventral hierarchy. Second, attention to faces modulates pRFs in face-selective regions, consequently enhancing the representation of faces in the peripheral visual field where visual acuity is the lowest. Third, our research shows that pRF properties in face-selective regions are behaviorally relevant. We find that face perception abilities are correlated with pRF properties: participants with larger pRFs perform better in face recognition than participants with smaller pRFs. These data suggest that computations performed by pRFs in face-selective regions may form a neural basis for holistic processing necessary for face recognition. Overall, these data highlight the importance of elucidating computational properties of neural populations in ventral temporal cortex as they offer a new mechanistic understanding of high-level visual processes such as face perception.

Several recent papers have used the technique of Intersubject Correlation (ISC) of fMRI data to study differences between typical individuals and those on the autism spectrum when they watch movies while being scanned (Byrge, et al., 2015; Salmi et al., 2013; Hasson et al., 2009). In this presentation I discuss preliminary results from a study using ISC of solo dances that explored the differences in biological motion processing in autism noted previously by our lab (McKay, et al., 2012). This will include introductory discussion of ISC studies of dance that have highlighted the possible confounding effect of using edited videos composed of different camera views (Herbec et al., 2015) as well as the motion signal that appears related to regions of highest ISC (Noble et al., 2014; Jola et al., 2013).

Learning lays the foundation for motivated behavior, enabling us to recognize and respond appropriately to salient events. However, to function adaptively in a dynamic environment, we must be able to flexibly alter learned behavioral responses in accordance with our ongoing experience. In this talk, I will present studies examining at the cognitive, neural, and computational levels how the learning processes that support adaptive behavioral flexibility change over the course of development from childhood to adulthood. I will show that development confers marked changes in the cognitive representations engaged during learning and I will propose that learning about the degree of instrumental agency afforded by the environment may be a critical factor that shapes an individual’s behavioral repertoire.