Figure 1. Marmosets are an ideal model for neural investigations of active vision. A: High precision eye tracking. B: Active visual foraging on natural images. C: Laminar recordings from populations in visual cortex.
My research aims to understand how active behavior alters visual processing in brain circuits. In primates rapid saccadic eye movements occur 2-3 times every second, providing information critical to navigating the world. They allow us to inspect targets of interest by repositioning the fovea, the regions of highest central visual acuity. However, early studies of visual neuroscience used anesthetized animals in which the eye was fixed. Findings from this passive-viewing paradigm were central in establishing feed-forward processing pathways of spatial and form vision. In contrast, research in human psychophysics has established that active processes such as top-down predictions and selective attention can profoundly influence perception. Similarly, it is now understood that feedback projections carrying motor and attention-related information from frontal areas of the brain are an important anatomical feature of the visual system. To bridge the gap in our understanding of the role of feedback during active vision we have developed novel tasks that allow us to investigate neural activity in cortical circuits during action. Our research is focused on four areas:
We investigate these questions in a novel animal model, the common marmoset (Callithrix Jacchus). While the development of transgenic lines originally spurred interest in this species, it also offers several neuroscientific advantages for studying active vision. First the brain organization is highly similar to other primates including the layout of visual areas and a foveal specialization for high acuity vision. Our research has led the field in characterizing their visual and eye movement behaviors. To gain insights about the underlying neural mechanisms of visual behavior, we combine our behavioral measures with simultaneous recordings from neural populations in visual cortex (Fig. 1). We are using high density linear arrays that enable us to sample from multiple cortical columns and different cellular layers, providing a more detailed view of circuitry. We are also testing opto-genetic tools for the causal manipulation of feedback pathways to visual cortex. Our aim is to understand how attention and visual predictions shape sensory processing.