Comparison of tuning properties across areas revealed that higher visual areas in the mouse encode unique combinations of spatiotemporal information that are distinct from V1 (Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8). Furthermore, we found that each extrastriate area could be distinguished from every other visual area based on specific combinations Lenvatinib datasheet of visual feature representations (Figure 7). Together with anatomical information (Berezovskii et al., 2011, Coogan and Burkhalter, 1993 and Wang and Burkhalter, 2007),
these results suggest that mouse visual cortical areas may comprise hierarchically organized parallel pathways, perhaps similar to the dorsal and ventral streams suggested in other species. This study provides a fundamental understanding of the basic tuning properties of the majority of mouse visual cortical areas using high-throughput methods, laying a foundation for the use of the mouse as a genetically tractable model of visual information processing. Our first goal was to efficiently and precisely map the retinotopic
organization of mouse striate and extrastriate visual cortex in order to rapidly target distinct visual areas for population imaging and analysis. Previous anatomical work MLN2238 in vivo in mice predicts the existence of at least nine extrastriate visual cortical areas, based on topographic projections from V1 (Olavarria
and Montero, 1989 and Wang and Burkhalter, 2007). However, functional studies have not identified several detailed features of the retinotopic maps predicted by anatomy, resulting in significant variation between proposed schemes for the areal organization of mouse visual cortex (Kalatsky and Stryker, 2003, Schuett et al., also 2002, Wagor et al., 1980 and Wang and Burkhalter, 2007). Given the extremely small size of some proposed extrastriate visual areas (≤500 μm), we reasoned that insufficient resolution of previous recording methods, in combination with stimulation of only portions of the visual field in some studies, resulted in incomplete functional retinotopic maps. Thus, to rapidly and reliably target any given visual area in each animal, we developed a fast, sensitive, high-resolution functional recording method to map the retinotopic organization of cortex corresponding to the complete visual hemifield. We adopted a two-step approach that provided sufficient resolution to reliably define the extent and organization of each cortical visual area rapidly in each animal. First, we used intrinsic signal imaging to measure the hemodynamic response across the visual cortex to drifting bar stimuli at moderate resolution (estimated previously to be on the order of 200 μm (Polimeni et al., 2005)).