Hierarchical feedforward (FF) models of the visual system have provided a foundation for most theories of visual processing over the past 40 years. It is problematic that these models have relied on probabilistic representations of FF connectivity between visual areas, partly because we lack information about the wiring principles and functional organization of FF connections, even between the earliest visual areas V1 and V2, which have been studied for decades. Our goal is to uncover the rules of anatomical and functional connectivity for V1 output pathways to V2 to anatomically-constrain FF models of vision. This information is crucial to understand how V1 and V2 reorganize retinal signals into processing streams, and how V1 output pathways contribute to generating the receptive field (RF) properties and functional maps in V2. In primates, parallel pathways from V1 project to distinct V2 cytochrome-oxidase (CO) stripes [thick (Tk), thin (Tn) and pale (Pl)]. It is unknown whether the local connections of V1 output cells, and their V1 inputs integrate information across parallel streams or maintain within-stream segregation. It is also debated whether distinct V1 and V2 CO compartments show specialized or diverse visual response properties, partly because it has been difficult to record from identified V1 output cells. During prior funding period, we found that the local intra-V1 connectivity of V1 cells projecting to Tk stripes shows within-stream segregation. It is, thus, important to extend these studies to V1 cells projecting to Tn and Pl stripes. To address this goal, we will label these cells using viral vectors, reconstruct them through whole V1 and V2 blocks rendered optically transparent, and align them to CO and functional maps of V1 and V2 (Aim1). Using viral-based monosynaptic circuit tracing combined with CO-staining and optical imaging (OI) of functional maps, we will test the hypothesis that the V1 and V2 inputs to V1 cells projecting to distinct V2 stripes are also stream specific, arising from the same CO and functional compartments as the V1 output cells that they contact (Aim2). We will also test the hypothesis of functional segregation in the monosynaptic projections from V1 to V2 stripes, by characterizing the visual responses of optogenetically-identified V1 cells projecting to distinct stripes (Aim3). Finally, it is unknown how V1 inputs are combined within local V2 columns in each stripe; this information is crucial to understand how V1 inputs contribute to generating the more complex RF properties of V2 cells. We will address this question both anatomically and functionally (Aim4). In SubAim4a, we will determine how V1 inputs to single V2 columns are distributed over the V1 functional maps, by combining OI of functional maps with injections of retrograde tracers in V2. In SubAim4b we will characterize the population RF of V1 inputs to a local V2 column, using simultaneous array recordings in V1 and V2 and spike-triggered CSD analysis. Thes studies will reveal how V1-to-V2 circuits are anatomically and functionally organized, their degree of specialization, and how V1 inputs are pooled in V2 to generate V2 RFs. The results will provide a mechanistic foundation for modeling studies of FF and parallel processing in visual cortex.
Normal brain function depends on the orderly development of circuits in the cerebral cortex and on their intact function. Knowledge of the normal circuitry provides a foundation for understanding the causes of impaired brain function and developing corrective measures. Our studies of the normal circuitry between early visual cortical areas will provide greater insight into the causes and effects of central vision defects when these circuits are damaged by stroke or other neurological or developmental cause. In addition, our studies of the normal organization of long-range circuits between visual cortical areas will provide a foundation for understanding the consequences of their dysfunction in disorders of brain function such as autism and schizophrenia, which have been directly linked to abnormalities in inter-areal connectivity (Belmonte et al., 2004, Lynall et al., 2010).
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