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When the head rotates, the image of the visual world slips across the retina. A dedicated set of retinal ganglion cells (RGCs) and brainstem visual nuclei termed the "accessory optic system" (AOS) generate slip-compensating eye movements that stabilize visual images on the retina and improve visual performance. Which types of RGCs project to each of the(More)
On-Off direction-selective retinal ganglion cells (DSGCs) encode the axis of visual motion. They respond strongly to an object moving in a preferred direction and weakly to an object moving in the opposite, "null," direction. Historically, On-Off DSGCs were classified into four subtypes according to their directional preference (anterior, posterior,(More)
How specific features in the environment are represented within the brain is an important unanswered question in neuroscience. A subset of retinal neurons, called direction-selective ganglion cells (DSGCs), are specialized for detecting motion along specific axes of the visual field. Despite extensive study of the retinal circuitry that endows DSGCs with(More)
1 Abstract This chapter describes a principled approach to meta-learning that has three distinctive features. First, whereas most previous work on meta-learning focused exclusively on the learning task, our approach applies meta-learning to the full knowledge discovery process and is thus more aptly referred to as meta-mining. Second, traditional(More)
How axons select their appropriate targets in the brain remains poorly understood. Here, we explore the cellular mechanisms of axon target matching in the developing visual system by comparing four transgenic mouse lines, each with a different population of genetically labeled retinal ganglion cells (RGCs) that connect to unique combinations of brain(More)
How specific features in the environment are represented within the brain is an important unanswered question in neuroscience. A subset of retinal neurons, called direction selective ganglion cells (DSGCs) are specialized for detecting motion along specific axes of the visual field 1. Despite extensive study of the retinal circuitry that endows DSGCs with(More)
The Data Mining OPtimization Ontology (DMOP) has been developed to support informed decision-making at various choice points of the data mining process. The ontology can be used by data miners and deployed in ontology-driven information systems. The primary purpose for which DMOP has been developed is the automation of algorithm and model selection through(More)
—The notion of meta-mining has appeared recently and extends the traditional meta-learning in two ways. First it does not learn meta-models that provide support only for the learning algorithm selection task but ones that support the whole data-mining process. In addition it abandons the so called black-box approach to algorithm description followed in(More)