A paamount component of intelligence is our ability to extract useful information in the world through our sensory observations. Object recognition is a fundamental problemin visual perception: everyday we depend on our ability to identify objects in our visual environment and our brain is capable of accoevery day we depend on our ability to identify objects in our visual environment, and our brain is capable of accomplishing it effortlessly and in a fraction of a second, in spite of immense variation in the sensory information that arrives in our retinas. Understanding the algorithm that the brain uses to do this complex task would be a decisive conquest in neuroscience but in order to understand ethologically relevant visual processing, we need to understand how it drives behavior. Despite the extensive research in the last few decades, we are still far from having a complete understanding of how the brain creates untangled transformation-invariant object representations in the perceptual/visual domain, that can subsequently be used to guide behavior. Recent advances in imaging techniques and high throughput behavioral training of mice that we developed, allows us to study how objects are represented in the activity of large populations of neurons across the visual hierarchy and relate these representations to the behavior of the animal. We seek to understand the algorithm used by the mouse visual cortex to extract relevant features from complex environments and guide natural behaviors. By starting with ethologically-relevant behaviors, we will be able to identify these latent causes, discover how they are represented in the mouse cortical visual system and how in turn these representations affect the behavior of the animals.