Brain is the most complicated system in the body, and one of the most important functions of the brain is the ability to track and perceive sensory impressions from surroundings. The neural circuits in the brain receive and process sensory information that permits them to perceive and interact with the environment at any given moment.
It has been known for many years that the eye contains nerve cells that signal and sense the direction of movement when an object moves in the vision field. Visual information can be processed in a highly parallel manner in a visual system which is a precision instrument. In this neural circuitry, light picks up at neighboring points on the retina at the back of the eye is projected onto neighboring neurons in the brain's visual cortex. These neurons connect like wires into neural circuits and convert light into information the brain can understand.
Retinotopic pathways convey motion and color/contrast signals from the eye to many visual centers (primary visual cortex) to process. In particular, the precise interplay in the receptive fields of neurons in the visual cortex plays a significant role that works similarly to a camera sensor. They encode specific properties of the visual scene and contain excitatory and inhibitory areas. These retinotopic projections involve many neurons, which encode specific visual information. Even in newborns without fully developed retinas, intricate networks of neuron circuits had already formed across their retinas.
Fig.1 Pathways of vision and reading. (Wandell, 2017)
Many neural pathways emanate in parallel from the retina to compute an array of visual features. However, much information remains to be revealed, including the specific neural circuit elements and their function to underly visual perception. Recent advances in developing cell-culture-based models to understand the visual information and monitor specific neural circuits in animals such as zebrafish and mice make answering these questions possible. Indeed, these state-of-the-art in vitro or in vivo model techniques have allowed us to study specific visual processing and vision neural circuitry in different ways.
Some researchers have developed a computational neural model to help neuroscientists understand how neuronal networks in the visual system process natural stimuli. With the advances of neural network modeling to enable major strides in computer vision, we are entering an exciting new era to build biologically computational models to understand how vision brains perform high-level feats.
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Reference
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