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There has been great progress in understanding of anatomical and functionalmicrocircuitry of the primate cortex. However, the fundamental principles ofcortical computation - the principles that allow the visual cortex to bindretinal spikes into representations of objects, scenes and scenarios - have sofar remained elusive. In an attempt to come closer to understanding thefundamental principles of cortical computation, here we present a functional,phenomenological model of the primate visual cortex. The core part of the modeldescribes four hierarchical cortical areas with feedforward, lateral, andrecurrent connections. The three main principles implemented in the model areinformation compression, unsupervised learning by prediction, and use oflateral and top-down context. We show that the model reproduces key aspects ofthe primate ventral stream of visual processing including Simple and Complexcells in V1, increasingly complicated feature encoding, and increasedseparability of object representations in higher cortical areas. The modellearns representations of the visual environment that allow for accurateclassification and state-of-the-art visual tracking performance on novelobjects.

Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback