Abstract
Pattern recognition is a fundamental neuronal process which enables a
cortical system to interpret visual stimuli. How the brain learns to
recognize patterns is, however, an unsolved problem. The frequently
employed method of back propagation excels at this task but has been
found to be unbiological in many aspects. In this Rapid Communication we
achieve pattern recognition tasks in a biologically, fully consistent
framework. We consider a neuronal network exhibiting avalanche dynamics,
as observed experimentally, and implement negative feedback signals.
These are chemical signals, such as dopamine, which mediate synaptic
plasticity and sculpt the network to achieve certain tasks. The system
is able to distinguish horizontal and vertical lines with high accuracy,
as well as to perform well at the more complicated task of handwritten
digit recognition. Resulting from the learning mechanism, spatially
separate activity regions emerge, as observed in the primary visual
cortex using functional magnetic resonance imaging techniques. The
results therefore suggest that negative feedback signals offer an
explanation for the emergence of distinct activity areas in the visual
cortex.
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