Abstract
This paper introduces an application of artificial neural networks for visualization of functions of neurons in the higher visual areas of the brain. First, a model that enables the prediction of an evoked neural response was implemented. The model has a correlation coefficient of up to 0.82 for certain cortical columns. Then, an approach to explaining representations encoded by neurons was proposed. The approach is based on generating images maximizing an activation in the model. A comparison of the visualization results with the experimental data suggests that the approach can be used to study the properties of the higher-level areas of the visual cortex.
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