Digital visualization of the activity of neural networks of the human brain before, during, and after insight when images are being recognized

Abstract

Technological resources have made it possible to begin experimental study of the activity of neural networks both in the conscious, systematic, analytic method of solving problems, and in sudden, abrupt enlightenment or insight. The purpose of this paper is to study the reconstruction of neural networks when they go from unconscious information processing to the conscious processes that accompany insight. Methods for digitally synthesizing tests (dynamic images) and methods for digitally analyzing images of brain responses can be used to establish the laws that govern the reconstruction of the activity of large-scale neural networks of the human brain at the instant of insight. The activity of large-scale neural networks reaches its maximum at the moment of insight, corresponding to the recognition threshold or the solution of a problem and is less under below-threshold and above-threshold conditions at which dynamic images are observed. The BOLD (blood-oxygen-level-dependent) value is initially maximized when the threshold is reached in some zones and the maximum falloff of the activity of the neural networks is reached in other zones of the brain.