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Common patterns of rearrangements of neural networks in the whole human brain on reaching the threshold of recognition of images in conditions of uncertainly were identifi ed. This result was obtained using a combination of digital synthesis of dynamic images and a brain activity mapping method using fMRI BOLD (blood oxygen level-dependent) signals. Reaching the threshold of recognition of images of objects was found to be associated with increases in the BOLD signal in some parts of the brain and decreases in the activity of neural networks in other areas. Brain areas whose activity was maximal at the time corresponding to the recognition threshold and task solution were described, and this activity was shown to be lesser in subthreshold and even suprathreshold conditions for observation of dynamic images. Areas in which this activity was minimal were identified. The data were interpreted in the framework of multichannel and multilevel model of systems taking decisions relating to visual signals.

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.

This article gives an analysis of the interconnection of the optical properties of incomplete (fragmented) images and the psychophysical recognition thresholds of objects as necessary conditions for the appearance of visual insight. A well-known method of measuring the perception thresholds of fragmented images—the Gollin test—is proposed for the first time for solving the problem of evaluating the characteristics of insight in a person. The architecture of the neural networks that ensure the appearance of insight is considered.