Methodological problems of empirical testing of predictive models of consciousness

predictive models of consciousness based on the principles of the Bayesian brain and predictive coding are one of the most influential theoretical frameworks in modern cognitive neuroscience. However, according to the author of this article, empirical testing of these models faces a number of fundamental methodological problems. Results. In this article, the author analyzes the main challenges, including the problems of operationalization of consciousness, measurement of predictive processes, establishment of causal relationships and interpretation of results. The limitations of existing experimental paradigms are considered and directions for the development of research methodology are proposed. Particular attention is paid to the need to integrate different levels of analysis and develop new experimental approaches for adequate testing of predictive theories of consciousness. Conclusion. In the course of the study, the author of this article found that the empirical testing of predictive models of consciousness faces fundamental methodological problems that require innovative solutions. Success in this area depends on the integration of different levels of analysis, the development of new experimental paradigms, and the deepening of theoretical understanding of the nature of consciousness. Of particular importance is the development of methods that can adequately reflect the complexity and multidimensionality of conscious processes, while maintaining scientific rigor and reproducibility of results.

psychology, development of psychology, consciousness, predictive coding, Bayesian brain, methodology, neuroscience