Frontiers in Systems Neuroscience (Oct 2016)
The Predictive Processing Paradigm Has Roots in Kant
Abstract
Predictive processing is a paradigm in computational and cognitive neuroscience that has recently attracted significant attention across domains, including psychology, robotics, artificial intelligence, and philosophy. It is often regarded as a fresh and possibly revolutionary paradigm shift, yet a handful of authors have remarked that aspects of predictive processing seem reminiscent of the work of 18th century philosopher Immanuel Kant. To date there have not been any substantive discussions of how exactly predictive processing links back to Kant. In this article I argue that several core aspects of predictive processing were anticipated by Kant in his 1781-87 works on perception and cognition. Themes from Kant active in predictive processing include (1) the emphasis on ‘top-down’ generation of percepts, (2) the role of ‘hyperpriors’, (3) the general function of ‘generative models’, (4) the process of ‘analysis-by-synthesis’, and (5) the crucial role of imagination in perception. In addition to these, I also point out that predictive processing echoes Kant’s general project in that it aims to explain how minds track causal structure in the world using only sensory data, and that it uses a reverse-engineer or ‘top-down’ method of analysis. I then locate a possible source of Kant’s influence on predictive processing by tracing the paradigm back to Hermann von Helmholtz, who saw himself as providing a scientific implementation of Kant’s conclusions. I conclude by arguing that predictive processing should not be regarded as a new paradigm but is more appropriately understood as the latest incarnation of an approach to perception and cognition initiated by Kant and refined by Helmholtz.
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