Consciousness as something that the brain learns to do
The Proceedings of the Annual Convention of the Japanese Psychological Association September 11, 2019 DOI: 10.4992/pacjpa.83.0_sl-002 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Theoretical or philosophical paper Peer reviewed |
|---|---|
| Key points | Argues that consciousness is a learned, prediction-driven capacity rather than a static neural property, and that first-order representations become conscious when targeted by higher-order metarepresentations that need not be conscious themselves. Proposes that these metarepresentations emerge through unconscious learning and plasticity, ground self-awareness, and share a prediction-driven process with theory of mind. |
Abstract
Starting from the radical idea that consciousness is something that the brain learns to do rather than a static property associated with some patterns of neural activity and not with others, I explore the links between theory of mind, self- awareness, and perceptual awareness. Considering first the link between self-awareness and perceptual awareness, I suggest, congruently with the Higher-Order Thought （HOT） Theory of consciousness developed by Rosenthal, that first- order representations are conscious if and only if they are targeted by appropriate higher-order representations, that is, metarepresentations. The main functions of such metarepresentations are （1） to redescribe the tar-get first-order representations in such a way as to explicitly indicate mental attitude, and （2） to subserve prediction-driven control mechanisms. Crucially, （1） such metarepresentations do not need to be conscious themselves （as in HOT）, and （2） they emerge over training and development as a result of unconscious learning and plasticity mechanisms. Metarepresentations thus form the basis for self- awareness because they enable agents to “know that they know”, that is, to be acquainted with the geography of their own representational systems. Next, I turn to the link between self-awareness and theory of mind. The main argument here is that developing infants continuously attempt to predict not only the consequences of their actions on the world, but also the consequences of their actions on other agents. But there is a crucial difference between interactions with the world and interactions with other agents: Understanding the reactions of the latter, unlike the former, requires assuming the existence of hidden, unobservables states. Thus, when one learns to interact with other agents, one also forms mental models of the internal states of those other agents. But this is the same prediction- driven process as involved in forming metarepresentations of one own’s mental states. There is thus a direct link between theory of mind and self-awareness, a point that was forcefully argued by Carruthers. Hence we bridge the gap from theory of mind to perceptual awareness through the joint involvement of prediction-driven, learned interactive loops that make it possible for agents to better anticipate the consequences of their actions. I illustrate these arguments with computational models and empirical data, and link these ideas to other theoretical renderings.