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RADICAL Report Summary

Project ID: 340718
Funded under: FP7-IDEAS-ERC
Country: Belgium

Periodic Report Summary 2 - RADICAL (The Radical Plasticity Thesis: How we learn to be conscious)

RADICAL is dedicated to the development of a new theory of consciousness — what it feels like to have experiences. Its overarching goal is to characterize the computational principles that differentiate conscious from unconscious cognition. To do so, we adopt a resolutely dynamical perspective, suggesting that consciousness, rather than being a single static property associated with some neural states and not others, is instead something that the brain learns to do. This motivates an experimental approach focused on the dynamics of change, at different time scales. Theoretically, RADICAL suggests that consciousness arises as a result of the brain’s continuous attempts at predicting not only the consequences of action on the world and on other agents, but also the consequences of activity in one cerebral region on activity in other regions. By this account, the brain continuously and unconsciously learns to redescribe its own activity to itself, so developing systems of metarepresentations that characterize and qualify their target representations. Such redescriptions form the basis of conscious experience, and also subtend successful control of action. By this hypothesis, consciousness critically depends on a cognitive system’s ability to learn about (1) the effects of its actions on the environment, (2) the effects of its actions on other agents, and on (3) the effects of activity in one cerebral region on other cerebral regions. On this view, the extent to which a representation is conscious depends in a graded manner on (1) properties such as its stability in time, its strength, and its distinctiveness and on (2) the existence of metarepresentations that redescribe the system’s representations to itself. Crucially, these properties accrue as a result of learning and plasticity processes, which are in turn viewed as mandatory processes that always accompany information processing. Thus, the core idea is that a cognitive system becomes a conscious cognitive system in virtue of its ability to continuously learn to represent (and hence, predict) the consequences of its own activity. Thus far, we have carried out (1) computational modelling work aimed at instantiating these ideas in the form of an implemented metacognitive neural network, (2) experimental work aimed at documenting how first-order processing interacts with metacognitive processing, in different domains (from perception to executive control) and over training, and (3) experimental work documenting the influence that high-level metacognitive beliefs (induced through suggestion or placebo) or instructions (i.e., commands) exert on first-order processing and on conscious experience. The highlight of this first period is the demonstration (Caspar et al., 2016) that our implicit sense of agency — a core aspect of what it means to be a conscious agent — is reduced when obeying orders.

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