Information is a central notion for cognitive sciences and neurosciences, but there is no agreement on what it means for a cognitive system to acquire information about its surroundings. In this paper, we approximate three influential views on information: the one at play in ecological psychology, which is sometimes called information for action; the notion of information as covariance as developed by some enactivists, and the idea of information as a minimization of uncertainty as presented by Shannon. Our main thesis is that information for action can be construed as covariant information, and that learning to perceive covariant information is a matter of minimizing uncertainty through skilled performance. We argue that the agent's cognitive system conveys information for acting in an environment by minimizing uncertainty about how to achieve intended goals in that environment. We conclude by reviewing empirical findings that support our view by showing how direct learning, seen as an instance of ecological rationality at work, is how mere possibilities for action are turned into embodied know-how. Finally, we indicate the affinity between direct learning and sense-making activity.Information is the bread and butter of cognitive science and neuroscience (CSN). Talk about information processing, control, storage, and retrieval is abundant in explanations of how cognitive systems can perform specific tasks and enable agents to interact intelligently with their environment. Accordingly, one of the defining tasks of CSN is to describe the mechanisms through which information is conveyed, an enterprise that, if successful, allows us to understand, predict, simulate, and intervene upon the cognitive capacities of real agents.The groundwork of the way information is understood by CSN today was laid by Shannon's (1948) mathematical account of information, which made possible nothing less than digital communication. Simply put, Shannon's theory defines information as entropy, which is the measure of average uncertainty of the selection of an encoded signal. The core idea of what became known as Shannon-information is that the less uncertain the selection of the encoded signal is at its receiver, the more information the signal carries from its sender. Noise, on the other hand, permanently corrupts the signal, thus increasing entropy and diminishing information. To summarize, information is a matter of minimization of uncertainty. Thus, CSN requires the Frontiers in Psychology | www.frontiersin.org 1

Ecological-enactive approaches to cognition aim to explain cognition in terms of the dynamic coupling between agent and environment. Accordingly, cognition of one's immediate environment (which is sometimes labeled "basic" cognition) depends on enaction and the picking up of affordances. However, ecological-enactive views supposedly fail to account for what is sometimes called "higher" cognition, i.e., cognition about potentially absent targets, which therefore can only be explained by postulating representational content. This challenge levelled against ecological-enactive approaches highlights a putative explanatory gap between basic and higher cognition. In this paper, we examine scientific cognition-a paradigmatic case of higher cognition-and argue that it shares fundamental features with basic cognition, for enaction and affordance selection are central to the scientific enterprise. Our argument focuses on modeling, and on how models promote scientific understanding. We base our argument on a non-representational account of scientific understanding and on the material engagement theory, for models are hereby conceived as material objects designed for scientific engagements. Having done so, we conclude that the explanatory gap is significantly less threatening to the ecological-enactive approach than it might appear.

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We advance a critical examination of two recent branches of the enactivist research program, namely, Radically Enactive Cognition and Linguistic Bodies. We argue that, although these approaches may look like diverging views within the wider enactivist program, when appraised in a conciliatory spirit, they can be interpreted as developing converging ideas. We examine how the notion of know-how figures in them to show an important point of convergence, namely, that the normativity of human cognitive capacities rests on shared know-how. Radical enactivism emphasizes the diachronic dimension of shared know-how, and linguistic bodies emphasize the synchronic one. Given that know-how is a normative notion, it is subject to success conditions. We then argue it implies basic content, which is the content of the successful ongoing interactions between agent(s) and environment. Basic content does not imply accuracy conditions and representational content, so it evades Hutto and Myin’s Hard Problem of Content. Moreover, this account is amenable to the central claim by Di Paolo et al. that the participatory sense-making relations at play in linguistic exchanges are explained in continuity with explanations of biological organization and sensorimotor engagements.