Recognising and representing one’s self as distinct from others is a fundamental component of self-awareness. However, current theories of self-recognition are not embedded within global theories of cortical function and therefore fail to provide a compelling explanation of how the self is processed. We present a theoretical account of the neural and computational basis of self-recognition that is embedded within the free-energy account of cortical function. In this account one’s body is processed in a Bayesian manner as the most likely to be “me”. Such probabilistic representation arises through the integration of information from hierarchically organised unimodal systems in higher-level multimodal areas. This information takes the form of bottom-up “surprise” signals from unimodal sensory systems that are explained away by top-down processes that minimise the level of surprise across the brain. We present evidence that this theoretical perspective may account for the findings of psychological and neuroimaging investigations into self-recognition and particularly evidence that representations of the self are malleable, rather than fixed as previous accounts of self-recognition might suggest.

Key words: self-recognition, self-awareness, voice recognition, face recognition, body ownership, bayesian, free energy, predictive coding, prediction error, rubber hand illusion, enfacement

Ten years ago, a group of researchers, led by Francisco Varela, were proposing an alternative vision of the immune system main behavior and function. I was part of this group. This new vision saw the immune system not as behaving distinctively with self and non-self or according to any dichotomy imposed a priori and from outside (the self-recognition vision), but rather as behaving in a unique way. From this indifferent behavior, any external impact would progressively been treated in two different ways, reactive and tolerant, but now, consequently and from inside the system (the self-assertion view). This paper will recall, through a very artificial simulation, the difference existing between these two visions. Also at that time, we believed that, from an engineering perspective, this new vision, emphasizing more the adaptability and the need for endogenous constraints than the recognition and the defensive ability, although less obvious to accept than the classical defensive one, should be more beneficial. These last ten years proved that we haven’t been convincing enough, and in this paper I resume the crusade.

This paper provides a conceptual framework to accommodate important recent developments in immunology (genetic determination, cellular interactions, suppression). The basic idea is to look at the immune system as a closed network of interactions which self-determines its ongoing pattern of stability and its capacities of interaction with its environment. Thus, all immune events are understood as a form of self-recognition, and whatever falls outside this domain, shaped by genetics and ontogeny, is simply non-sensical. This paradigm, stemming from the ideas of Jerne, represents almost a logical inversion of the Burnetian idea of self-discrimination. A detailed discussion of the immunological evidence that substantiates this view is presented, together with some new concepts (eigenbehavior, cognitive domains). Although the paper is addressed to biologists and immunologists, we make extensive use of system-theoretic notions in a non-mathematical form (recursion, nets and trees, self-organization).

Key words: immune networks, models, biological, immunosuppression, anti-idiotipic antibodies, immunoregulation, recursion