The free-energy self: A predictive coding account of self-recognition

Abstract

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.

Introduction

The awareness of one's self and the concepts used to depict it are steeped in intellectual and scientific history. The ability to recognise one's own physical features in a mirror, or know that a voice is one's own is key for our self-awareness (Gallup, 1970), and also for our ability to communicate effectively with others (Bertenthal and Fischer, 1978). Such abilities are purportedly possessed by only a small selection of primate species, including humans (Reiss and Marino, 2001, Suarez and Gallup, 1981), and they are considered as behavioural markers of self-awareness. The question of what, if anything, makes the “self” special has led to a plethora of different research projects and hypotheses in psychological sciences and cognitive neuroscience (Devue and Bredart, 2011, Feinberg and Keenan, 2005, Gillihan and Farah, 2005, Legrand and Ruby, 2009). Despite extensive discourse in the literature, there has been a failure to reach a consensus across – or to large extent within – disciplines as to how the brain self-recognises. As a result there is also an absence of a theoretical framework which produces hypotheses which can be tested experimentally using neuroscientific methods. Despite the absence of a theoretical framework, attempts have been made to examine the neural mechanisms which underpin self-recognition (Legrand and Ruby, 2009). Such investigations have highlighted how many different areas, from primary unimodal sensory areas, to high-level multimodal association cortices are engaged when recognising one's self compared to the features of another (Devue and Bredart, 2011, Platek et al., 2008). However, recent reviews of this literature have concluded that the absence of a unifying theoretical framework has resulted in a largely incoherent picture of the circuits and mechanisms which are engaged during self-recognition.

Recently several reviews of the literature have noted the importance that efference copy (copies of multimodal sensori-motor commands which cause predictions across the brain about incoming sensory input) has in “self-processing”, although not specifically in self-recognition (Legrand and Ruby, 2009). Specifically they argue that there are no self-specific networks in the brain, but that self-awareness and self-recognition result from the integration of motor efference (copies of the of motor commands which generate predictions of the multisensory consequence of an action) with reafference (the actual sensory consequences of an action). Alternative accounts have suggested that it is the integration of interoceptive efference and reafference that create the sense of a self or a self “presence” (Seth et al., 2011). Such accounts provide a useful insight into how self-specific information processing may arise in the brain, without the involvement of circuits that are specialised for processing “self-information”. However, they do not deal with the more low-level and basic concept of how the brain processes an incoming visual, auditory, somatosensory, or interoceptive sensory stimuli as “me” and how such input participates in the recognition of different aspects of one's physical self, such as one's face, voice, body or its movement. In addition, many of the accounts of self-processing distinguish self information as special and therefore purportedly phenomenologically unique. As a result, it has been particularly difficult to embed theories of self-recognition and self-processing within theories of cortical function. Despite the aforementioned limitations, the salience of “self-processing” in human cognition and the wide network of areas that reported to be engaged during self-recognition, necessitates that theories of self-recognition are integrated within broad theories of cortical function.

In this paper we attempt to highlight how the free-energy principle, a recent attempt at a unifying theory of the brain, can explain many previous findings in self-recognition research (Friston, 2009). Within this framework we argue that self-recognition arises as a result of the brain's attempts to minimise the amount of free-energy (or ‘surprise’) in sensory systems in order to be in states where the environment is highly predictable. We outline how any aspect of the bodily self (e.g. the physical features of a face or one's voice, etc.), may be recognised as one's own through the optimisation of predictions about the sensory consequences of events occurring in the environment. Such optimisation occurs through the dynamic updating of Bayesian sensory predictions, when there is a discrepancy between a predicted sensory outcome and an actual sensory event (Clark, in press). Such discrepancies are referred to as prediction errors. Like previous accounts of self-awareness, we place importance on the processing of discrepancies between predicted sensory states and actual sensory states (re-afference). However, by employing the free-energy principle as our conceptual and mathematical toolbox, we suggest that recognising one's physical form goes beyond integrating sensori-motor efference and reafference. Recognition of one's self will arise when predictions in the visual or auditory system about upcoming sensory input are congruent with other body related sensory information that includes, but is not exclusive to, predictions made based on corollary discharge (for a description see below). Recognition of one's self will therefore arise through the integration of sensory information creating multimodal representations of the self. Recently, it has been suggested that important metapsychological processes such as self-awareness can be explained within a free-energy framework (Fotopoulou, 2012). Here, we explain how this principle may also be able to account for empirical studies investigating self-recognition, which act as important behavioural markers of self-awareness.

The theory presented here is embedded within the Bayesian theoretical and mathematical framework of the free-energy principle. Within this article we will not provide a full treatment of the mathematics of free-energy, as eloquent and thorough accounts have been provided elsewhere (Friston, 2005, Friston, 2008a, Friston, 2009, Friston and Kiebel, 2009b). However, a description of the theory is pertinent for our aims and thus the earlier sections of this paper will provide an outline of the free-energy principle as a global theoretical account of cortical function. In later sections we will then outline what predictions this theory's many components make about how the brain might self-recognise. We will then discuss the extent to which this theory can account for the findings of Psychological and Neuroscientific investigations of self-recognition.