ReviewThe free-energy self: A predictive coding account of self-recognition
Highlights
► Self-recognition underpinned by Bayesian prediction and prediction error signals. ► Illusory ownership of others’ bodies underpinned by multisensory explaining away. ► Self-recognition is plastic and malleable during multisensory input. ► Self-processed by multimodal–unimodal interactions in non-self-specific regions.
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.
Section snippets
The free-energy principle
The free-energy principle states that biological agents resist a natural tendency towards disorder in a constantly changing environment (Friston, 2005). The phenotype of an organism defines the extent of the physiological and sensory states that an agent can be in and therefore the boundaries of what states that an organism can occupy. There is therefore a high probability that an agent (and its brain) will be in a small set of states and a low probability that it will be in a larger set of
Hierarchical predictive codes
An important aspect of the free energy principle is that it makes assumptions about the organisation of sensory systems and also about the flow of information in these systems (Friston, 2008a, Friston and Kiebel, 2009b). These assumptions can be summarised within a “predictive coding” model, a framework that can be used to explain the architecture of sensory processing (Clark, in press, Lee and Mumford, 2003, Rao and Ballard, 1999). Previous accounts have discussed how visual, auditory and
Free-energy self-recognition
The assumptions of the free-energy principle have implications for the neural and psychological processes that might underpin self-recognition. In this section we wish to highlight how its assumptions lead to several predictions about the mechanisms that will underpin self-recognition. At this point we will provide an overview of how the model could explain self-recognition in an abstract manner and not directly discuss the self-processing literature. In later sections we will discuss the core
The psychological self
As stated above, an important aspect of the free-energy principle is that the brain can minimise surprise by updating probabilistic representations (Friston, 2005). Therefore, at the core of this theory is the notion that probabilistic representations are plastic and updated when new information reveals a discrepancy between a predicted sensory state and the actual sensory state. Self-recognition should therefore also be plastic, such that surprising sensory events may be explained away by
The anatomy of the self
So far we have argued that self-stimuli are recognised as “me” when surprise in one sensory system is explained away at a multimodal node which processes information from a system in which there is minimal surprise. The information processed at multimodal nodes will therefore be highly abstract, i.e., they will process high level prior information about self-stimuli and explain away surprise in unimodal sensory systems by labelling a stimulus as “me”. This view is therefore predicated on three
Future directions and caveats
The aim of this article was to provide a new theoretical perspective on the cortical mechanisms that underlie self-recognition, in order to account for previous findings and provide a novel framework for future research. In doing so, we have largely looked for and reported evidence that supports some of the principles of free-energy and elsewhere have simply stated what this theory would assume, with limited direct evidence. In this section, we raise some caveats related to this discussion. In
Summary
In this article, we have attempted to illuminate how the free-energy principle may account for self-recognition. To conform to the principles of predictive coding and free-energy, we have suggested that recognising one's self is a process of associating the unimodal properties of the body (e.g., the visual properties of one's hand), with other information about the body from any sensory system. Such associations will be probabilistic such that one's own body is the most likely to be one's own.
Acknowledgements
This study was funded by the European Research Council Starting Investigator Grant (ERC-2010-StG-262853) to MT. The authors would like to thank Dr. Lara Maister for useful discussions during the preparation of the manuscript and the two reviewers for helping us nuance our arguments.
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