Trends in Neurosciences
OpinionUseful misrepresentation: perception as embodied proactive inference
Section snippets
Better safe than sorry: adaptive biases in perception
Imagine walking in a forest and coming across a seemingly ambiguous object lying on the ground, for instance a thin, elongated, and curved dark shape. Upon encountering this object, the task of your brain is to infer what it is so that it can formulate an appropriate behavioural response (Figure 1). According to predictive processing (PP) (see Glossary), perception of this object will entail a process of approximate Bayesian inference [1., 2., 3.], which combines sensory evidence (‘likelihood’)
Active inference, embodied prediction, and pragmatic perceivers
Biological agents are characterised by the ability to maintain themselves within a limited range of states that are compatible with continued survival [9]. This can be described in information-theoretical terms, where organisms preferentially occupy a set of high-probability states through minimising ‘surprising’ sensory exchanges with the environment. According to PP, this is achieved via the deployment of a hierarchical generative model, which minimises the prediction error (or average
Attention and expectations: are they functionally orthogonal?
Perceptual decision-making is optimised by distinct underlying computational mechanisms. Signal detection theory [23] models and distinguishes these influences in terms of sensitivity, the discriminability of a stimulus (d’), and bias, the probability of a given response (C). While both may improve perceptual accuracy through improving the detection of a target stimulus, they are dissociable in terms of their effects upon detecting a target’s absence, where increased sensitivity results in a
Expectations are utility driven: support from the empirical literature
Defending the claim that expectations are utility driven is complicated by the fact that accuracy and utility often coincide in perceptual inference. However, the probability-driven versus utility-driven models should lead to divergent predictions under conditions where accuracy and utility conflict with one another [8]. Empirically, this has been achieved by evaluating the effects of expectations in relation to ambiguous stimuli that give rise to percepts of comparable probability yet of
At what cost? Utility biases efficiently minimize interoceptive prediction error
On the surface, utility biases may seem to contradict the principle of prediction error minimisation, since they systematically lead organisms towards predictions that, on average, deviate from actual states in the world. However, they may be suitably accommodated once we revisit the notion that prediction error can arise in both the external and internal milieu. With this in mind, we view these respective models to be minimizing two conflicting sources of prediction error. On the one hand,
Concluding remarks
The core function of cognition is to successfully regulate the internal milieu [14], and perceptual models are thought to emerge as a consequence of this imperative [68]. We suggest that this optimisation is mediated by biases in the structure and tuning of predictive information in the brain, leading to internal models that usefully misrepresent the environment. Allostasis thus plays an essential role in constraining perceptual outcomes, consistent with the notion that the ‘brain recovers the
Acknowledgements
We acknowledge the Deutscher Akademischer Austauschdienst and the Berlin School of Mind and Brain for scholarship funding to J.M.M. and the Berlin Institute of Health for a Clinical Fellowship to P.S. in relation to this research. P.S. is further supported by grants from Deutsche Forschungsgemeinschaft (STE 1430/8-1 and STE 1430/9-1). Special thanks to Chiara Caporuscio, Marika Constant, and the members from the Visual Perception Laboratory for the fruitful discussions and motivational support.
Declaration of interests
The authors declare no competing interests in relation to this work.
Glossary
- Active inference
- a framework for incorporating the role of action into the PP framework. While perception functions to change one’s predictions of the world to accommodate the sensory evidence, action functions to change the sensory input to fulfil these predictions. Action can thus be cast as a type of ‘self-fulfilling prophecy’ where we actively engage with and sample the world to bring about the very predictions that our internal model deploys.
- Allostasis
- the process of preserving physiological
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2022, Consciousness and CognitionCitation Excerpt :Accordingly, theoretical explanations of context-effects on facial expression perception increasingly focus on predictive processing (e.g., Otten et al., 2017; Trapp, Schweinberger, Hayward, & Kovács, 2018; Pereira, Barbosa, de Haan, & Ferreira-Santos, 2019; Feldman Barrett, 2016). To reiterate the Bayesian-brain view of visual perception in a nutshell: Rather than a passive process providing us with an objective, veridical image of the physical world, perception is viewed as an active, constructive process with the purpose of providing a useful basis for adaptive behavior situated in our environment (Buzsáki, 2019; Lupyan & Clark, 2015; Seth & Tsakiris, 2018), even if that sometimes means to ”usefully misrepresent” the world (Martin, Solms, & Sterzer, 2021). In this view, the content of perception is specified through predictive processing–as the brain’s ”best guess” about the causes of its sensory input that minimizes the difference (prediction error) between actual sensory signals and the predictions based on constantly updated predictive models (Friston, 2009; Clark, 2013; Otten et al., 2017).
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