Dopamine, Affordance and Active Inference

By Karl J. Friston, Tamara Shiner, Thomas H. B. FitzGerald, Joseph M. Galea, Rick A Adams, Harriet R. Brown, R. J. Dolan, Rosalyn J. Moran, Klaas E. Stephan, Sven Bestmann. PLoS Comput. Biol., 2012

361 citations recorded by the source corpus.

The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/d8ca79626badba6da19de8d6dcee12bfeb8df130

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

Citations in the corpus

The Computational Anatomy of Psychosis (2013, background): “We have proposed that this dependency mediates attention and action selection in hierarchical processing (Feldman and Friston, 2010; Friston et al., 2012).”
Active interoceptive inference and the emotional brain (2016, background): “This contextual aspect of predictive coding has been associated with attentional gain control in sensory processing (41, 49) and has been discussed in terms of affordance in the setting of action selection (50-52).”
An aberrant precision account of autism (2014, neutral): “May 2014 | Volume 8 | Article 302 | 5 mediate the precision of cues (with affordance) that induce behavior (Friston et al., 2012a).”
Merging second-person and first-person neuroscience (2013, neutral): “This general capability of affordance-responsiveness may correspond to brain activities that heavily interact and need to be understood in rapidly communicating neurocircuitries (Freeman 2000; Friston 2011; Friston et al. 2012; Thelen & Smith 1994) rather than separate brain areas, which in turn exp”
Busting Out: Predictive Brains, Embodied Minds, and the Puzzle of the Evidentiary Veil (2017, background): “Contextually recruited patterns of precision weighting thus accomplish a form of set-selection or strategy switching – an effect that has been practically demonstrated in some simple simulations of cued reaching (K. J. Friston et al., 2012)).”
Ever-changing cycles of musical pleasure: The role of dopamine and anticipation. (2012, neutral): “…cognitive neuroscience have also found the Bayesian framework to be fruitful (Brown & Friston, 2012; Edwards, Adams, Brown, Parees, & Friston, 2012; Friston et al., 2012; Hohwy, 2012; Hohwy, Roepstorff, & Friston, 2008; Kilner, Friston, & Frith, 2007; Nazimek, Hunter, & Woodruff, 2012; Schiffer,…”
From cognitivism to autopoiesis: towards a computational framework for the embodied mind (2016, background): “…(Chemero 2011), FEP renders a productive union of the embodied cognition and information theory, allowing the enactivist not only to describe the importance of the body, but to also build models of the brain-body-world relationship (See Friston et al. 2012a,b for one illustrative example).”
How Prediction Errors Shape Perception, Attention, and Motivation (2012, background): “For example, dopaminergic firing signaling reward PEs have been proposed to serve as a supervised learning signal determining the weight of the associative strength between actions and stimuli (Schultz and Dickinson, 2000; Friston et al., 2012), as we will discuss in the next section.”
Affective Value in the Predictive Mind (2017, background): “In complexer animals, “the gross bodily form, biomechanics, and gross initial neural architecture of the agent all form part of the (initial) ‘model’ and […] this model is further tuned by learning and experience” (Friston et al. 2012a), using the general-purpose PP mechanisms.”
The anticipating brain is not a scientist: the free-energy principle from an ecological-enactive perspective (2016, result): “All these references can also be found in for instance, Friston (2000, 2012, 2013a) and Friston et al. (2012). part by situating our ideas in relation to those of Hohwy, Friston and Clark, in order to highlight some key differences.”
The anatomy of choice: active inference and agency (2013, methodology): “…treatments of hierarchical Bayesian inference (Mathys et al., 2011), from theoretical neurobiology (Frank et al., 2007; Fletcher and Frith, 2009; Friston et al., 2012b; Pellicano and Burr, 2012) and from empirical studies (Fiorillo et al., 2008; Coull et al., 2011; Galea et al., 2012; Zokaei et…”
Ecological-Enactive Cognition as engaging with a field of relevant affordances (2018, background): “2011; Withagen, Araújo and De Poel 2017), affective science (Frijda, Ridderinkhof, and Rietveld 2014), and neuroscience (Friston et al. 2012; Schilbach et al. 2013; Dotov 2014; Dotov et al. 2010; Kirchhoff 2015; Jelic 2016; Pezzulo and Cisek 2016).”