No CrossRef data available.
Article contents
Action-oriented predictive processing and the neuroeconomics of sub-cognitive reward
Published online by Cambridge University Press: 10 May 2013
Abstract
Clark expresses reservations about Friston's reductive interpretation of action-oriented predictive processing (AOPP) models of cognition, but he doesn't link these reservations to specific alternatives. Neuroeconomic models of sub-cognitive reward valuation, which, like AOPP, integrate attention with action based on prediction error, are such an alternative. They interpret reward valuation as an input to neocortical processing instead of reducing it.
- Type
- Open Peer Commentary
- Information
- Copyright
- Copyright © Cambridge University Press 2013
References
Everitt, B., Dickinson, A. & Robbins, T. (2001) The neuropsychological basis of addictive behavior. Brain Research Reviews
36:129–38.Google Scholar
Friston, K. (2011a) Embodied inference: Or I think therefore I am, if I am what I think. In: The implications of embodiment (Cognition and Communication), ed. Tschacher, W. & Bergomi, C., pp. 89–125. Imprint Academic.Google Scholar
Lee, D. & Wang, X.-J. (2009) Mechanisms for stochastic decision making in the primate frontal cortex: Single-neuron recording and circuit modeling. In: Neuroeconomics: Decision making and the brain, ed. Glimcher, P., Camerer, C., Fehr, E. & Poldrack, R., pp. 481–501. Elsevier.Google Scholar
Platt, M. & Glimcher, P. (1999) Neural correlates of decision variables in parietal cortex. Nature
400:233–38.CrossRefGoogle ScholarPubMed
Ross, D., Sharp, C., Vuchinich, R. & Spurrett, D. (2008) Midbrain mutiny: The picoeconomics and neuroeconomics of disordered gambling. MIT Press.Google Scholar
Schultz, W., Dayan, P. & Montague, P. R. (1997) A neural substrate of prediction and reward. Science
275:1593–99.Google Scholar
Target article
Whatever next? Predictive brains, situated agents, and the future of cognitive science
Related commentaries (30)
Action-oriented predictive processing and the neuroeconomics of sub-cognitive reward
Active inference and free energy
Affect and non-uniform characteristics of predictive processing in musical behaviour
Applications of predictive control in neuroscience
Attention and perceptual adaptation
Attention is more than prediction precision
Backwards is the way forward: Feedback in the cortical hierarchy predicts the expected future
Bayesian animals sense ecological constraints to predict fitness and organize individually flexible reproductive decisions
Distinguishing theory from implementation in predictive coding accounts of brain function
Expecting ourselves to expect: The Bayesian brain as a projector
Extending predictive processing to the body: Emotion as interoceptive inference
God, the devil, and the details: Fleshing out the predictive processing framework
Grounding predictive coding models in empirical neuroscience research
Interactively human: Sharing time, constructing materiality
Maximal mutual information, not minimal entropy, for escaping the “Dark Room”
Neuronal inference must be local, selective, and coordinated
Perception versus action: The computations may be the same but the direction of fit differs
Personal narratives as the highest level of cognitive integration
Prediction, explanation, and the role of generative models in language processing
Predictions in the light of your own action repertoire as a general computational principle
Schizophrenia-related phenomena that challenge prediction error as the basis of cognitive functioning
Skull-bound perception and precision optimization through culture
Sparse coding and challenges for Bayesian models of the brain
The brain is not an isolated “black box,” nor is its goal to become one
The problem with brain GUTs: Conflation of different senses of “prediction” threatens metaphysical disaster
Two kinds of theory-laden cognitive processes: Distinguishing intransigence from dogmatism
Unraveling the mind
What else can brains do?
When the predictive brain gets it really wrong
Whenever next: Hierarchical timing of perception and action
Author response
Are we predictive engines? Perils, prospects, and the puzzle of the porous perceiver