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Toward mechanistic models of action-oriented and detached cognition

Published online by Cambridge University Press:  30 June 2016

Giovanni Pezzulo
Giovanni Pezzulo*
Affiliation:
Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy. [email protected]://www.istc.cnr.it/people/giovanni-pezzulo
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Abstract

To be successful, the research agenda for a novel control view of cognition should foresee more detailed, computationally specified process models of cognitive operations including higher cognition. These models should cover all domains of cognition, including those cognitive abilities that can be characterized as online interactive loops and detached forms of cognition that depend on internally generated neuronal processing.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e130
Copyright
Copyright © Cambridge University Press 2016 

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References

Anderson, M. L. (2014) After phrenology: Neural reuse and the interactive brain. MIT Press.CrossRefGoogle Scholar
Ashby, W. R. (1952) Design for a brain. Wiley.Google Scholar
Attias, H. (2003) Planning by Probabilistic Inference. Proceedings of the Ninth International Conference on Artificial Intelligence and Statistics, Key West, FL. January 2003, ed. Bishop, C. M. & Frey, B. J.. Society for Artificial Intelligence and Statistics.Google Scholar
Barsalou, L. W. (1999) Perceptual symbol systems. Behavioral and Brain Sciences 22(4):577–660.CrossRefGoogle ScholarPubMed
Barsalou, L. W. (2008) Grounded cognition. Annual Review of Psychology 59:617–45.Google Scholar
Buzsáki, G. & Moser, E. I. (2013) Memory, navigation and theta rhythm in the hippocampal-entorhinal system. Natural Neuroscience 16:130–38. doi: 10.1038/nn.3304.Google Scholar
Buzsáki, G., Peyrache, A. & Kubie, J. (2015) Emergence of cognition from action. Cold Spring Harbor Symposia on Quantitative Biology 79:41–50. doi: 10.1101/sqb.2014.79.024679.CrossRefGoogle Scholar
Chemero, A. (2009) Radical embodied cognitive science. MIT Press.Google Scholar
Cisek, P. (1999) Beyond the computer metaphor: Behaviour as interaction. Journal of Consciousness Studies 6(11–12):125–42.Google Scholar
Cisek, P. (2006) Integrated neural processes for defining potential actions and deciding between them: A computational model. The Journal of Neuroscience 26:9761–70.CrossRefGoogle ScholarPubMed
Cisek, P. & Kalaska, J. F. (2010) Neural mechanisms for interacting with a world full of action choices. Annual Review of Neuroscience 33:269–98.Google Scholar
Clark, A. (1998) Being there. Putting brain, body, and world together. MIT Press.Google Scholar
Clark, A. (2013b) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences 36(3):181–204. doi: 10.1017/S0140525X12000477.Google Scholar
Clark, A. & Chalmers, D. J. (1998) The extended mind. Analysis 58:10–23.CrossRefGoogle Scholar
Clark, A. & Grush, R. (1999) Towards a cognitive robotics. Adaptive Behavior 7:5–16.CrossRefGoogle Scholar
Craik, K. (1943) The nature of explanation. Cambridge University Press.Google Scholar
Dehaene, S. (2005) Evolution of human cortical circuits for reading and arithmetic: The “neuronal recycling” hypothesis. In: From monkey brain to human brain: A Fyssen Foundation symposium, ed. Dehaene, S., Duhamel, J.-R., Hauser, M. D. & Rizzolatti, G., pp. 133–58. MIT Press.CrossRefGoogle Scholar
Diba, K. & Buzsáki, G. (2007) Forward and reverse hippocampal place-cell sequences during ripples. Nature Neuroscience 10:1241–42. doi: 10.1038/nn1961.CrossRefGoogle ScholarPubMed
Dragoi, G. & Tonegawa, S. (2011) Preplay of future place cell sequences by hippocampal cellular assemblies. Nature 469:397–401.Google Scholar
Engel, A. K., Maye, A., Kurthen, M. & König, P. (2013) Where's the action? The pragmatic turn in cognitive science. Trends in Cognitive Sciences 17:202–209.Google Scholar
Friston, K., Daunizeau, J., Kilner, J. & Kiebel, S. J. (2010) Action and behavior: A free-energy formulation. Biological Cybernetics 102:227–60.Google Scholar
Friston, K., Rigoli, F., Ognibene, D., Mathys, C., FitzGerald, T. & Pezzulo, G. (2015) Active inference and epistemic value. Cognitive Neuroscience 6(4):187–214.Google Scholar
Friston, K. J., Daunizeau, J., Kilner, J. & Kiebel, S. J. (2010) Action and behavior: A free-energy formulation. Biological Cybernetics 102:227–60. doi: 10.1007/s00422-010-0364-z.Google Scholar
Gallagher, S. (2005) How the body shapes the mind. Oxford University Press.Google Scholar
Gibson, J. J. (1977) The theory of affordances. In: Perceiving, acting, and knowing: Toward an ecological psychology, ed. Shaw, R. & Bransford, J., pp. 62–82. Erlbaum.Google Scholar
Glenberg, A. (1997) What memory is for. Behavioral and Brain Sciences 20:1–55.Google Scholar
Grush, R. (2004) The emulation theory of representation: Motor control, imagery, and perception. Behavioral and Brain Sciences 27:377–96.Google Scholar
Gupta, A. S., van der Meer, M. A., Touretzky, D. S. & Redish, A. D. (2010) Hippocampal replay is not a simple function of experience. Neuron 65:695–705.Google Scholar
Jeannerod, M. (2006) Motor cognition. Oxford University Press.Google Scholar
Johnson, A. & Redish, A. D. (2007) Neural ensembles in CA3 transiently encode paths forward of the animal at a decision point. Journal of Neuroscience 27:12176–89.Google Scholar
Kirsh, D. (2010) Thinking with external representations. AI Soc.Google Scholar
Lisman, J. (2015) The challenge of understanding the brain: Where we stand in 2015. Neuron 86:864–82. doi: 10.1016/j.neuron.2015.03.032.Google Scholar
Maye, A. & Engel, A. K. (2011) A discrete computational model of sensorimotor contingencies for object perception and control of behavior. IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9–13, 2011, pp. 3810–15. IEEE. doi: 10.1109/ICRA.2011.5979919.Google Scholar
O'Regan, K. & Noe, A. (2001) A sensorimotor account of vision and visual consciousness. Behavioral and Brain Sciences 24(5):939–73.Google Scholar
Pezzulo, G. (2011) Grounding procedural and declarative knowledge in sensorimotor anticipation. Mind and Language 26:78–114.Google Scholar
Pezzulo, G. (2012) An active inference view of cognitive control. Frontiers in Psychology 3:478. doi: 10.3389/fpsyg.2012.00478.CrossRefGoogle ScholarPubMed
Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K. & Spivey, M. (2011) The mechanics of embodiment: A dialogue on embodiment and computational modeling. Frontiers in Cognition 2:1–21.Google Scholar
Pezzulo, G., Barsalou, L. W., Cangelosi, A., Fischer, M. H., McRae, K. & Spivey, M. J. (2013) Computational grounded cognition: A new alliance between grounded cognition and computational modeling. Frontiers in Psychology 3:612. doi: 10.3389/fpsyg.2012.00612.Google Scholar
Pezzulo, G. & Castelfranchi, C. (2009) Thinking as the control of imagination: A conceptual framework for goal-directed systems. Psychological Research 73:559–77.Google Scholar
Pezzulo, G., Rigoli, F. & Friston, K. (2015) Active inference, homeostatic regulation and adaptive behavioural control. Progress in Neurobiology 134:17–35. doi: 10.1016/j.pneurobio.2015.09.001.Google Scholar
Pezzulo, G., van der Meer, M. A. A., Lansink, C. S. & Pennartz, C. M. A. (2014) Internally generated sequences in learning and executing goal-directed behavior. Trends in Cognitive Sciences 18:647–57. doi: 10.1016/j.tics.2014.06.011.CrossRefGoogle ScholarPubMed
Pfeifer, R. & Scheier, C. (1999) Understanding intelligence. MIT Press.Google Scholar
Pfeiffer, B. E. & Foster, D. J. (2013) Hippocampal place-cell sequences depict future paths to remembered goals. Nature 497:74–79. doi: 10.1038/nature12112.Google Scholar
Powers, W. (1973) Behavior, the control of perception. Aldine de Gruyter.Google Scholar
Rosenblueth, A., Wiener, N. & Bigelow, J. (1943) Behavior, purpose and teleology. Philosophy of Science 10(1):18–24.Google Scholar
Schacter, D. L., Addis, D. R. & Buckner, R. L. (2007) Remembering the past to imagine the future: The prospective brain. Nature Reviews Neuroscience 8:657–61.Google Scholar
Schacter, D. L., Addis, D. R., Hassabis, D., Martin, V. C., Spreng, R. N. & Szpunar, K. K. (2012) The future of memory: Remembering, imagining, and the brain. Neuron 76:677–94. doi: 10.1016/j.neuron.2012.11.001.Google Scholar
Scott, S. H. (2012) The computational and neural basis of voluntary motor control and planning. Trends in Cognitive Sciences 16:541–49. doi: 10.1016/j.tics.2012.09.008.Google Scholar
Seth, A. K. (2015) The cybernetic Bayesian brain – From interoceptive inference to sensorimotor contingencies. In: Open MIND: 35(T), ed. Metzinger, T. & Windt, J. M.. MIND Group. doi: 10.15502/9783958570108.Google Scholar
Shadmehr, R. & Mussa-Ivaldi, F. A. (2012) Biological learning and control. How the brain builds representations, predicts events and makes decisions. MIT Press.Google Scholar
Spivey, M. (2007) The continuity of mind. Oxford University Press.Google Scholar
Stoianov, I., Genovesio, A. & Pezzulo, G. (2016) Prefrontal goal codes emerge as latent states in probabilistic value learning. Journal of Cognitive Neuroscience 28(1):140–57. doi: 10.1162/jocn_a_00886.CrossRefGoogle ScholarPubMed
Toussaint, M. (2009) Probabilistic inference as a model of planned behavior. Künstliche Intelligenz. 3(9):23–29.Google Scholar
Varela, F. J., Thompson, E. T. & Rosch, E. (1992) The embodied mind: Cognitive science and human experience. MIT Press.Google Scholar
Verschure, P., Pennartz, C. M. A. & Pezzulo, G. (2014) The why, what, where, when and how of goal-directed choice: Neuronal and computational principles. Philosophical Transactions of the Royal Society B: Biological Sciences 369:20130483.Google Scholar
Wiener, N. (1948) Cybernetics: Or control and communication in the animal and the machine. MIT Press Google Scholar
Wikenheiser, A. M. & Redish, A. D. (2015) Hippocampal theta sequences reflect current goals. Nature Neuroscience 18:289–94.Google Scholar