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Anticipation in Neurocybernetics

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Handbook of Anticipation

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Abstract

There is an increasing recognition in cognitive sciences of the need to account for the fundamental role of anticipation; an ability exhibited by living systems to orient toward future. Anticipation has been even proposed in psychology as the foundational building block of cognition. More recently, cognitive sciences and philosophy of mind have seen proliferation of theories varying in flavor and emphasis but common in postulating the fundamental role of predictive inference in the brain’s function. These accounts are steeped in computational cognitive paradigm and a contributing factor to their rapid gains in popularity is their consistency with the mechanistic view dominant in sciences. However, due to this very computational commitment, these accounts face serious philosophical problems, in common with other computational approaches, in their inability to provide a satisfactory explanation of the most fundamental properties of our mental life. Robert Rosen offered an alternative account of living systems, which inextricably links life and cognition. His postulate is to extend narrowly constructed mechanistic (and henceforth computational) account beyond classical Newtonian mechanics to a framework recognizing that living systems constitute a distinct class of complex systems and positioning anticipation as the fundamental characteristics distinguishing them from inanimate ones. Anticipating synchronization, a recently discovered intriguing behavior of some dynamical systems, offers a possibility of explaining anticipation from ground up, based on simple features abundant in living systems in general, and in the nervous system, in particular. A review of the studies investigating the anticipating synchronization and its extensions is provided, and a special emphasis is placed on the investigations concerned with its neurobiological plausibility. The core definition of anticipation according to Rosen postulates the ability of an organism to change its behavior in view of potential future outcomes. Thus, an overview is included of research on motion coordination that is grounded in dynamics and also concerned with the role of anticipation in movement.

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References

  • Aitchison, L., & Lengyel, M. (2017). With or without you: Predictive coding and Bayesian inference in the brain. Current Opinion in Neurobiology, 46, 219–227. https://doi.org/10.1016/j.conb.2017.08.010. (Computational Neuroscience).

    Article  Google Scholar 

  • Akrami, A., Kopec, C. D., Diamond, M. E., & Brody, C. D. (2018). Posterior parietal cortex represents sensory history and mediates its effects on behaviour. Nature, 554, 368–372. https://doi.org/10.1038/nature25510.

    Article  Google Scholar 

  • Bickhard, M. H. (2009). The biological foundations of cognitive science. New Ideas in Psychology, 27(1), 75–84. https://doi.org/10.1016/j.newideapsych.2008.04.001.

    Article  Google Scholar 

  • Brovelli, A., Ding, M., Ledberg, A., Chen, Y., Nakamura, R., & Bressler, S. L. (2004). Beta oscillations in a large-scale sensorimotor cortical network: Directional influences revealed by granger causality. Proceedings of the National Academy of Sciences, 101(26), 9849–9854. https://doi.org/10.1073/pnas.0308538101.

    Article  Google Scholar 

  • Buck, C. L. (2018). Hibernation: Life in the fast lane. eLife, 7, e35029.

    Article  Google Scholar 

  • Butz, M., Sigaud, O., Pezzulo, G., & Baldassarre, G. (2007). Anticipatory behavior in adaptive learning systems: From brains to individual and social behavior. Berlin/Heidelberg: Springer.

    Book  Google Scholar 

  • Calvo, O., Chialvo, D., EguĂ­luz, V., Mirasso, C., & Toral, R. (2004). Anticipated synchronization: A metaphorical linear view. Chaos, 14, 7–13. https://doi.org/10.1063/1.1620991.

    Article  Google Scholar 

  • Ciszak, M., Calvo, O., Masoller, C., Mirasso, C. R., & Toral, R. (2003). Anticipating the response of excitable systems driven by random forcing. Physical Review Letters, 90, 204102. https://doi.org/10.1103/PhysRevLett.90.204102.

    Article  Google Scholar 

  • Ciszak, M., Marino, F., Toral, R., & Balle, S. (2004a). Dynamical mechanism of anticipating synchronization in excitable systems. Physical Review Letters, 93, 114102. https://doi.org/10.1103/PhysRevLett.93.114102.

    Article  Google Scholar 

  • Ciszak, M., Toral, R., & Mirasso, C. (2004b). Coupling and feedback effects in excitable systems: Anticipated synchronization. Modern Physics Letters B, 18(23), 1135–1155. https://doi.org/10.1142/S0217984904007694.

    Article  Google Scholar 

  • Ciszak, M., Mirasso, C. R., Toral, R., & Calvo, O. (2009). Predict-prevent control method for perturbed excitable systems. Physical Review E, 79, 046203. https://doi.org/10.1103/PhysRevE.79.046203.

    Article  Google Scholar 

  • Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181–204. https://doi.org/10.1017/S0140525X12000477.

    Article  Google Scholar 

  • Clark, A. (2015). Surfing uncertainty: Prediction, action, and the embodied mind. Oxford University Press. Retrieved from https://books.google.co.uk/books?id=TnqECgAAQBAJ

  • Corron, N. J., Blakely, J. N., & Pethel, S. D. (2005). Lag and anticipating synchronization without time-delay coupling. Chaos: An Interdisciplinary Journal of Nonlinear Science, 15(2), 023110. https://doi.org/10.1063/1.1898597.

    Article  Google Scholar 

  • Dennett, D. (1996). Darwin’s dangerous idea: Evolution and the meanings of life. Simon & Schuster. Retrieved from https://books.google.co.uk/books?id=FvRqtnpVotwC

  • Eberle, H., Nasuto, S., & Hayashi, Y. (2018). Anticipation from sensation: Using anticipating synchronisation to stabilise a system with inherent sensory delay. Royal Society Open Science, 5, 171314.

    Article  Google Scholar 

  • Ekman, M., Kok, P., & de Lange, F. P. (2017). Time-compressed preplay of anticipated events in human primary visual cortex. Nature Communications, 8, 15276. https://doi.org/10.1038/ncomms15276.

    Article  Google Scholar 

  • Engstrom, D. (1996). Reaction-anticipation transitions in human perception-action patterns. Human Movement Science, 15, 809–832.

    Article  Google Scholar 

  • Haggard, P. (2017). Sense of agency in the human brain [Journal Article]. Nature Reviews Neuroscience, 18, 196. https://doi.org/10.1038/nrn.2017.14.

    Article  Google Scholar 

  • Hayashi, Y., & Kondo, T. (2013). Mechanism for synchronized motion between two humans in mutual tapping experiments: Transition from alternative mode to synchronization mode. Physical Review E, 88(2), 022715.

    Article  Google Scholar 

  • Hayashi, Y., & Sawada, Y. (2013). Transition from an anti-phase error-correction-mode to a synchronization mode in the mutual hand tracking. Physical Review E, 88(2), 022704.

    Article  Google Scholar 

  • Hayashi, Y., Tamura, Y., Sase, K., Sugawara, K., & Sawada, Y. (2011). Intermittently-visual tracking experiments reveal the roles of error-correction and predictive mechanisms in the human visual-motor control system. Transactions of the Society of Instrument and Control Engineers, 46(7), 391–400.

    Article  Google Scholar 

  • Hayashi, Y., Blake, J., & Nasuto, S. (2015). Anticipatory engineering: Anticipation in sensory-motor systems of human. In Anticipation across disciplines (Cognitive systems monographs). Switzerland: Springer International Publishing.

    Google Scholar 

  • Hayashi, Y., Nasuto, S. J., & Eberle, H. (2016). Renormalized time scale for anticipating and lagging synchronization. Physical Review E, 93(5), 052229.

    Article  Google Scholar 

  • Hesslow, G. (2012). The current status of the simulation theory of cognition. Brain Research, 1428, 71–79. https://doi.org/10.1016/j.brainres.2011.06.026. Retrieved from http://www.sciencedirect.com/science/article/pii/S0006899311011309. (The Cognitive Neuroscience of Thought).

  • Ikegami, T., Hirashima, M., Taga, G., & Nozaki, D. (2010). Asymmetric transfer of visuomotor learning between discrete and rhythmic movements. The Journal of Neuroscience, 30(12), 4515–4521.

    Article  Google Scholar 

  • Ishida, F., & Sawada, Y. (2013). Human hand moves proactively to the external stimulus; An evolutional strategy for minimizing transient error. Physical Review E, 93, 168105.

    Google Scholar 

  • Jordan, D., Smith, P., & Smith, P. (2007). Nonlinear ordinary differential equations: An introduction for scientists and engineers. Oxford: Oxford University Press. Retrieved from https://books.google.co.uk/books?id=KpASDAAAQBAJ

  • Kawato, M. (1999). Internal models for motor control and trajectory planning. Current Opinion in Neurobiology, 9, 718.

    Article  Google Scholar 

  • Khalil, H. (2002). Nonlinear systems (3rd ed.). New Jersey: Prentice Hall.

    Google Scholar 

  • Liang, H., & Wang, H. (2003). Top-down anticipatory control in prefrontal cortex. Theory in Biosciences, 122(1), 70–86. https://doi.org/10.1007/s12064-003-0038-7.

    Article  Google Scholar 

  • Louie, A. H. (2009). More than life itself: A synthetic continuation in relational biology. ontos verlag, Frankfurt [now De Gruyter, Berlin].

    Google Scholar 

  • Louie, A. H. (2010). Robert Rosen’s anticipatory systems. Foresight, 12(3), 18–29.

    Article  Google Scholar 

  • Louie, A. H. (2019). Relational biology. In R. Poli (Ed.), Handbook of anticipation: Theoretical and applied aspects of the use of future in decision making (pp. 1–28). Cham: Springer International Publishing.

    Google Scholar 

  • Louie, A. H., & Poli, R. (2019). Complex systems. In R. Poli (Ed.), Handbook of anticipation: Theoretical and applied aspects of the use of future in decision making (pp. 1–19). Cham: Springer International Publishing.

    Google Scholar 

  • Marzen, S. E., & Crutchfield, J. P. (2018). Optimized bacteria are environmental prediction engines. Phys. Rev. E 98, 012408.

    Google Scholar 

  • Mates, J. (1994). A model of synchronization of motor acts to a stimulus sequence. I. Timing and error corrections. Biological Cybernetics, 70(5), 463–473.

    Article  Google Scholar 

  • Matias, F. S., Carelli, P. V., Mirasso, C. R., & Copelli, M. (2011). Anticipated synchronization in a biologically plausible model of neuronal motifs. Physical Review E, 84, 021922. https://doi.org/10.1103/PhysRevE.84.021922.

    Article  Google Scholar 

  • Matias, F. S., Gollo, L. L., Carelli, P. V., Bressler, S. L., Copelli, M., & Mirasso, C. R. (2014). Modeling positive granger causality and negative phase lag between cortical areas. NeuroImage, 99, 411–418. https://doi.org/10.1016/j.neuroimage.2014.05.063.

    Article  Google Scholar 

  • Matias, F. S., Carelli, P. V., Mirasso, C. R., & Copelli, M. (2015). Self-organized near-zero-lag synchronization induced by spike-timing dependent plasticity in cortical populations. PLoS One, 10(10), 1–18. https://doi.org/10.1371/journal.pone.0140504.

    Article  Google Scholar 

  • Matias, F. S., Gollo, L. L., Carelli, P. V., Mirasso, C. R., & Copelli, M. (2016). Inhibitory loop robustly induces anticipated synchronization in neuronal microcircuits. Physical Review E, 94, 042411. https://doi.org/10.1103/PhysRevE.94.042411.

    Article  Google Scholar 

  • Maturana, H., & Varela, F. (1991). Autopoiesis and cognition: The realization of the living. Springer Netherlands.

    Google Scholar 

  • Middleton, A. (2000). Basal ganglia and cereberllar loops: Motor and cognitive circuits. Brain Research Reviews, 31, 236–250.

    Article  Google Scholar 

  • Mirasso, C. R., Carelli, P. V., Pereira, T., Matias, F. S., & Copelli, M. (2017). Anticipated and zero-lag synchronization in motifs of delay-coupled systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(11), 114305. https://doi.org/10.1063/1.5006932.

    Article  Google Scholar 

  • Mita, A., Mushiake, H., Shima, K., Matsuzaka, Y., & Tanji, J. (2009). Interval time coding by neurons in the presupplementary and supplementary motor areas. Nature Neuroscience, 12, 502–507.

    Article  Google Scholar 

  • Nasuto, S. J., & Hayashi, Y. (2016a). Anticipation: Beyond synthetic biology and cognitive robotics. BioSystems, 148, 22–31.

    Article  Google Scholar 

  • Nasuto, S. J., & Hayashi, Y. (2016b). Synapses in digital medium: Computational investigations of neural basis of anticipation. In M. Nadin (Ed.), Anticipation across disciplines (pp. 187–201). Cham: Springer International Publishing.

    Chapter  Google Scholar 

  • Oguchi, T. (2007). A finite spectrum assignment for retarded non-linear systems and its solvability condition. International Journal of Control, 80(6), 898–907. https://doi.org/10.1080/17499510701204166.

    Article  Google Scholar 

  • Oguchi, T. (2017). Anticipating synchronization and state predictor for nonlinear systems. In N. van de Wouw, E. Lefeber, & I. Lopez Arteaga (Eds.), Nonlinear systems: Techniques for dynamical analysis and control (pp. 103–122). Cham: Springer International Publishing.

    Chapter  Google Scholar 

  • Oguchi, T., & Nijmeijer, H. (2005a). Control of nonlinear systems with time-delay using state predictor based on synchronization. In Proceedings of the ENOC 2005 (pp. 1150–1156).

    Google Scholar 

  • Oguchi, T., & Nijmeijer, H. (2005b). Prediction of chaotic behavior. IEEE Transactions on Circuits and Systems, 52-I(11), 2464–2472. https://doi.org/10.1109/TCSI.2005.853396.

    Article  Google Scholar 

  • Oguchi, T., & Nijmeijer, H. (2006). Anticipating synchronization of nonlinear systems with uncertainties. IFAC Proceedings Volumes, 39(10), 290–295. https://doi.org/10.3182/20060710-3-IT-4901.00048. (6th IFAC Workshop on Time Delay Systems).

    Article  Google Scholar 

  • Pezzulo, G., Butz, M., Sigaud, O., & Baldassarre, G. (2009). Anticipatory behavior in adaptive learning systems: From psychological theories to artificial cognitive systems. Berlin/Heidelberg: Springer.

    Book  Google Scholar 

  • Port, R., & Van Gelder, T. (1998). Mind as motion: Explorations in the dynamics of cognition. MIT Press. Retrieved from https://books.google.co.uk/books?id=rY2IPwAACAAJ

  • Preston, J., & Bishop, M. (2002). Views into the Chinese room: New essays on Searle and artificial intelligence. Clarendon Press. Retrieved from https://books.google.co.uk/books?id=0V6PwUrH2aYC

  • Pyragas, K., & PyragienÄ—, T. (2008). Coupling design for a long-term anticipating synchronization of chaos. Physical Review E, 78, 046217. https://doi.org/10.1103/PhysRevE.78.046217.

    Article  Google Scholar 

  • PyragienÄ—, T., & Pyragas, K. (2013). Anticipating spike synchronization in nonidentical chaotic neurons. Nonlinear Dynamics, 74(1), 297–306.

    Article  Google Scholar 

  • PyragienÄ—, T., & Pyragas, K. (2017). Anticipatory synchronization via low-dimensional filters. Physics Letters A, 381(22), 1893–1898. https://doi.org/10.1016/j.physleta.2017.04.005.

    Article  Google Scholar 

  • Repp, B. (2005). Sensorimotor synchronization. A review of the tapping literature. Psychonomic Bulletin Review, 12(6), 969–992.

    Article  Google Scholar 

  • Rosen, R. (2012). Anticipatory systems. In Anticipatory systems (pp. 313–370). New York: Springer.

    Chapter  Google Scholar 

  • Seligman, M. E., Railton, P., Baumeister, R. F., & Sripada, C. (2013). Navigating into the future or driven by the past. Perspectives on Psychological Science, 8(2), 119–141.

    Article  Google Scholar 

  • Seoane, L. F., & SolĂ©, R. V. (2018). Information theory, predictability and the emergence of complex life. Open Science, 5(2). https://doi.org/10.1098/rsos.172221.

  • Spencer, M. C., Roesch, E. B., Nasuto, S. J., Tanay, T., & Bishop, J. M. (2013, March). Abstract platforms of computation. In Aisb 2013 (pp. 25–32). Exeter. Retrieved from http://centaur.reading.ac.uk/35696/. (Published in: The 6th AISB symposium on computing and philosophy: The scandal of computation – What is computation? Mark Bishop and Yasemin J. Erden (editors) AISB Convention 2013, University of Exeter, 3–5 April 2013. Published by The Society for the Study of Artificial Intelligence and the Simulation of Behaviour. http://www.aisb.org.uk. ISBN: 9781908187314).

  • Stepp, N. (2009). Anticipation in feedback-delayed manual tracking of a chaotic oscillator. Experimental Brain Research, 198, 521.

    Article  Google Scholar 

  • Stepp, N., & Frank, T. (2009). A data-analysis method for decomposing synchronization variability of anticipatory systems into stochastic and deterministic components. The European Physical Journal B-Condensed Matter and Complex Systems, 67(2), 251–257.

    Article  Google Scholar 

  • Stepp, N., & Turvey, M. (2010). On strong anticipation. Cognitive Systems Research, 11(2), 148–164. https://doi.org/10.1016/j.cogsys.2009.03.003.

    Article  Google Scholar 

  • Sterling, P. (2012). Allostasis: A model of predictive regulation. Physiology & Behavior, 106(1), 5–15. https://doi.org/10.1016/j.physbeh.2011.06.004. (Allostasis and Allostatic Load).

    Article  Google Scholar 

  • Stewart, J., Gapenne, O., & Di Paolo, E. (2010). Enaction: Toward a new paradigm for cognitive science. Cambridge, MA: MIT Press.

    Book  Google Scholar 

  • Synofzik, M., Vosgerau, G., & Newen, G. (2007). Beyond the comparator model: A multifactorial two-step account of agency. Consciousness and Cognition, 17(1), 219–239.

    Article  Google Scholar 

  • Thompson, E. (2010). Mind in life: Biology, phenomenology, and the sciences of mind. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • van Boxtel, G. J., & Böcker, K. B. (2004). Cortical measures of anticipation. Journal of Psychophysiology, 18(2–3), 61–76. https://doi.org/10.1027/0269-8803.18.23.61.

    Article  Google Scholar 

  • Vernon, D., Beetz, M., & Sandini, G. (2015). Prospection in cognition: The case for joint episodic-procedural memory in cognitive robotics. Frontiers in Robotics and AI, 2, 19. https://doi.org/10.3389/frobt.2015.00019. Retrieved from https://www.frontiersin.org/article/10.3389/frobt.2015.00019

  • Voss, H. U. (2000). Anticipating chaotic synchronization. Physical Review E, 61, 5115–5119. https://doi.org/10.1103/PhysRevE.61.5115.

    Article  Google Scholar 

  • Voss, H. U. (2001). Dynamic long-term anticipation of chaotic states. Physical Review Letters, 87, 014102. https://doi.org/10.1103/PhysRevLett.87.014102.

    Article  Google Scholar 

  • Voss, H. U. (2016a). The leaky integrator with recurrent inhibition as a predictor. Neural Computation, 28, 1498.

    Article  Google Scholar 

  • Voss, H. U. (2016b). Signal prediction by anticipatory relaxation dynamics. Physical Review E, 93(3), 030201. https://doi.org/10.1103/PhysRevE.93.030201.

    Article  Google Scholar 

  • Voss, H. U. (2016c). A simple predictor based on delay-induced negative group delay. ArXiv e-prints.

    Google Scholar 

  • Voss, H. U. (2018). A delayed-feedback filter with negative group delay, Chaos: An Interdisciplinary Journal of Nonlinear Science 28, 113113.

    Google Scholar 

  • Ward, L., & Press, M. (2002). Dynamical cognitive science. MIT Press. Retrieved from https://books.google.co.uk/books?id=g1ZMAoWGYesC

  • Wiener, N., & SchadĂ©, J. (1963). Introduction to neurocybernetics. In N. Wiener & J. SchadĂ© (Eds.), Progress in Brain Research, 2, p. 1–7. Elsevier. https://doi.org/10.1016/S0079-6123(08)62055-5. Retrieved from http://www.sciencedirect.com/science/article/pii/S0079612308620555

  • Wiggins, S. (2006). Introduction to applied nonlinear dynamical systems and chaos. New York: Springer. Retrieved from https://books.google.co.uk/books?id=YhXnBwAAQBAJ

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  1. Division of Biomedical Sciences and Biomedical Engineering, School of Biological Sciences, University of Reading, Reading, UK

    Slawomir J. Nasuto & Yoshikatsu Hayashi

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  1. Slawomir J. Nasuto
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  2. Yoshikatsu Hayashi
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Correspondence to Slawomir J. Nasuto .

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  1. Dept of Sociology & Social Research, University of Trento Dept of Sociology & Social Research, Trento, Italy

    Roberto Poli

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Nasuto, S.J., Hayashi, Y. (2019). Anticipation in Neurocybernetics. In: Poli, R. (eds) Handbook of Anticipation. Springer, Cham. https://doi.org/10.1007/978-3-319-31737-3_61-1

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