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A potential mechanism for Gibsonian resonance: behavioral entrainment emerges from local homeostasis in an unsupervised reservoir network

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Abstract

While the cognitivist school of thought holds that the mind is analogous to a computer, performing logical operations over internal representations, the tradition of ecological psychology contends that organisms can directly “resonate” to information for action and perception without the need for a representational intermediary. The concept of resonance has played an important role in ecological psychology, but it remains a metaphor. Supplying a mechanistic account of resonance requires a non-representational account of central nervous system (CNS) dynamics. Towards this, we present a series of simple models in which a reservoir network with homeostatic nodes is used to control a simple agent embedded in an environment. This network spontaneously produces behaviors that are adaptive in each context, including (1) visually tracking a moving object, (2) substantially above-chance performance in the arcade game Pong, (2) and avoiding walls while controlling a mobile agent. Upon analyzing the dynamics of the networks, we find that behavioral stability can be maintained without the formation of stable or recurring patterns of network activity that could be identified as neural representations. These results may represent a useful step towards a mechanistic grounding of resonance and a view of the CNS that is compatible with ecological psychology.

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Notes

  1. Emphasis ours

  2. We emphasize that our proposal is a form of “how-possibly” explanation (Dray, 1968): our model shows one possible mechanism by which resonance could occur, but much further work will be necessary to determine if, or to what extent, something like this mechanism actually accounts for the behavior of humans or other organisms.

  3. Note that a reservoir computer can be trained to match its own input, becoming an autoencoder, so these are not exclusive categories.

  4. What we are describing has much in common with the active-inference and free-energy minimizing approach. However, we take there to be important distinctions as well, which are beyond the scope of this article to unpack.

  5. Data reported in this manuscript and code for running and visualizing all models is available on our Open Science Foundation repository: https://osf.io/6hqrt/. Our simulations leveraged the Agents.jl package (Datseris et al., 2022)

  6. The behavior of this agent-environment system is similar to that of a two-vehicle Braitenberg system, studied in depth by Hotton and Yoshimi (in press). In particular, the circular behaviors are comparable to what are there studied as “revolving type relative equilibria”.

  7. The second author, Yoshimi, interprets some points in this paper slightly differently than his co-authors, in two ways. (1) He allows that internal mediating states can be thought of as representations in a minimal sense, and has argued that that these minimal representations can have an illuminating mathematical structure, that is manifest in the “open phase portraits” of open dynamics systems (Hotton & Yoshimi, 2011, forthcoming). (2) He belives that ecological resonance of the kind described here is important and is indeed often non-representational, but also believes that an account like this can co-exist with one in which more classical forms of representation play an important role in cognitive science. In that sense he defends a form of pluralism (Yoshimi, in press)

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Acknowledgements

JBF would like to thank the following people for their helpful discussions and feedback during the development of this manuscript: Cody Moser, Paul Smaldino, Jeff Rodny, and Tim Shea from UC Merced; Charles Bakker, Noah Guzman, and Mike Anderson’s EMRG lab; Daniel Friedman and the Active Inference Institute; Maxwell Ramstead and the Computational Phenomenology group; and Mac Shine.

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Authors and Affiliations

  1. School of Social and Behavioral Sciences, Arizona State University, Glendale, USA

    J. Benjamin Falandays

  2. Department of Cognitive and Information Sciences, University of California, Merced, Merced, USA

    Jeffrey Yoshimi & Michael J. Spivey

  3. Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA

    William H. Warren

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  1. J. Benjamin Falandays
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  2. Jeffrey Yoshimi
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Falandays, J.B., Yoshimi, J., Warren, W.H. et al. A potential mechanism for Gibsonian resonance: behavioral entrainment emerges from local homeostasis in an unsupervised reservoir network. Cogn Neurodyn (2023). https://doi.org/10.1007/s11571-023-09988-2

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