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Behavior Considered as an Enabling Constraint

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Neural Mechanisms

Part of the book series: Studies in Brain and Mind ((SIBM,volume 17))

Abstract

Two fundamental challenges of contemporary neuroscience are to make sense of the scalar relations in the nervous system and to understand the way behavior emerges from these relations while at the same time affects them. In this paper, we analyze the notion of enabling constraint and the way it can frame the two kinds of relations involved in the challenges: of different neural scales (e.g., molecular scale, genetic scale, single-neurons, neural networks, etc.) and between neural systems and behavior. We think the notion of enabling constraint provides a promising alternative to other classic, mechanistic understandings of these relations and the different issues they raise for contemporary neuroscience.

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Notes

  1. 1.

    Biological systems being the subset of functional systems of interest to us here.

  2. 2.

    There are some potential complications here, since one could imagine that an input to or activity in S producing more than one outcome, such that the probability distribution over {O} need not sum to one. Here we will develop the theory in the context of the special case where there is a single such outcome, and thus the probability distribution across elements of {O} sums to 1.

  3. 3.

    “Near” because, whether or not biological systems are deterministic, it is clear that they do not exert deterministic control over themselves, nor over one another, at any level of description.

  4. 4.

    Thanks to Alessandra Buccella and Charles Rathkopf for pushing us on this issue, in their comments on an earlier draft of this paper.

  5. 5.

    What we gesture at by saying this is that we are in the business of developing a conceptual framework that will support fruitful empirical investigation. The proposal does not have to cleanly adjudicate between all border cases to be epistemically and heuristically useful in scientific practice.

  6. 6.

    It is important to flag that this is a significantly different, but we hope more precise and useful, definition than the one offered in Anderson (2015a: 12). Thanks to Alessandra Buccella, Charles Rathkopf, Michael Silberstein, and an anonymous reviewer for the various comments that motivated this revision.

  7. 7.

    Thanks to Michael Silberstein for pressing us to clarify this in his comments on an earlier draft of the essay.

  8. 8.

    We recognize that there are some authors, e.g. (Silberstein 2018, in press) who take such higher-order variables as order parameters or network topologies to be non-physical. We do not wish to enter into this debate here, and suspect neither resolution of it affects our conclusions here at all.

  9. 9.

    Although we focus on the notion of developmental constraint, Gould and Lewontin (1979) has remained influential within theoretical evolutionary biology in many ways—e.g., for the developmental systems approach (Oyama 2000; Oyama et al. 2001) or the evo-devo discourse in biology (Brigandt 2015; Carroll 2008; Goodman and Coughlin 2000; Hall 2003; Held 2014).

  10. 10.

    Obviously, “not available” is a temporal notion, since over vast swaths of time, there may be no part of the morphological landscape truly inaccessible.

  11. 11.

    Indeed, the name “enabling constraint” has been used to refer to the proposals of Stanley N. Salthe (1993) regarding the relationship between evolution and development in the form of self-organized processes (see, e.g., Juarrero 1999).

  12. 12.

    Actually, as far as evolution is a process and not a system, the notion of mechanism proposed by new mechanists might even not apply to it. Otherwise, if the mechanism of evolution is identified with natural selection itself, it seems that developmental constraints are not a proper part of the mechanism and, therefore, are not a constitutive part of it although still actively contribute to evolution as a process. In this latter sense, the notion of enabling constraint applied to developmental constraints would be more similar to the notion as we will use it regarding cognitive science.

  13. 13.

    For a detailed description of the mechanism, see Anderson (2015a).

  14. 14.

    On the assumption that the system that exhibits direction-selectivity here is the dendrite. There are some subtleties to be considered regarding how best to define the functional system in this case. For discussion see Anderson (2015a, b; Köhler 2015), and this section, below.

  15. 15.

    An alternate response might be to accept that they are part of the context, but to insist that the context operates precisely via constraint (see, e.g. Silberstein (2018, in press) on contextual constraint).

  16. 16.

    Notice that this fact may be true even for those mechanisms that include some kind of feed-forward model to reflect the current behavioral and perceptual outcomes of the behavioral mechanism on its future input as the behavioral output serially precedes the future input. See Pickering and Clark (2014).

  17. 17.

    Put simply, the criticism counters the idea that cognitive activity starts with stimulation (e.g., visual stimulation) and ends up with a response (e.g., some movement of the limbs). On the contrary, critics claim, we must acknowledge the role of the “response” in the “stimulation” itself: cognitive activities are organic cycles of interdependent perception and action. In this sense, behavior is not just an outcome of neural activity.

  18. 18.

    An example of this criticism is the supposed in-principle inability of a theory entailing a central controller to account for the coordination of all the effectors of a system as complex as the body of a human being to generate the desired behavior. The issue has been labeled as “the Charles V problem” in the literature on motor control (Meijer 2001).

  19. 19.

    Importantly, the reader can remain agnostic regarding which alternative for the explanation of the relationship between behavior and neural activity is the correct one. For our purposes in this paper, we only need to acknowledge that the alternative, dynamical view of that relationship is a reality in the cognitive sciences.

  20. 20.

    Especially if the realizer-outcome view of the relationship between behavior and neural activity is accepted.

  21. 21.

    Indeed, it is usual to understand both approaches as part of the same tradition and, generally, as part of the toolbox of nonlinear methods for the cognitive sciences (Riley and Van Orden 2005).

  22. 22.

    It’s important to note that the new mechanists have also acknowledged the inadequacy of the realizer-outcome approach, as they characterise cyclic and oscillatory mechanisms, such as circadian rhythms (Bechtel and Abrahamson 2013).

  23. 23.

    The best way to describe the sensitivity of neural systems to perceptual information is still an open question. We take the concept of ecological resonance to be a good candidate to explain that sensitivity (Raja 2018; Raja and Anderson 2019).

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Authors and Affiliations

  1. Rotman Institute of Philosophy, University of Western Ontario, London, ON, Canada

    Vicente Raja & Michael L. Anderson

  2. Department of Philosophy, University of Western Ontario, London, ON, Canada

    Michael L. Anderson

  3. Brain and Mind Institute, University of Western Ontario, London, ON, Canada

    Michael L. Anderson

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  1. Vicente Raja
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  1. Department of Letter, Philosophy, Communication, University of Bergamo LLC, Turin, Italy

    Fabrizio Calzavarini

  2. Department of Philosophy and Education, University of Turin, Turin, Italy

    Marco Viola

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Raja, V., Anderson, M.L. (2021). Behavior Considered as an Enabling Constraint. In: Calzavarini, F., Viola, M. (eds) Neural Mechanisms. Studies in Brain and Mind, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-030-54092-0_10

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