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01-02-2018

Rethinking Causality in Biological and Neural Mechanisms: Constraints and Control

Authors: Jason Winning, William Bechtel

Published in: Minds and Machines | Issue 2/2018

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Abstract

Existing accounts of mechanistic causation are not suited for understanding causation in biological and neural mechanisms because they do not have the resources to capture the unique causal structure of control heterarchies. In this paper, we provide a new account on which the causal powers of mechanisms are grounded by time-dependent, variable constraints. Constraints can also serve as a key bridge concept between the mechanistic approach to explanation and underappreciated work in theoretical biology that sheds light on how biological systems channel energy to actively respond to the environment in adaptive ways, perform work, and fulfill the requirements to maintain themselves far from equilibrium. We show how the framework applies to several concrete examples of control in simple organisms as well as the nervous system of complex organisms.

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The use of levels in the context of control is distinct from the notion of levels of organization or levels in a mechanism (as discussed by Craver 2007). Although control can be exercised by a mechanism on its component parts, control can also be exercised by completely separate mechanisms or even by parts of a given mechanism.

Philosophers presenting mechanistic explanation have discussed examples of control mechanisms, such as negative feedback (Bechtel 2011; Bechtel and Abrahamsen 2011) and circadian mechanisms (Bechtel 2010, 2013), but they have said little about how these mechanisms effect control on other mechanisms. The analysis presented in this paper is intended to fill that lacuna.

We are not suggesting that control is non-causal, but that it is something more than merely one process causally producing another.

In defending top-down causation, Craver and Bechtel (2007) argue that conditions that affect whole mechanisms also affect their parts, thereby providing a sense in which activities of whole mechanisms control those of their constituents. More recently, Bechtel (2017) has further characterized top-down causation in terms of activity in a larger system imposing constraints on individual units in the network. While this proposal resembles in some respects the one we advance here, it is limited to the context of top-down causation, while the account we offer applies more generally to cases in which one mechanism exercises control over another.

For that matter, the causal efficacy of the whole mechanism remains mysterious as well. Machamer e al. (2000) appeal to the productive continuity from one activity to the next and Bechtel and Abrahamsen (2005) appeal to the ability of researchers to simulate mentally the component operations to show how they generate the overall phenomenon. But actual accounts of mechanism are typically incomplete, and the gaps in the mechanism are sometimes only revealed much later after the explanation has been widely accepted.

See Glennan (2009) for an argument to the effect that the virtues of Woodward’s account of the epistemology of causal reasoning “[do] not legitimate the manipulability theory as a metaphysical account of causation” (2009, p. 318).

See Kuhlmann and Glennan (2014) for further discussion about how the classical mechanical causation of macro-level mechanisms can be understood as compatible with quantum mechanics on the Copenhagen interpretation. Rather than seeing theirs as a competing account, we believe that their paper fits well with this account because it is essentially a discussion about the relationship between classical and non-classical types of constraints.

It has been common to focus on organisms, especially single-celled organisms, as the locus of biological autonomy (Moreno and Mossio 2015). However, many organisms live in symbiotic relations in which crucial activities are shared between numerous organisms, often from multiple species (O’Malley 2014). Control relations such as we discuss later can involve entities in the environment with which an organism is tightly coupled. Accordingly, when considering autonomy, we speak of biological systems, not organisms.

An approach to mechanistic causation along similar Aristotelian lines was defended recently by Cartwright and Pemberton (2013).

For a mechanism to produce a phenomenon it must undergo changes induced by the activities of its parts and so fits the broad conception of a ‘dynamical system’ as “a structure of mutually and simultaneously influencing change” unfolding in real time (van Gelder and Port 1995, p. 3).

See chapter 1 of their book, where they rail against “esoteric debates about substance, universals, identity, time, properties, and so on, which make little or no reference to science, and worse, which seem to presuppose that science must be irrelevant to their resolution” and the associated tendency to prioritize “armchair intuitions about the nature of the universe over scientific discoveries” and to attach “epistemic significance to metaphysical intuitions” (Ross et al. 2007, p. 10).

Other authors that seem to invoke something similar to this physical and modal interpretation of constraints are Esfeld (2009), Kistler (2009), and Glennan (2017, pp. 167–168).

Juarrero (1999), pp. 131–132) and Moreno and Mossio (2015, p. 51) have also proposed that constraints can ground causal powers. For a more fully worked out version of the present account of causal powers, see Winning (forthcoming).

Time-invariant and time-dependent constraints are represented in analytical mechanics by scleronomic and rheonomic constraint equations, respectively.

In analytical mechanics, integrable constraint equations, yielding a state-determined dynamics (e.g., particles of a rigid object, or a series of tightly intermeshing gears), are called holonomic, whereas non-integrable constraints, yielding a flexibly constrained system (e.g., particles free to move but confined within a box, or loosely intermeshing gears), are called non-holonomic.

In addition to explaining self control within biological systems, a full account of autonomy would require explaining how biological systems build (Varela 1979) and repair (Rosen 1991) themselves.

On the notion of heterarchy and how it contrasts with hierarchy, see also McCulloch (1945), Turvey (1977), and Yates (1979).

When negative feedback is implemented in devices such as thermostats, there is once again a role for humans in setting the thermostat. The Watt governor does not permit such setting.

Like any representational system, the clock can misrepresent, for example, by indicating dawn when it is midday.

It is, in fact, more coupled than Fig. 3 indicates, since the synthesis of KaiA, KaiB, and KaiC is also under control of the clock mechanism. Nonetheless, the phosphorylation process is distinct from the synthesis process.

The ambiguous notion of a ‘functional level’ or a ‘functional hierarchy’ may have sometimes resulted in these distinctions being blurred, especially that between ordinary causal dependence and control.

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Title: Rethinking Causality in Biological and Neural Mechanisms: Constraints and Control
Authors: Jason Winning
William Bechtel
Publication date: 01-02-2018
Publisher: Springer Netherlands
Published in: Minds and Machines / Issue 2/2018
Print ISSN: 0924-6495
Electronic ISSN: 1572-8641
DOI: https://doi.org/10.1007/s11023-018-9458-5

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