The Dynamics of Environmental Insult - Computational Psychiatry: A Systems Biology Approach to the Epigenetics of Mental Disorders 1st ed.

Computational Psychiatry: A Systems Biology Approach to the Epigenetics of Mental Disorders 1st ed.

10. The Dynamics of Environmental Insult

Rodrick Wallace¹

(1)

New York State Psychiatric Institute, New York, NY, USA

Summary

The principal environment of humans, their machines, man/machine composites, and institutions, is other entities of the same sort, creating an inherent positive feedback for the environmental insults triggering developmental and cognitive dysfunctions at different scales and levels of organization. We bookend the evolutionary discussion of the opening chapter on consciousness with an analogous treatment adapted from evolutionary economics, parallel to the resilience theory of ecosystem studies .

10.1 Introduction

Environmental insult plays a central role in developmental and cognitive dysfunction, affecting regulatory decisions at the directed homotopy branch points that characterize both ontology and decision. But, for humans, their machines and man/machine composites, and for institutions, the principal determinant, and often the major component, of that environment is those very things. This is, then, inherently a highly reflexive system that has long been characterized by evolutionary economists as “Schumpeterian” (e.g., Hodgson and Knudsen 2010; Wallace 2015 and the references therein). Such systems are subject to evolutionary selection pressures similar to, but different from, those outlined in the first chapter of this book. Nonetheless, the similarities are sufficient to permit formal analysis of the dynamics of environmental insult from an evolutionary perspective, leading to a “punctuated equilibrium”treatment analogous to the “domain shifts” of ecosystem resilience theory (Gould 2002; Holling 1973, 1992).

For the USA, two recent phenomena have driven large-scale patterns of environmental insult, triggering behavioral dysfunctions across multiple scales and levels of organization. These phenomena are widespread deurbanizationand “rust belt” deindustrialization , both related to public policies and economic decisions (Wallace and Wallace 1998; Wallace 2015; Ullmann 1988; Melman 1971).

Beginning in the 1970s, cities like New York, Newark, Detroit, Cleveland, and elsewhere suffered outbreaks of contagious urban decay and building abandonment leaving vast areas resembling the bombed-out cities of Germany after WW II. In New York City, the outbreak was driven by cuts in fire-related municipal services delivered to minority voting blocs (Wallace and Wallace 1998). Figure 10.1 shows the loss of occupied housing units in the Bronx section of New York City between 1970 and 1980. The Bronx, with 1.4 million people, is one of the largest conurbations in the Western world. Some districts lost as much as 80% of their housing units in this time, causing massive population displacement and loss of the social cohesion that is the basis of population physical and mental health (Wallace and Wallace 1998).

Fig. 10.1

Percent change in occupied housing units for New York City’s Borough of the Bronx between 1970 and 1980. The degree of housing loss is unprecedented for an industrialized country outside of wartime. Similar losses have affected many US central cities, particularly across the “rust belt” counties suffering Cold War-induced deindustrialization (Wallace 2015, Chap. 7)

Widespread deindustrialization followed upon the death of the US economic “Red Queen” that had been fueled by a necessarily relentless focus of scientific and engineering resources on the improvement of civilian industry (Melman 1971; Ullmann 1988; Wallace 2015). That is, to remain globally competitive, Western “market” economies must improve productivity some 3% annually. Forever. Diversion of inherently limited scientific and technological resources into weapons development and production, what Seymour Melman called the establishment of “Pentagon capitalism,” fatally undercut the ability of the USA to compete with “Asian tiger” countries.

Figure 10.2 shows the result: counties of the US rust belt losing 1000 or more industrial jobs between 1972 and 1987, well before the “globalization” policies now blamed for the loss of those jobs. Globalization simply involved easing the use of offshore factories to manufacture what the USA could no longer competitively build at home.

Fig. 10.2

“Rust Belt” counties of the USA losing 1000 or more industrial jobs between 1972 and 1987, well before formal “globalization” policies

Chapter 7 of Wallace and Wallace (2017) provides a more complete treatment of the public health effects of deindustrialization, and Chap. 7 of Wallace (2015) models the economic impact of the Cold War diversion of scientific and engineering resources from civilian to military enterprise in terms of a dynamic “Pentagon ratchet,” treated in more detail here using evolutionary perspectives.

The evolutionary theory of institutional economics provides tools for understanding the action of selection pressure on institutional dynamics, and, at the population level for a Western nation, these dynamics determine levels of environmental insult resulting in the developmental disorders studied in the previous chapters. Even cognitive machine systems may be driven to dysfunction by the positive feedback of self-referential environmental insult. For example, under combat conditions it is easy to imagine a feedback loop in which lowering the “wind-chill” fog-of-war index $\mathcal{T}$ serves to intensify selection pressures that ratchet it further down.

We begin with a recapitulation of basic ideas from evolutionary economics.

10.2 Institutional Evolution

Evolutionary perspectives, long applied to social and economic enterprises, have become an increasingly attractive alternative to current failing “atomistic” economic theory (e.g., Hodgson and Knudsen 2010; Wallace 2013, 2015, Chap. 1, and the references therein). Two dynamics dominate: punctuated equilibrium, in the sense of Eldredge and Gould (1972), and path dependence (Gould 2002). The argument is as follows.

Socioeconomic infrastructure, consisting of interacting enterprises, undergoes evolutionary process according to a modified version of the traditional biological mode (Wallace 2013):

1. 1.

2. 2.

3. 3.

4. 4.

Many of the essential processes within this structure can be represented in terms of interacting information sources, constrained by the asymptotic limit theorems of information and control theories. Following the arguments of Wallace (2013, 2014, 2015), it can be shown that

1. 1.

2. 2.

3. 3.

4. 4.

As a consequence, we can define a joint Shannon uncertainty representing the interaction of these information sources as

$\displaystyle{H(X,Y,Z,L_{D})}$

Defining an “entropy” across a vector of system parameters J as the Legendre transform

$\displaystyle{ S \equiv H(\mathbf{J}) -\mathbf{J} \cdot \nabla _{\mathbf{J}}H }$

(10.1)

we can apply, in first order, an analog to the Onsager approximations of earlier chapters. That is, a first order dynamic equation follows using the stochastic version of the Onsager formalism from nonequilibrium thermodynamics (de Groot and Mazur 1984)

$\displaystyle{ dJ_{t}^{i} \approx \left (\sum _{ k}\mu _{i,k}\partial S/\partial J_{t}^{k}\right )dt +\sigma _{ i}J_{t}^{i}dB_{ t} }$

(10.2)

μ _i_, kdefines a diffusion matrix, the σ _iare parameters, and dB_trepresents a noise that may not the usual Brownian motion under undifferentiated white noise.

Setting the expectation of this relation to zero, we find a relatively large set of nonequilibrium steady states (nss), indexed by j. Each nss is characterized by an uncertainty value H_j.

Importing the environmental stress index $\mathcal{T}$ from earlier chapters,

$\displaystyle{\mathcal{T} = \frac{\kappa _{1}\varGamma +\kappa _{2}} {\kappa _{3}\varGamma +\kappa _{4}}}$

where Γ represents a scalar constructed from the invariants of a complex environmental crosstalk matrix, we can write a pseudoprobability for state q as

$\displaystyle{ P_{q} = \frac{\exp (-H_{q}/\mathcal{T} )} {\sum _{j}\exp (-H_{j}/\mathcal{T} )} }$

(10.3)

and define a “free energy” Morse Function $\hat{F}$ in terms of the denominator sum, i.e.,

$\displaystyle{ \exp (-\hat{F}/\mathcal{T} ) \equiv \sum _{j}\exp (-H_{j}/\mathcal{T} ) }$

(10.4)

Changes in $\mathcal{T}$ (inverse in the index of environmental insult Γ) will be associated with profound—and highly punctuated—evolutionary transitions (Eldredge and Gould 1972; Gould 2002; Wallace 2014). These transitions, involving cognitive groupoid analogs to physical “symmetry breaking” (Pettini 2007), then define entirely new pathways along which socioeconomic systems develop. There is never, ever, a “return to normal after perturbation” in path-dependent evolutionary process.

Taking the perspective of Wallace (2011), it is possible to examine an economic-like ratchet that, in evolutionary terms, is usually characterized as a “self-referential” dynamic . Goldenfeld and Wose (2010) describe the mechanism for biological evolution:

…[T]he genome encodes the information which governs the response of an organism to its physical and biological environment. At the same time, this environment actually shapes genomes through gene transfer processes and phenotype selection. Thus, we encounter a situation where the dynamics must be self-referential: the update rules change during the time evolution of the system, and the way in which they change is a function of the state and thus the history of the system…self-referential dynamics is an inherent and probably defining feature of evolutionary dynamics…

The evolutionary dynamic we propose for socioeconomic systems under the stress of environmental insult is illustrated by Fig. 10.3. The vertical axis represents an index of social organization—percent voting, educational attainment, percent active in civic associations or religious institutions, etc. The horizontal axis is taken as a measure of environmental stress Γ. At low levels of insult the system drifts about some nonequilibrium steady state having relatively high degrees of social integration. When stress exceeds a threshold, there is a punctuated phase change associated with a large deviation, leading to a less organized nonequilibrium steady state, as indicated. Thus onset of social disintegration itself constitutes a significant environmental insult, leading to a fully self-referential downward ratchet.

Fig. 10.3

The vertical axis indexes degree of social organization. The horizontal axis represents the degree of environmental insult Γ. At low insult the system drifts about a nonequilibrium steady state with significant social integration and organization. Insult exceeding some critical level triggers a punctuated phase change via a large deviation, leading to a less organized nonequilibrium steady state. Social disintegration, of itself, constitutes a serious environmental insult, leading to “self-referential” ratchet dynamics: a positive feedback-driven race to the bottom. Conversely, however, significant investment in social, technological, and physical infrastructure can trigger an upward ratchet

A relatively simple deterministic mathematical description of such a binary switch might be as follows. Assume Γ, the scalar index of environmental stress, is initially at some nonequilibrium steady state, and that Γ → Γ +Δ. Then Δ is assumed, in first order, to follow a relation

$\displaystyle{ d\varDelta /dt =\mu \varDelta -C/\varDelta,\,\,C,\mu> 0 }$

(10.5)

so that, if $\varDelta \leq \sqrt{C/\mu }$ , then d Δ∕dt ≤ 0, and the system remains at or near Γ. Otherwise d Δ∕dt becomes positive, and the switch is triggered, according to Fig. 10.3. Other models that lead to such quasi-stability could be used.

Next, we expand in a stochastic treatment, so that

$\displaystyle{ d\varDelta _{t} = (\mu \varDelta _{t} - C/\varDelta _{t})dt +\sigma \varDelta _{t}dW_{t} }$

(10.6)

where σ is an index of the magnitude of impinging white noise dW_t. Then, applying the Ito chain rule to log[Δ _t] (Protter 1990), in the context of Jensen's inequality for a concave function, the nonequilibrium steady state expectation is

$\displaystyle{ E[\Delta_{t}] \geq \sqrt{\frac{C}{\mu - \sigma^{2}/2}} }$

(10.7)

Sufficient noise drives an explosive perturbation. In addition, since Eq. (10.7) is an expectation across a probability distribution, even at relatively low mean values there may well be much larger stochastic excursions—large deviations—that can trigger a destabilizing transition, following Fig. 10.3. Again, Wallace (2015, Chap. 7) examines the impact of the diversion of technological resources from civilian to military industrial enterprise during the Cold War leading to the massive “rust belt” collapse in the USA.

Of course, given sufficient “available free energy,” in a large sense, upward ratchets in levels of organization—analogous to the famous aerobic transition or, in human social systems, to the American Revolution, the Industrial Revolution, or the US Labor and Civil Rights Movements—are also possible.

10.3 Discussion and Conclusions

Given that the principal environment of humans, their machines, man/machine composites, and embedding institutions, is more of the same, it becomes clear that environmental insult driving both developmental and cognitive dysfunction can become a self-dynamic force, triggering outcomes that can fuel the fire, as it were. This can, as indicated, go both ways: ratchets can be upward as well as downward. Sufficient sociotechnical investment can initiate socioeconomic and cultural dynamics that reverse environmental factors that are driving developmental and cognitive dysfunctions across many scales and levels of organization. The precipitate decline in “normal” death rates for industrialized nations that following the reforms of the late nineteenth and early twentieth centuries provides a cogent case history.

Holling (1992) argues persuasively that, for ecosystems, mesoscale “keystone” processes in particular entrain both higher and lower levels of organization. Given the recent history of the USA, it seems clear that the essential mesoscale perturbations involved deindustrialization and deurbanization, individually and in synergism. Both dynamics were driven by public policy. Unlike ecosystems undergoing eutrophication, however, socioeconomic systems can be ratcheted upward. For the USA, both deindustrialization and deurbanization can, in theory, be reversed by public policy, as outlined by Ullmann (1988) and Wallace (2015, Sect. 7.6). In brief, reversing the American Catastrophe would require ending “Pentagon Capitalism,” active reindustrialization and infrastructure reconstruction, rebuilding of cities to recapture economies of scale, public education through the Masters Degree for those who wish it, and draconian opposition to the scapegoating of minorities that is not only a distraction from real issues, but also the canonical process by which a dying empire eats its own entrails.

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