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Unpredictable homeodynamic and ambient constraints on irrational decision making of aneural and neural foragers

Published online by Cambridge University Press:  19 March 2019

Kevin B. Clark*
Affiliation:
Research and Development Service, Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA 90073; Felidae Conservation Fund, Mill Valley, CA 94941; Campus Champions, Extreme Science and Engineering Discovery Environment (XSEDE), National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL 61801; Expert Network, Penn Center for Innovation, University of Pennsylvania, Philadelphia, PA 19104; Virus Focus Group, NASA Astrobiology Institute, NASA Ames Research Center, Moffett Field, CA 94035. kbclarkphd@yahoo.comwww.linkedin.com/pub/kevin-clark/58/67/19a

Abstract

Foraging for nutritional sustenance represents common significant learned/heritable survival strategies evolved for phylum-diverse cellular life on Earth. Unicellular aneural to multicellular neural foragers display conserved rational or irrational decision making depending on outcome predictions for noise-susceptible real/illusory homeodynamic and ambient dietary cues. Such context-dependent heuristic-guided foraging enables optimal, suboptimal, or fallacious decisions that drive organismal adaptation, health, longevity, and life history.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2019 

Anselme and Güntürkün (A&G) develop intriguing data-persuasive hypotheses on the emergence of irrational decision making in animal foragers that illustrate common phenomena associated with phylogenetically diverse cellular life on Earth. According to A&G, animals experiencing conditions of uncertain food distribution and access become controlled by classically conditioned “incentive hope,” a nontrivial motivational state whereby animals increase their food seeking, hoarding, and/or consumption behaviors to stave off starvation risks. This sort of ecoevolutionary strategy exemplifies superstitious or irrational decision making because animals choose ecological trade-offs that favor performance of (corporally) riskier energy-depleting foraging when unreliable cues for nutritional supplies imprecisely signal life-sustaining food abundance or life-threatening food scarcity. A&G contend that the biological bases of these sign-tracking animal behaviors is mediated largely by brain dopamine-reward systems important for conditioned incentive motivation and by metabolic changes in high-caloric body-fat reserves. Although dopamine-reward systems likely serve a central role in expression of animal incentive hope, similar context-dependent irrational strategies leading to generational/transgenerational adaptive or maladaptive outcomes may be observed for aneural single-celled and multicellular foragers ranging from bacteria to protists to plants (cf. Beekman & Latty Reference Beekman and Latty2015; Cao & Goodrich-Blair Reference Cao and Goodrich-Blair2017; Clark Reference Clark2010a; Reference Clark2010b; Reference Clark2010c; Reference Clark2012; Reference Clark2013a; Reference Clark2013b; Dussutour et al. Reference Dussutour, Latty, Beekman and Simpson2010; Hillesland et al. Reference Hillesland, Velicer and Lenski2009; Latty & Beekman Reference Latty and Beekman2011a; Reference Latty and Beekman2011b; López Garcia de Lomana et al. Reference López Garcia de Lomana, Kaur, Turkarsian, Beer, Mast, Smith, Aitchison and Baliga2017; Trewavas Reference Trewavas2003). Such cross-taxonomic findings, regrettably unacknowledged in A&G's presentation, strongly indicate that irrational decision making, including fallible learned/heritable heuristic-guided foraging, is well-conserved across phylogeny, being mediated through assorted fuzzy somatic, epigenetic, and genetic systems responsive to real/illusory stochastic homeodynamic and/or ambient processes capable of driving organismal adaptation, health, longevity, and evolved life history (Anreiter et al. Reference Anreiter, Kramer and Sokolowski2017; Clark Reference Clark2012; Jobson et al. Reference Jobson, Jordan, Sandrof, Hibshman, Lennox and Baugh2015; Lumey et al. Reference Lumey, Stein and Susser2011; Meyer et al. Reference Meyer, Ansorge and Nakagaki2017; Reichert et al. Reference Reichert, Christiansen, Seiter and Schausberger2017; Trewavas Reference Trewavas2003; Vaiseman Reference Vaiseman2014; Wolf et al. Reference Wolf, Vazirani and Arkin2005).

To conquer limitations of A&G's animal-centric hypotheses, one must better characterize the ubiquitous influence of stochastic processes on context-dependent generational/transgenerational adaptive or maladaptive foraging choices irrespective of phylum-specific forager anatomy and physiology. Such efforts, employing instances of kingdom-invariant ecoevolutionary game contexts ignored by the authors, identify variable detection sensitivity of perfect or fallible decision makers to real/illusory homeodynamic and/or ambient environmental cues, critically exposing generalizable scenarios where irrational gambling fallacies and other probabilistic consequences of noiseless/noisy signal-detection constraints elicit judged/misjudged win-shift, lose-shift, win-stay, and lose-stay foraging strategies (Dussutour et al. Reference Dussutour, Latty, Beekman and Simpson2010; Latty & Beekman Reference Latty and Beekman2011a; Jobson et al. Reference Jobson, Jordan, Sandrof, Hibshman, Lennox and Baugh2015; Lumey et al. Reference Lumey, Stein and Susser2011; Meyer et al. Reference Meyer, Ansorge and Nakagaki2017; Trewavas Reference Trewavas2003; Vaiseman Reference Vaiseman2014; Wolf et al. Reference Wolf, Vazirani and Arkin2005). Notably, regardless of selective foraging biomechanisms and occurrence of real/illusory enteroception and exteroception, aneural, and neural organisms differentially apply absolute and comparative valuations of nourishment quality and diet balance when seeking, hoarding, and/or consuming foods during periods of famine or feast. Distinguishable linear divergence in food availability/quality magnitude and bioenergetics status results in rational optimal foraging decision making regulated by accurate representativeness or availability heuristics. However, when signal-detection noise distorts perception of homeodynamic and/or ambient environmental pressures, aneural and neural organisms begin to execute error-prone learned/inherited irrational heuristic-guided decisions consistent with uncertainty-forced incentive hope – findings that extend the external validity and power of A&G's conjecture. If stochastic processes emerge in less challenging game scenarios (e.g., unpredictable food availability and predictable food quality), win-stay or lose-shift selective foraging strategies, such as the hot hand fallacy, yield comparatively smaller ecoenvironmental advantages or disadvantages for individuals and populations of parents, progeny, and grandprogeny. On the contrary, lose-stay or win-shift choices, such as the gambler's fallacy manifesting from harder foraging dilemmas (e.g., unpredictable food availability and quality), may confer more profound positive or negative context-dependent effects over the life spans of individual organisms and across many generations, such as hunger-induced, robust or compromised phenotypic variations supporting survival and reproductive successes (Anreiter et al. Reference Anreiter, Kramer and Sokolowski2017; Jobson et al. Reference Jobson, Jordan, Sandrof, Hibshman, Lennox and Baugh2015; Lumey et al. Reference Lumey, Stein and Susser2011; Reichert et al. Reference Reichert, Christiansen, Seiter and Schausberger2017; Trewavas Reference Trewavas2003; Vaiseman Reference Vaiseman2014).

Thus, despite differences in biological bases of information acquisition, modification, representation/storage, and transmission (i.e., aneural vs. neural processing), predictability of internal and external dietary cues fundamentally determines rational or irrational foraging, with unreliable cues tending to compel directly proportional irrational goal-directed choice behavior. In many respects, this evidence-backed conclusion should be unsurprising to experimentalists and theorists, because the hypothetical construct of rationality is founded on and scaled to categorical and probabilistic traits of either natural or formal logic systems (Busemeyer & Bruza Reference Busemeyer and Bruza2011; Clark Reference Clark2012; Eisenstein & Eisenstein Reference Eisenstein and Eisenstein2006; Nisbett & Ross Reference Nisbett and Ross1980; Tversky & Kahneman Reference Tversky and Kahneman1974). Maybe a deeper, trickier question to answer is whether irrational foraging decisions, such as those accompanying hot hand and gambler's fallacies, and possibly similar public-/private-goods decisions made by aneural and neural hunters and farmers (Gowdy & Krall Reference Gowdy and Krall2016; Werner et al. Reference Werner, Strassmann, Ivens, Engelmoer, Verbruggen, Queller, Noë, Johnson, Hammerstein and Kiers2014), might counterintuitively generate dependable adaptive outcomes on organismal health, longevity, and life history. A&G's exposition of animal incentive hope suggests the appearance of just that kind of positive ecoevolutionary “irrational rationality” for metabolically compensatory foragers, where irrationality-causing life costs are reconciled or surmounted by changes in body-fat storage and utilization. Examples and exceptions to those types of generational/transgenerational trajectories in animals are well reported for fluctuating and persistent nutritional stress linked to developmental periods (Anreiter et al. Reference Anreiter, Kramer and Sokolowski2017; Jobson et al. Reference Jobson, Jordan, Sandrof, Hibshman, Lennox and Baugh2015; Lumey et al. Reference Lumey, Stein and Susser2011; Reichert et al. Reference Reichert, Christiansen, Seiter and Schausberger2017; Vaiseman Reference Vaiseman2014). Nonetheless, much remains unknown about conservation of learned/heritable irrational rationality for aneural organisms engaged in foraging or other vital tasks. The arguably best instance involving microbes may be extrapolated from a game scenario called Parrondo's paradox, a set of indeterministic conditions imposing prospective lose-stay winning plays that advance transitions to stable optimal ecoevolutionary strategies (Wolf et al. Reference Wolf, Vazirani and Arkin2005). Under such unpredictable homeodynamic and/or ambient constraints, microbes, very similar to taxonomically recent animals, irrationally produce dependable learned/heritable adaptive survival strategies capable of improving and protecting the health and longevity of individuals belonging to extant and future generations, reinforcing provocative notions that universal computational/informational/physical principles structure expression of irrationality and rationality in foragers, and perhaps predators and cultivators, independently of aneural and neural systems (Bekenstein Reference Bekenstein2004; Clark Reference Clark2010a; Reference Clark2010b; Reference Clark2015; Clark & Hassert Reference Clark and Hassert2013; Gödel Reference Gödel1931; Ladyman et al. Reference Ladyman, Presnell, Short and Groisman2007).

References

Anreiter, I., Kramer, J. M. & Sokolowski, M. B. (2017) Epigenetic mechanisms modulate differences in Drosophilia foraging behavior. Proceedings of the National Academy of Sciences USA 114(47):12518–23.Google Scholar
Beekman, M. & Latty, T. (2015) Brainless but multi-headed: Decision making by the acellular slime mould Physarum polycephalum. Journal of Molecular Biology 427(23):3734–43.Google Scholar
Bekenstein, J. D. (2004) Black holes and information theory. Contemporary Physics 45(1):3143.Google Scholar
Busemeyer, J. R. & Bruza, P. (2011) Quantum models of cognition and decision making. Cambridge University Press.Google Scholar
Cao, M. & Goodrich-Blair, H. (2017) Ready or not: Microbial adaptive responses in dynamic symbiosis environments. Journal of Bacteriology 199(15):e0088316.Google Scholar
Clark, K. B. (2010a) Arrhenius-kinetics evidence for quantum tunneling in microbial “social” decision rates. Communicative & Integrative Biology 3(6):540–44.Google Scholar
Clark, K. B. (2010b) Bose-Einstein condensates form in heuristics learned by ciliates deciding to signal ‘social’ commitments. BioSystems 99(3):167–78.Google Scholar
Clark, K. B. (2010c) On classical and quantum error-correction in ciliate mate selection. Communicative & Integrative Biology 3(4):374–78.Google Scholar
Clark, K. B. (2012) Social biases determine spatiotemporal sparseness of ciliate mating heuristics. Communicative & Integrative Biology 5(1):311.Google Scholar
Clark, K. B. (2013a) Biotic activity of Ca2+-modulating nontraditional antimicrobial and -viral agents. Frontiers in Microbiology 4:381.Google Scholar
Clark, K. B. (2013b) Ciliates learn to diagnose and correct classical error syndromes in mating strategies. Frontiers in Microbiology 4:229.Google Scholar
Clark, K. B. (2015) Insight and analysis problem solving in microbes to machines. Progress in Biophysics and Molecular Biology 119:183–93.Google Scholar
Clark, K. B. & Hassert, D. L. (2013) Undecidability and opacity of metacognition in animals and humans. Frontiers in Psychology 4:171.Google Scholar
Dussutour, A., Latty, T., Beekman, M. & Simpson, S. J. (2010) Amoeboid organism solves complex nutritional challenges. Proceedings of the National Academy of Sciences USA 107(10):4607–11.Google Scholar
Eisenstein, E. M. & Eisenstein, D. (2006) A behavioral homeostasis theory of habituation and sensitization: II. Further developments and predictions. Reviews in Neuroscience 17:533–57.Google Scholar
Gödel, K. (1931) Über formal unentscheidbare Säze der Principia Mathematica und verwandter Systeme I. Monatshefte für Mathematik und Physik 38:173–98.Google Scholar
Gowdy, J. & Krall, L. (2016) The economic origins of ultrasociality. Behavioral and Brain Sciences 39:e92.Google Scholar
Hillesland, K. L., Velicer, G. J. & Lenski, R. E. (2009) Experimental evolution of a microbial predator's ability to find prey. Proceedings of the Royal Society B: Biological Sciences 276(1656):459–67.Google Scholar
Jobson, M. A., Jordan, J. M., Sandrof, M. A., Hibshman, J. D., Lennox, A. L. & Baugh, L. R. (2015) Transgenerational effects of early life starvation on growth, reproduction, and stress resistance in Caenorhabditis elegans. Genetics 201(1):201–12.Google Scholar
Ladyman, J., Presnell, S., Short, A. J. & Groisman, B. (2007) The connection between logical and thermodynamic irreversibility. Studies in History and Philosophy of Modern Physics 38:5879.Google Scholar
Latty, T. & Beekman, M. (2011a) Irrational decision-making in an amoeboid organism: Transitivity and context-dependent preferences. Proceedings of the Royal Society B: Biological Sciences 278(1703):307–12.Google Scholar
Latty, T. & Beekman, M. (2011b) Speed-accuracy trade-offs during foraging decisions in the acellular slime mould physarum polycephalum. Proceedings of the Royal Society B: Biological Sciences 278(1705):539–45.Google Scholar
López Garcia de Lomana, A., Kaur, A., Turkarsian, S., Beer, K. D., Mast, F. D., Smith, J. J., Aitchison, J. D., & Baliga, N.S. (2017) Adaptive prediction emerges over short evolutionary time scales. Genome and Biological Evolution 9(6):1616–23.Google Scholar
Lumey, L. H., Stein, A. D. & Susser, E. (2011) Prenatal famine and adult health. Annual Review of Public Health 32:237–62.Google Scholar
Meyer, B., Ansorge, C. & Nakagaki, T. (2017) The role of noise in self-organized decision making by the true slime mold Physarum polycephalum. PLoS ONE 12(3):e0172933.Google Scholar
Nisbett, R. & Ross, L. (1980)Human inference: Strategies and shortcomings of social judgment. Prentice Hall.Google Scholar
Reichert, M.B., Christiansen, I.C., Seiter, M. & Schausberger, P. (2017) Transgenerational loss and recovery of early learning ability in foraging predatory mites. Experimental and Applied Acarology 71(3):243–58.Google Scholar
Trewavas, A. (2003) Aspects of plant intelligence. Annals of Botany 92:120.Google Scholar
Tversky, A. & Kahneman, D. (1974) Judgment under uncertainty: Heuristics and biases. Science 185:1124–31.Google Scholar
Vaiseman, A. M. (2014) Early-life nutritional programming of longevity. Journal of Developmental Origins of Health and Disease 5(5):325–38.Google Scholar
Werner, G. D. A., Strassmann, J. E., Ivens, A. B. F., Engelmoer, D. J. P., Verbruggen, E., Queller, D. C., Noë, R., Johnson, N. C., Hammerstein, P. & Kiers, E. T. (2014) Evolution of microbial markets. Proceedings of the National Academy of Sciences USA 111(4):1237–44.Google Scholar
Wolf, D. M., Vazirani, V. V. & Arkin, A. P. (2005) Diversity in times of adversity: Probabilistic strategies in microbial survival games. Journal of Theoretical Biology 234(2):227–53.Google Scholar