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Complex social ecology needs complex machineries of foraging

Published online by Cambridge University Press:  19 March 2019

Toshiya Matsushima
Affiliation:
Department of Biology, Faculty of Science, Hokkaido University, Sapporo 060-0810, Japan. matusima@sci.hokudai.ac.jphttps://www.sci.hokudai.ac.jp/~matusima/chinou3/Matsushima_english.html
Hidetoshi Amita
Affiliation:
Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, MD 20892-2510. amita.hidetoshi@gmail.com
Yukiko Ogura
Affiliation:
Department of Social Psychology, Graduate School of Humanities and Sociology, University of Tokyo, Tokyo 113-0033, Japan. ykk.ogr@gmail.com

Abstract

Uncertainty is caused not only by environmental changes, but also by social interference resulting from competition over food resources. Actually, foraging effort is socially facilitated, which, however, does not require incentive control by the dopamine system; Zajonc's “drive” theory is thus questionable. Instead, social adjustments may be pre-embedded in the limbic network responsible for decisions of appropriate effort-cost investment.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2019 

Classic theories of optimal foraging behaviors assumed single individuals that maximize the long-term gain rate while foraging in highly uncertain environments (Charnov Reference Charnov1976a; Stephens & Krebs Reference Stephens and Krebs1986). Because of their clear-cut arguments and fruitful sets of predictions, the optimality theories contributed not only to the behavioral ecology of animals, but also to the foundation of neuro-economics in humans (Glimcher Reference Glimcher2003). In particular, the marginal value theorem proposed for optimal patch-use behavior (Charnov Reference Charnov1976b) has been considered to represent a highly realistic situation to study the neural and pharmacological bases of value-based decision making (Blanchard & Hayden Reference Blanchard and Hayden2015; Hayden et al. Reference Hayden, Pearson and Platt2011; Matsunami et al. Reference Matsunami, Ogura, Amita, Izumi, Yoshioka and Matsushima2012). However, this is not enough. Most animals do not forage alone but do so in groups despite the enhanced competition over food resources.

In a group of foragers, as a result of the strong interdependence of consequences on each other's decisions, not one of the group of foragers can maximize the individual payoff (Giraldeau & Caraco Reference Giraldeau and Caraco2000). Instead, evolutionarily stable strategies are assumed to represent the stable and adaptive Nash equilibrium of the game-theoretical situation. A typical example is found in a producer-scrounger game, in which the former (producers, P) search and find food, but must share their find with the latter (scroungers, S). Note that each one does not necessarily follow a fixed strategy P or S, but can flexibly switch between them. We may further assume a group of opportunists, which can produce and scrounge at the same time. As the social foraging increases uncertainty, it is highly challenging for studying what is the best foraging decision.

Social facilitation appears under the social foraging accompanied by an increase in uncertainty (Ogura & Matsushima Reference Ogura and Matsushima2011). When animals such as domestic chicks are placed in an I-shaped maze with two terminal feeders at both ends, they start to actively shuttle between these feeders. Under the high level of uncertainty (i.e., the food supply is randomized at a low rate, and the subject is perfectly uncued), effort-cost investment is further enhanced if the subject is accompanied by competing foragers. Since systematically reviewed more than a half-century ago (Zajonc Reference Zajonc1965), enhancement in behavioral performance in the presence of conspecifics has been referred to as social facilitation. As an account generalizable to a wide variety of animals including humans, Zajonc proposed the drive theory. He hypothesized that the presence of others increases general arousal or level of drive, which is meant to be a non-selective enhancer of behavior in the sense that Hull (Reference Hull1943) argued. However, the assumed “drive” has not been addressed with respect to its causal machineries. As the social facilitation denotes a commonly found phenomenon, it does not have to imply any unitary and general mechanisms. Actually, Clayton (Reference Clayton1978) argues that this term can be used only descriptively, without specifying underlying causal processes.

The “incentive hope” hypothesis raised by the target article may sound like a renewed version of the drive theory by Zajonc, if the issues on the socially brought uncertainty are concerned. In this respect, we may reasonably predict that the dopaminergic system is involved in the social facilitation, which, however, was not true (Ogura et al. Reference Ogura, Izumi, Yoshioka and Matsushima2015). Dopamine-selective depletion by micro-infusion of 6-hydroxydopamine into the substantia nigra failed to suppress the social facilitation, even though a novel reinforcement learning was severely impaired. As the underlying neural substrates for the social facilitation, we would rather suggest the descending pathway from the limbic area in the telencephalon or the lateral part of the arcopallium (Arco) of domestic chicks (Xin et al. Reference Xin, Ogura, Uno and Matsushima2017b). On the one hand, Arco was initially assigned to be the avian counterpart of the mammalian amygdala (Phillips et al. Reference Phillips, Youngren and Peek1972) and also to a part of the motor/premotor area responsible for orofacial control (Wild et al. Reference Wild, Arends and Zeigler1985). On the other hand, lesions localized to Arco resulted in handling cost aversion in chicks (Aoki et al. Reference Aoki, Csillag and Matsushima2006), suggesting a functional similarity to the mammalian basolateral amygdala or anterior cingulate cortex. Lesions localized to the lateral Arco suppressed social facilitation, while sparing the foraging shuttles in the isolated (nonsocial, but yet highly uncertain) condition unchanged. Note that even without additional food gains, socially facilitated effort-cost investment can be beneficial (Xin et al. Reference Xin, Ogura and Matsushima2017a). Chicks foraging in pairs achieved a better matching to the food supply ratio and a significantly longer-lasting memory of the more profitable feeder. We would argue that if a group of opportunistic foragers shared information on the food resource more efficiently, the facilitated effort-cost investment could be paid in the long run. The game-theoretical nature of the social complexities also gives us ecologically reasonable accounts for a paradoxically high level of choice impulsiveness under competition (Amita et al. Reference Amita, Kawamori and Matsushima2010; Ogura et al. Reference Ogura, Amita and Matsushima2018). Behavioral adjustment to social foraging situations is supposed to be pre-embedded in decision mechanisms, allowing animals to flexibly change according to individual social and economic circumstances.

Considering these complexities in social foraging situations, it might be appropriate to assume a bit more complex machineries and processes than those assumed in the target article. The effort-control network is intensely intermingled with the social network responsible for conspecific perception, rather than (or in addition to) the incentive control network. To develop comprehensive views, it will be important to ask what sort of natural counterparts our psychological questions could have. By designing tasks in a manner that appropriately improves their external (or ecological) validity, we would more easily specify the internal processes underlying decision making.

References

Amita, H., Kawamori, A. & Matsushima, T. (2010) Social influences of competition on impulsive choices in domestic chicks. Biology Letters 6:183–86. doi: 10.1098/rsbl.2009.0748.Google Scholar
Aoki, N., Csillag, A. & Matsushima, T. (2006) Localized lesions of arcopallium intermedium of the lateral forebrain caused a handling-cost aversion in the domestic chick performing a binary choice task. European Journal of Neuroscience 24:2314–26. doi:10.1111/j.1460-9568.2006.05090.x.Google Scholar
Blanchard, T. C. & Hayden, B. Y. (2015) Monkeys are more patient in a foraging task than in a standard intertemporal choice task. PLoS One 10:e0117057. doi: 10.1371/journal.pone.0117057.Google Scholar
Charnov, E. L. (1976a) Optimal foraging: Attack strategy of a mantid. American Naturalists 110:141–51. doi:10.1086/283054.Google Scholar
Charnov, E. L. (1976b) Optimal foraging, the marginal value theorem. Theoretical Population Biology 9:129–36. doi: 10.1016/0040-5809(76)90040-X.Google Scholar
Clayton, D. A. (1978) Socially facilitated behavior. The Quarterly Review of Biology 53:373–92.Google Scholar
Giraldeau, L.-A. & Caraco, T. (2000) Social foraging theory. Princeton University Press.Google Scholar
Glimcher, P.W. (2003) Decisions, uncertainty, and the brain. MIT Press.Google Scholar
Hayden, B. Y., Pearson, J. M. & Platt, M. L. (2011) Neuronal basis of sequential foraging decisions in a patchy environment. Nature Neuroscience 14:933–39. doi: 10.1038/nn.2856.Google Scholar
Hull, C. (1943) Principles of behavior. Appleton-Century-Crofts.Google Scholar
Matsunami, S., Ogura, Y., Amita, H., Izumi, T., Yoshioka, M. & Matsushima, T. (2012) Behavioural and pharmacological effects of fluvoxamine on decision-making in food patches and the inter-temporal choices of domestic chicks. Behavioural Brain Research 233:577–86. doi: 10.1016/j.bbr.2012.05.045.Google Scholar
Ogura, Y., Amita, H. & Matsushima, T. (2018) Ecological bases of impulsive choice: Consequences of profitability-based short-sighted evaluation in the producer-scrounger game. Frontiers in Applied Mathematics and Statistics 4:49. doi: 10.3389/fams.2018.00049.Google Scholar
Ogura, Y., Izumi, T., Yoshioka, M. & Matsushima, T. (2015) Dissociation of the neural substrates of foraging effort and its social facilitation in the domestic chick. Behavioural Brain Research 294:162–76. http://dx.doi.org/10.1016/j.bbr.2015.07.052.Google Scholar
Ogura, Y. & Matsushima, T. (2011) Social facilitation revisited: Increase in foraging efforts and synchronization of running in domestic chicks. Frontiers in Neuroscience 5:91. 10.3389/fnins.2011.00091.Google Scholar
Phillips, R.E., Youngren, O.M., & Peek, F.W. (1972) Repetitive vocalizations evoked by local electrical stimulation of avian brains: I. Awake chickens (Gallus gallus). Animal Behaviour 20:689705.Google Scholar
Stephens, D. W. & Krebs, J. R. (1986) Foraging theory. Princeton University Press.Google Scholar
Wild, J. M., Arends, J. J. A. & Zeigler, H. P. (1985) Telencephalic connections of the trigeminal system in the pigeon (Columba livia): A trigeminal sensorimotor circuit. Journal of Comparative Neurology 234:441–64. doi:10.1002/cne.902340404.Google Scholar
Xin, Q., Ogura, Y. & Matsushima, T. (2017a) Four eyes match better than two: Sharing of precise patch-use time among socially foraging domestic chicks. Behavioural Processes 140:127–32. doi:10.1016/j.beproc.2017.04.020.Google Scholar
Xin, Q., Ogura, Y., Uno, L. & Matsushima, T. (2017b) Selective contribution of the telencephalic arcopallium to the social facilitation of foraging efforts in the domestic chicks. European Journal of Neuroscience, 45:365–80. doi: 10.1111/ejn.13475.Google Scholar
Zajonc, R. B. (1965) Social facilitation. Science 149:269–74.Google Scholar