One of the first serious accounts for the emergence of anticipation in biological systems is due to Rosen [174], who defined an anticipatory system as:
“(...) a system containing a predictive model of itself and/or of its environment that allows it to change state at an instant in accord with the model’s predictions pertaining to a later instant.”
At this point, it is worth making a distinction between prediction and anticipation. The former is merely a representation of a future event or outcome, whereas the latter is a future- oriented decision, based on prediction. Butz et al. [47] described anticipation as:
(...) a process or behavior that does not only depends on past and present but also on predictions, expectations, or beliefs about the future.
Among the many examples of biological anticipation found in Rosen [174], we highlight the case of negatively phototropic organisms, i.e., organisms that are attracted to darkness. Rosen argues that while darkness in itself is physiologically neutral, it is correlated with non-neutral environmental features such as the absence of sighted predators. Effectively, such organisms would act in accordance with a built-in model that has somehow learned the correlation between moving towards darkness and higher chances of survival [174]. In this thesis, we argue for this particular viewpoint of anticipation as being triggered by learned correlations.
1.5.1
Signaling Theory
Meaningful correlations triggering anticipatory actions permeate the field of signaling theory. For instance, Thomas and Stoddart [206] made the case that some tree species react to the shortening of daylight in autumn by changing color and shedding their leafs in anticipation to the high physiological costs of maintaining them during winter, what otherwise could supersede the benefits from photosynthesis. Hamilton [105] suggested that “autumn coloration serves as an honest signal of defensive commitment against autumn colonizing insect pests”.
Signaling theory plays an important role for explaining the co-evolutionary dynamics be- tween different species. Signals would evolve to influence the behavior of the receiver to benefit the signaler. While those signals can be honest or dishonest8, they may in effect anticipate
a counteraction to mitigate or nullify the potential future actions of the receiver as predicted by the signaler. Models of mate selection are heavily influenced by this theory. For exam- ple, experiments with the mating dynamics of the jumping spider Phidippus clarus species in Sivalinghem et al. [191] showed that signaling rates “significantly predicted mating success in all copulations”. Males of other species such as Habronattus dossenus that made strong use of courtship signals were also found to suffer lower pre-mating cannibalism rates.
In an application of signaling theory to explain the dynamics of the job-market, Spence [197] defined hiring as an “investment under uncertainty” in which applicants signal their skills to
8The adaptive dynamics of the proportions of individuals within species relying on honest and dishonest
1.5. Biological Basis of Anticipatory Systems 21
the employer by showcasing their credentials. The informational value of such signals to the contractor emerges when he/she analyzes the benefits of hiring the applicants for which they predict positive correlation between the credentials shown and superior work performance.
1.5.2
Hormonal Regulation and Sensorimotor Control
In vertebrate species, anticipatory hormonal regulations can be triggered by the autonomic nervous system in response to stressful stimuli followed by the perception of endangerment. For instance, subconscious processes triggered by acute stress may release hormones such as epinephrine (adrenaline) into the bloodstream causing a diverse range of physiological responses in different organs, including increased heart and respiratory rates, increased blood vessels diameter, and muscle contraction.
Because such anticipatory responses prepare the body to respond to a potential future (harmful) event, not only they are thought to be crucial to triggering fight-or-flight-or-freeze [48] behavior, but also they play an essential role in sensorimotor control. For instance, muscle contractions can compensate eventual disturbances in the body’s balance, in anticipation of the potential harms of falling to the ground. Several experiments regarding the motor system dynamics have supported the existence of an internal model accountable for estimating the relative location of body members, what is essential when sensorial feedback is not available, as it is the case e.g. when walking in a dark room [222].
1.5.3
Anticipation as a Built in Feature of the Brain
It seems to us that the concept of a self-referential conscious brain fits nicely into Rosen’s definition of anticipatory systems. For instance, the acclaimed evolutionary biologist Richard Dawkins presented an interesting explanatory narrative of how the capacity of simulating the future may have evolved to enable animals to benefit from vicarious experience9 [64]:
“Natural selection built in the capacity to simulate the world as it is because this was necessary in order to perceive the world. You cannot see that two-dimensional patterns of lines on two retinas amount to a single solid cube unless you simulate, in your brain, a model of the cube. Having built in the capacity to simulate mod- els of things as they are, natural selection found that it was but a short step to simulate things as they are not quite yet-to simulate the future. This turned out to have valuable consequences, for it enabled animals to benefit from ’experience’, not trial-and-error experience in their own past (...), but vicarious experience in the safe interior of the skull. And once natural selection had built brains capable of simulating slight departures from reality into the imagined future, a further capacity automatically flowered. Now it was but another short step to the wilder reaches of imagination revealed in dreams and in art, an escape from mundane reality that has no obvious limits.”
9We understand “vicarious experiences” as those gained after generating and processing the feelings arising
One of the most prominent evidences that (primates) brains indeed encode mechanisms sup- porting simulation and vicarious experiences was the discovery of the so-called mirror neurons in the premotor cortex [171]. They are regarded as a distinctive class of neurons because they exhibit activity both when a motor task is executed and when the subject has access to a visual feedback of another subject performing the same motor task.
Barbey et al. [20] suggested that counter-factual thinking about the past (e.g. “Had I studied harder, I would have passed the exam.”) for improving future performance or simulating future behavior (e.g. “What would I do if X happens in the future?”) depend on structures in the prefrontal cortex. From functional magnetic resonance imaging (fMRI) experimental analyzes, Van Hoeck et al. [212] concluded that counter-factual and standard episodic thinking “(...) share a common brain network, involving a core memory network (hippocampal area, temporal lobes, midline, and lateral parietal lobes) and prefrontal areas that might be related to mentalizing (medial prefrontal cortex) and performance monitoring (right prefrontal cortex)”.
1.5.4
Game Theoretic Analyzes of Anticipation
It turns out that anticipation accordingly to feelings and expectations about the future can lead to a form of personal equilibria in a game theoretic framework. K´oszegi [137] conceived a model of sequential decision-making wherein the utility function of a DM is elicited not only by physical outcomes but also from their own expectations over future outcomes. He then argued that those two payoff components – future expectations and present actions – can interact and jointly lead to personal equilibrium, subject to the requirement that the current action conditioned on past expectations must attain a certain degree of consistency.
K´oszegi’s [137] model thus predicts equilibrium points resulting from the positive feedback between expectations and behavior, what resembles Merton’s notion of self-fulfilling prophe- cies [154]. This viewpoint may explain to a certain extent human behavior and emotions arising from the degree to which the DM is consistent over time. For instance, the willingness of a pessimistic DM to keep doing a riskless, low rewarding action can be higher if he/she had been wrongly believing that all other available options would also yield low rewards. Because of this prior belief, he/she may also not be willing to assume the cost of acquiring more informa- tion about alternative options – whose rewards could actually have been greatly improved since when the DM formulated his/her beliefs. Hence, because of the time consistency constraint, such DM will end up materializing his/her own prior expectations of acquiring low rewards.