Human behavioral complexity peaks at age 25

Nicolas Gauvrit (1) , Hector Zenil (2) , Fernando Soler-Toscano (3) , Jean-Paul Delahaye (4, 5) , Peter Brugger (6)

1 DIDIREM (EA_1547) - Équipe de Recherche en Didactique des Mathématiques
2 Chercheur indépendant
3 Universidad de Sevilla = University of Seville
4 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
5 SMAC - Systèmes Multi-Agents et Comportements
6 EAC - Espaces acoustiques et cognitifs

Random Item Generation tasks (RIG) are commonly used to assess high cognitive abilities such as inhibition or sustained attention. They also draw upon our approximate sense of complexity. A detrimental effect of aging on pseudo-random productions has been demonstrated for some tasks, but little is as yet known about the developmental curve of cognitive complexity over the lifespan. We investigate the complexity trajectory across the lifespan of human responses to five common RIG tasks, using a large sample (n = 3429). Our main finding is that the developmental curve of the estimated algorithmic complexity of responses is similar to what may be expected of a measure of higher cognitive abilities, with a performance peak around 25 and a decline starting around 60, suggesting that RIG tasks yield good estimates of such cognitive abilities. Our study illustrates that very short strings of, i.e., 10 items, are sufficient to have their complexity reliably estimated and to allow the documentation of an age-dependent decline in the approximate sense of complexity. Author summary It has been unclear how this ability evolves over a person's lifetime and it had not been possible to be assessed with previous classical tools for statistical randomness. To better understand how age impacts behavior, we have assessed more than 3,400 people aged 4 to 91 years old. Each participant performed a series of online tasks that assessed their ability to behave randomly. The five tasks included listing the hypothetical results of a series of 12 coin flips so that they would " look random to somebody else, " guessing which card would appear when selected from a randomly shuffled deck, and listing the hypothetical results of 10 rolls of a die. We analyzed the participants' choices according to their algo-rithmic randomness, which is based on the idea that patterns that are more random are harder to encode in a short computer program. After controlling for characteristics such as gender, language, and education. We have found that age was the only factor that affected the ability to behave randomly. This ability peaked at age 25, on average, and declined from then on. We also demonstrate that a relatively short list of choices, say 10 hypothetical coin flips, can be used to reliably gauge randomness of human behavior. A similar approach could be then used to study potential connections between the ability to behave randomly, cognitive decline, neurodegenerative diseases and abilities such as human creativity.

Domaines: Complexité [cs.CC]

Nicolas Gauvrit, Hector Zenil, Fernando Soler-Toscano, Jean-Paul Delahaye, Peter Brugger. Human behavioral complexity peaks at age 25. PLoS Computational Biology, 2017. ⟨hal-01745690⟩