Inter-Individual Differences in Cognitive Tasks: Focusing on the Shaping of Decision-Making Strategies

Abstract

In this paper, we review recent (published and novel) data showing inter-individual variation in decision-making strategies established by mice in a gambling task (MGT for Mouse Gambling Task). It may look intriguing, at first, that congenic animals develop divergent behaviors. However, using large groups of mice, we show that individualities emerge in the MGT, with about 30% of healthy mice displaying risk-averse choices while about 20-25% of mice make risk-prone choices. These strategies are accompanied by different brain network mobilization and individual levels of regional -prefrontal and striatal- monoamines. We further illustrate three ecological ways that influence drastically cognitive strategies in healthy adult mice: sleep deprivation, sucrose or artificial sweetener exposure, and regular exposure to stimulating environments. Questioning how to unmask individual strategies, what are their neural/neurochemical bases and whether we can shape or reshape them with different environmental manipulations is of great value, first to understand how the brain may build flexible decisions, and second to study behavioral plasticity, in healthy adult, as well as in developing brains. The latter may open new avenues for the identification of vulnerability traits to adverse events, before the emergence of mental pathologies.

Behavioral, molecular and neuronal mechanisms involved in recognition memory retrieval under degraded spatial cues in the rat hippocampus

“…However, the variability observed could also be due to individual variability in the encoding of the environment between trials that results in the animal being able to retrieve the original memory in some trials but not in others. In fact, interindividual and intraindividual variability in behavior is more the rule than the exception in behavioral studies and it only recently has caught the attention of researchers [84][85][86][87]. However, the relationship between remapping of these representations and the behavioral output of memory recall remained unclear.…”

Diverse and flexible behavioral strategies arise in recurrent neural networks trained on multisensory decision making

“…Individuals usually display a high level of variability in their cognitive abilities and goaldirected behavior 1,2 , often exceeding what would be expected even from genetically identical subjects [3][4][5] . When performing cognitive tasks such as decision making [6][7][8][9] or multisensory integration [10][11][12][13][14][15] , individuals have often been shown to develop separate choice strategies [16][17][18][19][20] . In the case of mice performing decision-making tasks, Pittaras and colleagues observed a broad distribution of behavioral strategies depending on the risk-aversiveness of the animals 17 .…”

“…When performing cognitive tasks such as decision making [6][7][8][9] or multisensory integration [10][11][12][13][14][15] , individuals have often been shown to develop separate choice strategies [16][17][18][19][20] . In the case of mice performing decision-making tasks, Pittaras and colleagues observed a broad distribution of behavioral strategies depending on the risk-aversiveness of the animals 17 . Rats performing context-dependent decision-making tasks display individually different behavioral strategies, even when their performance levels were similar 18 .…”

“…Behavioral strategies are, furthermore, not an invariant quality for a given animal, as mice have been shown to alter their decision strategy within the same session 19,20 . While the mechanisms underlying different behavioral strategies are still unclear, there is evidence of behavioral strategies being reflected in neurobiological features 17 , suggesting a connection between behavioral variability and neural and circuit heterogeneity, which is already known to play a beneficial role in neural processing and computations [21][22][23][24][25] .…”