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The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice

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Intermittent animal behavior: the adjustment-deployment dilemma.

Miguel Aguilera¹, Manuel G Bedia, Francisco Seron

¹University of Zaragoza.

Artificial Life

|April 16, 2014

Summary

Animal behavior often involves intermittent adaptation, a trade-off between adjusting a response and deploying it. Optimal solutions involve high intermittency, balancing fitness gains and losses, predictable by simple neural models.

Keywords:

Intermittent behavior adaptive behavior adjustment-deployment dilemma behavioral modeling

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Last Updated: May 1, 2026

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Area of Science:

Behavioral Ecology
Computational Neuroscience
Animal Behavior

Background:

Intermittency is a widespread phenomenon in animal behavior, reflecting complex adaptive strategies.
Existing models often simplify the dynamic trade-offs inherent in intermittent behaviors.

Purpose of the Study:

To formally characterize and solve the adjustment-deployment dilemma in intermittent adaptation.
To investigate the relationship between fitness dynamics and optimal intermittency levels.
To explore potential neural mechanisms underlying the resolution of this dilemma.

Main Methods:

Formal mathematical modeling of the adjustment-deployment dilemma.
Computational analysis to determine optimal solutions and fitness values.
Comparison of model predictions with empirical data on animal intermittent behaviors.

Main Results:

Optimal solutions invariably exhibit high intermittency between adjustment and deployment phases.
The achieved non-maximal fitness is determined by the ratio of adjustment gain to deployment decay rates.
A single continuous-time recurrent neuron model can effectively solve the dilemma under various conditions.

Conclusions:

The adjustment-deployment dilemma offers a unifying framework for understanding intermittent animal behaviors.
Simple neural mechanisms may underlie complex intermittent behavioral patterns observed across species.
Optimal intermittency strategies balance fitness improvement during adjustment with fitness decay during deployment.