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Updated: Mar 15, 2026

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in Free Moving Rodents
Published on: August 2, 2018
Previous motor activity affects the transition from uncertainty to decision making in snails
Tatiana A Korshunova1, Dmitry D Vorontsov1, Varvara E Dyakonova2
1Laboratory of Developmental Neurobiology, Institute of Developmental Biology, Russian Academy of Sciences, Moscow 119334, Russia.
Abstract:
One of the most widely accepted benefits of enhanced physical activity is an improvement in the symptoms of depression, including the facilitation of decision making. Up until now, these effects have been shown in rodents and humans only. Little is known about their evolutionary origin or biological basis, and the underlying cellular mechanisms also remain relatively elusive. Here, we demonstrate for the first time that preceding motor activity accelerates decision making in an invertebrate, the pond snail Lymnaea stagnalis To investigate decision making in a novel environment, snails, which normally live in water, were placed on a flat dry surface to simulate the potentially threatening consequence of being in an arid environment. This stimulus initiated two distinct phases in snail behaviour: slow circular movements, followed by intense locomotion in a chosen direction. The first phase was prolonged when the test arena was symmetrically lit, compared with one with an apparent gradient of light. However, forced muscular locomotion for 2 h prior to the test promoted the transition from random circular motions to a directional crawl, accompanied by an increase in crawling speed but with no effect on the choice of direction. Intense locomotion for 2 h also produced a strong excitatory effect on the activity of serotonergic neurons in L. stagnalis Our results suggest that the beneficial effects of physical exercise on cognitive performance in mammals might have deep roots in evolution, granting the opportunity to unravel the origins of such effects at the single-neuron and network levels.
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