ePoster

ACETYLCHOLINE AND DOPAMINE TRACK PROGRESSION IN THE SERIAL REACTION TIME TASK IN MICE

Hanga Dormánand 5 co-authors

HUN-REN Institute of Experimental Medicine

FENS Forum 2026 (2026)
Barcelona, Spain
Board PS07-10AM-362

Presentation

Date TBA

Board: PS07-10AM-362

Poster preview

ACETYLCHOLINE AND DOPAMINE TRACK PROGRESSION IN THE SERIAL REACTION TIME TASK IN MICE poster preview

Event Information

Poster Board

PS07-10AM-362

Abstract

Implicit sequence learning is integral to performing many everyday activities, such as language use and sports, yet the underlying mechanisms remain poorly understood. In the Serial Reaction Time Task (SRT), subjects are required to respond to sequences of visual stimuli in a limited time. As a measure of implicit sequence learning, performance is typically compared between sequential blocks with a deterministic, and baseline blocks with a randomized order of stimuli. Here, we conducted the SRT in mice in conjunction with dual photometry measurements to gain mechanistic insights into the learning process. We found that animals could rely on implicit learning during the task, as evidenced by higher accuracies and faster reaction times in sequential relative to baseline blocks. In the final phase of the training, subjects received a water reward after four consecutive correct trials. We found that the neuromodulators acetylcholine and dopamine tracked the progression toward reward in successful trial sequences. Namely, acetylcholine response to the stimulus in the basolateral amygdala increased monotonously over the four correct trials, while dopamine in the prelimbic area exhibited a reverse tendency, decreasing monotonously until the third step and reaching its peak at the last (rewarded) trial. Interestingly, this effect was present regardless of whether stimuli were presented in a deterministic or random order, suggesting that these activity patterns might be related to reinforcement rather than the implicit learning aspect of the task. Further investigation will target a potential implicit learning-specific signature of the observed neuromodulator dynamics, as well as their oscillatory nature.

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