We specifically aimed to investigate neurons expressing acetylcholine (cholinergic neurons) or dopamine (dopaminergic neurons) in mice performing different associative learning tasks. We designed a custom-built, open source setup for these studies that we have published (Solari et al., 2018, Open source tools for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations, Frontiers in Systems Neuroscience). We also developed software tools to speed up the experiments, made freely available (Szell et al., 2020, OPETH: Open Source Solution for Real-time Peri-event Time Histogram Based on Open Ephys, Frontiers in Neuroinformatics; software downloadable from github repository). In addition, we introduced a new micro-CT-based method to allow more precise mouse surgeries (Kiraly et al., 2020, In vivo localization of chronically implanted electrodes and optic fibers in mice, Nature Communications) and also achieved fully automated mouse training in reduced-stress environment (Birtalan et al., 2020, Efficient training of mice on the 5-choice serial reaction time task in an automated rodent training system, Scientific Reports).
We first investigated cholinergic neurons separately and found that these cells come in two clearly distinct types. The first type emits tight packages of action potentials, called bursts, which specifically signal reinforcing events (rewards and punishments) and strongly engage the cerebral cortex. The second type is incapable of burst firing; instead, these cells show slow rhythmic activity, often independent of each other, but occasionally synchronizing with cortical activity, thus influencing behavioral performance. We propose that these two types of cholinergic neurons have different roles in associative learning. These results are published (Laszlovszky et al., 2020, Distinct synchronization, cortical coupling and behavioural function of basal forebrain cholinergic neuron types, Nature Neuroscience).
We compared the activity of the cholinergic and dopaminergic neuromodulatory systems as one of the major goals of this research program. We found that these systems convey partially similar information about predicting future outcomes. The two systems acted similarly when future rewards were predicted; however, opposing activity could be found when negative outcomes (i.e. future punishments) could be predicted (see our publication Hegedus et al., 2022, Cholinergic activity reflects reward expectations and predicts behavioral responses, iScience). In addition, the two systems showed different adaptation speed to a changing environment as well as a surprising complex correlation structure (Sutrgill et al., 2020, Basal forebrain-derived acetylcholine encodes valence-free reinforcement prediction error, bioRxiv; a final publication is in preparation).
