Periodic Reporting for period 3 - CholAminCo (Synergy and antagonism of cholinergic and dopaminergic systems in associative learning)
Reporting period: 2020-05-01 to 2021-10-31
Learning, memory and attention are under the control of our ‘inner drug’ systems including acetylcholine and dopamine, also known as neuromodulators. However, how these neuromodulators work together during complex processes such as learning is not known. Because diseases of learning, like dementia, are treated with drugs acting on the acetylcholine and dopamine system, it is important to investigate this problem to later develop more specific and efficient cures. Therefore, we are investigating these two systems in parallel in a set of technically challenging mouse experiments. We expect to reveal how acetylcholine and dopamine acts synergistically or competitively during learning, memory and attention processes.
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 already published (Solari et al., 2018, Open source tools for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations). We also developed software tools to speed up the experiments, already made freely available (Szell et al., OPETH: Open Source Solution for Real-time Peri-event Time Histogram Based on Open Ephys, bioRxiv; software downloadable from github repository).
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 as preprint (Laszlovszky et al., Distinct synchronization, cortical coupling and behavioural function of basal forebrain cholinergic neuron types, bioRxiv) and we are in the process of peer review. Further results are in preparation; therefore, they are not yet public.
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 as preprint (Laszlovszky et al., Distinct synchronization, cortical coupling and behavioural function of basal forebrain cholinergic neuron types, bioRxiv) and we are in the process of peer review. Further results are in preparation; therefore, they are not yet public.
We expect to progress beyond current state of art both in terms of techniques and in scientific results.
We already developed innovations that increase the efficiency of the experiments by allowing better experimental control (Solari et al., 2018, Open source tools for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations) and online neural activity monitoring (Szell et al., OPETH: Open Source Solution for Real-time Peri-event Time Histogram Based on Open Ephys). We are working on behavior automation that could fully automate part of the experiments and non-invasive localization of implants.
Neuromodulators are rarely studied in parallel and there is no simultaneous recording of cholinergic and dopaminergic neurons yet. We expect that achieving such recordings will reveal the potential correlations of the two systems. This will help us understand whether these neurons encode similar or different behavioral variables and under which conditions they act synergistically or antagonistically. Such knowledge will lead us closer to understand how these neuromodulatory systems jointly control learning and memory, which is also important with respect to Alzheimer’s and Parkinson’s disease.
We already developed innovations that increase the efficiency of the experiments by allowing better experimental control (Solari et al., 2018, Open source tools for temporally controlled rodent behavior suitable for electrophysiology and optogenetic manipulations) and online neural activity monitoring (Szell et al., OPETH: Open Source Solution for Real-time Peri-event Time Histogram Based on Open Ephys). We are working on behavior automation that could fully automate part of the experiments and non-invasive localization of implants.
Neuromodulators are rarely studied in parallel and there is no simultaneous recording of cholinergic and dopaminergic neurons yet. We expect that achieving such recordings will reveal the potential correlations of the two systems. This will help us understand whether these neurons encode similar or different behavioral variables and under which conditions they act synergistically or antagonistically. Such knowledge will lead us closer to understand how these neuromodulatory systems jointly control learning and memory, which is also important with respect to Alzheimer’s and Parkinson’s disease.