The role of different midbrain dopamine neuron populations in signalling reward and cost
Lead Research Organisation:
University of Bristol
Department Name: Physiology and Pharmacology
Abstract
The brain must learn to use environmental cues to predict whether an action will have positive or negative consequences and the associated cost (e.g. effort) of performing the action. This type of learning involves the chemical messenger dopamine and there are good theoretical models that explain how the nerve impulses generated by dopamine-releasing cells might signal reward. However, despite the elegant simplicity of these models, at the cellular level there is greater complexity. For example, dopamine cells seem to consist of several populations which convey different aspects of the reward signal. Therefore, to better understand reward processes and when these go awry (e.g. in addiction), we must first understand how different dopamine-cell populations signal different parts of the reward signal and to which parts of the brain these signals are sent.
To do this, we will divide populations of dopamine cells according to the brain regions that they innervate and use the combination of different molecules present in each population as a kind of barcode to identify them. We will then use newly-developed, powerful techniques to record nerve impulses from individual dopamine cells in mice during a reward-task and label each recorded neuron. We will investigate how different populations of dopamine cells signal 1) positive and negative consequences and 2) the amount of effort required to obtain reward. We will use each labelled dopamine cell's 'barcode' to tell us where in the brain the signals were sent. To further test the role of different dopamine-cell populations, we will use cutting-edge technologies to measure dopamine released in a particular brain-region and then switch-off one of the dopamine-cell populations. We will also use computer simulations to help us interpret how the dopamine nerve-impulses translate into dopamine release in different regions of the brain.
This research will help us to better understand some of the complexity of reward-related signalling and enhance our theoretical models of learning. We will define populations of dopamine cells and reveal which brain regions receive different components of the reward signal. The 'barcodes', data, and computer models we generate will enable us and other researchers to build a better picture of reward learning and understand how it goes wrong in brain disorders.
To do this, we will divide populations of dopamine cells according to the brain regions that they innervate and use the combination of different molecules present in each population as a kind of barcode to identify them. We will then use newly-developed, powerful techniques to record nerve impulses from individual dopamine cells in mice during a reward-task and label each recorded neuron. We will investigate how different populations of dopamine cells signal 1) positive and negative consequences and 2) the amount of effort required to obtain reward. We will use each labelled dopamine cell's 'barcode' to tell us where in the brain the signals were sent. To further test the role of different dopamine-cell populations, we will use cutting-edge technologies to measure dopamine released in a particular brain-region and then switch-off one of the dopamine-cell populations. We will also use computer simulations to help us interpret how the dopamine nerve-impulses translate into dopamine release in different regions of the brain.
This research will help us to better understand some of the complexity of reward-related signalling and enhance our theoretical models of learning. We will define populations of dopamine cells and reveal which brain regions receive different components of the reward signal. The 'barcodes', data, and computer models we generate will enable us and other researchers to build a better picture of reward learning and understand how it goes wrong in brain disorders.
Technical Summary
In order to choose optimum actions, the brain must associate environmental stimuli with an outcome, distinguish whether the outcome is positive, and determine the cost (e.g. effort) associated with obtaining it. Dopamine is thought to provide a uniform teaching signal which guides such learning. However, the neurons that generate the signal are heterogeneous, with different neurons signalling different aspects of reward. How then can such diverse neurons transmit a coherent signal to guide learning?
Recent evidence suggests that subpopulations of neurons innervating different regions encode different aspects of reward; it is therefore essential to define how a neuron encodes reward in the context of which brain region it innervates. To achieve this, we will identify combinations of molecular markers which define populations of midbrain dopamine neurons projecting to particular regions of the nucleus accumbens and striatum. We will then record and label single dopamine neurons in head-fixed, behaving mice, and use the molecular signatures to determine how different populations of neurons signal reward and the cost of obtaining it.
We will first examine how neurons projecting to different regions differentially encode positive and negative outcomes. Then, to investigate how neuronal activity translates into dopamine release, we will optogenetically silence one of the target-defined populations and measure dopamine release using fast-scan cyclic voltammetry during a positive/negative outcome task. To examine encoding of cost we will use an instrumental task where the effort required to obtain reward is varied. We will record the activity of different, target-defined dopamine neurons during high- and low-effort trials. These cutting-edge experiments will elucidate how different aspects of reward are encoded by discrete populations of dopamine neurons and transmitted to different forebrain regions.
Recent evidence suggests that subpopulations of neurons innervating different regions encode different aspects of reward; it is therefore essential to define how a neuron encodes reward in the context of which brain region it innervates. To achieve this, we will identify combinations of molecular markers which define populations of midbrain dopamine neurons projecting to particular regions of the nucleus accumbens and striatum. We will then record and label single dopamine neurons in head-fixed, behaving mice, and use the molecular signatures to determine how different populations of neurons signal reward and the cost of obtaining it.
We will first examine how neurons projecting to different regions differentially encode positive and negative outcomes. Then, to investigate how neuronal activity translates into dopamine release, we will optogenetically silence one of the target-defined populations and measure dopamine release using fast-scan cyclic voltammetry during a positive/negative outcome task. To examine encoding of cost we will use an instrumental task where the effort required to obtain reward is varied. We will record the activity of different, target-defined dopamine neurons during high- and low-effort trials. These cutting-edge experiments will elucidate how different aspects of reward are encoded by discrete populations of dopamine neurons and transmitted to different forebrain regions.
Planned Impact
The main deliverables from this work are: 1) Identification of molecular markers that define populations of dopamine neurons projecting to different brain regions. 2) Mechanistic insight into how different populations signal positive and negative outcomes and the cost associated with obtaining them. These findings will increase our understanding of how discrete populations of dopamine neurons encode different aspects of reward and how these signals are transmitted to different brain regions. Defining molecular signatures of dopaminergic populations will enable researchers in the field to better understand the development of different groups of dopaminergic neurons and to generate new tools to study the function of discrete populations. The results will also enable us and other researchers to better understand reward learning and how it goes wrong. For example, while this research is not focussed on mechanisms of addiction, further understanding the fundamental processes underlying reinforcement learning will improve our knowledge of how differences in these processes may result in overeating, drug abuse or other forms of addiction (which are estimated to have social and economic costs for the UK exceeding £60bn per year).
The findings from this research will primarily benefit academic labs researching reward, the basal ganglia, development, addiction, and disorders involving the dopaminergic system (e.g. Parkinson's, Schizophrenia). Further understanding signalling by dopaminergic neurons may also provide insight to druggable targets for new or improved therapies. To realise these benefits we will disseminate our findings through talks at scientific meetings, by rapid publication in open-access journals and will make available data, computational models and equipment designs arising from this work.
The other major beneficiary is the post-doctoral research assistant on this programme. They will receive training in cutting-edge in vivo techniques only available in a few laboratories worldwide. This will be of significant value both to them and UK science, given the shortage of researchers with in vivo expertise in both academia and industry. In addition to practical techniques, they will also gain skills in writing, presentation and project management, which would be of benefit in all employment sectors.
The findings from this research will primarily benefit academic labs researching reward, the basal ganglia, development, addiction, and disorders involving the dopaminergic system (e.g. Parkinson's, Schizophrenia). Further understanding signalling by dopaminergic neurons may also provide insight to druggable targets for new or improved therapies. To realise these benefits we will disseminate our findings through talks at scientific meetings, by rapid publication in open-access journals and will make available data, computational models and equipment designs arising from this work.
The other major beneficiary is the post-doctoral research assistant on this programme. They will receive training in cutting-edge in vivo techniques only available in a few laboratories worldwide. This will be of significant value both to them and UK science, given the shortage of researchers with in vivo expertise in both academia and industry. In addition to practical techniques, they will also gain skills in writing, presentation and project management, which would be of benefit in all employment sectors.
People |
ORCID iD |
Paul Dodson (Principal Investigator) |
Publications
Reynolds JNJ
(2022)
Coincidence of cholinergic pauses, dopaminergic activation and depolarisation of spiny projection neurons drives synaptic plasticity in the striatum.
in Nature communications
Description | We have found that different groups of dopamine cells signal reward in different ways. To do this we categorised dopamine cells according to where in the brain they send information and the different proteins they express. We then recorded how different dopamine cells signal reward, and then married the two pieces of information together to understand the types of different signals that are sent. |
Exploitation Route | These findings will be used by other academics to enhance their understanding of reward systems and guide future research. In addition, it will be used by computational modelers to improve current, and generate new, models. |
Sectors | Education |
Description | Academic Research Hub for the Prevention of Gambling Harms |
Amount | £4,000,000 (GBP) |
Organisation | GambleAware |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 07/2022 |
End | 06/2027 |
Description | BrainSight: Imaging of neural codes over the lifecourse |
Amount | £203,000 (GBP) |
Funding ID | BB/S019227/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 07/2019 |
End | 06/2020 |
Description | Encoding of decision making by dopamine neurons |
Amount | £300,000 (GBP) |
Funding ID | 2279496 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 10/2019 |
End | 09/2023 |
Description | The role of cerebellum in dopamine neuron reward prediction error coding |
Amount | £538,547 (GBP) |
Funding ID | BB/T013907/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 12/2020 |
End | 06/2023 |
Description | WaterR: A tool for better management and monitoring of rodent fluid intake |
Amount | £74,391 (GBP) |
Funding ID | NC/V000993/1 |
Organisation | National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) |
Sector | Public |
Country | United Kingdom |
Start | 05/2020 |
End | 05/2022 |
Title | Home cage activity monitor |
Description | We developed a low cost activity monitor to assess activity in the animals home cage |
Type Of Material | Technology assay or reagent |
Year Produced | 2019 |
Provided To Others? | No |
Impact | The tool enabled us to perform non-invasive activity monitoring. Because activity was monitored in the animals home-cage it was less stressful for the animals |
Title | Stereotaxic holder |
Description | A holder for mounting equipment (e.g. an injection pipette holder) to a Kopf or Stoelting stereotaxic arm. |
Type Of Material | Technology assay or reagent |
Year Produced | 2019 |
Provided To Others? | Yes |
Impact | None yet |
URL | https://doi.org/10.5523/bris.39c1ki3hce9yk2g7lcnj0kkv2j |
Title | WaterR: A tool for better management and monitoring of rodent fluid intake |
Description | We have developed and established a low-cost (<£50) device (named WaterR) for automated home-cage water delivery and monitoring for rodents. Automation of fluid control will help to refine procedures by minimising the degree of water restriction used and thus not only reduce the cumulative effects experienced by each animal, but in some cases result in lower severity of procedures. |
Type Of Material | Technology assay or reagent |
Year Produced | 2019 |
Provided To Others? | No |
Impact | WaterR is helping to refine fluid control procedures by minimising the degree of water restriction used and thus not only reduce the cumulative effects experienced by each animal, but in some cases result in lower severity of procedures. |
Title | anaesthesia mask (04-2019) |
Description | 3d print files of an anaesthesia mask for gas anaesthesia for mouse surgery using Kopf or Stoelting stereotaxic frames |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
Title | coronal mouse brain block (04-2019) |
Description | 3d print files of a brain block to facilitate cutting blocks of mouse brain tissue for sectioning. |
Type Of Material | Database/Collection of data |
Year Produced | 2019 |
Provided To Others? | Yes |
Description | Computational prediction - value encoding |
Organisation | University of Bristol |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We provided data from neuronal recordings |
Collaborator Contribution | The partner performed computational modelling using our data |
Impact | No outputs yet |
Start Year | 2021 |
Description | Recording dopamine signals |
Organisation | University of Otago |
Department | Dunedin School of Medicine |
Country | New Zealand |
Sector | Academic/University |
PI Contribution | We supported research from groups at these universities by recording dopamine signals during learning |
Collaborator Contribution | Groups at these universities recorded neural signals from other brain regions during learning |
Impact | Publication |
Start Year | 2021 |
Description | Recording dopamine signals |
Organisation | University of Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We supported research from groups at these universities by recording dopamine signals during learning |
Collaborator Contribution | Groups at these universities recorded neural signals from other brain regions during learning |
Impact | Publication |
Start Year | 2021 |
Title | 3d printed syringe drive |
Description | These are downloadable files for 3d printing an 'easy to make' piece of behavioural equipment equipment. The syringe drive was designed to be a low-cost device to repeatedly deliver small volumes (~10ul) or to slowly deliver larger volumes. One example use of the pump is to provide liquid rewards in operant behavioural experiments. |
Type Of Technology | Physical Model/Kit |
Year Produced | 2018 |
Impact | none yet (in progress) |
URL | https://data.mrc.ox.ac.uk/data-set/syringe-pump |
Description | 3D printing workshop for behavioural research |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Other audiences |
Results and Impact | We held a workshop on 3D design and printing for behavioural research at the university of Bristol. ~40 scientists and students attended the workshop. Many that attended went on to design and 3d print equipment for their own experiments |
Year(s) Of Engagement Activity | 2019 |
Description | Parkinson's patients visit |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | Two short presentations on "Deep Brain Stimulation as a therapy for Parkinson's" and "Use of animals in Parkinson's research", followed by a laboratory tour, talks, and a chance to meet with scientists. The visit concluded with a Q & A session, and a chance for the visitors to give their feedback. We took the opportunity to promote our local networks for Patient and Public Involvement (PPI) in research which resulted in half of the attendees signing up for PPI. |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.mrcbndu.ox.ac.uk/news/unit-hosts-parkinsons-groups-2018-mrc-festival-medical-research |
Description | Parkinson's research day 2019 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Patients, carers and/or patient groups |
Results and Impact | ~120 patients and carers attended a research day where we presented talks and discussed the drug discovery process. It was useful to discuss patient's needs. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.bna.org.uk/mediacentre/events/movement-disorders-research-showcase-bristol/ |
Description | Schools open day 2018 |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Schools |
Results and Impact | 70 GCSE/A level students from 6 local schools within Oxfordshire area attended the school open day. A range of hands-on practical sessions, lab tours and talks to provide the students with an insight into the nature and benefits of medical/brain research, and inspire them to pursue a career in science. Also in attendance were the Mrs Jean Fooks - Lord Mayor of Oxford, Cllr Chris Wright - Chair of Garsington Parish Council and Cllr Elizabeth Gillespie - South Oxfordshire District Council |
Year(s) Of Engagement Activity | 2018 |
URL | https://www.mrcbndu.ox.ac.uk/news/schools-open-day-2018 |