Retroactive effect of dopamine on hippocampal spike timing-dependent plasticity

How can the brain store our experiences in memory? And of all the events that we experience each day, why is it that some are remembered and others not? Many factors may influence how well we remember. Whether we remember a particular event or not is influenced not only by what happens during the event, but also by what happens after the event. For example, the presentation of a reward may help us remember the event that preceded the reward. In this proposal, we will study the basic mechanisms for how reward may influence memory.
It is generally believed that memories are stored as changes in the connections between the nerve cells of the brain. This is known as synaptic plasticity. In this project, we will investigate the basic rules for how these changes are induced, and specifically, how a reward signal in the brain, dopamine, can influence this plasticity. To address these questions, we will use a new technique, known as optogenetics. This technique enables us to activate specific cell types using a laser. The specificity is achieved by expressing a light-sensitive protein in only one specific cell type. In this way, we can isolate a specific connection in the brain, and we can release dopamine specifically onto those connections. We will test the hypothesis that dopamine is capable of altering the rules of synaptic plasticity. Specifically, we will test whether dopamine is capable of modulating plasticity retroactively, and thus help explain how rewards may influence memory for events that led up to the reward. We will also investigate the molecular cascades that dopamine acts on to produce these changes in synaptic plasticity. The results should give us new insights into memory and could potentially open up new avenues for improving memory in ageing individuals and for treating memory disorder.

The overall aim of this proposal is to investigate the retroactive modulation of hippocampal spike timing-dependent plasticity (STDP) by dopamine, and the underlying mechanisms. To this end, we will use optogenetics to study the CA3-to-CA1 synaptic connection in isolation without the co-activation of other excitatory pathways or neuromodulatory inputs that would be inevitable using extracellular electrical stimulation. To express channelrhodopsin specifically in CA3 afferent input to CA1, we would use Grik4-cre mice cross-bred with Ai32 mice, or inject a Cre-dependent viral construct into the CA3 of Grik4-cre mice. To characterise hippocampal STDP time windows in control condition, experimental protocols would be employed in which presynaptic optogenetic activation would be paired with postsynaptic action potentials, with timing intervals between presynaptic stimulation and postsynaptic spikes varying between -100 ms and +100 ms between experiments The effect of dopamine would be investigated using bath application, uncaging and optogenetic release of dopamine, the latter using DAT-cre mice. Dopamine would be applied at various time points after the pairing protocol. Our preliminary data show that dopamine can retroactively modulate the direction of plasticity. The underlying mechanisms would be investigated using dopamine receptor agonists and antagonists and modulators of various intracellular signalling pathways including the cAMP-PKA cascade, for which we have preliminary evidence to suggest is important for the retroactive effect of dopamine on synaptic plasticity.
The results of this study would indicate a novel mechanism for the coupling of the time scales of induction of STDP to the time scales of events at behavioural level.

The proposed project aims to understand the effect of reward on synaptic plasticity. We have identified four areas of possible impact:
1. Computational neuroscience and machine learning. The results of our studies are likely to be of significant interest to researchers in computational neuroscience and machine learning. The algorithms used by the brain will be important for biologically inspired reinforcement learning. We will collaborate with computational neuroscientists to increase the impact of our results.
2. Robotics. Algorithms that are capable of seeking novelty and navigating towards rewarding locations would be useful to enable robots and drones to search more efficiently through an environment. We intend to contact investigators in robotics to explore possible interactions.
3. Education. Better understanding of the mechanisms of reward-based learning could have implications for education, and we would discuss with researchers in the neuroscience of education to understand if our basic findings might have practical applications in education.
4. Combating age-related memory decline. Better understanding of reward processing and how it influences memory could have important consequences for treatment of normal age-related memory decline as well as memory disorders such as dementia. We will share our insights with clinicians to enable them to utilise new basic understanding for treating patients.
In addition, we would communicate our research to the wider public.