Elucidating the basis of inter-individual differences in learning

Some individuals learn faster than others but the molecular and circuit basis of these inter-individual differences are unknown. In principle, differences in learning could be due to differences in: 1) numbers or types of neurons in learning circuits; 2) patterns of synaptic connections between neurons; 3) functional strengths of connections; 4) baseline excitability and intrinsic properties of neurons; or 5) second messenger cascades and effector molecules that implement synaptic plasticity. These properties are dependent on specific patterns of gene expression in neurons that write or store memories. However, identifying homologous neurons in different individuals and comparing their synaptic connectivity, functional properties and transcriptomes is challenging in larger brains. We propose to use the tractable genetic model system, the Drosophila melanogaster larva, to uncover the circuit and molecular basis of differences in associative learning between distinct strains of the same species. Due to its small size, the 1st instar larval brain (with ca. 3000 neurons) can be rapidly imaged with electron-microscopy (EM) and we have recently published the synaptic-resolution connectome of one larval brain, revealing all neurons and their connections1. Most neurons are uniquely identifiable based on their morphology and gene expression and we have generated a collection of selective genetic driver lines, each targeting gene expression to a single neuron per brain hemisphere, that allow manipulation of homologous neurons in different individuals. Like all insects, Drosophila larvae have a higher-order learning circuit, the mushroom body (MB), specialised in forming associative memories. We have characterised the connectivity and functional roles of the core components of the larval MB and identified specific dopamine neurons (DANs) that drive appetitive or aversive learning, as well as their target neurons that store and recall memories. Thus, we know exactly which neurons are involved in writing and storing aversive or appetitive odour memories and we can selectively label and manipulate these neurons in different individuals, using our selective GAL4 lines. Furthermore, we have developed automated methods for training larvae to avoid or approach odours by pairing them repeatedly with punishments or rewards2,3. Using these methods, we have identified a strain of D. melanogaster larvae that learn faster than others, even though their innate responses to conditioned and unconditioned stimuli are the same. With these tools and findings in hand, we are in a unique position to identify structural, electrophysiological and molecular underpinnings of differences in learning between different strains of the same species by performing the following Aims: Aim 1) Identify differences in synaptic connectivity and activity of learning-circuit neurons between the faster- and slower-learner strain and determine which differences in activity improve learning. Aim 2) Identify genes differentially expressed in specific learning-circuit neurons between the faster- and slower learner strain that can improve learning and their mechanisms of action. By revealing circuit features that improve learning this project will provide fundamental insights into the way in which learning is implemented and regulated in the brain and may provide potential avenues for treating learning deficits and improving artificial neural networks. Furthermore, the project will reveal gene molecules that enhance learning and their mechanisms of action. Many genes implicated in learning and memory to date have conserved functions across the animal kingdom, so we expect the genes and mechanisms we discover here will also be conserved.