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CEN launch, Gert Westermann


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CEN launch, Gert Westermann

  1. 1. Neuroscience, Computational Modelling and Education: Reflections on Neil Burgess’ talk Gert Westermann
  2. 2. Modelling already featured in Neil’s talk: x j x i w ij e.g. w ij -> w ij + ε x j x i w ij -> w ij + Δ w ij x j w j Different learning rules in hippocampus and striatum?
  3. 3. So what can modelling offer to neuroscience and education?
  4. 4. BEHAVIOUR Huge gap! Computational models
  5. 5. Models… <ul><li>… help us to understand how learning changes the brain </li></ul><ul><li>(to characterize the process of change) </li></ul><ul><li>Basic idea: </li></ul><ul><li>We observe a process (e.g., brain-behaviour correlates), </li></ul><ul><li>or more relevant here, a behavioural change </li></ul><ul><li>We develop a computational model that displays the ‘same’ behaviour </li></ul><ul><li>We know how the model works, and this becomes our theory of how the process works in real life </li></ul><ul><li>But this is not always followed. </li></ul>/rIt/ write
  6. 6. Neural network (connectionist) models <ul><li>Added (important) benefit: </li></ul><ul><li>Functionality of these models is inspired by how neurons work </li></ul>Although we should stay alert to the limits of this analogy.
  7. 7. Characterizing constraints on change <ul><li>Models as a tool to explore what affects change: </li></ul><ul><li>Environment </li></ul><ul><li>frequency of exposure </li></ul><ul><li>order of exposure (age of acquisition) </li></ul><ul><li>type of exposure (e.g., similarity between stimuli) </li></ul>
  8. 8. Characterizing constraints on change <ul><li>Genes/internal constraints </li></ul><ul><li>Structure/resources of the learning system </li></ul><ul><li>(critical periods, developmental disorders, speed-accuracy </li></ul><ul><li>trade-off in learning) </li></ul>ε = 0.1
  9. 9. Characterizing constraints on change <ul><li>Links between brain and cognitive development </li></ul><ul><li>Effect of environmental exposure on development of </li></ul><ul><li>functional structures </li></ul><ul><li>Effect of the integration of subsystems on behaviour </li></ul><ul><li>Maturation and experience-dependent plasticity </li></ul>
  10. 10. <ul><li>These aspects of models should be constrained by neuroscience: </li></ul><ul><ul><li>Mechanisms of synaptic change </li></ul></ul><ul><ul><li>Interplay of functional brain regions </li></ul></ul><ul><li>and give rise to relevant behaviour. </li></ul><ul><li>Converging evidence </li></ul>
  11. 11. Bridging the gap… <ul><li>Models can be built at different levels of abstraction. </li></ul><ul><li>Is there a level that is acceptable both to neuroscientists and psychologists? </li></ul><ul><li>I think: yes, if we constantly remind ourselves what a model is for. </li></ul>