JJ Orban de Xivry jj.orban@kuleuven.be Hands on session JJ Orban de Xivry jj.orban@kuleuven.be

Visuomotor rotation Changing the direction of cursor motion with respect to actual hand motion

Saving in visuomotor rotation

Interference Error (deg) Cycles (8 trials each) Krakauer et al. Journal of Neuroscience 2005

Model-free memory Huang, V. S., Haith, A. M., Mazzoni, P., & Krakauer, J. W. (2011). Rethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models. Neuron, 70(4), 787–801.

Model-free memory Huang, V. S., Haith, A. M., Mazzoni, P., & Krakauer, J. W. (2011). Rethinking motor learning and savings in adaptation paradigms: model-free memory for successful actions combines with internal models. Neuron, 70(4), 787–801.

Effect of reinforcement learning Shmuelof, L., Huang, V. S., Haith, A. M., Delnicki, R. J., Mazzoni, P., & Krakauer, J. W. (2012). Overcoming motor “forgetting” through reinforcement of learned actions. Journal of Neuroscience, 32(42), 14617–21.

Effect of reinforcement learning Shmuelof, L., Huang, V. S., Haith, A. M., Delnicki, R. J., Mazzoni, P., & Krakauer, J. W. (2012). Overcoming motor “forgetting” through reinforcement of learned actions. Journal of Neuroscience, 32(42), 14617–21.

Shmuelof: to do list Fit exponential to first learning phase Compute average during the last 20 trials of reinforcement Compare the two groups Look at error at the end of “error-clamp” measure. Did you reproduce the results from original paper? Fit a state-space model on the average data (from initial learning to end of error-clamp period). Any differences between the two groups?

Huang: to do list Fit exponential to first learning phase Fit exponential to second learning phase Compute average error at the end of washout Compare the two groups Fit a state-space model on the average data. Any differences between the two groups? What is the variability of the learning rate? How many subjects are needed to detect a change of learning rate of 50% (effect size = 0.5)? s= estimated standard deviation (from sample) d = effect size 2 is parameter for 95% confidence interval

Design of an experiment You are nothing without a good control group Inter-subject variability: need of a power analysis to compute require sample size Choosing the right variable (mid-movement, end of movement)

Richness of behavior Reaction time Feedforward (planning) vs feedback (online control of movement) Different measures of motor memory (faster relearning, interference, error-clamp measure, ) Many factors can influence motor memories (errors, binary reinforcement, reward, etc)

Further ideas How to obtain a motor memory (following learning, sequence learning, motor adaptation, bimanual coordination learning, etc.) How can you measure it, improve it, disrupt it, etc. Which patients are likely to be impaired at this memory? Motor behavior is really rich if it is adequately measured. Models can make predictions that are testable