Talk1: Estimating Representational Dissimilarity Measures
Talk2: Time-Resolved RSA: Applying RSA to Single-Cell Recordings and EEG/MEG Data
In the first talk, I'll cover the different approaches in estimating representational dissimilarities. I'll show how multivariate noise normalisation can lead to more reliables estimates of fMRI pattern dissimilarities. In the second talk, I'll talk about time-resolved RSA. Having measurements that have high temporal resolution allows us to investigate the representational dynamics as well. I'll show examples of applying RSA to single-cell data (area MT of macaque monkeys), MEG and EEG, each aiming at its own question: encoding of visual features, working memory and decision making.
In the final session, I'd like to lead a discussion on the questions we can work together. That includes applying topological data analysis to neural data and studying the grid cells.
