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A Multimodal Approach to Representational Similarity Analysis
Authors:
SU, L., WINGFIELD, C., BOZIC, M., FONTENEAU, E., MARSLEN-WILSON, W and KRIEGESKORTE, N.
Reference:
16th Annual Meeting of the Organization for Human Brain Mapping
Year of publication:
2010
CBU number:
7160
Abstract:
Multivariate Pattern Analysis (MVPA) has been successfully applied to fMRI (e.g. Haxby et al., 2001; Kriegeskorte et al., 2006; Haynes and Rees, 2006) and (quasi) time series data (Mourão-Miranda et al., 2007). The particular approach of Representational Similarity Analysis (RSA; Kriegeskorte et al., 2008a) has also demonstrated potential to integrate neuroscientific data from different modalities, experimental designs, or even species. For instance, RSA has been used to relate cell-recording from monkey Inferior Temporal cortex (IT) with the blood-oxygen-level dependent responses from human IT (Kriegeskorte et al., 2008b). Unlike mass-univariate approaches such as SPM (Friston et al., 1995), RSA is based on the pattern-information that is naturally embedded in multi-channel recording of neural activations. Despite some previous endeavours, application of MVPA across modalities is still very limited. Here, we present recent developments in our work to extend RSA to both fMRI and MEG/EEG data in a unified framework.
