- Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools (2011)
- Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.
- FOSE: a framework for open science evaluation (2012)
- Pre-publication peer review of scientific literature in its present state suffers from a lack of evaluation validity and transparency to the community. Inspired by social networks, we propose a framework for the open exchange of post-publication evaluation to complement the current system. We first formulate a number of necessary conditions that should be met by any design dedicated to perform open scientific evaluation. To introduce our framework, we provide a basic data standard and communication protocol. We argue for the superiority of a provider-independent framework, over a few isolated implementations, which allows the collection and analysis of open evaluation content across a wide range of diverse providers like scientific journals, research institutions, social networks, publishers websites, and more. Furthermore, we describe how its technical implementation can be achieved by using existing web standards and technology. Finally, we illustrate this with a set of examples and discuss further potential.