Abstract:
The investigation of diseased brain is one of the major methods in cognitive
neuroscience. This approach allows numerous insights both into human cognition and
brain architecture. Most prominent is the method of lesion behaviour mapping, where
inferences about functional brain architecture are drawn from focally lesioned brains.
In the last 15 years, the state-of-the-art implementation of lesion behaviour mapping
has been voxel-based lesion behaviour mapping, which is based on the framework of
statistical parametric mapping. Recently, the validity of this method has been
criticised and multivariate methods have been proposed to complement or even
replace it.
In my thesis, I aim to evaluate these different methodological approaches to
lesion behaviour mapping and to provide guidelines on how lesion-brain inference
should be drawn. In my first empirical work, I investigate the validity of voxel-based
lesion behaviour mapping. It shows that previous studies overestimated biases
inherent to the method, and that validity can be improved by the use of correction
factors. The second empirical work deals with a recently developed method of
multivariate lesion behaviour mapping. On the one hand, I clarify how this method
can be used to obtain valid lesion-brain inference. On the other hand, I show that the
method is not able to overcome all limitations of voxel-based lesion behaviour
mapping. In my last work, I apply multivariate lesion behaviour mapping to
investigate the neural correlates of higher motor cognition. This analysis is the first to
identify a brain network to underlie apraxia, a disorder of higher motor cognition,
which underlines the benefits of the new multivariate approach in brain networks.
