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Recently, olfactory training has been introduced as a promising treatment for patients with olfactory dysfunction. However, less is known about the neuronal basis and the influence on functional networks of this training. Thus, we aimed to investigate the neuroplasticity of chemosensory perception through an olfactory training program in patients with smell loss. The experimental setup included functional MRI (fMRI) experiments with three different types of chemosensory stimuli. Ten anosmic patients (7f, 3m) and 14 healthy controls (7f, 7m) underwent the same testing sessions. After a 12-week olfactory training period, seven patients (4f, 3m) were invited for follow-up testing using the same fMRI protocol. Functional networks were identified using independent component analysis and were further examined in detail using functional connectivity analysis. We found that anosmic patients and healthy controls initially use the same three networks to process chemosensory input: the olfactory; the somatosensory; and the integrative network. Those networks did not differ between the two groups in their spatial extent, but in their functional connectivity. After the olfactory training, the sensitivity to detect odors significantly increased in the anosmic group, which was also manifested in modifications of functional connections in all three investigated networks. The results of this study indicate that an olfactory training program can reorganize functional networks, although, initially, no differences in the spatial distribution of neural activation were observed.

Establishing a reliable correspondence between lesioned brains and a template is challenging using current normalization techniques. The optimum procedure has not been conclusively established, and a critical dichotomy is whether to use input data sets which contain skull signal, or whether skull signal should be removed. Here we provide a first investigation into whether clinical fMRI benefits from skull stripping, based on data from a presurgical language localization task. Brain activation changes related to deskulled/not-deskulled input data are determined in the context of very recently developed (New Segment, Unified Segmentation) and standard normalization approaches. Analysis of structural and functional data demonstrates that skull stripping improves language localization in MNI space - particularly when used in combination with the New Segment normalization technique.