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  Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses: The case of behavioral variant frontotemporal dementia

Schroeter, M. L., Laird, A. R., Chwiesko, C., Deuschl, C., Schneider, E., Bzdok, D., et al. (2014). Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses: The case of behavioral variant frontotemporal dementia. Cortex, 57, 22-37. doi:10.1016/j.cortex.2014.02.022.

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Schroeter, Matthias L.1, 2, 3, 4, Author           
Laird, Angela R.5, Author
Chwiesko, Caroline1, Author
Deuschl, Christine1, Author
Schneider, Else1, Author
Bzdok, Danilo6, Author
Eickhoff, Simon B.6, 7, Author
Neumann, Jane1, 8, Author           
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              
3Leipzig Research Center for Civilization Diseases (LIFE), University of Leipzig, Germany, ou_persistent22              
4German Consortium for Frontotemporal Lobar Degeneration (FTLD), Bonn, Germany, ou_persistent22              
5Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA, ou_persistent22              
6Institute of Neuroscience and Medicine, Research Center Jülich, Germany, ou_persistent22              
7Institute for Clinical Neuroscience and Medical Psychology, Heinrich Heine University Düsseldorf, Germany, ou_persistent22              
8Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany, ou_persistent22              


Free keywords: Behavioral variant frontotemporal dementia; Cognitive neuropsychiatry; FDG-PET; Meta-analysis; MRI
 Abstract: Introduction: Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this ‘nexopathy’ elucidates the healthy social and emotional brain. Methods: Here, we combine three multimodal meta-analyses approaches – anatomical and activation likelihood estimates and behavioral domain profiles – to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. Results: The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. Conclusions: The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future.


Language(s): eng - English
 Dates: 2014-01-302013-10-092014-02-272014-03-212014-08
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.cortex.2014.02.022
PMID: 24763126
PMC: PMC4108513
Other: Epub 2014
 Degree: -



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Title: Cortex
  Other : Cortex
Source Genre: Journal
Publ. Info: Milan [etc.] : Elsevier Masson SAS
Pages: - Volume / Issue: 57 Sequence Number: - Start / End Page: 22 - 37 Identifier: ISSN: 0010-9452
CoNE: https://pure.mpg.de/cone/journals/resource/954925393344