The analysis of semantic networks in multiple sclerosis identifies preferential damage of long-range connectivity.
OBJECTIVE
To analyze the characteristics of semantic networks derived from fluency tests in patients with multiple sclerosis (MS).


METHODS
We built semantic networks by applying co-occurrence statistics to the data from verbal fluency tests performed on patients with MS (n=36) and matched controls (n=200), assessing the differences in network topology.


RESULTS
As expected, the semantic networks from both patients and controls showed 'small-world' properties. Topological analysis of these semantic networks indicated that there were fewer nodes (words) and links (defined by significant co-occurrence of words) in those derived from MS patients. The average connectivity was not significantly affected, while the local connectivity (clustering coefficient) is preserved. Quantifiers of the cohesiveness of the network, which reflect long distance connectivity, such as assortativity and maximum centrality coefficients, differed significantly between MS patients and controls.


CONCLUSIONS
The analysis of semantic networks reveals quantitative differences in MS patients and identifies preferential damage of long-range connectivity. The analysis of semantic networks may be useful in clinical practice for the assessment of cognitive impairment or recovery after damage.
Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
Elena
E
Abad
Division of Nuclear Medicine and Molecular Imaging, Department of Radiology, Harvard Medical School, Boston, USA.
Jorge
J
Sepulcre
Center of Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) - Hospital Clinic of Barcelona, Barcelona, Spain.
Elena H
EH
Martinez-Lapiscina
Center of Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) - Hospital Clinic of Barcelona, Barcelona, Spain.
Irati
I
Zubizarreta
Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain.
Jordi
J
Garcia-Ojalvo
Center of Neuroimmunology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) - Hospital Clinic of Barcelona, Barcelona, Spain; Department of Neurology, University of California, San Francisco, USA. Electronic address: pvilloslada@clinic.ub.es.
Pablo
P
Villoslada
D000328:Adult; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D016000:Cluster Analysis; D003627:Data Interpretation, Statistical; D005260:Female; D006801:Humans; D007807:Language Tests; D008297:Male; D009103:Multiple Sclerosis / Q000503:physiopathology* / Q000523:psychology; D009434:Neural Pathways / Q000503:physiopathology; D009483:Neuropsychological Tests; D012660:Semantics
Brain networks; Cognition; Fluency tests; Multiple sclerosis; Network analysis; Neuropsychology; Semantic networks