Paola Valsasina1, Maria Assunta Rocca1, Filippo Savoldi1, Marta Radaelli2, Paolo Preziosa1, Giancarlo Comi2, Andrea Falini3, and Massimo Filippi1
1Neuroimaging Research Unit, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 2Department of Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy, 3Department of Neuroradiology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
Synopsis
This study gives a comprehensive description of sensory and motor
resting state functional connectivity abnormalities in patients with
neuromyelitis optica spectrum disorders (NMOSD) fulfilling the new 2015 diagnostic
criteria. Functional connectivity abnormalities found in these patients were
compared with isolated optic neuritis and myelitis. Our results suggest
different mechanisms of brain reorganization in NMOSD vs isolated optic neuritis and myelitis, with a more evident
cross-modal plasticity between sensory systems in NMOSD patients. This result
might help to better characterize the different pathophysiological mechanisms
occurring in these conditions.Background and purpose
The assessment of functional connectivity (FC) at resting state (RS) has
demonstrated the presence of functionally relevant RS networks (RSNs) in the
human brain [1]. Previous studies suggested the presence of cross-modal
plasticity between sensory modalities when one sensory system is severely hit
by pathology [2]. The assessment of large-scale network RS FC
abnormalities may help to define the selectivity of system involvement (e.g.,
visual and motor network) in patients with neuromyelitis optica spectrum disorder (NMOSD) fulfilling the new 2015 criteria.
Against this
background, aim of this study was to compare
RS FC within and among motor and sensory RSN between NMOSD, isolated recurrent
optic neuritis (ON) and recurrent myelitis patients.
Methods
RS fMRI was acquired from 30 right-handed NMOSD, 11 ON, 12 myelitis
patients and 30 healthy controls (HC). Independent
component analysis (ICA) was used to identify the main sensory and motor networks [3]. Between-group comparison and correlations with motor
performance (9-hole peg test and 10m-walking test) were assessed using SPM12. Inter-network
connectivity modifications were estimated with a functional network
connectivity (FNC) analysis [4].
Results
ICA analysis detected 7 spatial maps of potentially
relevant sensory and motor RS networks. There were two networks related to
sensorimotor areas, two networks associated with primary visual regions, two
networks associated with secondary visual regions, and one network associated with
auditory functions (Figure 1). Compared
with HC, NMOSD patients showed decreased RS FC of the secondary visual
network. They also showed increased RS FC of the visual and auditory networks vs HC, ON and myelitis patients. No sensorimotor
RS FC abnormalities were detected. ON patients experienced decreased RS FC of the
visual and auditory networks and increased RS FC of primary visual regions. Myelitis
patients had reduced RS FC of the sensorimotor, visual and auditory networks vs HC, NMOSD and ON. They also showed increased
RS FC of the precuneus (sensorimotor network) and cerebellum (visual network) (Figure
2). In all groups, decreased RS FC correlated with poor motor performance. In
myelitis patients, increased precuneus RS FC correlated with a better motor
performance. FNC between motor and visual RSNs was increased in NMOSD, while
FNC was markedly decreased between primary and secondary visual RSNs in ON.
Conclusions
In recurrent ON and myelitis, abnormal RS FC was observed in networks primarily affected by the
pathological process. NMOSD showed decreased visual system RS FC and increased RS
FC in other sensory networks, suggesting cross-modal plasticity among different
sensory modalities.
Acknowledgements
No acknowledgement found.References
[1] Biswal B. et al., PNAS 2010; 107: 4734-39.
[2] Rocca
M.A., et al. Plos One 2011; 10: 6(2).e17081.
[3] Calhoun
V. et al., Hum Brain Mapp 2001; 14: 140-151.
[4] Jafri M. et al., Neuroimage 2008; 39: 1666-81.