Physiological Aging Impacts the Hemispheric Balances of Resting State Primary Somatosensory Activities
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To hone knowledge of sensorimotor cerebral organization changes with physiological aging, we focused on the primary somatosensory cortical area (S1). S1 neuronal pools (FS_S1) were identified by the functional source separation (FSS) algorithm applied to magnetoencephalographic recordings during median nerve stimulation. Age-dependence of FS_S1 was then studied at rest separately in the left and right hemispheres of 26 healthy, right-handed subjects between the ages of 24 and 95 years. The resting state FS_S1 spectral features changed with increasing age: (1) alpha activity slowed down; (2) total power increased only in the right hemisphere; (3) right>left interhemispheric asymmetry increased in the whole spectrum; (4) spectral entropy increased with age selectively in the left hemisphere. The present FSS-enriched electrophysiological procedure provided measures of resting state hand representation area sensitive to changes with age. Alterations were stronger in the right hemisphere. Relationships between resting state S1 activity and its responsiveness to external stimuli, revealed that the interhemispheric unbalances which emerged with age were conceivably due to an increased excitability within the right thalamocortical circuit impacting left versus right unbalances of spontaneous firing rates and of local inhibitory-excitatory networks.
KeywordsMagnetoencephalography (MEG) Interhemispheric asymmetries Median nerve stimulation Functional source separation (FSS)
The Authors thank Dr. Patrizio Pasqualetti for his support to statistical analysis. This study was supported by the following grants: (1) FISM—Fondazione Italiana Sclerosi Multipla—FaMuSNe Cod.2010/R/38; (2) FISM FaReMuS DiC diT Cod.2011/R/32; (3) Italian Ministry of Health Cod. GR-2008-1138642 ‘Promoting recovery from Stroke: Individually enriched therapeutic intervention in Acute phase’ [ProSIA]; (4) Royal Society International Joint Project—2010/R1: ‘The Key Movement Controllers: an EEG/fMRI study of the hand network dynamics [KeyMoCo]’.
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