Effects of neonatal deafness on resting-state functional network connectivity.

Normal brain development depends on early sensory experience. Behavioral consequences of brain maturation in the absence of sensory input early in life are well documented. For example, experiments with mature, neonatally deaf human or animal subjects have revealed improved peripheral visual motion detection and spatial localization abilities. Such supranormal behavioral abilities in the nondeprived sensory modality are evidence of compensatory plasticity occurring in deprived brain regions at some point or throughout development. Sensory deprived brain regions may simply become unused neural real-estate resulting in a loss of function. Compensatory plasticity and loss of function are likely reflected in the differences in correlations between brain networks in deaf compared with hearing subjects. To address this, we used resting-state functional magnetic resonance imaging (fMRI) in lightly anesthetized hearing and neonatally deafened cats. Group independent component analysis (ICA) was used to identify 20 spatially distinct brain networks across all animals including auditory, visual, somatosensory, cingulate, insular, cerebellar, and subcortical networks. The resulting group ICA components were back-reconstructed to individual animal brains. The maximum correlations between the time-courses associated with each spatial component were computed using functional network connectivity (FNC). While no significant differences in the delay to peak correlations were identified between hearing and deaf cats, we observed 10 (of 190) significant differences in the amplitudes of between-network correlations. Six of the significant differences involved auditory-related networks and four involved visual, cingulate, or somatosensory networks. The results are discussed in context of known behavioral, electrophysiological, and anatomical differences following neonatal deafness. Furthermore, these results identify novel targets for future investigations at the neuronal level