Abstract
Parkinson's disease (PD), the second most frequent neurodegenerative disease, affects significantly life quality by a combination of motor and cognitive disturbances. Although it is traditionally associated with basal ganglia dysfunction, cortical alterations are also involved in disease symptoms. Our objective is to evaluate the alterations in brain dynamics in de novo and recently treated PD subjects using a nonlinear method known as Active Information Storage. In the current research, Active Information Storage (AIS) was used to study the complex dynamics in motor cortex spontaneous activity captured using resting state functional Magnetic Resonance Imaging (rs-fMRI) at early-stage in non-medicated and recently medicated PD subjects. Supplementary to AIS, the fractional Amplitude of Low Frequency Fluctuation (fALFF), which is a better-established technique of analysis of rs-fMRI signals, was also evaluated. Compared to healthy subjects, the AIS values were significantly reduced in PD patients over the analyzed motor cortex regions; differences were also found at less extent using the fALFF measure. Correlations between AIS and fALFF values showed that the measures seem to capture similar neuronal phenomena in rs-fMRI data. The highest sensitivity when detecting group differences revealed by AIS, and not captured by traditional linear approaches, suggests that this measure is a promising tool for the analysis of rs-fMRI neural data in PD.
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