Characterization of Neural Signals in Preclinical Studies of Neural Plasticity Using Nonlinear Time Series Analysis

The capacity of the brain to change its basic functions and structures is called neural plasticity. Neural plasticity is one of the most challenging themes in neuroscience and its comprehension may lead to fundamental understanding on brain dynamics. Here, we have characterized the intra and inter regional neuroplastic changes in animal models (mice) of different diseases (i.e. stroke and epilepsy) and sensorimotor stimulation induced by environmental enrichment conditions through the quantitative linear and nonlinear analysis of electrophysiological signals (Local Field Potentials, LFPs). Various properties characterizing LFPs such as power spectra, scaling behavior and interdependence have been quantified. These characterizations were able to discriminate between different experimental conditions, thus providing a good set of quantities that could be useful as biomarkers in medical diagnostics. In particular, we reported some cases in which nonlinear time series analysis reveals effects that are not detected by linear methods. For the epileptic mice, the spectral analysis has shown that epileptic activity determines a power redistribution among the different neurophysiological bands. Symbolic Transfer Entropy measure indicates a greater driving influence of the focal epileptic side on activity in the contra-lateral hemisphere, while Granger causality measures fails at detecting it. Inter-hemispheric functional coupling within delta band (0.5-4 Hz) was reduced in homotopic Pre-Motor Areas of ischemic animals, as shown by a statistically significant decrease in the mutual information measures (not captured by cross-correlation index). Finally, we estimated the scaling properties of LFPs recorded from freely-moving mice reared in environmental enrichment (EE) and standard condition (SC) by using an integrated approach combining three different techniques: the Higuchi method, DFA and spectral analysis. Our results indicated the existence of a particular power spectrum scaling law 1/f? with ?<0 for low frequencies (f<4Hz) for both SC and EE rearing conditions. Notably, the difference between scaling exponents in EE and SC for individual cortical regions (M2) and (V1) was not statistically significant. Altogether, these findings shed light on the mechanism involved in neocortical plasticity suggesting both robust plasticity of transcallosal interactions and intra-hemispheric rearrangement of the local neural activities in normal and pathological brain conditions.