Quantifying muscle alterations in a Parkinson's disease animal model using electromyographic biomarkers.

Parkinson's disease (PD) is a neurodegenerative disease currently diagnosed based on characteristic motor dysfunctions. The most common Parkinson's disease animal model induces massive nigrostriatal degeneration by intracerebral infusion of 6-hydroxydopamine (6-OHDA). Motor deficits in rat models of Parkinson's disease were previously addressed in other works. However, an accurate quantification of muscle function in freely moving PD-lesioned rats over time has not been described until now. In this work, we address the muscular activity characterization of a 6-OHDA-lesion model of PD along 6 weeks post-lesion based on spectral and morphological analysis of the signals. Using chronic implanted EMG electrodes in a hindlimb muscle of freely moving rats, we have evaluated the effect of the PD neurotoxic model in the muscular activity during locomotion. EMG signals obtained from animals with different time post-injury were analyzed. Power spectral densities were characterized by the mean and median frequency, and the EMG burst stationarity was previously verified for all animals. Our results show that as the time post-lesion increases both frequency parameters decrease. Probability distribution function analysis was also performed. The results suggest that contractile dynamics of the biceps femoris muscle change with time post-lesion. We have also demonstrated here the usefulness of frequency parameters as biomarkers for monitoring the muscular function changes that could be used for early detection of motor dysfunction.

Identification of Functionally Interconnected Neurons Using Factor Analysis.

The advances in electrophysiological methods have allowed registering the joint activity of single neurons. Thus, studies on functional dynamics of complex-valued neural networks and its information processing mechanism have been conducted. Particularly, the methods for identifying neuronal interconnections are in increasing demand in the area of neurosciences. Here, we proposed a factor analysis to identify functional interconnections among neurons via spike trains. This method was evaluated using simulations of neural discharges from different interconnections schemes. The results have revealed that the proposed method not only allows detecting neural interconnections but will also allow detecting the presence of presynaptic neurons without the need of the recording of them.

Discriminability measures and time-frequency features: an application to vibrissal tactile discrimination.

BACKGROUND: Often, the first problem that the neuroscientist must face is to determine if a specific stimulus set applied to biological system produces specific, precise and well differentiated responses. NEW METHOD: In the present study we have proposed four discriminability measures to evaluate the feasibility of differentiating experimental conditions: information measures based on information theory, percentage overlap based on Linacre method, Bhattacharyya distance and univariate standard distance. All discriminability measures were evaluated on experimental protocols related to vibrissal tactile discrimination. RESULTS: Time-frequency features were extracted from afferent discharges and then, pairwise comparisons were realized by using the proposed discriminability measures. Our results reveal the existence of time-frequency patterns which allows differentiating of sweep conditions from multifiber recordings. COMPARISON WITH EXISTING METHODS: Currently, statistical methods used to justify significant differences in experimental conditions have rigorous criteria that must be met for correct validation of results. Discriminability measures proposed here are robust and can be adjusted to different experimental conditions (time series, repeated measures, specific variables and other). CONCLUSIONS: Discriminability measures allowed determining the time intervals where two sweep situations have the highest probability to be differentiated from each other. High discriminability percentages were observed into protraction phase, although to a lesser degree, it was also observed in retraction phase. It was demonstrated that sensibility of discriminability measures are different. This revealing a greater ability to highlight percentage changes of pairwise comparisons. Finally, the methods here proposed can be adapted to other features of biological responses.