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Biomedical subjects

O A Rosso

Publications and source records attributed to O A Rosso.

7 recordsLinked to original sources

A transient dominance of theta ERP component characterizes passive auditory processing: evidence from a developmental study.

This study analyzed relationships among co-existent EEG frequency responses during passive auditory stimulus processing. By applying quantifiers based on wavelet entropy, it is demonstrated that a short-lasting ordering of the complex post-stimulus EEG signal occurs as a result of a transient synchronization in the theta frequency channel. Further, by using a developmental model it is shown that, independently of the frequency content of the background EEG and ERPs, a highly-ordered microstate in the ERP is always determined by theta frequency. Thus, transient dominance of synchronized theta oscillations may reflect an important functional mechanism subserving stimulus information processing.

Acoustic Stimulation↗

Wavelet entropy: a new tool for analysis of short duration brain electrical signals.

Since traditional electrical brain signal analysis is mostly qualitative, the development of new quantitative methods is crucial for restricting the subjectivity in the study of brain signals. These methods are particularly fruitful when they are strongly correlated with intuitive physical concepts that allow a better understanding of brain dynamics. Here, new method based on orthogonal discrete wavelet transform (ODWT) is applied. It takes as a basic element the ODWT of the EEG signal, and defines the relative wavelet energy, the wavelet entropy (WE) and the relative wavelet entropy (RWE). The relative wavelet energy provides information about the relative energy associated with different frequency bands present in the EEG and their corresponding degree of importance. The WE carries information about the degree of order/disorder associated with a multi-frequency signal response, and the RWE measures the degree of similarity between different segments of the signal. In addition, the time evolution of the WE is calculated to give information about the dynamics in the EEG records. Within this framework, the major objective of the present work was to characterize in a quantitative way functional dynamics of order/disorder microstates in short duration EEG signals. For that aim, spontaneous EEG signals under different physiological conditions were analyzed. Further, specific quantifiers were derived to characterize how stimulus affects electrical events in terms of frequency synchronization (tuning) in the event related potentials.

Adult↗

Wavelet entropy in event-related potentials: a new method shows ordering of EEG oscillations.

In this work we show the application of a measure of entropy defined from the wavelet transform, namely the wavelet entropy (WS), to the study of event-related potentials (ERPs). WS was computed for ERPs recorded from nine healthy subjects with three different types of stimuli, among them target stimuli in a cognitive task. A significant decrease of entropy was correlated with the responses to target stimuli (P300), thus showing that these responses correspond to a more "ordered" state than the spontaneous EEG. Furthermore, we propose the WS as a quantitative measure for such transitions between EEG ("disordered state") and ERP ("ordered state").

Adult↗

Searching for hidden information with Gabor Transform in generalized tonic-clonic seizures.

The analysis of generalized tonic clonic seizures is usually difficult with scalp EEG due to muscle artifact. We applied Gabor Transform to evaluate 20 seizures from 8 consecutive patients admitted for video-EEG monitoring. We studied the relative intensity ratios of alpha, theta and delta bands over time. In 14/20 events we found a significant decremental activity in the delta band at the onset of the seizure indicating that this is dominated by theta and alpha bands. We conclude that GT is a useful auxiliary tool in the analysis of ictal activity that sheds light on the underlying pathophysiological mechanisms.

Adult↗