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Martinez-Montes, E.

Publications and source records attributed to Martinez-Montes, E..

2 recordsLinked to original sources

Estimation of auditory steady-state responses based on the averaging of independent EEG epochs

The amplitude of the auditory steady-state responses (ASSRs) generated in the brainstem exponentially decreases over the averaging of subsequent EEG epochs. This behavior is partially due to the adaptation of the auditory response to the continuous and monotonous stimulation. We analyzed the potential clinical relevance of the ASSR adaptation. Specifically, we compare the ASSR amplitude computed in two conditions: (1) when the auditory responses -embedded in the EEG epochs that are averaged in the estimation procedure- are influenced by the previous stimulation; and (2) when they are independent of the previous stimulation. ASSR were elicited in eight anesthetized adult rats by 8-kHz tones, modulated in amplitude at 115 Hz. ASSR amplitudes were computed using three averaging methods (standard, weighted and sorted averaging). We evaluated the ASSR amplitude as a function of sub-set of epochs selected for the averaging and the improvement in the ASSR detection resulting from averaging independent epochs. Due to adaptation, the ASSR amplitude computed by averaging dependent EEG epochs relied upon the averaging method. Lower ASSR amplitudes were obtained as EEG segments containing unadapted responses were systematically excluded from the averaging. In the absence of EEG artifacts, the ASSR amplitudes did not depend on the averaging method when they were computed from independent EEG epochs. The amplitude of independent ASSRs were up to 35% higher than those obtained by processing dependent EEG segments. Extracting the ASSR amplitude from independent epochs halved the number of EEG segments needed to be averaged to achieve the maximum detection rate of the response. Acquisition paradigm based on a discrete acoustic stimulation (in which segments of AM-sounds of several seconds in length are presented after a given inter stimulus interval), in combination with appropriated averaging methods might increase the accuracy of audiological tests based on ASSRs.

neuroscience

Populational Super-Resolution Sparse M/EEG Sources and Connectivity Estimation

In this paper, we describe a novel methodology, BC-VARETA, for estimating the Inverse Solution (sources activity) and its Precision Matrix (connectivity parameters) in the frequency domain representation of Stationary Time Series. The aims of this method are three. First: Joint estimation of Source Activity and Connectivity as a frequency domain linear dynamical system identification approach. Second: Achieve super high resolution in the connectivity estimation through Sparse Hermitian Sources Graphical Model. Third: To be a populational approach, preventing the Inverse Solution and Connectivity statistical analysis across subjects as a postprocessing, by modeling population features of Source Activity and Connectivity. Our claims are supported by a wide simulation framework using realistic head models, realistic Sources Setup, and Inverse Crime effects evaluation. Also, a fair quantitative analysis is performed, based on a diversification of quality measures on which state of the art Inverse Solvers were tested.

neuroscience