Latency of evoked potentials in the tasks involving classification of images after wavelet filtration


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Abstract

We studied the characteristics of evoked potentials recorded during the recognition test based on four types of series of images subjected to the wavelet filtration: images of living objects containing either low frequency or high frequency portion of the spatial frequency spectrum, and imaging of non-living objects in the same two spatial frequency bands. Each subject had to classify the image either by its semantic feature (living–non-living), or by its physical feature (low frequency–high frequency). The purpose of this study was to compare the time characteristics of evoked potentials in these two types of tasks, which provides information on the time characteristics of categorization mechanisms of visual images. Analysis of the latent periods and amplitudes of the components of evoked potentials allowed us to detect the occipital areas of the leads where the early components (up to 170 ms) are associated with spatial and frequency characteristics of the image, the frontal and temporal areas where the components of 170–200 ms correspond to the process of categorization, and the later frontal, central, and parietal areas (300–500 ms) correspond to the process of error detection and the organization of motor response.

About the authors

G. A. Moiseenko

Pavlov Institute of Physiology

Author for correspondence.
Email: galina_pbox@mail.ru
Russian Federation, St. Petersburg

E. A. Vershinina

Pavlov Institute of Physiology

Email: galina_pbox@mail.ru
Russian Federation, St. Petersburg

S. V. Pronin

Pavlov Institute of Physiology; National Research University of Information Technologies, Mechanics, and Optics (ITMO University)

Email: galina_pbox@mail.ru
Russian Federation, St. Petersburg; St. Petersburg

V. N. Chihman

Pavlov Institute of Physiology

Email: galina_pbox@mail.ru
Russian Federation, St. Petersburg

E. S. Mikhailova

Institute of Higher Nervous Activity and Neurophysiology

Email: galina_pbox@mail.ru
Russian Federation, Moscow

Yu. E. Shelepin

Pavlov Institute of Physiology; St. Petersburg State University; National Research University of Information Technologies, Mechanics, and Optics (ITMO University)

Email: galina_pbox@mail.ru
Russian Federation, St. Petersburg; St. Petersburg; St. Petersburg


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