Development of the Principle of Analyzing the Dynamics of the Psychophysical Indicator d′ Using the “Moving Average” Method

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Abstract

The article describes the possibilities of using the “moving average” method in the analysis of psychophysical indicators using the example of indicator d′ used in the “Yes” method/No”, based on the Theory of signal detection. The general principles of applying the “sliding window” method to the psychophysical indicator d′ are considered, as well as the features of its use. Methods are described to test the basic assumptions inherent in the model of the Theory of signal detection, but in relation to dynamic data. Some possible tasks are analyzed, the solution of which becomes available when using this method of data analysis.

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About the authors

V. V. Apanovich

State Academic University for Humanities; Institute of Psychology, Russian Academy of Sciences; National Research University Higher School of Economics

Author for correspondence.
Email: apanovitschvv@yandex.ru

Ph.D. (Psychology), Associate Professor of the Faculty, Researcher at the Lab. V.B. Shvyrkov Psychophysiology, Junior Researcher at the International Lab. Social Neuroscience

Russian Federation, 119049, Moscow, Maronovsky lane, 26; 129366, Moscow, Yaroslavskaya str., 13, bldg. 1; 101000, Moscow, Myasnitskaya str., 10

K. S. Yudakov

State Academic University for Humanities; Institute of Psychology, Russian Academy of Sciences

Email: kost05062000@mail.ru

Graduate Student of the Faculty of Psychology, Junior Researcher at the Lab. Psychophysiology Named after V.B. Shvyrkov

Russian Federation, 119049, Moscow, Maronovsky lane, 26; 129366, Moscow, Yaroslavskaya str., 13, bldg. 1

P. I. Egorova

State Academic University for Humanities

Email: polina.egorova2102@gmail.com

Graduate student of the Faculty of Psychology

Russian Federation, 119049, Moscow, Maronovsky lane, 26

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Supplementary files

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2. Fig. 1. Graphical representation of the Signal Detection Theory model: N — blank sample; S — signal sample; P(y/S) — probability of “yes” response to signal sample; P(n/N) — probability of “no” response to blank sample; P(n/S) — probability of “no” response to signal sample; P(y/N) — probability of “yes” response to blank sample

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3. Fig. 2. Dependence of mathematical expectations of the required number of samples for the possibility of calculating the main psychophysical indicators (d′, β) on the expected indicator d′ in the experiment, provided the balanced decision criterion (β)

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4. Fig. 3. Illustration of the sliding window principle with a window size of 50 samples and a step of 1 sample

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5. Fig. 4. Example of primary data (a) and smoothed (b) using the Gaussian method

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6. Fig. 5. Example of study participants who exceeded the point of a “non-random” decision (a) or improved the result relative to the initial range of d′ indicators (b). Note: The horizontal line indicates the “threshold” value, exceeding which indicates a reliable difference from zero (a) or the initial values of d′ (b).

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