Hostname: page-component-586b7cd67f-tf8b9 Total loading time: 0 Render date: 2024-11-25T19:21:22.689Z Has data issue: false hasContentIssue false

Multidimensional Scaling of Schematically Represented Faces Based on Dissimilarity Estimates and Evoked Potentials of Differences Amplitudes

Published online by Cambridge University Press:  10 April 2014

Chingiz A. Izmailov*
Affiliation:
Moscow State University
Evgeni N. Sokolov
Affiliation:
Moscow State University
Svetlana G. Korshunova
Affiliation:
Moscow State University
*
Correspondence should be addressed to Ch. A. Izmailov, Moscow State University. E-mail: [email protected]

Abstract

This study researches the input of the cerebral occipital and temporal cortex in the analysis of facial configuration and expressive characteristics. Analysis is based on the construction of a spherical model for the differentiation of schematically presented faces with quantitatively altering curvature of the mouth and brows. The model is designed using the method of multidimensional scaling of the dissimilarity judgments between stimuli (faces) and the amplitude of evoked potentials of differences (EPD) between abrupt stimulus changes recorded from the occipital and posterior temporal cortex. Analysis of the structure of the spherical model of facial differentiation depending on the electrode site and the latency of the EPD component within the duration of 120-240 ms has demonstrated that the activity of the occipital and posterior temporal cortex of the right hemisphere is associated with the emotional characteristics of the presented face, whereas facial configuration is reflected in the activation of both posterior temporal cortex and the occipital cortex of the left hemisphere. At all electrode sites maximum information of the emotional expression and configuration is represented in inter-peak amplitude P120-N180. With increasing latency there is increased distortion of the structure of differences in the spherical model of schematically presented faces, which is interpreted as an attenuation of electrical activity associated with the analysis of the emotional expression, which occurs more rapidly than configuration analysis.

Este estudio investiga la entrada del córtex cerebral occipital y temporal en el análisis de la confirguración facial y de las características expresivas. El análisis se basa en la construcción de un modelo esférico de diferenciación de caras presentadas esquemáticamente cuando la curvatura de boca y cejas varía quantitativamente. El modelo se ha diseñado empleando el método de escalonamiento multidimensional de los juicios de disimilitud entre los estímulos (caras) y la amplitud de los potenciales evocados de las diferencias (PED) entre los cambios abruptos de los estímulos registrados desde el córtex occipital y temporal posterior. Dependiendo del lugar de inserción del electrodo y la latencia del componente PED, el análisis de la estructura del modelo esférico de diferenciación facial en de la duración de 120-240 ms ha demostrado que la actividad del córtex occipital y temporal posterior del hemisferio derecho se asocia con las características emocionales de la cara presentada, y que la confguración facial se refleja en la activación de los córtex temporal posterior y occipital del hemisferio izquierdo. En todos los lugares de inserción de los electrodos, la máxima información de la expresión y configuración emocional se representa en una amplitud inter-pico de P120-N180. Al incrementar la latencia, aumenta la distorsión de la esturtura de las diferencias en el modelo esférico de caras presentadas esquemáticamente, lo cual se interpreta como la atenuación de la actividad eléctrica asociada al análisis de la expresión emocional, el cual ocurre más rápidamente que el análisis configuracional.

Type
Articles
Copyright
Copyright © Cambridge University Press 2005

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abelson, R.P., & Sermat, V. (1962). Multidimensional scaling of facial expressions. Journal of Experimental Psychology, 63, 546554.CrossRefGoogle ScholarPubMed
Adolphs, R., Tranel, D., Damasio, H., & Damasio, A. (1994). Impaired recognition of emotion in facial expressions following bilateral damage to the human amigdala. Nature, 372, 669672.CrossRefGoogle Scholar
Bimler, D., & Kirkland, J. (2001). Categorical perception of facial expressions of emotion: Evidence from multidimensional scaling. Cognition and Emotion, 15, 633658.CrossRefGoogle Scholar
Bongard, M.M. (1955). Kolorimetriya na jivotnyh (Colorimetry on the animals). Proceedings from Soviet Union Academy of Science, 103, 239242.Google Scholar
Boucsein, W., Schaefer, F., Sokolov, E.N., Schroder, C., & Fureby, J.J. (2001). The color-vision approach to emotional space: Cortical evoked potential data. Integrative Physiological and Behavioral Sciences, 36, 137153.CrossRefGoogle ScholarPubMed
Damasio, A.R, Damasio, H., & Van Hoesen, G.W. (1982). Prosopagnosia: Anatomic basis and behavioral mechanisms. Neurology 32, 331341CrossRefGoogle ScholarPubMed
Davidson, J.R. (1984). Hemispheric asymmetry and emotion. In Sherer, K.R. & Ekman, P. (Eds.), Approaches to emotion (pp. 3957). London: Erlbaum.Google Scholar
Eirner, M., & McCarthy, R.A. (1999). Prosopagnosia and structural encoding of faces: Evidence from event-related potentials. NeuroReport, 10, 255259.Google Scholar
Ekman, P., & Friesan, W.V. (1978). Facial action coding system: A technique for the measurement of facial movement. Palo Alto, CA: Consulting Psychology Press.Google Scholar
Estevez, O., & Spekreijse, H. (1982). The “silent substitution” method in visual research. Vision Research, 22, 681691.CrossRefGoogle Scholar
Fomin, S.V., Sokolov, E.N., & Vaitkyavichus, G.G. (1979). Isskustvennye organy chuvstv [Artificial sensory organs]. S. Petersburg: Nauka.Google Scholar
Herrmann, M.J., Aranda, D., Ellgring, H., Mueller, T.J., Strik, W.K., Heidrich, A., & Fallgatter, A.J. (2002). Face-specific event-related potential in humans is independent from facial expression. International Journal of Psychophysiology, 45, 241244.CrossRefGoogle ScholarPubMed
Hubel, D.N., & Wiesel, T.N. (1962). Receptive fields, binocular integration and functional architecture in the cat's visual cortex. Journal of Physiology, 160, 106154.CrossRefGoogle Scholar
Izmailov, Ch.A., Isaichev, S.A., Korshunova, C.G., & Sokolov, E.N. (1998). Spetsifikatsia tsvetovogo I iarkostnogo komponentov zritelnogo VP u cheloveka [Specification of color and brightness components of human visual EP]. Zhurnal vysshei nervnoi deiatelnosti, 48, 518527.Google Scholar
Izmailov, Ch.A., Korshunova, C.G., & Sokolov, E.N. (1999). Sfericheskaia model razlichenia emotsionalnykh vyrazhenii skhematicheskogo litsa [A spherical schematic face emotional expression differentiation model]. Zhurnal vysshei nervnoi deiatelnosti, 49, 186199.Google Scholar
Izmailov, Ch.A., Korshunova, S.G., & Sokolov, E.N. (2001). Relationship between visual evoked potentials and subjective differences between emotional expressions in “face diagrams.” Neuroscience and Behavioral Physiology, 31, 5, 529538.CrossRefGoogle Scholar
Izmailov, Ch.A., Korshunova, C.G., Sokolov, E.N., & Chudina, Yu.A. (2004). Geometricheskaia model razlichenia orientatsii linii, osnovannaia na subektivnykh otsenkakh I zritelnykh vyzvannykh potentsialakh [A geometric model of line orientation based on subjective estimates and visual evoked potentials]. Zhurnal vysshei nervnoi deiatelnosti, 54, 267279.Google Scholar
Izmailov, Ch.A., & Sokolov, E.N. (2004). Subjective and objective scaling of large color differences. In Kaernbach, C., Schroger, E., & Muller, H. (Eds.), Psychophysics beyond sensation. Laws and invariants of human cognition (pp. 2742). Mahwah, NJ: Erlbaum.Google Scholar
Jeffreys, D.A. (1992). The vertex-positive scalp potential evoked by faces and by objects Experimental Brain Research, 91, 340350.CrossRefGoogle ScholarPubMed
Kostandov, E.A. (1980). Hemispheric asymmetry of cortical visual evoked potentials to neutral and emotional stimuli. In Lechner, H. (Ed.), EEG and Clinical Neurophysiology (pp. 740745). Amsterdam: Elsevier.Google Scholar
Osgood, C.E. (1966). Dimensionality of the semantic space for communication via facial expressions. Scandinavian Journal of Psychology, 7, 130.CrossRefGoogle ScholarPubMed
Paramey, G.V. (1996). Konturnye izobrazhenia litsa: mogut li oni peredavat emotsionalnye sostoiania? [Contour facial imaging: Can it portray emotion?]. Psikhologicheski zhurnal, 17, 7085.Google Scholar
Paramey, G.V., Izmailov, Ch.A., & Babina, V.S. (1992). Emotsionalno-ekspressivnye kharakteristiki skhematicheskogo litsa na displee komputera [Schematic face emotional expression characteristics on computer screens]. Vesti MGU. Ser. 14. Psikhologia, 3, 3038.Google Scholar
Perrett, D.I., Rolls, E.T., & Caan, W. (1982). Visual neurons responsive to faces in the monkey temporal cortex. Experimental Brain Research, 47, 329342.CrossRefGoogle ScholarPubMed
Rolls, E.T. (1984). Neurons in the cortex of the temporal lobe and in the amygdala of the monkey with responses selective to faces. Human Neurobiology, 3, 209222.Google ScholarPubMed
Rolls, E.T. (1998). The brain and emotions. Oxford, UK: Oxford University Press.CrossRefGoogle Scholar
Rudell, A.P. (1991). The recognition potential contrasted with the P300. International Journal of Neuroscience, 60, 85111.CrossRefGoogle ScholarPubMed
Schlosberg, H.S. (1941). A scale for the judgment of facial expressions. Journal of Experimental Psychology, 29, 497510.CrossRefGoogle Scholar
Shepard, R.N. (1964). Attention and the metric structure of the stimulus space. Journal of Mathematical Psychology, 1, 5487.CrossRefGoogle Scholar
Shepard, R. (1981). Mnogomernoe shkalirovanie i nemetricheskie predstavlenia. Normativnye i deskriptivnye modeli priniatia reshenii [Multidimensional scaling and non-metric representation. Normative and descriptive models of decision making]. Materials of the Soviet-American Symposium (pp. 8497). Moscow: Nauka.Google Scholar
Shvelev, I.A., Kamenkovich, V.M., & Sharaev, G.A. (2000). Otnositelnoie znachenie linii I uglov geometricheskikh figut dlia ikh opoznania chelovekom [Relative values of lines and angles in human perception]. Zhurnal vysshei nervnoi deiatelnosti, 50, 403409.Google Scholar
Sokolov, E.N. (1992). Detector mechanisms of perceptions and emotions. In Forgays, D.G., Sosnowski, T., & Wrzsiewski, K. (Eds.), Anxiety: Recent developments in cognitive, psychophysiological, and health research (pp. 153165). Washington, DC: Hemisphere Publishing Corporation.Google Scholar
Sokolov, E.N., & Izmailov, Ch.A. (1983). The conceptual reflex arc: A model of neural processing as developed for color vision. In Geissler, H.G. (Ed.), Modern Issues of Perception (pp. 192216). Berlin: VEB Deutscher Verlag der Wissenschaften.CrossRefGoogle Scholar
Supin, A.Ya. (1981). Neirofiziologia zrenia mlekopitaiushchikh [Neurophysiology of vision in mammals]. Moscow: Nauka.Google Scholar
Zimachev, M.M., Shehter, E.D., Sokolov, E.N., & Izmailov, Ch.A. (1986). Hromaticheskaya sostavlyauschaya elektroretinogrammy lyagushki [Chromatic component in frog's ERG]. Zhurnal vysshei nervnoi deiatelnosti, 36, 11001107.Google Scholar