Facial affect manifested by multiple oscillations Bahar Güntekin, Erol Başar ⁎ Brain Dynamics, Cognition and Complex Systems Research Unit, Istanbul Kültür University, Faculty of Science and Letters, Istanbul Turkey abstract article info Available online 31 July 2008 Keywords: Face recognition Face expressions Emotion Event-related oscillations Delta Theta The present study describes electrophysiological differentiation of “Facial Expressions” by using the method of event-related oscillations (EROs). These measures were used to assess electrical manifestations of emotional expressions of 20 healthy subjects exposed to neutral, angry, and happy” faces. The present study extended previous analysis to frequency windows of delta (0.5–3.5 Hz) and theta (5–8.5 Hz) oscillations. No significant differences among responses to various face expression stimuli were observed, however, topological differences in response to all facial expressions were found. Delta oscillatory responses in the parietal–temporal–occipital locations were larger than the frontal and central locations, whereas theta oscillatory responses in the right temporal–occipital electrodes were larger than the right central electrodes. Assessment of topologically distributed multiple oscillations opens a new avenue for understanding of the electrophysiology of recognition of “faces” and “facial expressions”. © 2008 Elsevier B.V. All rights reserved. 1. Introduction According to Mountcastle (1992) the paradigm change introduced by using brain oscillations became one of the most important conceptual and analytic tools for the understanding of cognitive processes. A major task for neuroscience is to devise ways to study and to analyze the activity of distributed systems in waking brains. Luria (1966) suggested that mental functions too are a product of complex systems, a component part, which may be distributed through the structures of the brain, which he called “dynamic localization.”. The task of neuroscience is therefore not to localize “centers,” but rather, to identify the components of the various complex systems that interact to generate the mental functions. A recent study tested the possible interplay between the working and long-term memory systems that indicated the relevance of this dynamic localization (Sauseng et al., 2002). Lashley (1929) proposed that memories are in fact scattered across the entire brain rather than being concentrated in specific regions. Thus, the analytical and conceptual framework of the present study is premised on the methodological advices of Mountcastle and the conceptual statements of Luria and Lashley. In the Sherringtonian view, “the grandmother neuron” is defined as a neuron, which responds to nothing else but the face of one's grandmother. According to Barlow's (1995) concept we would have a specific neuron in the brain firing while seeing the face of a particular grandmother. Following the relevant work of Eckhorn et al. (1988) and Gray and Singer (1989) on gamma oscillations Stryker (1989) raised the question “Is grandmother an oscillation?” by commenting that neurons in the visual cortex activated by the same object, tend to discharge rhythmically and in unison. In the analysis of the facial percepts the experimenter is confronted with the process of face processing, which comprises (i) perceptual and memory processes required for the recognition of complex stimulation as a face, (ii) the identification of the particular face in view, (iii) the analysis of facial expression (McCarthy, 2000) and (iv) the concept of dynamics in integrative brain function. In addition to the processes pointed out face recognition requires integration of attention, perception, learning and memory. Recent publications favor the idea that attention, perception, learning and memory are inseparable as described by Hayek (1952) (see also Baddeley, 1996; Başar, 2004; Damasio, 1994; Desimone, 1996; Fuster, 1997) Therefore, face recognition can be considered as a prototype of processing complex signals by the brain. In a series of publications on “face recognition” we have reported differentiations of “known” and “unknown” faces by using several oscillatory components (Başar et al., 2006, 2007). Furthermore, EROs of facial expressions yielded relevant differ- entiation between responses to angry and happy face expressions in the alpha and beta frequency ranges (Güntekin and Başar, 2007). In the present report two new steps are described: (1) extension of the analysis of facial expressions to theta and delta frequency windows, and (2) integration of the discussion of oscillatory International Journal of Psychophysiology 71 (2009) 31–36 ⁎ Corresponding author. Tel.: +90 212 498 43 92; fax: +90 212 498 45 46. E-mail address: e.basar@iku.edu.tr (E. Başar). 0167-8760/$ – see front matter © 2008 Elsevier B.V. All rights reserved. doi:10.1016/j.ijpsycho.2008.07.019 Contents lists available at ScienceDirect International Journal of Psychophysiology journal homepage: www.elsevier.com/locate/ijpsycho