Brain Signals of Face Processing as Revealed by Event-Related Potentials

Hindawi Publishing Corporation Behavioural Neurology Volume 2015, Article ID 514361, 16 pages http://dx.doi.org/10.1155/2015/514361 Review Article Brain Signals of Face Processing as Revealed by Event-Related Potentials Ela I. Olivares,1 Jaime Iglesias,1 Cristina Saavedra,2 Nelson J. Trujillo-Barreto,3 and Mitchell Valdés-Sosa4 1 Departamento de Psicologı́a Biológica y de la Salud, Facultad de Psicologı́a, Universidad Autónoma de Madrid, 28049 Madrid, Spain División de Psicologı́a, Colegio Universitario Cardenal Cisneros, 28006 Madrid, Spain 3 Institute of Brain, Behaviour and Mental Health, Centre for Clinical and Cognitive Neuroscience, University of Manchester, Manchester M13 9PL, UK 4 Centro de Neurociencias de Cuba, 11600 Havana, Cuba 2 Correspondence should be addressed to Ela I. Olivares; Received 11 March 2015; Revised 10 May 2015; Accepted 11 May 2015 Academic Editor: João Quevedo Copyright © 2015 Ela I. Olivares et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We analyze the functional significance of different event-related potentials (ERPs) as electrophysiological indices of face perception and face recognition, according to cognitive and neurofunctional models of face processing. Initially, the processing of faces seems to be supported by early extrastriate occipital cortices and revealed by modulations of the occipital P1. This early response is thought to reflect the detection of certain primary structural aspects indicating the presence grosso modo of a face within the visual field. The posterior-temporal N170 is more sensitive to the detection of faces as complex-structured stimuli and, therefore, to the presence of its distinctive organizational characteristics prior to within-category identification. In turn, the relatively late and probably more rostrally generated N250r and N400-like responses might respectively indicate processes of access and retrieval of face-related information, which is stored in long-term memory (LTM). New methods of analysis of electrophysiological and neuroanatomical data, namely, dynamic causal modeling, single-trial and time-frequency analyses, are highly recommended to advance in the knowledge of those brain mechanisms concerning face processing. 1. Objective The present work is intended to offer a comprehensive review of the literature regarding those evoked brain responses related to face perception and face recognition. Moreover, we stress the pertinence of using new approaches to better understand the functional meaning of such responses and the underlying neural mechanisms. Firstly, we analyze the theoretical framework (inspired by cognitive psychology, neuropsychology, and, more recently, neuroimaging studies) that has been most frequently used to interpret ERP studies of face processing. We then dedicate a section to each of the clusters of ERP components that have been related to different stages of face processing and examine their possible relationship with the posited nodes of the face processing network derived from neuroimaging studies. In the next section, we consider recent findings derived from new methodological approaches such as dynamic causal modeling, single trial and time-frequency analyses. Finally, the conclusions are set out. This review will be limited to studies of face structural processing which eventually leads to face recognition (i.e., recognizing a person by seeing her/his face). Other aspects of face processing (recognition of emotional expressions, gaze direction, lip reading, and so on) merit special attention and are beyond the scope of the article. 2. Theoretical Framework on Face Processing 2.1. Cognitive and Neurofunctional Models Derived from Functional Magnetic Resonance (fMRI) Studies. Conceptualizations on cognitive operations underlying face recognition have been largely influenced by the seminal model of Bruce and Young [1]. This model assumes that face recognition is 2 achieved, after an initial stage of visual analysis, by sequential access to visual-structural and verbal-semantic codes in longterm memory (LTM). The structural codes concerning the physical appearance of each known individual face, with information about the shape of facial features (lips, eyes, etc.) as well as their spatial configuration, are contained in Face Recognition Units (“FRUs”). These memory units are assumed to be specific to the face domain. The verbal-semantic codes comprise personal biographical information (occupation, context where an individual is usually seen, etc.) contained in Person Identity Nodes (PINs) that are in turn connected to verbal codes for the corresponding name. Subsequent interactive activation implementations of Bruce and Young’s model have provided working models to demonstrate, through simulation, certain empirical phenomena like semantic priming, repetition priming, cross-modal cueing, and distinctiveness in face recognition [2, 3]. A basic assumption of Bruce and Young’s model is that FRUs, PINs, and name codes are activated in a strictly sequential mode. However, the complete model includes several parallel pathways originating after the initial visual analysis, each dedicated to the processing of other types of facial information (not considered further in this paper). Reports on brain damaged subjects document dissociations and in some cases double dissociations of symptoms that are consistent with the distinctions among cognitive operations posited in the original Bruce and Young’s model. More recent psychological and neuropsychological evidence has prompted modifications [4] or rebuttals [5] of the model, including a substantial revision [6], but the original version has guided ERP research on face recognition over recent decades. It is important to note that all models assume that many different types of memory codes (pictorial, face structural, emotional, social, semantic, episodic, verbal, etc.) are associated with each familiar face, a fact to be remembered when considering the experiments reviewed below. The notable increase of fMRI studies concerning both face perception and face recognition in recent years has induced the formulation of neurofunctional models which are intended to explain how the distinct functional aspects involved in face processing are supported by brain architecture with components or nodes that are stimulus- and task-dependent, specialized in the processing of different inputs relative to faces [6, 9, 10]. Some neural models try to explain how neural connectivity among certain brain regions (not necessarily close to each other) is required for efficient processing [11, 12]. Haxby et al. [10] proposed that facial information processing is mediated by a hierarchically organized and distributed neural system, composed of both a “core” and an “extended sys (...truncated)