'Faceness' and affectivity: Evidence for genetic contributions to distinct components of electrocortical response to human faces

Robert W. Shannon, Christopher J. Patrick, Noah C. Venables, Sheng He

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

The ability to recognize a variety of different human faces is undoubtedly one of the most important and impressive functions of the human perceptual system. Neuroimaging studies have revealed multiple brain regions (including the FFA, STS, OFA) and electrophysiological studies have identified differing brain event-related potential (ERP) components (e.g., N170, P200) possibly related to distinct types of face information processing. To evaluate the heritability of ERP components associated with face processing, including N170, P200, and LPP, we examined ERP responses to fearful and neutral face stimuli in monozygotic (MZ) and dizygotic (DZ) twins. Concordance levels for early brain response indices of face processing (N170, P200) were found to be stronger for MZ than DZ twins, providing evidence of a heritable basis to each. These findings support the idea that certain key neural mechanisms for face processing are genetically coded. Implications for understanding individual differences in recognition of facial identity and the emotional content of faces are discussed.

Original languageEnglish (US)
Pages (from-to)609-615
Number of pages7
JournalNeuroImage
Volume83
DOIs
StatePublished - Dec 2013

Bibliographical note

Funding Information:
This work was supported by NIMH grants MH072850 and MH089727 . We are grateful to Megan Lucy for coordinating the project; Uma Vaidyanathan, Lindsay Nelson, Marianna Gasperi, Melissa Johnson, Elisabeth Kallenberger, Saaraa Ameri, Beth Dicks, and Michael Storlie for assisting with data collection; Melanie Fuhrman, Siri Scott, and Genevieve Ryczek for assisting with recruitment; Jennifer Cermak for coordinating diagnostic and questionnaire data coding and entry; Justin Jobelius for assisting with physiological data processing; Paul Arbisi for participating in diagnostic consensus meetings; and Mark Kramer, Robert Krueger, William Iacono, and Matt McGue for their assistance in accessing and characterizing the participant sample.

Keywords

  • Faces
  • N170
  • P200
  • Twins

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