Expertise Effects in Face-Selective Areas are Robust to Clutter and Diverted Attention, but not to Competition.

McGugin RW, Van Gulick AE, Tamber-Rosenau BJ, Ross DA, Gauthier I
Cereb Cortex. 2015 25 (9): 2610-22

PMID: 24682187 · PMCID: PMC4537424 · DOI:10.1093/cercor/bhu060

Expertise effects for nonface objects in face-selective brain areas may reflect stable aspects of neuronal selectivity that determine how observers perceive objects. However, bottom-up (e.g., clutter from irrelevant objects) and top-down manipulations (e.g., attentional selection) can influence activity, affecting the link between category selectivity and individual performance. We test the prediction that individual differences expressed as neural expertise effects for cars in face-selective areas are sufficiently stable to survive clutter and manipulations of attention. Additionally, behavioral work and work using event related potentials suggest that expertise effects may not survive competition; we investigate this using functional magnetic resonance imaging. Subjects varying in expertise with cars made 1-back decisions about cars, faces, and objects in displays containing one or 2 objects, with only one category attended. Univariate analyses suggest car expertise effects are robust to clutter, dampened by reducing attention to cars, but nonetheless more robust to manipulations of attention than competition. While univariate expertise effects are severely abolished by competition between cars and faces, multivariate analyses reveal new information related to car expertise. These results demonstrate that signals in face-selective areas predict expertise effects for nonface objects in a variety of conditions, although individual differences may be expressed in different dependent measures depending on task and instructions.

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MeSH Terms (17)

Adult Attention Brain Mapping Cerebral Cortex Competitive Behavior Face Female Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Male Oxygen Pattern Recognition, Visual Photic Stimulation Professional Competence Statistics as Topic Young Adult

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