Individuals with high levels of anxiety show preferential processing of threatening information, and this cognitive bias is thought to be an integral component of anxiety disorders. In threat classification tasks, this bias manifests as high-anxiety participants being more likely to classify stimuli as threatening than their low-anxiety counterparts. However, it is unclear which cognitive mechanisms drive this bias in threat classification. To better understand this phenomenon, threat classification data were analyzed with 2 decision models: a signal detection model and a drift-diffusion model. Signal detection models can dissociate measures of discriminability and bias, and diffusion models can further dissociate bias due to response preparation from bias due to stimulus evaluation. Individuals in the study completed a trait anxiety measure and classified threatening and neutral words based on whether they deemed them threatening. Signal detection analysis showed that high-anxiety participants had a bias driven by a weaker threat criterion than low-anxiety participants, but no differences in discriminability. Drift-diffusion analysis further decomposed the threat bias to show that it is driven by both an expectation bias that the threat response was more likely to be correct, and a stimulus bias driven by a weaker criterion for evaluating the stimuli under consideration. These model-based analyses provide valuable insight and show that multiple cognitive mechanisms underlie differential threat processing in anxiety. Implications for theories of anxiety are discussed.

An area within the ventral occipitotemporal cortex (vOTC), the "visual word form area" (VWFA), typically exhibits a strongly left-lateralized response to orthographic stimuli in skilled readers. While individual variation in VWFA lateralization has been observed, the behavioral significance of laterality differences remains unclear. Here, we test the hypothesis that differences in VWFA lateralization reflect differing preferences for holistic orthographic analysis. To examine this hypothesis, we implemented a new multivariate method that uses machine learning to assess functional lateralization, along with a traditional univariate lateralization method. We related these neural metrics to behavioral indices of holistic orthographic analysis (inversion sensitivity). The multivariate measure successfully detected the lateralization of orthographic processing in the VWFA, and as hypothesized, predicted behavioral differences in holistic orthographic analysis. An exploratory whole brain analysis identified further regions with a relationship between inversion sensitivity and lateralization: one near the junction of the inferior frontal and precentral sulci, and another along the superior temporal gyrus. We conclude that proficient native readers of English exhibit differences in cortical lateralization of the VWFA that have significant implications for reading behavior.

No abstract

No abstract

No abstract