This may be interpreted as a mechanistic description of how low decision confidence and highly surprising aversive Obeticholic Acid manufacturer feedback can lead to altered decision making. The multiple regression approach used here capitalizes on prior knowledge of temporospatial EEG features (e.g., P3b), but side-steps

methodological and interpretive pitfalls common to the selection of event-related potential components. In addition, the operational definition of cognitive events based on algorithmic modeling facilitates a transparent and replicable method for assessing the latent cognitive features thought to influence such neural signals. The advantage of this combined data-driven method (with appropriate correction for multiple comparisons) is exemplified here in the definition of the information content of neural signals associated with P3b. The psychological significance of P3b has been long known, but an appropriately sensitive and specific definition remains be elusive. In a recent review, Nieuwenhuis et al. (2005) summarized how subjective probability and motivational significance, modulated by attention, codetermine P3b amplitude. The P3b component is correlated with the algorithmic quantification of surprise (Mars et al., 2008) and has also been shown to predict the decision to switch behavioral responses (Chase et al., 2010), yet rarely have these multitudinous definitions

and disparate findings been combined to provide an inclusive description of the neurobehavioral correlates of P3b. Indeed, a single global definition of this neural event would MG-132 be inappropriate, as Fischer and Ullsperger (2013) demonstrated an inversion of the relationship between P3b amplitude and behavioral outcome depending on whether the neural signal was locked to the gambling image or to the feedback. By stepping away from cross-trial averaging and oftentimes subjective peak-picking methods common to event-related potential analyses,

Fischer and Ullsperger (2013) have been able to provide novel insight into a wider class of second interrelated neurobehavioral phenomena. However, the major caveat of such a data-driven approach is a lack of theoretical motivation and generalizability. These deficiencies in each method may be best addressed by a synthesis: capitalizing on the foundations provided by the rich literature of event-related potentials while developing methodological advancements to push past previous boundaries. Future advancements may include a better understanding of the information carried within the EEG spectra within this temporospatial network, as phase and power information may reflect different aspects of information content (Buzsáki, 2010). Imminent reports are also sure to further refine algorithmic definitions for subjective probability (e.g., prediction error) and motivational significance (e.g.