Leveraging decision consistency to decompose suboptimality in terms of its ultimate predictability.

Although the suboptimality of perceptual decision making is indisputable in its strictest sense, characterizing the nature of suboptimalities constitutes a valuable drive for future research. I argue that decision consistency offers a rarely measured, yet important behavioral metric for decomposing suboptimality (or, more generally, deviations from any candidate model of decision making) into ultimately predictable and inherently unpredictable components.