EEG-representational geometries and psychometric distortions in approximate numerical judgment.

ABSTRACT: When judging the average value of sample stimuli (e.g., numbers) people tend to either over- or underweight extreme sample values, depending on task context. In a context of overweighting, recent work has shown that extreme sample values were overly represented also in neural signals, in terms of an anti-compressed geometry of number samples in multivariate electroencephalography (EEG) patterns. Here, we asked whether neural representational geometries may also reflect a relative underweighting of extreme values (i.e., compression) which has been observed behaviorally in a great variety of tasks. We used a simple experimental manipulation (instructions to average a single-stream or to compare dual-streams of samples) to induce compression or anti-compression in behavior when participants j

SUBMITTER: Appelhoff S 

PROVIDER: S-EPMC9754589 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature