One Process, Two Biases: A Precision-Weighting Account of the Vierordt Effect and Serial Dependence

Abstract:

In 1868, Karl von Vierordt, working in Tübingen, discovered that short durations are overestimated and long durations underestimated. This central tendency effect has since been replicated many times. What went unnoticed for over 150 years is that Vierordt's finding resulted from an accidental deviation from Fechner's prescribed method: by randomizing his stimulus sequence, he inadvertently created a volatile environment that amplifies temporal biases. When the sequence is kept stable, as Woodrow demonstrated in 1930, the effect largely vanishes. This historical puzzle opens a deeper question: how does the brain integrate past experience with current sensory evidence when judging duration, and what neural architectures support this integration? I present converging behavioral, computational, and neuroimaging evidence — across duration reproduction and temporal bisection — showing that central tendency and serial dependence are two expressions of a single precision-weighted inference process. In duration reproduction, Kalman filter models capture central tendency, serial dependence, and decision carryover through one mechanism: precision-dependent modulation of Kalman gain. The model accounts for both uncertainty-driven and context-driven changes in sequential biases without requiring separate gating mechanisms. Functional MRI reveals that the hippocampus gates how strongly prior trials influence current judgments, with active motor engagement amplifying serial dependence through action-perception binding. In temporal bisection, ensemble statistics of the stimulus distribution shape the perceptual prior, shifting decisional criteria without altering temporal sensitivity. Here, neuroimaging shows a dissociation: distributional context does not merely modulate a fixed timing circuit but dynamically reconfigures which brain networks encode duration. Long-biased environments recruit a cortico-striatal pathway through the supplementary motor area, inferior frontal gyrus, and putamen, whereas short-biased environments engage the left insula.

Bio:

Zhuanghua Shi studied mathematics before completing his PhD in psychology in Zhejiang University. He then moved to LMU Munich as a postdoctoral fellow and has remained on the faculty since, earning his Habilitation in 2013 and appointment as Professor in 2020. His research combines psychophysics, EEG, fMRI, and computational modeling to investigate how the brain represents time, integrates information across the senses, and learns from perceptual experience. He coordinates the Neuroimaging Core Unit Munich (NICUM) and is an associated faculty member of the Graduate School of Systemic Neurosciences at LMU, Munich.

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