Visual detection of time-varying signals: opposing biases and their timescales

TL;DR

This study explores how human visual perception fluctuates over time due to opposing biases operating at different timescales, influenced by the temporal structure of stimuli and internal cognitive dynamics.

Contribution

It identifies and characterizes two opposing biases in visual perception, recency and adaptation, and demonstrates their interaction with stimulus timescales through experimental and modeling approaches.

Findings

Positive recency bias operates over short timescales.

Adaptation bias influences responses over longer timescales.

A mathematical model captures the dynamics of perception biases.

Abstract

Human visual perception is a complex, dynamic and fluctuating process. In addition to the incoming visual stimulus, it is affected by many other factors including temporal context, both external and internal to the observer. In this study we investigate the dynamic properties of psychophysical responses to a continuous stream of visual near-threshold detection tasks. We manipulate the incoming signals to have temporal structures with various characteristic timescales. Responses of human observers to these signals are analyzed using tools that highlight their dynamical features as well. We find that two opposing biases shape perception, and operate over distinct timescales. Positive recency appears over short times, e.g. consecutive trials. Adaptation, entailing an increased probability of changed response, reflects trends over longer times. Analysis of psychometric curves conditioned on various temporal events reveals that the balance between the two biases can shift depending on their interplay with the temporal properties of the input signal. A simple mathematical model reproduces the experimental data in all stimulus regimes. Taken together, our results support the view that visual response fluctuations reflect complex internal dynamics, possibly related to higher cognitive processes.