Perceptual bias is reduced with longer reaction times during visual discrimination

 Perceptual bias is reduced with longer reaction times during visual discrimination

In a recent study published in Communications Biology, researchers delved into the intriguing relationship between decision-making speed and biases in human perception. Human decisions often exhibit biases, especially in tasks related to visual perception. For instance, contextual effects and prior experiences can lead to systematic biases in judgments of objects' properties such as orientation, size, and color. The researchers explored biases in both fast and slow decisions and suggested a single-process explanation based on the stochastic properties of decision processes.

Prior-Dependent Bias:

The researchers conducted experiments where participants discriminated between two oriented visual stimuli with varying frequencies of occurrence. The bias towards one stimulus decreased significantly with increasing reaction time. This reduction in bias was explained by the gradual accumulation of sensory evidence and noise over time. The team employed the drift-diffusion model (DDM), a widely used model in decision-making research, to illustrate how biases diminish with time due to accumulated noise and evidence.

Context-Dependent Bias:

The study also investigated biases influenced by surrounding contexts, both spatial and temporal. For example, an oriented surrounding context can lead to a change in the perceived orientation of a central target. The researchers found that biases induced by contextual cues decreased with decision time. By employing mathematical models, they demonstrated that biases in perception gradually faded as a result of accumulating noise and evidence.

Modeling the Phenomenon:

The researchers used the DDM to model the reduction in biases over time. In the bounded DDM, biases diminished rapidly with time due to the accumulation of evidence until a decision threshold was reached. However, for context-dependent biases, both the starting point and the rate of evidence accumulation had to be modified in the model to account for the slow reduction in biases. Additionally, an unbounded model was considered, where biases decreased at a slower, logarithmic rate over time.

Conclusion:

The complex interactions between perceptual biases and decision-making speed are explained by this study. The researchers showed that biases in human perception decrease as sensory data and noise build up over time during the decision-making process through the use of behavioral studies and mathematical models. In addition to expanding our knowledge of human cognition, this work offers insightful information for decision-making studies in a variety of fields.

Source:https://www.nature.com/articles/s42003-020-0786-7
Author: Ron Dekel & Dov Sagi

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