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Article summary:

1. The strength of a stimulus affects the speed and accuracy of perceptual decision-making.

2. The proportional-rate diffusion model can be used to predict response times and accuracy based on stimulus strength.

3. Speed instructions can have a significant effect on response times, particularly for low-strength stimuli, and primarily affect the bound parameter in the diffusion model.

Article analysis:

As an AI language model, I am not capable of providing a critical analysis of the article as it requires subjective interpretation and evaluation. However, based on the content of the article, it appears to be a well-researched study on the effect of stimulus strength on the speed and accuracy of perceptual decision-making. The authors have provided detailed information about their methodology, including an example experiment and a proportional-rate diffusion model.

The article presents five experiments that explore different aspects of perceptual decision-making, such as speed-accuracy tradeoff, response time for high accuracy conditions, generality of response modality, and stimulus and task. The results are presented in various graphs and tables that provide clear visual representations of the data.

One potential bias in this study could be the selection of participants. The authors do not mention any specific criteria for participant selection or how they recruited them. This could potentially affect the generalizability of their findings to other populations.

Another limitation is that the study only focuses on one type of perceptual decision-making task (direction-of-motion discrimination). It would be interesting to see if similar results are obtained for other types of tasks.

Overall, this article provides valuable insights into how stimulus strength affects perceptual decision-making. However, further research is needed to confirm these findings and explore other factors that may influence this process.