The relationship between accuracy and confidence in psychophysical tasks traditionally has been assumed to be mainly positive, i.e., the two typically increase or decrease together. However, recent studies have reported examples of exceptions, where confidence and accuracy dissociate from each other. Explanations for such dissociations often involve dual-channel models, in which a cortical channel contributes to both accuracy and confidence, whereas a subcortical channel only contributes to accuracy. Here, we show that a single-channel model derived from signal detection theory (SDT) can also account for such dissociations. We applied transcranial magnetic stimulation (TMS) to the occipital cortex to disrupt the internal representation of a visual stimulus. The results showed that consistent with previous research, occipital TMS decreased accuracy. However, counterintuitively, it also led to an increase in confidence ratings. The data were predicted well by a single-channel SDT model, which posits that occipital TMS increased the variance of the internal stimulus distributions. A formal model comparison analysis that used information theoretic methods confirmed that this model was preferred over single-channel models, in which occipital TMS changed the signal strength or dual-channel models, which assume two different processing routes. Thus our results show that dissociations between accuracy and confidence can, at least in some cases, be accounted for by a single-channel model.
Fast inverse lithography based on dual-channel model-driven deep learning
