A model framework and toolbox to quantify metacognitive biases and sources of metacognitive noise in animal and human confidence data.

Improvement in levels of anxious-depression corresponds with increased confidence in performance among individuals receiving mental health treatment within a large longitudinal dataset.

Explicit judgments of agency incorporate uncertainty by reflecting first-order measures of a noisy signal, but they do not correspond to second-order metacognitive measures of the noise in a signal.

The neurotransmitter noradrenaline selectively modulates metacognition, the conscious insight into one's performance, but does not alter perceptual decision making, revealing that different neuromodulators affect different stages of a decision making process.

Error detection is contingent on the continuation of evidence accumulation after choice commitment, and the speed and accuracy of this process are modulated by high-level signals from medial frontal cortex.

Combining psychophysics and functional MRI reveals a qualitative asymmetry in neural engagement when reflecting on whether a stimulus is seen (detection) compared to reflecting on what a stimulus is (discrimination).

Intra-individual variability in choice, response time, subjective effort, confidence, and choice-induced preference change and certainty gain is explained by a cost–benefit model of cognitive resource allocation.

Neural processes for perception and confidence can be separated thanks to computational electroencephalography, thus revealing a neural circuit specific to metacognition.

Changes in physiological arousal – as revealed by pupil dilation and heart rate – shape our confidence in decisions about uncertain perceptual information.

Simultaneous EEG-fMRI reveals neural representations of decision confidence unfolding prior to explicit perceptual choices, in a region of the ventromedial prefrontal cortex typically linked to reward processing and value-based decisions.