Leave-One-Trial-Out (LOTO) is a general, efficient and easily implementable approach for inferring trial-by-trial measures of computational model parameters in order to link these measures to neural mechanisms.
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.
Facing discrepancies in the sensory environment, multisensory information is combined in the medial superior parietal cortex to guide immediate judgements and to also adjust subsequent unisensory perception.
During behavior, many neurons do not have classic trial-averaged responses to behaviorally relevant stimuli, but can still have activity and population dynamics related to stimulus and behavioral choice on single trials.
During learning, one climbing fiber input instructs plasticity that is expressed in the simple-spike responses of cerebellar Purkinje cells, and causes neural learning that may inhibit future climbing fiber instructions.
A molecular model of the assembled COPI coat, determined by cryo-electron tomography of an in vitro reconstituted budding reaction, reveals details of interactions mediating coat assembly and shows the binding site of ArfGAP2.