RT Journal Article
SR Electronic
T1 Neuronal population correlates of target selection and distractor filtering
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 422873
DO 10.1101/422873
A1 Elaine Astrand
A1 Claire Wardak
A1 Suliann Ben Hamed
YR 2018
UL http://biorxiv.org/content/early/2018/09/20/422873.abstract
AB Frontal Eye Field (FEF) single-cell neuronal activity discriminates between relevant and irrelevant visual stimuli and its magnitude has been shown to predict conscious perception. How this is reflected at the population level in terms of spatial codes is unknown. We recorded neuronal population activity in the FEF while monkeys were performing a forced choice cued detection task with identical target and distractor stimuli. Using machine learning techniques, we quantified information about the spatial estimate of targets and distracters in the FEF population activity and we analyzed how these relate to the report of perception. We found that the FEF population activity provides a precise estimate of the spatial location of perception. This estimate doesn’t necessarily match the actual physical world. Importantly, the closer this prefrontal population estimate is to the veridical spatial information, the higher the probability that the stimulus was reported as perceived. This was observed both when the reported stimulus was a target (i.e. correct detection trials) or a distractor (i.e. false alarm trials). Overall, we thus show that how and what we perceive of our environments depends on the precision with which this environment is coded by prefrontal neuronal populations.