<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Cao, Runnan</style></author><author><style face="normal" font="default" size="100%">Wang, Jinge</style></author><author><style face="normal" font="default" size="100%">Brunner, Peter</style></author><author><style face="normal" font="default" size="100%">Willie, Jon T</style></author><author><style face="normal" font="default" size="100%">Li, Xin</style></author><author><style face="normal" font="default" size="100%">Rutishauser, Ueli</style></author><author><style face="normal" font="default" size="100%">Brandmeir, Nicholas J</style></author><author><style face="normal" font="default" size="100%">Wang, Shuo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Neural mechanisms of face familiarity and learning in the human amygdala and hippocampus.</style></title><secondary-title><style face="normal" font="default" size="100%">Cell Rep</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Cell Rep</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amygdala</style></keyword><keyword><style  face="normal" font="default" size="100%">Facial Recognition</style></keyword><keyword><style  face="normal" font="default" size="100%">Hippocampus</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Learning</style></keyword><keyword><style  face="normal" font="default" size="100%">Pattern Recognition, Visual</style></keyword><keyword><style  face="normal" font="default" size="100%">Recognition, Psychology</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2024 Jan 23</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">43</style></volume><pages><style face="normal" font="default" size="100%">113520</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Recognizing familiar faces and learning new faces play an important role in social cognition. However, the underlying neural computational mechanisms remain unclear. Here, we record from single neurons in the human amygdala and hippocampus and find a greater neuronal representational distance between pairs of familiar faces than unfamiliar faces, suggesting that neural representations for familiar faces are more distinct. Representational distance increases with exposures to the same identity, suggesting that neural face representations are sharpened with learning and familiarization. Furthermore, representational distance is positively correlated with visual dissimilarity between faces, and exposure to visually similar faces increases representational distance, thus sharpening neural representations. Finally, we construct a computational model that demonstrates an increase in the representational distance of artificial units with training. Together, our results suggest that the neuronal population geometry, quantified by the representational distance, encodes face familiarity, similarity, and learning, forming the basis of face recognition and memory.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record></records></xml>