Automaticity speeds the retrieval of instances from the human hippocampus - Yuanyuan Zhang; Junxi Chen; Geoffrey F. Woodman; Rongqi Lin; Fuyong Chen; Xuchu Weng; Ole Jensen; Jan Theeuwes; Benchi Wang (Proceedings of the National Academy of Sciences, 2025)
Automatic processing allows humans to perform tasks with minimal effort following learning. Although theories of automaticity propose that learning should result in faster processing, studies have universally found that learning reduces the amplitude of neural activity, not that it speeds neural activity. Here, we show that with intracranial activity recorded from the hippocampus of twenty-two humans, we could decode the target the participant was about to report faster across learning. Theta oscillations in the hippocampus afforded faster decoding of the to-be-reported target as learning progressed, unlike in prefrontal and temporal regions of the cortex. Furthermore, hippocampal ripples (70 to 180 Hz bursts) appear to support memory retrieval after learning established automaticity. Our findings demonstrate that the hippocampus plays a key role in speeding memory retrieval of previous learning episodes as humans gain expertise, supporting a critical but untested prediction of learning theories.