RT Journal Article SR Electronic T1 Temporal Dynamics of Competition between Statistical Learning and Episodic Memory in Intracranial Recordings of Human Visual Cortex JF The Journal of Neuroscience JO J. Neurosci. FD Society for Neuroscience SP 9053 OP 9068 DO 10.1523/JNEUROSCI.0708-22.2022 VO 42 IS 48 A1 Brynn E. Sherman A1 Kathryn N. Graves A1 David M. Huberdeau A1 Imran H. Quraishi A1 Eyiyemisi C. Damisah A1 Nicholas B. Turk-Browne YR 2022 UL http://www.jneurosci.org/content/42/48/9053.abstract AB The function of long-term memory is not just to reminisce about the past, but also to make predictions that help us behave appropriately and efficiently in the future. This predictive function of memory provides a new perspective on the classic question from memory research of why we remember some things but not others. If prediction is a key outcome of memory, then the extent to which an item generates a prediction signifies that this information already exists in memory and need not be encoded. We tested this principle using human intracranial EEG as a time-resolved method to quantify prediction in visual cortex during a statistical learning task and link the strength of these predictions to subsequent episodic memory behavior. Epilepsy patients of both sexes viewed rapid streams of scenes, some of which contained regularities that allowed the category of the next scene to be predicted. We verified that statistical learning occurred using neural frequency tagging and measured category prediction with multivariate pattern analysis. Although neural prediction was robust overall, this was driven entirely by predictive items that were subsequently forgotten. Such interference provides a mechanism by which prediction can regulate memory formation to prioritize encoding of information that could help learn new predictive relationships.SIGNIFICANCE STATEMENT When faced with a new experience, we are rarely at a loss for what to do. Rather, because many aspects of the world are stable over time, we rely on past experiences to generate expectations that guide behavior. Here we show that these expectations during a new experience come at the expense of memory for that experience. From intracranial recordings of visual cortex, we decoded what humans expected to see next in a series of photographs based on patterns of neural activity. Photographs that generated strong neural expectations were more likely to be forgotten in a later behavioral memory test. Prioritizing the storage of experiences that currently lead to weak expectations could help improve these expectations in future encounters.