Assistant Professor, Department of Psychology
Ph.D. Stanford University
Postdoctoral Fellowship, Yale University
Research Interests: Cognitive Neuroscience, Memory, Cognitive Control, fMRI Methods
Overview: I am interested in how our perceptual experiences are transformed into memories and how we recreate and selectively recall these experiences. Research in my lab makes use of behavioral and neuroimaging methods (primarily fMRI) with an emphasis on applying machine learning algorithms and multivariate pattern analyses to neuroimaging data in order to understand how memories are represented and transformed in distributed patterns of brain activity.
Some of the specific topics my lab addresses include: What are the cognitive and neural mechanisms that cause forgetting? How is competition between memories signaled and resolved in the brain during retrieval? How do we reduce interference between memories during encoding? Addressing these questions involves understanding the interactions and relative contributions of fronto-parietal cortex and medial temporal lobe structures.
Overlap among Spatial Memories Triggers Repulsion of Hippocampal Representations.
Curr Biol. 2017 Jul 15;:
Authors: Chanales AJH, Oza A, Favila SE, Kuhl BA
Across the domains of spatial navigation and episodic memory, the hippocampus is thought to play a critical role in disambiguating (pattern separating) representations of overlapping events. However, it is not fully understood how and why hippocampal patterns become separated. Here, we test the idea that event overlap triggers a "repulsion" among hippocampal representations that develops over the course of learning. Using a naturalistic route-learning paradigm and spatiotemporal pattern analysis of human fMRI data, we found that hippocampal representations of overlapping routes gradually diverged with learning to the point that they became less similar than representations of non-overlapping events. In other words, the hippocampus not only disambiguated overlapping events but formed representations that "reversed" the objective similarity among routes. This finding, which was selective to the hippocampus, is not predicted by standard theoretical accounts of pattern separation. Critically, because the overlapping route stimuli that we used ultimately diverged (so that each route contained overlapping and non-overlapping segments), we were able to test whether the reversal effect was selective to the overlapping segments. Indeed, once overlapping routes diverged (eliminating spatial and visual similarity), hippocampal representations paradoxically became relatively more similar. Finally, using a novel analysis approach, we show that the degree to which individual hippocampal voxels were initially shared across route representations was predictive of the magnitude of learning-related separation. Collectively, these findings indicate that event overlap triggers a repulsion of hippocampal representations-a finding that provides critical mechanistic insight into how and why hippocampal representations become separated.
PMID: 28736170 [PubMed - as supplied by publisher]