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Butola T, Hernández Frausto M, Blankvoort S, Flatset MS, Peng L, Elmaleh M, Hairston A, Hussain F, Clopath C, Kentros C, Basu J. Hippocampus shapes cortical sensory output and novelty coding through a direct feedback circuit. Res Sq 2023:rs.3.rs-3270016. [PMID: 37674706 PMCID: PMC10479401 DOI: 10.21203/rs.3.rs-3270016/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/08/2023]
Abstract
To extract behaviorally relevant information from our surroundings, our brains constantly integrate and compare incoming sensory information with those stored as memories. Cortico-hippocampal interactions could mediate such interplay between sensory processing and memory recall1-4 but this remains to be demonstrated. Recent work parsing entorhinal cortex-to-hippocampus circuitry show its role in episodic memory formation5-7 and spatial navigation8. However, the organization and function of the hippocampus-to-cortex back-projection circuit remains uncharted. We combined circuit mapping, physiology and behavior with optogenetic manipulations, and computational modeling to reveal how hippocampal feedback modulates cortical sensory activity and behavioral output. Here we show a new direct hippocampal projection to entorhinal cortex layer 2/3, the very layer that projects multisensory input to the hippocampus. Our finding challenges the canonical cortico-hippocampal circuit model where hippocampal feedback only reaches entorhinal cortex layer 2/3 indirectly via layer 5. This direct hippocampal input integrates with cortical sensory inputs in layer 2/3 neurons to drive their plasticity and spike output, and provides an important novelty signal during behavior for coding objects and their locations. Through the sensory-memory feedback loop, hippocampus can update real-time cortical sensory processing, efficiently and iteratively, thereby imparting the salient context for adaptive learned behaviors with new experiences.
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Affiliation(s)
- T. Butola
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - M. Hernández Frausto
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - S. Blankvoort
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology; Trondheim, Norway
| | - M. S. Flatset
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology; Trondheim, Norway
| | - L. Peng
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - M. Elmaleh
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - A. Hairston
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - F. Hussain
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
| | - C. Clopath
- Department of Bioengineering, Imperial College London; London, SW7 2AZ, UK
| | - C. Kentros
- Centre for Neural Computation, Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology; Trondheim, Norway
- Institute of Neuroscience, University of Oregon; Eugene, United States
| | - J. Basu
- Neuroscience Institute, New York University Langone Health; New York City, 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine; New York City, 10016, USA
- Department of Psychiatry, New York University Grossman School of Medicine; New York City, 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
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