Abstract
Whether and how persistent firing in lateral entorhinal cortex layer III (LEC III) supports temporal associative learning is still unknown. In this study, persistent firing was evoked in vitro from LEC III neurons from young and aged rats that were behaviorally naive or trained on trace eyeblink conditioning. Persistent firing ability from neurons from behaviorally naive aged rats was lower compared to neurons from young rats. Neurons from learning impaired aged animals also exhibited reduced persistent firing capacity, which may contribute to aging-related learning impairments. Successful acquisition of the trace eyeblink task, however, increased persistent firing ability in both young and aged rats. These changes in persistent firing ability are due to changes to the afterdepolarization, which may in turn be modulated by the postburst afterhyperpolarization. Together, these data indicate that successful learning increases persistent firing ability and decreases in persistent firing ability contribute to learning impairments in aging.
Original language | English (US) |
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Article number | e56816 |
Pages (from-to) | 1-30 |
Number of pages | 30 |
Journal | eLife |
Volume | 9 |
DOIs | |
State | Published - Jul 2020 |
Funding
We thank Dr. Motoharu Yoshida for advice regarding evoking persistent firing in entorhinal neurons. We thank Michael McCarthy and Natalia Vilcek for training the rats on trace eyeblink conditioning and analyzing the behavioral data. We thank Dr. John Power for writing the eyeblink conditioning LabView software that was used to train the animals and analyze the behavioral data. We thank Dr. Shoai Hattori for writing the Matlab code to analyze the postburst AHP data. This work was supported by NIH Grant R37AG008796 (to JFD), RF1AG017139 (to JFD) and F31AG055331 (to CL). We thank Dr. Motoharu Yoshida for advice regarding evoking persistent firing in entorhinal neurons. We thank Michael McCarthy and Natalia Vilcek for training the rats on trace eyeblink conditioning and analyzing the behavioral data. We thank Dr. John Power for writing the eyeblink conditioning LabView software that was used to train the animals and analyze the behavioral data. We thank Dr. Shoai Hattori for writing the Matlab code to analyze the postburst AHP data. This work was supported by NIH Grant R37AG008796 (to JFD), RF1AG017139 (to JFD) and F31AG055331 (to CL). National Institutes of Health AG008796 John F Disterhoft National Institutes of Health AG017139 John F Disterhoft National Institutes of Health AG55331 Carmen Lin.
ASJC Scopus subject areas
- General Immunology and Microbiology
- General Biochemistry, Genetics and Molecular Biology
- General Neuroscience