Experience-dependent trends in CA1 theta and slow gamma rhythms in freely behaving mice
Abstract
CA1 place cells become more anticipatory with experience, an effect thought to be caused by NMDA receptor-dependent plasticity in the CA3–CA1 network. Theta (~5–12 Hz), slow gamma (~25–50 Hz), and fast gamma (~50–100 Hz) rhythms are thought to route spatial information in the hippocampal formation and to coordinate place cell ensembles. Yet, it is unknown whether these rhythms exhibit experience-dependent changes concurrent with those observed in place cells. Slow gamma rhythms are thought to indicate inputs from CA3 to CA1, and such inputs are thought to be strengthened with experience. Thus, we hypothesized that slow gamma rhythms would become more evident with experience. We tested this hypothesis using mice freely traversing a familiar circular track for three 10-min sessions per day. We found that slow gamma amplitude was reduced in the early minutes of the first session of each day, even though both theta and fast gamma amplitudes were elevated during this same period. However, in the first minutes of the second and third sessions of each day, all three rhythms were elevated. Interestingly, theta was elevated to a greater degree in the first minutes of the first session than in the first minutes of later sessions. Additionally, all three rhythms were strongly influenced by running speed in dynamic ways, with the influence of running speed on theta and slow gamma changing over time within and across sessions. These results raise the possibility that experience-dependent changes in hippocampal rhythms relate to changes in place cell activity that emerge with experience.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Feb 01, 2018
- Source ID
- 10.1152/jn.00472.2017
Entities
People
- Alexandra J. Mably
- Brian J. Gereke
- Laura Colgin
Organizations
- Alfred P. Sloan Foundation
- Alzheimer's Association
- Esther A. & Joseph Klingenstein Fund
- National Science Foundation
- Office of Naval Research
- University of Texas at Austin