Beta oscillations and hippocampal place cell learning during exploration of novel environments
✍ Scribed by Stephen Grossberg
- Book ID
- 102243682
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- English
- Weight
- 183 KB
- Volume
- 19
- Category
- Article
- ISSN
- 1050-9631
No coin nor oath required. For personal study only.
✦ Synopsis
The role of the hippocampal system in spatial navigation has been of great interest since O' Keefe and Dostrowsky (1971) showed the spatial correlates of pyramidal cell firing in the hippocampus. Many of these cells tend to fire in a specific portion of the environment independently of the head direction and movement speed, hence the term place cells. Such place cell selectivity can develop within seconds to minutes, and can remain stable for months (Thompson and Best, 1990;Wilson and McNaughton, 1993;Muller, 1996;Frank et al., 2004). Many models of hippocampal place cell formation have been proposed but, until recently, none has explained this combination of fast learning and stable memory, which is often called the stability-plasticity dilemma (Grossberg, 1980(Grossberg, , 1999)). How place cells are learned and remembered has attracted even more interest since the recent discovery of grid cells (Hafting et al., 2005) within entorhinal cortical circuits that project to the hippocampus.
Berke et al. ( 2008) have reported that beta oscillations occur during the learning of hippocampal place cell receptive fields in novel environments. Paradoxically, beta power was very low during the first lap of exploration, grew to full strength as a mouse traversed a lap for the second and third times, became low again after the first 2 min of exploration, and remained low on subsequent days of exploration. Beta oscillation power also correlated with the rate at which place cells became spatially selective, and did not correlate with theta oscillations. Given the rapidity with which place cell learning occurred, and the sharp increase in beta activity during the second exposure to the environment, it would seem that a highly selective learning mechanism is at work. The present letter explains these properties of beta oscillations as natural consequences of brain processes that enable place cell receptive fields to solve the stability-plasticity dilemma. This explanation unifies three parallel streams of modeling activity, and leads to testable predictions aimed at clarifying the underlying neural mechanisms.