Running Speed Alters the Frequency of Hippocampal Gamma Oscillations

Abstract

Successful spatial navigation is thought to employ a combination of at least two strategies: the following of landmark cues and path integration. Path integration requires that the brain use the speed and direction of movement in a meaningful way to continuously compute the position of the animal. Indeed, the running speed of rats modulates both the firing rate of neurons and the spectral properties of low frequency, theta oscillations seen in the local field potential (LFP) of the hippocampus, a region important for spatial memory formation. Higher frequency, gamma-band LFP oscillations are usually associated with decision-making, increased attention and improved reaction times. Here, we show that increased running speed is accompanied by large, systematic increases in the frequency of hippocampal CA1 network oscillations spanning the entire gamma range (30–120 Hz) and beyond. These speed-dependent changes in frequency are seen on both linear tracks and two-dimensional platforms, and are thus independent of the behavioral task. Synchrony between anatomically distant CA1 regions also shifts to higher gamma frequencies as running speed increases. The changes in frequency are strongly correlated with changes in the firing rates of individual interneurons, consistent with models of gamma generation. Our results suggest that as a rat runs faster, there are faster gamma frequency transitions between sequential place cell-assemblies. This may help to preserve the spatial specificity of place cells and spatial memories at vastly different running speeds.

Fast Gamma Rhythms in the Hippocampus Promote Encoding of Novel Object–Place Pairings

“…2, 3). Slow and fast gamma power estimates were plotted against running speed to examine whether effects were related to differences in running speed, considering that slow and fast gamma are differentially affected by running speed (Ahmed and Mehta, 2012;Kemere et al, 2013;Zheng et al, 2015). Time windows within novel and familiar sessions were also time-matched to account for changes in gamma power that occur across time within a testing session (Bieri et al, 2014; see Materials and Methods, Detection of object exploration periods).…”

“…Estimation of power spectra across running speeds during object exploration The power spectra were measured across different running speeds as described previously (Ahmed and Mehta, 2012;Zheng et al, 2015;see Figs. 2, 3, 7).…”

“…Speed and frequency were plotted on a log-log scale for gamma frequencies (Figs. 2, 3), which allows for better visualization of the relatively narrow band of slow gamma frequencies (ie, compared to the fast gamma band) and the reduced range of running speeds associated with slow gamma compared to fast gamma (Ahmed and Mehta, 2012;Zheng et al, 2015).…”

Grid cells and cortical representation

“…Because beta and gamma epochs are both short-lasting and regionally specific 173,174 , place cells may interact dynamically with a range of entorhinal cell assemblies each carrying a distinct type of information. The efficiency of individual functional inputs depends on behaviour, such as running speed 175 , and evolves in parallel with behavioural learning 174 , suggesting that the balance between inputs to a place cell is experience-dependent.…”

Within-session dynamics of theta–gamma coupling and high-frequency oscillations during spatial alternation in rat hippocampal area CA1

“…In the rat hippocampus, there is a remarkable low-frequency activity, the well-known ''theta rhythm.'' It has been reported that the theta rhythm modulates gamma oscillations (Bragin et al 1995a;Tort et al 2008;Colgin et al 2009;Belluscio et al 2012) and their CFC alters depending on the running speed (Chen et al 2011;Ahmed and Mehta 2012) and the behavioral performance (Tort et al 2009;Shirvalkar et al 2010). Here we particularly focused on the CFC during a delay period, which several studies have suggested to require the involvement of hippocampus for successful task performance (Ainge et al 2007;Pastalkova et al 2008;Takahashi et al 2009a, b;MacDonald et al 2011).…”