Gamma Rhythms & Running Speed
Gamma oscillations, often coupled to the theta rhythm, are common signatures of processing throughout the hippocampus (Buzsáki et al., 1983; Bragin et al., 1995; Csicsvari et al., 2003; for review, see Colgin and Moser, 2010) and neocortex (Gray et al., 1989; Sanes and Donoghue, 1993; Fries et al., 2001; Sirota et al., 2008). Neocortical gamma rhythms play important roles in sensory perception, decision-making, and attention and have been proposed to ‘bind’ distributed networks encoding related information (Singer 1999; Engel and Singer, 2001; Engel et al., 2001; Fries 2005; 2009; but see Ray and Maunsell, 2010). Given the speed-dependent rate modulation of inhibitory FS neurons discussed above and the critical role FS cells play in generating gamma oscillations (Cardin et al., 2009; Börgers et al., 2005; Traub et al., 1999; Ahmed and Cash, 2013), one would expect hippocampal gamma rhythms to also be speed modulated. Indeed, numerous studies have now documented precise changes in hippocampal gamma at different running speeds. Hippocampal CA1 gamma frequency in rats (Ahmed and Mehta 2012; Kemere et al., 2013) and gamma power in mice (Chen et al., 2011; Gereke et al., 2017; Lopes-dos-Santos et al., 2018) have both been shown to increase with faster running speeds. Similar changes in CA1 gamma have been noted as a function of increasing acceleration (Kemere et al., 2013).
Recent evidence has shown that speed exerts a larger influence on ‘fast’ gamma frequencies (~60-100 Hz) compared to that on ‘slow’ gamma (~25-55 Hz) (Zheng et al., 2015; Trimper et al., 2017; but see Gereke et al., 2017) (Fig. 2). Moreover, a decrease in CA1 slow gamma power with increased speed has also been reported (Ahmed & Mehta, 2012; Kemere et al., 2013; Lopes-dos-Santos et al., 2018). Given that fast and slow CA1 gamma are differentially coupled to MEC and CA3 inputs, respectively (Colgin et al., 2009), these findings, in conjunction with the aforementioned findings for differential rate-speed relationships throughout this network, suggest that MEC grid cells are likely to exert stronger influences over CA1 place cells at faster running speeds, especially when compared to influences from CA3. This idea is further supported by the finding that transgenic mice lacking CA3 innervation of CA1 display unaffected speed modulation of CA1 fast gamma (Middleton and McHugh, 2016).
There may be key computational advantages to speeding up rhythms at faster running speeds. As one moves more quickly through an environment, there is a need for faster transitions between spatially modulated place and grid cell assemblies (Dragoi and Buzsáki, 2006; Harris, 2005). The changes in the precise frequency of both gamma and theta rhythms may facilitate this process (Geisler et al., 2007; Maurer et al., 2012; Ahmed and Mehta, 2012), helping to maintain a spatially-invariant representation of our environment even as we move at very different speeds. Despite this tantalizing theoretical framework, additional work is needed to causally establish how precise changes in brain rhythms at different running speeds impact spatial memory formation.