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.