Support for this class of models has come from the analysis of grid cells in the entorhinal cortex (de Almeida et al., 2012), a region that provides input to the hippocampus and has been previously implicated in working memory (Gaffan and Murray, 1992; Ranganath

and D’Esposito, 2001; Stern et al., 2001; Suzuki et al., 1997; Young et al., 1997). It was found that the entorhinal cortex has a working memory mode in which find protocol grid cells represent the recent past (i.e., positions behind the animal). Consistent with the model of Figure 1B, cells representing different positions fired in different gamma subcycles of the theta cycle. Another way of asking whether the theta-gamma code underlies working memory is to relate the oscillations to the psychophysically measured properties of working memory. A classic result (Miller, 1956) is that working memory has a capacity limit (span) of 7 ± 2 (see Cowan [2001] for a slightly lower value). The number of gamma cycles within a theta cycle may be what sets the capacity limitation for working memory (Lisman and Idiart, 1995). Initial efforts

to test this concept sought to use the theta-gamma framework to quantitatively account for response time properties of the Sternberg task (i.e., time to respond to whether a given test item was on a short list presented several seconds before). Selleck Inhibitor Library The linear dependence of response no time on the number of items in working memory suggested that the list was serially and exhaustively scanned at a rate of 20–30 ms per memory item (Sternberg, 1966), a time that approximately equals the duration of a gamma cycle. These and other quantitative results of the Sternberg task can be accounted for by models based on the theta-gamma code assuming either that theta phase is reset by stimuli or that theta frequency decreases with memory load (Jensen and Lisman, 1998). Experiments provide evidence for both effects (Axmacher et al.,

2010; Moran et al., 2010; Mormann et al., 2005; Rizzuto et al., 2006). Recent work sought to determine whether properties of theta and gamma oscillations in individuals could explain their memory span. The ratio of theta to gamma (i.e., the maximum number of gamma cycles within a theta cycle) was found to correlate with span (Kamiński et al., 2011). However, the determinations of oscillation frequencies were very noise sensitive, raising doubts about the conclusion. Rigorous testing of this relationship will require resolution of the controversy about which brain regions are responsible for short-term memory maintenance and better methods for noninvasive measurement of the oscillatory frequencies at those locations.