Using an idealized and detailed biophysical model based on sine waves, Remme et al., (2010) demonstrated that a biologically realistic bidirectional interaction between the local dendritic

oscillations and global oscillations (in this case, soma oscillations) results Panobinostat molecular weight in complete phase locking between all oscillations and a subsequent loss of the grid cell firing pattern. Phase locking occurred in the range of hundreds of milliseconds, even with parameters generously skewed toward promoting dendritic independence (Remme et al., 2010). Though not ruling out the potential importance of oscillatory and resonant properties, the detrimental effects of phase locking emphasize the importance of multicellular and network mechanisms click here in the generation of spatial periodicity. Motivated by the challenges of dealing with noise and phase locking, the single-cell oscillatory model has evolved into several

second-generation models. In general, oscillatory-interference models use oscillatory phase to perform a temporal integration of a rate-coded velocity signal (a rate-to-phase transformation). This transformation does not need to occur within a single neuron, and several models have simply moved the oscillators into clusters of different neurons. The velocity-driven oscillators can take the form of persistent-firing neurons (Hasselmo, 2008), single oscillatory neurons (Burgess, 2008), subcortical ring attractors generating velocity-modulated theta

and oscillations (Blair et al., 2008), or networks of coupled oscillatory neurons (Zilli and Hasselmo, 2010) (Figures 2C and 2D). However, persistent-firing models still suffer from the same noise problems as those encountered by the single-cell oscillatory models (Zilli et al., 2009), due to the variability in the frequency of persisting spiking. One method for dealing with noisy oscillators is to assume that sensory cues frequently or constantly update the grid cell network. It has been proposed that memories of sensory configurations, supported by the hippocampus, can provide the needed updates to maintain a coherent grid pattern in the presence of noise (Burgess et al., 2007, Hasselmo et al., 2007 and O’Keefe and Burgess, 2005). The frequency of the required updating has not been determined. Grid cells can maintain firing fields for up to ten minutes during foraging in complete darkness (Hafting et al., 2005), but the animals continue to receive tactile input from the walls of the recording box in such experiments, and the map may disintegrate with a much faster time constant on an open surface. Future studies must establish the accuracy of path integration over time, under conditions with no external sensory input, if we are to determine whether the limited persistence of grid representations in the oscillatory-interference models is biologically valid.