9957, p = 2e−07). To account for the sensory consequences of morphing on LEC, we assumed that the spatial response of each cell is switched from one map to an independently generated one at some random point during morphing (different assumptions are examined

online in Supplemental Text, Figure S1). The resulting receptive fields are shown for 10 LEC cells in Figure 1B. In Lonafarnib ic50 order to approximate the response dynamics of the EC during environment morphing, we generated the rate maps for both LEC and MEC (10,000 neurons each). To compute the excitatory input to each individual DG neuron, we used a realistic number of inputs (1200 from the MEC and 1500 from LEC; see Experimental Procedures) and summed them. Each synaptic input to the DG was taken from a population of randomly chosen entorhinal neurons, with the synaptic weight randomly assigned according to the synaptic weight distribution derived from the distribution selleck inhibitor of synapse sizes (de Almeida et al., 2009a) as determined by serial EM (Trommald and Hulleberg, 1997). The spatial distribution of firing of 10,000 DG granule cells was computed by applying, at each position, a winner-take-all interaction over the sum of excitation input. This winner-take-all process is governed by the so-called E%-max principle (de Almeida et al., 2009b) derived from the

interaction of excitation with gamma frequency feedback inhibition, a form of inhibition known to exist in this brain region (Bragin et al., 1995, Towers et al., 2002 and Pöschel et al., 2002) that synchronizes the firing of DG cells (reviewed by Bartos et al., 2007). According to this principle, the level of inhibition is set such that cells will fire provided their excitation is within 10% of the cell with maximum excitation. For these cells, their rate is proportional to where they (-)-p-Bromotetramisole Oxalate fall in this 10% range. The value of 10% is computed from d/τm (de Almeida et al., 2009b),

where d = delay of feedback inhibition and τm = membrane time constant, both of which have been experimentally determined. A previous study showed that the interaction of MEC input with this form of inhibition is able to quantitatively account for the size and number of place fields exhibited by active DG cells (de Almeida et al., 2009a). In our simulations, we also take into consideration the LEC. The interaction of the two inputs depends on the ratio (α) of the mean drive of MEC and LEC onto EC. No data is available that would allow us to directly estimate α. However, our results provide for a quantitative estimate of its value (see below). With this simulation framework in place, we investigated whether the cumulative decorrelation of population output from the DG observed during progressive morphing of the arena shape (Leutgeb et al., 2007; population vector [PV] correlation curve, Figure 3A) could be explained by the changes of the LEC spatial response.