Figure 9.

Learning-associated desynchronization in model excitatory neurones and IT. Graphs show (A) Significantly greater desynchronization of the 100 excitatory neurons in the model as a function of stimulus strength (Iapp) after learning (black) compared with during it (grey) (using an overall mean for all Iapp values t18 = -5.30, p < 0.0001). Data are mean ± sem from 10 runs. (B) Negative correlation between synchronization and the theta/gamma ratio in MUA recordings from IT (r = -0.32, p < 0.001), (C) Negative correlation between excitatory neuron synchronization and size of the theta/gamma ratio, r = -0.42, p < 0.001, (D) Negative correlation between synchronization index and firing rate of the downstream neuron r = -0.60, p < 0.001, (E) Firing frequency distribution and theta waves generated by the model's 100 excitatory neurons in 5 ms bins for 1s after stimulus onset during learning and (F) after learning (Iapp = 0.8). After learning more time bins during theta waves have active neurons compared with before learning as a result of greater desynchronization. NMDA, AMPA and GABA A receptor coefficients as in Figure 8.

Kendrick et al. BMC Neuroscience 2011 12:55   doi:10.1186/1471-2202-12-55
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