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Fig. 3 | The Journal of Mathematical Neuroscience

Fig. 3

From: Inhomogeneous Sparseness Leads to Dynamic Instability During Sequence Memory Recall in a Recurrent Neural Network Model

Fig. 3

Inhomogeneous pattern sizes lead to dynamic instability during sequence replay. In all graphs, we show the fraction m t / M t of hits (blue) at time step t and the fraction n t /(N M t ) of false alarms (red) during the replay of a sequence of length Q=100, using the mean field model of equations (9) and following. Left to right: increasing inhomogeneity σ ϕ . Bottom to top: increasing firing thresholds θ. Other parameters were N= 10 5 , c m =0.1, c=0.05 and ϕ 0 =0.01

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