Fig. 1From: Multiscale analysis of slow-fast neuronal learning models with noiseThis shows the (k,q)-temporal profiles with l μ =1, i.e., the functions g 1 ( k + 1 ) ∗ g 1 ′ ( q + 1 ) for q=0 and k ranging from 0 to 6. For k=q=0, the temporal profile is even and this also occurs to be true for any k=q. When k>q, the function reaches its maximum for strictly positive values that grow with the difference k−q. Besides, the temporal profiles are flattened when k+q increases.Back to article page