4 papers
Lyapunov spectra of chaotic recurrent neural networks
Rainer Engelken, Fred Wolf, L. F. Abbott
Brains process information through the collective dynamics of large neural networks. Collective chaos was suggested to underlie the complex ongoing dynamics observed in cerebral co…
Training dynamically balanced excitatory-inhibitory networks
Alessandro Ingrosso, L. F. Abbott
The construction of biologically plausible models of neural circuits is crucial for understanding the computational properties of the nervous system. Constructing functional networ…
Feedback alignment in deep convolutional networks
Theodore H. Moskovitz, Ashok Litwin-Kumar, L. F. Abbott
Ongoing studies have identified similarities between neural representations in biological networks and in deep artificial neural networks. This has led to renewed interest in devel…
Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity
Ran Rubin, L. F. Abbott, Haim Sompolinsky
Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustn…