Physical Sciences and Mathematics Commons^™

Unique Scales Preserve Self-Similar Integrate-And-Fire Functionality Of Neuronal Clusters, Anar Amgalan, Patrick Taylor, Lilianne R. Mujica-Parodi, Hava T. Siegelmann

Computer Science Department Faculty Publication Series

Brains demonstrate varying spatial scales of nested hierarchical clustering. Identifying the brain's neuronal cluster size to be presented as nodes in a network computation is critical to both neuroscience and artificial intelligence, as these define the cognitive blocks capable of building intelligent computation. Experiments support various forms and sizes of neural clustering, from handfuls of dendrites to thousands of neurons, and hint at their behavior. Here, we use computational simulations with a brain-derived fMRI network to show that not only do brain networks remain structurally self-similar across scales but also neuron-like signal integration functionality (integrate and fire) is preserved at …