TY - JOUR TI - A diversity of localized timescales in network activity AU - Chaudhuri, Rishidev AU - Bernacchia, Alberto AU - Wang, Xiao-Jing A2 - Tsodyks, Misha VL - 3 PY - 2014 DA - 2014/01/21 SP - e01239 C1 - eLife 2014;3:e01239 DO - 10.7554/eLife.01239 UR - https://doi.org/10.7554/eLife.01239 AB - Neurons show diverse timescales, so that different parts of a network respond with disparate temporal dynamics. Such diversity is observed both when comparing timescales across brain areas and among cells within local populations; the underlying circuit mechanism remains unknown. We examine conditions under which spatially local connectivity can produce such diverse temporal behavior. In a linear network, timescales are segregated if the eigenvectors of the connectivity matrix are localized to different parts of the network. We develop a framework to predict the shapes of localized eigenvectors. Notably, local connectivity alone is insufficient for separate timescales. However, localization of timescales can be realized by heterogeneity in the connectivity profile, and we demonstrate two classes of network architecture that allow such localization. Our results suggest a framework to relate structural heterogeneity to functional diversity and, beyond neural dynamics, are generally applicable to the relationship between structure and dynamics in biological networks. KW - timescale KW - network dynamics KW - neural network JF - eLife SN - 2050-084X PB - eLife Sciences Publications, Ltd ER -