Polarity-specific high-level information propagation in neural networks.

ABSTRACT: Analyzing the connectome of a nervous system provides valuable information about the functions of its subsystems. Although much has been learned about the architectures of neural networks in various organisms by applying analytical tools developed for general networks, two distinct and functionally important properties of neural networks are often overlooked. First, neural networks are endowed with polarity at the circuit level: Information enters a neural network at input neurons, propagates through interneurons, and leaves via output neurons. Second, many functions of nervous systems are implemented by signal propagation through high-level pathways involving multiple and often recurrent connections rather than by the shortest paths between nodes. In the present study, we analyzed two neu

SUBMITTER: Lin YN 

PROVIDER: S-EPMC3955877 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature