Network Design and the Brain.
The Salk Institute for Biological Studies, Integrative Biology Laboratory, La Jolla, CA 92037, USA. Electronic address: [email protected]
Carnegie Mellon University, Machine Learning Department, Computational Biology Department, Pittsburgh, PA 15213, USA.
Carnegie Mellon University, Center for the Neural Basis of Cognition, Department of Biological Sciences, Pittsburgh, PA 15213, USA.
- Published Article
Trends in cognitive sciences
- Publication Date
Oct 17, 2017
Neural circuits have evolved to accommodate similar information processing challenges as those faced by engineered systems. Here, we compare neural versus engineering strategies for constructing networks. During circuit development, synapses are overproduced and then pruned back over time, whereas in engineered networks, connections are initially sparse and are then added over time. We provide a computational perspective on these two different approaches, including discussion of how and why they are used, insights that one can provide the other, and areas for future joint investigation. By thinking algorithmically about the goals, constraints, and optimization principles used by neural circuits, we can develop brain-derived strategies for enhancing network design, while also stimulating experimental hypotheses about circuit development and function.
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This record was last updated on 06/09/2018 and may not reflect the most current and accurate biomedical/scientific data available from NLM.
The corresponding record at NLM can be accessed at https://www.ncbi.nlm.nih.gov/pubmed/29054336