Biomedical subjects

C Cherniak

Publications and source records attributed to C Cherniak.

3 recordsLinked to original sources

PubMed1995

Neural component placement.

A range of neuroanatomical results supports the idea that 'save wire' is an organizing principle of brain structure: that the theory of combinatorial optimization of networks applies to the anatomy of the nervous system. In particular, optimization of the placement of components operates at several hierarchical levels in the nervous system, from gross to microscopic anatomy, and from invertebrates to primates. That is, when anatomical positioning of interconnected neural components is treated like a problem of wire minimization in microchip layout, a hypothesis of 'best of all possible brains' is consistent with the observed siting of brains, ganglia, and even somata of individual neurons that minimizes the length of interconnections. In the case of the positioning of ganglia of Caenorhabditis elegans, optimization predictions of one-in-a-million precision can be verified.

Animals↗

PubMed1994

Component placement optimization in the brain.

This computational neuroanatomy study evaluates how well some formalisms derived from combinatorial network optimization theory fit as models for brain structure. At multiple hierarchical levels--brain, ganglion, individual cell--physical placement of neural components appears consistent with a single, simple goal: minimize cost of connections among the components. The most dramatic instance of this "save wire" organizing principle is reported for adjacencies among ganglia in the nematode nervous system; among about 40,000,000 alternative layout orderings, the actual ganglion placement in fact requires the least total connection length. In addition, evidence supports a component placement optimization hypothesis for positioning of individual neurons in the nematode, and also for positioning of mammalian cortical areas.

Adult↗

PubMed1992

Local optimization of neuron arbors.

How parsimoniously is brain wiring laid out, that is, how well does a neuron minimize costs of connections among its synapses? Neural optimization of dendritic and axonic arbors can be evaluated using a generalization of the Steiner tree concept from combinatorial network optimization theory. Local branch-junction geometry of neuronal connecting structures fits a volume minimization model well. In addition, volume of the arborizations at this neighborhood level is significantly more strongly minimized than their length, signal propagation speed, or surface area. The mechanism of this local volume optimization resembles those involved in formation of nonliving tree structures such as river junctions and electric-discharge patterns, and appears to govern initial nerve growth-cone behavior through vector-mechanical energy minimization.

Animals↗