Nonoptimal Component Placement, but Short Processing Paths, due to Long-Distance Projections in Neural Systems

By Marcus Kaiser, Claus C. Hilgetag. 2006

670 citations recorded by the source corpus.

It has been suggested that neural systems across several scales of organization show optimal component placement, in which any spatial rearrangement of the components would lead to an increase of total wiring. Using extensive connectivity datasets for diverse neural networks combined with spatial coordinates for network nodes, we applied an optimization algorithm to the network layouts, in order to search for wire-saving component rearrangements. We found that optimized component rearrangements could substantially reduce total wiring length in all tested neural networks. Specifically, total wiring among 95 primate (Macaque) cortical areas could be decreased by 32%, and wiring of neuronal networks in the nematode Caenorhabditis elegans could be reduced by 48% on the global level, and by 49% for neurons within frontal ganglia. Wiring length reductions were possible due to the existence of long-distance projections in neural networks. We explored the role of these projections by comparing the original networks with minimally rewired networks of the same size, which possessed only the shortest possible connections. In the minimally rewired networks, the number of processing steps along the shortest paths between components was significantly increased compared to the original networks. Additional benchmark comparisons also indicated that neural networks are more similar to network layouts that minimize the length of processing paths, rather than wiring length. These findings suggest that neural systems are not exclusively optimized for minimal global wiring, but for a variety of factors including the minimization of processing steps.

Subfields: Aging, Cognitive Neuroscience

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Citations in the corpus

The hubs of the human connectome are generally implicated in the anatomy of brain disorders (2014, background): “As such, hubs appear to transgress the parsimonious drive to minimize wiring cost (Kaiser and Hilgetag, 2006), which explains several other organizational features of brain networks (Chen et al., 2006).”
Whole-brain anatomical networks: Does the choice of nodes matter? (2010, background): “, 2000), local efficiency and global efficiency (Kaiser and Hilgetag, 2006; Latora and Marchiori, 2001) and betweenness centrality (Freeman, 1979; Newman, 2003).”
High-cost, high-capacity backbone for global brain communication (2012, background): “Previous analyses of connectivity in nonhuman primates suggested that long-distance projections, although violating strict minimization of wiring volume, act as long-distance shortcuts, ensuring high levels of global information integration while lowering the number of processing steps during commun”
Communication dynamics in complex brain networks (2017, background): “Several computational studies have demonstrated that geometrically embedded networks that minimize wiring cost are characterized by physically short connections that have an overall topology that increases the mean path length 37,39,40 .”
A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks (2011, background): “[57] Chklovskii DB, Schikorski, T and Stevens, CF (2002) Wiring optimization in cortical circuits Neuron 34: 341–347 [58] Kaiser M, Hilgetag CC (2006) Nonoptimal component placement, but short processing paths due to long-distance projections in neural systems.”
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning (2020, background): “ele [65] is a neural network of C.”
Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence (2008, background): “Many of the additional networks we added filled sub-domains missing from the prior data-set, for example: the dolphin network [41] is an example of an animal social network; the cortical area connectivity map [42] is an example of large-scale neural connectivity.”
Gradients of structure–function tethering across neocortex (2019, neutral): “Neural elements have a pronounced tendency to form local cliques and tightly coupled communities with common functional properties (3); a small proportion of long-distance projections allows signals to be sampled and integrated from these specialized domains (4–6).”
Schizophrenia, neuroimaging and connectomics (2012, background): “The brain does not minimize wiring costs in an absolute sense however, as it possesses long-range inter-regional projections that, though costly, provide topological short-cuts which greatly increase network efficiency (Buzsaki et al., 2004; Kaiser and Hilgetag, 2006).”
Brain Anatomical Network and Intelligence (2009, methodology): “A previous study performed by Kaiser and Hilgetag [53] demonstrated that neural systems are not optimized exclusively for minimal global wiring length, but for a variety of factors including Table 4.”