Neuron arbor geometry is sensitive to the limited-range fractal properties of their dendrites
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Date
2023-01-25
Authors
Rowland, Conor
Smith, Julian H.
Moslehi, Saba
Harland, Bruce
Dalrymple-Alford, John
Taylor, Richard P.
Journal Title
Journal ISSN
Volume Title
Publisher
Frontiers in Network Physiology
Abstract
Fractal geometry is a well-known model for capturing the multi-scaled complexity of
many natural objects. By analyzing three-dimensional images of pyramidal neurons
in the rat hippocampus CA1 region, we examine how the individual dendrites within
the neuron arbor relate to the fractal properties of the arbor as a whole. We find that
the dendrites reveal unexpectedly mild fractal characteristics quantified by a low
fractal dimension. This is confirmed by comparing two fractal methods—a traditional
“coastline” method and a novel method that examines the dendrites’ tortuosity
across multiple scales. This comparison also allows the dendrites’ fractal geometry to
be related to more traditional measures of their complexity. In contrast, the arbor’s
fractal characteristics are quantified by a much higher fractal dimension. Employing
distorted neuron models that modify the dendritic patterns, deviations from natural
dendrite behavior are found to induce large systematic changes in the arbor’s
structure and its connectivity within a neural network. We discuss how this
sensitivity to dendrite fractality impacts neuron functionality in terms of balancing
neuron connectivity with its operating costs. We also consider implications for
applications focusing on deviations from natural behavior, including pathological
conditions and investigations of neuron interactions with artificial surfaces in human
implants.
Description
12 pages
Keywords
Neurons, Fractal analysis, Fractal dimension (D), Tortuosity, Connectivity, Neuromorphology, Confocal microscopy, Hippocampal CA1
Citation
Rowland C, Smith JH, Moslehi S, Harland B, Dalrymple-Alford J and Taylor RP (2023), Neuron arbor geometry is sensitive to the limited-range fractal properties of their dendrites. Front. Netw. Physiol. 3:1072815. doi: 10.3389/fnetp.2023.1072815