ArticleFrontiers in network physiology2023
Neuron arbor geometry is sensitive to the limited-range fractal properties of their dendrites.
Article in Frontiers in network physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 8 citations in OpenAlex.
- Quantifying Structural Changes in Cultured Neurons Using Fractal Analysis.Neuroinformatics · 2026Article
- Fractal Dimension in Healthy Hippocampi and Hippocampi With Mesial Temporal Sclerosis: An Observational Study.Cureus · 2025Article
- Study of prediction model for high-grade meningioma using fractal geometry combined with radiological features.Journal of neuro-oncology · 2025Article
- Evolution of Retinal Neuron Fractality When Interfacing with Carbon Nanotube Electrodes.Bioengineering (Basel, Switzerland) · 2024Article
- Fractal Electronics for Stimulating and Sensing Neural Networks: Enhanced Electrical, Optical, and Cell Interaction Properties.Advances in neurobiology · 2024Article
- Fractal Resonance: Can Fractal Geometry Be Used to Optimize the Connectivity of Neurons to Artificial Implants?Advances in neurobiology · 2024Article
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
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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.
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