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Dynamic Computational Model of the Human Spinal Cord Connectome
Jeffrey E Arle1, Nicolae Iftimia2, Jay L Shils3
1Department of Neurosurgery, Beth Israel Deaconess Medical Center, Boston, MA 02215; Department of Neurosurgery, Harvard Medical School, Boston, MA 02115; and Department of Neurosurgery, Mt. Auburn Hospital, Cambridge, MA 02138, U.S.A. jarle@bidmc.harvard.edu.
Neural Computation
|December 22, 2018
Summary
Researchers created a computational model of the human spinal cord connectome using literature data. This model maps neural circuitry and neuron counts, serving as a foundation for future spinal cord research and therapeutic development.
Area of Science:
- Neuroscience
- Computational Biology
- Anatomy
Background:
- Limited detailed connectivity maps exist for the human spinal cord.
- Understanding spinal cord circuitry is crucial for neurological research and treatment.
Purpose of the Study:
- To construct a draft connectivity map of the human spinal cord connectome.
- To develop an initial computational model of the human spinal cord.
- To provide a template for future research and hypothesis testing.
Main Methods:
- Comprehensive literature review for cell types, connectivity, and connection strength.
- Utilized cadaveric spinal cord measurements, histology, and cytoarchitectural data.
- Employed neural circuitry simulation software for model development.
Main Results:
- Developed a computational model encompassing all ten Rexed laminae and 31 spinal cord segments.
- Included intralaminar, interlaminar, intersegmental, and brain connections.
- Estimated neuron counts for various cell types within each lamina.
Conclusions:
- The human spinal cord connectome model reveals highly interconnected complex networks.
- The model serves as a foundational tool for developing and testing hypotheses in spinal cord research.
- Future work will expand the model to include more segments and applications, such as spinal cord stimulation for analgesia.
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