Generative modeling of the enteric nervous system employing point pattern analysis and graph construction
We describe a generative network model of the architecture of the enteric nervous system (ENS) in the colon employing data from images of human and mouse tissue samples obtained through confocal microscopy. Our models combine spatial point pattern analysis with graph generation to characterize the spatial and topological properties of the ganglia (clusters of neurons and glial cells), the inter-ganglionic connections, and the neuronal organization within the ganglia. We employ a hybrid hardcore-Strauss process for spatial patterns and a planar random graph generation for constructing the spatially embedded network. We show that our generative model may be helpful in both basic and translational studies, and it is sufficiently expressive to model the ENS architecture of individuals who vary in age and health status. Increased understanding of the ENS connectome will enable the use of neuromodulation strategies in treatment and clarify anatomic diagnostic criteria for people with bowel motility disorders.
Code (0)
등록된 구현이 없습니다.
Tasks
Diagnosticgraph constructionGraph GenerationSimilar Papers 제목 키워드 기반
Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images
Studies recently accomplished on the Enteric Nervous System have shown that chronic degenerative diseases affect the Enteric Glial Cells (EGC) and, thus, the development of recognition methods able to identify whether or…
Representation LearningTransfer LearningENSeg: A Novel Dataset and Method for the Segmentation of Enteric Neuron Cells on Microscopy Images
The Enteric Nervous System (ENS) is a dynamic field of study where researchers devise sophisticated methodologies to comprehend the impact of chronic degenerative diseases on Enteric Neuron Cells (ENCs). These investigat…
Instance SegmentationMedical Image SegmentationSegmentationSemantic SegmentationNeurological disorders leading to mechanical dysfunction of the esophagus: an emergent behavior of a neuromechanical dynamical system
An understanding how neurological disorders lead to mechanical dysfunction of the esophagus requires knowledge of the neural circuit of the enteric nervous system. Historically, this has been elusive. Here, we present an…
Discrete Modeling of Multi-Transmitter Neural Networks with Neuron Competition
We propose a novel discrete model of central pattern generators (CPG), neuronal ensembles generating rhythmic activity. The model emphasizes the role of nonsynaptic interactions and the diversity of electrical properties…
DiversityModeling the Nervous System as An Open Quantum System
We propose a neural network model of multi-neuron interacting system that simulates neurons to interact each other through the surroundings of neuronal cell bodies. We physically model the neuronal cell surroundings, inc…