Summary
Quantification of neuronal morphology is essential for understanding neuronal connectivity and many software tools have been developed for neuronal reconstruction and morphometry. However, such tools remain domain-specific, tethered to specific imaging modalities, and were not designed to accommodate the rich metadata generated by recent whole-brain cellular connectomics. To address these limitations, we created SNT: a unifying framework for neuronal morphometry and analysis of single-cell connectomics for the widely used Fiji and ImageJ platforms.
We demonstrate that SNT can be used to tackle important problems in contemporary neuroscience, validate its utility, and illustrate how it establishes an end-to-end platform for tracing, proof-editing, visualization, quantification, and modeling of neuroanatomy.
With an open and scriptable architecture, a large user base, and thorough community-based documentation, SNT is an accessible and scalable resource for the broad neuroscience community that synergizes well with existing software.
Competing Interest Statement
The authors have declared no competing interest.
Glosssary
- GRNs
- Artificial gene regulatory networks (GRNs) are mathematical algorithms inspired by mechanisms of biological gene regulation. GRNs can be used to model or solve problems with a strong dynamic or stochastic component
- Mesh
- A polygon mesh defines the shape of a three-dimensional polyhedral object. In neuronal anatomy, meshes define neuropil annotations, typically compartments of a reference brain atlas (e.g., the hippocampal formation in mammals, or mushroom bodies in insects)
- Multi-dimensional image
- An image with more than 3 dimensions (3D). Examples include fluorescent images associated with multiple fluorophores (multi-channel) and images with a time-dimension (time-lapse videos). A 3D multi-channel timelapse has 5 dimensions
- Neurite
- Same as neuronal process. Either an axon or a dendrite
- Path
- Can be defined as a sequence of branches, starting from soma or a branch point until a termination. In manual and assisted (semi-automated) tracing, neuronal arbors are traced using paths, not branches. Fitting algorithms that take into account voxel intensities can be used to refine the center-line coordinates of a path, typically to obtain more accurate curvatures. Fitting procedures can also be used to estimate the volume of the neurite(s) associated with a path
- (Neuronal) morphometry
- Quantification of neuronal morphology
- Neuropil
- Any area in the nervous system. The cellular tissue around neuronal processes
- Out-of-core
- Software with out-of-core capabilities is able to process data that is too large to fit into a computer’s main memory
- Reconstruction
- See Tracing
- ROI
- Region of Interest. Define specific parts of an image to be processed in image processing routines
- Skeleton
- A thinned version of a digitize shape (such as a neuronal reconstruction) or of a binary image
- Tracing
- A digital reconstruction of a neuron or neurite. The term predates computational neuroscience and reflects the manual ‘tracing’ on paper performed with camera lucida devices by early neuroanatomists
- Volume rendering
- A visualization technique for displaying image volumes (3D images) directly as 3D objects