Welcome to NeuraLib’s documentation!

NeuraLib is a utility toolkit designed for rodent systems neuroscience research. It provides wrappers, parsers, and tools for efficient data handling, analysis, and reproducibility within open-source neuroscience workflows.

Key Features

• Utility tools for rodent neuroscience experiments

• Open-source parsers and wrappers

• Lightweight, modular design for easy integration

• Clean documentation and comprehensive API reference

Resources

• GitHub Repository

• Release Notes

Installation

To install NeuraLib via pip:

pip install neura-library

For more detailed instructions, see Installation.

Getting Started

Atlas

• Atlas
  • BrainRender
    • Region Reconstruction
    • ROI Reconstruction
    • Probe Reconstruction
  • ROI DataFrame
    • RoiClassifierDataFrame
    • RoiNormalizedDataFrame
    • RoiSubregionDataFrame
  • CellAtlas Dataframe
    • Example of loading the dataframe
  • ATLAS Tree
  • Example notebook neuralib.atlas
    • Example of ML offset in coronal slice
    • Example of DV offset in sagittal slice
    • Example of Annotate regions
    • Example of Annotate regions in transverse view
    • Example of max projection

Imaging

• Imaging
  • ScanBox
    • Metadata information
    • Metadata to Json
    • Screen Shot file to tiff
    • ScanBox Imaging View
  • Spikes
    • OASIS
    • Cascade
  • Suite2p
  • WideField
    • FFT View with Bokeh
    • Align with Napari
  • Example notebook neuralib.imaging
    • Load Suite2p results
    • See the Suite2p registered ROIs
    • Calculate dF/F
    • Calculate deconvolution spikes using OASIS method
    • Predict spikes from dF/F using pre-trained model from Cascade

Other

• Other
  • Cellular Segmentation
    • StarDist
    • Cellpose
  • Confocal Scan
    • LSM Data
    • CZI Data
  • Position Tracking
    • DeepLabCut Parser
    • Facemap Parser
  • Animal Locomotion
    • Epoch
    • Position
  • Model
    • Bayesian Position decoding
    • RasterMap
  • Morphology
    • SWC Data
  • Example notebook neuralib.model.rastermap
    • Example of cellular dataset
    • Example of widefield imaging dataset
  • Example notebook neuralib.segmentation
    • Example of Run StarDist model
    • Example of Run Cellpose model

Utility

• Utility
  • General Plotting
  • Image library
    • Array Factory
    • CV2 Labeller
  • IO processing
    • Helper Function
    • Example data
  • Persistence Class
    • Define a Persistence Class
    • Cooperate with PersistenceOptions
    • Dynamically Generated Methods
    • Auto-Increment Field
    • Pickle Format
  • SQL statement builder
  • Utility Tool
    • Google SpreadSheet
    • Slack Notification
  • Example notebook neuralib.plot
    • Plot the data with violin and box with dots
    • See correlation and histogram of two variables
    • Diagonal plot value comparison
    • Dotsplot with colormap
    • Venn Diagram
    • Grid subplots

API Reference

• neuralib core module
• neuralib utility module

Command-Line Tools

neuralib_brainrender

• Visualize brain region data with built-in rendering support

• See examples in the BrainRender

neuralib_brainrender -h

neuralib_widefield

• Widefield imaging CLI analysis

• See examples in the WideField

neuralib_widefield -h

Array Annotation Syntax

Used in documentation to describe array-shaped data structures:

• Array[DType, [*Shape]] where: - DType = data type (e.g., int, float, bool) - Shape = array shape (e.g., [N, T]) - | = denotes a union of shapes or types

Examples:

• Boolean or integer array with shape (N, 3):

  Array[int|bool, [N, 3]]

• Float array with shape (N, 2) or (N, T, 2):

  Array[float, [N, 2] | [N, T, 2]]

Roadmap

• Roadmap
  • Short-Term Goals (Next 1–3 Months)
  • Mid-Term Goals (3–6 Months)
  • Community Involvement

Indices and Tables

• Index

• Module Index

• Search Page