Overview of naplib-python¶
naplib-python is a Python module for analyzing neural-acoustic data such as ECoG or EEG paired with acoustic stimuli.
naplib-python aims to facilitate the easy processing and analysis of neural-acoustic data - i.e. neural recordings collected from sensory systems in response to auditory stimuli. The collection of algorithms and methods in the package can be used with a wide variety of data modalities, enabling the easy transfer of methods and code between researchers in the field of auditory neuroscience.
Highlighted examples to get started¶
The following examples can give you a sense of how to get started with naplib-python for analyzing neural-acoustic data. More examples and tutorial notebooks can be found in the Examples gallery.
- Importing data from BIDS:
Getting started with naplib-python by importing data from BIDS format.
- Preprocessing neural data:
Preprocessing neural data, including electrode selection and frequency band extraction.
- Fitting STRF models:
Fitting and evaluating spectro-temporal receptive field (STRF) models of auditory cortex.
Python is a powerful programming language that allows concise expressions of network algorithms. Python has a vibrant and growing ecosystem of packages that naplib-python uses to provide more features such as numerical linear algebra. In order to use all the capabilities of naplib-python, you will want to know how to write basic programs in Python. Among the many guides to Python, we recommend the Python documentation.