A modular and adaptable analysis pipeline to compare slow cerebral rhythms across heterogeneous datasets.

ABSTRACT: Neuroscience is moving toward a more integrative discipline where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow-wave activity (<1 Hz), which occurs during unconscious brain states like sleep and general anesthesia and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications.

SUBMITTER: Gutzen R 

PROVIDER: S-EPMC10831958 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature