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Tools and services for multilevel validation of models

EBRAINS Provides available tools for analysis, statistics and model validation across brain scales, datasets and species.

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The Python library Electrophysiology Analysis Toolkit (Elephant) provides tools for analysing neuronal activity data, such as spike trains, local field potentials and intracellular data. In addition to providing a platform for sharing analysis codes from different laboratories, Elephant provides a consistent and homogeneous framework for data analysis built on a modular foundation. The underlying data model is the Neo library. This framework easily captures a wide range of neuronal data types and methods, including dozens of file formats and network simulation tools. A common data description, as the Neo library provides, is essential for developing interoperable analysis workflows.

Modelling and simulationData analysis and visualisationValidation and inference

Frites - Framework for information theoretical analysis of electrophysiological data and statistics

Frites allows the characterisation of task-related cognitive brain networks. Neural correlates of cognitive functions can be extracted both at the single brain area (or channel) and network level. The toolbox includes time-resolved directed (e.g., Granger causality) and undirected (e.g., Mutual Information) Functional Connectivity metrics. In addition, it includes cluster-based and permutation-based statistical methods for single-subject and group-level inference.

Validation and inference

Collaborative Brain Wave Analysis Pipeline

The pipeline ingests data from multiple measurement types of spatially organized neuronal activity, such as ECoG or calcium imaging recordings. The pipeline returns statistical measures to quantify the dynamic wave-like activity patterns found in the data. Individual parts of the snakemake-based pipeline are fully configurable. The composition of Cobrawap elements can be adapted to various datasets through by means of a modular design of self-contained sequential stages composed of multiple atomic blocks.

Validation and inference

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