Detecting neural assemblies in calcium imaging data.

ABSTRACT:

Background

Activity in populations of neurons often takes the form of assemblies, where specific groups of neurons tend to activate at the same time. However, in calcium imaging data, reliably identifying these assemblies is a challenging problem, and the relative performance of different assembly-detection algorithms is unknown.

Results

To test the performance of several recently proposed assembly-detection algorithms, we first generated large surrogate datasets of calcium imaging data with predefined assembly structures and characterised the ability of the algorithms to recover known assemblies. The algorithms we tested are based on independent component analysis (ICA), principal component analysis (Promax), similarity analysis (CORE), singular value decomposition (SVD), g

SUBMITTER: Molter J 

PROVIDER: S-EPMC6262979 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature