Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery

6 Nov 2015 • Gal Mishne • Ronen Talmon • Ron Meir • Jackie Schiller • Uri Dubin • Ronald R. Coifman

In the wake of recent advances in experimental methods in neuroscience, the ability to record in-vivo neuronal activity from awake animals has become feasible. The availability of such rich and detailed physiological measurements calls for the development of advanced data analysis tools, as commonly used techniques do not suffice to capture the spatio-temporal network complexity... (read more)

PDF Abstract

Code

Add Remove Mark official

No code implementations yet. Submit your code now

Tasks

Add Remove

Results from the Paper

Add Remove

Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

METHOD	TYPE
🤖 No Methods Found	Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet

Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Add Remove

Methods used in the Paper

Add Remove

Edit Social Preview

Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery Edit social preview

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Datasets Edit

Results from the Paper Edit Add Remove

Methods used in the Paper Edit Add Remove

Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Add Remove

Methods used in the Paper

Add Remove