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Found 2 papers, 1 papers with code
Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience
Thus, we offer a flexible approach to remove inter-experimental variability and integrate datasets across experiments in systems neuroscience.
Using persistent homology to reveal hidden information in neural data
We propose a method, based on persistent homology, to uncover topological properties of a priori unknown covariates of neuron activity.
Neurons and Cognition Algebraic Topology
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