| Title: | Using Eigenvalues to Classify Neuronal Networks |
| Speaker: | Paulina Volosov Assistant Professor of Mathematics Mathematics Hillsdale College Hillsdale, MI |
| Abstract: | When neuroscientists reconstruct brain networks, they often do not know how to index the neurons in order reveal the underlying structure of the connections between neurons. How can a mathematician help in this case? It turns out that by studying the eigenvalues of the connectivity matrix, we can in fact derive a metric that classifies small-world networks using information from the spectrum. This is yet one more case in which we see the beauty and usefulness of eigenvalues. |
| Location: | Palenske 227 |
| Date: | 10/20/2022 |
| Time: | 3:30 PM |
@abstract{MCS:Colloquium:PaulinaVolosov:2022:10:20,
author = "{Paulina Volosov}",
title = "{Using Eigenvalues to Classify Neuronal Networks}",
address = "{Albion College Mathematics and Computer Science Colloquium}",
month = "{20 October}",
year = "{2022}"
}