21 citations · 22 across the 4 of their papers we have counts for
4 papers · 1 filter
Sequence generation in inhibition-dominated neural networks
Caitlyn Parmelee, Juliana Londono Alvarez, Carina Curto +1
This is a brief overview of results from [arXiv:2107.10244, ref 11], on network architectures that produce sequential dynamics in a special family of inhibition-dominated neural ne…
Core motifs predict dynamic attractors in combinatorial threshold-linear networks
Caitlyn Parmelee, Samantha Moore, Katherine Morrison +1
Combinatorial threshold-linear networks (CTLNs) are a special class of inhibition-dominated TLNs defined from directed graphs. Like more general TLNs, they display a wide variety o…
Sequential attractors in combinatorial threshold-linear networks
Caitlyn Parmelee, Juliana Londono Alvarez, Carina Curto +1
Sequences of neural activity arise in many brain areas, including cortex, hippocampus, and central pattern generator circuits that underlie rhythmic behaviors like locomotion. Whil…
Applications of Discrete Mathematics for Understanding Dynamics of Synapses and Networks in Neuroscience
Caitlyn M. Parmelee
Mathematical modeling has broad applications in neuroscience whether modeling the dynamics of a single synapse or an entire network of neurons. In Part I, we model vesicle replenis…