5 papers
The refractory period matters: unifying mechanisms of macroscopic brain waves
Corey Weistuch, Lilianne R. Mujica-Parodi, Ken Dill
The relationship between complex, brain oscillations and the dynamics of individual neurons is poorly understood. Here we utilize Maximum Caliber, a dynamical inference principle,…
Ground-truth resting-state signal provides data-driven estimation and correction for scanner distortion of fMRI time-series dynamics
Rajat Kumar, Liang Tan, Alan Kriegstein +4
The fMRI community has made great strides in decoupling neuronal activity from other physiologically induced T2* changes, using sensors that provide a ground-truth with respect to…
Inferring a network from dynamical signals at its nodes
Corey Weistuch, Luca Agozzino, Lilianne R. Mujica-Parodi +1
We give an approximate solution to the difficult inverse problem of inferring the topology of an unknown network from given time-dependent signals at the nodes. For example, we mea…
Unique Scales Preserve Self-Similar Integrate-and-Fire Functionality of Neuronal Clusters
Anar Amgalan, Patrick Taylor, Lilianne R. Mujica-Parodi +1
Identifying the brain's neuronal cluster size to be presented as nodes in a network computation is critical to both neuroscience and artificial intelligence, as these define the co…
Making Sense of Computational Psychiatry
LR Mujica-Parodi, HH Strey
In psychiatry, we often speak of constructing "models." Here we try to make sense of what such a claim might mean, starting with the most fundamental question: "What is (and isn't)…