Researcher ORCID Identifier


Graduation Year


Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts



Reader 1

Sarah Marzen

Reader 2

Adam Landsberg

Rights Information

© 2021 Callie A Morken


This thesis examined the significance of criticality in neural data by creating a model, like those found in thermodynamics and statistical mechanics, to explore how common and easy it is to find criticality in neural systems. The neural systems were modeled in terms of abstract heat, rather than literal heat. By introducing abstract temperature, we moved away from neural data to abstract data. We computed heat capacity as a function of abstract temperature which peaks at temperature T=1 when criticality occurs in neural data. A python computational program modeled neurons under randomly generated conditions to create several neuron distributions. No resulting distribution peaked at temperature T=1, meaning no signs of criticality were observed. The lack of observed criticality suggests that criticality does not commonly occur in neural data, but when it does occur, it is significant.

This thesis is restricted to the Claremont Colleges current faculty, students, and staff.