Article
Version 1
Preserved in Portico This version is not peer-reviewed
Visualizing Complexity and Emergence: Insights from the Hippocampus Representation Model
Version 1
: Received: 7 May 2024 / Approved: 8 May 2024 / Online: 9 May 2024 (12:04:58 CEST)
How to cite: Montgomery, R. Visualizing Complexity and Emergence: Insights from the Hippocampus Representation Model. Preprints 2024, 2024050523. https://doi.org/10.20944/preprints202405.0523.v1 Montgomery, R. Visualizing Complexity and Emergence: Insights from the Hippocampus Representation Model. Preprints 2024, 2024050523. https://doi.org/10.20944/preprints202405.0523.v1
Abstract
This article explores the intricate dynamics of complexity and emergence through the lens of a graphical model representing hippocampal functions. Utilizing a series of overlapping curves that intersect at varying degrees and frequencies, we create a visual metaphor for the sophisticated processes to store information observed in the hippocampus. This model not only depicts the spatial and frequency-related interactions of these curves but also illustrates the emergent patterns that arise from these interactions. These patterns exemplify the principles of complexity and emergence, where the collective behavior of simple elements results in intricate and unexpected outcomes. This graphical representation serves as a bridge between the abstract mathematical concepts of complexity theory and the tangible biological processes observed in neuroscience. By drawing parallels to the hippocampus, known for its role in memory formation and spatial navigation, the article sheds light on how complex systems, such as neural networks, exhibit properties that are more than just the sum of their parts. The model thus offers a unique perspective on understanding complex systems, not only in neuroscience but in broader scientific inquiries where complexity and emergent phenomena are pivotal.
Keywords
complexity, emergence, hippocampus, memory, graphical representation, neuroscience
Subject
Biology and Life Sciences, Neuroscience and Neurology
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Comments (0)
We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.
Leave a public commentSend a private comment to the author(s)
* All users must log in before leaving a comment
