Next Article in Journal
Intersecting Endocrine Pathways in Cardiomyopathy: The Role of Metabolic Burden in Structural Heart Disease
Previous Article in Journal
Gastrointestinal Symptoms in Obesity Therapy: Mechanisms, Epidemiology, and Management Strategies
Previous Article in Special Issue
Comparative Analysis of Davidson and Glyoxal Fixatives on Autofluorescence and Immunolabeling in Medaka (Oryzias latipes) Tissues
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Organization and Community Usage of a Neuron Type Circuitry Knowledge Base of the Hippocampal Formation

Bioengineering Department and Center for Neural Informatics, Structures, & Plasticity, College of Engineering and Computing, George Mason University, Fairfax, VA 22030, USA
*
Author to whom correspondence should be addressed.
Biomedicines 2025, 13(10), 2363; https://doi.org/10.3390/biomedicines13102363
Submission received: 4 September 2025 / Revised: 22 September 2025 / Accepted: 24 September 2025 / Published: 26 September 2025

Abstract

Background/Objectives: Understanding the diverse neuron types within the hippocampal formation is essential for advancing our knowledge of its fundamental roles in learning and memory. Hippocampome.org serves as a comprehensive, evidence-based knowledge repository that integrates morphological, electrophysiological, and molecular features of neurons across the rodent dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex. In addition to these core properties, this open access resource includes detailed information on synaptic connectivity, signal propagation, and plasticity, facilitating sophisticated modeling of hippocampal circuits. A distinguishing feature of Hippocampome.org is its emphasis on quantitative, literature-backed data that can help constrain and validate spiking neural network simulations via an interactive web interface. Methods: To assess and enhance its utility to the neuroscience community, we integrated Google Analytics (GA) into the platform to monitor user behavior, identify high-impact content, and evaluate geographic reach. Results: GA data provided valuable page view metrics, revealing usage trends, frequently accessed neuron properties, and the progressive adoption of new functionalities. Conclusions: These insights directly inform iterative development, particularly in the design of a robust Application Programming Interface (API) to support programmatic access. Ultimately, the integration of GA empowers data-driven optimization of this public resource to better serve the global neuroscience community.
Keywords: hippocampus; neuron classification; circuit connectivity; electrophysiology; morphology; spiking neural networks; Google Analytics hippocampus; neuron classification; circuit connectivity; electrophysiology; morphology; spiking neural networks; Google Analytics

Share and Cite

MDPI and ACS Style

Nadella, K.; Wheeler, D.W.; Ascoli, G.A. Organization and Community Usage of a Neuron Type Circuitry Knowledge Base of the Hippocampal Formation. Biomedicines 2025, 13, 2363. https://doi.org/10.3390/biomedicines13102363

AMA Style

Nadella K, Wheeler DW, Ascoli GA. Organization and Community Usage of a Neuron Type Circuitry Knowledge Base of the Hippocampal Formation. Biomedicines. 2025; 13(10):2363. https://doi.org/10.3390/biomedicines13102363

Chicago/Turabian Style

Nadella, Kasturi, Diek W. Wheeler, and Giorgio A. Ascoli. 2025. "Organization and Community Usage of a Neuron Type Circuitry Knowledge Base of the Hippocampal Formation" Biomedicines 13, no. 10: 2363. https://doi.org/10.3390/biomedicines13102363

APA Style

Nadella, K., Wheeler, D. W., & Ascoli, G. A. (2025). Organization and Community Usage of a Neuron Type Circuitry Knowledge Base of the Hippocampal Formation. Biomedicines, 13(10), 2363. https://doi.org/10.3390/biomedicines13102363

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop