دورية أكاديمية
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A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

التفاصيل البيبلوغرافية
العنوان: A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.
المؤلفون: Sutton NM; Bioengineering Department, George Mason University, Fairfax, VA 22030, USA., Gutiérrez-Guzmán BE; Bioengineering Department, George Mason University, Fairfax, VA 22030, USA., Dannenberg H; Bioengineering Department, George Mason University, Fairfax, VA 22030, USA.; Interdisciplinary Program in Neuroscience, George Mason University, Fairfax, VA 22030, USA., Ascoli GA; Bioengineering Department, George Mason University, Fairfax, VA 22030, USA.; Interdisciplinary Program in Neuroscience, George Mason University, Fairfax, VA 22030, USA.
المصدر: International journal of molecular sciences [Int J Mol Sci] 2024 May 31; Vol. 25 (11). Date of Electronic Publication: 2024 May 31.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067 (Electronic) Linking ISSN: 14220067 NLM ISO Abbreviation: Int J Mol Sci Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI, [2000-
مواضيع طبية MeSH: Models, Neurological* , Grid Cells*/physiology , Synapses*/physiology , Entorhinal Cortex*/physiology , Entorhinal Cortex*/cytology , Action Potentials*/physiology, Animals ; Computer Simulation ; Neurons/physiology ; Neurons/cytology ; Hippocampus/physiology ; Hippocampus/cytology ; Nerve Net/physiology ; Nerve Net/cytology ; Neural Networks, Computer
مستخلص: Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.
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معلومات مُعتمدة: R00 NS116129 United States NS NINDS NIH HHS; R01 NS039600 United States NS NINDS NIH HHS; R01NS39600 United States NH NIH HHS; R00NS116129 United States NH NIH HHS
فهرسة مساهمة: Keywords: computational model; entorhinal cortex; hippocampus; mice; neural network; neuron types; spatial navigation
تواريخ الأحداث: Date Created: 20240619 Date Completed: 20240619 Latest Revision: 20240701
رمز التحديث: 20240701
مُعرف محوري في PubMed: PMC11173171
DOI: 10.3390/ijms25116059
PMID: 38892248
قاعدة البيانات: MEDLINE
الوصف
تدمد:1422-0067
DOI:10.3390/ijms25116059