ArticleFrontiers in computational neuroscience2020
Neuronal Degeneration Impairs Rhythms Between Connected Microcircuits.
Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 18 citations in OpenAlex.
- Individualized mouse brain network models produce asymmetric patterns of functional connectivity after simulated traumatic injury.Network neuroscience (Cambridge, Mass.) · 2025Article
- Article
- Hippocampome.org v2.0: a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits.bioRxiv : the preprint server for biology · 2024Article
- Spike Timing-Dependent Plasticity with Enhanced Long-Term Depression Leads to an Increase of Statistical Complexity.Entropy (Basel, Switzerland) · 2022Article
- A multilayer network model of neuron-astrocyte populations in vitro reveals mGluRNetwork neuroscience (Cambridge, Mass.) · 2022Article
- Plasticity impairment alters community structure but permits successful pattern separation in a hippocampal network model.Frontiers in cellular neuroscience · 2022Article
- NMDA Receptor Alterations After Mild Traumatic Brain Injury Induce Deficits in Memory Acquisition and Recall.Neural computation · 2021Article
- High-Frequency Head Impact Disrupts Hippocampal Neural Ensemble Dynamics.Frontiers in cellular neuroscience · 2021Article
- Neurodegeneration exposes firing rate dependent effects on oscillation dynamics in computational neural networks.PloS one · 2020Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Synchronization of neural activity across brain regions is critical to processes that include perception, learning, and memory. After traumatic brain injury (TBI), neuronal degeneration is one possible effect and can alter communication between neural circuits. Consequently, synchronization between neurons may change and can contribute to both lasting changes in functional brain networks and cognitive impairment in patients. However, fundamental principles relating exactly how TBI at the cellular scale affects synchronization of mesoscale circuits are not well understood. In this work, we use computational networks of Izhikevich integrate-and-fire neurons to study synchronized, oscillatory activity between clusters of neurons, which also adapt according to spike-timing-dependent plasticity (STDP). We study how the connections within and between these neuronal clusters change as unidirectional connections form between the two neuronal populations. In turn, we examine how neuronal deletion, intended to mimic the temporary or permanent loss of neurons in the mesoscale circuit, affects these dynamics. We determine synchronization of two neuronal circuits requires very modest connectivity between these populations; approximately 10% of neurons projecting from one circuit to another circuit will result in high synchronization. In addition, we find that synchronization level inversely affects the strength of connection between neuronal microcircuits - moderately synchronized microcircuits develop stronger intercluster connections than do highly synchronized circuits. Finally, we find that highly synchronized circuits are largely protected against the effects of neuronal deletion but may display changes in frequency properties across circuits with targeted neuronal loss. Together, our results suggest that strongly and weakly connected regions differ in their inherent resilience to damage and may serve different roles in a larger network.
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