Abstract
Synchronous activities among neurons in the brain generate emergent network oscillations such as the hippocampal Sharp-wave ripples (SPWRs) that facilitate information processing during memory formation. However, how neurons and circuits are functionally organized to generate oscillations remains unresolved. Biophysical models of neuronal networks can shed light on how thousands of neurons interact in intricate circuits to generate such emergent SPWR network events. Here we developed a large-scale biophysically realistic neural network model of CA1 hippocampus with functionally organized circuit modules containing distinct types of neurons. Model simulations reproduced synaptic, cellular and network aspects of physiological SPWRs. The model provided insights into the role of neuronal types and their microcircuit motifs in generating SPWRs in the CA1 region. The model also suggests experimentally testable predictions including the role of specific neuron types in the genesis of hippocampal SPWRs.
Original language | English |
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Pages (from-to) | 1784-1788 |
Number of pages | 5 |
Journal | IEEE Transactions on Circuits and Systems II: Express Briefs |
Volume | 70 |
Issue number | 5 |
DOIs | |
Publication status | Published - May 2023 |
Externally published | Yes |
Event | IEEE International Symposium on Circuits and Systems 2023 - Monterey, United States of America Duration: 21 May 2023 → 25 May 2023 https://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=10124122&punumber=8920 |
Keywords
- Biophysical neuron model
- hippocampus
- local field potential
- neural network