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PreprintCC BY 4.0HAL

A reduced multicompartment network model of CA1 theta–gamma oscillations under extracellular stimulation

Abstract

Deep brain stimulation has demonstrated its therapeutic potential in modulating pathological oscillations associated with Parkinson's disease and epilepsy. However, its efficacy in treating disrupted theta-gamma phase-amplitude coupling seen in memory-related disorders, such as Alzheimer's disease, remains poorly understood. While recent studies have targeted the entorhinal-hippocampal circuit, results remain inconsistent. This discrepancy stems from a lack of mechanistic understanding regarding how stimulation protocols affect this circuit. In this work, we present a reduced multicompartment model of the hippocampal CA1 area that reproduces theta-nested gamma oscillations characteristic of healthy neural activity during memory performance. The model comprises pyramidal, basket and OLM cells with simplified morphologies. We also incorporated CA3-to-CA1 axonal projections, providing a foundational framework for studying how stimulation-induced recruitment of afferent pathways modulates CA1 dynamics. By balancing computational efficiency with anatomical accuracy, our model enables systematic investigation of the effects of electrode placement and orientation, as well as stimulation amplitude and frequency on CA1 neural activity. We demonstrate that the excitatory response in CA1 is primarily driven by the recruitment of Schaffer collateral projections. Overall, this work provides a computationally efficient template for exploring diverse stimulation configurations and could be expanded for developing neuromodulatory strategies to restore physiological network dynamics.

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BibTeX
@misc{andriantsoamberomanga2026reduced,
  title = {{A reduced multicompartment network model of CA1 theta–gamma oscillations under extracellular stimulation}},
  author = {Maeva Andriantsoamberomanga and Nicolas P Rougier and Fabien Bertrand Paul Wagner and Amélie Aussel},
  howpublished = {HAL},
  year = {2026},
  month = jun,
  doi = {10.64898/2026.06.22.733913},
  url = {https://hal.science/hal-05854340v1},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - A reduced multicompartment network model of CA1 theta–gamma oscillations under extracellular stimulation
AU  - Maeva Andriantsoamberomanga
AU  - Nicolas P Rougier
AU  - Fabien Bertrand Paul Wagner
AU  - Amélie Aussel
PY  - 2026
DA  - 2026/06/28
PB  - HAL
DO  - 10.64898/2026.06.22.733913
UR  - https://hal.science/hal-05854340v1
AB  - Deep brain stimulation has demonstrated its therapeutic potential in modulating pathological oscillations associated with Parkinson's disease and epilepsy. However, its efficacy in treating disrupted theta-gamma phase-amplitude coupling seen in memory-related disorders, such as Alzheimer's disease, remains poorly understood. While recent studies have targeted the entorhinal-hippocampal circuit, results remain inconsistent. This discrepancy stems from a lack of mechanistic understanding regarding how stimulation protocols affect this circuit. In this work, we present a reduced multicompartment model of the hippocampal CA1 area that reproduces theta-nested gamma oscillations characteristic of healthy neural activity during memory performance. The model comprises pyramidal, basket and OLM cells with simplified morphologies. We also incorporated CA3-to-CA1 axonal projections, providing a foundational framework for studying how stimulation-induced recruitment of afferent pathways modulates CA1 dynamics. By balancing computational efficiency with anatomical accuracy, our model enables systematic investigation of the effects of electrode placement and orientation, as well as stimulation amplitude and frequency on CA1 neural activity. We demonstrate that the excitatory response in CA1 is primarily driven by the recruitment of Schaffer collateral projections. Overall, this work provides a computationally efficient template for exploring diverse stimulation configurations and could be expanded for developing neuromodulatory strategies to restore physiological network dynamics.
ER  -