A Biophysically Realistic Computational Model of Hippocampal Electrical Stimulation
Maeva Andriantsoamberomanga*1,2, Nicolas P. Rougier1,2, Fabien Wagner1, Amélie Aussel1,2
1Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000 Bordeaux, France 2 Univ. Bordeaux, CNRS, Bordeaux INP, INRIA, LaBRI, UMR 5800, F-33400 Talence, France
*Email: maeva.andriantsoamberomanga@inria.fr
Introduction
Memory process emerges from the communication between several brain areas including the hippocampal formation. Correct encoding and retrieval of memory relies on coupling of theta (4-8 Hz) and gamma (30-120Hz) oscillations, with disruptions of theta-gamma coupling observed in memory disorders [1]. In recent years, efforts have been made to investigate the impact of electrical stimulation of the hippocampal formation on memory performance. However, discrepancies in the results highlight the complexity of the underlying mechanisms [2-4], hence the need of a biophysically realistic computational model to better understand the effects of electrical stimulation on neuronal oscillations and to choose the best stimulation parameters.
Methods
We implemented tools to build a simple model of hippocampal extracellular electrical stimulation. The hippocampal formation was constrained to a coronal slice subdivided into different regions (entorhinal cortex, subiculum, CA1 and CA3 areas and dentate gyrus). We then developed an intrinsic coordinate system of the hippocampal slice in order to more accurately place and connect our neurons. Each region was populated with three different neuron types, required to elicit theta-nested gamma oscillations. Each neuron was implemented as a conductance-based model [5] with multiple compartments representing realistic neuronal morphologies. Finally, the axonal projections between different regions were modeled explicitly for increased accuracy.
Results
We studied the response of single neurons as well as interconnected neurons to extracellular stimulation. We have observed that the stimulation current needed to elicit an action potential in pyramidal cells varied greatly depending on the position of the electrode relative to the neuron. Furthermore, the propagation delay and decay differed when the axonal projections were modeled explicitly or implicitly. Finally, we focused on the internal dynamics of the CA1 area. Upon giving an oscillatory input of theta frequency (6 Hz) to the model, we observed patterns of spikes occurring at a theta frequency, with neurons firing at a gamma frequency within each pattern.
Discussion
Our first aim was to test the feasibility of an anatomically realistic model with explicit axonal projections and tractable computation times. Therefore, we made some simplifications in terms of number of neurons and connectivity between them. We have successfully managed to build a model which exhibits both theta and gamma oscillations in the CA1 area of the hippocampus. We have also set up the tools that will be needed to extend the CA1 network to the whole hippocampal formation. Future work will focus on extending this preliminary model to both the CA3 and CA1 areas as a first step, and to investigate the effects of extracellular stimulation on theta-gamma oscillations.
None
1. Kitchigina, V. F. (2018). Alterations of Coherent Theta and Gamma Network Oscillations as an Early Biomarker of Temporal Lobe Epilepsy and Alzheimer's Disease. Frontiers in Integrative Neuroscience, 12. https://www.frontiersin.org/article/10.3389/fnint.2018.00036 2. https://doi.org/10.1056/NEJMoa1107212 3. https://doi.org/10.1016/j.neuron.2016.10.062 4. https://doi.org/10.7554/eLife.29515 5. Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of Physiology, 117(4), 500-544.
