Modeling Acquisition and Extinction of Conditioned Fear in LA Neurons using Learning Algorithm

We develop a biophysical network model of the lateral amygdala (LA) neurons to investigate the underlying mechanisms for acquisition and extinction of conditioned fear. A Hodgkin-Huxley formalism is used to model two main types of LA neurons: pyramidal cells and GABAergic interneurons, which are connected based on biological evidence. Hebbian type synaptic plasticity is implemented into the excitatory NMDA/AMPA receptor mediated synapses to model the learning process. We constrained our models on both the single cell and the network levels by matching the experimental recording. The network model is used to simulate the classical auditory fear conditioning experiment and the results show the model can replicate the neuronal behaviors well during three training process. Our major finding is that expression of conditioned fear and extinction in LA is controlled by the balance between pyramidal cell and interneuron activations. Extinction does not erase the fear memory, but instead further activates the local interneurons which inhibit the responses of pyramidal cells.