Using an animal learning model of the hippocampus to simulate human fMRI data

Recent human fMRI studies have shown that the hippocampal region is essential for probabilistic category learning, memory formation-retrieval and context based performance. We present an artificial neural network model that can qualitatively simulate the BOLD signal for these tasks. The model offers ideas on the functional architecture and the relationship between the hippocampus and other brain structures. We also show that symptoms of neurobiological diseases like Parkinson´s disease (PD) and Schizophrenia can be simulated and studied using the model.