Generic and comparative models of the hippocampus
The hippocampus is a subcortical brain region that likely emerged in the common ancestors of mammals and amphibians. Its internal structure is very well conserved within mammals but differs considerably between different taxa. Its functional role in spatial navigation, however, seems to be important in all lineages. The hippocampus is therefore a prime candidate to study the relationship between the structure and function of large-scale networks and to differentiate between generic and species-specific properties of a network. But how can computational neuroscience help to uncover the general principles of nervous system organization and its species-specific implementations? In this talk, I will outline different approaches to use computational models for comparative neuroscience.
One of them will be a recently developed modeling paradigm, called Parametric Anatomical Modeling (PAM). PAM facilitates the translation of large-scale anatomical 3d data into a formal description of neural networks with connection patterns and connection lengths derived from anatomical features of the biological network (Pyka and Cheng 2014). Using a 3d model of the rat hippocampus and entorhinal cortex, we reconstructed the information flow within the hippocampal loop, that is the timing and temporal order, in which spiking activity propagates through the network. The simulations provide first insights of how spatial relations between different brain areas affect functional and other structural properties of the network. Additionally, our simulations of information flow help to constrain the space of more abstract computational models of the hippocampus.
The talk is open to the public. Guests are cordially invited!