Prediction of neural activity in connectome-constrained recurrent networks
In this talk, I will explain a theory of connectome-constrained neural networks in which a “student” networks is trained to reproduce the activity of a ground-truth “teacher”, representing a neural system for which a connectome is available. Unlike standard paradigms with unconstrained connectivity, here both networks have the same connectivity but they have different biophysical parameters, reflecting uncertainty in neuronal and synaptic properties. We find that the connectome is often insufficient to constrain the dynamics of networks that perform a specific task, illustrating the difficulty of inferring function from connectivity alone. However, recordings from a small subset of neurons can remove this degeneracy, producing dynamics in the student that agree with the teacher. Our theory can prioritize which neurons to record from to most efficiently unmeasured network activity. The analysis shows that the solution spaces of connectome-constrained and unconstrained models are qualitatively different, and provides a framework to determine when such models yield consistent dynamics. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2024-04-03. Recording duration: 00:42:28.
A macaque connectome for simulating large-scale network dynamics in The VirtualBrain
TheVirtualBrain (TVB; thevirtualbrain.org) is a software platform for simulating whole-brain network dynamics. TVB models link biophysical parameters at the cellular level with systems-level functional neuroimaging signals. Data available from animal models can provide vital constraints for the linkage across spatial and temporal scales. I will describe the construction of a macaque cortical connectome as an initial step towards a comprehensive multi-scale macaque TVB model. I will also describe our process of validating the connectome and show an example simulation of macaque resting-state dynamics using TVB. This connectome opens the opportunity for the addition of other available data from the macaque, such as electrophysiological recordings and receptor distributions, to inform multi-scale models of brain dynamics. Future work will include extensions to neurological conditions and other nonhuman primate species.