Input and feed-back contributions to neural manifolds

• Applicant: Professor Dr. Christian Leibold
• Subject Area: Experimental and Theoretical Network Neuroscience
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 563718082

Currently, the mathematical concept of neural manifolds is a highly promising tool in the analysis of highly parallel single-cell recordings. Manifold methods contribute fundamentally to the functional interpretation and visualization of high-dimensional neuronal activity measurements. There are, however, currently only vague ideas about how manifold analyses can be related to anatomical and cellular physiological mechanisms. This gap in knowledge currently severely limits the applicability of manifold methods and restricts them to phenomenological approaches. In this project, a bridge is supposed to be built between cellular and network properties on the one hand and the manifold concept of population activity dynamics on the other hand using computer simulations and mathematical analysis of biologically inspired neuronal networks. The aim is to particularly capture the contributions of anatomically separated synaptic populations, inter-area and intra-area synapses. The project will also demonstrate relations and differences between the different uses of the manifold concept in systems neuroscience. The project will thus provide necessary methods to be able to better mechanistically interpret experimental manifold analyses.

• DFG Programme: Research Grants