Energy metabolism reveals hidden properties of brain functional connectivity

• Applicant: Privatdozent Dr. Valentin Riedl
• Subject Area: Human Cognitive and Systems Neuroscience
• Term: from 2015 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 273427765

Systems neuroscience has moved a major step forward in understanding brain organization by investigating large-scale networks of functionally connected systems rather than singular brain regions. Here, functional connectivity (FC) approaches have revealed a signature of brain networks that occur in several species and show substantial alterations in neuropsychiatric disorders. However, the method is currently stuck at a descriptive level of network organization as its relationship to basic neurophysiology is still largely unknown. Two aspects of FC still prohibit a neurophysiological interpretation of (mal)-functioning in the brain´s network architecture. First, FC is calculated on the signal of functional magnetic-resonance-imaging (fMRI), which is an indirect measure of neuronal activity. Second, FC is an undirected measure of connectivity, simply indicating that two regions are communicating with each other but being blind for direction of neuronal communication. This means that several important aspects of neuronal signaling related to FC are unknown. In the baseline state the brain consumes roughly 20% of the body´s energy and most of this energy is dedicated to signaling between connected neurons. Neuroenergetics of single primate neurons indicate that signaling energy is predominantly consumed post-synaptically, i.e. at target neurons. As glucose is the obligatory energy substrate for the brain, local energy consumption measured on the systems level offers two interpretations of neuronal signaling. (1) Local energy consumption should scale with the amount of incoming connections. (2) The energy profile of two connected brain regions should reflect the connectivity profile of the target rather than the output region. By integrating large-scale FC and local glucose metabolism from human brain imaging at a novel integrated scanner simultaneously performing positron-emmission-tomography (PET) and fMRI we test these two hypotheses of neuroenergetics and neurotransmission on the systems level. Assuming the cellular model holds true for systems level data, we can identify energy demanding signaling pathways in the human brain and trace signaling pathways of large-scale brain networks. Our approach might have strong implications for better understanding and testing pathological mechanisms in currently descriptive FC networks.

• DFG Programme: Research Grants