A novel way to visualize the energetic coupling between neurons and astrocytes and to improve understanding of brain metabolism has been discovered by the researchers at KAUST and their collaborators in France. The human brain uses more energy than any other organ, accounting for around 20 percent of all glucose-derived energy. Neurons can’t meet their own energy requirements: they depend on supporting glial cells and the neurovascular system to supply various forms of sugar fuel. However, it is still unclear how this neuro-glio-vasculature network manages the brain’s energy demands. Lactate is a fuel that neurons rely on for their energy needs. It is produced by astrocytes - the most abundant glial cell type in the central nervous system - and is shuttled to neurons. 

One will not understand the brain without an integrated exploration of structure and function, these attributes being two sides of the same coin: together they form the currency of biological computation. Accordingly, biologically realistic models require the re-creation of the architecture of the cellular components in which biochemical reactions are contained. 

The researchers have now published the four-stage process they are following to develop computer simulations of the energetic coupling between neurons and astrocytes. Realistic simulations require an understanding of the cellular space in which the biochemical reactions that manage energy supply take place.

To make biologically accurate models, the team employs serial block-face electron microscopy to image thousands of serial sections from rodent brains and use them to make 3D models of astrocytes. These reconstructions reveal the strategic location of energy stores and power sources (mitochondria) in astrocytic compartments to improve the cells’ energetic efficiency. Developing bespoke analytical tools to describe the astrocyte’s morphology mathematically enables the researchers to incorporate this information into computer simulations. This represents a major step forward because, to date, 3D models have mostly been used for qualitative rather than quantitative analysis.

Another unique aspect of this study is the pioneering use of virtual reality (VR) in neuroscience. The resulting models are difficult to analyze on a 2D screen, so to make them more accessible, the researchers at KAUST’s Visual Computing Center embedded them in a VR analytical framework. They have produced tools for the visual analysis of data extracted from electron microscopy images that help understand brain-energy metabolism in various parts of cells.

Although this study focused on brain-energy metabolism, the process developed by the authors can be applied to any cellular grouping to gain knowledge on other fundamental neural functions, such as learning and memory formation, at the molecular, cellular and network level.