A Cellular Perspective on Brain Energy Metabolism and Functional Imaging.

The energy demands of the brain are high: they account for at least 20% of the body's energy consumption. Evolutionary studies indicate that the emergence of higher cognitive functions in humans is associated with an increased glucose utilization and expression of energy metabolism genes. Functional brain imaging techniques such as fMRI and PET, which are widely used in human neuroscience studies, detect signals that monitor energy delivery and use in register with neuronal activity. Recent technological advances in metabolic studies with cellular resolution have afforded decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism and point at a key role of neuron-astrocyte metabolic interactions. This article reviews some of the most salient features emerging from recent studies and aims at providing an integration of brain energy metabolism across resolution scales.

Review of quantitative phase-digital holographic microscopy: promising novel imaging technique to resolve neuronal network activity and identify cellular biomarkers of psychiatric disorders.

Quantitative phase microscopy (QPM) has recently emerged as a new powerful quantitative imaging technique well suited to noninvasively explore a transparent specimen with a nanometric axial sensitivity. In this review, we expose the recent developments of quantitative phase-digital holographic microscopy (QP-DHM). Quantitative phase-digital holographic microscopy (QP-DHM) represents an important and efficient quantitative phase method to explore cell structure and dynamics. In a second part, the most relevant QPM applications in the field of cell biology are summarized. A particular emphasis is placed on the original biological information, which can be derived from the quantitative phase signal. In a third part, recent applications obtained, with QP-DHM in the field of cellular neuroscience, namely the possibility to optically resolve neuronal network activity and spine dynamics, are presented. Furthermore, potential applications of QPM related to psychiatry through the identification of new and original cell biomarkers that, when combined with a range of other biomarkers, could significantly contribute to the determination of high risk developmental trajectories for psychiatric disorders, are discussed.