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Identification of the cellular players and molecular messengers that communicate neuronal activity to the vasculature driving cerebral hemodynamics is important for (1) the basic understanding of cerebrovascular regulation and (2) interpretation of functional Magnetic Resonance Imaging (fMRI) signals. Using a combination of optogenetic stimulation and 2-photon imaging in mice, we demonstrate that selective activation of cortical excitation and inhibition elicits distinct vascular responses and identify the vasoconstrictive mechanism as Neuropeptide Y (NPY) acting on Y1 receptors. The latter implies that task-related negative Blood Oxygenation Level Dependent (BOLD) fMRI signals in the cerebral cortex under normal physiological conditions may be mainly driven by the NPY-positive inhibitory neurons. Further, the NPY-Y1 pathway may offer a potential therapeutic target in cerebrovascular disease. Unlike other cells in the body, brain cells contain almost no energy reserves and rely on blood vessels for continuous supply of oxygen. A change in the brain’s activity can cause these blood vessels to either dilate or constrict, which alters the supply to match the change in demand. However, it is not known which signals cause these changes in the blood vessels. Previous studies have shown that individual blood vessels in an intact brain tend to dilate when the brain’s activity increases, and constrict when brain activity is inhibited. However, these studies were based on correlations, and there was no direct evidence that the inhibitory cells cause blood vessels to constrict. Uhlirova, Kılıç et al. now provide such evidence. The experiments made use of mice that had been genetically modified such that the excitatory or inhibitory nerve cells in their brains could be selectively activated by shining a blue light on the brain’s surface. The vessels in the outer millimeter of the gray matter of each mouse’s brain were imaged in detail, both before and after the blue light was used to activate the nerve cells. The experiments reveal that both excitatory and inhibitory nerve cells can cause blood vessels in the brain to dilate. However, blood vessels in the brain will only constrict in response to inhibitory nerve cells. Uhlirova, Kılıç et al. went on to identify a molecule called Neuropeptide Y (or NPY short) as a signal that triggers the constriction of the blood vessels. This signaling molecule is released by a specific sub-type of inhibitory nerve cell and it binds to a receptor protein on the brain’s blood vessels to make them constrict. These findings suggest that NPY and its receptor on blood vessels may offer promising targets for drugs to treat diseases of the brain’s blood vessels. Further studies are now needed to identify the signals responsible for the dilation of blood vessels in the brain.

In vivo optical imaging of cerebral blood flow (CBF) and metabolism did not exist 50 years ago. While point optical fluorescence and absorption measurements of cellular metabolism and hemoglobin concentrations had already been introduced by then, point blood flow measurements appeared only 40 years ago. The advent of digital cameras has significantly advanced two-dimensional optical imaging of neuronal, metabolic, vascular, and hemodynamic signals. More recently, advanced laser sources have enabled a variety of novel three-dimensional high-spatial-resolution imaging approaches. Combined, as we discuss here, these methods are permitting a multifaceted investigation of the local regulation of CBF and metabolism with unprecedented spatial and temporal resolution. Through multimodal combination of these optical techniques with genetic methods of encoding optical reporter and actuator proteins, the future is bright for solving the mysteries of neurometabolic and neurovascular coupling and translating them to clinical utility.

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed ‘bottom-up’ forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the ‘ground truth’ for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

An optical flow gradient algorithm was applied to spontaneously forming networks of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling with single pixel resolution. Optical flow estimates the direction and speed of motion of objects in an image between subsequent frames in a recorded digital sequence of images (i.e., a movie). Computed vector field outputs by the algorithm were able to track the spatiotemporal dynamics of calcium signaling patterns. We begin by briefly reviewing the mathematics of the optical flow algorithm, and then describe how to solve for the displacement vectors and how to measure their reliability. We then compare computed flow vectors with manually estimated vectors for the progression of a calcium signal recorded from representative astrocyte cultures. Finally, we applied the algorithm to preparations of primary astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in order to illustrate the capability of the algorithm for capturing different types of spatiotemporal calcium activity. We discuss the imaging requirements, parameter selection and threshold selection for reliable measurements, and offer perspectives on uses of the vector data.

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. Qn the essential path towards this goal is the development of a detailed 'bottom-up' forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the 'ground truth' for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

Historically, experimental methods to investigate astrocyte function in the intact brain have been limited by the fact that glia are electrically silent. This has led to a heavy reliance on calcium imaging techniques in the study of astrocyte function. In the past decade, the widespread use of this technique, particularly in vivo, has pushed the boundaries of what can be accomplished with fluorescent imaging. This series of studies is dedicated to taking that boundary a step further, utilizing the technology currently available to ask fundamental questions regarding the neurovascular unit (NVU), and concluding with some perspectives on the advances still needed to fully elucidate the functional role of astrocytes within the NVU. This dissertation is focused on astrocytic function in relation to the vascular compartment, astrocytic function in relation to the neuronal compartment, and finally, astrocytic function in relation to each other (Fig. A.1). In considering the vascular aspect of the NVU, we compare the in vivo temporal characteristics of the cerebral blood vessel dilation and the astrocytic calcium response to increased neuronal activity. We provide evidence of a significant temporal mismatch that challenges the popular idea of a calcium-dependent astrocytic role in triggering neurovascular coupling. In considering the metabolic aspect of the NVU, we report here the first application of 2-photon laser scanning microscopy (TPLSM) to functional imaging of intrinsically fluorescent β-nicotinamide adenine dinucleotide (NADH) as a means to visualize single cell metabolism in vivo. We demonstrate, through this new imaging modality, that astrocytes respond readily and rapidly to evoked neuronal activity. We suggest that, contrary to what is indicated by their calcium activity, astrocytes are actually very sensitive to neuronal activity, and do respond on a relevant time scale, but do not necessarily act as mediators in translating neuronal activity to the vasculature. Given their prominent yet mysterious place within the NVU, there is a great need to identify suitable methodologies to describe the large repertoire of astrocytic calcium dynamics, ranging from subcellular compartments to network-level waves. Toward this end, we report on the application of optical flow image analysis to calcium signaling dynamics in spontaneously forming networks of astrocytes and neurons. By using information gained from a reduced preparation in conjunction with the whole animal approach, we hope to contribute to the set of tools that will be necessary to accurately assess the role(s) of astrocytes within the NVU.

An optical flow gradient algorithm was applied to spontaneously forming net- works of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling with single pixel resolution. Optical flow estimates the direction and speed of motion of objects in an image between subsequent frames in a recorded digital sequence of images (i.e. a movie). Computed vector field outputs by the algorithm were able to track the spatiotemporal dynamics of calcium signaling pat- terns. We begin by briefly reviewing the mathematics of the optical flow algorithm, and then describe how to solve for the displacement vectors and how to measure their reliability. We then compare computed flow vectors with manually estimated vectors for the progression of a calcium signal recorded from representative astrocyte cultures. Finally, we applied the algorithm to preparations of primary astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in order to illustrate the capability of the algorithm for capturing different types of spatiotemporal calcium activity. We discuss the imaging requirements, parameter selection and threshold selection for reliable measurements, and offer perspectives on uses of the vector data.