Since the work of Golgi and Cajal, light microscopy has remained a key tool for neuroscientists to observe cellular properties. Ongoing advances have enabled new experimental capabilities using light to inspect the nervous system across multiple spatial scales, including ultrastructural scales finer than the optical diffraction limit. Other progress permits functional imaging at faster speeds, at greater depths in brain tissue, and over larger tissue volumes than previously possible. Portable, miniaturized fluorescence microscopes now allow brain imaging in freely behaving mice. Complementary progress on animal preparations has enabled imaging in head-restrained behaving animals, as well as time-lapse microscopy studies in the brains of live subjects. Mouse genetic approaches permit mosaic and inducible fluorescence-labeling strategies, whereas intrinsic contrast mechanisms allow in vivo imaging of animals and humans without use of exogenous markers. This review surveys such advances and highlights emerging capabilities of particular interest to neuroscientists. Keywordstwo-photon fluorescence; super-resolution; fiber optics; laser-scanning; fluorescence labeling; transgenic mice THE CHANGING ROLE OF MICROSCOPY IN NEUROSCIENCEThe light microscope has long been one of neuroscientists' cardinal tools. When used together with Golgi's technique for staining a sparse population of cells, the light microscope provided the data that drove the famous debate between Golgi and Cajal about whether the nervous system was composed of cells or a syncytium (Cajal 1906, Golgi 1906. Although neuroscientists historically used light microscopy mainly to inspect histological specimens for studies of cellular morphology and the brain's cyto-architecture, optical microscopy has progressed to where it now routinely provides information about cellular and circuit dynamics, on timescales ranging from milliseconds to months. In addition to this considerable expansion in usage, the basic character of the data provided by the light microscope has also evolved.Early studies in light microscopy treated images as data represented in pictorial form. These images were either observed directly by eye or captured by photography, but in both cases the data were inspected visually. Over the past few decades, digital image acquisition and laserCorrespondence to: Mark J. Schnitzer, mschnitz@stanford.edu. DISCLOSURE STATEMENTThe authors are not aware of any affiliations, memberships, funding, or financial holdings that might be perceived as affecting the objectivity of this review. NIH Public Access Author ManuscriptAnnu Rev Neurosci. Author manuscript; available in PMC 2010 February 11. Published in final edited form as:Annu Rev Neurosci. 2009 ; 32: 435. doi:10.1146/annurev.neuro.051508.135540. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript scanning microscopy have transformed the data microscopes typically provide into a numerical format, with a specified number of bits per image pixel. This transition has in turn ...

Optical approaches for tracking neural dynamics are of widespread interest, but a theoretical framework quantifying the physical limits of these techniques has been lacking. We formulate such a framework by using signal detection and estimation theory to obtain physical bounds on the detection of neural spikes and the estimation of their occurrence times as set by photon counting statistics (shot noise). These bounds are succinctly expressed via a discriminability index that depends on the kinetics of the optical indicator and the relative fluxes of signal and background photons. This approach facilitates quantitative evaluations of different indicators, detector technologies, and data analyses. Our treatment also provides optimal filtering techniques for optical detection of spikes. We compare various types of Ca(2+) indicators and show that background photons are a chief impediment to voltage sensing. Thus, voltage indicators that change color in response to membrane depolarization may offer a key advantage over those that change intensity. We also examine fluorescence resonance energy transfer indicators and identify the regimes in which the widely used ratiometric analysis of signals is substantially suboptimal. Overall, by showing how different optical factors interact to affect signal quality, our treatment offers a valuable guide to experimental design and provides measures of confidence to assess optically extracted traces of neural activity.