Saturated Reconstruction of a Volume of Neocortex.

We describe automated technologies to probe the structure of neural tissue at nanometer resolution and use them to generate a saturated reconstruction of a sub-volume of mouse neocortex in which all cellular objects (axons, dendrites, and glia) and many sub-cellular components (synapses, synaptic vesicles, spines, spine apparati, postsynaptic densities, and mitochondria) are rendered and itemized in a database. We explore these data to study physical properties of brain tissue. For example, by tracing the trajectories of all excitatory axons and noting their juxtapositions, both synaptic and non-synaptic, with every dendritic spine we refute the idea that physical proximity is sufficient to predict synaptic connectivity (the so-called Peters' rule). This online minable database provides general access to the intrinsic complexity of the neocortex and enables further data-driven inquiries.

Super-resolution laser scanning microscopy through spatiotemporal modulation.

Super-resolution optical microscopy has attracted great interest among researchers in many fields, especially in biology where the scale of physical structures and molecular processes fall below the diffraction limit of resolution for light. As one of the emerging techniques, structured illumination microscopy can double the resolution by shifting unresolvable spatial frequencies into the pass-band of the microscope through spatial frequency mixing with a wide-field structured illumination pattern. However, such a wide-field scheme typically can only image optically thin samples and is incompatible with multiphoton processes such as two-photon fluorescence, which require point scanning with a focused laser beam. Here, we propose two new super-resolution schemes for laser scanning microscopy by generalizing the concept of a spatially nonuniform imaging system. One scheme, scanning patterned illumination (SPIN) microscopy, employs modulation of the excitation combined with temporally cumulative imaging by a nondescanned array detector. The other scheme, scanning patterned detection (SPADE) microscopy, utilizes detection modulation together with spatially cumulative imaging, in this case by a nondescanned single-element detector. When combined with multiphoton excitation, both schemes can image thick samples with three-dimensional optical sectioning and much improved resolution.

Extended depth-of-focus microscopy via constrained deconvolution.

We derive a method for extended depth-of-focus imaging, i.e., a method to render a 2-D image of a thick specimen, such that all the structures within the specimen appear in focus and with greatly increased contrast. We acquire a single image while moving the specimen through focus. The resulting image, which is severely blurred and has very low contrast, is then deconvolved. In the deconvolved image, the entire depth of the specimen is in focus. Because the image is collected continuously while the specimen moves through focus, the acquisition time is short. Likewise, because the deconvolution is done in 2-D, it is done very quickly even with an iterative algorithm.

Fluorescence microscopy.

Although fluorescence microscopy permeates all of cell and molecular biology, most biologists have little experience with the underlying photophysical phenomena. Understanding the principles underlying fluorescence microscopy is useful when attempting to solve imaging problems. Additionally, fluorescence microscopy is in a state of rapid evolution, with new techniques, probes and equipment appearing almost daily. Familiarity with fluorescence is a prerequisite for taking advantage of many of these developments. This review attempts to provide a framework for understanding excitation of and emission by fluorophores, the way fluorescence microscopes work, and some of the ways fluorescence can be optimized.

Optical sectioning microscopy.

Confocal scanning microscopy, a form of optical sectioning microscopy, has radically transformed optical imaging in biology. These devices provide a powerful means to eliminate from images the background caused by out-of-focus light and scatter. Confocal techniques can also improve the resolution of a light microscope image beyond what is achievable with widefield fluorescence microscopy. The quality of the images obtained, however, depends on the user's familiarity with the optical and fluorescence concepts that underlie this approach. We describe the core concepts of confocal microscopes and important variables that adversely affect confocal images. We also discuss data-processing methods for confocal microscopy and computational optical sectioning techniques that can perform optical sectioning without a confocal microscope.

Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy.

We derive an algorithm for maximum-likelihood image estimation on the basis of the expectation-maximization (EM) formalism by using a new approximate model for depth-varying image formation for optical sectioning microscopy. This new strata-based model incorporates spherical aberration that worsens as the microscope is focused deeper under the cover slip and is the result of the refractive-index mismatch between the immersion medium and the mounting medium of the specimen. Images of a specimen with known geometry and refractive index show that the model captures the main features of the image. We analyze the performance of the depth-variant EM algorithm with simulations, which show that the algorithm can compensate for image degradation changing with depth.

Numerical evaluation of Hankel transforms for oscillating functions.

Six methods for the numerical calculation of zero-order Hankel transforms of oscillating functions were evaluated. One method based on Filon quadrature philosophy, two published projection-slice methods, and a third projection-slice method based on a new approach to computation of the Abel transform were implemented; alternative versions of two of the projection-slice methods were derived for more accurate approximations in the projection step. These six algorithms were tested with an oscillating sweep signal and with the calculation of a three-dimensional diffraction-limited point-spread function of a fluorescence microscope. We found that the Filon quadrature method is highly accurate but also computationally demanding. The projection-slice methods, in particular the new one that we derived, offer an excellent compromise between accuracy and computational efficiency.