On-chip lensless imaging in general aims to replace bulky lens-based optical microscopes with simpler and more compact designs, especially for high-throughput screening applications. This emerging technology platform has the potential to eliminate the need for bulky and/or costly optical components through the help of novel theories and digital reconstruction algorithms. Along the same lines, here we demonstrate an on-chip fluorescent microscopy modality that can achieve e.g., <4μm spatial resolution over an ultra-wide field-of-view (FOV) of >0.6-8 cm2 without the use of any lenses, mechanical-scanning or thin-film based interference filters. In this technique, fluorescent excitation is achieved through a prism or hemispherical-glass interface illuminated by an incoherent source. After interacting with the entire object volume, this excitation light is rejected by total-internal-reflection (TIR) process that is occurring at the bottom of the sample micro-fluidic chip. The fluorescent emission from the excited objects is then collected by a fiber-optic faceplate or a taper and is delivered to an optoelectronic sensor array such as a charge-coupled-device (CCD). By using a compressive-sampling based decoding algorithm, the acquired lensfree raw fluorescent images of the sample can be rapidly processed to yield e.g., <4μm resolution over an FOV of >0.6-8 cm2. Moreover, vertically stacked micro-channels that are separated by e.g., 50-100 μm can also be successfully imaged using the same lensfree on-chip microscopy platform, which further increases the overall throughput of this modality. This compact on-chip fluorescent imaging platform, with a rapid compressive decoder behind it, could be rather valuable for high-throughput cytometry, rare-cell research and microarray-analysis.
25 Related JoVE Articles!
Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Institutions: University of Washington.
Magneto- and electroencephalography (MEG/EEG) are neuroimaging techniques that provide a high temporal resolution particularly suitable to investigate the cortical networks involved in dynamical perceptual and cognitive tasks, such as attending to different sounds in a cocktail party. Many past studies have employed data recorded at the sensor level only, i.e
., the magnetic fields or the electric potentials recorded outside and on the scalp, and have usually focused on activity that is time-locked to the stimulus presentation. This type of event-related field / potential analysis is particularly useful when there are only a small number of distinct dipolar patterns that can be isolated and identified in space and time. Alternatively, by utilizing anatomical information, these distinct field patterns can be localized as current sources on the cortex. However, for a more sustained response that may not be time-locked to a specific stimulus (e.g
., in preparation for listening to one of the two simultaneously presented spoken digits based on the cued auditory feature) or may be distributed across multiple spatial locations unknown a priori
, the recruitment of a distributed cortical network may not be adequately captured by using a limited number of focal sources.
Here, we describe a procedure that employs individual anatomical MRI data to establish a relationship between the sensor information and the dipole activation on the cortex through the use of minimum-norm estimates (MNE). This inverse imaging approach provides us a tool for distributed source analysis. For illustrative purposes, we will describe all procedures using FreeSurfer and MNE software, both freely available. We will summarize the MRI sequences and analysis steps required to produce a forward model that enables us to relate the expected field pattern caused by the dipoles distributed on the cortex onto the M/EEG sensors. Next, we will step through the necessary processes that facilitate us in denoising the sensor data from environmental and physiological contaminants. We will then outline the procedure for combining and mapping MEG/EEG sensor data onto the cortical space, thereby producing a family of time-series of cortical dipole activation on the brain surface (or "brain movies") related to each experimental condition. Finally, we will highlight a few statistical techniques that enable us to make scientific inference across a subject population (i.e
., perform group-level analysis) based on a common cortical coordinate space.
Neuroscience, Issue 68, Magnetoencephalography, MEG, Electroencephalography, EEG, audition, attention, inverse imaging
Structure of HIV-1 Capsid Assemblies by Cryo-electron Microscopy and Iterative Helical Real-space Reconstruction
Institutions: University of Pittsburgh School of Medicine.
Cryo-electron microscopy (cryo-EM), combined with image processing, is an increasingly powerful tool for structure determination of macromolecular protein complexes and assemblies. In fact, single particle electron microscopy1
and two-dimensional (2D) electron crystallography2
have become relatively routine methodologies and a large number of structures have been solved using these methods. At the same time, image processing and three-dimensional (3D) reconstruction of helical objects has rapidly developed, especially, the iterative helical real-space reconstruction (IHRSR) method3
, which uses single particle analysis tools in conjunction with helical symmetry. Many biological entities function in filamentous or helical forms, including actin filaments4
, amyloid fibers6
, tobacco mosaic viruses7
, and bacteria flagella8
, and, because a 3D density map of a helical entity can be attained from a single projection image, compared to the many images required for 3D reconstruction of a non-helical object, with the IHRSR method, structural analysis of such flexible and disordered helical assemblies is now attainable.
In this video article, we provide detailed protocols for obtaining a 3D density map of a helical protein assembly (HIV-1 capsid9
is our example), including protocols for cryo-EM specimen preparation, low dose data collection by cryo-EM, indexing of helical diffraction patterns, and image processing and 3D reconstruction using IHRSR. Compared to other techniques, cryo-EM offers optimal specimen preservation under near native conditions. Samples are embedded in a thin layer of vitreous ice, by rapid freezing, and imaged in electron microscopes at liquid nitrogen temperature, under low dose conditions to minimize the radiation damage. Sample images are obtained under near native conditions at the expense of low signal and low contrast in the recorded micrographs. Fortunately, the process of helical reconstruction has largely been automated, with the exception of indexing the helical diffraction pattern. Here, we describe an approach to index helical structure and determine helical symmetries (helical parameters) from digitized micrographs, an essential step for 3D helical reconstruction. Briefly, we obtain an initial 3D density map by applying the IHRSR method. This initial map is then iteratively refined by introducing constraints for the alignment parameters of each segment, thus controlling their degrees of freedom. Further improvement is achieved by correcting for the contrast transfer function (CTF) of the electron microscope (amplitude and phase correction) and by optimizing the helical symmetry of the assembly.
Immunology, Issue 54, cryo-electron microscopy, helical indexing, helical real-space reconstruction, tubular assemblies, HIV-1 capsid
How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index
Institutions: University of Geneva School of Medicine, École Polytechnique Fédérale de Lausanne, University Hospital Center and University of Lausanne, Massachusetts General Hospital.
Cortical folding (gyrification) is determined during the first months of life, so that adverse events occurring during this period leave traces that will be identifiable at any age. As recently reviewed by Mangin and colleagues2
, several methods exist to quantify different characteristics of gyrification. For instance, sulcal morphometry can be used to measure shape descriptors such as the depth, length or indices of inter-hemispheric asymmetry3
. These geometrical properties have the advantage of being easy to interpret. However, sulcal morphometry tightly relies on the accurate identification of a given set of sulci and hence provides a fragmented description of gyrification. A more fine-grained quantification of gyrification can be achieved with curvature-based measurements, where smoothed absolute mean curvature is typically computed at thousands of points over the cortical surface4
. The curvature is however not straightforward to comprehend, as it remains unclear if there is any direct relationship between the curvedness and a biologically meaningful correlate such as cortical volume or surface. To address the diverse issues raised by the measurement of cortical folding, we previously developed an algorithm to quantify local gyrification with an exquisite spatial resolution and of simple interpretation. Our method is inspired of the Gyrification Index5
, a method originally used in comparative neuroanatomy to evaluate the cortical folding differences across species. In our implementation, which we name l
ocal Gyrification Index (l
), we measure the amount of cortex buried within the sulcal folds as compared with the amount of visible cortex in circular regions of interest. Given that the cortex grows primarily through radial expansion6
, our method was specifically designed to identify early defects of cortical development.
In this article, we detail the computation of local Gyrification Index, which is now freely distributed as a part of the FreeSurfer
Software (http://surfer.nmr.mgh.harvard.edu/, Martinos Center for Biomedical Imaging, Massachusetts General Hospital). FreeSurfer
provides a set of automated reconstruction tools of the brain's cortical surface from structural MRI data. The cortical surface extracted in the native space of the images with sub-millimeter accuracy is then further used for the creation of an outer surface, which will serve as a basis for the l
GI calculation. A circular region of interest is then delineated on the outer surface, and its corresponding region of interest on the cortical surface is identified using a matching algorithm as described in our validation study1
. This process is repeatedly iterated with largely overlapping regions of interest, resulting in cortical maps of gyrification for subsequent statistical comparisons (Fig. 1). Of note, another measurement of local gyrification with a similar inspiration was proposed by Toro and colleagues7
, where the folding index at each point is computed as the ratio of the cortical area contained in a sphere divided by the area of a disc with the same radius. The two implementations differ in that the one by Toro et al. is based on Euclidian distances and thus considers discontinuous patches of cortical area, whereas ours uses a strict geodesic algorithm and include only the continuous patch of cortical area opening at the brain surface in a circular region of interest.
Medicine, Issue 59, neuroimaging, brain, cortical complexity, cortical development
The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Institutions: University of Montréal, McGill University, University of Minnesota.
Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33
. To help improve this understanding, proton magnetic resonance spectroscopy (1
H-MRS) can be used as it allows the in vivo
quantification of brain metabolites such as γ-aminobutyric acid (GABA) and glutamate in a region-specific manner 41
. In fact, a recent study demonstrated that 1
H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34
. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1
H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31
. Methodological factors to consider and possible modifications to the protocol are also discussed.
Neuroscience, Issue 93, proton magnetic resonance spectroscopy, transcranial direct current stimulation, primary motor cortex, GABA, glutamate, stroke
Assessment of Cardiac Function and Myocardial Morphology Using Small Animal Look-locker Inversion Recovery (SALLI) MRI in Rats
Institutions: German Heart Institute Berlin, German Heart Institute Berlin, Hamburg, Germany.
Small animal magnetic resonance imaging is an important tool to study cardiac function and changes in myocardial tissue. The high heart rates of small animals (200 to 600 beats/min) have previously limited the role of CMR imaging. Small animal Look-Locker inversion recovery (SALLI) is a T1 mapping sequence for small animals to overcome this problem 1
. T1 maps provide quantitative information about tissue alterations and contrast agent kinetics. It is also possible to detect diffuse myocardial processes such as interstitial fibrosis or edema 1-6
. Furthermore, from a single set of image data, it is possible to examine heart function and myocardial scarring by generating cine and inversion recovery-prepared late gadolinium enhancement-type MR images 1
The presented video shows step-by-step the procedures to perform small animal CMR imaging. Here it is presented with a healthy Sprague-Dawley rat, however naturally it can be extended to different cardiac small animal models.
Medicine, Issue 77, Biomedical Engineering, Anatomy, Physiology, Cardiology, Heart Diseases, Cardiomyopathies, Heart Failure, Diagnostic Imaging, Cardiac Imaging Techniques, Magnetic Resonance Imaging, MRI, Cardiovascular Diseases, small animal imaging, T1 mapping, heart disease, cardiac function, myocardium, rat, animal model
A Comprehensive Protocol for Manual Segmentation of the Medial Temporal Lobe Structures
Institutions: University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign, University of Illinois Urbana-Champaign.
The present paper describes a comprehensive protocol for manual tracing of the set of brain regions comprising the medial temporal lobe (MTL): amygdala, hippocampus, and the associated parahippocampal regions (perirhinal, entorhinal, and parahippocampal proper). Unlike most other tracing protocols available, typically focusing on certain MTL areas (e.g.
, amygdala and/or hippocampus), the integrative perspective adopted by the present tracing guidelines allows for clear localization of all MTL subregions. By integrating information from a variety of sources, including extant tracing protocols separately targeting various MTL structures, histological reports, and brain atlases, and with the complement of illustrative visual materials, the present protocol provides an accurate, intuitive, and convenient guide for understanding the MTL anatomy. The need for such tracing guidelines is also emphasized by illustrating possible differences between automatic and manual segmentation protocols. This knowledge can be applied toward research involving not only structural MRI investigations but also structural-functional colocalization and fMRI signal extraction from anatomically defined ROIs, in healthy and clinical groups alike.
Neuroscience, Issue 89, Anatomy, Segmentation, Medial Temporal Lobe, MRI, Manual Tracing, Amygdala, Hippocampus, Perirhinal Cortex, Entorhinal Cortex, Parahippocampal Cortex
Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
Institutions: Johns Hopkins University.
Patient-specific simulations of heart (dys)function aimed at personalizing cardiac therapy are hampered by the absence of in vivo
imaging technology for clinically acquiring myocardial fiber orientations. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo
images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via
semiautomatic segmentation, from an in vivo
computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4 °. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.The new insights obtained from the project will pave the way for the development of patient-specific models of the heart that can aid physicians in personalized diagnosis and decisions regarding electrophysiological interventions.
Bioengineering, Issue 71, Biomedical Engineering, Medicine, Anatomy, Physiology, Cardiology, Myocytes, Cardiac, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, MRI, Diffusion Magnetic Resonance Imaging, Cardiac Electrophysiology, computerized simulation (general), mathematical modeling (systems analysis), Cardiomyocyte, biomedical image processing, patient-specific modeling, Electrophysiology, simulation
Mapping the After-effects of Theta Burst Stimulation on the Human Auditory Cortex with Functional Imaging
Institutions: McGill University .
Auditory cortex pertains to the processing of sound, which is at the basis of speech or music-related processing1
. However, despite considerable recent progress, the functional properties and lateralization of the human auditory cortex are far from being fully understood. Transcranial Magnetic Stimulation (TMS) is a non-invasive technique that can transiently or lastingly modulate cortical excitability via the application of localized magnetic field pulses, and represents a unique method of exploring plasticity and connectivity. It has only recently begun to be applied to understand auditory cortical function 2
An important issue in using TMS is that the physiological consequences of the stimulation are difficult to establish. Although many TMS studies make the implicit assumption that the area targeted by the coil is the area affected, this need not be the case, particularly for complex cognitive functions which depend on interactions across many brain regions 3
. One solution to this problem is to combine TMS with functional Magnetic resonance imaging (fMRI). The idea here is that fMRI will provide an index of changes in brain activity associated with TMS. Thus, fMRI would give an independent means of assessing which areas are affected by TMS and how they are modulated 4
. In addition, fMRI allows the assessment of functional connectivity, which represents a measure of the temporal coupling between distant regions. It can thus be useful not only to measure the net activity modulation induced by TMS in given locations, but also the degree to which the network properties are affected by TMS, via any observed changes in functional connectivity.
Different approaches exist to combine TMS and functional imaging according to the temporal order of the methods. Functional MRI can be applied before, during, after, or both before and after TMS. Recently, some studies interleaved TMS and fMRI in order to provide online mapping of the functional changes induced by TMS 5-7
. However, this online combination has many technical problems, including the static artifacts resulting from the presence of the TMS coil in the scanner room, or the effects of TMS pulses on the process of MR image formation. But more importantly, the loud acoustic noise induced by TMS (increased compared with standard use because of the resonance of the scanner bore) and the increased TMS coil vibrations (caused by the strong mechanical forces due to the static magnetic field of the MR scanner) constitute a crucial problem when studying auditory processing.
This is one reason why fMRI was carried out before and after TMS in the present study. Similar approaches have been used to target the motor cortex 8,9
, premotor cortex 10
, primary somatosensory cortex 11,12
and language-related areas 13
, but so far no combined TMS-fMRI study has investigated the auditory cortex. The purpose of this article is to provide details concerning the protocol and considerations necessary to successfully combine these two neuroscientific tools to investigate auditory processing.
Previously we showed that repetitive TMS (rTMS) at high and low frequencies (resp. 10 Hz and 1 Hz) applied over the auditory cortex modulated response time (RT) in a melody discrimination task 2
. We also showed that RT modulation was correlated with functional connectivity in the auditory network assessed using fMRI: the higher the functional connectivity between left and right auditory cortices during task performance, the higher the facilitatory effect (i.e.
decreased RT) observed with rTMS. However those findings were mainly correlational, as fMRI was performed before rTMS. Here, fMRI was carried out before and immediately after TMS to provide direct measures of the functional organization of the auditory cortex, and more specifically of the plastic reorganization of the auditory neural network occurring after the neural intervention provided by TMS.
Combined fMRI and TMS applied over the auditory cortex should enable a better understanding of brain mechanisms of auditory processing, providing physiological information about functional effects of TMS. This knowledge could be useful for many cognitive neuroscience applications, as well as for optimizing therapeutic applications of TMS, particularly in auditory-related disorders.
Neuroscience, Issue 67, Physiology, Physics, Theta burst stimulation, functional magnetic resonance imaging, MRI, auditory cortex, frameless stereotaxy, sound, transcranial magnetic stimulation
Fabrication And Characterization Of Photonic Crystal Slow Light Waveguides And Cavities
Institutions: University of St Andrews.
Slow light has been one of the hot topics in the photonics community in the past decade, generating great interest both from a fundamental point of view and for its considerable potential for practical applications. Slow light photonic crystal waveguides, in particular, have played a major part and have been successfully employed for delaying optical signals1-4
and the enhancement of both linear5-7
and nonlinear devices.8-11
Photonic crystal cavities achieve similar effects to that of slow light waveguides, but over a reduced band-width. These cavities offer high Q-factor/volume ratio, for the realization of optically12
pumped ultra-low threshold lasers and the enhancement of nonlinear effects.14-16
Furthermore, passive filters17
have been demonstrated, exhibiting ultra-narrow line-width, high free-spectral range and record values of low energy consumption.
To attain these exciting results, a robust repeatable fabrication protocol must be developed. In this paper we take an in-depth look at our fabrication protocol which employs electron-beam lithography for the definition of photonic crystal patterns and uses wet and dry etching techniques. Our optimised fabrication recipe results in photonic crystals that do not suffer from vertical asymmetry and exhibit very good edge-wall roughness. We discuss the results of varying the etching parameters and the detrimental effects that they can have on a device, leading to a diagnostic route that can be taken to identify and eliminate similar issues.
The key to evaluating slow light waveguides is the passive characterization of transmission and group index spectra. Various methods have been reported, most notably resolving the Fabry-Perot fringes of the transmission spectrum20-21
and interferometric techniques.22-25
Here, we describe a direct, broadband measurement technique combining spectral interferometry with Fourier transform analysis.26
Our method stands out for its simplicity and power, as we can characterise a bare photonic crystal with access waveguides, without need for on-chip interference components, and the setup only consists of a Mach-Zehnder interferometer, with no need for moving parts and delay scans.
When characterising photonic crystal cavities, techniques involving internal sources21
or external waveguides directly coupled to the cavity27
impact on the performance of the cavity itself, thereby distorting the measurement. Here, we describe a novel and non-intrusive technique that makes use of a cross-polarised probe beam and is known as resonant scattering (RS), where the probe is coupled out-of plane into the cavity through an objective. The technique was first demonstrated by McCutcheon et al.28
and further developed by Galli et al.29
Physics, Issue 69, Optics and Photonics, Astronomy, light scattering, light transmission, optical waveguides, photonics, photonic crystals, Slow-light, Cavities, Waveguides, Silicon, SOI, Fabrication, Characterization
Lensfree On-chip Tomographic Microscopy Employing Multi-angle Illumination and Pixel Super-resolution
Institutions: University of California, Los Angeles , University of California, Los Angeles , University of California, Los Angeles .
Tomographic imaging has been a widely used tool in medicine as it can provide three-dimensional (3D) structural information regarding objects of different size scales. In micrometer and millimeter scales, optical microscopy modalities find increasing use owing to the non-ionizing nature of visible light, and the availability of a rich set of illumination sources (such as lasers and light-emitting-diodes) and detection elements (such as large format CCD and CMOS detector-arrays). Among the recently developed optical tomographic microscopy modalities, one can include optical coherence tomography, optical diffraction tomography, optical projection tomography and light-sheet microscopy. 1-6
These platforms provide sectional imaging of cells, microorganisms and model animals such as C. elegans
, zebrafish and mouse embryos.
Existing 3D optical imagers generally have relatively bulky and complex architectures, limiting the availability of these equipments to advanced laboratories, and impeding their integration with lab-on-a-chip platforms and microfluidic chips. To provide an alternative tomographic microscope, we recently developed lensfree optical tomography (LOT) as a high-throughput, compact and cost-effective optical tomography modality. 7
LOT discards the use of lenses and bulky optical components, and instead relies on multi-angle illumination and digital computation to achieve depth-resolved imaging of micro-objects over a large imaging volume. LOT can image biological specimen at a spatial resolution of <1 μm x <1 μm x <3 μm in the x, y and z dimensions, respectively, over a large imaging volume of 15-100 mm3
, and can be particularly useful for lab-on-a-chip platforms.
Bioengineering, Issue 66, Electrical Engineering, Mechanical Engineering, lensfree imaging, lensless imaging, on-chip microscopy, lensfree tomography, 3D microscopy, pixel super-resolution, C. elegans, optical sectioning, lab-on-a-chip
Training Synesthetic Letter-color Associations by Reading in Color
Institutions: University of Amsterdam.
Synesthesia is a rare condition in which a stimulus from one modality automatically and consistently triggers unusual sensations in the same and/or other modalities. A relatively common and well-studied type is grapheme-color synesthesia, defined as the consistent experience of color when viewing, hearing and thinking about letters, words and numbers. We describe our method for investigating to what extent synesthetic associations between letters and colors can be learned by reading in color in nonsynesthetes. Reading in color is a special method for training associations in the sense that the associations are learned implicitly while the reader reads text as he or she normally would and it does not require explicit computer-directed training methods. In this protocol, participants are given specially prepared books to read in which four high-frequency letters are paired with four high-frequency colors. Participants receive unique sets of letter-color pairs based on their pre-existing preferences for colored letters. A modified Stroop task is administered before and after reading in order to test for learned letter-color associations and changes in brain activation. In addition to objective testing, a reading experience questionnaire is administered that is designed to probe for differences in subjective experience. A subset of questions may predict how well an individual learned the associations from reading in color. Importantly, we are not claiming that this method will cause each individual to develop grapheme-color synesthesia, only that it is possible for certain individuals to form letter-color associations by reading in color and these associations are similar in some aspects to those seen in developmental grapheme-color synesthetes. The method is quite flexible and can be used to investigate different aspects and outcomes of training synesthetic associations, including learning-induced changes in brain function and structure.
Behavior, Issue 84, synesthesia, training, learning, reading, vision, memory, cognition
Simultaneous Multicolor Imaging of Biological Structures with Fluorescence Photoactivation Localization Microscopy
Institutions: University of Maine.
Localization-based super resolution microscopy can be applied to obtain a spatial map (image) of the distribution of individual fluorescently labeled single molecules within a sample with a spatial resolution of tens of nanometers. Using either photoactivatable (PAFP) or photoswitchable (PSFP) fluorescent proteins fused to proteins of interest, or organic dyes conjugated to antibodies or other molecules of interest, fluorescence photoactivation localization microscopy (FPALM) can simultaneously image multiple species of molecules within single cells. By using the following approach, populations of large numbers (thousands to hundreds of thousands) of individual molecules are imaged in single cells and localized with a precision of ~10-30 nm. Data obtained can be applied to understanding the nanoscale spatial distributions of multiple protein types within a cell. One primary advantage of this technique is the dramatic increase in spatial resolution: while diffraction limits resolution to ~200-250 nm in conventional light microscopy, FPALM can image length scales more than an order of magnitude smaller. As many biological hypotheses concern the spatial relationships among different biomolecules, the improved resolution of FPALM can provide insight into questions of cellular organization which have previously been inaccessible to conventional fluorescence microscopy. In addition to detailing the methods for sample preparation and data acquisition, we here describe the optical setup for FPALM. One additional consideration for researchers wishing to do super-resolution microscopy is cost: in-house setups are significantly cheaper than most commercially available imaging machines. Limitations of this technique include the need for optimizing the labeling of molecules of interest within cell samples, and the need for post-processing software to visualize results. We here describe the use of PAFP and PSFP expression to image two protein species in fixed cells. Extension of the technique to living cells is also described.
Basic Protocol, Issue 82, Microscopy, Super-resolution imaging, Multicolor, single molecule, FPALM, Localization microscopy, fluorescent proteins
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Institutions: University of Ulm.
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo
. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls.
DTI data analysis is performed in a variate fashion, i.e.
voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e.
differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels.
In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
Medicine, Issue 77, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Anatomy, Physiology, Neurodegenerative Diseases, nuclear magnetic resonance, NMR, MR, MRI, diffusion tensor imaging, fiber tracking, group level comparison, neurodegenerative diseases, brain, imaging, clinical techniques
Cortical Source Analysis of High-Density EEG Recordings in Children
Institutions: UCL Institute of Child Health, University College London.
EEG is traditionally described as a neuroimaging technique with high temporal and low spatial resolution. Recent advances in biophysical modelling and signal processing make it possible to exploit information from other imaging modalities like structural MRI that provide high spatial resolution to overcome this constraint1
. This is especially useful for investigations that require high resolution in the temporal as well as spatial domain. In addition, due to the easy application and low cost of EEG recordings, EEG is often the method of choice when working with populations, such as young children, that do not tolerate functional MRI scans well. However, in order to investigate which neural substrates are involved, anatomical information from structural MRI is still needed. Most EEG analysis packages work with standard head models that are based on adult anatomy. The accuracy of these models when used for children is limited2
, because the composition and spatial configuration of head tissues changes dramatically over development3
In the present paper, we provide an overview of our recent work in utilizing head models based on individual structural MRI scans or age specific head models to reconstruct the cortical generators of high density EEG. This article describes how EEG recordings are acquired, processed, and analyzed with pediatric populations at the London Baby Lab, including laboratory setup, task design, EEG preprocessing, MRI processing, and EEG channel level and source analysis.
Behavior, Issue 88, EEG, electroencephalogram, development, source analysis, pediatric, minimum-norm estimation, cognitive neuroscience, event-related potentials
Test Samples for Optimizing STORM Super-Resolution Microscopy
Institutions: National Physical Laboratory.
STORM is a recently developed super-resolution microscopy technique with up to 10 times better resolution than standard fluorescence microscopy techniques. However, as the image is acquired in a very different way than normal, by building up an image molecule-by-molecule, there are some significant challenges for users in trying to optimize their image acquisition. In order to aid this process and gain more insight into how STORM works we present the preparation of 3 test samples and the methodology of acquiring and processing STORM super-resolution images with typical resolutions of between 30-50 nm. By combining the test samples with the use of the freely available rainSTORM processing software it is possible to obtain a great deal of information about image quality and resolution. Using these metrics it is then possible to optimize the imaging procedure from the optics, to sample preparation, dye choice, buffer conditions, and image acquisition settings. We also show examples of some common problems that result in poor image quality, such as lateral drift, where the sample moves during image acquisition and density related problems resulting in the 'mislocalization' phenomenon.
Molecular Biology, Issue 79, Genetics, Bioengineering, Biomedical Engineering, Biophysics, Basic Protocols, HeLa Cells, Actin Cytoskeleton, Coated Vesicles, Receptor, Epidermal Growth Factor, Actins, Fluorescence, Endocytosis, Microscopy, STORM, super-resolution microscopy, nanoscopy, cell biology, fluorescence microscopy, test samples, resolution, actin filaments, fiducial markers, epidermal growth factor, cell, imaging
From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data
Institutions: Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory, Lawrence Berkeley National Laboratory.
Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g.
, signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation.
The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data, we propose a triage scheme that categorizes both objective data set characteristics and subjective personal criteria for the analysis of the different data sets.
Bioengineering, Issue 90, 3D electron microscopy, feature extraction, segmentation, image analysis, reconstruction, manual tracing, thresholding
Using an Automated 3D-tracking System to Record Individual and Shoals of Adult Zebrafish
Like many aquatic animals, zebrafish (Danio rerio
) moves in a 3D space. It is thus preferable to use a 3D recording system to study its behavior. The presented automatic video tracking system accomplishes this by using a mirror system and a calibration procedure that corrects for the considerable error introduced by the transition of light from water to air. With this system it is possible to record both single and groups of adult zebrafish. Before use, the system has to be calibrated. The system consists of three modules: Recording, Path Reconstruction, and Data Processing. The step-by-step protocols for calibration and using the three modules are presented. Depending on the experimental setup, the system can be used for testing neophobia, white aversion, social cohesion, motor impairments, novel object exploration etc
. It is especially promising as a first-step tool to study the effects of drugs or mutations on basic behavioral patterns. The system provides information about vertical and horizontal distribution of the zebrafish, about the xyz-components of kinematic parameters (such as locomotion, velocity, acceleration, and turning angle) and it provides the data necessary to calculate parameters for social cohesions when testing shoals.
Behavior, Issue 82, neuroscience, Zebrafish, Danio rerio, anxiety, Shoaling, Pharmacology, 3D-tracking, MK801
Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking
Institutions: Yale University, Yale University, Yale University, Yale University, Massachusetts General Hospital, University of California, Irvine.
We describe experimental and statistical steps for creating dopamine movies of the brain from dynamic PET data. The movies represent minute-to-minute fluctuations of dopamine induced by smoking a cigarette. The smoker is imaged during a natural smoking experience while other possible confounding effects (such as head motion, expectation, novelty, or aversion to smoking repeatedly) are minimized.
We present the details of our unique analysis. Conventional methods for PET analysis estimate time-invariant kinetic model parameters which cannot capture short-term fluctuations in neurotransmitter release. Our analysis - yielding a dopamine movie - is based on our work with kinetic models and other decomposition techniques that allow for time-varying parameters 1-7
. This aspect of the analysis - temporal-variation - is key to our work. Because our model is also linear in parameters, it is practical, computationally, to apply at the voxel level. The analysis technique is comprised of five main steps: pre-processing, modeling, statistical comparison, masking and visualization. Preprocessing is applied to the PET data with a unique 'HYPR' spatial filter 8
that reduces spatial noise but preserves critical temporal information. Modeling identifies the time-varying function that best describes the dopamine effect on 11
C-raclopride uptake. The statistical step compares the fit of our (lp-ntPET) model 7
to a conventional model 9
. Masking restricts treatment to those voxels best described by the new model. Visualization maps the dopamine function at each voxel to a color scale and produces a dopamine movie. Interim results and sample dopamine movies of cigarette smoking are presented.
Behavior, Issue 78, Neuroscience, Neurobiology, Molecular Biology, Biomedical Engineering, Medicine, Anatomy, Physiology, Image Processing, Computer-Assisted, Receptors, Dopamine, Dopamine, Functional Neuroimaging, Binding, Competitive, mathematical modeling (systems analysis), Neurotransmission, transient, dopamine release, PET, modeling, linear, time-invariant, smoking, F-test, ventral-striatum, clinical techniques
From Fast Fluorescence Imaging to Molecular Diffusion Law on Live Cell Membranes in a Commercial Microscope
Institutions: Scuola Normale Superiore, Instituto Italiano di Tecnologia, University of California, Irvine.
It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn’t need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn
-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.
Bioengineering, Issue 92, fluorescence, protein dynamics, lipid dynamics, membrane heterogeneity, transient confinement, single molecule, GFP
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Institutions: University of Calgary , University of Calgary .
We demonstrate methods for the detection of architectural distortion in prior mammograms of interval-cancer cases based on analysis of the orientation of breast tissue patterns in mammograms. We hypothesize that architectural distortion modifies the normal orientation of breast tissue patterns in mammographic images before the formation of masses or tumors. In the initial steps of our methods, the oriented structures in a given mammogram are analyzed using Gabor filters and phase portraits to detect node-like sites of radiating or intersecting tissue patterns. Each detected site is then characterized using the node value, fractal dimension, and a measure of angular dispersion specifically designed to represent spiculating patterns associated with architectural distortion.
Our methods were tested with a database of 106 prior mammograms of 56 interval-cancer cases and 52 mammograms of 13 normal cases using the features developed for the characterization of architectural distortion, pattern classification via
quadratic discriminant analysis, and validation with the leave-one-patient out procedure. According to the results of free-response receiver operating characteristic analysis, our methods have demonstrated the capability to detect architectural distortion in prior mammograms, taken 15 months (on the average) before clinical diagnosis of breast cancer, with a sensitivity of 80% at about five false positives per patient.
Medicine, Issue 78, Anatomy, Physiology, Cancer Biology, angular spread, architectural distortion, breast cancer, Computer-Assisted Diagnosis, computer-aided diagnosis (CAD), entropy, fractional Brownian motion, fractal dimension, Gabor filters, Image Processing, Medical Informatics, node map, oriented texture, Pattern Recognition, phase portraits, prior mammograms, spectral analysis
Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
Institutions: Dartmouth College, Dartmouth College, Dartmouth College, University of Birmingham .
Small animal fluorescence molecular imaging (FMI) can be a powerful tool for preclinical drug discovery and development studies1
. However, light absorption by tissue chromophores (e.g., hemoglobin, water, lipids, melanin) typically limits optical signal propagation through thicknesses larger than a few millimeters2
. Compared to other visible wavelengths, tissue absorption for red and near-infrared (near-IR) light absorption dramatically decreases and non-elastic scattering becomes the dominant light-tissue interaction mechanism. The relatively recent development of fluorescent agents that absorb and emit light in the near-IR range (600-1000 nm), has driven the development of imaging systems and light propagation models that can achieve whole body three-dimensional imaging in small animals3
Despite great strides in this area, the ill-posed nature of diffuse fluorescence tomography remains a significant problem for the stability, contrast recovery and spatial resolution of image reconstruction techniques and the optimal approach to FMI in small animals has yet to be agreed on. The majority of research groups have invested in charge-coupled device (CCD)-based systems that provide abundant tissue-sampling but suboptimal sensitivity4-9
, while our group and a few others10-13
have pursued systems based on very high sensitivity detectors, that at this time allow dense tissue sampling to be achieved only at the cost of low imaging throughput. Here we demonstrate the methodology for applying single-photon detection technology in a fluorescence tomography system to localize a cancerous brain lesion in a mouse model.
The fluorescence tomography (FT) system employed single photon counting using photomultiplier tubes (PMT) and information-rich time-domain light detection in a non-contact conformation11
. This provides a simultaneous collection of transmitted excitation and emission light, and includes automatic fluorescence excitation exposure control14
, laser referencing, and co-registration with a small animal computed tomography (microCT) system15
. A nude mouse model was used for imaging. The animal was inoculated orthotopically with a human glioma cell line (U251) in the left cerebral hemisphere and imaged 2 weeks later. The tumor was made to fluoresce by injecting a fluorescent tracer, IRDye 800CW-EGF (LI-COR Biosciences, Lincoln, NE) targeted to epidermal growth factor receptor, a cell membrane protein known to be overexpressed in the U251 tumor line and many other cancers18
. A second, untargeted fluorescent tracer, Alexa Fluor 647 (Life Technologies, Grand Island, NY) was also injected to account for non-receptor mediated effects on the uptake of the targeted tracers to provide a means of quantifying tracer binding and receptor availability/density27
. A CT-guided, time-domain algorithm was used to reconstruct the location of both fluorescent tracers (i.e.
, the location of the tumor) in the mouse brain and their ability to localize the tumor was verified by contrast-enhanced magnetic resonance imaging.
Though demonstrated for fluorescence imaging in a glioma mouse model, the methodology presented in this video can be extended to different tumor models in various small animal models potentially up to the size of a rat17
Cancer Biology, Issue 65, Medicine, Physics, Molecular Biology, fluorescence, glioma, light transport, tomography, CT, molecular imaging, epidermal growth factor receptor, biomarker
Coherence between Brain Cortical Function and Neurocognitive Performance during Changed Gravity Conditions
Institutions: German Sport University Cologne, University of Toronto, Queensland University of Technology, Gilching, Germany.
Previous studies of cognitive, mental and/or motor processes during short-, medium- and long-term weightlessness have only been descriptive in nature, and focused on psychological aspects. Until now, objective observation of neurophysiological parameters has not been carried out - undoubtedly because the technical and methodological means have not been available -, investigations into the neurophysiological effects of weightlessness are in their infancy (Schneider et al.
While imaging techniques such as positron emission tomography (PET) and magnetic resonance imaging (MRI) would be hardly applicable in space, the non-invasive near-infrared spectroscopy (NIRS) technique represents a method of mapping hemodynamic processes in the brain in real time that is both relatively inexpensive and that can be employed even under extreme conditions. The combination with electroencephalography (EEG) opens up the possibility of following the electrocortical processes under changing gravity conditions with a finer temporal resolution as well as with deeper localization, for instance with electrotomography (LORETA).
Previous studies showed an increase of beta frequency activity under normal gravity conditions and a decrease under weightlessness conditions during a parabolic flight (Schneider et al.
2008a+b). Tilt studies revealed different changes in brain function, which let suggest, that changes in parabolic flight might reflect emotional processes rather than hemodynamic changes. However, it is still unclear whether these are effects of changed gravity or hemodynamic changes within the brain. Combining EEG/LORETA and NIRS should for the first time make it possible to map the effect of weightlessness and reduced gravity on both hemodynamic and electrophysiological processes in the brain. Initially, this is to be done as part of a feasibility study during a parabolic flight. Afterwards, it is also planned to use both techniques during medium- and long-term space flight.
It can be assumed that the long-term redistribution of the blood volume and the associated increase in the supply of oxygen to the brain will lead to changes in the central nervous system that are also responsible for anaemic processes, and which can in turn reduce performance (De Santo et al.
2005), which means that they could be crucial for the success and safety of a mission (Genik et al.
2005, Ellis 2000).
Depending on these results, it will be necessary to develop and employ extensive countermeasures. Initial results for the MARS500 study suggest that, in addition to their significance in the context of the cardiovascular and locomotor systems, sport and physical activity can play a part in improving neurocognitive parameters. Before this can be fully established, however, it seems necessary to learn more about the influence of changing gravity conditions on neurophysiological processes and associated neurocognitive impairment.
Neuroscience, Issue 51, EEG, NIRS, electrotomography, parabolic flight, weightlessness, imaging, cognitive performance
Determining 3D Flow Fields via Multi-camera Light Field Imaging
Institutions: Brigham Young University, Naval Undersea Warfare Center, Newport, RI.
In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and observed phenomena in fluid flows. Thus, a need exists for an accessible method capable of resolving three-dimensional (3D) data sets for a range of problems. We present a novel technique for performing quantitative 3D imaging of many types of flow fields. The 3D technique enables investigation of complicated velocity fields and bubbly flows. Measurements of these types present a variety of challenges to the instrument. For instance, optically dense bubbly multiphase flows cannot be readily imaged by traditional, non-invasive flow measurement techniques due to the bubbles occluding optical access to the interior regions of the volume of interest. By using Light Field Imaging we are able to reparameterize images captured by an array of cameras to reconstruct a 3D volumetric map for every time instance, despite partial occlusions in the volume. The technique makes use of an algorithm known as synthetic aperture (SA) refocusing, whereby a 3D focal stack is generated by combining images from several cameras post-capture 1
. Light Field Imaging allows for the capture of angular as well as spatial information about the light rays, and hence enables 3D scene reconstruction. Quantitative information can then be extracted from the 3D reconstructions using a variety of processing algorithms. In particular, we have developed measurement methods based on Light Field Imaging for performing 3D particle image velocimetry (PIV), extracting bubbles in a 3D field and tracking the boundary of a flickering flame. We present the fundamentals of the Light Field Imaging methodology in the context of our setup for performing 3DPIV of the airflow passing over a set of synthetic vocal folds, and show representative results from application of the technique to a bubble-entraining plunging jet.
Physics, Issue 73, Mechanical Engineering, Fluid Mechanics, Engineering, synthetic aperture imaging, light field, camera array, particle image velocimetry, three dimensional, vector fields, image processing, auto calibration, vocal chords, bubbles, flow, fluids
Monitoring Tumor Metastases and Osteolytic Lesions with Bioluminescence and Micro CT Imaging
Institutions: Caliper Life Sciences.
Following intracardiac delivery of MDA-MB-231-luc-D3H2LN cells to Nu/Nu mice, systemic metastases developed in the injected animals. Bioluminescence imaging using IVIS Spectrum was employed to monitor the distribution and development of the tumor cells following the delivery procedure including DLIT reconstruction to measure the tumor signal and its location.
Development of metastatic lesions to the bone tissues triggers osteolytic activity and lesions to tibia and femur were evaluated longitudinally using micro CT. Imaging was performed using a Quantum FX micro CT system with fast imaging and low X-ray dose. The low radiation dose allows multiple imaging sessions to be performed with a cumulative X-ray dosage far below LD50. A mouse imaging shuttle device was used to sequentially image the mice with both IVIS Spectrum and Quantum FX achieving accurate animal positioning in both the bioluminescence and CT images. The optical and CT data sets were co-registered in 3-dimentions using the Living Image 4.1 software. This multi-mode approach allows close monitoring of tumor growth and development simultaneously with osteolytic activity.
Medicine, Issue 50, osteolytic lesions, micro CT, tumor, bioluminescence, in vivo, imaging, IVIS, luciferase, low dose, co-registration, 3D reconstruction
Functional Mapping with Simultaneous MEG and EEG
Institutions: MGH - Massachusetts General Hospital.
We use magnetoencephalography (MEG) and electroencephalography (EEG) to locate and determine the temporal evolution in brain areas involved in the processing of simple sensory stimuli. We will use somatosensory stimuli to locate the hand somatosensory areas, auditory stimuli to locate the auditory cortices, visual stimuli in four quadrants of the visual field to locate the early visual areas. These type of experiments are used for functional mapping in epileptic and brain tumor patients to locate eloquent cortices. In basic neuroscience similar experimental protocols are used to study the orchestration of cortical activity. The acquisition protocol includes quality assurance procedures, subject preparation for the combined MEG/EEG study, and acquisition of evoked-response data with somatosensory, auditory, and visual stimuli. We also demonstrate analysis of the data using the equivalent current dipole model and cortically-constrained minimum-norm estimates. Anatomical MRI data are employed in the analysis for visualization and for deriving boundaries of tissue boundaries for forward modeling and cortical location and orientation constraints for the minimum-norm estimates.
JoVE neuroscience, Issue 40, neuroscience, brain, MEG, EEG, functional imaging