Arthur W. Wetzel

Network anatomy and in vivo physiology of visual cortical neurons

In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neurons function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property—the preferred stimulus orientation—of a group of neurons in the mouse primary visual cortex. Large-scale electron microscopy of serial thin sections was then used to trace a portion of these neurons’ local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.

Design and analysis of a content-based pathology image retrieval system

A prototype, content-based image retrieval system has been built employing a client/server architecture to access supercomputing power from the physicians desktop. The system retrieves images and their associated annotations from a networked microscopic pathology image database based on content similarity to user supplied query images. Similarity is evaluated based on four image feature types: color histogram, image texture, Fourier coefficients, and wavelet coefficients, using the vector dot product as a distance metric. Current retrieval accuracy varies across pathological categories depending on the number of available training samples and the effectiveness of the feature set. The distance measure of the search algorithm was validated by agglomerative cluster analysis in light of the medical domain knowledge. Results show a correlation between pathological significance and the image document distance value generated by the computer algorithm. This correlation agrees with observed visual similarity. This validation method has an advantage over traditional statistical evaluation methods when sample size is small and where domain knowledge is important. A multi-dimensional scaling analysis shows a low dimensionality nature of the embedded space for the current test set.

The Fuzzy Logic of Network Connectivity in Mouse Visual Thalamus.

In an attempt to chart parallel sensory streams passing through the visual thalamus, we acquired a 100-trillion-voxel electron microscopy (EM) dataset and identified cohorts of retinal ganglion cell axons (RGCs) that innervated each of a diverse group of postsynaptic thalamocortical neurons (TCs). Tracing branches of these axons revealed the set of TCs innervated by each RGC cohort. Instead of finding separate sensory pathways, we found a single large network that could not be easily subdivided because individual RGCs innervated different kinds of TCs and different kinds of RGCs co-innervated individual TCs. We did find conspicuous network subdivisions organized on the basis of dendritic rather than neuronal properties. This work argues that, in the thalamus, neural circuits are not based on a canonical set of connections between intrinsically different neuronal types but, rather, may arise by experience-based mixing of different kinds of inputs onto individual postsynaptic cells.

Factors Influencing the Emergence and Spread of HIV Drug Resistance Arising from Rollout of Antiretroviral Pre-Exposure Prophylaxis (PrEP)

Background The potential for emergence and spread of HIV drug resistance from rollout of antiretroviral (ARV) pre-exposure prophylaxis (PrEP) is an important public health concern. We investigated determinants of HIV drug resistance prevalence after PrEP implementation through mathematical modeling. Methodology A model incorporating heterogeneity in age, gender, sexual activity, HIV infection status, stage of disease, PrEP coverage/discontinuation, and HIV drug susceptibility, was designed to simulate the impact of PrEP on HIV prevention and drug resistance in a sub-Saharan epidemic. Principal Findings Analyses suggest that the prevalence of HIV drug resistance is influenced most by the extent and duration of inadvertent PrEP use in individuals already infected with HIV. Other key factors affecting drug resistance prevalence include the persistence time of transmitted resistance and the duration of inadvertent PrEP use in individuals who become infected on PrEP. From uncertainty analysis, the median overall prevalence of drug resistance at 10 years was predicted to be 9.2% (interquartile range 6.9%–12.2%). An optimistic scenario of 75% PrEP efficacy, 60% coverage of the susceptible population, and 5% inadvertent PrEP use predicts a rise in HIV drug resistance prevalence to only 2.5% after 10 years. By contrast, in a pessimistic scenario of 25% PrEP efficacy, 15% population coverage, and 25% inadvertent PrEP use, resistance prevalence increased to over 40%. Conclusions Inadvertent PrEP use in previously-infected individuals is the major determinant of HIV drug resistance prevalence arising from PrEP. Both the rate and duration of inadvertent PrEP use are key factors. PrEP rollout programs should include routine monitoring of HIV infection status to limit the spread of drug resistance.

Whole-brain serial-section electron microscopy in larval zebrafish

High-resolution serial-section electron microscopy (ssEM) makes it possible to investigate the dense meshwork of axons, dendrites, and synapses that form neuronal circuits. However, the imaging scale required to comprehensively reconstruct these structures is more than ten orders of magnitude smaller than the spatial extents occupied by networks of interconnected neurons, some of which span nearly the entire brain. Difficulties in generating and handling data for large volumes at nanoscale resolution have thus restricted vertebrate studies to fragments of circuits. These efforts were recently transformed by advances in computing, sample handling, and imaging techniques, but high-resolution examination of entire brains remains a challenge. Here, we present ssEM data for the complete brain of a larval zebrafish (Danio rerio) at 5.5 days post-fertilization. Our approach utilizes multiple rounds of targeted imaging at different scales to reduce acquisition time and data management requirements. The resulting dataset can be analysed to reconstruct neuronal processes, permitting us to survey all myelinated axons (the projectome). These reconstructions enable precise investigations of neuronal morphology, which reveal remarkable bilateral symmetry in myelinated reticulospinal and lateral line afferent axons. We further set the stage for whole-brain structure–function comparisons by co-registering functional reference atlases and in vivo two-photon fluorescence microscopy data from the same specimen. All obtained images and reconstructions are provided as an open-access resource.

Computational Aspects of Pathology Image Classification and Retrieval

We are investigating the role of high performance computing for support of a comprehensive pathology image atlas. The primary computing component is a database access mechanism providing retrieval by content based image matching (CBIR) along with traditional term based queries. An organization based on information theoretic and Bayesian principles using decision trees and signature files is being developed. The essential role of HPC is the discovery, selection, and optimization of medically useful image feature sets via genetic algorithm and simulated annealing methods. This paper outlines the problem area along with aspects of the underlying theoretical basis and distinguishing computing characteristics. Efficiency of key portions of the computations can be greatly improved by using parallelism within the computer word length using bit counting instructions to implement voting and multimedia style instruction sets for low level image processing.

Left ventricle volume measurements in cardiac micro-CT: The impact of radiation dose and contrast agent

Micro-CT-based cardiac function estimation in small animals requires measurement of left ventricle (LV) volume at multiple time points during the cardiac cycle. Measurement accuracy depends on the image resolution, its signal and noise properties, and the analysis procedure. This work compares the accuracy of the Otsu thresholding and a region sampled binary mixture approach, for live mouse LV volume measurement using 100 microm resolution datasets. We evaluate both analysis methods after varying the volume of injected contrast agent and the number of projections used for CT reconstruction with a goal of permitting reduced levels of both X-ray and contrast agent doses.

High-resolution reconstruction of fluorescent inclusions in mouse thorax using anatomically guided sampling and parallel Monte Carlo computing

We present a method for high-resolution reconstruction of fluorescent images of the mouse thorax. It features an anatomically guided sampling method to retrospectively eliminate problematic data and a parallel Monte Carlo software package to compute the Jacobian matrix for the inverse problem. The proposed method was capable of resolving microliter-sized femtomole amount of quantum dot inclusions closely located in the middle of the mouse thorax. The reconstruction was verified against co-registered micro-CT data. Using the proposed method, the new system achieved significantly higher resolution and sensitivity compared to our previous system consisting of the same hardware. This method can be applied to any system utilizing similar imaging principles to improve imaging performance.

Photo-realistic representation of anatomical structures for medical education by fusion of volumetric and surface image data

We have produced improved photo-realistic views of anatomical structures for medical education combining data from photographic images of anatomical surfaces with optical, CT and MRI volumetric data such as provided by the NLM Visible Human Project. Volumetric data contains the information needed to construct 3D geometrical models of anatomical structures, but cannot provide a realistic appearance for surfaces. Nieder has captured high quality photographic sequences of anatomy specimens over a range of rotational angles. These have been assembled into QuickTime VR Object movies that can be viewed statically or dynamically. We reuse this surface imagery to produce textures and surface reflectance maps for 3D anatomy models to allow viewing from any orientation and lighting condition. Because the volumetric data comes from different individuals than the surface images, we have to warp these data into alignment. Currently we do not use structured lighting or other direct 3D surface information, so surface shape is recovered from rotational sequences using silhouettes and texture correlations. The results of this work improves the appearance and generality of models, used for anatomy instruction with the PSC Volume Browser.

Design of a high-speed slide imaging system for pathology

Digital imaging has definite advantages for many areas of anatomic pathology, including documentation, education, and telemedicine. Despite these benefits, the majority of diagnoses are made via manual examination of slides using a light microscope. The primary factor limiting the clinical use of digital images is the amount of time required to image an entire slide. This paper describes an imaging system that overcomes this limitation. Pulsed light illumination is the key that allows fast continuous slide motion during image capture, reducing capture time to minutes rather than hours. A position sensor and a timing circuit provide accurate stage positioning and timing signals, enabling simple and accurate assembly of a full slide montage. Preliminary studies indicate that diagnoses made from the resulting images agree with those made using a microscope.