A Wireless Multi-Channel Recording System for Freely Behaving Mice and Rats

To understand the neural basis of behavior, it is necessary to record brain activity in freely moving animals. Advances in implantable multi-electrode array technology have enabled researchers to record the activity of neuronal ensembles from multiple brain regions. The full potential of this approach is currently limited by reliance on cable tethers, with bundles of wires connecting the implanted electrodes to the data acquisition system while impeding the natural behavior of the animal. To overcome these limitations, here we introduce a multi-channel wireless headstage system designed for small animals such as rats and mice. A variety of single unit and local field potential signals were recorded from the dorsal striatum and substantia nigra in mice and the ventral striatum and prefrontal cortex simultaneously in rats. This wireless system could be interfaced with commercially available data acquisition systems, and the signals obtained were comparable in quality to those acquired using cable tethers. On account of its small size, light weight, and rechargeable battery, this wireless headstage system is suitable for studying the neural basis of natural behavior, eliminating the need for wires, commutators, and other limitations associated with traditional tethered recording systems.     

A Novel Extended Granger Causal Model Approach Demonstrates Brain Hemispheric Differences during Face Recognition Learning

Two main approaches in exploring causal relationships in biological systems using time-series data are the application of Dynamic Causal model (DCM) and Granger Causal model (GCM). These have been extensively applied to brain imaging data and are also readily applicable to a wide range of temporal changes involving genes, proteins or metabolic pathways. However, these two approaches have always been considered to be radically different from each other and therefore used independently. Here we present a novel approach which is an extension of Granger Causal model and also shares the features of the bilinear approximation of Dynamic Causal model. We have first tested the efficacy of the extended GCM by applying it extensively in toy models in both time and frequency domains and then applied it to local field potential recording data collected from in vivo multi-electrode array experiments. We demonstrate face discrimination learning-induced changes in inter- and intra-hemispheric connectivity and in the hemispheric predominance of theta and gamma frequency oscillations in sheep inferotemporal cortex. The results provide the first evidence for connectivity changes between and within left and right inferotemporal cortexes as a result of face recognition learning.     

Filtering noise for synchronised activity in multi-trial electrophysiology data using Wiener and Kalman filters

Novel approaches to effectively reduce noise in data recorded from multi-trial physiology experiments have been investigated using two-dimensional filtering methods, adaptive Wiener filtering and reduced update Kalman filtering. Test data based on signal and noise model consisting of different conditions of signal components mixed with noise have been considered with filtering effects evaluated using analysis of frequency coherence and of time-dependent coherence. Various situations that may affect the filtering results have been explored and reveal that Wiener and Kalman filtering can considerably improve the coherence values between two channels of multi-trial data and suppress uncorrelated components. We have extended our approach to experimental data: multi-electrode array (MEA) local field potential (LFPs) recordings from the inferotemporal cortex of sheep and LFP vs. electromyogram (LFP-EMG) recording data during resting tremor in Parkinson’s disease patients. Finally general procedures for implementation of these filtering techniques are described.     

Multi-Reception Strategy with Improved SNR for Multichannel MR Imaging

A multi-reception strategy with extended GRAPPA is proposed in this work to improve MR imaging performance at ultra-high field MR systems with limited receiver channels. In this method, coil elements are separated to two or more groups under appropriate grouping criteria. Those groups are enabled in sequence for imaging first, and then parallel acquisition is performed to compensate for the redundant scan time caused by the multiple receptions. To efficiently reconstruct the data acquired from elements of each group, a specific extended GRAPPA was developed. This approach was evaluated by using a 16-element head array on a 7 Tesla whole-body MRI scanner with 8 receive channels. The in-vivo experiments demonstrate that with the same scan time, the 16-element array with twice receptions and acceleration rate of 2 can achieve significant SNR gain in the periphery area of the brain and keep nearly the same SNR in the center area over an eight-element array, which indicates the proposed multi-reception strategy and extended GRAPPA are feasible to improve image quality for MRI systems with limited receive channels. This study also suggests that it is advantageous for a MR system with N receiver channels to utilize a coil array with more than N elements if an appropriate acquisition strategy is applied.     

Single Molecule Analysis Research Tool (SMART): an integrated approach for analyzing single molecule data

Single molecule studies have expanded rapidly over the past decade and have the ability to provide an unprecedented level of understanding of biological systems. A common challenge upon introduction of novel, data-rich approaches is the management, processing, and analysis of the complex data sets that are generated. We provide a standardized approach for analyzing these data in the freely available software package SMART: Single Molecule Analysis Research Tool. SMART provides a format for organizing and easily accessing single molecule data, a general hidden Markov modeling algorithm for fitting an array of possible models specified by the user, a standardized data structure and graphical user interfaces to streamline the analysis and visualization of data. This approach guides experimental design, facilitating acquisition of the maximal information from single molecule experiments. SMART also provides a standardized format to allow dissemination of single molecule data and transparency in the analysis of reported data.     

On the global CRISPR array behavior in class I systems

Background

Much effort is underway to build and upgrade databases and tools related to occurrence, diversity, and characterization of CRISPR-Cas systems. As microbial communities and their genome complements are unearthed, much emphasis has been placed on details of individual strains and model systems within the CRISPR-Cas classification, and that collection of information as a whole affords the opportunity to analyze CRISPR-Cas systems from a quantitative perspective to gain insight into distribution of CRISPR array sizes across the different classes, types and subtypes. CRISPR diversity, nomenclature, occurrence, and biological functions have generated a plethora of data that created a need to understand the size and distribution of these various systems to appreciate their features and complexity.

Results

By utilizing a statistical framework and visual analytic techniques, we have been able to test several hypotheses about CRISPR loci in bacterial class I systems. Quantitatively, though CRISPR loci can expand to hundreds of spacers, the mean and median sizes are 40 and 25, respectively, reflecting rather modest acquisition and/or retention overall. Histograms uncovered that CRISPR array size displayed a parametric distribution, which was confirmed by a goodness-of fit test. Mapping the frequency of CRISPR loci on a standardized chromosome plot revealed that CRISPRs have a higher probability of occurring at clustered locations along the positive or negative strand. Lastly, when multiple arrays occur in a particular system, the size of a particular CRISPR array varies with its distance from the cas operon, reflecting acquisition and expansion biases.

Conclusions

This study establishes that bacterial Class I CRISPR array size tends to follow a geometric distribution; these CRISPRs are not randomly distributed along the chromosome; and the CRISPR array closest to the cas genes is typically larger than loci in trans. Overall, we provide an analytical framework to understand the features and behavior of CRISPR-Cas systems through a quantitative lens.

Reviewers

This article was reviewed by Eugene Koonin (NIH-NCBI) and Uri Gophna (Tel Aviv University).

     

High-resolution color video cytophotometry

Comparison was made between cytophotometric measurements obtained using two data acquisition systems, one a microphotometer and the other a rapid video camera system, to ascertain whether the degradation of data with the faster video acquisition system still results in recorded images of sufficient quality to permit computer discrimination between cells of very similar appearance. Normal-appearing intermediate cells from cases with normal cytology and those from patients with dysplasia or malignant disease, as well as the subvisual markers within these cells that have rendered them capable of cytophotometric discrimination, were used for the study. Comparison of the data recorded by the two systems indicates that the diagnostic information is preserved in the change-over to a full-field, video-rate scanning system, with differences in the data caused primarily by differences in the spectral response of the two systems. This was reflected in the substantial differences observed in the color-related features and the lesser differences seen in the textural features, while the morphometric features (outline and shape) were virtually unaffected. The differences were primarily expressed on a cell-to-cell basis; in sets of about 300 cells, which would be used in patient-to-patient comparisons, the feature values showed remarkable consistency between the two systems.     

Breeding Systems of Three Tree Ferns: Alsophila firma (Cyatheaceae), Cyathea stipularis (Cyatheaceae), and Lophosoria quadripinnata (Lophosoriaceae)

Abstract Breeding-system data have been available for a large number and diverse array of angio-sperms for a relatively long time. In contrast, breeding systems of ferns and their allies (pteridophytes) have only recently been examined, and breeding-system data from natural populations of sporophytes are still lacking for pteridophytes representing many life-history strategies. Few studies, for example, have examined breeding systems of tropical pteridophytes, and no breeding-system data are available for tree ferns. We therefore examined the breeding systems of three species of tree ferns from Costa Rica, Alsophila firma (Cyatheaceae), Cyathea stipularis (Cyatheaceae), and Lophosoria quadripinnata (Lophosoriaceae) using enzyme electro-phoresis. Genetic data were used to estimate intragametophytic self-fertilization and F , the fixation index. Analysis of genetic data indicates that the gametophytes of these three species predominantly cross-fertilize; all three species would be characterized as outcrossers. However, some population-to-population variation in breeding system was detected in all three species. Outcrossing also typifies a diverse array of temperate ferns. Thus, despite the potential for self-fertilization, outcrossing appears to characterize the majority of pteridophytes representing a variety of evolutionary lineages, life-history strategies, and environments.     

High-resolution color video cytophotometry

Comparison was made between cytophotometric measurements obtained using two data acquisition systems, one a microphotometer and the other a rapid video camera system, to ascertain whether the degradation of data with the faster video acquisition system still results in recorded images of sufficient quality to permit computer discrimination between cells of very similar appearance. Normal-appearing intermediate cells from cases with normal cytology and those from patients with dysplasia or malignant disease, as well as the subvisual markers within these cells that have rendered them capable of cytophotometric discrimination, were used for the study. Comparison of the data recorded by the two systems indicates that the diagnostic information is preserved in the change-over to a full-field, video-rate scanning system, with differences in the data caused primarily by differences in the spectral response of the two systems. This was reflected in the substantial differences observed in the color-related features and the lesser differences seen in the textural features, while the morphometric features (outline and shape) were virtually unaffected. The differences were primarily expressed on a cell-to-cell basis; in sets of about 300 cells, which would be used in patient-to-patient comparisons, the feature values showed remarkable consistency between the two systems.     

Epidemiological and evolutionary consequences of different types of CRISPR-Cas systems

Bacteria have adaptive immunity against viruses (phages) in the form of CRISPR-Cas immune systems. Currently, 6 types of CRISPR-Cas systems are known and the molecular study of three of these has revealed important molecular differences. It is unknown if and how these molecular differences change the outcome of phage infection and the evolutionary pressure the CRISPR-Cas systems faces. To determine the importance of these molecular differences, we model a phage outbreak entering a population defending exclusively with a type I/II or a type III CRISPR-Cas system. We show that for type III CRISPR-Cas systems, rapid phage extinction is driven by the probability to acquire at least one resistance spacer. However, for type I/II CRISPR-Cas systems, rapid phage extinction is characterized by an a threshold-like behaviour: any acquisition probability below this threshold leads to phage survival whereas any acquisition probability above it, results in phage extinction. We also show that in the absence of autoimmunity, high acquisition rates evolve. However, when CRISPR-Cas systems are prone to autoimmunity, intermediate levels of acquisition are optimal during a phage outbreak. As we predict an optimal probability of spacer acquisition 2 factors of magnitude above the one that has been measured, we discuss the origin of such a discrepancy. Finally, we show that in a biologically relevant parameter range, a type III CRISPR-Cas system can outcompete a type I/II CRISPR-Cas system with a slightly higher probability of acquisition.     

Determination of multiple redox-active compounds by high-performance liquid chromatography with coulometric multi-electrode array system

Studies of the antioxidant defense system and the related metabolic pathways are often complicated by cumbersome analytical methods, which require separate and multi-step extraction and chemical reaction procedures. Further, assaying multiple parameters is limited because of the usual small sample amounts. High-performance liquid chromatography coupled with a coulometric multi-electrode array system provides us high specificity and sensitivity to measure electrochemically oxidizable compounds in biological samples. In contrast to previously reported methods with two columns in series and a complex gradient elution profile, we have developed an automated procedure to simultaneously measure multiple redox-active low-molecular weight compounds that utilizes a single column with a simplified binary gradient profile. No other chemical reactions are necessary. In order to reduce the running time and yet achieve a reproducible retention time by the auto sampler injection, our gradient elution profile was modified to produce a shorter equilibration time, stable retention time, and a reduced cost per test.     

A Simple and Accurate Model to Predict Responses to Multi-electrode Stimulation in the Retina

Implantable electrode arrays are widely used in therapeutic stimulation of the nervous system (e.g. cochlear, retinal, and cortical implants). Currently, most neural prostheses use serial stimulation (i.e. one electrode at a time) despite this severely limiting the repertoire of stimuli that can be applied. Methods to reliably predict the outcome of multi-electrode stimulation have not been available. Here, we demonstrate that a linear-nonlinear model accurately predicts neural responses to arbitrary patterns of stimulation using in vitro recordings from single retinal ganglion cells (RGCs) stimulated with a subretinal multi-electrode array. In the model, the stimulus is projected onto a low-dimensional subspace and then undergoes a nonlinear transformation to produce an estimate of spiking probability. The low-dimensional subspace is estimated using principal components analysis, which gives the neuron’s electrical receptive field (ERF), i.e. the electrodes to which the neuron is most sensitive. Our model suggests that stimulation proportional to the ERF yields a higher efficacy given a fixed amount of power when compared to equal amplitude stimulation on up to three electrodes. We find that the model captures the responses of all the cells recorded in the study, suggesting that it will generalize to most cell types in the retina. The model is computationally efficient to evaluate and, therefore, appropriate for future real-time applications including stimulation strategies that make use of recorded neural activity to improve the stimulation strategy.     

Open, reconfigurable cytometric acquisition system: ORCAS.

A digital signal processing (DSP)-based digital data acquisition system has been developed to support novel flow cytometry efforts. The system flexibility includes how it detects, captures, and processes event data. Custom data capture boards utilizing analog to digital converters (ADCs) and field programmable gate arrays (FPGA) detect events and capture correlated event data. A commercial DSP board processes the captured data and sends the results over the IEEE 1394 bus to the host computer that provides a user interface for acquisition, display, analysis, and storage. The system collects list mode data, correlated pulse shapes, or streaming data from a variety of detector types using Linux, Mac OS X, and Windows host computers. It extracts pulse features not found on commercial systems with excellent sensitivity and linearity over a wide dynamic range. List mode data are saved in FCS 3.0 formatted files while streaming or correlated waveform data are saved in custom format files for postprocessing. Open, reconfigurable cytometric acquisition system is compact, scaleable, flexible, and modular. Programmable feature extraction algorithms have exciting possibilities for both new and existing applications. The recent availability of a commercial data capture board will enable general availability of similar systems.     

Extracting kinetic rate constants from surface plasmon resonance array systems

Surface plasmon resonance imaging systems, such as Flexchip from Biacore, are capable of monitoring hundreds of reaction spots simultaneously within a single flow cell. Interpreting the binding kinetics in a large-format flow cell presents a number of potential challenges, including accounting for mass transport effects and spot-to-spot sample depletion. We employed a combination of computer simulations and experimentation to characterize these effects across the spotted array and established that a simple two-compartment model may be used to accurately extract intrinsic rate constants from the array under mass transport-limited conditions. Using antibody systems, we demonstrate that the spot-to-spot variability in the binding kinetics was <9%. We also illustrate the advantage of globally fitting binding data from multiple spots within an array for a system that is mass transport limited.     

神经电生理信号多道同步采集和分析系统

单细胞多点同步记录技术在国内外已经被广泛应用,但在国内仍缺乏与国产或日产细胞电生理记录仪器相匹配的多通道同步生物电信号采集与分析系统。本文介绍了新近研制的可进行双通道甚至晚多通道细胞电生理信号采集的神经细胞电生理信号采集与分析系统,及其关键技术及实现方法和应用实例。     

Neural correlations, population coding and computation

How the brain encodes information in population activity, and how it combines and manipulates that activity as it carries out computations, are questions that lie at the heart of systems neuroscience. During the past decade, with the advent of multi-electrode recording and improved theoretical models, these questions have begun to yield answers. However, a complete understanding of neuronal variability, and, in particular, how it affects population codes, is missing. This is because variability in the brain is typically correlated, and although the exact effects of these correlations are not known, it is known that they can be large. Here, we review studies that address the interaction between neuronal noise and population codes, and discuss their implications for population coding in general.     

A picture is worth a thousand words: Genomics to phenomics in the yeast Saccharomyces cerevisiae

Large scale cell biological experiments are beginning to be applied as a systems-level approach to decipher mechanisms that govern cellular function in health and disease. The use of automated microscopes combined with digital imaging, machine learning and other analytical tools has enabled high-content screening (HCS) in a variety of experimental systems. Successful HCS screens demand careful attention to assay development, data acquisition methods and available genomic tools. In this minireview, we highlight developments in this field pertaining to yeast cell biology and discuss how we have combined HCS with methods for automated yeast genetics (synthetic genetic array (SGA) analysis) to enable systematic analysis of cell biological phenotypes in a variety of genetic backgrounds.     

A versatile data acquisition system for physiological modelling of laboratory fermentation processes

Summary A versatile data acquisition system for physiological modelling of laboratory fermentation processes is given. This system meets the stringent qualifications of modern modelling techniques in terms of signal to noise ratios and sampling rates using readily available equipment. The data are portable to any data processing system for modelling and analysing the culture characteristics. Two completely equipped fermentation systems are sampled with a sampling period of six seconds. The data acquisition system is used to acquire data of a set of continuous fermenters showing sustained oscillations. Oscillation data was used to show the performance of the data acquisition system. With the high sampling rate signal to noise ratios of 30 dB or higher are achieved. It was possible to determine periods of oscillatory behaviour and delay times. The system has shown to be versatile in alaboratory set up. Addition or subtraction of sensors or complete fermentation systems can be done without major alterations to the system.     

High-throughput polymorphism screening and genotyping with high-density oligonucleotide arrays

A highly reliable and efficient technology has been developed for high-throughput DNA polymorphism screening and large-scale genotyping. Photolithographic synthesis has been used to generate miniaturized, high-density oligonucleotide arrays. Dedicated instrumentation and software have been developed for array hybridization, fluorescent detection, and data acquisition and analysis. Specific oligonucleotide probe arrays have been designed to rapidly screen human STSs, known genes and full-length cDNAs. This has led to the identification of several thousand biallelic single-nucleotide polymorphisms (SNPs). Meanwhile, a rapid and robust method has been developed for genotyping these SNPs using oligonucleotide arrays. Each allele of an SNP marker is represented on the array by a set of perfect match and mismatch probes. Prototype genotyping chips have been produced to detect 400, 600 and 3000 of these SNPs. Based on the preliminary results, using oligonucleotide arrays to genotype several thousand polymorphic loci simultaneously appears feasible.     

A composite sensor array impedentiometric electronic tongue Part I. Characterization

A study aimed at the characterization of five compounds with different chemical characteristics and gustative perceptions by measuring the variations of the electrical impedance of a composite sensor array is presented. The array was composed of five sensors of three different types based on carbon nanotubes or carbon black dispersed in polymeric matrices and doped polythiophenes. Measurements were carried out by evaluating the electrical impedance of the sensor array at a frequency of 150 Hz, and the data acquisition process was automated; a mechanical arm and a rotating platform controlled by a data acquisition card and a dedicated software allowed the sequential dipping of sensors in the test solutions. Fifty different solutions eliciting the 5 basic tastes (sodium chloride, citric acid, glucose, glutamic acid and sodium dehydrocholate for salty, sour, sweet, umami and bitter, respectively) at 10 concentration levels comprising the human perceptive range were analysed. More than 100 measurements were carried for each sample in a 4-month period to evaluate the system repeatability and robustness. The impedentiometric composite sensor array is shown to be sensitive, selective and stable for use in an electronic tongue.