Proton feedback mediates the cascade of color-opponent signals onto H3 horizontal cells in goldfish retina.

It has been postulated that horizontal cells (HCs) send feedback signals onto cones via a proton feedback mechanism, which generates the center-surround receptive field of bipolar cells, and color-opponent signals in many non-mammalian vertebrates. Here we used a strong pH buffer, HEPES, to reduce extracellular proton concentration changes and so determine whether protons mediate color-opponent signals in goldfish H3 (triphasic) HCs. Superfusion with 10mM HEPES-fortified saline elicited depolarization of H3 HCs' dark membrane potential and enhanced hyperpolarizing responses to blue stimuli, but suppressed both depolarization by yellow and orange and hyperpolarization by red stimuli. The response components suppressed by HEPES resembled the inverse of spectral responses of H2 (biphasic) HCs. These results are consistent with the Stell-Lightfoot cascade model, in which the HEPES-suppressed component of H3 HCs was calculated using light responses recorded experimentally in H1 (monophasic) and H2 HCs. Selective suppression of long- or long-+middle-wavelength cone signals by long-wavelength background enhanced the responses to short-wavelength stimuli. These results suggest that HEPES inhibited color opponent signals in H3 HCs, in which the source of opponent-color signals is primarily a feedback from H2 HCs and partly from H1 HCs onto short-wavelength cones, probably mediated by protons.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software.

Simulation Platform: a cloud-based online simulation environment.

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software.

A model-based theory on the signal transformation for microsaccade generation.

The eyes are continuously fluctuating even during fixation. The fluctuations are called miniature eye movements and consist of microsaccades, drifts, and tremors. It has been revealed that these miniature eye movements aid our vision; they improve the visibility of high spatial frequency components, and prevent retinal adaptation during fixation. Although the functional roles of the miniature eye movements have gradually been uncovered, their generation mechanism remains a mystery. Here, we focused on microsaccades, and constructed a neuronal network model to explore their generation mechanism. Several lines of evidence ensure that microsaccades and saccades share the same neuronal circuitry because they fall on the same main sequence, a relationship between their amplitudes and peak velocities. In the saccade pathway, saccade commands generated in the superior colliculus are relayed to motoneurons via burst neurons (BNs) and the integrator network. The BNs are inhibited by omnipause neurons (OPNs) except when saccades are generated. We configured a model for microsaccades based on the well-defined saccade neuronal pathway including tonic neurons, BNs, OPNs, the integrator network, and the eye plant. The model successfully reproduced various characteristics of microsaccade: square-wave jerk, single-sided microsaccades, and the main sequence. Moreover, during microsaccades, BNs showed low-rate spikes due to a partial release from the OPN inhibition. These results suggest that microsaccades are generated when BNs are partially, but not completely, released from tonic inhibition by OPNs during fixation, in contrast to the generation of ordinary saccades in which OPNs pause firing and release BNs from their strong inhibition.

PLATO: data-oriented approach to collaborative large-scale brain system modeling.

The brain is a complex information processing system, which can be divided into sub-systems, such as the sensory organs, functional areas in the cortex, and motor control systems. In this sense, most of the mathematical models developed in the field of neuroscience have mainly targeted a specific sub-system. In order to understand the details of the brain as a whole, such sub-system models need to be integrated toward the development of a neurophysiologically plausible large-scale system model. In the present work, we propose a model integration library where models can be connected by means of a common data format. Here, the common data format should be portable so that models written in any programming language, computer architecture, and operating system can be connected. Moreover, the library should be simple so that models can be adapted to use the common data format without requiring any detailed knowledge on its use. Using this library, we have successfully connected existing models reproducing certain features of the visual system, toward the development of a large-scale visual system model. This library will enable users to reuse and integrate existing and newly developed models toward the development and simulation of a large-scale brain system model. The resulting model can also be executed on high performance computers using Message Passing Interface (MPI).

Enlarged gold-tipped silicon microprobe arrays and signal compensation for multi-site electroretinogram recordings in the isolated carp retina.

In order to record multi-site electroretinogram (ERG) responses in isolated carp retinae, we utilized three-dimensional (3D), extracellular, 3.5-µm-diameter silicon (Si) probe arrays fabricated by the selective vapor-liquid-solid (VLS) growth method. Neural recordings with the Si microprobe exhibit low signal-to-noise (S/N) ratios of recorded responses due to the high-electrical-impedance characteristics of the small recording area at the probe tip. To increase the S/N ratio, we designed and fabricated enlarged gold (Au) tipped Si microprobes (10-µm-diameter Au tip and 3.5-µm-diameter probe body). In addition, we demonstrated that the signal attenuation and phase delay of ERG responses recorded via the Si probe can be compensated by the inverse filtering method. We conclude that the reduction of probe impedance and the compensation of recorded signals are useful approaches to obtain distortion-free recording of neural signals with high-impedance microelectrodes.

Electrical interfacing between neurons and electronics via vertically integrated sub-4 microm-diameter silicon probe arrays fabricated by vapor-liquid-solid growth.

We report here a technique for use in electrical interfaces between neurons and microelectronics, using vertically integrated silicon probe arrays with diameters of 2-3.5 microm and lengths of 60-120 microm. Silicon probe arrays can be fabricated by selective vapor-liquid-solid (VLS) growth. A doped n-type silicon probe with the resistance of 1 k Omega has an electrical impedance of less than 10 M Omega in physiological saline. After inserting the probe arrays into the retina of a carp (Cyrpinus carpio), we conducted electrical recording of neural signals, using the probes to measure light-evoked electrical neural signals. We determined that recorded signals represented local field potentials of the retina (electroretinogram (ERG)). The VLS-probe can provide minimally invasive neural recording/stimulation capabilities at high spatial resolution for fundamental studies of nervous systems. In addition, the probe arrays can be integrated with microelectronics; therefore, these probes make it possible to construct interfaces between neurons and microelectronics in advanced neuroscience applications.

Simulation analysis of bandpass filtering properties of a rod photoreceptor network.

The bandpass filtering properties of a rod network were studied via computer simulations. Sinusoidal current stimuli were applied to a single rod model to characterize its temporal filtering properties. The simulated frequency response revealed that a single rod behaves as a bandpass filter whose characteristics are affected by the stimulus strength and frequency. We analyzed the contribution of individual ionic currents to bandpass filtering and found that the filtering of small signals is largely regulated by the calcium-dependent currents I(K(Ca)) and I(Cl(Ca)), whereas the filtering of large signals is regulated by the hyperpolarization-activated current, I(h). Furthermore, rod network modeling by electrically interconnecting the single rod models revealed that the acceleration of signals that spread laterally through the rod network is attributed to I(K(Ca)) and not I(h).

Identification of retinal ganglion cells and their projections involved in central transmission of information about upward and downward image motion.

The direction of image motion is coded by direction-selective (DS) ganglion cells in the retina. Particularly, the ON DS ganglion cells project their axons specifically to terminal nuclei of the accessory optic system (AOS) responsible for optokinetic reflex (OKR). We recently generated a knock-in mouse in which SPIG1 (SPARC-related protein containing immunoglobulin domains 1)-expressing cells are visualized with GFP, and found that retinal ganglion cells projecting to the medial terminal nucleus (MTN), the principal nucleus of the AOS, are comprised of SPIG1+ and SPIG1(-) ganglion cells distributed in distinct mosaic patterns in the retina. Here we examined light responses of these two subtypes of MTN-projecting cells by targeted electrophysiological recordings. SPIG1+ and SPIG1(-) ganglion cells respond preferentially to upward motion and downward motion, respectively, in the visual field. The direction selectivity of SPIG1+ ganglion cells develops normally in dark-reared mice. The MTN neurons are activated by optokinetic stimuli only of the vertical motion as shown by Fos expression analysis. Combination of genetic labeling and conventional retrograde labeling revealed that axons of SPIG1+ and SPIG1(-) ganglion cells project to the MTN via different pathways. The axon terminals of the two subtypes are organized into discrete clusters in the MTN. These results suggest that information about upward and downward image motion transmitted by distinct ON DS cells is separately processed in the MTN, if not independently. Our findings provide insights into the neural mechanisms of OKR, how information about the direction of image motion is deciphered by the AOS.

Engineering-approach accelerates computational understanding of V1-V2 neural properties.

We present two computational models (i) long-range horizontal connections and the nonlinear effect in V1 and (ii) the filling-in process at the blind spot. Both models are obtained deductively from standard regularization theory to show that physiological evidence of V1 and V2 neural properties is essential for efficient image processing. We stress that the engineering approach should be imported to understand visual systems computationally, even though this approach usually ignores physiological evidence and the target is neither neurons nor the brain.

Exploration of a collection of documents in neuroscience and extraction of topics by clustering.

This paper presents a preliminary analysis of the neuroscience knowledge domain, and an application of cluster analysis to identify topics in neuroscience. A collection of posters presented at the Society for Neuroscience (SfN) Annual Meeting in 2006 is first explored by viewing existing topics and poster sessions using multidimensional scaling. Based on the Vector Space Model, several Term Spaces were built on the basis of a set of terms extracted from the posters' abstracts and titles, and a set of free keywords assigned to the posters by their authors. The ensuing Term Spaces were compared from the point of view of retrieving the genuine category titles. Topics were extracted from the abstracts of posters by clustering the documents using a bisecting k-means algorithm and selecting the most salient terms for each cluster by ranking. The terms extracted as topic descriptors were evaluated by comparing them to existing titles assigned to thematic categories defined by human experts in neuroscience. A comparison of two approaches for terms ranking (Document Frequency and Log-Entropy) resulted in better performance of the Log-Entropy scores, allowing to retrieve 31.0% of original title terms in clustered documents (and 37.1% in original thematic categories).

Computational theory and applications of a filling-in process at the blind spot.

A mathematical model for filling-in at the blind spot is proposed. The general scheme of the standard regularization theory was used to derive the model deductively. First, we present the problems encountered with a diffusion equation, which is frequently used for various types of perceptual completion. To solve these problems, we investigated the computational meaning of a neural property discovered by Matsumoto and Komatsu [Matsumoto, M., & Komatsu, H. (2005). Neural responses in the macaque V1 to bar stimuli with various lengths presented on the blind spot. Journal of Neurophysiology, 93, 2374-2387]. Based on our observations, we introduce two types of curvature information of image properties into the a priori knowledge of missing images in the blind spot. Moreover, two different information pathways for filling-in, which were suggested by results of physiological experiments (slow conductive paths of horizontal connections in V1, and fast feedforward/feedback paths via V2), were considered theoretically as the neural embodiment of an adiabatic approximation between V1 and V2 interaction. Numerical simulations show that the output of the proposed model for filling-in is consistent with neurophysiological experimental results. The model can be used as a powerful tool for digital image inpainting.

Relationship between residual aberration and light-adapted pupil size.

PURPOSE: The relationship between residual aberration (residual astigmatism and higher-order aberration) and light-adapted pupil size was investigated in human subjects to verify that the pupil size is adjusted to provide good image quality on the retina through control of the image sharpness and illuminance. METHODS: Monochromatic wave aberration and light-adapted pupil diameters were measured from 20 subjects. The measured wave aberration was reconstructed using a sixth-order Zernike polynomial expansion; the neural sharpness was computed as a metric of the residual aberration. Subsequently, the correlation of the neural sharpness and the light-adapted pupil diameter was examined statistically across the subjects in each luminance level. RESULTS: The light-adapted pupil diameter showed a significant positive correlation with the neural sharpness, except under dark-adapted conditions. In contrast, the pupil diameter showed no significant correlation with the spherical equivalent, as previously shown. CONCLUSION: Our results suggest that the level of aberration present in an eye has an influence on pupil size.

Customizable neuroinformatics database system: XooNIps and its application to the pupil platform.

The developing field of neuroinformatics includes technologies for the collection and sharing of neuro-related digital resources. These resources will be of increasing value for understanding the brain. Developing a database system to integrate these disparate resources is necessary to make full use of these resources. This study proposes a base database system termed XooNIps that utilizes the content management system called XOOPS. XooNIps is designed for developing databases in different research fields through customization of the option menu. In a XooNIps-based database, digital resources are stored according to their respective categories, e.g., research articles, experimental data, mathematical models, stimulations, each associated with their related metadata. Several types of user authorization are supported for secure operations. In addition to the directory and keyword searches within a certain database, XooNIps searches simultaneously across other XooNIps-based databases on the Internet. Reviewing systems for user registration and for data submission are incorporated to impose quality control. Furthermore, XOOPS modules containing news, forums schedules, blogs and other information can be combined to enhance XooNIps functionality. These features provide better scalability, extensibility, and customizability to the general neuroinformatics community. The application of this system to data, models, and other information related to human pupils is described here.

Concierge: personal database software for managing digital research resources.

This article introduces a desktop application, named Concierge, for managing personal digital research resources. Using simple operations, it enables storage of various types of files and indexes them based on content descriptions. A key feature of the software is a high level of extensibility. By installing optional plug-ins, users can customize and extend the usability of the software based on their needs. In this paper, we also introduce a few optional plug-ins: literature management, electronic laboratory notebook, and XooNlps client plug-ins. XooNIps is a content management system developed to share digital research resources among neuroscience communities. It has been adopted as the standard database system in Japanese neuroinformatics projects. Concierge, therefore, offers comprehensive support from management of personal digital research resources to their sharing in open-access neuroinformatics databases such as XooNIps. This interaction between personal and open-access neuroinformatics databases is expected to enhance the dissemination of digital research resources. Concierge is developed as an open source project; Mac OS X and Windows XP versions have been released at the official site (http://concierge.sourceforge.jp).

Visualization of Documents and Concepts in Neuroinformatics with the 3D-SE Viewer.

A new interactive visualization tool is proposed for mining text data from various fields of neuroscience. Applications to several text datasets are presented to demonstrate the capability of the proposed interactive tool to visualize complex relationships between pairs of lexical entities (with some semantic contents) such as terms, keywords, posters, or papers' abstracts. Implemented as a Java applet, this tool is based on the spherical embedding (SE) algorithm, which was designed for the visualization of bipartite graphs. Items such as words and documents are linked on the basis of occurrence relationships, which can be represented in a bipartite graph. These items are visualized by embedding the vertices of the bipartite graph on spheres in a three-dimensional (3-D) space. The main advantage of the proposed visualization tool is that 3-D layouts can convey more information than planar or linear displays of items or graphs. Different kinds of information extracted from texts, such as keywords, indexing terms, or topics are visualized, allowing interactive browsing of various fields of research featured by keywords, topics, or research teams. A typical use of the 3D-SE viewer is quick browsing of topics displayed on a sphere, then selecting one or several item(s) displays links to related terms on another sphere representing, e.g., documents or abstracts, and provides direct online access to the document source in a database, such as the Visiome Platform or the SfN Annual Meeting. Developed as a Java applet, it operates as a tool on top of existing resources.

Effect of surrounding blur on foveal visibility.

Visibility of a simple stimulus is known to be determined not only by its physical contrast, but also by the configuration of surrounding stimuli. In this study, we investigated the surrounding modulation of foveal visibility of a blurred target. Subjects were instructed to respond to the gap orientation of a Gaussian-blurred Landolt ring presented at a fixation point with a surrounding stimulus. The correct response rate was measured as a metric of the foveal visibility. Results were subsequently compared among different surrounding stimulus conditions. Results showed an improvement in the subjects' performance when low-pass white noise filtered with the same Gaussian function used for the target was presented in the surrounding area, although no effect was observed using high-contrast white noise. A performance improvement was observed when the surround stimulus had an intermediate contrast in the spatial frequency band necessary for identifying the target orientation.

Prostaglandins E1 and E2, but not F2alpha or latanoprost, inhibit monkey ciliary muscle contraction.

PURPOSE: To investigate the effects of prostaglandin (PG) E1, E2, F2alpha, and latanoprost acid on the electrically evoked contractile response of isolated rhesus monkey ciliary muscle. METHODS: Longitudinal ciliary muscle preparations from rhesus monkeys were mounted in an organ bath, and tension changes were recorded by an isometric transducer. Electrical field stimulation (100 Hz, 0.3 ms, 10 V) was applied through a pair of platinum plate electrodes. RESULTS: The ciliary muscle produced atropine-sensitive excitatory contraction in response to field stimulation. PGE1 and PGE2 (1 microM) attenuated the contraction to levels that were 68% and 65.1%, respectively, of the normal amplitude. However, PGF2alpha and latanoprost acid (1 microM) did not significantly change the response amplitude. CONCLUSIONS: Our results indicate that PGF2alpha and latanoprost acid do not interact with the prostanoid receptor involved at the pre- and/or postsynaptic site. Therefore, it is unlikely that the hypotensive action by these agents is due to relaxation of the ciliary muscle.