A Push-Pull CORF Model of a Simple Cell with Antiphase Inhibition Improves SNR and Contour Detection

We propose a computational model of a simple cell with push-pull inhibition, a property that is observed in many real simple cells. It is based on an existing model called Combination of Receptive Fields or CORF for brevity. A CORF model uses as afferent inputs the responses of model LGN cells with appropriately aligned center-surround receptive fields, and combines their output with a weighted geometric mean. The output of the proposed model simple cell with push-pull inhibition, which we call push-pull CORF, is computed as the response of a CORF model cell that is selective for a stimulus with preferred orientation and preferred contrast minus a fraction of the response of a CORF model cell that responds to the same stimulus but of opposite contrast. We demonstrate that the proposed push-pull CORF model improves signal-to-noise ratio (SNR) and achieves further properties that are observed in real simple cells, namely separability of spatial frequency and orientation as well as contrast-dependent changes in spatial frequency tuning. We also demonstrate the effectiveness of the proposed push-pull CORF model in contour detection, which is believed to be the primary biological role of simple cells. We use the RuG (40 images) and Berkeley (500 images) benchmark data sets of images with natural scenes and show that the proposed model outperforms, with very high statistical significance, the basic CORF model without inhibition, Gabor-based models with isotropic surround inhibition, and the Canny edge detector. The push-pull CORF model that we propose is a contribution to a better understanding of how visual information is processed in the brain as it provides the ability to reproduce a wider range of properties exhibited by real simple cells. As a result of push-pull inhibition a CORF model exhibits an improved SNR, which is the reason for a more effective contour detection.     

Relative spike time coding and STDP-based orientation selectivity in the early visual system in natural continuous and saccadic vision: a computational model

We have built a phenomenological spiking model of the cat early visual system comprising the retina, the Lateral Geniculate Nucleus (LGN) and V1’s layer 4, and established four main results (1) When exposed to videos that reproduce with high fidelity what a cat experiences under natural conditions, adjacent Retinal Ganglion Cells (RGCs) have spike-time correlations at a short timescale (~30 ms), despite neuronal noise and possible jitter accumulation. (2) In accordance with recent experimental findings, the LGN filters out some noise. It thus increases the spike reliability and temporal precision, the sparsity, and, importantly, further decreases down to ~15 ms adjacent cells’ correlation timescale. (3) Downstream simple cells in V1’s layer 4, if equipped with Spike Timing-Dependent Plasticity (STDP), may detect these fine-scale cross-correlations, and thus connect principally to ON- and OFF-centre cells with Receptive Fields (RF) aligned in the visual space, and thereby become orientation selective, in accordance with Hubel and Wiesel (Journal of Physiology 160:106–154, 1962) classic model. Up to this point we dealt with continuous vision, and there was no absolute time reference such as a stimulus onset, yet information was encoded and decoded in the relative spike times. (4) We then simulated saccades to a static image and benchmarked relative spike time coding and time-to-first spike coding w.r.t. to saccade landing in the context of orientation representation. In both the retina and the LGN, relative spike times are more precise, less affected by pre-landing history and global contrast than absolute ones, and lead to robust contrast invariant orientation representations in V1.     

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids

The visual response of a cell in the primary visual cortex (V1) to a drifting grating stimulus at the cell’s preferred orientation decreases when a second, perpendicular, grating is superimposed. This effect is called masking. To understand the nonlinear masking effect, we model the response of Macaque V1 simple cells in layer 4Cα to input from magnocellular Lateral Geniculate Nucleus (LGN) cells. The cortical model network is a coarse-grained reduction of an integrate-and-fire network with excitation from LGN input and inhibition from other cortical neurons. The input is modeled as a sum of LGN cell responses. Each LGN cell is modeled as the convolution of a spatio-temporal filter with the visual stimulus, normalized by a retinal contrast gain control, and followed by rectification representing the LGN spike threshold. In our model, the experimentally observed masking arises at the level of LGN input to the cortex. The cortical network effectively induces a dynamic threshold that forces the test grating to have high contrast before it can overcome the masking provided by the perpendicular grating. The subcortical nonlinearities and the cortical network together account for the masking effect. Melinda Koelling is formerly from Center for Neural Science and Courant Institute, New York University.     

Combined Hebbian development of geniculocortical and lateral connectivity in a model of primary visual cortex

We present a network model of visual map development in layer 4 of primary visual cortex. Our model comprises excitatory and inhibitory spiking neurons. The input to the network consists of correlated spike trains to mimick the activity of neurons in the lateral geniculate nucleus (LGN). An activity-driven Hebbian learning mechanism governs the development of both the network's lateral connectivity and feedforward projections from LGN to cortex. Plasticity of inhibitory synapses has been included into the model so as to control overall cortical activity. Even without feedforward input, Hebbian modification of the excitatory lateral connections can lead to the development of an intracortical orientation map. We have found that such an intracortical map can guide the development of feedforward connections from LGN to cortical simple cells so that the structure of the final feedforward orientation map is predetermined by the intracortical map. In a scenario in which left- and right-eye geniculocortical inputs develop sequentially one after the other, the resulting maps are therefore very similar, provided the intracortical connectivity remains unaltered. This may explain the outcome of so-called reverse lid-suture experiments, where animals are reared so that both eyes never receive input at the same time, but the orientation maps measured separately for the two eyes are nevertheless nearly identical. Received: 20 December 1999 / Accepted in revised form: 9 June 2000     

A neural network model for the emergence of grating cells

A correlation-based learning (CBL) neural network model is proposed, which simulates the emergence of grating cells as well as some of their response characteristics to periodic pattern stimuli. These cells, found in areas V1 and V2 of the visual cortex of monkeys, respond vigorously and exclusively to bar gratings of a preferred orientation and periodicity. Their non-linear behaviour differentiates grating cells from other orientation-selective cells, which show linear spatial frequency filtering. Received: 9 June 1997 / Accepted in revised form: 9 February 1998     

A cooperation and competition based simple cell receptive field model and study of feed-forward linear and nonlinear contributions to orientation selectivity

We present a model for development of orientation selectivity in layer IV simple cells. Receptive field (RF) development in the model, is determined by diffusive cooperation and resource limited competition guided axonal growth and retraction in geniculocortical pathway. The simulated cortical RFs resemble experimental RFs. The receptive field model is incorporated in a three-layer visual pathway model consisting of retina, LGN and cortex. We have studied the effect of activity dependent synaptic scaling on orientation tuning of cortical cells. The mean value of hwhh (half width at half the height of maximum response) in simulated cortical cells is 58° when we consider only the linear excitatory contribution from LGN. We observe a mean improvement of 22.8° in tuning response due to the non-linear spiking mechanisms that include effects of threshold voltage and synaptic scaling factor.     

Energy model for contrast detection: spatiotemporal characteristics of threshold vision

A model for contrast detection of spatiotemporal stimuli is proposed which consists of a spatiotemporal linear filter, an energy device and a threshold device. Assuming the existence of independent intrinsic noise, the probability of stimulus detection was approximated by a Weibull function of the response energy. With this assumption, the stimulus energy is a constant at fixed detection probability. This energy model for contrast detection satisfactorily accounted for the elliptical threshold contours of line pairs at stimulus separations within the range 2–30 min and at stimulus onset asynchronies within the range 20–140 ms. The threshold contour at a large stimulus onset asynchrony (300 ms) was in the form of a rounded square. This finding was explained by assuming that the probability of seeing the line pair was determined by the joint probability that at least one stimulus had been detected. With the energy model, the temporal and spatial autocorrelation functions of the response to a flashed line were evaluated. The autocorrelation functions thus determined were used to predict the temporal contrast sensitivity function to a flickering line stimulus and the spatial contrast sensitivity function to flashed gratings, which were in agreement with the experimental data. The data obtained were fitted adequately by an impulse response approximated by a spatiotemporal Gabor-like function. Received: 08 December 1997 / Accepted in revised form: 26 January 1999     

A computational neural model of orientation detection based on multiple guesses: comparison of geometrical and algebraic models

The implementation of Hubel-Wiesel hypothesis that orientation selectivity of a simple cell is based on ordered arrangement of its afferent cells has some difficulties. It requires the receptive fields (RFs) of those ganglion cells (GCs) and LGN cells to be similar in size and sub-structure and highly arranged in a perfect order. It also requires an adequate number of regularly distributed simple cells to match ubiquitous edges. However, the anatomical and electrophysiological evidence is not strong enough to support this geometry-based model. These strict regularities also make the model very uneconomical in both evolution and neural computation. We propose a new neural model based on an algebraic method to estimate orientations. This approach synthesizes the guesses made by multiple GCs or LGN cells and calculates local orientation information subject to a group of constraints. This algebraic model need not obey the constraints of Hubel-Wiesel hypothesis, and is easily implemented with a neural network. By using the idea of a satisfiability problem with constraints, we also prove that the precision and efficiency of this model are mathematically practicable. The proposed model makes clear several major questions which Hubel-Wiesel model does not account for. Image-rebuilding experiments are conducted to check whether this model misses any important boundary in the visual field because of the estimation strategy. This study is significant in terms of explaining the neural mechanism of orientation detection, and finding the circuit structure and computational route in neural networks. For engineering applications, our model can be used in orientation detection and as a simulation platform for cell-to-cell communications to develop bio-inspired eye chips.     

Analysis of ethanol in fermentation samples by a robust nanocomposite-based microbial biosensor

A robust microbial biosensor was constructed from a bionanocomposite prepared by a direct mixing of bacterial cells of Gluconobacter oxydans and carbon nanotubes with ferricyanide employed as a mediator for enhanced sensitivity of ethanol oxidation. A successful integration of the device into flow injection analysis mode of operation provided a high sensitivity of detection of (74 ± 2.7) μA mM⁻¹ cm⁻², a low detection limit of 5 μM and a linear range from 10 μM up to 1 mM. A short response time of the biosensor allowed a sample throughput of 67 h⁻¹ at 0.3 ml min⁻¹. The biosensor exhibited high operational stability with a decrease in the biosensor response of 1.7% during 43 h of continuous operation. The device was used to analyse ethanol in fermentation samples with a good agreement with a HPLC method.     

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

In order to probe into the self-organizing emergence of simple cell orientation selectivity, we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells. However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.     

A neural network model on self-organizing emergence of simple-cell receptive field with orientation selectivity in visual cortex

In order to probe into the self-organizing emergence of simple cell orientation selectivity, we tried to construct a neural network model that consists of LGN neurons and simple cells in visual cortex and obeys the Hebbian learning rule. We investigated the neural coding and representation of simple cells to a natural image by means of this model. The results show that the structures of their receptive fields are determined by the preferred orientation selectivity of simple cells. However, they are also decided by the emergence of self-organization in the unsupervision learning process. This kind of orientation selectivity results from dynamic self-organization based on the interactions between LGN and cortex.     

Effect of Ganciclovir on murine cytomegalovirus-induced hearing loss in a mouse model

We evaluated the effect of Ganciclovir on murine cytomegalovirus (MCMV)-induced hearing impairment in a mouse model by studying modulations in auditory brainstem response (ABR) and pathological changes in the inner ear. MCMV infection was established via trans-brain. For this purpose, 24 BALB/c newborn mice were randomly and equally divided into control group (10 μl of sterile normal saline was injected); model group (10 μl of MCMV TCID50—10⁴ IU/0.1 ml was injected); and interfered group (Trans-brain MCMV; Ganciclovir at the rate of 60 mg/kg was intraperitoneally injected). ABR audiometry was performed after 14 days. Acoustic vesicles were obtained for MCMV-PCR analysis and histopathological examination. Comparing ABR in model group against controls, incubation period of wave was lengthened (F = 9.151, P = 0.011–0.05) and wave amplitude was cut down (F = 5.095, P = 0.043–0.05). Comparing ABR in model group against interfered group, incubation period and amplitude of wave were F = 13.797 (P = 0.003–0.05) and F = 14.587 (P = 0.002–0.05), respectively. Cochlear histopathological changes in model group included thickening of vestibular membrane, lymphocytic infiltration, and fibrous degeneration of cochlear duct. In Ganciclovir interfered group, however, these pathologic changes were less significant as compared with those of model group. We, therefore, conclude that Ganciclovir treatment at the early stage of MCMV-induced hearing impairment inhibits the disease progression in infected mice.     

Highly sensitive and selective uric acid biosensor based on a three-dimensional graphene foam/indium tin oxide glass electrode

A three-dimensional (3D) continuous and interconnected network graphene foam (GF) was synthesized by chemical vapor deposition using nickel foam as a template. The morphologies of the GF were observed by scanning electron microscopy. X-ray diffraction and Raman spectroscopy were used to investigate the structure of GF. The graphene with few layers and defect free was closely coated on the backbone of the 3D nickel foam. After etching nickel, the GF was transferred onto indium tin oxide (ITO) glass, which acted as an electrode to detect uric acid using cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The GF/ITO electrode showed a high sensitivity for the detection of uric acid: approximately 9.44 mA mM⁻¹ in the range of 25 nM–0.1 μM and 1.85 mA mM⁻¹ in the range of 0.1–60 μM. The limit of detection of GF/ITO electrode for uric acid is 3 nM. The GF/ITO electrode also showed a high selectivity for the detection of uric acid in the presence of ascorbic acid. This electrode will have a wide range of potential application prospects in electrochemical detection.     

Immobilizing Pt nanoparticles and chitosan hybrid film on polyaniline naofibers membrane for an amperometric hydrogen peroxide biosensor

A convenient and effective way for fabricating amperometric hydrogen peroxide (H₂O₂) biosensor was designed in this paper. First, the polyaniline (PANI) nanofibers membrane with good conductance and high surface area was electropolymerized on a gold electrode surface. Then, Pt nanoparticle (PtNP) was electrochemically deposited on the PANI nanofibers membrane. Finally, the hybrid film of gold nanoparticle, chitosan, and horseradish peroxidase (HRP) was cast onto the modified electrode to form a stable biofunctional film, which was also employed as a protective layer to PtNP. The proposed biosensor exhibited a rapid response to H₂O₂ with the linear range from 7.0 × 10⁻⁶ to 1.4 × 10⁻² M and a detection limit of 2.8 × 10⁻⁶ M (S/N = 3). The sensitivity of 558 μA mM⁻¹ cm⁻² was obtained. The Michaelis–Menten constant, K_\textM^\textapp K_{\text{M}}^{\text{app}} value was 1.90 mM suggesting a high affinity. Moreover, it displayed a good reproducibility and long-term stability.     

Characterization and validation of a chemiluminescent assay based on 1,2-dioxetanes for rapid detection of viable Escherichia coli

[(4-methoxy-4(3-β-d-galactose-4-chlorophenyl)]spiro[1,2-dioxetane-3-1,3-tricyclo[7.3.1.0^2,7]tridec-2,7-ene] (“sβ-Gal 102”) and sodium [4-methoxy-4(3-β-d-glucuronic acid-4-chlorophenyl)]spiro[1,2-dioxetane-3-1,3-tricyclo[7.3.1.0^2,7]tridec-2,7-ene] (“sβ-Glucor 102”) are carbohydrate-containing 1,2-dioxetane compounds that produce chemiluminescence upon enzymatic hydrolysis by β-d-galactosidase, and β-d-glucuronidase, respectively. In this study, we have characterized and validated a sensitive detection principle for viable Escherichia coli based on enzymatic cleavage of sβ-Gal 102 and sβ-Glucor 102 (“ColiLight II”). The proposed chemiluminescent assay was optimized with respect to analytical requirements including incubation time, temperature, pH, enzyme induction, and cell permeabilization. The sensitivity and specificity rates of the assay were tested on ten different bacterial genera. The assay was found to be representative based on low coefficients of variations for both accuracy and precision. The analysis time was less than 1 h and the analytical detection limit was 10² to 10³ E. coli cells. In combination with membrane filtration and a brief resuscitation step of 4 h, the proposed assay was capable of detecting low concentrations of stressed E. coli in potable water (<30 CFU 100 ml⁻¹). The proposed chemiluminescent enzyme assay may be used for assessing the metabolic activity of E. coli in oligotrophic environments and for early warning detection of low concentrations of E. coli in water for human consumption.     

The responses to illusory contours of neurons in cortex areas 17 and 18 of the cats

Responses to illusory contours (ICs) were sampled from neurons in cortical areas 17 and 18 of the anesthetized cats. For ICs sensitive cells, the differences of receptive field properties were compared when ICs and real contour stimuli were applied. Two hundred orientation or direction selective cells were studied. We find that about 42 percent of these cells were the ICs sensitive cells. Although their orientation or direction tuning curves to ICs bar and real bars were similar, the response modes (especially latency and time course) were different. The cells’ responses to ICs were independent of the spatial phases of sinusoidal gratings, which composed the ICs. The cells’ optimal spatial frequency to composing gratings the ICs was much higher than the one to moving gratings. Therefore, these cells really responded to the ICs rather than the line ends of composing gratings. For some kinds of velocity-tuning cells, the optimal velocity to moving ICs bar was much lower than the optimal velocity to moving bars. The present results demonstrate that some cells in areas 17 and 18 of cats have the ability to respond to ICs and have different response properties of the receptive fields to ICs and luminance boundaries via different neural mechanisms.     

Use of lysozyme for treatment of bacterial contamination in <Emphasis Type="Italic">in vitro</Emphasis> shoot cultures of fruit plants

Summary Use of lysozyme was tested for treatment of bacterial contaminations in in vitro shoot cultures of quince (Cydonia oblonga) ‘BA 29’ and the hybrid (Prunus persica × P. amygdalus) rootstock ‘GF 677’. Shoots which had been contaminated for about 1 yr by Bacillus circulans and Sphingomonas paucimobilis were treated in liquid culture, at pH 4.5, with 9–36 mg ml⁻¹ egg white lysozyme (EWL), and compared to each other and to untreated cultures for their growth, proliferation, and number of bacterial colony-forming units in the tissues. EWL did not negatively affect shoot growth up to 18 mg ml⁻¹; furthermore, the proliferation rates of EWL-treated shoots were sometimes higher than those of controls. In contrast, the concentration of 36 mg ml⁻¹ had some deleterious effect on the regrowth capacity and shoot production of ‘GF 677’ at the first subculture to solid medium after EWL, treatments. EWL had a simple bacteriostatic effect against Sphingomonas paucimobilis; in contrast, it was effective at 18 mg ml⁻¹ in eliminating Bacillus circulans in both ‘BA 29’ and ‘GF 677’ cultures, after optimal treatment duration.     

Consequences of chemosensory phenomena for leukocyte chemotactic orientation

The stochastic nature of cell surface receptor-ligand binding is known to limit the accuracy of detection of chemoattractant gradients by leukocytes (11, 12), thus limiting the orientation ability that is crucial to the chemotactic response in host defense. The probabilistic cell orientation model of Lauffenburger (11) is extended here to assess the consequences of recently discovered receptor phenomena: “down-regulation” of total surface receptor number, spatial asymmetry of surface receptors, and existence of a higher-affinity receptor subpopulation. In general, a reduction in orientation accuracy is predicted by inclusion of these phenomena. An orientation signal based on a simple model of chemosensory adaptation (i.e., a spatial difference inrelative receptor occupancy) is found to be functionally different from the signal suggested by an experimental correlation (i.e., a spatial difference inabsolute receptor occupancy). However, in the context of receptor “signal noise,” the signal based on adaptation yields predictions in better qualitative agreement with the experimental orientation data of Zigmond (10). From this cell orientation model we can estimate the effective timeaveraging period required for noise diminution to a level allowing orientation predictions to match observed levels. This time-averaging period presumably reflects the time constant for receptor signal transduction and locomotory response.     

Dynamic modeling for flow-activated chloride-selective membrane current in vascular endothelial cells

In this paper, a dynamic model is proposed to quantify the relationship between fluid flow and Cl⁻-selective membrane current in vascular endothelial cells (VECs). It is assumed that the external shear stress would first induce channel deformation in VECs. This deformation could activate the Cl⁻ channels on the membrane, thus allowing Cl⁻ transport across the membrane. A modified Hodgkin–Huxley model is embedded into our dynamic system to describe the electrophysiological properties of the membrane, such as the Cl⁻-selective membrane current (I), voltage (V) and conductance. Three flow patterns, i. e., steady flow, oscillatory flow, and pulsatile flow, are applied in our simulation studies. When the extracellular Cl⁻ concentration is constant, the I-V characteristics predicted by our dynamic model shows strong consistency with the experimental observations. It is also interesting to note that the Cl⁻ currents under different flow patterns show some differences, indicating that VECs distinguish among and respond differently to different types of flows. When the extracellular Cl⁻ concentration keeps constant or varies slowly with time (i.e. oscillates at 0.02 Hz), the convection and diffusion of Cl⁻ in extracellular space can be ignored and the Cl⁻ current is well captured by the modified Hodgkin–Huxley model alone. However, when the extracellular Cl⁻ varies fast (i.e., oscillates at 0.2 Hz), the convection and diffusion effect should be considered because the Cl⁻ current dynamics is different from the case where the convection-diffusion effect is simply ignored. The proposed dynamic model along with the simulation results could not only provide more insights into the flow-regulated electrophysiological behavior of the cell membrane but also help to reveal new findings in the electrophysiological experimental investigations of VECs in response to dynamic flow and biochemical stimuli.