Causal connectivity measures for pulse-output network reconstruction: Analysis and applications.

The causal connectivity of a network is often inferred to understand network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the network's underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity.

A biochemical description of postsynaptic plasticity-with timescales ranging from milliseconds to seconds.

Synaptic plasticity [long-term potentiation/depression (LTP/D)], is a cellular mechanism underlying learning. Two distinct types of early LTP/D (E-LTP/D), acting on very different time scales, have been observed experimentally-spike timing dependent plasticity (STDP), on time scales of tens of ms; and behavioral time scale synaptic plasticity (BTSP), on time scales of seconds. BTSP is a candidate for a mechanism underlying rapid learning of spatial location by place cells.

Modeling the role of gap junctions between excitatory neurons in the developing visual cortex.

Recent experiments in the developing mammalian visual cortex have revealed that gap junctions couple excitatory cells and potentially influence the formation of chemical synapses. In particular, cells that were coupled by a gap junction during development tend to share an orientation preference and are preferentially coupled by a chemical synapse in the adult cortex, a property that is diminished when gap junctions are blocked. In this work, we construct a simplified model of the developing mouse visual cortex including spike-timing-dependent plasticity of both the feedforward synaptic inputs and recurrent cortical synapses.

Neural networks of different species, brain areas and states can be characterized by the probability polling state.

Cortical networks are complex systems of a great many interconnected neurons that operate from collective dynamical states. To understand how cortical neural networks function, it is important to identify their common dynamical operating states from the probabilistic viewpoint. Probabilistic characteristics of these operating states often underlie network functions.

Ring models of binocular rivalry and fusion.

When similar visual stimuli are presented binocularly to both eyes, one perceives a fused single image. However, when the two stimuli are distinct, one does not perceive a single image; instead, one perceives binocular rivalry. That is, one perceives one of the stimulated patterns for a few seconds, then the other for few seconds, and so on - with random transitions between the two percepts.

Dendritic computations captured by an effective point neuron model.

Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent viewpoint simplifies the neuronal morphology as a point representing the soma, and the excitatory and inhibitory synaptic currents originated from the dendrites are treated as linearly summed at the soma. Despite its extensive applications, the validity of the synaptic current description remains unclear, and the existing point neuron framework fails to characterize the spatiotemporal aspects of dendritic integration supporting specific computations.

Mechanisms underlying contrast-dependent orientation selectivity in mouse V1.

Recent experiments have shown that mouse primary visual cortex (V1) is very different from that of cat or monkey, including response properties-one of which is that contrast invariance in the orientation selectivity (OS) of the neurons' firing rates is replaced in mouse with contrast-dependent sharpening (broadening) of OS in excitatory (inhibitory) neurons. These differences indicate a different circuit design for mouse V1 than that of cat or monkey. Here we develop a large-scale computational model of an effective input layer of mouse V1.

Spatiotemporal dynamics of neuronal population response in the primary visual cortex.

One of the fundamental questions in system neuroscience is how the brain encodes external stimuli in the early sensory cortex. It has been found in experiments that even some simple sensory stimuli can activate large populations of neurons. It is believed that information can be encoded in the spatiotemporal profile of these collective neuronal responses.

Aneurysmectomy and revascularization of a large hepatic artery aneurysm.

Aneurysms of the hepatic artery are rare, but are associated with significant mortality because of their lack of symptoms at presentation and risk of rupture. We report a case of an enlarging 4-cm hepatic artery aneurysm involving the proximal common hepatic artery to the bifurcation of the right and left hepatic arteries which was found incidentally on ultrasound examination. Endovascular treatment with a stent was considered, but because of the location of the aneurysm as well as the presence of significant thrombosis involving the right and left hepatic arteries, aneurysmectomy and revascularization using saphenous vein was performed.

Quantifying neuronal network dynamics through coarse-grained event trees.

Animals process information about many stimulus features simultaneously, swiftly (in a few 100 ms), and robustly (even when individual neurons do not themselves respond reliably). When the brain carries, codes, and certainly when it decodes information, it must do so through some coarse-grained projection mechanism. How can a projection retain information about network dynamics that covers multiple features, swiftly and robustly? Here, by a coarse-grained projection to event trees and to the event chains that comprise these trees, we propose a method of characterizing dynamic information of neuronal networks by using a statistical collection of spatial-temporal sequences of relevant physiological observables (such as sequences of spiking multiple neurons).

Estimation of synaptic conductances.

In order to identify and understand mechanistically the cortical circuitry of sensory information processing estimates are needed of synaptic input fields that drive neurons. From intracellular in vivo recordings one would like to estimate net synaptic conductance time courses for excitation and inhibition, g(E)(t) and g(I)(t), during time-varying stimulus presentations. However, the intrinsic conductance transients associated with neuronal spiking can confound such estimates, and thereby jeopardize functional interpretations.

Orientation selectivity in visual cortex by fluctuation-controlled criticality.

Within a large-scale neuronal network model of macaque primary visual cortex, we examined how intrinsic dynamic fluctuations in synaptic currents modify the effect of strong recurrent excitation on orientation selectivity. Previously, we showed that, using a strong network inhibition countered by feedforward and recurrent excitation, the cortical model reproduced many observed properties of simple and complex cells. However, that network's complex cells were poorly selective for orientation, and increasing cortical self-excitation led to network instabilities and unrealistically high firing rates.

Modeling the spatiotemporal cortical activity associated with the line-motion illusion in primary visual cortex.

Our large-scale computational model of the primary visual cortex that incorporates orientation-specific, long-range couplings with slow NMDA conductances operates in a fluctuating dynamic state of intermittent desuppression (IDS), which captures the behavior of coherent spontaneous cortical activity, as revealed by in vivo optical imaging based on voltage-sensitive dyes. Here, we address the functional significance of the IDS cortical operating points by investigating our model cortex response to the Hikosaka line-motion illusion (LMI) stimulus-a cue of a quickly flashed stationary square followed a few milliseconds later by a stationary bar. As revealed by voltage-sensitive dye imaging, there is an intriguing similarity between the cortical spatiotemporal activity in response to (i) the Hikosaka LMI stimulus and (ii) a small moving square.

Architectural and synaptic mechanisms underlying coherent spontaneous activity in V1.

To investigate the existence and the characteristics of possible cortical operating points of the primary visual cortex, as manifested by the coherent spontaneous ongoing activity revealed by real-time optical imaging based on voltage-sensitive dyes, we studied numerically a very large-scale ( approximately 5 x 10(5)) conductance-based, integrate-and-fire neuronal network model of an approximately 16-mm(2) patch of 64 orientation hypercolumns, which incorporates both isotropic local couplings and lateral orientation-specific long-range connections with a slow NMDA component. A dynamic scenario of an intermittent desuppressed state (IDS) is identified in the computational model, which is a dynamic state of (i) high conductance, (ii) strong inhibition, and (iii) large fluctuations that arise from intermittent spiking events that are strongly correlated in time as well as in orientation domains, with the correlation time of the fluctuations controlled by the NMDA decay time scale. Our simulation results demonstrate that the IDS state captures numerically many aspects of experimental observation related to spontaneous ongoing activity, and the specific network mechanism of the IDS may suggest cortical mechanisms and the cortical operating point underlying observed spontaneous activity.

Physicochemical characterisation and biological evaluation of hydrogel-poly(epsilon-caprolactone) interpenetrating polymer networks as novel urinary biomaterials.

Hydrogels are frequently employed as medical device biomaterials due to their advantageous biological properties, e.g. resistance to infection and encrustation, biocompatibility; however, their poor mechanical properties generally limit the scope of application to coatings of medical devices.

An embedded network approach for scale-up of fluctuation-driven systems with preservation of spike information.

To address computational "scale-up" issues in modeling large regions of the cortex, many coarse-graining procedures have been invoked to obtain effective descriptions of neuronal network dynamics. However, because of local averaging in space and time, these methods do not contain detailed spike information and, thus, cannot be used to investigate, e.g.

An effective kinetic representation of fluctuation-driven neuronal networks with application to simple and complex cells in visual cortex.

A coarse-grained representation of neuronal network dynamics is developed in terms of kinetic equations, which are derived by a moment closure, directly from the original large-scale integrate-and-fire (I&F) network. This powerful kinetic theory captures the full dynamic range of neuronal networks, from the mean-driven limit (a limit such as the number of neurons N --> infinity, in which the fluctuations vanish) to the fluctuation-dominated limit (such as in small N networks). Comparison with full numerical simulations of the original I&F network establishes that the reduced dynamics is very accurate and numerically efficient over all dynamic ranges.

Impact of boron deficiency on Xenopus laevis: a summary of biological effects and potential biochemical roles.

The toxicity of boron has been understood for many years. However, limited data currently exist concerning the nutritional essentiality of B in chordates. Results from an ongoing research program evaluating the nutritional essentiality of B in the South African clawed frog, Xenopus laevis, found that X.

Evaluation of the developmental toxicities of ethanol, acetaldehyde, and thioacetamide using FETAX.

Potential mechanisms of the developmental toxicities of ethanol, acetaldehyde, and thioacetamide were evaluated using frog embryo teratogenesis assay-Xenopus (FETAX). Early X. laevis embryos were exposed to ethanol and thioacetamide in two separate definitive concentration-response tests with and without differentially induced exogenous metabolic activation systems (MAS) or selectively inhibited MAS.

Effect of endocrine disrupting chemicals on germinal vesicle breakdown in Xenopus in vitro.

Currently, no standardized and well-validated alternative models exist for screening for progesterone-responsive endocrine disrupting chemicals (EDCs). Because of this, a rapid assay for evaluating progestin/antiprogestin activity using Xenopus oocyte germinal vesicle breakdown (GVBD) as a model was evaluated. Five compounds, including progesterone (P), ethinyl estradiol (EE), ethylene glycol monomethyl ether (EGME), cadmium (Cd), and boric acid (B) were used to validate the model on a preliminary basis.

Comparison of commercial latex agglutination and sandwich enzyme immunoassays with a competitive binding inhibition enzyme immunoassay for detection of antigenemia and antigenuria in a rabbit model of invasive aspergillosis.

A commercial latex agglutination assay (LA) and a sandwich enzyme immunoassay (SEIA) (Sanofi Diagnostics Pasteur, Marnes-la-Coquette, France) were compared with a competitive binding inhibition assay (enzyme immunoassay [EIA]) to determine the potential uses and limitations of these antigen detection tests for the sensitive, specific, and rapid diagnosis of invasive aspergillosis (IA). Toward this end, well-characterized serum and urine specimens were obtained by using a rabbit model of IA. Serially collected serum or urine specimens were obtained daily from control rabbits or from rabbits immunosuppressed and infected systemically with Aspergillus fumigatus.

Spectral bifurcations in dispersive wave turbulence.

Dispersive wave turbulence is studied numerically for a class of one-dimensional nonlinear wave equations. Both deterministic and random (white noise in time) forcings are studied. Four distinct stable spectra are observed-the direct and inverse cascades of weak turbulence (WT) theory, thermal equilibrium, and a fourth spectrum (MMT; Majda, McLaughlin, Tabak).

Purification and characterization of the extracellular aspartyl proteinase of Candida albicans: removal of extraneous proteins and cell wall mannoprotein and evidence for lack of glycosylation.

Aspartyl proteinase (AP) is an extracellular enzyme of Candida albicans implicated as a pathogenic factor. Previous reports on the purification and characterization of AP suggested that a single DEAE-Sephadex chromatographic step was sufficient for the removal of extraneous proteins and that the final product was glycosylated. We purified AP using a chromatographic series consisting of DEAE-Sephadex A25, Sephadex G75 and rechromatography on DEAE-Sephadex A25.