Studies on Strobilation in the Scyphozoa

The use of green, red, and far-red light-emitting diodes (LEDs) as light sources for plant physiological studies is described. LED lamps have the advantage over conventional light sources in that they are lightweight, low cost, portable, easily constructed and, more important, do not require colour filters. Using LED lamps, red/far-red reversal of germination of Grand Rapids lettuce seeds was demonstrated and the effectiveness of a green LED safelight was compared with that of a conventional filtered safelight, using extension growth of photosensitive Avena fatua L. seedlings as an indicator. The green LEDs gave comparable performance to the conventional filter-type safelight. An infra-red LED light source was also evaluated.     

K-way neural network graph partitioning with separator vertices

A neural network for partitioning graphs into any number of subgraphs using a k-way procedure is presented. The resulting neural network optimises all subgraphs so that they contain approximately the same number of vertices with the exception of a `separator' subgraph. The latter separates all the other subgraphs and is optimised to contain a minimum number of vertices. Expressions for the neuron link weights for such a network are derived analytically, and the recall mechanism of the mean field theorem neural network is used to obtain the graph partitioning. Applications focus on partitioning graphs associated with finite element meshes which, together with parallel domain decomposition solution methods, provide the motivation for this work. Received: 14 January 1998 / Accepted in revised form: 24 November 1998     

Insect reactions to light and its applications to pest management

Insects are able to see ultraviolet (UV) radiation. Nocturnal insects are often attracted to light sources that emit large amounts of UV radiation, and devices that exploit this behavior, such as light traps for forecasting pest outbreaks, and electric insect killers, have been developed. Some diurnal species are attracted to yellow; yellow pan traps are used for conducting surveys for pest outbreaks and yellow sticky plates are used for pest control. Lamps that give off yellow illumination have been used effectively to control the activity of nocturnal moths and thus reduce damage to fruit, vegetables, and flowers. Covering cultivation facilities with film that filters out near-UV radiation reduces the invasion of pests such as whiteflies and thrips into the facilities, thus reducing damage. Reflective material placed on cultivated land can control the approach of flying insects such as aphids. Future development and use of new light sources such as light-emitting diodes is anticipated for promoting integrated pest management.     

Geographic variation in beak colouration in gentoo penguins <Emphasis Type="Italic">Pygoscelis papua</Emphasis>

Ornamental colouration is often due to carotenoid pigments and varies inter- and intra-specifically. This paper reports on variation in beak colour of the gentoo penguin, Pygoscelis papua, corresponding to different geographical locations along a latitudinal gradient in the Antarctic Peninsula (from King George Island (62o15′S–58o37′W) to Rongé Island (64o40′S–62o40′W). The gentoo penguin has a conspicuous red spot on both sides of the beak that indicates the presence of the carotenoid pigment, astaxanthin. Beak colouration was measured with a portable spectrophotometer for 20 individuals in three locations, along the Western coast of the Antarctic Peninsula. In the study area, marked variation can be found in terms of factors such us parasite load, human impact, variations in UV radiation and the abundance of krill; all possibly affecting carotenoid availability for signalling purposes. Colour traits were expected to be more intense, that is more vivid, saturated and pure, in places where there is diminished pressure from factors such as contamination, parasites or diseases, all of which may reduce the availability of carotenoids for other functions, such as antioxidant or immune stimulation involving physiological trade-offs. Likewise, colour traits might be predicted to be more intense where carotenoid sources, krill in the case of gentoo penguins, are more available. However, contrary to this initial expectation, our results indicate that northerly penguins’ populations, which are in the most polluted and parasitized areas, have more saturated beaks. An alternative hypothesis suggests that environmental constraints relating to the variation in abundance of krill may explain the geographical variation in colour expression found among gentoo penguins.     

Stimulus-induced bifurcations in discrete-time neural oscillators

Based on theoretical issues and neurobiological evidence, considerable interest has recently focused on dynamic computational elements in neural systems. Such elements respond to stimuli by altering their dynamical behavior rather than by changing a scalar output. In particular, neural oscillators capable of chaotic dynamics represent a potentially very rich substrate for complex spatiotemporal information processing. However, the response properties of such systems must be studied in detail before they can be used as computational elements in neural models. In this paper, we focus on the response of a very simple discrete-time neural oscillator model to a fixed input. We show that the oscillator responds to the stimulus through a fairly complex set of bifurcations, and shows critical switching between attractors. This information can be used to construct very sophisticated dynamic computational elements with well-understood response properties. Examples of such elements are presented in the paper. We end with a brief discussion of simple architectures for networks of dynamical elements, and the relevance of our results to neurobiological models. Received: 7 August 1997 / Accepted in revised form: 22 April 1998     

Nonuniformity in the linear network model of the oculomotor integrator produces approximately fractional-order dynamics and more realistic neuron behavior

The oculomotor integrator is a network that is composed of neurons in the medial vestibular nuclei and nuclei prepositus hypoglossi in the brainstem. Those neurons act approximately as fractional integrators of various orders, converting eye velocity commands into signals that are intermediate between velocity and position. The oculomotor integrator has been modeled as a network of linear neural elements, the time constants of which are lengthened by positive feedback through reciprocal inhibition. In this model, in which each neuron reciprocally inhibits its neighbors with the same Gaussian profile, all model neurons behave as identical, first-order, low-pass filters with dynamics that do not match the variable, approximately fractional-order dynamics of the neurons that compose the actual oculomotor integrator. Fractional-order integrators can be approximated by weighted sums of first-order, low-pass filters with diverse, broadly distributed time constants. Dynamic systems analysis reveals that the model integrator indeed has many broadly distributed time constants. However, only one time constant is expressed in the model due to the uniformity of its network connections. If the model network is made nonuniform by removing the reciprocal connections to and from a small number of neurons, then many more time constants are expressed. The dynamics of the neurons in the nonuniform network model are variable, approximately fractional-order, and resemble those of the neurons that compose the actual oculomotor integrator. Completely removing the connections to and from a neuron is equivalent to eliminating it, an operation done previously to demonstrate the robustness of the integrator network model. Ironically, the resulting nonuniform network model, previously supposed to represent a pathological integrator, may in fact represent a healthy integrator containing neurons with realistically variable, approximately fractional-order dynamics. Received: 8 August 1997 / Accepted in revised form: 18 June 1998     

Comments on ‘Is Partial Coherence a Viable Technique for Identifying Generators of Neural Oscillations?’

To aid prospective neural connectivity inference analysts and hoping to preclude misconception spread, we exploit the didatic value of some of the issues raised by Albo et al. (Biol Cybern 90: 318–326, 2004) who claim that signal-to-noise ratio (SNR) values can lead to mistakes in structural inference when using partial coherence in connection to Gersch’s 1970 method for spotting signal sources (Gersch in Math Biosci 14: 177– 196, 1972). We show theoretically that Gersch’s method is able only to spot which measurement of some common underlying factor has the least amount of additive noise and that this has nothing to do with any reasonable notion of ‘causality’ as suggested by Albo et al. (Biol Cybern 90: 318–326, 2004). We also show that despite the inherent structural ambiguity of the model used by Albo et al. (Biol Cybern 90: 318–326, 2004) to back their claim, its data can nonetheless furnish the correct time precedence hierarchy between the activities in its measured structures, both when simple (correlation) and more sophisticated methods are used (partial directed coherence) (Baccala and Sameshima in Biol Cybern 84:463–474, 2001a) in a true depiction of time series causality.     

Neural network mosaic model for pupillary responses to spatial stimuli

A neural network mosaic model was developed to investigate the spatial-temporal properties of the human pupillary control system. It was based on the double-layer neural network model developed by Cannon and Robinson and the pupillary dual-path model developed by Sun and Stark. The neural network portion of the model received its input from a sensor array and consisted of a retina-like two-dimensional neuronal layer. The dual-path portion of the model was composed of interconnections of the neurons that formed a mosaic of AC transient and DC sustained paths. The spatial aggregates of the AC and DC signals were input to the AC and DC summing neurons, respectively. Finally, the weighted sum of the aggregate AC and DC signals provided the output for driving the pupillary response. An important property of the model was that it could adaptively learn from training samples by adjustment of the weights. The neural network mosaic model showed excellent performance in simulating both the traditional pupillary phenomena and the new spatial stimulation findings such as responses to change in stimulus pattern and shift of light spot. Moreover, the model could also be used for the diagnosis of clinical deficits and image processing in machine vision. Received: 12 December 1997 / Accepted in revised form: 22 April 1998     

A dynamic neural network with temporal coding and functional connectivity

A neural network model capable of altering its pattern classifying properties by program input is proposed. Here the “program input” is another source of input besides the pattern input. Unlike most neural network models, this model runs as a deterministic point process of spikes in continuous time; connections among neurons have finite delays, which are set randomly according to a normal distribution. Furthermore, this model utilizes functional connectivity which is dynamic connectivity among neurons peculiar to temporal-coding neural networks with short neuronal decay time constants. Computer simulation of the proposed network has been performed, and the results are considered in light of experimental results shown recently for correlated firings of neurons. Received: 6 December 1996 / Accepted in revised form: 15 September 1997     

Sensor fusion by neural networks using spatially represented information

 A neural network model based on a lateral-inhibition-type feedback layer is analyzed with regard to its capabilities to fuse signals from two different sensors reporting the same event (“multisensory convergence”). The model consists of two processing stages. The input stage holds spatial representations of the sensor signals and transmits them to the second stage where they are fused. If the input signals differ, the model exhibits two different processing modes: with small differences it produces a weighted average of the input signals, whereas with large differences it enters a decision mode where one of the two signals is suppressed. The dynamics of the network can be described by a series of two first-order low-pass filters, whose bandwidth depends nonlinearly on the level of concordance of the input signals. The network reduces sensor noise by means of both its averaging and filtering properties. Hence noise suppression, too, depends on the level of concordance of the inputs. When the network's neurons have internal noise, sensor noise suppression is reduced but still effective as long as the input signals do not differ strongly. The possibility of extending the scheme to three and more inputs is discussed. Received: 2 August 2000 / Accepted in revised form: 3 May 2001     

A neural network simulation of the vestibular system: implications on the role of intervestibular nuclear coupling during vestibular compensation

 Previous neural network simulations of the vestibular system have been based loosely on known physiology. This research involved the use of a strongly physiologically based neural network model which was used to investigate the role of the vestibular commissure in restoring the bilateral symmetry of the resting rates of the vestibular nuclei during vestibular compensation following unilateral labyrinthectomy. It was found that readjustments in the gain of the vestibular commissure were not primarily responsible for vestibular compensation, as has previously been suggested, but rather that it was modifications in extralabyrinthine sources of tone which mediated the restoration of the central symmetry between the two nuclei. Received: 20 November 1995/Accepted in revised form: 24 July 1996     

Coupled map lattice simulation of epileptogenesis in hippocampal slices

Bioelectric activity of a nervous tissue and its synchronization with formating epileptiform bursts are simulated by a coupled map lattice. The functional units of the map located in the lattice sites represent neural masses which consist of current sources and sinks. The sources lead to depolarization of neurons, and sinks provide hyperpolarization. The map describes a single variable – the bioelectric potential. This potential is created by the interplay of all current sources and sinks in the neural masses. The neural masses are diffusively coupled with each other both by electrotonic influence and synaptic coupling. Both mechanisms mentioned are suggested to be essential for the formation of synchronous bursts. The transition from chaotic activity to bursts was studied. Received: 30 September 1997 / Accepted in revised from: 11 March 1998     

Psychophysical Evaluation of Congenital Colour Vision Deficiency: Discrimination between Protans and Deutans Using Mollon-Reffin’s Ellipses and the Farnsworth-Munsell 100-Hue Test

We have used the Farnsworth-Munsell 100-hue (FM 100) test and Mollon-Reffin (MR) test to evaluate the colour vision of 93 subjects, 30.4 ± 9.7 years old, who had red-green congenital colour vision deficiencies. All subjects lived in Belém (State of Pará, Brazil) and were selected by the State of Pará Traffic Department. Selection criteria comprised the absence of visual dysfunctions other than Daltonism and no history of systemic diseases that could impair the visual system performance. Results from colour vision deficient were compared with those from 127 normal trichromats, 29.3 ± 10.3 years old. For the MR test, measurements were taken around five points of the CIE 1976 colour space, along 20 directions irradiating from each point, in order to determine with high-resolution the corresponding colour discrimination ellipses (MacAdam ellipses). Three parameters were used to compare results obtained from different subjects: diameter of circle with same ellipse area, ratio between ellipse’s long and short axes, and ellipse long axis angle. For the FM 100 test, the parameters were: logarithm of the total number of mistakes and positions of mistakes in the FM diagram. Data were also simultaneously analysed in two or three dimensions as well as by using multidimensional cluster analysis. For the MR test, Mollon-Reffin Ellipse #3 (u’ = 0.225, v’ = 0.415) discriminated more efficiently than the other four ellipses between protans and deutans once it provided larger angular difference in the colour space between protan and deutan confusion lines. The MR test was more sensitive than the FM 100 test. It separated individuals by dysfunctional groups with greater precision, provided a more sophisticated quantitative analysis, and its use is appropriate for a more refined evaluation of different phenotypes of red-green colour vision deficiencies.     

New methods and uses for fast optical scanning

Advanced optical imaging techniques used in neurobiology commonly employ fluorescent molecules for studying the structure and function of neural tissue. To obtain adequate spatio-temporal resolution, sophisticated scanning schemes are used to manage the excitation light going to and emission light coming from objects under observation. Although the fundamental principles of these techniques remain the same, such as scanning point illumination and point detection for confocal imaging, their physical implementation is the subject of technological advance, for example, the advent of inertia-free discontinuous scanning schemes. In general, the aims of these technological advances are to improve the spatio-temporal resolution of and/or reduce potential photodamage caused by optical imaging in live neural tissue. The number of recent advances in scanning methods indicates their increasing importance in imaging techniques.     

Neuromodulation: selected approaches and challenges

The brain operates through complex interactions in the flow of information and signal processing within neural networks. The ‘wiring’ of such networks, being neuronal or glial, can physically and/or functionally go rogue in various pathological states. Neuromodulation, as a multidisciplinary venture, attempts to correct such faulty nets. In this review, selected approaches and challenges in neuromodulation are discussed. The use of water‐dispersible carbon nanotubes has been proven effective in the modulation of neurite outgrowth in culture and in aiding regeneration after spinal cord injury in vivo. Studying neural circuits using computational biology and analytical engineering approaches brings to light geometrical mapping of dynamics within neural networks, much needed information for stimulation interventions in medical practice. Indeed, sophisticated desynchronization approaches used for brain stimulation have been successful in coaxing ‘misfiring’ neuronal circuits to resume productive firing patterns in various human disorders. Devices have been developed for the real‐time measurement of various neurotransmitters as well as electrical activity in the human brain during electrical deep brain stimulation. Such devices can establish the dynamics of electrochemical changes in the brain during stimulation. With increasing application of nanomaterials in devices for electrical and chemical recording and stimulating in the brain, the era of cellular, and even intracellular, precision neuromodulation will soon be upon us.     

Competition in the temporal domain among neural activities phase-locked to subthreshold oscillations

 In the presence of a subthreshold membrane oscillation, analog information may be encoded in the timing of spike generation phase-locked to the oscillation. With this spike timing neural code, a competitive network of inhibitory spiking neurons was shown to achieve a novel timing mechanism of neural activity selection: the neurons had higher probabilities of becoming winners if they were stimulated earlier in each oscillatory cycle. Here the timing mechanism and its robustness are studied both numerically and analytically, and the conditions to yield a given number of winners (the inhibitory neurons that remain active after the competition) are investigated. The analysis revealed that activity selection with a small number of winners is ensured for broad ranges of values of the parameters such as the strength and time constant of inhibition. In particular, the number of winners is almost unchanged for various timing differences between stimuli to different neurons. This implies that the timing mechanism is useful for such biological information processing as requires perception of a relatively small number of significant stimulus components. Received: 24 January 1996 / Accepted in revised form: 24 July 1996     

Characteristics of Human Luminance Discrimination and Modeling a Neural Network Based on the Response Properties of the Visual Cortex

Reaction time (RT) and error rate that depend on stimulus duration were measured in a luminance-discrimination reaction time task. Two patches of light with different luminance were presented to participants for ‘short’ (150 ms) or ‘long’ (1 s) period on each trial. When the stimulus duration was ‘short’, the participants responded more rapidly with poorer discrimination performance than they did in the longer duration. The results suggested that different sensory responses in the visual cortices were responsible for the dependence of response speed and accuracy on the stimulus duration during the luminance-discrimination reaction time task. It was shown that the simple winner-take-all-type neural network model receiving transient and sustained stimulus information from the primary visual cortex successfully reproduced RT distributions for correct responses and error rates. Moreover, temporal spike sequences obtained from the model network closely resembled to the neural activity in the monkey prefrontal or parietal area during other visual decision tasks such as motion discrimination and oddball detection tasks.     

The importance of optical optimization in whole slide imaging (WSI) and digital pathology imaging

In the last 10 years, whole slide imaging (WSI) has seen impressive progress not only in image quality and scanning speed but also in the variety of systems available to pathologists. However, we have noticed that most systems have relatively simple optics axes and rely on software to optimize image quality and colour balance. While much can be done in software, this study examines the importance of optics, in particular optical filters, in WSI.Optical resolution is a function of the wavelength of light used and the numerical aperture of the lens system (Resolution = (f) wavelength/2 NA). When illumining light is not conditioned correctly with filters, there is a tendency for the wavelength to shift to longer values (more red) because of the characteristics of the lamps in common use. Most microscopes (but remarkably few WSI devices) correct for this with ND filter for brightness and Blue filter (depends on the light source) for colour correction.Using H&E slides research microscopes (Axiophot, Carl Zeiss MicroImaging, Inc. NY. Eclipse 50i., Nikon Inc. NY) at 20x, an attached digital camera (SPOT RT741 Slider Color, Diagnosis Instruments., MI USA), and a filter set, we examined the effect of filters and software enhancement on digital image quality. The focus value (as evaluated by focus evaluation software developed in house and SPOT imaging Software v4.6) was used as a proxy for image quality. Resolution of tissue features was best with the use of both the Blue and ND filters (in addition to software enhancement). Images without filters but with software enhancement while superficially good, lacked some details of specimen morphology and were unclear compared with the images with filters.The results indicate that the appropriate use of optical filters could measurably improve the appearance and resolution of WSI images.     

Effects of the torso boundary and internal conductivity interfaces in electrocardiography: An evaluation of the ‘Infinite medium’ approximation

The analytic, eccentric spheres model of the torso was used to examine the validity of approximating the ‘infinite medium’ potential by integrating ‘finite medium potentials’ over the torso surface. Although idealized, the analytic model is sophisticated enough for all important torso conductivity and geometry parameters to be preserved in the formulation. The model generates both ‘finite medium’ potentials (for which the torso is surrounded by air) and also ‘infinite medium’ potentials (for which the outermost layer of the torso extends outward to infinity). The finite medium torso potentials were integrated over the torso surface in accordance with the approximation used by many investigators in an effort to make the surface distribution more representative of the primary cardiac sources. The resulting potential distribution was compared with the true infinite medium potential, in which the effects of internal inhomogeneities (secondary sources) were taken into account. The difference between the two representations was found to be significant, and caution should be used when interpreting such data.     

Colour and AOX removal from pulping effluents by algae

A mixed culture of algae was used to treat pulping mill effluent in terms of removing both colour and adsorbably organic halides (AOX). The removal of AOX from pulping effluent increased with increasing initial colour value of the effluent. However, for the total mill effluent (composed of both pulping and bleaching effluents), AOX removal was found to be independent of initial colour value, and was around 70%. Up to 80% removal of colour from pulping effluent was achieved within 30 days under continuous lighting conditions. It was found that algae reduced the colour of pulping effluent of relatively low initial colour more efficiently than that of high initial colour. Under simulated field lighting conditions, up to 60% colour removal from pulping effluent was observed after 60 days of exposure, whereas for the total mill effluent it was up to 64% after 45 days. Total organic carbon and lignin (UVA₂₈₀) were also removed to a significant extent, suggesting that the mechanism of colour removal might not be transformation of the coloured lignin molecules to non-coloured ones. Analysis of alkaline extraction of the algal biomass and material balance findings indicated that the main colour removal mechanism was metabolism rather than adsorption. The experimental results were also analysed using multiple regression techniques and a mathematical model was developed to express the removal of colour from pulping effluents in terms of initial colour value, exposure time and lighting periods as well as interactions between these variables. Received: 12 January 1999 / Revision received: 25 March 1999 / Accepted: 26 March 1999