Towards a unifying model of neural net activity in the visual cortex

A neural net model describing the non-linear interactions between axonal spikes is presented. It reconciles aspects of pattern recognition (as action of an associative memory) with those of spike synchronization and phase locking. The stability of the synchronized state is studied in detail.     

Calcium response in single osteocytes to locally applied mechanical stimulus: Differences in cell process and cell body

It is proposed that osteocytes embedded in the bone matrix have the ability to sense deformation and/or damage to the matrix and to feed these mechanical signals back to the adaptive bone remodeling process. When osteoblasts differentiate into osteocytes during the bone formation process, they change their morphology to a stellate form with many slender processes. This characteristic cell shape may underlie the differences in mechanosensitivity between the cell processes and cell body. To elucidate the mechanism of cellular response to mechanical stimulus in osteocytes, we investigated the site-dependent response to quantitatively controlled local mechanical stimulus in single osteocytes isolated from chick embryos, using the technique of calcium imaging. A mechanical stimulus was applied to a single osteocyte using a glass microneedle targeting a microparticle adhered to the cell membrane by modification with a monoclonal antibody OB7.3. Application of the local deformation induced calcium transients in the vicinity of the stimulated point and caused diffusive wave propagation of the calcium transient to the entire intracellular region. The rate of cell response to the stimulus was higher when applied to the cell processes than when applied to the cell body. In addition, a large deformation was necessary at the cell body to induce calcium transients, whereas a relatively small deformation was sufficient at the cell processes, suggesting that the mechanosensitivity of the cell processes was higher than that of the cell body. These results suggest that the cell shape with slender processes contributes to the site-dependent mechanosensitivity in osteocytes.     

Olfactory experience modifies the effect of odour on feeding behaviour in a goal-related manner

Natural food odours elicit different behavioural responses in snails. The tentacle carries an olfactory organ, and it either protracts toward a stimulating carrot odour or retraces in a startle-like fashion away from a cucumber odour. The tentacle retraction to cucumber was still present after the snails were fed cucumber during inter-trial periods. Also, snails without any food experience displayed a longer latency to the first bite of cucumber than of carrot and rejected cucumber more often. After tasting these foods, the latency to carrot was not affected while the latency to and number of rejections of cucumber decreased. These results suggest that initial repulsive features of food odour can be only partially compensated by olfactory learning and feeding experience. In the present study, we demonstrated that an invertebrate can be repulsed or attracted by the same natural odour at the same time and that these behavioural responses are likely aimed at achieving different physiologically relevant goals.     

Quantum-like model of behavioral response computation using neural oscillators

In this paper we propose the use of neural interference as the origin of quantum-like effects in the brain. We do so by using a neural oscillator model consistent with neurophysiological data. The model used was shown elsewhere to reproduce well the predictions of behavioral stimulus-response theory. The quantum-like effects are brought about by the spreading activation of incompatible oscillators, leading to an interference-like effect mediated by inhibitory and excitatory synapses.     

Theoretical results for chemotactic response and drift of E. coli in a weak attractant gradient

The bacterium Escherichia coli (E. coli) moves in its natural environment in a series of straight runs, interrupted by tumbles which cause change of direction. It performs chemotaxis towards chemo-attractants by extending the duration of runs in the direction of the source. When there is a spatial gradient in the attractant concentration, this bias produces a drift velocity directed towards its source, whereas in a uniform concentration, E. coli adapts, almost perfectly in case of methyl aspartate. Recently, microfluidic experiments have measured the drift velocity of E. coli in precisely controlled attractant gradients, but no general theoretical expression for the same exists. With this motivation, we study an analytically soluble model here, based on the Barkai-Leibler model, originally introduced to explain the perfect adaptation. Rigorous mathematical expressions are obtained for the chemotactic response function and the drift velocity in the limit of weak gradients and under the assumption of completely random tumbles. The theoretical predictions compare favorably with experimental results, especially at high concentrations. We further show that the signal transduction network weakens the dependence of the drift on concentration, thus enhancing the range of sensitivity.     

Simulation of hand cooling due to touching cold materials

A simple analytical model has been developed to simulate the cooling of the hands due to touching various types of cold material. The model consisted of a slab of tissue, covered on both sides with skin. The only active mechanism was the skin blood flow. The blood flow was controlled by body core temperature, mean skin temperature, and local hand temperature. The blood flowed along the palm before returning via the back of the hand. The control function was adapted from an earlier study, dealing with feet, but enhanced with a cold induced vasodilatation term. The palm of the hand was touching materials that were specified by conductivity and heat capacity. The hand was initially at a steady-state in a neutral environment and then suddenly grabbed the material. The resulting cooling curves have been compared to data from an experiment including six materials (foam, wood, nylon, steel, aluminium and metal at a constant temperature), three temperatures (-10, 0, and 10 degrees C), two thermal states of the body (neutral and 0.4 degrees C raised), and with and without gloves. There was a fair general agreement between the model and the experiment but the model failed to predict three specific effects: the unequal effect of equal 10 degrees C steps in cold surface temperature on the temperature of the palm of the hand, the cooling effect of nylon, and the rapid drop in back of the hand temperature. Nevertheless the overall regression was 0.88 with a standard deviation between model and experiment of about 2.5 degrees C.     

Functional model of biological neural networks

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.     

Assessing the encoding of stimulus attributes with rapid sequences of stimulus events

In a preceding paper (M. Eger and R. Eckhorn, J. Comput. Neurosci., 2002) we have published a three step method for the quantification of transinformation in multi-input and -output neuronal systems. Here we present an extension that applies to rapid series of transient stimuli and thus, fills the gap between the discrete and continuous stimulation paradigm. While the three step method potentially captures all stimulus aspects, the present approach quantifies the discriminability of selected attributes of discrete stimuli and thus, assesses their encoding. Based on simulated and recorded data we investigate the performance of the implemented algorithm. Our approach is illustrated by analyses of neuronal population activity from the visual cortex of the cat, evoked by electrical stimuli of the retina.     

Cardiodynamic response to psychological and cold pressor stress: Further evidence for stimulus response specificity and directional fractionation

In the present study 36 police officers were exposed to a psychological stressor (IQ quiz) and to cold pressor stress while several cardiovascular variables were monitored. Impedance cardiography was used to provide measures of heart rate, stroke volume, cardiac output, myocardial contractility, and total peripheral resistance. In addition, measures of systolic and diastolic blood pressure and peripheral skin temperature were obtained. A multivariate analysis of variance (MANOVA) indicated that significant increases in diastolic and systolic blood pressure during the cold pressor test were mediated by large increases in total peripheral resistance, whereas blood pressure elevation during the IQ quiz were accompanied by significant increases in heart rate and, to a lesser extent, cardiac output. Peripheral skin temperature decreased in response to each stressor. Additional analysis indicated a degree of stimulus specificity for several variables. For example, diastolic blood pressure showed greater increases to cold pressor than quiz, whereas systolic blood pressure increased more with the psychological than the physical stressor. Directional fractionation occurred for both myocardial contractility and cardiac output.     

Techniques for temporal detection of neural sensitivity to external stimulation

We propose a simple measure of neural sensitivity for characterizing stimulus coding. Sensitivity is defined as the fraction of neurons that show positive responses to n stimuli out of a total of N. To determine a positive response, we propose two methods: Fisherian statistical testing and a data-driven Bayesian approach to determine the response probability of a neuron. The latter is non-parametric, data-driven, and captures a lower bound for the probability of neural responses to sensory stimulation. Both methods are compared with a standard test that assumes normal probability distributions. We applied the sensitivity estimation based on the proposed method to experimental data recorded from the mushroom body (MB) of locusts. We show that there is a broad range of sensitivity that the MB response sweeps during odor stimulation. The neurons are initially tuned to specific odors, but tend to demonstrate a generalist behavior towards the end of the stimulus period, meaning that the emphasis shifts from discrimination to feature learning.     

Modeling the host response to inhalation anthrax

Inhalation anthrax, an often fatal infection, is initiated by endospores of the bacterium Bacillus anthracis, which are introduced into the lung. To better understand the pathogenesis of an inhalation anthrax infection, we propose a two-compartment mathematical model that takes into account the documented early events of such an infection. Anthrax spores, once inhaled, are readily taken up by alveolar phagocytes, which then migrate rather quickly out of the lung and into the thoracic/mediastinal lymph nodes. En route, these spores germinate to become vegetative bacteria. In the lymph nodes, the bacteria kill the host cells and are released into the extracellular environment where they can be disseminated into the blood stream and grow to a very high level, often resulting in the death of the infected person. Using this framework as the basis of our model, we explore the probability of survival of an infected individual. This is dependent on several factors, such as the rate of migration and germination events and treatment with antibiotics.     

Simulation of the response of the inner hair cell stereocilia bundle to an acoustical stimulus

Mammalian hearing relies on a cochlear hydrodynamic sensor embodied in the inner hair cell stereocilia bundle. It is presumed that acoustical stimuli induce a fluid shear-driven motion between the tectorial membrane and the reticular lamina to deflect the bundle. It is hypothesized that ion channels are opened by molecular gates that sense tension in tip-links, which connect adjacent stepped rows of stereocilia. Yet almost nothing is known about how the fluid and bundle interact. Here we show using our microfluidics model how each row of stereocilia and their associated tip links and gates move in response to an acoustical input that induces an orbital motion of the reticular lamina. The model confirms the crucial role of the positioning of the tectorial membrane in hearing, and explains how this membrane amplifies and synchronizes the timing of peak tension in the tip links. Both stereocilia rotation and length change are needed for synchronization of peak tip link tension. Stereocilia length change occurs in response to accelerations perpendicular to the oscillatory fluid shear flow. Simulations indicate that nanovortices form between rows to facilitate diffusion of ions into channels, showing how nature has devised a way to solve the diffusive mixing problem that persists in engineered microfluidic devices.     

The influence of early odour experience on the neural response of the olfactory bulb in laboratory mice

Summary In mice (strain NMRI) the influence of olfactory rearing conditions on the ontogenetic development of the bulbar electroencephalogram (EEG) was investigated.The cages of control animals were perfused continually with filtered air, whereas in the three experimental groups geraniol was added to the atmosphere at different times (group G_0–13, from birth till day 13; group G_0–6, from birth till day 6; group G_6–12, from day 6 till day 12). At various ages the EEG of the bulbus olfactorius was studied by means of permanently implanted tungsten electrodes, and the neural response to nest odour and geraniol (10^–2 vol. %) was recorded.No differences were found between the groups regarding the overall development of the bulbar EEG, nor did the raising conditions affect the neural response to nest odour. However, in groups G_0–13 and G_6–12 a marked response to the odour of geraniol was recorded, while in the controls and the individuals that had experienced geraniol only during their first week of life, the bulbar response to this odourant did not differ from that obtained following stimulation with clean air. In the animals of group g_0–13, which were investigated as adults (day 70), the prominent geraniol response was still recordable 2 months after the last contact with the odour.These results indicate that odours experienced during a sensitive period in the nest evoke neuronal alterations in the olfactory system of the mouse that facilitate processing of a known odourant.     

Muscle contraction and relaxation-response time in response to on or off status of visual stimulus

Background

It is unclear whether response time is affected by a stimulus cue, such as a light turned on or off, or if there are differences in response to these cues during a muscle contraction task compared with a muscle relaxation task. The objective of this study was to assess the response time of a relaxation task, including the contraction portion of the task, to a stimulus of a light turned on or off. In addition, we investigated the effect of the pre-contraction level on the relaxation task.

Results

Contraction response time was significantly shorter during the light-on status than during the light-off status (P <0.01), and relaxation response time in each maximum voluntary contraction was significantly longer during the light-on status than during the light-off status (P <0.01). The relaxation response time became longer in order of 25% to 75% maximum voluntary contraction regardless of light-on or -off status, and was significantly longer than the contraction response time (P <0.05-0.01).

Conclusions

This study found that as the contraction level increased, the relaxation response time became longer than the contraction response time regardless of light status. However, contraction response time or relaxation response time findings were opposite to this during the light-on status and light-off status: contraction response time became shorter in the light-on status than in the light-off status and relaxation response time became longer in the light-on status than in the light-off status. These results suggest that the length of each response time is affected by motor control in the higher order brain and involves specific processing in the visual system.     

Multisensory integration in the superior colliculus: a neural network model

Neurons in the superior colliculus (SC) are known to integrate stimuli of different modalities (e.g., visual and auditory) following specific properties. In this work, we present a mathematical model of the integrative response of SC neurons, in order to suggest a possible physiological mechanism underlying multisensory integration in SC. The model includes three distinct neural areas: two unimodal areas (auditory and visual) are devoted to a topological representation of external stimuli, and communicate via synaptic connections with a third downstream area (in the SC) responsible for multisensory integration. The present simulations show that the model, with a single set of parameters, can mimic various responses to different combinations of external stimuli including the inverse effectiveness, both in terms of multisensory enhancement and contrast, the existence of within- and cross-modality suppression between spatially disparate stimuli, a reduction of network settling time in response to cross-modal stimuli compared with individual stimuli. The model suggests that non-linearities in neural responses and synaptic (excitatory and inhibitory) connections can explain several aspects of multisensory integration.     

Exact Bayesian bin classification: a fast alternative to Bayesian classification and its application to neural response analysis

We investigate the general problem of signal classification and, in particular, that of assigning stimulus labels to neural spike trains recorded from single cortical neurons. Finding efficient ways of classifying neural responses is especially important in experiments involving rapid presentation of stimuli. We introduce a fast, exact alternative to Bayesian classification. Instead of estimating the class-conditional densities p(x|y) (where x is a scalar function of the feature[s], y the class label) and converting them to P(y|x) via Bayes’ theorem, this probability is evaluated directly and without the need for approximations. This is achieved by integrating over all possible binnings of x with an upper limit on the number of bins. Computational time is quadratic in both the number of observed data points and the number of bins. The algorithm also allows for the computation of feedback signals, which can be used as input to subsequent stages of inference, e.g. neural network training. Responses of single neurons from high-level visual cortex (area STSa) to rapid sequences of complex visual stimuli are analysed. Information latency and response duration increase nonlinearly with presentation duration, suggesting that neural processing speeds adapt to presentation speeds. Action Editor: Alexander Borst     

Flight behaviour of tsetse flies in host odour plumes: the initial response to leaving or entering odour

ABSTRACT. Free-flying, wild male and female Glossina pallidipes Aust. and G. m. morsitans Westw. were video-recorded in the field in Zimbabwe as they entered or left the side of a host-odour plume in cross-wind flight, or as they overshot a source of host odour in upwind flight (camera 2.5 m up looking down at a 3 times 2.5 m field of view at ground level). 80% of cross-wind odour leavers turned sharply ( turns 95^o), but without regard to wind direction (overshooters behaved essentially the same except that nearly 100% turned). Many fewer flies entering a plume cross wind turned ( c . 60%), and when they did they made much smaller turns ( 58^o); these turns were, however, significantly biassed upwind ( c . 70%). All three classes of fly had similar groundspeeds ( 5.5–6.5 m s^_1) and angular velocities ( 350–400^o s^-1). Clear evidence was obtained of in-flight sensitivity to wind direction: significantly more flies entering odour turned upwind than downwind, and odour losers turning upwind made significantly larger turns than average. The main basis for the different sizes of turn was the different durations of the turning flight, rather than changes in angular velocity or speed. No evidence was found of flies landing after losing contact with odour.     

Travelling waves and EEG patterns during epileptic seizure: analysis with an integrate-and-fire neural network

Epilepsy is characterized by paradoxical patterns of neural activity. They may cause different types of electroencephalogram (EEG), which dynamically change in shape and frequency content during the temporal evolution of seizure. It is generally assumed that these epileptic patterns may originate in a network of strongly interconnected neurons, when excitation dominates over inhibition. The aim of this work is to use a neural network composed of 50 x 50 integrate-and-fire neurons to analyse which parameter alterations, at the level of synapse topology, may induce network instability and epileptic-like discharges, and to study the corresponding spatio-temporal characteristics of electrical activity in the network. We assume that a small group of central neurons is stimulated by a depolarizing current (epileptic focus) and that neurons are connected via a Mexican-hat topology of synapses. A signal representative of cortical EEG (ECoG) is simulated by summing the membrane potential changes of all neurons. A sensitivity analysis on the parameters describing the synapse topology shows that an increase in the strength and in spatial extension of excitatory vs. inhibitory synapses may cause the occurrence of travelling waves, which propagate along the network. These propagating waves may cause EEG patterns with different shape and frequency, depending on the particular parameter set used during the simulations. The resulting model EEG signals include irregular rhythms with large amplitude and a wide frequency content, low-amplitude high-frequency rapid discharges, isolated or repeated bursts, and low-frequency quasi-sinusoidal patterns. A slow progressive temporal variation in a single parameter may cause the transition from one pattern to another, thus generating a highly non-stationary signal which resembles that observed during ECoG measurements. These results may help to elucidate the mechanisms at the basis of some epileptic discharges, and to relate rapid changes in EEG patterns with the underlying alterations at the network level.     

A dynamical model of human immune response to influenza A virus infection

We present a simplified dynamical model of immune response to uncomplicated influenza A virus (IAV) infection, which focuses on the control of the infection by the innate and adaptive immunity. Innate immunity is represented by interferon-induced resistance to infection of respiratory epithelial cells and by removal of infected cells by effector cells (cytotoxic T-cells and natural killer cells). Adaptive immunity is represented by virus-specific antibodies. Similar in spirit to the recent model of Bocharov and Romanyukha [1994. Mathematical model of antiviral immune response. III. Influenza A virus infection. J. Theor. Biol. 167, 323-360], the model is constructed as a system of 10 ordinary differential equations with 27 parameters characterizing the rates of various processes contributing to the course of disease. The parameters are derived from published experimental data or estimated so as to reproduce available data about the time course of IAV infection in a na?ve host. We explore the effect of initial viral load on the severity and duration of the disease, construct a phase diagram that sheds insight into the dynamics of the disease, and perform sensitivity analysis on the model parameters to explore which ones influence the most the onset, duration and severity of infection. To account for the variability and speed of adaptation of the adaptive response to a particular virus strain, we introduce a variable that quantifies the antigenic compatibility between the virus and the antibodies currently produced by the organism. We find that for small initial viral load the disease progresses through an asymptomatic course, for intermediate value it takes a typical course with constant duration and severity of infection but variable onset, and for large initial viral load the disease becomes severe. This behavior is robust to a wide range of parameter values. The absence of antibody response leads to recurrence of disease and appearance of a chronic state with nontrivial constant viral load.     

Parallel morphological/neural processing of hyperspectral images using heterogeneous and homogeneous platforms

The wealth spatial and spectral information available from last-generation Earth observation instruments has introduced extremely high computational requirements in many applications. Most currently available parallel techniques treat remotely sensed data not as images, but as unordered listings of spectral measurements with no spatial arrangement. In thematic classification applications, however, the integration of spatial and spectral information can be greatly beneficial. Although such integrated approaches can be efficiently mapped in homogeneous commodity clusters, low-cost heterogeneous networks of computers (HNOCs) have soon become a standard tool of choice for dealing with the massive amount of image data produced by Earth observation missions. In this paper, we develop a new morphological/neural algorithm for parallel classification of high-dimensional (hyperspectral) remotely sensed image data sets. The algorithm’s accuracy and parallel performance is tested in a variety of homogeneous and heterogeneous computing platforms, using two networks of workstations distributed among different locations, and also a massively parallel Beowulf cluster at NASA’s Goddard Space Flight Center in Maryland.