Lateral Neural Model of Binocular Rivalry

This article introduces a two-dimensionally extended, neuron-based model for binocular rivalry. The basic block of the model is a certain type of astable multivibrator comprising excitatory and inhibitory neurons. Many of these blocks are laterally coupled on a medium range to provide a two-dimensional layer. Our model, like others, needs noise to reproduce typical stochastic oscillations. Due to its spatial extension, the noise has to be laterally correlated. When the contrast ratio of the pictures varies, their share of the perception time changes in a way that is known from comparable experimental data (Levelt, 1965; Mueller & Blake, 1989). This is a result of the lateral coupling and not a property of the single model block. The presentation of simple and suitable inhomogeneous stimuli leads to an easily describable perception of periodically moving pictures like propagating fronts or breathing spots. This suggests new experiments. Under certain conditions, a bifurcation from static to moving perceptions is predicted and may be checked and employed by future experiments. Recent “paradox” (Logothetis, 1999) observations of two different neuron classes in cortical areas MT (Logothetis & Schall, 1989) and V4 (Leopold & Logothetis, 1996), one that behaves alike under rivaling and nonrivaling conditions and another that drastically changes its behavior, are interpreted as being related to separate inhibitor neurons.

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Stochastic stability of a neural model for binocular rivalry

IEICE Proceeding Series ◽

10.15248/proc.1.739 ◽

2014 ◽

Vol 1 ◽

pp. 739-742

Author(s):

Tetsuya Shimokawa ◽

Kenji Leibnitz ◽

Ferdinand Peper

Keyword(s):

Binocular Rivalry ◽

Stochastic Stability ◽

Neural Model

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The locus of flicker adaptation in the migraine visual system: A dichoptic study

Cephalalgia ◽

10.1177/0333102412462640 ◽

2012 ◽

Vol 33 (1) ◽

pp. 5-19 ◽

Cited By ~ 8

Author(s):

Michel Thabet ◽

Frances Wilkinson ◽

Hugh R Wilson ◽

Olivera Karanovic

Keyword(s):

Visual System ◽

Interocular Transfer ◽

Neural Model ◽

Inhibitory Neurons ◽

High Contrast ◽

Low Contrast ◽

Full Field ◽

Dichoptic Viewing ◽

High Stimulus ◽

And Control

Background Flickering light has been shown to sensitize the migraine visual system at high stimulus contrast while elevating thresholds at low contrast. The present study employs a dichoptic psychophysical paradigm to ask whether the abnormal adaptation to flicker in migraine occurs before or after the binocular combination of inputs from the two eyes in the visual cortex. Methods Following adaptation to high contrast flicker presented to one eye only, flicker contrast increment thresholds were measured in each eye separately using dichoptic viewing. Results Modest interocular transfer of adaptation was seen in both migraine and control groups at low contrast. Sensitization at high contrast in migraine relative to control participants was seen in the adapted eye only, and an unanticipated threshold elevation occurred in the non-adapted eye. Migraineurs also showed significantly lower aversion thresholds to full field flicker than control participants, but aversion scores and increment thresholds were not correlated. Conclusions The results are simulated with a three-stage neural model of adaptation that points to strong adaptation at monocular sites prior to binocular combination, and weaker adaptation at the level of cortical binocular neurons. The sensitization at high contrast in migraine is proposed to result from stronger adaptation of inhibitory neurons, which act as a monocular normalization pool.

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How Noise Affects the Synchronization Properties of Recurrent Networks of Inhibitory Neurons

Neural Computation ◽

10.1162/neco.2006.18.5.1066 ◽

2006 ◽

Vol 18 (5) ◽

pp. 1066-1110 ◽

Cited By ~ 88

Author(s):

Nicolas Brunel ◽

David Hansel

Keyword(s):

Cluster State ◽

Low Noise ◽

Inhibitory Neurons ◽

Neuron Models ◽

Integrate And Fire ◽

Full Picture ◽

The Central Nervous System ◽

Asynchronous State ◽

Stochastic Oscillations ◽

Fully Connected

GABAergic interneurons play a major role in the emergence of various types of synchronous oscillatory patterns of activity in the central nervous system. Motivated by these experimental facts, modeling studies have investigated mechanisms for the emergence of coherent activity in networks of inhibitory neurons. However, most of these studies have focused either when the noise in the network is absent or weak or in the opposite situation when it is strong. Hence, a full picture of how noise affects the dynamics of such systems is still lacking. The aim of this letter is to provide a more comprehensive understanding of the mechanisms by which the asynchronous states in large, fully connected networks of inhibitory neurons are destabilized as a function of the noise level. Three types of single neuron models are considered: the leaky integrate-and-fire (LIF) model, the exponential integrate-and-fire (EIF), model and conductance-based models involving sodium and potassium Hodgkin-Huxley (HH) currents. We show that in all models, the instabilities of the asynchronous state can be classified in two classes. The first one consists of clustering instabilities, which exist in a restricted range of noise. These instabilities lead to synchronous patterns in which the population of neurons is broken into clusters of synchronously firing neurons. The irregularity of the firing patterns of the neurons is weak. The second class of instabilities, termed oscillatory firing rate instabilities, exists at any value of noise. They lead to cluster state at low noise. As the noise is increased, the instability occurs at larger coupling, and the pattern of firing that emerges becomes more irregular. In the regime of high noise and strong coupling, these instabilities lead to stochastic oscillations in which neurons fire in an approximately Poisson way with a common instantaneous probability of firing that oscillates in time.

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Fast cyclic stimulus flashing modulates perception of bi-stable figure

PeerJ ◽

10.7717/peerj.6011 ◽

2018 ◽

Vol 6 ◽

pp. e6011

Author(s):

Henrikas Vaitkevicius ◽

Vygandas Vanagas ◽

Alvydas Soliunas ◽

Algimantas Svegzda ◽

Remigijus Bliumas ◽

...

Keyword(s):

Binocular Rivalry ◽

Necker Cube ◽

Common Mechanism ◽

Perceptual Information ◽

Alternation Rate ◽

Bistable Perception ◽

Perception Time ◽

Neuronal Processing ◽

External Stimuli ◽

The Brain

Many experiments have demonstrated that the rhythms in the brain influence the initial perceptual information processing. We investigated whether the alternation rate of the perception of a Necker cube depends on the frequency and duration of a flashing Necker cube. We hypothesize that synchronization between the external rhythm of a flashing stimulus and the internal rhythm of neuronal processing should change the alternation rate of a Necker cube. Knowing how a flickering stimulus with a given frequency and duration affects the alternation rate of bistable perception, we could estimate the frequency of the internal neuronal processing. Our results show that the perception time of the dominant stimulus depends on the frequency or duration of the flashing stimuli. The duration of the stimuli, at which the duration of the perceived image was maximal, was repeated periodically at 4 ms intervals. We suppose that such results could be explained by the existence of an internal rhythm of 125 cycles/s for bistable visual perception. We can also suppose that it is not the stimulus duration but the precise timing of the moments of switching on of external stimuli to match the internal stimuli which explains our experimental results. Similarity between the effects of flashing frequency on alternation rate of stimuli perception in present and previously performed experiment on binocular rivalry support the existence of a common mechanism for binocular rivalry and monocular perception of ambiguous figures.

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A Neural Model of Olfactory Sensory Memory in the Honeybee's Antennal Lobe

Neural Computation ◽

10.1162/neco.1996.8.1.94 ◽

1996 ◽

Vol 8 (1) ◽

pp. 94-114 ◽

Cited By ~ 15

Author(s):

Christiane Linster ◽

Claudine Masson

Keyword(s):

Experimental Data ◽

Neural Activity ◽

Antennal Lobe ◽

Neural Model ◽

Neural Circuitry ◽

Neural Mechanisms ◽

Sensory Memory ◽

Inhibitory Neurons ◽

Stimulus Offset ◽

Neuronal Assembly

We present a neural model for olfactory sensory memory in the honeybee's antennal lobe. To investigate the neural mechanisms underlying odor discrimination and memorization, we exploit a variety of morphological, physiological, and behavioral data. The model allows us to study the computational capacities of the known neural circuitry, and to interpret under a new light experimental data on the cellular as well as on the neuronal assembly level. We propose a scheme for memorization of the neural activity pattern after stimulus offset by changing the local balance between excitation and inhibition. This modulation is achieved by changing the intrinsic parameters of local inhibitory neurons or synapses.

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An Astable Multivibrator Model of Binocular Rivalry

Perception ◽

10.1068/p170215 ◽

1988 ◽

Vol 17 (2) ◽

pp. 215-228 ◽

Cited By ~ 166

Author(s):

Sidney R Lehky

Keyword(s):

Neural Network ◽

Binocular Rivalry ◽

Weak Coupling ◽

Feedback Inhibition ◽

Reciprocal Inhibition ◽

Astable Multivibrator ◽

Inhibitory Coupling ◽

Binocular Inhibition ◽

The Right ◽

Stable Fusion

The behavior of a neural network model for binocular rivalry is explored through the development of an analogy between it and an electronic astable multivibrator circuit. The model incorporates reciprocal feedback inhibition between signals from the left and the right eyes prior to binocular convergence. The strength of inhibitory coupling determines whether the system undergoes rivalrous oscillations or remains in stable fusion: strong coupling leads to oscillations, weak coupling to fusion. This implies that correlation between spatial patterns presented to the two eyes can affect the strength of binocular inhibition. Finally, computer simulations are presented which show that a reciprocal inhibition model can reproduce the stochastic behavior of rivalry. The model described is a counterexample to claims that reciprocal inhibition models as a class cannot exhibit many of the experimentally observed properties of rivalry.

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Neural model of temporal and stochastic properties of binocular rivalry

Neurocomputing ◽

10.1016/s0925-2312(00)00252-6 ◽

2000 ◽

Vol 32-33 ◽

pp. 843-853 ◽

Cited By ~ 36

Author(s):

George J. Kalarickal ◽

Jonathan A. Marshall

Keyword(s):

Binocular Rivalry ◽

Neural Model ◽

Stochastic Properties

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Detection and Characterization of earth-like Planets

International Astronomical Union Colloquium ◽

10.1017/s0252921100014810 ◽

1997 ◽

Vol 161 ◽

pp. 299-311 ◽

Cited By ~ 22

Author(s):

Jean Marie Mariotti ◽

Alain Léger ◽

Bertrand Mennesson ◽

Marc Ollivier

Keyword(s):

Direct Detection ◽

Contrast Ratio ◽

Angular Size ◽

Physical Nature ◽

Major Axis ◽

Infrared Emission ◽

Space Technology ◽

Semi Major Axis ◽

Earth Like Planets ◽

Visible Wavelengths

AbstractIndirect methods of detection of exo-planets (by radial velocity, astrometry, occultations,...) have revealed recently the first cases of exo-planets, and will in the near future expand our knowledge of these systems. They will provide statistical informations on the dynamical parameters: semi-major axis, eccentricities, inclinations,... But the physical nature of these planets will remain mostly unknown. Only for the larger ones (exo-Jupiters), an estimate of the mass will be accessible. To characterize in more details Earth-like exo-planets, direct detection (i.e., direct observation of photons from the planet) is required. This is a much more challenging observational program. The exo-planets are extremely faint with respect to their star: the contrast ratio is about 10−10at visible wavelengths. Also the angular size of the apparent orbit is small, typically 0.1 second of arc. While the first point calls for observations in the infrared (where the contrast goes up to 10−7) and with a coronograph, the latter implies using an interferometer. Several space projects combining these techniques have been recently proposed. They aim at surveying a few hundreds of nearby single solar-like stars in search for Earth-like planets, and at performing a low resolution spectroscopic analysis of their infrared emission in order to reveal the presence in the atmosphere of the planet of CO H2O and O3. The latter is a good tracer of the presence of oxygen which could be, like on our Earth, released by biological activity. Although extremely ambitious, these projects could be realized using space technology either already available or in development for others missions. They could be built and launched during the first decades on the next century.

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