A neural model of feature attention in motion perception

We utilize a model of motion perception to link a physiological study of feature attention in cortical motion processing to a psychophysical experiment of motion perception. We explain effects of feature attention by modulatory excitation of neural activity patterns in a framework of biased competition. Our model allows us to qualitatively replicate physiological data concerning attentional modulation and to generate model behavior in a decision experiment that is consistent with psychophysical observations. Furthermore, our investigation makes predictions for future psychophysical experiments.     

A transduction model of the Meissner corpuscle

I propose a transduction model of the Meissner corpuscle that integrates ideas put forth by Freeman and Johnson and results obtained by Looft. The principal development in the present model is its specification that RA receptor potentials are updated as a linear function of stimulus velocity above baseline; the model thus readily accommodates non-sinusoidal input. It also incorporates modifications to Freeman and Johnson's model proposed by Slavík and Bell, namely a period of refractoriness lasting 1 ms followed by a period of hyperexcitability lasting 13.5 ms. The model is applied to various psychophysical and physiological situations: psychophysical threshold vs. frequency, RA afferent impulse rates vs. intensity, impulse regularity vs. frequency, phase retardation vs. frequency, and responses to non-repeating noise and to complex stimuli. Model output closely matches psychophysical and neurophysiological data. The proposed model thus reliably predicts RA afferent responses to arbitrary stimuli and may facilitate the development of theories relating psychophysical phenomena to their underlying neural representations.     

The dynamics of velocity adaptation in human vision

Since Barlow and Hill's classic study of the adaptation of the rabbit ganglion cell to movement [1], there have been several reports that motion adaptation is accompanied by an exponential reduction in spike rate, and similar estimates of the time course of velocity adaptation have been found across species [2-4]. Psychophysical studies in humans have shown that perceived velocity may reduce exponentially with adaptation [5,6]. It has been suggested that the reduction in firing of single cells may constitute the neural substrate of the reduction in perceived speed in humans [1,5-7]. Although a model of velocity coding in which the firing rate directly encodes speed may have the advantage of simplicity, it is not supported by psychophysical research. Furthermore, psychophysical estimates of the time course of perceived speed adaptation are not entirely consistent with physiological estimates. This discrepancy between psychophysical and physiological estimates may be due to the unrealistic assumption that speed is coded in the gross spike rate of neurons in the primary visual cortex. The psychophysical data on motion processing are, however, generally consistent with a model in which perceived velocity is derived from the ratio of two temporal channels [8-14]. We have examined the time course of speed adaptation and recovery to determine whether the observed rates can be better related to the established physiology if a ratio model of velocity processing is assumed. Our results indicate that such a model describes the data well and can accommodate the observed difference in the time courses of physiological and psychophysical processes.     

Testing Neuronal Accounts of Anisotropic Motion Perception with Computational Modelling

There is an over-representation of neurons in early visual cortical areas that respond most strongly to cardinal (horizontal and vertical) orientations and directions of visual stimuli, and cardinal- and oblique-preferring neurons are reported to have different tuning curves. Collectively, these neuronal anisotropies can explain two commonly-reported phenomena of motion perception – the oblique effect and reference repulsion – but it remains unclear whether neuronal anisotropies can simultaneously account for both perceptual effects. We show in psychophysical experiments that reference repulsion and the oblique effect do not depend on the duration of a moving stimulus, and that brief adaptation to a single direction simultaneously causes a reference repulsion in the orientation domain, and the inverse of the oblique effect in the direction domain. We attempted to link these results to underlying neuronal anisotropies by implementing a large family of neuronal decoding models with parametrically varied levels of anisotropy in neuronal direction-tuning preferences, tuning bandwidths and spiking rates. Surprisingly, no model instantiation was able to satisfactorily explain our perceptual data. We argue that the oblique effect arises from the anisotropic distribution of preferred directions evident in V1 and MT, but that reference repulsion occurs separately, perhaps reflecting a process of categorisation occurring in higher-order cortical areas.     

A neural network model for visual motion detection that can explain psychophysical and neurophysiological phenomena

This paper proposes a new neural network model for visual motion detection. The model can well explain both psychophysical findings (the changes of displacement thresholds with stimulus velocity and the perception of apparent motion) and neurophysiological findings (the selectivity for the direction and the velocity of a moving stimulus). To confirm the behavior of the model, numerical examinations were conducted. The results were consistent with both psychophysical and neurophysiological findings.     

A role for calcium release-activated current (CRAC) in cholinergic modulation of electrical activity in pancreatic beta-cells.

S. Bordin and colleagues have proposed that the depolarizing effects of acetylcholine and other muscarinic agonists on pancreatic beta-cells are mediated by a calcium release-activated current (CRAC). We support this hypothesis with additional data, and present a theoretical model which accounts for most known data on muscarinic effects. Additional phenomena, such as the biphasic responses of beta-cells to changes in glucose concentration and the depolarizing effects of the sarco-endoplasmic reticulum calcium ATPase pump poison thapsigargin, are also accounted for by our model. The ability of this single hypothesis, that CRAC is present in beta-cells, to explain so many phenomena motivates a more complete characterization of this current.     

A biologically plausible model of early visual motion processing I: Theory and implementation

A model of local image encoding is described which explicitly incorporates quantitative data about the number density, bandwidth and receptive field organisation of neurons involved in motion detection. The model solves the problem of extracting local velocity on the basis of inputs tuned to spatiotemporal frequency and sensitive to contrast. The spatiotemporally tuned, opponent motion filters are followed by a compressive non-linearity and comprise a first stage. The inter-stage signals are interpreted as those from single neurons and the second stage is modelled as a neural-network layer. The second stage uses semilinear units and models the effect of lateral, on-centre off-surround, intralayer connections. Characterisation of the first stage leads to a clarification of the concept of the psychophysical channel and its relation to physiological data. The quantitative parametrisation of the model allows the simulation of several psychophysical phenomena which are reported in a companion paper.     

Bottom�Cup attention: pulsed PCA transform and pulsed cosine transform

In this paper we propose a computational model of bottom–up visual attention based on a pulsed principal component analysis (PCA) transform, which simply exploits the signs of the PCA coefficients to generate spatial and motional saliency. We further extend the pulsed PCA transform to a pulsed cosine transform that is not only data-independent but also very fast in computation. The proposed model has the following biological plausibilities. First, the PCA projection vectors in the model can be obtained by using the Hebbian rule in neural networks. Second, the outputs of the pulsed PCA transform, which are inherently binary, simulate the neuronal pulses in the human brain. Third, like many Fourier transform-based approaches, our model also accomplishes the cortical center-surround suppression in frequency domain. Experimental results on psychophysical patterns and natural images show that the proposed model is more effective in saliency detection and predict human eye fixations better than the state-of-the-art attention models.     

Coarse-grained modeling reveals the impact of supercoiling and loop length in DNA looping kinetics

Measurements of protein-mediated DNA looping reveal that in vivo conditions favor the formation of loops shorter than those that occur in vitro, yet the precise physical mechanisms underlying this shift remain unclear. To understand the extent to which in vivo supercoiling may explain these shifts, we develop a theoretical model based on coarse-grained molecular simulation and analytical transition state theory, enabling us to map out looping energetics and kinetics as a function of two key biophysical parameters: superhelical density and loop length. We show that loops on the scale of a persistence length respond to supercoiling over a much wider range of superhelical densities and to a larger extent than longer loops. This effect arises from a tendency for loops to be centered on the plectonemic end region, which bends progressively more tightly with superhelical density. This trend reveals a mechanism by which supercoiling favors shorter loop lengths. In addition, our model predicts a complex kinetic response to supercoiling for a given loop length, governed by a competition between an enhanced rate of looping due to torsional buckling and a reduction in looping rate due to chain straightening as the plectoneme tightens at higher superhelical densities. Together, these effects lead to a flattening of the kinetic response to supercoiling within the physiological range for all but the shortest loops. Using experimental estimates for in vivo superhelical densities, we discuss our model’s ability to explain available looping data, highlighting both the importance of supercoiling as a regulatory force in genetics and the additional complexities of looping phenomena in vivo.     

The role of the plant properties in point-to-point arm movements: a robustness study

In recent papers we demonstrated by means of a modeling study that the smoothness of hand paths and the bell-shaped character of hand velocity profiles which have been experimentally observed in point-to-point arm movements can be largely attributed to the biomechanical properties of the arm rather than to specific planning by the central nervous system. In this paper we present a study of the robustness of our earlier results comprising two goals: (i) the determination of the range of model parameters for which such observations remain valid, (ii) the identification of possible relationships between model parameters and kinematic variables. The results of this study imply three conclusions: (i) the valid range of the tested model parameters (namely the main muscle parameters) is large, (ii) the modeled phenomena are well behaved in that parametric changes do not give rise to bifurcations or other behavioral discontinuities in the analyzed ranges, (iii) there exist precise relationships between certain muscle parameters and the time course of the hand velocity. These results point out that the phenomena observed in our previous work are indeed robust and can lead to useful insights into the mechanisms comprising the regulatory action of the central nervous system as well as into the design principles for biologically inspired artificial arms. Received: 4 December 1995 / Accepted in revised form: 6 November 1996     

A Computational Model of Afterimage Rotation in the Peripheral Drift Illusion Based on Retinal ON/OFF Responses

Human observers perceive illusory rotations after the disappearance of circularly repeating patches containing dark-to-light luminance. This afterimage rotation is a very powerful phenomenon, but little is known about the mechanisms underlying it. Here, we use a computational model to show that the afterimage rotation can be explained by a combination of fast light adaptation and the physiological architecture of the early visual system, consisting of ON- and OFF-type visual pathways. In this retinal ON/OFF model, the afterimage rotation appeared as a rotation of focus lines of retinal ON/OFF responses. Focus lines rotated clockwise on a light background, but counterclockwise on a dark background. These findings were consistent with the results of psychophysical experiments, which were also performed by us. Additionally, the velocity of the afterimage rotation was comparable with that observed in our psychophysical experiments. These results suggest that the early visual system (including the retina) is responsible for the generation of the afterimage rotation, and that this illusory rotation may be systematically misinterpreted by our high-level visual system.     

Modelling stereokinetic phenomena by a minimum relative motion assumption: the tilted disk, the ellipsoid and the tilted bar

The stereokinetic phenomena of the tilted disk and of the ellipsoid are visual illusions of depth elicited by a flat figure with elliptic contour rotating at uniform speed in the frontal plane of an observer. Strictly related to the appearance of the ellipsoid is the stereokinetic phenomenon of the tilted bar, elicited by a line segment of constant length rotating at uniform speed in the frontal plane. We present a mathematical model of these phenomena, based on an assumption of minimization by the Visual System of the differences between the lengths of the velocity vectors of the stimulus (minimum relative motion assumption): the "rigidity hypothesis" is able to explain the appearance of the tilted disk but not the appearance of the ellipsoid and of the tilted bar. The theoretical results obtained by our modelling are in good agreement with the experimental observations.     

Presenting Scientific Theories Within Risk Assessments

We propose a structure for presenting risk assessments with the purpose of enhancing the transparency of the selection process of scientific theories and models derived from them. The structure has two stages, with 7 steps, where the stages involve two types of theories: core and auxiliary, which need to be identified in order to explain and evaluate observations and predictions. Core theories are those that are “fundamental” to the phenomena being observed, whereas auxiliary theories are those that describe or explain the actual observation process of the phenomena. The formulation of a scientific theory involves three constitutive components or types of judgments: explanative, evaluative, and regulative or aesthetic, driven by reason. Two perspectives guided us in developing the proposed structure: (1) In a risk assessment explanations based on notions of causality can be used as a tool for developing models and predictions of possible events outside the range of direct experience. The use of causality for development of models is based on judgments, reflecting regulative or aesthetic conceptualizations of different phenomena and how they (should) fit together in the world. (2) Weight of evidence evaluation should be based on falsification principles for excluding models, rather than validation or justification principles that select the best or nearly best-fitting models. Falsification entails discussion that identifies challenges to proposed models, and reconciles apparent inconsistencies between models and data. Based on the discussion of these perspectives the 7 steps of the structure are: the first stage for core theories, (A) scientific concepts, (B) causality network, and (C) mathematical model; and the second stage for auxiliary theories, (D) data interpretation, (E) statistical model, (F) evaluation (weight of evidence), and (G) reconciliation, which includes the actual decision formulation.     

Experimental and computational studies of strain-conduction velocity relationships in cardiac tissue

Velocity of electrical conduction in cardiac tissue is a function of mechanical strain. Although strain-modulated velocity is a well established finding in experimental cardiology, its underlying mechanisms are not well understood. In this work, we summarized potential factors contributing to strain-velocity relationships and reviewed related experimental and computational studies. We presented results from our experimental studies on rabbit papillary muscle, which supported a biphasic relationship of strain and velocity under uni-axial straining conditions. In the low strain range, the strain-velocity relationship was positive. Conduction velocity peaked with 0.59 m/s at 100% strain corresponding to maximal force development. In the high strain range, the relationship was negative. Conduction was reversibly blocked at 118+/-1.8% strain. Reversible block occurred also in the presence of streptomycin. Furthermore, our studies revealed a moderate hysteresis of conduction velocity, which was reduced by streptomycin. We reconstructed several features of the strain-velocity relationship in a computational study with a myocyte strand. The modeling included strain-modulation of intracellular conductivity and stretch-activated cation non-selective ion channels. The computational study supported our hypotheses, that the positive strain-velocity relationship at low strain is caused by strain-modulation of intracellular conductivity and the negative relationship at high strain results from activity of stretch-activated channels. Conduction block was not reconstructed in our computational studies. We concluded this work by sketching a hypothesis for strain-modulation of conduction and conduction block in papillary muscle. We suggest that this hypothesis can also explain uni-axially measured strain-conduction velocity relationships in other types of cardiac tissue, but apparently necessitates adjustments to reconstruct pressure or volume related changes of velocity in atria and ventricles.     

Experimental and computational studies of strain–conduction velocity relationships in cardiac tissue

Velocity of electrical conduction in cardiac tissue is a function of mechanical strain. Although strain-modulated velocity is a well established finding in experimental cardiology, its underlying mechanisms are not well understood. In this work, we summarized potential factors contributing to strain–velocity relationships and reviewed related experimental and computational studies. We presented results from our experimental studies on rabbit papillary muscle, which supported a biphasic relationship of strain and velocity under uni-axial straining conditions. In the low strain range, the strain–velocity relationship was positive. Conduction velocity peaked with 0.59 m/s at 100% strain corresponding to maximal force development. In the high strain range, the relationship was negative. Conduction was reversibly blocked at 118±1.8% strain. Reversible block occurred also in the presence of streptomycin. Furthermore, our studies revealed a moderate hysteresis of conduction velocity, which was reduced by streptomycin. We reconstructed several features of the strain–velocity relationship in a computational study with a myocyte strand. The modeling included strain-modulation of intracellular conductivity and stretch-activated cation non-selective ion channels. The computational study supported our hypotheses, that the positive strain–velocity relationship at low strain is caused by strain-modulation of intracellular conductivity and the negative relationship at high strain results from activity of stretch-activated channels. Conduction block was not reconstructed in our computational studies. We concluded this work by sketching a hypothesis for strain-modulation of conduction and conduction block in papillary muscle. We suggest that this hypothesis can also explain uni-axially measured strain–conduction velocity relationships in other types of cardiac tissue, but apparently necessitates adjustments to reconstruct pressure or volume related changes of velocity in atria and ventricles.     

The effect of morphology upon electrophysiological responses of retinal ganglion cells: simulation results

Retinal ganglion cells (RGCs) display differences in their morphology and intrinsic electrophysiology. The goal of this study is to characterize the ionic currents that explain the behavior of ON and OFF RGCs and to explore if all morphological types of RGCs exhibit the phenomena described in electrophysiological data. We extend our previous single compartment cell models of ON and OFF RGCs to more biophysically realistic multicompartment cell models and investigate the effect of cell morphology on intrinsic electrophysiological properties. The membrane dynamics are described using the Hodgkin - Huxley type formalism. A subset of published patch-clamp data from isolated intact mouse retina is used to constrain the model and another subset is used to validate the model. Two hundred morphologically distinct ON and OFF RGCs are simulated with various densities of ionic currents in different morphological neuron compartments. Our model predicts that the differences between ON and OFF cells are explained by the presence of the low voltage activated calcium current in OFF cells and absence of such in ON cells. Our study shows through simulation that particular morphological types of RGCs are capable of exhibiting the full range of phenomena described in recent experiments. Comparisons of outputs from different cells indicate that the RGC morphologies that best describe recent experimental results are ones that have a larger ratio of soma to total surface area.     

Analytical theory for extracellular electrical stimulation of nerve with focal electrodes. I. Passive unmyelinated axon.

The cable model of a passive, unmyelinated fiber in an applied extracellular field is derived. The solution is valid for an arbitrary, time-varying, applied field, which may be determined analytically or numerically. Simple analytical computations are presented. They explain a variety of known phenomena and predict some previously undescribed properties of extracellular electrical stimulation. The polarization of a fiber in an applied field behaves like the output of a spatial high-pass and temporal low-pass filter of the stimulus. High-frequency stimulation results in a more spatially restricted region of fiber excitation, effectively reducing current spread relative to that produced by low-frequency stimulation. Chronaxie measured extracellularly is a function of electrode position relative to the stimulated fiber, and its value may differ substantially from that obtained intracellularly. Frequency dependence of psychophysical threshold obtained by electrical stimulation of the macaque cochlea closely follows the frequency dependence of single-fiber passive response.     

A laminar cortical model of stereopsis and 3D surface perception: closure and da Vinci stereopsis

A laminar cortical model of stereopsis and 3D surface perception is developed and simulated. The model describes how monocular and binocular oriented filtering interact with later stages of 3D boundary formation and surface filling-in in the LGN and cortical areas V1, V2, and V4. It proposes how interactions between layers 4, 3B, and 2/3 in V1 and V2 contribute to stereopsis, and how binocular and monocular information combine to form 3D boundary and surface representations. The model includes two main new developments: (1) It clarifies how surface-to-boundary feedback from V2 thin stripes to pale stripes helps to explain data about stereopsis. This feedback has previously been used to explain data about 3D figure-ground perception. (2) It proposes that the binocular false match problem is subsumed under the Gestalt grouping problem. In particular, the disparity filter, which helps to solve the correspondence problem by eliminating false matches, is realized using inhibitory interneurons as part of the perceptual grouping process by horizontal connections in layer 2/3 of cortical area V2. The enhanced model explains all the psychophysical data previously simulated by Grossberg and Howe (2003), such as contrast variations of dichoptic masking and the correspondence problem, the effect of interocular contrast differences on stereoacuity, Panum's limiting case, the Venetian blind illusion, stereopsis with polarity-reversed stereograms, and da Vinci stereopsis. It also explains psychophysical data about perceptual closure and variations of da Vinci stereopsis that previous models cannot yet explain.     

Analysis and Modeling of Frequency-Specific Habituation of the Goldfish Vestibulo-Ocular Reflex

Modification of the vestibulo-ocular reflex (VOR) by vestibular habituation is an important paradigm in the study of neural plasticity. The VOR is responsible for rotating the eyes to maintain the direction of gaze during head rotation. The response of the VOR to sinusoidal rotation is quantified by its gain (eye rotational velocity/head rotational velocity) and phase difference (eye velocity phase—inverted head velocity phase). The frequency response of the VOR in naïve animals has been previously modeled as a high-pass filter (HPF). A HPF passes signals above its corner frequency with gain 1 and phase 0 but decreases gain and increases phase lead (positive phase difference) as signal frequency decreases below its corner frequency. Modification of the VOR by habituation occurs after prolonged low-frequency rotation in the dark. Habituation causes a reduction in low-frequency VOR gain and has been simulated by increasing the corner frequency of the HPF model. This decreases gain not only at the habituating frequency but further decreases gain at all frequencies below the new corner frequency. It also causes phase lead to increase at all frequencies below the new corner frequency (up to some asymptotic value). We show that habituation of the goldfish VOR is not a broad frequency phenomena but is frequency specific. A decrease in VOR gain is produced primarily at the habituating frequency, and there is an increase in phase lead at nearby higher frequencies and a decrease in phase lead at nearby lower frequencies (phase crossover). Both the phase crossover and the frequency specific gain decrease make it impossible to simulate habituation of the VOR simply by increasing the corner frequency of the HPF model. The simplest way to simulate our data is to subtract the output of a band-pass filter (BPF) from the output of the HPF model of the naïve VOR. A BPF passes signals over a limited frequency range only. A BPF decreases gain and imparts a phase lag and lead, respectively, as frequency increases and decreases outside this range. Our model produces both the specific decrease in gain at the habituating frequency, and the phase crossover centered on the frequency of habituation. Our results suggest that VOR habituation may be similar to VOR adaptation (in which VOR modification is produced by visual-vestibular mismatch) in that both are frequency-specific phenomena.