scholarly journals An Optimization framework for Nonspiking Neuronal Networks and Aided Discovery of a Model for the Elementary Motion Detector

2019 ◽  
Author(s):  
Arunava Banerjee
Keyword(s):  
Optic Lobe ◽  
Optimization Procedure ◽  
Theoretical Models ◽  
Direction Selectivity ◽  
Recurrent Networks ◽  
Motion Detector ◽  
Null Direction ◽  
Optimization Framework ◽  
Preferred Direction ◽  
Low Pass

AbstractWe present a general optimization procedure that given a parameterized network of nonspiking conductance based compartmentally modeled neurons, tunes the parameters to elicit a desired network behavior. Armed with this tool, we address the elementary motion detector problem. Central to established theoretical models, the Hassenstein-Reichardt and Barlow-Levick detectors, are delay lines whose outputs from spatially separated locations are prescribed to be nonlinearly integrated with the direct outputs to engender direction selectivity. The neural implementation of the delays—which are substantial as stipulated by interomatidial angles—has remained elusive although there is consensus regarding the neurons that constitute the network. Assisted by the optimization procedure, we identify parameter settings consistent with the connectivity architecture and physiology of the Drosophila optic lobe, that demonstrates that the requisite delay and the concomitant direction selectivity can emerge from the nonlinear dynamics of small recurrent networks of neurons with simple tonically active synapses. Additionally, although the temporally extended responses of the neurons permit simple synaptic integration of their signals to be sufficient to induce direction selectivity, both preferred direction enhancement and null direction suppression is necessary to abridge the overall response. Finally, the characteristics of the response to drifting sinusoidal gratings are readily explained by the charging-up of the recurrent networks and their low-pass nature.

scholarly journals Complementary mechanisms create direction selectivity in the fly

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Juergen Haag ◽  
Alexander Arenz ◽  
Etienne Serbe ◽  
Fabrizio Gabbiani ◽  
Alexander Borst
Keyword(s):  
Motion Detection ◽  
Visual Motion ◽  
Optic Lobe ◽  
Direction Selectivity ◽  
Neural Computation ◽  
Directional Selectivity ◽  
Motion Sensing ◽  
Null Direction ◽  
Preferred Direction ◽  
High Degree

How neurons become sensitive to the direction of visual motion represents a classic example of neural computation. Two alternative mechanisms have been discussed in the literature so far: preferred direction enhancement, by which responses are amplified when stimuli move along the preferred direction of the cell, and null direction suppression, where one signal inhibits the response to the subsequent one when stimuli move along the opposite, i.e. null direction. Along the processing chain in the Drosophila optic lobe, directional responses first appear in T4 and T5 cells. Visually stimulating sequences of individual columns in the optic lobe with a telescope while recording from single T4 neurons, we find both mechanisms at work implemented in different sub-regions of the receptive field. This finding explains the high degree of directional selectivity found already in the fly’s primary motion-sensing neurons and marks an important step in our understanding of elementary motion detection.

scholarly journals A common directional tuning mechanism of Drosophila motion-sensing neurons in the ON and in the OFF pathway

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Juergen Haag ◽  
Abhishek Mishra ◽  
Alexander Borst
Keyword(s):  
Optic Lobe ◽  
Receptive Fields ◽  
Fruit Fly ◽  
Direction Selectivity ◽  
Motion Sensing ◽  
Null Direction ◽  
Directional Tuning ◽  
Tuning Mechanism ◽  
Preferred Direction ◽  
High Degree

In the fruit fly optic lobe, T4 and T5 cells represent the first direction-selective neurons, with T4 cells responding selectively to moving brightness increments (ON) and T5 cells to brightness decrements (OFF). Both T4 and T5 cells comprise four subtypes with directional tuning to one of the four cardinal directions. We had previously found that upward-sensitive T4 cells implement both preferred direction enhancement and null direction suppression (Haag et al., 2016). Here, we asked whether this mechanism generalizes to OFF-selective T5 cells and to all four subtypes of both cell classes. We found that all four subtypes of both T4 and T5 cells implement both mechanisms, that is preferred direction enhancement and null direction inhibition, on opposing sides of their receptive fields. This gives rise to the high degree of direction selectivity observed in both T4 and T5 cells within each subpopulation.

scholarly journals Substructure of Direction-Selective Receptive Fields in Macaque V1

2003 ◽  
Vol 89 (5) ◽  
pp. 2743-2759 ◽  
Author(s):  
Margaret S. Livingstone ◽  
Bevil R. Conway
Keyword(s):  
Receptive Fields ◽  
Direction Selectivity ◽  
Positive Interactions ◽  
Null Direction ◽  
Simple Cells ◽  
Complex Cells ◽  
Preferred Direction ◽  
Orientation Axis ◽  
Interaction Regions ◽  
Simple And Complex Cells

We used two-dimensional (2-D) sparse noise to map simultaneous and sequential two-spot interactions in simple and complex direction-selective cells in macaque V1. Sequential-interaction maps for both simple and complex cells showed preferred-direction facilitation and null-direction suppression for same-contrast stimulus sequences and the reverse for inverting-contrast sequences, although the magnitudes of the interactions were weaker for the simple cells. Contrast-sign selectivity in complex cells indicates that direction-selective interactions in these cells must occur in antecedent simple cells or in simple-cell-like dendritic compartments. Our maps suggest that direction selectivity, and on andoff segregation perpendicular to the orientation axis, can occur prior to receptive-field elongation along the orientation axis. 2-D interaction maps for some complex cells showed elongated alternating facilitatory and suppressive interactions as predicted if their inputs were orientation-selective simple cells. The negative interactions, however, were less elongated than the positive interactions, and there was an inflection at the origin in the positive interactions, so the interactions were chevron-shaped rather than band-like. Other complex cells showed only two round interaction regions, one negative and one positive. Several explanations for the map shapes are considered, including the possibility that directional interactions are generated directly from unoriented inputs.

scholarly journals Spatially displaced excitation contributes to the encoding of interrupted motion by the retinal direction-selective circuit

2020 ◽  
Author(s):  
Jennifer Ding ◽  
Albert Chen ◽  
Janet Chung ◽  
Hector Acaron Ledesma ◽  
David M. Berson ◽  
...  
Keyword(s):  
Ganglion Cells ◽  
Spatial Location ◽  
Direction Selectivity ◽  
Natural Scenes ◽  
Visual Response ◽  
Null Direction ◽  
Motion Trajectories ◽  
Preferred Direction ◽  
Synchronous Firing ◽  
Spatially Distributed

AbstractSpatially distributed excitation and inhibition collectively shape a visual neuron’s receptive field (RF) properties. In the direction-selective circuit of the mammalian retina, the effects of strong null-direction inhibition of On-Off direction-selective ganglion cells (ON-OFF DSGCs) on their direction selectivity are well-studied. However, how excitatory inputs influence the On-Off DSGC’s visual response is underexplored. Here, we report that the glutamatergic excitation of On-Off DSGCs shows a spatial displacement to the side where preferred-direction motion stimuli approach the soma (the ‘preferred side’). Underlying this displacement is a non-uniform distribution of excitatory conductance across the dendritic span of the DSGC on the preferred-null motion axis. The skewed excitatory RF contributes to robust null-direction spiking during RF activation limited to the preferred side, a potential ethologically relevant signal to encode interrupted or discontinuous motion trajectories abundant in natural scenes. Theoretical analysis indicates that such differential firing patterns of On-Off DSGCs to continuous and interrupted motion stimuli may help leverage synchronous firing to signal the spatial location of a moving object in complex, naturalistic visual environments. Our study highlights that visual circuitry, even the well-defined direction-selective circuit, exploits different sets of neural mechanisms under different stimulus conditions to generate context-dependent neural representations of visual features.

scholarly journals Direction Selectivity in Drosophila Emerges from Preferred-Direction Enhancement and Null-Direction Suppression

2016 ◽  
Vol 36 (31) ◽  
pp. 8078-8092 ◽  
Author(s):  
J. C. S. Leong ◽  
J. J. Esch ◽  
B. Poole ◽  
S. Ganguli ◽  
T. R. Clandinin
Keyword(s):  
Direction Selectivity ◽  
Null Direction ◽  
Preferred Direction

Motion selectivity in macaque visual cortex. I. Mechanisms of direction and speed selectivity in extrastriate area MT

1986 ◽  
Vol 55 (6) ◽  
pp. 1308-1327 ◽  
Author(s):  
A. Mikami ◽  
W. T. Newsome ◽  
R. H. Wurtz
Keyword(s):  
Discharge Rate ◽  
Direction Selectivity ◽  
Peak Discharge ◽  
Spontaneous Discharge ◽  
Null Direction ◽  
Area Mt ◽  
Mt Neurons ◽  
Preferred Direction ◽  
Single Flash ◽  
Temporal Intervals

Mechanisms of direction selectivity and speed selectivity were studied in single neurons of the middle temporal visual area (MT) of behaving macaque monkeys. Visual stimuli were presented in both smooth and stroboscopic motion within a neuron's receptive field as the monkey fixated a stationary point of light. Direction selectivity, speed selectivity, and the spontaneous discharge characteristics of MT neurons in behaving monkeys were similar to those reported in previous studies in anesthetized monkeys. Stroboscopic motion stimuli were sequences of flashes characterized by the spatial and temporal intervals between each flash. The spatial and temporal intervals were systematically varied so that suppressive and facilitatory interactions could be studied in both the preferred and null directions. Suppression and facilitation were measured by subtracting the peak discharge rate elicited by a single flash from the peak discharge rate elicited by a stroboscopic train of flashes. The dominant mechanism of direction selectivity in MT was a pronounced suppression of discharge for motion in the null direction which we interpreted as inhibition. The inhibition was sufficiently potent to abolish the responses to single flashed stimuli when they were embedded in a series of flashes in the null direction, and it frequently reduced the neuronal discharge to a level below the spontaneous firing rate. Facilitation in the preferred direction was a prominent feature of the responses of some, but not all, MT neurons. The peak discharge rate for stroboscopic motion in the preferred direction was more than twice the peak rate to a single flash for approximately 50% of the neurons in our sample. The direction selectivity of most MT neurons showed the effects of both inhibitory and facilitatory mechanisms, and it was not possible to segregate MT neurons into distinct groups on the basis of these measures. Suppressive mechanisms contributed to speed tuning as well as direction tuning. The low-speed cutoff for motion in the preferred direction resulted from suppression in 82% of the neurons tested. The high-speed cutoff resulted from suppression in 32% of the neurons tested. The latter mechanism appeared to be distinct from the inhibitory mechanism which acted in the null direction in that large spatial intervals were required for its activation.

A BIOLOGICALLY PLAUSIBLE ACOUSTIC MOTION DETECTION NEURAL NETWORK

1999 ◽  
Vol 09 (05) ◽  
pp. 453-459 ◽  
Author(s):  
SOFIA CAVACO ◽  
JOHN HALLAM
Keyword(s):  
Neural Network ◽  
Mobile Robot ◽  
Motion Detection ◽  
Detection System ◽  
Motion Detector ◽  
Null Direction ◽  
Motion Direction ◽  
Preferred Direction ◽  
Computational Implementation ◽  
Motion Detection System

In this paper we present an acoustic motion detection system to be used in a small mobile robot. While the first purpose of the system has been to be a reliable computational implementation, cheap enough to be built in hardware, effort has also been taken to construct a biologically plausible solution. The motion detector consists of a neural network composed of motion-direction sensitive neurons with a preferred direction and a preferred region of the azimuth. The system was designed to produce a higher response when stimulated by motion in the preferred direction than in the null direction and that is in fact what the system does, which means that, as desired, the system can detect motion and distinguish its direction.

scholarly journals Modeling simple-cell direction selectivity with normalized, half-squared, linear operators

1993 ◽  
Vol 70 (5) ◽  
pp. 1885-1898 ◽  
Author(s):  
D. J. Heeger
Keyword(s):  
Linear Prediction ◽  
Direction Selectivity ◽  
Linear Operators ◽  
Simple Cell ◽  
Physiological Data ◽  
Simple Cells ◽  
Cell Responses ◽  
Preferred Direction ◽  
Model Cell ◽  
Actual Response

1. A longstanding view of simple cells is that they sum their inputs linearly. However, the linear model falls short of a complete account of simple-cell direction selectivity. We have developed a nonlinear model of simple-cell responses (hereafter referred to as the normalization model) to explain a larger body of physiological data. 2. The normalization model consists of an underlying linear stage along with two additional nonlinear stages. The first is a half-squaring nonlinearity; half-squaring is half-wave rectification followed by squaring. The second is a divisive normalization non-linearity in which each model cell is suppressed by the pooled activity of a large number of cells. 3. By comparing responses with counterphase (flickering) gratings and drifting gratings, researchers have demonstrated that there is a nonlinear contribution to simple-cell responses. Specifically they found 1) that the linear prediction from counterphase grating responses underestimates a direction index computed from drifting grating responses, 2) that the linear prediction correctly estimates responses to gratings drifting in the preferred direction, and 3) that the linear prediction overestimates responses to gratings drifting in the nonpreferred direction. 4. We have simulated model cell responses and derived mathematical expressions to demonstrate that the normalization model accounts for this empirical data. Specifically the model behaves as follows. 1) The linear prediction from counterphase data underestimates the direction index computed from drifting grating responses. 2) The linear prediction from counterphase data overestimates the response to gratings drifting in the nonpreferred direction. The discrepancy between the linear prediction and the actual response is greater when using higher contrast stimuli. 3) For an appropriate choice of contrast, the linear prediction from counterphase data correctly estimates the response to gratings drifting in the preferred direction. For higher contrasts the linear prediction overestimates the actual response, and for lower contrasts the linear prediction underestimates the actual response. 5. In addition, the normalization model is qualitatively consistent with data on the dynamics of simple-cell responses. Tolhurst et al. found that simple cells respond with an initial transient burst of activity when a stimulus first appears. The normalization model behaves similarly; it takes some time after a stimulus first appears before the model cells are fully normalized. We derived the dynamics of the model and found that the transient burst of activity in model cells depends in a particular way on stimulus contrast. The burst is short for high-contrast stimuli and longer for low-contrast stimuli.(ABSTRACT TRUNCATED AT 400 WORDS)

Orthopteran DCMD neuron: a reevaluation of responses to moving objects. II. Critical cues for detecting approaching objects

1992 ◽  
Vol 68 (5) ◽  
pp. 1667-1682 ◽  
Author(s):  
P. J. Simmons ◽  
F. C. Rind
Keyword(s):  
Moving Objects ◽  
Optic Lobe ◽  
Receptive Fields ◽  
Wide Field ◽  
Motion Detector ◽  
Dark Light ◽  
Subsequent Response ◽  
Object Movement ◽  
Line Movement ◽  
Important Stimulus

1. We examine the critical image cues that are used by the locust visual system for the descending contralateral motion detector (DCMD) neuron to distinguish approaching from receding objects. Images were controlled by computer and presented on an electrostatic monitor. 2. Changes in overall luminance elicited much smaller and briefer responses from the DCMD than objects that appeared to approach the eye. Although a decrease in overall luminance might boost the response to an approaching dark object, movement of edges of the image is more important. 3. When two pairs of lines, in a cross-hairs configuration, were moved apart and then together again, the DCMD showed no preference for divergence compared with convergence of edges. A directional response was obtained by either making the lines increase in extent during divergence and decrease in extent during convergence; or by continually increasing the velocity of line movement during divergence and decreasing velocity during convergence. 4. The DCMD consistently gave a larger response to growing than to shrinking solid rectangular images. An increase compared with a decrease in the extent of edge in an image is, therefore, an important cue for the directionality of the response. For single moving edges of fixed extent, the neuron gave the largest response to edges that subtended 15 degrees at the eye. 5. The DCMD was very sensitive to the amount by which an edge traveled between frames on the display screen, with the largest responses generated by 2.5 degrees of travel. This implies that the neurons in the optic lobe that drive this movement-detecting system have receptive fields of about the same extent as a single ommatidium. 6. For edges moving up to 250 degree/s, the excitation of the DCMD increases with velocity. The response to an edge moving at a constant velocity adapts rapidly, in a manner that depends on velocity. Movement over one part of the retina can adapt the subsequent response to movement over another part of the retina. 7. For the DCMD to track and continue to respond to the image of an approaching object, the edges of the image must continually increase in velocity. This is the second important stimulus cue. 8. Edges of opposite contrasts (light-dark compared with dark-light) are processed in separate pathways that inhibit each other. This would contribute to the reduction of responses to wide-field movements.

Directional selectivity and spatiotemporal structure of receptive fields of simple cells in cat striate cortex

1991 ◽  
Vol 66 (2) ◽  
pp. 505-529 ◽  
Author(s):  
R. C. Reid ◽  
R. E. Soodak ◽  
R. M. Shapley
Keyword(s):  
Time Course ◽  
Linear Prediction ◽  
Striate Cortex ◽  
Receptive Fields ◽  
Quantitative Measure ◽  
Direction Selectivity ◽  
Simple Cells ◽  
Preferred Direction ◽  
Orientation Contrast ◽  
Cat Striate Cortex

1. Simple cells in cat striate cortex were studied with a number of stimulation paradigms to explore the extent to which linear mechanisms determine direction selectivity. For each paradigm, our aim was to predict the selectivity for the direction of moving stimuli given only the responses to stationary stimuli. We have found that the prediction robustly determines the direction and magnitude of the preferred response but overestimates the nonpreferred response. 2. The main paradigm consisted of comparing the responses of simple cells to contrast reversal sinusoidal gratings with their responses to drifting gratings (of the same orientation, contrast, and spatial and temporal frequencies) in both directions of motion. Although it is known that simple cells display spatiotemporally inseparable responses to contrast reversal gratings, this spatiotemporal inseparability is demonstrated here to predict a certain amount of direction selectivity under the assumption that simple cells sum their inputs linearly. 3. The linear prediction of the directional index (DI), a quantitative measure of the degree of direction selectivity, was compared with the measured DI obtained from the responses to drifting gratings. The median value of the ratio of the two was 0.30, indicating that there is a significant nonlinear component to direction selectivity. 4. The absolute magnitudes of the responses to gratings moving in both directions of motion were compared with the linear predictions as well. Whereas the preferred direction response showed only a slight amount of facilitation compared with the linear prediction, there was a significant amount of nonlinear suppression in the nonpreferred direction. 5. Spatiotemporal inseparability was demonstrated also with stationary temporally modulated bars. The time course of response to these bars was different for different positions in the receptive field. The degree of spatiotemporal inseparability measured with sinusoidally modulated bars agreed quantitatively with that measured in experiments with stationary gratings. 6. A linear prediction of the responses to drifting luminance borders was compared with the actual responses. As with the grating experiments, the prediction was qualitatively accurate, giving the correct preferred direction but underestimating the magnitude of direction selectivity observed.(ABSTRACT TRUNCATED AT 400 WORDS)

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