scholarly journals Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds

2020 ◽  
Vol 114 (4-5) ◽  
pp. 443-460
Author(s):  
Qinbing Fu ◽  
Shigang Yue
Keyword(s):  
Motion Perception ◽  
Computational Modelling ◽  
Fruit Fly ◽  
Neural System ◽  
Direction Selectivity ◽  
System Model ◽  
Wide Field ◽  
Motion Vision ◽  
Preferred Direction ◽  
On And Off Pathways

Abstract Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly Drosophila motion vision pathways and presents computational modelling based on cutting-edge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-field horizontal-sensitive (HS) and vertical-sensitive (VS) systems. The main contributions of this research are on two aspects: (1) the proposed model articulates the forming of both direction-selective and direction-opponent responses, revealed as principal features of motion perception neural circuits, in a feed-forward manner; (2) it also shows robust direction selectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-filtering mechanisms and ensembles of local correlators inside both the ON and OFF pathways, which works effectively to suppress irrelevant background motion or distractors, and to improve the dynamic response. Accordingly, the direction of translating objects is decoded as global responses of both the HS and VS systems with positive or negative output indicating preferred-direction or null-direction translation. The experiments have verified the effectiveness of the proposed neural system model, and demonstrated its responsive preference to faster-moving, higher-contrast and larger-size targets embedded in cluttered moving backgrounds.

scholarly journals How fly neurons compute the direction of visual motion

2019 ◽  
Vol 206 (2) ◽  
pp. 109-124 ◽  
Author(s):  
Alexander Borst ◽  
Jürgen Haag ◽  
Alex S. Mauss
Keyword(s):  
Information Needs ◽  
Visual Motion ◽  
Fruit Fly ◽  
Direction Selectivity ◽  
Image Motion ◽  
Exact Nature ◽  
Motion Information ◽  
Preferred Direction ◽  
Direct Excitation ◽  
Directional Motion

Abstract Detecting the direction of image motion is a fundamental component of visual computation, essential for survival of the animal. However, at the level of individual photoreceptors, the direction in which the image is shifting is not explicitly represented. Rather, directional motion information needs to be extracted from the photoreceptor array by comparing the signals of neighboring units over time. The exact nature of this process as implemented in the visual system of the fruit fly Drosophila melanogaster has been studied in great detail, and much progress has recently been made in determining the neural circuits giving rise to directional motion information. The results reveal the following: (1) motion information is computed in parallel ON and OFF pathways. (2) Within each pathway, T4 (ON) and T5 (OFF) cells are the first neurons to represent the direction of motion. Four subtypes of T4 and T5 cells exist, each sensitive to one of the four cardinal directions. (3) The core process of direction selectivity as implemented on the dendrites of T4 and T5 cells comprises both an enhancement of signals for motion along their preferred direction as well as a suppression of signals for motion along the opposite direction. This combined strategy ensures a high degree of direction selectivity right at the first stage where the direction of motion is computed. (4) At the subsequent processing stage, tangential cells spatially integrate direct excitation from ON and OFF-selective T4 and T5 cells and indirect inhibition from bi-stratified LPi cells activated by neighboring T4/T5 terminals, thus generating flow-field-selective responses.

Organization of orientation and direction selectivity in areas 17 and 18 of cat cerebral cortex

1987 ◽  
Vol 58 (4) ◽  
pp. 676-699 ◽  
Author(s):  
N. E. Berman ◽  
M. E. Wilkes ◽  
B. R. Payne
Keyword(s):  
Receptive Fields ◽  
Direction Selectivity ◽  
Preferred Orientation ◽  
Wide Field ◽  
Area 17 ◽  
Stimulus Motion ◽  
Area 18 ◽  
Preferred Direction ◽  
Area Centralis ◽  
Areas 17 And 18

1. The organization of subunits and sequences subserving preferred stimulus orientation and preferred direction of stimulus motion in cat cerebral cortical areas 17 and 18 was determined by making vertical, tangential, and oblique microelectrode penetrations into those areas. 2. Quantitative measurements of direction selectivity indicated that not all shades of direction selectivity are equally represented in area 17. Peaks in the distribution of direction indices may correspond to the bidirectional, direction biased, and direction selective categories used in qualitative studies. 3. The relationship between preferred direction and location in the visual field was examined for units with receptive fields centered more than 15 degrees from the area centralis. Simple cells had orientation preferences that tended to be parallel to radii extending out from the area centralis. Wide-field complex cells had orientation preferences that tended to be parallel to concentric circles centered on the area centralis; the direction preferences of this group were biased toward motion away from the area centralis. 4. Unit pairs separated by 200 microns or less were 4.2 times as likely to have the same preferred direction as to have opposite preferred directions, indicating that, on average, strings of five neurons have similar direction preferences. 5. Tracks in area 18 showed a similar pattern to those in area 17. 6. In the vertical tracks in area 17 a small proportion (12%) of the units recorded in infragranular layers had preferred orientations that deviated 30 degrees or more from the first unit recorded in the same column. The presence of these cells most likely reflects the relative crowding of columns in infragranular layers, which occurs at the crown of the lateral gyrus. Columns with such large jumps in preferred orientation were not observed in area 18, which occupies a relatively flat region of cortex. 7. In both areas 17 and 18 direction preference in vertical tracks usually reversed at least once, either between supra- and infragranular layers or within infragranular layers. Along these same tracks, orientation preference usually did not change. 8. In tangential tracks, preferred direction and orientation preferences changed together in small increments. Occasionally a large jump in preferred direction would occur with only a small change in preferred orientation. These large jumps were considered to mark the boundaries of the direction sequences. Most frequently these boundaries were separated by 400-600 microns. This value is approximately half the size of a complete set of orientation preferences (700-1,200 microns).(ABSTRACT TRUNCATED AT 400 WORDS)

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.

Cholinergic and GABAergic receptors on fly tangential cells and their role in visual motion detection

1996 ◽  
Vol 76 (3) ◽  
pp. 1786-1799 ◽  
Author(s):  
T. M. Brotz ◽  
A. Borst
Keyword(s):  
Visual Motion ◽  
Direction Selectivity ◽  
Motion Processing ◽  
Wide Field ◽  
Calliphora Erythrocephala ◽  
Lobula Plate ◽  
Preferred Direction ◽  
Visual Motion Processing ◽  
Gabaa Receptor Antagonist ◽  
Alpha Bungarotoxin

1. To identify some of the neurotransmitters involved in the processing of visual motion information the pharmacology of transmitter receptors on motion-sensitive visual interneurons (VS and HS cells) was investigated in an in vitro preparation of the blowfly (Calliphora erythrocephala) brain. Cholinergic and GABAergic drugs were applied in the bath and iontophoretically while recording intracellularly from HS and VS cells. 2. Bath-applied carbachol (10 and 100 microM) leads to a depolarization in HS and VS cells. One micromolar nicotine also has a depolarizing effect. Both agonists are effective in 0 Ca2+/high Mg(2+)-saline, too, which isolates the cells synaptically. The muscarinic agonists pilocarpine and oxotremorine have no effects on the membrane potential. 3. Iontophoretic application of acetylcholine, carbachol, and nicotine depolarizes VS and HS cells. The iontophoretic carbachol response is antagonized by alpha-bungarotoxin (EC50 = 0.19 microM), mecamylamine (EC50 = 0.32 microM), d-tubocurarine (EC50 = 9.5 microM), and bicuculline but not by decamethonium and scopolamine. 4. Bath application of muscimol strongly hyperpolarizes VS cells in normal fly saline. The gamma-aminobutyric acid-C (GABAC)-receptor agonist cis-4-aminocrotonic acid (CACA) has no effects. The hyperpolarizing response to iontophoretic applied muscimol is present in 0 Ca2+/high Mg2+ saline as well as in Co(2+)-containing saline. The muscimol response is reduced in low chloride saline and thus chloride sensitive. The muscimol response is blocked by picrotoxinin (EC50 = 3.4 microM) but not by the GABAA receptor antagonist bicuculline. 5. Taken together the primary responses of the lobula plate tangential cells appear to be nicotinic cholinergic and GABAergic. 6. The pharmacology of natural synaptic input to VS cells was investigated by extracellular electrical stimulation of the medulla. Such evoked excitatory postsynaptic potentials (EPSPs) are blocked reversibly in 0 Ca2+/high Mg2+ saline. The nicotinic antagonists mecamylamine (1 microM) and d-tubocurarine (50-100 microM) abolish or diminish the EPSPs, respectively. 7. The pharmacological data are incorporated into a semicellular model of a visual motion detector favoring a role of lobula plate tangential cells in certain steps of visual motion processing. Cholinergic and GABAergic inputs are an ideal cellular implementation of a linear subtraction of the signals arising from local motion-sensitive elements with opposite preferred direction. Such a mechanism enhances direction-selectivity and, together with dendritic integration, increases the sensitivity of the tangential cells for wide-field motion.

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)

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)

scholarly journals Weighting neurons by selectivity produces near-optimal population codes

2019 ◽  
Vol 121 (5) ◽  
pp. 1924-1937
Author(s):  
Elizabeth Zavitz ◽  
Nicholas S. C. Price
Keyword(s):  
A Priori ◽  
Maximum Level ◽  
Optimization Methods ◽  
Neuronal Population ◽  
Direction Selectivity ◽  
Motion Direction ◽  
Temporal Area ◽  
Linear Discriminant ◽  
Preferred Direction

Perception is produced by “reading out” the representation of a sensory stimulus contained in the activity of a population of neurons. To examine experimentally how populations code information, a common approach is to decode a linearly weighted sum of the neurons’ spike counts. This approach is popular because of the biological plausibility of weighted, nonlinear integration. For neurons recorded in vivo, weights are highly variable when derived through optimization methods, but it is unclear how the variability affects decoding performance in practice. To address this, we recorded from neurons in the middle temporal area (MT) of anesthetized marmosets ( Callithrix jacchus) viewing stimuli comprising a sheet of dots that moved coherently in 1 of 12 different directions. We found that high peak response and direction selectivity both predicted that a neuron would be weighted more highly in an optimized decoding model. Although learned weights differed markedly from weights chosen according to a priori rules based on a neuron’s tuning profile, decoding performance was only marginally better for the learned weights. In the models with a priori rules, selectivity is the best predictor of weighting, and defining weights according to a neuron’s preferred direction and selectivity improves decoding performance to very near the maximum level possible, as defined by the learned weights. NEW & NOTEWORTHY We examined which aspects of a neuron’s tuning account for its contribution to sensory coding. Strongly direction-selective neurons are weighted most highly by optimal decoders trained to discriminate motion direction. Models with predefined decoding weights demonstrate that this weighting scheme causally improved direction representation by a neuronal population. Optimizing decoders (using a generalized linear model or Fisher’s linear discriminant) led to only marginally better performance than decoders based purely on a neuron’s preferred direction and selectivity.

Research on an olfactory neural system model and its applications based on deep learning

2019 ◽  
Vol 32 (10) ◽  
pp. 5713-5724
Author(s):  
Jin Zhang ◽  
Tiantian Tian ◽  
Shengchun Wang ◽  
Xiaofei Liu ◽  
Xuanyu Shu ◽  
...  
Keyword(s):  
Deep Learning ◽  
Neural System ◽  
System Model

scholarly journals Comparison of the Spatial Limits on Direction Selectivity in Visual Areas MT and V1

2005 ◽  
Vol 93 (3) ◽  
pp. 1235-1245 ◽  
Author(s):  
Mark M. Churchland ◽  
Nicholas J. Priebe ◽  
Stephen G. Lisberger
Keyword(s):  
Apparent Motion ◽  
Great Majority ◽  
Spatial Separation ◽  
Direction Selectivity ◽  
Temporal Separation ◽  
Temporal Area ◽  
Mean Values ◽  
V1 Neurons ◽  
Preferred Direction ◽  
The Difference

We recorded responses to apparent motion from directionally selective neurons in primary visual cortex (V1) of anesthetized monkeys and middle temporal area (MT) of awake monkeys. Apparent motion consisted of multiple stationary stimulus flashes presented in sequence, characterized by their temporal separation (Δ t) and spatial separation (Δ x). Stimuli were 8° square patterns of 100% correlated random dots that moved at apparent speeds of 16 or 32°/s. For both V1 and MT, the difference between the response to the preferred and null directions declined with increasing flash separation. For each neuron, we estimated the maximum flash separation for which directionally selective responses were observed. For the range of speeds we used, Δ x provided a better description of the limitation on directional responses than did Δ t. When comparing MT and V1 neurons of similar preferred speed, there was no difference in the maximum Δ x between our samples from the two areas. In both V1 and MT, the great majority of neurons had maximal values of Δ x in the 0.25–1° range. Mean values were almost identical between the two areas. For most neurons, larger flash separations led to both weaker responses to the preferred direction and increased responses to the opposite direction. The former mechanism was slightly more dominant in MT and the latter slightly more dominant in V1. We conclude that V1 and MT neurons lose direction selectivity for similar values of Δ x, supporting the hypothesis that basic direction selectivity in MT is inherited from V1, at least over the range of stimulus speeds represented by both areas.

Response selectivity of neurons in area MT of the macaque monkey during reversible inactivation of area V1

1992 ◽  
Vol 67 (6) ◽  
pp. 1437-1446 ◽  
Author(s):  
P. Girard ◽  
P. A. Salin ◽  
J. Bullier
Keyword(s):  
Receptive Field ◽  
Macaque Monkey ◽  
Direction Selectivity ◽  
Area 17 ◽  
Visual Responses ◽  
Area Mt ◽  
Reversible Inactivation ◽  
Mt Neurons ◽  
Preferred Direction ◽  
Blocking Index

1. Behavioral results in the monkey and clinical studies in human show remarkable residual visual capacities after a lesion of area V1. Earlier work by Rodman et al. demonstrated that visual activity can be recorded in the middle temporal area (MT) of the macaque monkey several weeks after a complete lesion of V1. These authors also tested the effect of a reversible block of area V1 on the visual responses of a small number of neurons in area MT and showed that most of these cells remain visually responsive. From the results of that study, however, it is difficult to assess the contribution of area 17 to the receptive-field selectivity of area MT neurons. To address this question, we have quantitatively measured the effects of a reversible inactivation of area 17 on the direction selectivity of MT neurons. 2. A circular part of the opercular region of area V1 was reversibly inactivated by cooling with a Peltier device. A microelectrode was positioned in the lower layers of V1 to control the total inactivation of that area. Eighty percent of the sites recorded in the retinotopically corresponding region of MT during inactivation of V1 were found to be visually responsive. The importance of the effect was assessed by calculating the blocking index (0 for no effect, 1 for complete inactivation). Approximately one-half of the quantitatively studied neurons gave a blocking index below 0.6, illustrating the strong residual responses recorded in many neurons. 3. Receptive-field properties were examined with multihistograms. It was found that, during inactivation of V1, the preferred direction changed for most neurons but remained close to the preferred direction or to its opposite in the control situation. During inactivation of V1, the average tuning curve of neurons became broader mostly because of strong reductions in the response to directions close to the preferred and nonpreferred. Very little change was observed in the responses for directions at 90 degrees to the optimal. These results are consistent with a model in which direction selectivity is present without an input from V1 but is reinforced by the spatial organization of this excitatory input. 4. Residual responses were found to be highly dependent on the state of anesthesia because they were completely abolished by the addition of 0.4-0.5% halothane to the ventilation gases. Finally, visual responses were recorded in area MT several hours after an acute lesion of area 17.(ABSTRACT TRUNCATED AT 400 WORDS)

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