scholarly journals Mechanism of Motion Direction Detection Based on Barlow’s Retina Inhibitory Scheme in Direction-Selective Ganglion Cells

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1663
Author(s):  
Mianzhe Han ◽  
Yuki Todo ◽  
Zheng Tang
Keyword(s):  
Ganglion Cells ◽  
Direction Selectivity ◽  
Detection Accuracy ◽  
Local Motion ◽  
Motion Direction ◽  
Preferred Direction ◽  
Directional Detection ◽  
Direction Detection ◽  
Series Of Experiments ◽  
Better Than

Previous studies have reported that directionally selective ganglion cells respond strongly in their preferred direction, but are only weakly excited by stimuli moving in the opposite null direction. Various studies have attempted to elucidate the mechanisms underlying direction selectivity with cellular basis. However, these studies have not elucidated the mechanism underlying motion direction detection. In this study, we propose the mechanism based on Barlow’s inhibitory scheme for motion direction detection. We described the local motion-sensing direction-selective neurons. Next, this model was used to construct the two-dimensional multi-directional detection neurons which detect the local motion directions. The information of local motion directions was finally used to infer the global motion direction. To verify the validity of the proposed mechanism, we conducted a series of experiments involving a dataset with a number of images. The proposed mechanism exhibited good performance in all experiments with high detection accuracy. Furthermore, we compare the performance of our proposed system and traditional Convolution Neural Network (CNN) on motion direction prediction. It is found that the performance of our system is much better than that of CNN in terms of accuracy, calculation speed and cost.

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.

Functional Inhibition in Direction-Selective Retinal Ganglion Cells: Spatiotemporal Extent and Intralaminar Interactions

2002 ◽  
Vol 88 (2) ◽  
pp. 1026-1039 ◽  
Author(s):  
Steven F. Stasheff ◽  
Richard H. Masland
Keyword(s):  
Ganglion Cells ◽  
Receptive Fields ◽  
Plexiform Layer ◽  
Direction Selectivity ◽  
Inner Plexiform Layer ◽  
Neural Element ◽  
Preferred Direction ◽  
Subsequent Response ◽  
Intermediate Distance ◽  
Excitatory Stimulus

We recorded from on-off direction-selective ganglion cells (DS cells) in the rabbit retina to investigate in detail the inhibition that contributes to direction selectivity in these cells. Using paired stimuli moving sequentially across the cells' receptive fields in the preferred direction, we directly confirmed the prediction of Wyatt and Daw (1975) that a wave of inhibition accompanies any moving excitatory stimulus on its null side, at a fixed spatial offset. Varying the interstimulus distance, stimulus size, luminance, and speed yielded a spatiotemporal map of the strength of inhibition within this region. This “null” inhibition was maximal at an intermediate distance behind a moving stimulus: ½ to 1½ times the width of the receptive field. The strength of inhibition depended more on the distance behind the stimulus than on stimulus speed, and the inhibition often lasted 1–2 s. These spatial and temporal parameters appear to account for the known spatial frequency and velocity tuning of on-off DS cells to drifting contrast gratings. Stimuli that elicit distinct onand off responses to leading and trailing edges revealed that an excitatory response of either polarity could inhibit a subsequent response of either polarity. For example, an offresponse inhibited either an on or off response of a subsequent stimulus. This inhibition apparently is conferred by a neural element or network spanning the on andoff sublayers of the inner plexiform layer, such as a multistratified amacrine cell. Trials using a stationary flashing spot as a probe demonstrated that the total amount of inhibition conferred on the DS cell was equivalent for stimuli moving in either the null or preferred direction. Apparently the cell does not act as a classic “integrate and fire” neuron, summing all inputs at the soma. Rather, computation of stimulus direction likely involves interactions between excitatory and inhibitory inputs in local regions of the dendrites.

Computation of motion direction in the vertebrate retina

e-Neuroforum ◽  
2012 ◽  
Vol 18 (3) ◽  
Author(s):  
T. Euler ◽  
S.E. Hausselt
Keyword(s):  
Large Scale ◽  
Petri Dish ◽  
Cell Types ◽  
Direction Selectivity ◽  
Dendritic Morphology ◽  
Image Motion ◽  
Target Area ◽  
Motion Direction ◽  
Preferred Direction ◽  
The Brain

AbstractHow direction of image motion is detected as early as at the level of the vertebrate eye has been intensively studied in retina research. Although the first direction-selective (DS) ret­inal ganglion cells were already described in the 1960s and have since then been in the fo­cus of many studies, scientists are still puz­zled by the intricacy of the neuronal circuits and computational mechanisms underlying retinal direction selectivity. The fact that the retina can be easily isolated and studied in a Petri dish-by presenting light stimuli while recording from the various cell types in the retinal circuits-in combination with the ex­tensive anatomical, molecular and physiolog­ical knowledge about this part of the brain presents a unique opportunity for studying this intriguing visual circuit in detail. This ar­ticle provides a brief overview of the histo­ry of research on retinal direction selectivi­ty, but then focuses on the past decade and the progress achieved, in particular driven by methodological advances in optical record­ing techniques, molecular genetics approach­es and large-scale ultrastructural reconstruc­tions. As it turns out, retinal direction selec­tivity is a complex, multi-tiered computation, involving dendrite-intrinsic mechanisms as well as several types of network interactions on the basis of highly selective, likely genet­ically predetermined synaptic connectivi­ty. Moreover, DS ganglion cell types appear to be more diverse than previously thought, differing not only in their preferred direction and response polarity, but also in physiology, DS mechanism, dendritic morphology and, importantly, the target area of their projec­tions in the brain.

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 The Most Informative Neural Code Accounts For Population Heterogeneity

2017 ◽  
Author(s):  
Elizabeth Zavitz ◽  
Nicholas SC Price
Keyword(s):  
Machine Learning ◽  
Maximum Level ◽  
Direction Selectivity ◽  
Machine Learning Algorithms ◽  
Population Heterogeneity ◽  
Motion Direction ◽  
Temporal Area ◽  
Firing Rates ◽  
Preferred Direction

AbstractPerception is produced by ‘reading out’ the representation of a sensory stimulus contained in the firing rates 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’ firing rates. This approach is popular because of its biological validity: weights in a computational decoder are analogous to synaptic strengths. For neurons recorded in vivo, weights are highly variable when derived through machine learning methods, but it is unclear what neuronal properties explain this variability, and how the variability affects decoding performance. 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 one of twelve different directions. We found that high gain and direction selectivity both predicted that a neuron would be weighted more highly in an optimised 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 & NoteworthyWe examined which aspects of a neuron’s tuning account for its contribution to sensory coding. Strongly direction-selective neurons were weighted most highly by machine learning algorithms trained to discriminate motion direction. Models with a priori defined decoding weights demonstrate that the learned weighting scheme causally improved direction representation by a neuronal population. Optimising decoders (using machine learning) lead to only marginally better performance than decoders based purely on a neuron’s preferred direction and selectivity.

scholarly journals Conserved Circuits for Direction Selectivity in the Primate Retina

2021 ◽  
Author(s):  
Sara S Patterson ◽  
Briyana N Bembry ◽  
Marcus A Mazzaferri ◽  
Maureen Neitz ◽  
Fred Rieke ◽  
...  
Keyword(s):  
Ganglion Cells ◽  
Selective Inhibition ◽  
Direction Selectivity ◽  
Structural Basis ◽  
Motion Processing ◽  
Retinal Ganglion ◽  
Accessory Optic System ◽  
Motion Direction ◽  
Open Question ◽  
Starburst Amacrine Cell

The detection of motion direction is a fundamental visual function and a classic model for neural computation. In the non-primate mammalian retina, direction selectivity arises in starburst amacrine cell (SAC) dendrites, which provide selective inhibition to ON and ON-OFF direction selective retinal ganglion cells (dsRGCs). While SACs are present in primates, their connectivity is unknown and the existence of primate dsRGCs remains an open question. Here we present a connectomic reconstruction of the primate ON SAC circuit from a serial electron microscopy volume of macaque central retina. We show that the structural basis for the SAC's ability to compute and confer directional selectivity on post-synaptic RGCs is conserved in primates and that SACs selectively target a single ganglion cell type, a candidate homolog to the mammalian ON-sustained dsRGCs that project to the accessory optic system and contribute to gaze-stabilizing reflexes. These results indicate that the capacity to compute motion direction is present in the retina, far earlier in the primate visual system than classically thought, and they shed light on the distinguishing features of primate motion processing by revealing the extent to which ancestral motion circuits are conserved.

Temporal Dynamics of Direction Tuning in Motion-Sensitive Macaque Area MT

2005 ◽  
Vol 93 (4) ◽  
pp. 2104-2116 ◽  
Author(s):  
János A. Perge ◽  
Bart G. Borghuis ◽  
Roger J. E. Bours ◽  
Martin J. M. Lankheet ◽  
Richard J. A. van Wezel
Keyword(s):  
Temporal Dynamics ◽  
Random Sequence ◽  
Nonlinear Effects ◽  
Direction Selectivity ◽  
Second Phase ◽  
Motion Direction ◽  
Area Mt ◽  
Mt Neurons ◽  
Static Nonlinearity ◽  
Preferred Direction

We studied the temporal dynamics of motion direction sensitivity in macaque area MT using a motion reverse correlation paradigm. Stimuli consisted of a random sequence of motion steps in eight different directions. Cross-correlating the stimulus with the resulting neural activity reveals the temporal dynamics of direction selectivity. The temporal dynamics of direction selectivity at the preferred speed showed two phases along the time axis: one phase corresponding to an increase in probability for the preferred direction at short latencies and a second phase corresponding to a decrease in probability for the preferred direction at longer latencies. The strength of this biphasic behavior varied between neurons from weak to very strong and was uniformly distributed. Strong biphasic behavior suggests optimal responses for motion steps in the antipreferred direction followed by a motion step in the preferred direction. Correlating spikes to combinations of motion directions corroborates this distinction. The optimal combination for weakly biphasic cells consists of successive steps in the preferred direction, whereas for strongly biphasic cells, it is a reversal of directions. Comparing reverse correlograms to combinations of stimuli to predictions based on correlograms for individual directions revealed several nonlinear effects. Correlations for successive presentations of preferred directions were smaller than predicted, which could be explained by a static nonlinearity (saturation). Correlations to pairs of (nearly) opposite directions were larger than predicted. These results show that MT neurons are generally more responsive when sudden changes in motion directions occur, irrespective of the preferred direction of the neurons. The latter nonlinearities cannot be explained by a simple static nonlinearity at the output of the neuron, but most likely reflect network interactions.

scholarly journals Global motion processing by populations of direction-selective retinal ganglion cells

2019 ◽  
Author(s):  
Jon Cafaro ◽  
Joel Zylberberg ◽  
Greg Field
Keyword(s):  
Ganglion Cells ◽  
Neural Population ◽  
Mouse Retina ◽  
Motion Processing ◽  
High Temporal Resolution ◽  
Retinal Ganglion ◽  
Global Motion ◽  
Local Motion ◽  
Motion Direction ◽  
Temporal Precision

AbstractSimple stimuli have been critical to understanding neural population codes in sensory systems. Yet it remains necessary to determine the extent to which this understanding generalizes to more complex conditions. To explore this problem, we measured how populations of direction-selective ganglion cells (DSGCs) from mouse retina respond to a global motion stimulus with its direction and speed changing dynamically. We then examined the encoding and decoding of motion direction in both individual and populations of DSGCs. Individual cells integrated global motion over ~200 ms, and responses were tuned to direction. However, responses were sparse and broadly tuned, which severely limited decoding performance from small DSGC populations. In contrast, larger populations compensated for response sparsity, enabling decoding with high temporal precision (<100 ms). At these timescales, correlated spiking was minimal and had little impact on decoding performance, unlike results obtained using simpler local motion stimuli decoded over longer timescales. We use these data to define different DSGC population decoding regimes that utilize or mitigate correlated spiking to achieve high spatial versus high temporal resolution.

Contribution of linear mechanisms to the specification of local motion by simple cells in areas 17 and 18 of the cat

1994 ◽  
Vol 11 (2) ◽  
pp. 271-294 ◽  
Author(s):  
J. McLean ◽  
S. Raab ◽  
L. A. Palmer
Keyword(s):  
Direction Selectivity ◽  
Space Time ◽  
Correlation Technique ◽  
Local Motion ◽  
Separable Space ◽  
Linear Superposition ◽  
Simple Cells ◽  
Optimal Velocity ◽  
Preferred Direction ◽  
Areas 17 And 18

AbstractA reverse correlation technique, which permits estimation of three-dimensional first-order properties of receptive fields (RFs), was applied to simple cells in areas 17 and 18 of cat. Two classes of simple cells were found. For one class, the spatial and temporal RF characteristics were Separable, i.e. they could be synthesized as the product of spatial and temporal weighting functions. RFs in the other class were Inseparable, i.e. bright and dark subregions comprising each field were obliquely oriented in space-time. Based on a linear superposition model, these observations led to testable hypotheses: (1) simple cells with separable space-time characteristics should be speed but not direction selective and (2) simple cells with inseparable space-time characteristics should be direction selective and the optimal velocity of moving stimuli should be predictable from the slope of the oriented subregions. These hypotheses were tested by comparing responses to moving bars with those predicted by application of the convolution integral. Linear predictions accounted for waveforms of responses to moving bars in detail. For cells with oriented space-time characteristics, the preferred direction was always predicted correctly and the optimal speed was predicted quite well. Most cells with separable space-time characteristics were not direction selective as predicted. The major discrepancies between measured and predicted behavior were twofold. First, 8/32 cells with separable space-time RFs were direction selective. Second, predicted directional indices were weakly correlated with actual measurements. These conclusions hold for simple cells in both areas 17 and 18. The major difference between simple RFs in these areas is the coarser spatial scale seen in area 18. These results demonstrate a significant linear contribution to the speed and direction selectivity of simple cells in areas 17 and 18. Where additional, nonlinear mechanisms are inferred, they appear to act synergistically with the linear mechanism.

Research of the activity and viability of spermatozoa at different concentrations and proportions of diluents after incubation

2020 ◽  
pp. 88-95
Author(s):  
Svitlana Lobchenko ◽  
Tetiana Husar ◽  
Viktor Lobchenko
Keyword(s):  
Plasma Concentration ◽  
Incubation Time ◽  
Coefficient Of Variation ◽  
Incubation Medium ◽  
Wide Range ◽  
Series Of Experiments ◽  
The Subject ◽  
Boar Spermatozoa ◽  
Native Plasma ◽  
Better Than

The results of studies of the viability of spermatozoa with different incubation time at different concentrations and using different diluents are highlighted in the article. (Un) concentrated spermatozoa were diluented: 1) with their native plasma; 2) medium 199; 3) a mixture of equal volumes of plasma and medium 199. The experiment was designed to generate experimental samples with spermatozoa concentrations prepared according to the method, namely: 0.2; 0.1; 0.05; 0.025 billion / ml. The sperm was evaluated after 2, 4, 6 and 8 hours. The perspective of such a study is significant and makes it possible to research various aspects of the subject in a wide range. In this regard, a series of experiments were conducted in this area. The data obtained are statistically processed and allow us to highlight the results that relate to each stage of the study. In particular, in this article it was found out some regularities between the viability of sperm, the type of diluent and the rate of rarefaction, as evidenced by the data presented in the tables. As a result of sperm incubation, the viability of spermatozoa remains at least the highest trend when sperm are diluted to a concentration of 0.1 billion / ml, regardless of the type of diluent used. To maintain the viability of sperm using this concentration of medium 199 is not better than its native plasma, and its mixture with an equal volume of plasma through any length of time incubation of such sperm. Most often it is at this concentration of sperm that their viability is characterized by the lowest coefficient of variation, regardless of the type of diluent used, which may indicate the greatest stability of the result under these conditions. The viability of spermatozoa with a concentration of 0.1 billion / ml is statistically significantly reduced only after 6 or even 8 hours of incubation. If the sperm are incubated for only 2 hours, regardless of the type of diluent used, the sperm concentrations tested do not affect the viability of the sperm. Key words: boar, spermatozoa, sperm plasma, concentration, incubation, medium 199, activity, viability, rarefaction.

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