Preferred Direction Of Motion Research Articles

Fitness benefits of grouping during foraging in beef cattle: Social behaviour or affinity to vegetation resources?

Grouping behaviour in gregarious species expresses a dynamic cost-benefit equilibrium. The balance between costs and benefits differs amongst individuals that were selected to maximize their individual fitness. In environments where resources are limited, benefits of grouping may come at the expense of increased competition over resources. This study aimed to test whether grouping behaviour during foraging in a free-ranging beef cattle herd is a social choice bearing fitness benefits for all participants, or reflects affinity to vegetation resources with possible differentiating fitness benefits. GPS location data were recorded in a herd of 60 beef cows grazing a semi-arid pasture in northern Israel. Pasture vegetation was chemically and spectrally analysed. GPS location data were used to investigate individual and shared foraging locations and the temporal sequence of initiating foraging movement. Co-travel function in ArcPro v3.0 was used to investigate the amount and variability of individual proximity associations and their correlation with fitness. Fitness proxies were conception result (yes/no) and the interval between calving and conception within the cows who conceived. A positive correlation was found between fitness and the individual number of proximity associations, but not with the variability in associations' partners. No significant correlations were found between fitness and vegetation biomass, N content and spectral properties measured by REEVI2 index in foraging locations. Individual sequence of arrival at shared foraging locations and foraging movement initiation sequence were also not correlated with fitness. Vegetation biomass in grouping locations was lower than in individually foraged locations, but no difference was found in N content between individual and shared foraging locations. No differences were found in vegetation biomass and N content between herd foraging locations and random locations, thus no evidence for herd foraging strategy aimed to increase biomass or N consumption was found. No further differences in pasture resources availability, i.e., water, shade, human or predator presence could explain grouping. Circular variance values implied the absence of preferred movement direction. Our results suggest that grouping during foraging is fitness beneficial and is not related to vegetation biomass or N content. Our results further suggest the absence of consistent leading individuals and no significant correlations between foraging movement initiation and fitness. This study provides insights into social and vegetation factors affecting cattle foraging behaviour in constrained pasture, and may allow ranchers to improve grazing management systems. We suggest that further research into pasture characteristics that affect beef cattle pasture location choice is needed.

The collective dynamics of a stochastic Port-Hamiltonian self-driven agent model in one dimension

This paper studies the collective motion of self-driven agents in a one-dimensional space with periodic boundaries, using a stochastic Port-Hamiltonian system (PHS) with symmetric nearest-neighbor interactions and additive Brownian noise as an external input. In the case of a quadratic potential the PHS is an Ornstein-Uhlenbeck process for which we explicitly determine the distribution for any time t ≥ 0 and in the limit t → ∞. In particular, we characterize the collective motion by showing that the agents’ positions tend to build exactly one cluster. This is confirmed in simulations that show rapid and coordinated motion among agents, driven by noise, despite the absence of a preferred direction of motion in the model. Remarkably, the theoretical properties observed in the Ornstein-Uhlenbeck process also emerge in simulations of the nonlinear model incorporating a general interaction potential.

Asymmetry-Enhanced Motion of Urease-Powered Micromotors from Double Emulsion-Templated Microcapsules.

Autonomous motion of enzyme-powered motors has important implications for drug delivery, cell-cell communication, and protocell engineering. Although many of these systems are inspired by the motion of biological cells, most of them lack key structural features, like micrometer-sized boundaries and aqueous compartments, and rely on bubble propulsion to generation motion. In this study, we use droplet microfluidics to generate large populations of cell-sized microcapsules with poly(lactic-co-glycolic acid) shells and functionalize their surfaces with the enzyme urease to drive their motion. We adjust the number of surface functional groups for urease conjugation by preparing microcapsules with two different surfactants, poly(vinyl alcohol) (PVA) and poly(ethylene-alt-maleic anhydride) (PEMA). We also tune the surface roughness of the microcapsules by varying the concentration of silica nanoparticles in the droplet middle phase. We find that PEMA plays a crucial role in increasing the grafting density of urease on the surface of smooth microcapsules, leading to active motion in the presence of urea. In addition, rough microcapsules prepared with PEMA and loaded with comparable amounts of urease move up to three times faster than their smooth counterparts, which we believe is due to an asymmetric distribution of urease on the surface, giving rise to a preferred direction of motion. Taken together, these results provide new insights into the role that various stabilizing agents play in the induction of motion by enzymatic motors prepared from microfluidics, which is a potentially powerful tool for future preparation of motile protocells in biomedicine.

A Transfer entropy-based methodology to analyze information flow under eyes-open and eyes-closed conditions with a clinical perspective

Studying brain dynamics under normal or pathological conditions has proven to be a challenging task, as there is no unified consensus on the best approach. In this article, we present a methodology based on Transfer Entropy to study the information flow between different brain hemispheres in healthy subjects during eyes-open (EO) and eyes-closed (EC) resting states. We used an experimental setup that mimics the technical conditions found in clinical settings and collected data sets from short records of 24 channels electroencephalogram (EEG) at a sampling rate of 65 Hz. Our methodology accounts for interhemispheric and intrahemispheric information flow analysis in both conditions and relies on 4 indexes calculated from the transfer entropy estimations between EEG channels. These indexes provide information on the number, strength, and directionality of active connections. Our results suggest an increase in information transfer in the EC condition for the alpha, beta1, and beta2 frequency bands, but no preferred direction of interhemispheric information movement under either condition. These results are consistent with previously reported studies conducted with denser EEG recordings sampled at a higher rate. In conclusion, our methodology shows a significant difference in the brain’s dynamics of information transfer between EO and EC resting states, which can also be applied to regular clinical sessions.

Diffusion in crowded environments: Trapped by the drift.

The diffusion type is determined not only by microscopic dynamics but also by the environment properties. For example, the environment's fractal structure is responsible for the emergence of subdiffusive scaling of the mean square displacement in Markovian systems because the presence of nontrivially placed obstacles puts constraints on possible displacements. We investigate how the additional action of drift changes properties of the diffusion in the crowded environment. It is shown that the action of a constant drift increases chances of trapping, which suppresses the persistent ballistic motion. Such a diffusion becomes anisotropic because the drift introduces a preferred direction of motion which is further altered by interactions with obstacles. Moreover, individual trajectories display a high level of variability, which is responsible for the macroscopic properties of the diffusing front. Overall, the interplay among drift, diffusion, and a crowded environment, as measured by the time-averaged mean square displacement, is responsible for the emergence of superdiffusive and subdiffusive patterns in the very same system. Importantly, in contrast to free motion, the constant drift can enhance signatures of subdiffusive motion as it increases trapping chances.

The deformation and failure of strip footings on anisotropic cohesionless sloping grounds

AbstractFooting foundations are sometimes built on sloping grounds of natural sand which is highly anisotropic. The anisotropic mechanical behaviour of sand can significantly influence the bearing capacity of a foundation and the failure mechanism of its supporting slope. Neglecting sand anisotropy may lead to overestimated bearing capacity and under‐design of foundations. A numerical investigation on the response of a supporting slope under a strip footing is presented, placing a special focus on the effect of sand anisotropy. A critical state sand model accounting for fabric evolution is used. The nonlocal method has been used to regularize the mesh‐dependency of the numerical solutions. Predictions of the anisotropic model on the bearing capacity of strip footings on slopes are validated by centrifuge test data on Toyoura sand. Compared to the centrifuge test data, an isotropic model may overpredict the bearing capacity of the footing by up to 100% when the model parameters are determined based on test data on a horizontal bedding plane case. When the isotropic model parameters are determined based on test data where the bedding plane is vertical, the predictions of bearing capacity can be improved for some cases but the settlement at failure may be significantly overestimated. The soil body tends to move along the bedding plane upon the footing loading due to the non‐coaxial strain increment caused by fabric anisotropy. The slip surface appears to be deeper with lower bearing capacity when the preferred soil movement direction caused by bedding plane is towards the slope.

Three-dimensional random walk models of individual animal movement and their application to trap counts modelling

Random walks (RWs) have proved to be a powerful modelling tool in ecology, particularly in the study of animal movement. An application of RW concerns trapping which is the predominant sampling method to date in insect ecology and agricultural pest management. A lot of research effort has been directed towards modelling ground-dwelling insects by simulating their movement in 2D, and computing pitfall trap counts, but comparatively very little for flying insects with 3D elevated traps. We introduce the mathematics behind 3D RWs and present key metrics such as the mean squared displacement (MSD) and path sinuosity, which are already well known in 2D. We develop the mathematical theory behind the 3D correlated random walk (CRW) which involves short-term directional persistence and the 3D Biased random walk (BRW) which introduces a long-term directional bias in the movement so that there is an overall preferred movement direction. In this study, we focus on the geometrical aspects of the 3D trap and thus consider three types of shape; a spheroidal trap, a cylindrical trap and a rectangular cuboidal trap. By simulating movement in 3D space, we investigated the effect of 3D trap shapes and sizes and of movement diffusion on trapping efficiency. We found that there is a non-linear dependence of trap counts on the trap surface area or volume, but the effect of volume appeared to be a simple consequence of changes in area. Nevertheless, there is a slight but clear hierarchy of trap shapes in terms of capture efficiency, with the spheroidal trap retaining more counts than a cylinder, followed by the cuboidal type for a given area. We also showed that there is no effect of short-term persistence when diffusion is kept constant, but trap counts significantly decrease with increasing diffusion. Our results provide a better understanding of the interplay between the movement pattern, trap geometry and impacts on trapping efficiency, which leads to improved trap count interpretations, and more broadly, has implications for spatial ecology and population dynamics.

Predictive Visual Motion Extrapolation Emerges Spontaneously and without Supervision at Each Layer of a Hierarchical Neural Network with Spike-Timing-Dependent Plasticity.

The fact that the transmission and processing of visual information in the brain takes time presents a problem for the accurate real-time localization of a moving object. One way this problem might be solved is extrapolation: using an object's past trajectory to predict its location in the present moment. Here, we investigate how a simulated in silico layered neural network might implement such extrapolation mechanisms, and how the necessary neural circuits might develop. We allowed an unsupervised hierarchical network of velocity-tuned neurons to learn its connectivity through spike-timing-dependent plasticity (STDP). We show that the temporal contingencies between the different neural populations that are activated by an object as it moves causes the receptive fields of higher-level neurons to shift in the direction opposite to their preferred direction of motion. The result is that neural populations spontaneously start to represent moving objects as being further along their trajectory than where they were physically detected. Because of the inherent delays of neural transmission, this effectively compensates for (part of) those delays by bringing the represented position of a moving object closer to its instantaneous position in the world. Finally, we show that this model accurately predicts the pattern of perceptual mislocalization that arises when human observers are required to localize a moving object relative to a flashed static object (the flash-lag effect; FLE).SIGNIFICANCE STATEMENT Our ability to track and respond to rapidly changing visual stimuli, such as a fast-moving tennis ball, indicates that the brain is capable of extrapolating the trajectory of a moving object to predict its current position, despite the delays that result from neural transmission. Here, we show how the neural circuits underlying this ability can be learned through spike-timing-dependent synaptic plasticity and that these circuits emerge spontaneously and without supervision. This demonstrates how the neural transmission delays can, in part, be compensated to implement the extrapolation mechanisms required to predict where a moving object is at the present moment.

Spiking Characteristics of Network-Mediated Responses Arising in Direction-Selective Ganglion Cells of Rabbit and Mouse Retinas to Electric Stimulation for Retinal Prostheses.

To restore the sight of individuals blinded by outer retinal degeneration, numerous retinal prostheses have been developed. However, the performance of those implants is still hampered by some factors including the lack of comprehensive understanding of the electrically-evoked responses arising in various retinal ganglion cell (RGC) types. In this study, we characterized the electrically-evoked network-mediated responses (hereafter referred to as electric responses) of ON-OFF direction-selective (DS) RGCs in rabbit and mouse retinas for the first time. Interestingly, both species in common demonstrated strong negative correlations between spike counts of electric responses and direction selective indices (DSIs), suggesting electric stimulation activates inhibitory presynaptic neurons that suppress null direction responses for high direction tuning in their light responses. The DS cells of the two species showed several differences including different numbers of bursts. Also, spiking patterns were more heterogeneous across DS RGCs of rabbits than those of mice. The electric response magnitudes of rabbit DS cells showed positive and negative correlations with ON and OFF light response magnitudes to preferred direction motion, respectively. But the mouse DS cells showed positive correlations in both comparisons. Our Fano Factor (FF) and spike time tiling coefficient (STTC) analyses revealed that spiking consistencies across repeats were reduced in late electric responses in both species. Moreover, the response consistencies of DS RGCs were lower than those of non-DS RGCs. Our results indicate the species-dependent retinal circuits may result in different electric response features and therefore suggest a proper animal model may be crucial in prosthetic researches.

Rock-paper-scissors models with a preferred mobility direction

We investigate a modified spatial stochastic Lotka-Volterra formulation of the rock-paper-scissors model using off-lattice stochastic simulations. In this model one of the species moves preferentially in a specific direction —the level of preference being controlled by a noise strength parameter ( and corresponding to total preference and no preference, respectively)— while the other two species have no preferred direction of motion. We study the behaviour of the system starting from random initial conditions, showing that the species with asymmetric mobility has always an advantage over its predator. We also determine the optimal value of the noise strength parameter which gives the maximum advantage to that species. Finally, we find that the critical number of individuals, below which the probability of extinction becomes significant, decreases as the noise level increases, thus showing that the addition of a preferred mobility direction studied in the present letter does not favour coexistence.

Sensory stimulation in the treatment of children with sleep-related rhythmic movement disorder: a feasibility and acceptability study

BackgroundSleep-related rhythmic movement disorder is characterized by repetitive gross-motor movements at sleep onset or during sleep, which result in clinical consequences such as impact on daytime functioning and injury. No well-established therapies exist today. Substituting the patient’s movements with external sensory stimulation may offer a treatment modality. The aim of the current study was to test the feasibility and acceptability of vestibular stimulation using a rocking bed (Somnomat) in children with rhythmic movement disorder and to assess children’s movement preference.MethodsChildren with rhythmic movement disorder (n = 6, Age: 5–14 years) were studied over three nights in a sleep laboratory: adaptation night (normal bed) and randomised-order baseline (Somnomat) and intervention nights (Somnomat). Child’s preferred movement direction (head-to-toe or side-to-side) and frequency (between 0.25 and 2 Hz), determined during an afternoon protocol, were applied using the Somnomat for 1 h after lights out, and in response to subsequent episodes of rhythmic movement during intervention nights. Comfort assessed using a questionnaire, and objective sleep parameters assessed using videosomnography, were compared.ResultsThe participants’ sometimes violent rhythmic movements did not disturb device performance. All children rated intervention nights equally or more comfortable than baseline nights. Self-reported sleep quality, as well as the number and duration of movement episodes did not significantly differ between baseline and intervention nights.ConclusionsProviding rocking movements using the Somnomat is both technically feasible and acceptable to the target population. The therapeutic value of this novel stimulus substitution for rhythmic movement disorder should now be evaluated in a larger sample over a longer period in the home setting.Trial registrationThe trial was retrospectively registered at clinicaltrials.gov (NCT03528096) on May 17th 2018.

Human group coordination in a sensorimotor task with neuron-like decision-making

The formation of cooperative groups of agents with limited information-processing capabilities to solve complex problems together is a fundamental building principle that cuts through multiple scales in biology from groups of cells to groups of humans. Here, we study an experimental paradigm where a group of humans is joined together to solve a common sensorimotor task that cannot be achieved by a single agent but relies on the cooperation of the group. In particular, each human acts as a neuron-like binary decision-maker that determines in each moment of time whether to be active or not. Inspired by the population vector method for movement decoding, each neuron-like decision-maker is assigned a preferred movement direction that the decision-maker is ignorant about. From the population vector reflecting the group activity, the movement of a cursor is determined, and the task for the group is to steer the cursor into a predefined target. As the preferred movement directions are unknown and players are not allowed to communicate, the group has to learn a control strategy on the fly from the shared visual feedback. Performance is analyzed by learning speed and accuracy, action synchronization, and group coherence. We study four different computational models of the observed behavior, including a perceptron model, a reinforcement learning model, a Bayesian inference model and a Thompson sampling model that efficiently approximates Bayes optimal behavior. The Bayes and especially the Thompson model excel in predicting the human group behavior compared to the other models, suggesting that internal models are crucial for adaptive coordination. We discuss benefits and limitations of our paradigm regarding a better understanding of distributed information processing.

Reaching around obstacles accounts for uncertainty in coordinate transformations

When reaching to a visual target, humans need to transform the spatial target representation into the coordinate system of their moving arm. It has been shown that increased uncertainty in such coordinate transformations, for instance, when the head is rolled toward one shoulder, leads to higher movement variability and influence movement decisions. However, it is unknown whether the brain incorporates such added variability in planning and executing movements. We designed an obstacle avoidance task in which participants had to reach with or without visual feedback of the hand to a visual target while avoiding collisions with an obstacle. We varied coordinate transformation uncertainty by varying head roll (straight, 30° clockwise, and 30° counterclockwise). In agreement with previous studies, we observed that the reaching variability increased when the head was tilted. Indeed, head roll did not influence the number of collisions during reaching compared with the head-straight condition, but it did systematically change the obstacle avoidance behavior. Participants changed the preferred direction of passing the obstacle and increased the safety margins indicated by stronger movement curvature. These results suggest that the brain takes the added movement variability during head roll into account and compensates for it by adjusting the reaching trajectories.NEW & NOTEWORTHY We show that changing body geometry such as head roll results in compensatory reaching behaviors around obstacles. Specifically, we observed head roll causes changed preferred movement direction and increased trajectory curvature. As has been shown before, head roll increases movement variability due to stochastic coordinate transformations. Thus these results provide evidence that the brain must consider the added movement variability caused by coordinate transformations for accurate reach movements.

A phase diagram for bacterial swarming

Bacterial swarming is a rapid mass-migration, in which thousands of cells spread collectively to colonize surfaces. Physically, swarming is a natural example for active particles that use energy to generate motion. Accordingly, understanding the constraints physics imposes on these dynamics is essential for understanding the mechanisms underlying swarming. We present new experiments of swarming Bacillus subtilis mutants with different aspect ratios and at different densities; two physical quantities known to be associated with collective behavior. Analyzing the dynamics reveals a rich phase diagram of qualitatively distinct swarming regimes, describing how cell shape and population density govern the dynamical characteristics of the swarm. In particular, we show that under standard conditions, bacteria inhabit a region of phase space that is associated with rapid mixing and robust dynamics, with homogeneous density and no preferred direction of motion. The results suggest that bacteria have adapted their physical properties to optimize the principle functions assumed for swarming.

Dopamine Gates Visual Signals in Monkey Prefrontal Cortex Neurons

The neurotransmitter dopamine, which acts via the D1-like receptor (D1R) and D2-like receptor (D2R) family, may play an important role in gating sensory information to the prefrontal cortex (PFC). We tested this hypothesis in awake macaques and recorded visual motion-direction tuning functions of single PFC neurons. Using micro-iontophoretic drug application combined with single-unit recordings, we simulated receptor-specific dopaminergic input to the PFC and explored cellular gating mechanisms. We find that stimulating D1Rs, and particularly D2Rs, enhances the single-neuron and populationcoding quality in PFC neurons. D2R stimulation causes aclear increase of the neurons' responses to the preferred motion direction and a decrease to the non-preferred motion direction, thus enhancing neuronal signal-to-noise ratio. Neither D1R nor D2R stimulation had any impact on the neurons' tuning sharpness. These results elucidate the mechanisms of how receptor-specific dopamine effects can act as a gating signal that enables privileged access of sensory information to PFC circuits.

Migratory flight on the Pacific Flyway: strategies and tendencies of wind drift compensation.

Applications of remote sensing data to monitor bird migration usher a new understanding of magnitude and extent of movements across entire flyways. Millions of birds move through the western USA, yet this region is understudied as a migratory corridor. Characterizing movements in the Pacific Flyway offers a unique opportunity to study complementary patterns to those recently highlighted in the Atlantic and Central Flyways. We use weather surveillance radar data from spring and autumn (1995-2018) to examine migrants' behaviours in relation to winds in the Pacific Flyway. Overall, spring migrants tended to drift on winds, but less so at northern latitudes and farther inland from the Pacific coastline. Relationships between winds and autumn flight behaviours were less striking, with no latitudinal or coastal dependencies. Differences in the preferred direction of movement (PDM) and wind direction predicted drift patterns during spring and autumn, with increased drift when wind direction and PDM differences were high. We also observed greater total flight activity through the Pacific Flyway during the spring when compared with the autumn. Such complex relationships among birds' flight strategies, winds and seasonality highlight the variation within a migration system. Characterizations at these scales complement our understanding of strategies to clarify aerial animal movements.

A potential justifying superconductivity and pseudogap formation in high-Tc superconductors

Copper and Iron based high temperature superconductors exhibit d-wave type superconducting gap and order parameter and posses a universal phase diagram. Here a potential is introduced that accounts for high temperature superconductivity, justifies d-wave symmetric behavior, and successfully explains phase diagram’s salient features. This potential is stipulated by principles of special relativity and arises from the difference between the electric potential of moving electrons and the potential of stationary nuclei. In quasi-two-dimensional materials this difference results in an uncompensated angular dependent attraction force in preferred directions of motion and a repulsion force in the perpendicular directions. The attraction force causes d-wave angular dependent superconducting gap and order parameter at high temperatures for d or p orbitals, which are the orbitals involved in Copper and Iron based superconductors. The repulsion force justifies the existence of angular dependent pseudogap and since the attraction and repulsions forces confine electrons to two directions of motion the number of allowed momentum states are reduced resulting in anti-ferromagnetic Mott-insulator behavior. The combination of the attraction and repulsion forces is shown to create charge density waves in these quasi-two-dimensional materials. This potential is able to justify the main features of the universal phase diagram self-consistently.

The destabilization of hydrogen bonds in an external E-field for improved switch performance.

The effect of an electric field on a recently proposed molecular switch based on a quinone analogue was investigated using next-generation quantum theory of atoms in molecules (QTAIM) methodology. The reversal of a homogenous external electric field was demonstrated to improve the "OFF" functioning of the switch. This was achieved by destabilization of the H atom participating in the tautomerization process along the hydrogen bond that defines the switch. The "ON" functioning of the switch, from the position of the tautomerization barrier, is also improved by the reversal of the homogenous external electric field: this result was previously inaccessible. The "ON" and "OFF" functioning of the switch was visualized in terms of the response of the most preferred directions of motion of the electronic charge density to the applied external field. All measures from QTAIM and the stress tensor provide consistent results for the factors affecting the "ON" and "OFF" switch performance. Our analysis therefore demonstrates use for future design of molecular electronic devices. © 2019 Wiley Periodicals, Inc.

Some Special Characteristics of Track and Intensity of Typhoons Over the Western North Pacific

ABSTRACT Joint Typhoon Warning Center (JTWC) Best Track data from 1995 to 2014 are processed to examine some specific patterns and trends shown by Typhoons over the Western North Pacific. With a multivariate dataset of 588 TC cases in hand, we carry out a sub-domain analysis by dividing the Western North Pacific region into domains of 2°x2° and find the preferred regions of genesis, favourable direction of movement, steep recurvature, rapid intensification, and rapid decay. The region from longitude 132°E to 134°E and latitude 16°N to 18°N showed the highest number of cases (19) for rapid intensification (RI) and a general pattern is found that the RI systems occurred mostly in the later half of the year with a negative Pacific Decadal Oscillation (PDO) index. Similarly, the domain from longitude 114°E to 116°E and latitude 26°N to 28°N had the highest probability of 0.857 for rapid decay. The probabilities of recurvature for each sub-domain were calculated for angles 30°, 45°, 60°, 90°, 120° and 150°. The sub-domain around longitude 118°E and latitude 12°N had the steepest recurve of 168.69°. It also had a high probability of 0.714 for a recurvature of greater than 90°. The most taken direction of movement of typhoons around the Western North Pacific were analysed in different ways and along the 16 points of compass, the direction from 270° to 292.5° was found to be the most preferred direction of movement.

A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds.

Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the insect's visual system, a class of specific neurons, called small target motion detectors (STMDs), have been identified as showing exquisite selectivity for small target motion. Some of the STMDs have also demonstrated direction selectivity which means these STMDs respond strongly only to their preferred motion direction. Direction selectivity is an important property of these STMD neurons which could contribute to tracking small targets such as mates in flight. However, little has been done on systematically modeling these directionally selective STMD neurons. In this paper, we propose a directionally selective STMD-based neural network for small target detection in a cluttered background. In the proposed neural network, a new correlation mechanism is introduced for direction selectivity via correlating signals relayed from two pixels. Then, a lateral inhibition mechanism is implemented on the spatial field for size selectivity of the STMD neurons. Finally, a population vector algorithm is used to encode motion direction of small targets. Extensive experiments showed that the proposed neural network not only is in accord with current biological findings, i.e., showing directional preferences but also worked reliably in detecting the small targets against cluttered backgrounds.