Motion Detection Mechanisms Research Articles

Manipulating the Fourier spectra of stimuli comprising a two-frame kinematogram to study early visual motion-detecting mechanisms: Perception versus short latency ocular-following responses.

Two-frame kinematograms have been extensively used to study motion perception in human vision. Measurements of the direction-discrimination performance limits (Dmax) have been the primary subject of such studies, whereas surprisingly little research has asked how the variability in the spatial frequency content of individual frames affects motion processing. Here, we used two-frame one-dimensional vertical pink noise kinematograms, in which images in both frames were bandpass filtered, with the central spatial frequency of the filter manipulated independently for each image. To avoid spatial aliasing, there was no actual leftward-rightward shift of the image: instead, the phases of all Fourier components of the second image were shifted by ±¼ wavelength with respect to those of the first. We recorded ocular-following responses (OFRs) and perceptual direction discrimination in human subjects. OFRs were in the direction of the Fourier components' shift and showed a smooth decline in amplitude, well fit by Gaussian functions, as the difference between the central spatial frequencies of the first and second images increased. In sharp contrast, 100% correct perceptual direction-discrimination performance was observed when the difference between the central spatial frequencies of the first and second images was small, deteriorating rapidly to chance when increased further. Perceptual dependencies moved closer to the OFR ones when subjects were allowed to grade the strength of perceived motion. Response asymmetries common for perceptual judgments and the OFRs suggest that they rely on the same early visual processing mechanisms. The OFR data were quantitatively well described by a model which combined two factors: (1) an excitatory drive determined by a power law sum of stimulus Fourier components' contributions, scaled by (2) a contrast normalization mechanism. Thus, in addition to traditional studies relying on perceptual reports, the OFRs represent a valuable behavioral tool for studying early motion processing on a fine scale.

Using perception and short latency ocular-following responses (OFRs) to study early visual motion-detecting mechanisms.

Using perception and short latency ocular-following responses (OFRs) to study early visual motion-detecting mechanisms.

Eye pupil signals life motion perception.

The ability to readily detect and recognize biological motion (BM) is fundamental to survival and interpersonal communication. However, perception of BM is strongly disrupted when it is shown upside down. This well-known inversion effect is proposed to be caused by a life motion detection mechanism highly tuned to gravity-compatible motion cues. In the current study, we assessed the inversion effect in BM perception using a no-report pupillometry. We found that the pupil size was significantly enlarged when observers viewed upright BMs (gravity-compatible) compared with the inverted counterparts (gravity-incompatible). Importantly, such an effect critically depended on the dynamic biological characteristics, and could be extended to local feet motion signals. These findings demonstrate that the eye pupil can signal gravity-dependent life motion perception. More importantly, with the convenience, objectivity, and noninvasiveness of pupillometry, the current study paves the way for the potential application of pupillary responses in detecting the deficiency of life motion perception in individuals with socio-cognitive disorders.

Visual odometry of Rhinecanthus aculeatus depends on the visual density of the environment

Distance travelled is a crucial metric that underpins an animal’s ability to navigate in the short-range. While there is extensive research on how terrestrial animals measure travel distance, it is unknown how animals navigating in aquatic environments estimate this metric. A common method used by land animals is to measure optic flow, where the speed of self-induced visual motion is integrated over the course of a journey. Whether freely-swimming aquatic animals also measure distance relative to a visual frame of reference is unclear. Using the marine fish Rhinecanthus aculeatus, we show that teleost fish can use visual motion information to estimate distance travelled. However, the underlying mechanism differs fundamentally from previously studied terrestrial animals. Humans and terrestrial invertebrates measure the total angular motion of visual features for odometry, a mechanism which does not vary with visual density. In contrast, the visual odometer used by Rhinecanthus acuelatus is strongly dependent on the visual density of the environment. Odometry in fish may therefore be mediated by a movement detection mechanism akin to the system underlying the optomotor response, a separate motion-detection mechanism used by both vertebrates and invertebrates for course and gaze stabilisation.

The Understanding of ON-Edge Motion Detection Through the Simulation Based on the Connectome of Drosophila’s Optic Lobe

The optic lobe of the fly is one of the prominent model systems for the neural mechanism of the motion detection. How a fly who lives under various visual situations of the nature processes the information from at most a few thousands of ommatidia in their neural circuit for the detection of moving objects is not exactly clear though many computational models of the fly optic lobe as a moving objects detector were suggested. Here we attempted to elucidate the mechanisms of ON-edge motion detection by a simulation approach based on the TEM connectome of Drosophila. Our simulation model of the optic lobe with the NEURON simulator that covers the full scale of ommatidia, reproduced the characteristics of the receptor neurons, lamina monopolar neurons, and T4 cells in the lobula. The contribution of each neuron can be estimated by changing synaptic connection strengths in the simulation and measuring the response to the motion stimulus. Those show the paradelle pathway provide motion detection in the fly optic lobe has more robustness and is more sophisticated than a simple combination of HR and BL systems.

Visual Responses to Moving and Flashed Stimuli of Neurons in Domestic Pigeon (Columba livia domestica) Optic Tectum.

Birds can rapidly and accurately detect moving objects for better survival in complex environments. This visual ability may be attributed to the response properties of neurons in the optic tectum. However, it is unknown how neurons in the optic tectum respond differently to moving objects compared to static ones. To address this question, neuronal activities were recorded from domestic pigeon (Columba livia domestica) optic tectum, responsible for orienting to moving objects, and the responses to moving and flashed stimuli were compared. An encoding model based on the Generalized Linear Model (GLM) framework was established to explain the difference in neuronal responses. The experimental results showed that the first spike latency to moving stimuli was smaller than that to flashed ones and firing rate was higher. The model further implied the faster and stronger response to a moving target result from spatiotemporal integration process, corresponding to the spatially sequential activation of tectal neurons and the accumulation of information in time. This study provides direct electrophysiological evidence about the different tectal neuron responses to moving objects and flashed ones. The findings of this investigation increase our understanding of the motion detection mechanism of tectal neurons.

A novel motion direction detection mechanism based on dendritic computation of direction-selective ganglion cells

The visual system plays a vital role when the brain receives and processes information. Approximately ninety percent of the information received by the brain comes from the visual system, and motion detection is a crucial part of processing visual information. To further understand the generation of direction selectivity, we propose a novel apparent motion detection mechanism using direction-selective ganglion cells (DSGCs). Considering the simplicity of neural computation, each neuron is responsible for detection in a specific direction. For example, eight neurons are employed to detect movements in eight directions, and local information is collected by scanning. The global motion direction is obtained according to the degree of activation of the neurons. We report that this method not only has striking biological similarities with hypercomplex retinal cells, but can also make accurate discriminations. The pioneering mechanism may lead to a new technique for understanding more complex principles of the visual nervous system.

The mechanoreceptors of the trilobite larva ofLimulus polyphemus(Linnaeus, 1758) (Merostomata: Xiphosurida: Limulidae)

AbstractThree types of mechanoreceptors were found on the cuticle of the first post-hatching instar of the trilobite larva of Limulus polyphemus (Linnaeus, 1758) examined by scanning electron microscopy: 1) tactile sensilla on the margin of the carapace of the prosoma; 2) sensilla, adapted to detect near-field sound energy in the form of particle motions and water currents, on the dorsal surface of the carapace covering the prosoma; 3) sensilla, having a helical structure of unknown function and not seen before, on the walking legs and pusher. The morphology of the mechanoreceptors of L. polyphemus, specifically the sensilla capable of sensing particle motions, may shed some light on the mechanisms of near-field sound or particle motion detection of these Jurassic “living fossils.”

Differentiation of Theta Visual Motion from Fourier Motion Requires LC16 and R18C12 Neurons in Drosophila.

SummaryMany animals perceive features of higher-order visual motion that are beyond the spatiotemporal correlations of luminance defined in first-order motion. Although the neural mechanisms of first-order motion detection have become understood in recent years, those underlying higher-order motion perception remain unclear. Here, we established a paradigm to assess the detection of theta motion—a type of higher-order motion—in freely walking Drosophila. Behavioral screening using this paradigm identified two clusters of neurons in the central brain, designated as R18C12, which were required for perception of theta motion but not for first-order motion. Furthermore, theta motion-activated R18C12 neurons were structurally and functionally located downstream of visual projection neurons in lobula, lobula columnar cells LC16, which activated R18C12 neurons via interactions of acetylcholine (ACh) and muscarinic acetylcholine receptors (mAChRs). The current study provides new insights into LC neurons and the neuronal mechanisms underlying visual information processing in complex natural scenes.

Application of Computer Vision in the Construction Industry

In recent years, there is a proliferation of computer vision applications in different industries. Computer vision enables machines to see visually and allows images or videos to be analysed with machine learning algorithms. An abundance of data can be generated daily from sensors, cameras, drones, autonomous robots, BIM (building information model) and other devices. With the help of AI, insights from big data can be drawn to improve construction design, workflow and schedule. In this paper, the focus is to look at computer vision applications that can be employed in the construction industry to resolve construction issues and improve productivity, security and safety of the worksites. Object detection using deep learning algorithm can be employed for inspection of construction material components. This may include contour detection, counting objects and determining size of objects. In terms of security on worksites, facial detection and recognition can be carried out at various points to ensure only qualified people are allowed to enter certain regions to carry out necessary work that include operating on a particular machine. Motion detection mechanism can be deployed in cameras to detect motion in certain regions for surveillance purposes. Real-time interactions of workers and machinery can be captured and workers’ emotions’ can be monitored to check on their wellbeing. Workers’ safety at worksite is always a top concern for companies. Drowsiness detection devices can be installed in cranes to monitor crane operators’ alertness at work. We will look at functionalities provided by OpenCV and discuss the setup, the use and boundary of applications such as object detection, motion detection, facial recognition and drowsiness detection that can be used in the construction industry.

Neuronal Substrates for Infrared Contrast Enhancement and Motion Detection in Rattlesnakes

Pit vipers detect infrared (IR) radiation with loreal pit organs [1] that are connected to the hindbrain by trigeminal nerve fibers [2-4]. The pattern of central afferent termination forms a topographical representation of the sensory periphery within the nucleus of the lateral descending trigeminal tract (LTTD) [4-7]. All LTTD neurons project to another specialized, ipsilateral hindbrain area, the nucleus reticularis caloris (RC) [8-11], before IR signals are integrated with visual signals in the optic tectum [12, 13]. Pit-organ-innervating afferent fibers provoke in individual LTTD neurons a direct, robust spike activity upon peripheral activation [7, 14]. This discharge is truncated by an indirect, delayed synaptic inhibition from afferent fibers of adjacent sensory areas through parallel microcircuitry that converges with afferent fibers onto the same target neurons [7]. Here, we determined the impact of this interaction on IR contrast enhancement and/or motion detection in LTTD and RC neurons using isolated whole-brain preparations of rattlesnakes with intact pit organs. Simulated and real IR source motion provoked weak directional tuning of the discharge in LTTD neurons and RC neurons expressed a strong, motion-direction-differentiating activity. The hierarchically increasing motion sensitivity potentially derives from a direction-specific inhibition or spike frequency adaptation of LTTD neuronal discharge that becomes further pronounced by convergent projections onto individual RC neurons. The emerging signaling pattern complies with contrast enhancement (LTTD) and extraction of movement-related signals (RC), thereby forming a motion detection mechanism that encodes moving IR sources relative to the ambient temperature [14].

Neuronal mechanisms of motion detection underlying blindsight assessed by functional magnetic resonance imaging (fMRI)

Brain imaging offers a valuable tool to observe functional brain plasticity by showing how sensory inputs reshape cortical activations after a visual impairment. Following a unilateral post-chiasmatic lesion affecting the visual cortex, patients may suffer a contralateral visual loss referred to homonymous hemianopia. Nevertheless, these patients preserve the ability to unconsciously detect, localize and discriminate visual stimuli presented in their impaired visual field. To investigate this paradox, known as blindsight, we conducted a study using functional magnetic resonance imaging (fMRI) to evaluate the structural and functional impact of such lesion in a 33-year old patient (ML), who suffers a complete right hemianopia without macular sparing and showing strong evidences of blindsight. We thus performed whole brain and sliced thalamic fMRI scan sequences during an event-related motion detection task. We provided evidence of the neuronal fingerprint of blindsight by acquiring and associating neural correlates, specific structures and functional networks of the midbrain during blindsight performances which may help to better understand this condition. Accurate performance demonstrated the presence of residual vision and the ability to unconsciously perceive motion presented in the blind hemifield, although her reaction time was significantly higher in her blind-field. When the normal hemifield was stimulated, we observed significant contralateral activations in primary and secondary visual areas as well as motion specific areas, such as the supramarginal gyrus and middle temporal area. We also demonstrated sub-thalamic activations within the superior colliculi (SC) and the pulvinar. These results suggest a role of secondary subcortical structures in normal spontaneous motion detection. In a similar way, when the lesioned hemifield was stimulated, we observed contralateral activity in extrastriate areas with no activation of the primary lesioned visual cortex. Moreover, we observed activations within the SC when the blind hemifield was stimulated. However, we observed unexpected ipsilateral activations within the same motion specific areas, as well as bilateral frontal activations. These results highlight the importance of abnormal secondary pathways bypassing the primary visual area (V1) in residual vision. This reorganization in the structure and function of the visual pathways correlates with behavioral changes, thus offering a plausible explanation for the blindsight phenomenon. Our results may potentially impact the development of rehabilitation strategies to target subcortical pathways.

Using fMRI to Identify Neuronal Mechanisms of Motion Detection Underlying Blindsight

Using fMRI to Identify Neuronal Mechanisms of Motion Detection Underlying Blindsight

White noise analysis for the correlation-type elementary motion detectors with half-wave rectifiers

The motion detection mechanism of insects has been attracted attention of many researchers. Several motion-detection models have been proposed on the basis of insect visual system studies. Here, we examine two models, the Hassenstein–Reichardt (HR) model and the two-detector (2D) model. We analytically obtain the mean and variance of the stationary responses of the HR and the 2D models to white noise, and we derive the signal-to-fluctuation-noise ratio (SFNR) to evaluate encoding abilities of the two models. Especially when analyzing the 2D model, we calculate higher-order cumulants of a rectified Gaussian. The results show that the 2D model robustly works almost as well as the HR model in several sets of parameters estimated on the basis of experimental data.

The optomotor response of the praying mantis is driven predominantly by the central visual field

The optomotor response has been widely used to investigate insect sensitivity to contrast and motion. Several studies have revealed the sensitivity of this response to frequency and contrast, but we know less about the spatial integration underlying this response. Specifically, few studies have investigated how the horizontal angular extent of stimuli influences the optomotor response. We presented mantises with moving gratings of varying horizontal extents at three different contrasts in the central or peripheral regions of their visual fields. We assessed the relative effectivity of different regions to elicit the optomotor response and modelled the dependency of the response on the angular extent subtended by stimuli at these different regions. Our results show that the optomotor response is governed by stimuli in the central visual field and not in the periphery. The model also shows that in the central region, the probability of response increases linearly with increase in horizontal extent up to a saturation point. Furthermore, the dependency of the optomotor response on the angular extent of the stimulus is modulated by contrast. We discuss the implications of our results for different modes of stimulus presentation and for models of the underlying mechanisms of motion detection in the mantis.

Artificial selection for food colour preferences.

Colour is an important factor in food detection and acquisition by animals using visually based foraging. Colour can be used to identify the suitability of a food source or improve the efficiency of food detection, and can even be linked to mate choice. Food colour preferences are known to exist, but whether these preferences are heritable and how these preferences evolve is unknown. Using the freshwater fish Poecilia reticulata, we artificially selected for chase behaviour towards two different-coloured moving stimuli: red and blue spots. A response to selection was only seen for chase behaviours towards the red, with realized heritabilities ranging from 0.25 to 0.30. Despite intense selection, no significant chase response was recorded for the blue-selected lines. This lack of response may be due to the motion-detection mechanism in the guppy visual system and may have novel implications for the evolvability of responses to colour-related signals. The behavioural response to several colours after five generations of selection suggests that the colour opponency system of the fish may regulate the response to selection.

Chapter 6 - Sound localization

The auditory system derives locations of sound sources from spatial cues provided by the interaction of sound with the head and external ears. Those cues are analyzed in specific brainstem pathways and then integrated as cortical representation of locations. The principal cues for horizontal localization are interaural time differences (ITDs) and interaural differences in sound level (ILDs). Vertical and front/back localization rely on spectral-shape cues derived from direction-dependent filtering properties of the external ears. The likely first sites of analysis of these cues are the medial superior olive (MSO) for ITDs, lateral superior olive (LSO) for ILDs, and dorsal cochlear nucleus (DCN) for spectral-shape cues. Localization in distance is much less accurate than that in horizontal and vertical dimensions, and interpretation of the basic cues is influenced by additional factors, including acoustics of the surroundings and familiarity of source spectra and levels. Listeners are quite sensitive to sound motion, but it remains unclear whether that reflects specific motion detection mechanisms or simply detection of changes in static location. Intact auditory cortex is essential for normal sound localization. Cortical representation of sound locations is highly distributed, with no evidence for point-to-point topography. Spatial representation is strictly contralateral in laboratory animals that have been studied, whereas humans show a prominent right-hemisphere dominance.

Motion as a source of environmental information: a fresh view on biological motion computation by insect brains.

Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around (“optic flow”) to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and—in many behavioral contexts—less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

Spatial vision in insects: How visual information processing is facilitated by an active flight and gaze strategy

Event Abstract Back to Event Spatial vision in insects: How visual information processing is facilitated by an active flight and gaze strategy Martin Egelhaaf1*, Roland Kern1 and Jens P. Lindemann1 1 Bielefeld University, Neurobiology & CITEC, Germany Flying insects, such as blowflies and bees rely on the image flow on their eyes (“optic flow”) solving spatial tasks as diverse as collision avoidance and local navigation, i.e. localizing a previously learnt inconspicuous goal on the basis of landmark cues. In free flight flies and bees exhibit characteristic behavioural actions to shape the dynamics of the optic flow. By employing a saccadic flight and gaze strategy they squeeze rotations into brief and rapid turns leaving most of the flight time for various types of translational prototypical movements. Separation of rotational and translational optic flow components by a behavioural strategy is reasonable , since only the optic flow component induced by translations contains information about the relative distance of environmental structures from the animal. By combined electrophysiological analysis and model simulations we analyzed how during rotational and translational self-motion information about the spatial layout and the textural properties of both experimenter-designed and natural environments are represented at the different processing stages of the visual motion pathway. Only two major conclusions shall be mentioned here: (1) during intersaccadic translational flight, the mechanisms of local motion detection segregate in a computationally cheap way natural sceneries into their depth structure: nearby objects pop out in the activity profile of retinotopic arrays of local motion detectors, whereas more distant structures evoke only negligible responses. (2) Even after spatial pooling of local motion signals by the dendritic trees of the wide-field cells in the lobula complex of flies and bees, these distance dependent response modulations persist. Hence, these neurons, which are traditionally conceived as rotation sensors being involved in mediating compensatory optomotor responses, provide information about the spatial properties of the environment. In conclusion, the neural processing of spatial information in flies and bees is greatly facilitated by their saccadic flight and gaze strategy. This active vision strategy enables the nervous system to solve apparently complex spatial vision tasks in a computationally parsimonious way. Thus, by making use of the closed action–perception loop in a smart way, insects with their tiny brains are capable of performing extraordinarily well even on extremely fast timescales of some ten milliseconds. Acknowledgements The work in our lab is supported by the Deutsche Forschungsgemeinschaft (DFG) Keywords: motion vision, Spatial Vision, Optic Flow, collision avoidance, navigation, fly, Honeybee, Bumblebee, Flight control Conference: International Conference on Invertebrate Vision, Fjälkinge, Sweden, 1 Aug - 8 Aug, 2013. Presentation Type: Oral presentation preferred Topic: Motion vision Citation: Egelhaaf M, Kern R and Lindemann JP (2019). Spatial vision in insects: How visual information processing is facilitated by an active flight and gaze strategy. Front. Physiol. Conference Abstract: International Conference on Invertebrate Vision. doi: 10.3389/conf.fphys.2013.25.00044 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 25 Feb 2013; Published Online: 09 Dec 2019. * Correspondence: Prof. Martin Egelhaaf, Bielefeld University, Neurobiology & CITEC, Bielefeld, D-33501, Germany, martin.egelhaaf@uni-bielefeld.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Martin Egelhaaf Roland Kern Jens P Lindemann Google Martin Egelhaaf Roland Kern Jens P Lindemann Google Scholar Martin Egelhaaf Roland Kern Jens P Lindemann PubMed Martin Egelhaaf Roland Kern Jens P Lindemann Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Effect of image statistics on fixational eye movements

Under natural viewing conditions, small movements of the eyes prevent the maintenance of a steady direction of gaze. It is unclear how the spatiotemporal content of the fixated scene has an impact on the properties of miniatures, fixational eye movements. We have investigated the characteristics of fixational eye movements recorded while human subjects are instructed to fixate natural statistics random textures (Motion Clouds) in which we manipulated the spatial frequency content. We used long presentations (5 sec) of Motion Clouds stimuli (Schrater et al. 2000) of varying spatial frequency bandwidths (Bsf) around different central spatial frequency (Sf0). We found that central spatial frequency has an effect upon microsaccadic eye movements. In particular, smaller saccadic amplitudes were associated with high spatial frequencies, and larger saccades with low spatial frequencies. Broadening the spatial frequency bandwidth also changed the distribution of microsaccade amplitudes. A lower spatial frequencies, larger Bsf resulted in a large reduction of microsaccades amplitude while fixation behavior for high spatial frequencies texture was not affected. Relationship between microsaccade rate and intersaccadic timing was also dependent upon Bsf. These results suggest that the spatial frequency content of the fixated images have a strong impact upon fixation instability. Paul R. Schrater, David C. Knill and Eero P. Simoncelli (2000) " Mechanisms of visual motion detection" Nature Neuroscience 3, 64 - 68. Meeting abstract presented at VSS 2012