Visual Motion Detection Research Articles

Asynchronous Event-based Cooperative Stereo Matching Using Neuromorphic Silicon Retinas

Biologically-inspired event-driven silicon retinas, so called dynamic vision sensors (DVS), allow efficient solutions for various visual perception tasks, e.g. surveillance, tracking, or motion detection. Similar to retinal photoreceptors, any perceived light intensity change in the DVS generates an event at the corresponding pixel. The DVS thereby emits a stream of spatiotemporal events to encode visually perceived objects that in contrast to conventional frame-based cameras, is largely free of redundant background information. The DVS offers multiple additional advantages, but requires the development of radically new asynchronous, event-based information processing algorithms. In this paper we present a fully event-based disparity matching algorithm for reliable 3D depth perception using a dynamic cooperative neural network. The interaction between cooperative cells applies cross-disparity uniqueness-constraints and within-disparity continuity-constraints, to asynchronously extract disparity for each new event, without any need of buffering individual events. We have investigated the algorithm's performance in several experiments; our results demonstrate smooth disparity maps computed in a purely event-based manner, even in the scenes with temporally-overlapping stimuli.

The contrast sensitivity function of the praying mantis Sphodromantis lineola

The detection of visual motion and its direction is a fundamental task faced by several visual systems. The motion detection system of insects has been widely studied with the majority of studies focussing on flies and bees. Here we characterize the contrast sensitivity of motion detection in the praying mantis Sphodromantis lineola, an ambush predator that stays stationary for long periods of time while preying on fast-moving prey. In this, its visual behaviour differs from previously studied insects and we might therefore expect its motion detection system to differ from theirs. To investigate the sensitivity of the mantis we analyzed its optomotor response in response to drifting gratings with different contrasts and spatio-temporal frequencies. We find that the contrast sensitivity of the mantis depends on the spatial and temporal frequencies present in the stimulus and is separably tuned to spatial and temporal frequency rather than specifically to object velocity. Our results also suggest that mantises are sensitive to a broad range of velocities, in which they differ from bees and are more similar to hoverflies. We discuss our results in relation to the contrast sensitivities of other insects and the visual ecology of the mantis.Electronic supplementary materialThe online version of this article (doi:10.1007/s00359-015-1008-5) contains supplementary material, which is available to authorized users.

Unconscious reward facilitates motion perceptual learning

Reward signal plays an important role in guiding human learning behaviour. Recent studies have provided evidence that reward signal modulates perceptual learning of basic visual features. Typically, the reward effects on perceptual learning were accompanied with consciously presented reward during the learning process. However, whether an unconsciously presented reward signal that minimizes the contribution of attentional and motivational factors can facilitate perceptual learning remains less well understood. We trained human subjects on a visual motion detection task and subliminally delivered a monetary reward for correct response during the training. The results showed significantly larger learning effect for high reward-associated motion direction than low reward-associated motion direction. Importantly, subjects could neither discriminate the relative values of the subliminal monetary reward nor correctly report the reward-direction contingencies. Our findings suggest that reward signal plays an important modulatory role in perceptual learning even if the magnitude of the reward was not consciously perceived.

The behavioral and neural effects of language on motion perception.

Perception does not function as an isolated module but is tightly linked with other cognitive functions. Several studies have demonstrated an influence of language on motion perception, but it remains debated at which level of processing this modulation takes place. Some studies argue for an interaction in perceptual areas, but it is also possible that the interaction is mediated by "language areas" that integrate linguistic and visual information. Here, we investigated whether language-perception interactions were specific to the language-dominant left hemisphere by comparing the effects of language on visual material presented in the right (RVF) and left visual fields (LVF). Furthermore, we determined the neural locus of the interaction using fMRI. Participants performed a visual motion detection task. On each trial, the visual motion stimulus was presented in either the LVF or in the RVF, preceded by a centrally presented word (e.g., "rise"). The word could be congruent, incongruent, or neutral with regard to the direction of the visual motion stimulus that was presented subsequently. Participants were faster and more accurate when the direction implied by the motion word was congruent with the direction of the visual motion stimulus. Interestingly, the speed benefit was present only for motion stimuli that were presented in the RVF. We observed a neural counterpart of the behavioral facilitation effects in the left middle temporal gyrus, an area involved in semantic processing of verbal material. Together, our results suggest that semantic information about motion retrieved in language regions may automatically modulate perceptual decisions about motion.

Motion detection based on recurrent network dynamics.

The detection of visual motion requires temporal delays to compare current with earlier visual input. Models of motion detection assume that these delays reside in separate classes of slow and fast thalamic cells, or slow and fast synaptic transmission. We used a data-driven modeling approach to generate a model that instead uses recurrent network dynamics with a single, fixed temporal integration window to implement the velocity computation. This model successfully reproduced the temporal response dynamics of a population of motion sensitive neurons in macaque middle temporal area (MT) and its constituent parts matched many of the properties found in the motion processing pathway (e.g., Gabor-like receptive fields (RFs), simple and complex cells, spatially asymmetric excitation and inhibition). Reverse correlation analysis revealed that a simplified network based on first and second order space-time correlations of the recurrent model behaved much like a feedforward motion energy (ME) model. The feedforward model, however, failed to capture the full speed tuning and direction selectivity properties based on higher than second order space-time correlations typically found in MT. These findings support the idea that recurrent network connectivity can create temporal delays to compute velocity. Moreover, the model explains why the motion detection system often behaves like a feedforward ME network, even though the anatomical evidence strongly suggests that this network should be dominated by recurrent feedback.

Connectome of the fly visual circuitry.

Recent powerful tools for reconstructing connectomes using electron microscopy (EM) have made outstanding contributions to the field of neuroscience. As a prime example, the detection of visual motion is a classic problem of neural computation, yet our understanding of the exact mechanism has been frustrated by our incomplete knowledge of the relevant neurons and synapses. Recent connectomic studies have successfully identified the concrete neuronal circuit in the fly's visual system that computes the motion signals. This identification was greatly aided by the comprehensiveness of the EM reconstruction. Compared with light microscopy, which gives estimated connections from arbor overlap, EM gives unequivocal connections with precise synaptic counts. This paper reviews the recent study of connectomics in a brain of the fruit fly Drosophila and highlights how connectomes can provide a foundation for understanding the mechanism of neuronal functions by identifying the underlying neural circuits.

Implementation of Visual Motion Detection in Analog “Neuromorphic” Circuitry—A Case Study of the Issue of Circuit Precision

Many animals rely on visual motion to infer their relation to the surrounding environment while moving around in it. Motion processing in biological nervous systems, particularly in the insects, has been a subject of active research for over 50 years. With the advent of interest in “neuromorphic” integrated circuits in the late 1980s, this mode of sensory processing has also been the subject of various analog silicon modeling efforts. The author discusses the background of certain models for motion detection in insects, and then the implementation of a particular model in analog integrated circuitry. The paper does not focus on such circuits themselves, however, but on the issue of computational precision in the analog domain: it is argued that insufficient attention to this issue has been an impediment to the development of neuromorphic circuits that are practically useful in engineering applications. A statistical approach is described for assessing one of the designs discussed herein, and the degradation of its performance due to variations in the electrical properties of its constituent devices, with an eye toward suitability for application in autonomous robotics. This approach relies on tools and models routinely used in conventional analog/mixed signal design. The author argues that adoption of such techniques, along with a deeper consideration of computational precision, i.e., a shift in the neuromorphic design philosophy, would be an important step in moving the field forward.

Direct Observation of ON and OFF Pathways in the Drosophila Visual System

Visual motion perception is critical to many animal behaviors, and flies have emerged as a powerful model system for exploring this fundamental neural computation. Although numerous studies have suggested that fly motion vision is governed by a simple neural circuit [1-3], the implementation of this circuit has remained mysterious for decades. Connectomics and neurogenetics have produced a surge in recent progress, and several studies have shown selectivity for light increments (ON) or decrements (OFF) in key elements associated with this circuit [4-7]. However, related studies have reached disparate conclusions about where this selectivity emerges and whether it plays a major role in motion vision [8-13]. To address these questions, we examined activity in the neuropil thought to be responsible for visual motion detection, the medulla, of Drosophila melanogaster in response to a range of visual stimuli using two-photon calcium imaging. We confirmed that the input neurons of the medulla, the LMCs, are not responsible for light-on and light-off selectivity. We then examined the pan-neural response of medulla neurons and found prominent selectivity for light-on and light-off in layers of the medulla associated with two anatomically derived pathways (L1/L2 associated) [14, 15]. We next examined the activity of prominent interneurons within each pathway (Mi1 and Tm1) and found that these neurons have corresponding selectivity for light-on or light-off. These results provide direct evidence that motion is computed in parallel light-on and light-off pathways, demonstrate that this selectivity emerges in neurons immediately downstream of the LMCs, and specify where crucial elements of motion computation occur.

Enhancement of visual motion detection thresholds in early deaf people.

In deaf people, the auditory cortex can reorganize to support visual motion processing. Although this cross-modal reorganization has long been thought to subserve enhanced visual abilities, previous research has been unsuccessful at identifying behavioural enhancements specific to motion processing. Recently, research with congenitally deaf cats has uncovered an enhancement for visual motion detection. Our goal was to test for a similar difference between deaf and hearing people. We tested 16 early and profoundly deaf participants and 20 hearing controls. Participants completed a visual motion detection task, in which they were asked to determine which of two sinusoidal gratings was moving. The speed of the moving grating varied according to an adaptive staircase procedure, allowing us to determine the lowest speed necessary for participants to detect motion. Consistent with previous research in deaf cats, the deaf group had lower motion detection thresholds than the hearing. This finding supports the proposal that cross-modal reorganization after sensory deprivation will occur for supramodal sensory features and preserve the output functions.

Structured Connectivity in Cerebellar Inhibitory Networks

SummaryDefining the rules governing synaptic connectivity is key to formulating theories of neural circuit function. Interneurons can be connected by both electrical and chemical synapses, but the organization and interaction of these two complementary microcircuits is unknown. By recording from multiple molecular layer interneurons in the cerebellar cortex, we reveal specific, nonrandom connectivity patterns in both GABAergic chemical and electrical interneuron networks. Both networks contain clustered motifs and show specific overlap between them. Chemical connections exhibit a preference for transitive patterns, such as feedforward triplet motifs. This structured connectivity is supported by a characteristic spatial organization: transitivity of chemical connectivity is directed vertically in the sagittal plane, and electrical synapses appear strictly confined to the sagittal plane. The specific, highly structured connectivity rules suggest that these motifs are essential for the function of the cerebellar network.

2A1-X09 昆虫の視覚情報に基づく回避対象選抜モデルを用いた移動ロボットの衝突回避性能の評価(バイオロボティクス)

2A1-X09 昆虫の視覚情報に基づく回避対象選抜モデルを用いた移動ロボットの衝突回避性能の評価(バイオロボティクス)

Cross‐modal reorganization of cortical afferents to dorsal auditory cortex following early‐ and late‐onset deafness

Cat auditory cortex is known to undergo cross-modal reorganization following deafness, such that behavioral advantages in visual motion detection are abolished when a specific region of deaf auditory cortex, the dorsal zone (DZ), is deactivated. The purpose of the present investigation was to examine the connectional adaptations that might subserve this plasticity. We deposited biotinylated dextran amine (BDA; 3,000 MW), a retrograde tracer, unilaterally into the posterior portion of the suprasylvian fringe, corresponding to area DZ of hearing, early-deafened (onset <1 month), and late-deafened (onset >3 months) cats to reveal cortical afferent projections. Overall, the pattern of cortical projections to DZ was similar in both hearing and deafened animals. However, there was a progressive increase in projection strength among hearing and late- and early-deafened cats from an extrastriate visual cortical region known to be involved in the processing of visual motion, the posterolateral lateral suprasylvian area (PLLS). Additionally, although no such change was documented for the posteromedial lateral suprasylvian area (PMLS), labeled neurons were present within a subregion of PMLS devoted to foveal vision in both late- and early-deafened animals but not in hearing controls. PMLS is also an extrastriate visual motion processing area and is widely considered to be the homolog of primate middle temporal area. No changes in auditory cortical connectivity were observed among groups. These observations suggest that amplified cortical projections from extrastriate visual areas involved in visual motion processing to DZ may contribute to the cross-modal reorganization that functionally manifests as superior visual motion detection ability in the deaf animal.

A visual motion detection circuit suggested by Drosophila connectomics.

SummaryAnimal behavior arises from computations in neuronal circuits, but our understanding of these computations has been frustrated by the lack of detailed synaptic connection maps, or connectomes. For example, despite intensive investigations over half a century, the neuronal implementation of local motion detection in the insect visual system remains elusive. Here, we developed a semi-automated pipeline using electron microscopy to reconstruct a connectome, containing 379 neurons and 8,637 chemical synaptic contacts, within the Drosophila optic medulla. By matching reconstructed neurons to examples from light microscopy, we assigned neurons to cell types and assembled a connectome of the medulla's repeating module. Within this module, we identified cell types constituting a motion detection circuit and showed that the connections onto individual motion-sensitive neurons in this circuit were consistent with their direction selectivity. Our results identify cellular targets for future functional investigations, and demonstrate that connectomes can provide key insights into neuronal computations.

Accurate maps of visual circuitry

Such is the brain's complexity that even small neural circuits contain hundreds of neurons making thousands of connections. Connectivity and optical analyses provide close-up views of two such circuits. See Articles p.168 , p.175 & Letter p.212 Three papers in this issue of Nature use the retina as a model for mapping neuronal circuits from the level of individual synaptic contacts to the long-range scale of dendritic interactions. Helmstaedter et al. used electron microscopy to map a mammalian retinal circuit of close to a thousand neurons. The work reveals a new type of retinal bipolar neuron and suggests functional mechanisms for known visual computations. The other two groups study the detection of visual motion in the Drosophila visual system — a classic neural computation model. Takemura et al. used semi-automated electron microscopy to reconstruct the basic connectome (8,637 chemical synapses among 379 neurons) of Drosophila's optic medulla. Their results reveal a candidate motion detection circuit with a wiring plan consistent with direction selectivity. Maisak et al. used calcium imaging to show that T4 and T5 neurons are divided into specific subpopulations responding to motion in four cardinal directions, and are specific to 'ON' versus 'OFF' edges, respectively.

Motion based prediction and development of response to an "on the way" stimulus

Prior information on regularities of the world is essential for optimal performance of sensory processing. In the particular case of the detection of visual motion, the prior knowledge on the temporal coherency of motion facilitates estimation of predictable trajectories. Based on such prior information, we have proposed a generic bayesian modeling framework to implement anisotropic diffusion of estimated motion information. By applying particle filtering (Sequential Monte Carlo) we were able to study the emergence of a global neural response through a probabilistic pool of local sensory information. To explore if such diffusive mechanisms could explain neurophysiological recordings from the responses of neural populations to a predictable moving stimulus that we have recorded from V1 neurons in macaque monkeys, we simulated such response in the model. Our main experimental protocol consisted of a bar moving to a fixed direction but with different trajectory lengths before reaching the receptive fields of the recorded neurons. Experimental results show that a bar moving towards a long trajectory generates an anticipatory response that build-up gradually with time before the bar actually enters into the receptive field of the cell. In the modeling part we aim to asses the role of prediction in the dynamical development of neural activity at, or before, the arrival of the sensory stimulus. We simulated the response of the model in target receptive fields to a smoothly moving stimulus whose trajectory crosses the receptive field. This was done under various conditions for two classic stimuli: a dot and a slanted bar. We found that, as expected, a smoothly moving stimulus triggers a transient response as it crosses the receptive field and that he peak time of this response matches the arrival of the stimulus to the it’s center. We found that the development of a response to an ‘on the way stimulus’ is enhanced by increasing the reliability of sensory information along the trajectory of motion. Also we observed an advance of the peak time with respect to the degree of predictability of the trajectory. This is in agreement with the neural activity that we have recorded from V1 neurons in response to a smoothly moving slanted bar with different trajectory lengths. This results may be explained with the definition of classical and extra classical receptive fields while former is activated only by having a stimulus inside it and later covers bigger area and collects information from a wider neighborhood [1]. Motion based prediction by highlighting the anisotropic diffusion of estimated motion information can develop another perspective on lateral spread of activity in primary visual cortex and better understanding of modulatory effect of cells on each other.

Visual movement perception in deaf and hearing individuals.

A number of studies have investigated changes in the perception of visual motion as a result of altered sensory experiences. An animal study has shown that auditory-deprived cats exhibit enhanced performance in a visual movement detection task compared to hearing cats (Lomber, Meredith, & Kral, 2010). In humans, the behavioural evidence regarding the perception of motion is less clear. The present study investigated deaf and hearing adult participants using a movement localization task and a direction of motion task employing coherently-moving and static visual dot patterns. Overall, deaf and hearing participants did not differ in their movement localization performance, although within the deaf group, a left visual field advantage was found. When discriminating the direction of motion, however, deaf participants responded faster and tended to be more accurate when detecting small differences in direction compared with the hearing controls. These results conform to the view that visual abilities are enhanced after auditory deprivation and extend previous findings regarding visual motion processing in deaf individuals.

Unattended and attended visual change detection of motion as indexed by event-related potentials and its behavioral correlates

Visual mismatch negativity (vMMN) is a negative-going component amongst cognitive event-related potentials. It reflects an automatic change-detection process that occurs when an infrequent stimulus is presented that is incongruent with the representation of a frequent (standard) event. In our research we use visual motion (more specifically motion direction changes) to study vMMN. Since movement in the visual field is quite irresistible to our brain, the question in hand is, if the detection of motion direction changes is dependent on attention directed to the stimulus. We present a new continuous whole-display stimulus configuration, where the attention capturing primary task of motion onset detection is in the central part of the visual display and visual oddball sequence on the background. The visual oddball paradigm consisted of 85% standard and 15% deviant events, motion direction change being the deviant. We show that even though the unattended visual oddball sequence does not affect the performance in the demanding behavioral primary task, the differences appearing in that sequence are noticed by our brain and reflected in two distinguishable vMMN components in occipital and parietal scalp locations. When attention is directed toward the visual oddball sequence, we only see different processing of standards and deviants in later time-windows and task-related activity in frontal scalp location. Our results are obtained under strict attention manipulation conditions.

Maturation of polarization and luminance contrast sensitivities in cuttlefish (Sepia officinalis)

Polarization sensitivity is a characteristic of the visual system of cephalopods. It has been well documented in adult cuttlefish, which use polarization sensitivity in a large range of tasks such as communication, orientation and predation. Because cuttlefish do not benefit from parental care, their visual system (including the ability to detect motion) must be efficient from hatching to enable them to detect prey or predators. We studied the maturation and functionality of polarization sensitivity in newly hatched cuttlefish. In a first experiment, we examined the response of juvenile cuttlefish from hatching to the age of 1 month towards a moving, vertically oriented grating (contrasting and polarized stripes) using an optomotor response apparatus. Cuttlefish showed differences in maturation of polarization versus luminance contrast motion detection. In a second experiment, we examined the involvement of polarization information in prey preference and detection in cuttlefish of the same age. Cuttlefish preferentially chose not to attack transparent prey whose polarization contrast had been removed with a depolarizing filter. Performances of prey detection based on luminance contrast improved with age. Polarization contrast can help cuttlefish detect transparent prey. Our results suggest that polarization is not a simple modulation of luminance information, but rather that it is processed as a distinct channel of visual information. Both luminance and polarization sensitivity are functional, though not fully matured, in newly hatched cuttlefish and seem to help in prey detection.

Biologically Inspired Feature Detection Using Cascaded Correlations of off and on Channels

Abstract Flying insects are valuable animal models for elucidating computational processes underlying visual motion detection. For example, optical flow analysis by wide-field motion processing neurons in the insect visual system has been investigated from both behavioral and physiological perspectives [1]. This has resulted in useful computational models with diverse applications [2,3]. In addition, some insects must also extract the movement of their prey or conspecifics from their environment. Such insects have the ability to detect and interact with small moving targets, even amidst a swarm of others [4,5]. We use electrophysiological techniques to record from small target motion detector (STMD) neurons in the insect brain that are likely to subserve these behaviors. Inspired by such recordings, we previously proposed an ‘elementary’ small target motion detector (ESTMD) model that accounts for the spatial and temporal tuning of such neurons and even their ability to discriminate targets against cluttered surrounds [6-8]. However, other properties such as direction selectivity [9] and response facilitation for objects moving on extended trajectories [10] are not accounted for by this model. We therefore propose here two model variants that cascade an ESTMD model with a traditional motion detection model algorithm, the Hassenstein Reichardt ‘elementary motion detector’ (EMD) [11]. We show that these elaborations maintain the principal attributes of ESTMDs (i.e. spatiotemporal tuning and background clutter rejection) while also capturing the direction selectivity observed in some STMD neurons. By encapsulating the properties of biological STMD neurons we aim to develop computational models that can simulate the remarkable capabilities of insects in target discrimination and pursuit for applications in robotics and artificial vision systems.

A Biophysical Model for Neural ‘Delay-and-Correlate’

Event Abstract Back to Event A Biophysical Model for Neural ‘Delay-and-Correlate’ Patrick A. Shoemaker1* 1 Tanner Research, Inc., United States The Hassenstein-Reichardt (1956) model for visual motion detection in insects has been influential for decades, but the identities of the neurons associated with its 'delay-and-correlate' operations have remained elusive − and the associated biophysical mechanisms are also unknown. A neural delay could be implemented any number of ways, but a truly conjunctive 'correlator' is more difficult to explain. The simple convergence of two signal pathways onto a single neuron may be necessary but is not sufficient to account for a multiplication-like interaction. Here I present a notional but biophysically-plausible concept for a neural ‘correlator’. In this model, two input channels interact in a target neuron, with the effectiveness of synaptic input from one channel augmented by the action of the second, which increases the incremental membrane resistance of the neuron. In a stage post-synaptic to the target neuron, the excitation that would be induced by the first input alone is nulled out. In the context of this model, I nominate NMDA receptors (NMDARs), which have been found in the insect brain including the optic lobes of Drosophila (Xia et al., 2005; Xia and Chiang, 2009), as a possible component of a neural ‘delay-and-correlate’. Although mechanisms not involving NMDARs may be conceived for both a delay, and a ‘correlate’ operation consistent with the model framework, I show that: 1) NMDAR kinetics are at least roughly consistent with the delay in an insect elementary motion detector; 2) the nonlinear electrical characteristics of NMDAR channels provide an intrinsic, direct means to modulate membrane resistance in the manner required for ‘correlation’. Furthermore, NMDARs are subject to neuromodulation (see, e.g., Yamakura and Shimoji, 1999), providing a mechanism for behaviorally-dependent modulation of motion detection. While these ideas are speculative, they generate hypotheses amenable to testing with current neuropharmacological and genetic techniques. Acknowledgements This work has been supported by US Air Force Office of Scientific Research Grant FA9550-12-1-0034 References Hassenstein, B., and Reichardt, W. (1956) Systemtheoretische analyse der Zeit-, Reihenfolgen-, und Vorseichenauswertung bei der Berwegungsperzeption des Rüsselkäfers Chlorophanus. Zeitschrift für Naturforschung 11b, 513-524. Xia, S., Miyashita, T., Fu, T.-S., Lin, W.-L., Wu, C.L., Pyzocha, L., Lin, I.R., Saitoe, M., Tully, T., and Chiang, A.-S. (2005) NMDA receptors mediate learning and memory in Drosophila. Current Biology 15, 603-615. Xia, S., and Chiang, A.-S. (2009) NMDA receptors in Drosophila. Ch. 10 in Biology of the NMDA Receptor, ed. A.M. van Dongen (Boca Raton, FL: CRC Press). Yamakura, T., and Shimoji, K. (1999) Subunit- and site-specific pharmacology of the NMDA receptor channel. Progress in Neurobiology 59, 279-98. Keywords: insect vision, elementary motion detector, delay and correlate, biophysical models, NMDA receptors, Neuromodulation Conference: International Conference on Invertebrate Vision, Fjälkinge, Sweden, 1 Aug - 8 Aug, 2013. Presentation Type: Poster presentation preferred Topic: Motion vision Citation: Shoemaker PA (2019). A Biophysical Model for Neural ‘Delay-and-Correlate’. Front. Physiol. Conference Abstract: International Conference on Invertebrate Vision. doi: 10.3389/conf.fphys.2013.25.00087 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: 23 Apr 2013; Published Online: 09 Dec 2019. * Correspondence: Dr. Patrick A Shoemaker, Tanner Research, Inc., Monrovia, California, 91016, United States, pshoemaker@sdsu.edu 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 Patrick A Shoemaker Google Patrick A Shoemaker Google Scholar Patrick A Shoemaker PubMed Patrick A Shoemaker 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.