Direction Selectivity Research Articles

A Coil Positioning Method Integrated With an Orthogonal Decoupled Transformer for Inductive Power Transfer Systems

Misalignment between primary and secondary coils in inductive power transfer systems decreases power capacity and efficiency. In this article, a secondary coil positioning method integrated with an orthogonal decoupled transformer is proposed. This nested rectangular and solenoidal structure consists of a pair of double-D coils and a pair of solenoidal coils. The coils are integrated spatially and decoupled magnetically. Based on their directional selectivity characteristics, a coil positioning method is proposed prior to the power path activation. Coordinates can be obtained with polynomial fit calculations. The positioning method is compatible with power transfer and has merits of less auxiliary equipment, higher compatibility, and higher positioning precision considering both horizontal and vertical misalignment cases. The transformer performance is simulated with a three-dimensional finite element modeling tool and verified experimentally on a 3.2-kW prototype. In the preactivation sensing process, points distributed throughout a ±180 mm × 180 mm positioning range were tested. Experimental results show that 92% of tested points are accurate to within 10 mm given a 210 mm vertical distance. When air gap variations are taken into consideration, 90% of tested points are accurate to within 12 mm over the tested range. In the power transfer stage, the maximum full-power dc–dc system efficiency is 94.6%.

A corollary discharge mediates saccade-related inhibition of single units in mnemonic structures of the human brain

Despite the critical link between visual exploration and memory, little is known about how neuronal activity in the human mesial temporal lobe (MTL) is modulated by saccades. Here, we characterize saccade-associated neuronal modulations, unit-by-unit, and contrast them to image onset and to occipital lobe neurons. We reveal evidence for a corollary discharge (CD)-like modulatory signal that accompanies saccades, inhibiting/exciting a unique population of broad-/narrow-spiking units, respectively, before and during saccades and with directional selectivity. These findings comport well with the timing, directional nature, and inhibitory circuit implementation of a CD. Additionally, by linking neuronal activity to event-related potentials (ERPs), which are directionally modulated following saccades, we recontextualize the ERP associated with saccades as a proxy for both the strength of inhibition and saccade direction, providing a mechanistic underpinning for the more commonly recorded saccade-related ERP in the human brain.

Full-field differential interference contrast imaging with radial-shearing Greek-ladder sieves

The traditional differential interference contrast (DIC) technique is an effective method of quantitative phase imaging, but it has the specific property of orientation and direction selectivity, which decreases the contrast of images in some degree. Here an approach of Radial-shearing DIC (RsDIC) is proposed to realize phase imaging of omnidirectional selectivity as well as high sensitivity, in which the key is an amplitude-only ancient Greek-ladder sieve. Two setups are proposed. One contains only one sieve, in which the interference occurs in the overlap region near to the two adjacent image planes. The other contains two confocal sieves, in which the interference occurs in the coincident image plane. The effectiveness of our proposed method is demonstrated by preliminary results obtained from the software GLAD simulation and experiment performed in visible light. RsDIC allows for full-field DIC imaging as well as for DIC scanning transmission x-ray microscopy, which can also provide a nanometer resolution nondestructive imaging tool in x-ray region for ultra-large-scale integrated circuits, living cells, etc.

Spike‐Based Spatiotemporal Processing Enabled by Oscillation Neuron for Energy‐Efficient Artificial Sensory Systems

Developing an energy‐efficient artificial sensory system is of great significance for neuroprosthesis, neurorobotics, and intelligent human–machine interfaces. Inspired by the biological perception, achieving this goal through spatiotemporal processing is viable. But some challenges, such as continuous signal coding resulting in high‐energy consumption, are yet to be solved, hindering the realization of human perception emulation. Herein, a perceptual simulation enabled by spike‐based spatiotemporal processing is demonstrated, which is analogous to the biological behavior, through an NbOx‐based oscillation neuron. The time difference between distinct inputs has a notable impact on the output spiking activity of oscillation neuron. On the basis of these features, the temporal‐related perceptions, for example, direction selectivity and sound localization are closely imitated. Unambiguous differentiation of direction or azimuth is enabled according to the output spiking numbers of oscillation neuron. Furthermore, by combining the oscillation neuron with a spiking neural network, azimuth recognition is conceptually established to mimic the human's response to auditory stimuli. Herein, the feasibility of employing spike‐based spatiotemporal processing of oscillation neurons to emulate sensory functionality, paving a highly potential way for realizing energy‐efficient artificial sensory systems, is proved.

Complex Wavelets and SPIHTL for Edge Feature Enhancement and Optimum Feature Selection with Deep Learning Algorithm for Video Salient Object Detection

Cognitive property of the human visual system to detect salient objects in image and video sequences to correlate with neighbouring objects for information retrieval and understanding is developed for computer vision application. Detecting salient objects with accurate boundaries and features is addressed in this work by using the directional selectivity property of complex wavelets. Computation complexity of processing complex wavelet sub band is addressed by companding the features into eight sub bands and optimum number of features are selected using SPIHTL (Set Partition In Hierarchical Trees List) algorithm. Five layered deep learning algorithm is designed with 2D FFNN ( Feed Forward Neural Network) structure and reordering units to detect salient object features. The 3D DTCWT (Dual Tree Complex Wavelet Transform) model combined with 2D SPIHTL encoder and deep learning algorithm is modelled in MATLAB and is trained to identify 120 objects with PSNR (Peak Signal To Noise Ration) of 40dB. The designed model is demonstrated to detect generic objects. Keywords: Video saliency, DTCWT, Directional Features, SPIHTL, Deep Learning, 2D Neural Network

Origins of direction selectivity in the primate retina

From mouse to primate, there is a striking discontinuity in our current understanding of the neural coding of motion direction. In non-primate mammals, directionally selective cell types and circuits are a signature feature of the retina, situated at the earliest stage of the visual process. In primates, by contrast, direction selectivity is a hallmark of motion processing areas in visual cortex, but has not been found in the retina, despite significant effort. Here we combined functional recordings of light-evoked responses and connectomic reconstruction to identify diverse direction-selective cell types in the macaque monkey retina with distinctive physiological properties and synaptic motifs. This circuitry includes an ON-OFF ganglion cell type, a spiking, ON-OFF polyaxonal amacrine cell and the starburst amacrine cell, all of which show direction selectivity. Moreover, we discovered that macaque starburst cells possess a strong, non-GABAergic, antagonistic surround mediated by input from excitatory bipolar cells that is critical for the generation of radial motion sensitivity in these cells. Our findings open a door to investigation of a precortical circuitry that computes motion direction in the primate visual system.

Specializations in optic flow encoding in the pretectum of hummingbirds and zebra finches

All visual animals experience optic flow-global visual motion across the retina, which is used to control posture and movement.1 The midbrain circuitry for optic flow is highly conserved in vertebrates,2-6 and these neurons show similar response properties across tetrapods.4,7-16 These neurons have large receptive fields and exhibit both direction and velocity selectivity in response to large moving stimuli. Hummingbirds deviate from the typical vertebrate pattern in several respects.17,18 Their lentiformis mesencephali (LM) lacks the directional bias seen in other tetrapods and has an overall bias for faster velocities. This led Ibbotson19 to suggest that the hummingbird LM may be specialized for hovering close to visual structures, such as plants. In such an environment, even slight body motions will translate into high-velocity optic flow. A prediction from this hypothesis is that hummingbird LM neurons should be more responsive to large visual features. We tested this hypothesis by measuring neural responses of hummingbirds and zebra finches to sine wave gratings of varying spatial and temporal frequencies. As predicted, the hummingbird LM displayed an overall preference for fast optic flow because neurons were biased to lower spatial frequencies. These neurons were also tightly tuned in the spatiotemporal domain. We found that the zebra finch LM specializes along another domain: many neurons were initially tuned to high temporal frequencies followed by a shift in location and orientation to slower velocity tuning. Collectively, these results demonstrate that the LM has distinct and specialized tuning properties in at least two bird species.

Conserved circuits for direction selectivity in the primate retina

The detection of motion direction is a fundamental visual function and a classic model for neural computation. In the non-primate retina, direction selectivity arises in starburst amacrine cell (SAC) dendrites, which provide selective inhibition to direction-selective retinal ganglion cells (dsRGCs). Although SACs are present in primates, their connectivity and the existence of dsRGCs remain open questions. Here, we present a connectomic reconstruction of the primate ON SAC circuit from a serial electron microscopy volume of the macaque central retina. We show that the structural basis for the SACs' ability to confer directional selectivity on postsynaptic neurons is conserved. SACs selectively target a candidate homolog to the mammalian ON-sustained dsRGCs that project to the accessory optic system (AOS) and contribute to gaze-stabilizing reflexes. These results indicate that the capacity to compute motion direction is present in the retina, which is earlier in the primate visual system than classically thought.

Estimating How Sounds Modulate Orientation Representation in the Primary Visual Cortex Using Shallow Neural Networks.

Audiovisual perception results from the interaction between visual and auditory processing. Hence, presenting auditory and visual inputs simultaneously usually improves the accuracy of the unimodal percepts, but can also lead to audiovisual illusions. Cross-talks between visual and auditory inputs during sensory processing were recently shown to occur as early as in the primary visual cortex (V1). In a previous study, we demonstrated that sounds improve the representation of the orientation of visual stimuli in the naïve mouse V1 by promoting the recruitment of neurons better tuned to the orientation and direction of the visual stimulus. However, we did not test if this type of modulation was still present when the auditory and visual stimuli were both behaviorally relevant. To determine the effect of sounds on active visual processing, we performed calcium imaging in V1 while mice were performing an audiovisual task. We then compared the representations of the task stimuli orientations in the unimodal visual and audiovisual context using shallow neural networks (SNNs). SNNs were chosen because of the biological plausibility of their computational structure and the possibility of identifying post hoc the biological neurons having the strongest influence on the classification decision. We first showed that SNNs can categorize the activity of V1 neurons evoked by drifting gratings of 12 different orientations. Then, we demonstrated using the connection weight approach that SNN training assigns the largest computational weight to the V1 neurons having the best orientation and direction selectivity. Finally, we showed that it is possible to use SNNs to determine how V1 neurons represent the orientations of stimuli that do not belong to the set of orientations used for SNN training. Once the SNN approach was established, we replicated the previous finding that sounds improve orientation representation in the V1 of naïve mice. Then, we showed that, in mice performing an audiovisual detection task, task tones improve the representation of the visual cues associated with the reward while deteriorating the representation of non-rewarded cues. Altogether, our results suggest that the direction of sound modulation in V1 depends on the behavioral relevance of the visual cue.

Visual System Hyperexcitability and Compromised V1 Receptive Field Properties in Early-Stage Retinitis Pigmentosa in Mice.

Inherited retinal degenerative diseases are a prominent cause of blindness. Although mutations causing death of photoreceptors are mostly known, the pathophysiology downstream in the inner retina and along the visual pathway is incompletely characterized in the earliest disease stages. Here, we investigated retinal, midbrain and cortical visual function using electroretinography (ERG), the optomotor response (OMR), visual evoked potentials (VEPs), respectively, and single unit electrophysiology at the primary visual cortex (V1) in light-adapted juvenile (approximately one-month-old) and young adult (three-month-old) RhoP23H/WT mice, representative of early-stage retinitis pigmentosa (RP). Photopic ERG revealed up to ∼30% hypersensitivity to light in RhoP23H/WT mice, as measured by the light intensity required to generate half-maximal b-wave (I50 parameter). RhoP23H/WT mice also showed increased OMRs toward low spatial frequency (SF) drifting gratings, indicative of visual overexcitation at the midbrain level. At the V1 level, VEPs and single-cell recordings revealed prominent hyperexcitability in the juvenile RhoP23H/WT mice. Mean VEP amplitudes for light ON stimuli were nearly doubled in one-month-old RhoP23H/WT mice compared with controls, and more than doubled for light OFF. Single-cell recordings showed a significantly increased spontaneous V1 neuron firing in the RhoP23H/WT mice, and persistent contrast and temporal sensitivities. In contrast, direction selectivity was severely compromised. Our data suggest that during early RP, the visual pathway becomes hyperexcited. This could have both compensatory and deleterious consequences for visual behavior. Further studies on the mechanisms of hyperexcitability are warranted as this could lead to therapeutic interventions for RP.

An Artificial Visual System for Motion Direction Detection Based on the Hassenstein–Reichardt Correlator Model

The perception of motion direction is essential for the survival of visual animals. Despite various theoretical and biophysical investigations that have been conducted to elucidate directional selectivity at the neural level, the systemic mechanism of motion direction detection remains elusive. Here, we develop an artificial visual system (AVS) based on the core computation of the Hassenstein–Reichardt correlator (HRC) model for global motion direction detection. With reference to the biological investigations of Drosophila, we first describe a local motion-sensitive, directionally detective neuron that only responds to ON motion signals with high pattern contrast in a particular direction. Then, we use the full-neurons scheme motion direction detection mechanism to detect the global motion direction based on our previous research. The mechanism enables our AVS to detect multiple directions in a two-dimensional view, and the global motion direction is inferred from the outputs of all local motion-sensitive directionally detective neurons. To verify the reliability of our AVS, we conduct a series of experiments and compare its performance with the time-considered convolution neural network (CNN) and the EfficientNetB0 under the same conditions. The experimental results demonstrated that our system is reliable in detecting the direction of motion, and among the three models, our AVS has better motion direction detection capabilities.

Visual Stimulation Induces Distinct Forms of Sensitization of On-Off Direction-Selective Ganglion Cell Responses in the Dorsal and Ventral Retina.

Experience-dependent modulation of neuronal responses is a key attribute in sensory processing. In the mammalian retina, the On-Off direction-selective ganglion cell (DSGC) is well known for its robust direction selectivity. However, how the On-Off DSGC light responsiveness dynamically adjusts to the changing visual environment is underexplored. Here, we report that On-Off DSGCs tuned to posterior motion direction [i.e. posterior DSGCs (pDSGCs)] in mice of both sexes can be transiently sensitized by prior stimuli. Notably, distinct sensitization patterns are found in dorsal and ventral pDSGCs. Although responses of both dorsal and ventral pDSGCs to dark stimuli (Off responses) are sensitized, only dorsal cells show the sensitization of responses to bright stimuli (On responses). Visual stimulation to the dorsal retina potentiates a sustained excitatory input from Off bipolar cells, leading to tonic depolarization of pDSGCs. Such tonic depolarization propagates from the Off to the On dendritic arbor of the pDSGC to sensitize its On response. We also identified a previously overlooked feature of DSGC dendritic architecture that can support dendritic integration between On and Off dendritic layers bypassing the soma. By contrast, ventral pDSGCs lack a sensitized tonic depolarization and thus do not exhibit sensitization of their On responses. Our results highlight a topographic difference in Off bipolar cell inputs underlying divergent sensitization patterns of dorsal and ventral pDSGCs. Moreover, substantial crossovers between dendritic layers of On-Off DSGCs suggest an interactive dendritic algorithm for processing On and Off signals before they reach the soma.SIGNIFICANCE STATEMENT Visual neuronal responses are dynamically influenced by the prior visual experience. This form of plasticity reflects the efficient coding of the naturalistic environment by the visual system. We found that a class of retinal output neurons, On-Off direction-selective ganglion cells, transiently increase their responsiveness after visual stimulation. Cells located in dorsal and ventral retinas exhibit distinct sensitization patterns because of different adaptive properties of Off bipolar cell signaling. A previously overlooked dendritic morphologic feature of the On-Off direction-selective ganglion cell is implicated in the cross talk between On and Off pathways during sensitization. Together, these findings uncover a topographic difference in the adaptive encoding of upper and lower visual fields and the underlying neural mechanism in the dorsal and ventral retinas.

Use of Genetic Algorithms for Design an FPGA-Integrated Acoustic Camera.

The goal of this paper is to design a broadband acoustic camera using micro-electromechanical system (MEMS) microphones. The paper describes how an optimization of the microphone array has been carried out. Furthermore, the final goal of the described optimization is that the gain in the desired direction and the attenuation of side lobes is maximized at a frequency up to 4 kHz. Throughout the research, various shapes of microphone arrays and their directivity patterns have been considered and analyzed using newly developed algorithms implemented in Matlab. A hemisphere algorithm, genetic algorithm, and genetic square algorithm were used to find the optimal position and number of microphones placed on an acoustic camera. The proposed acoustic camera design uses a large number of microphones for high directional selectivity, while a field programmable gate array system on a chip (FPGA SoC) is selected as the processing element of the system. According to the obtained results, three different acoustic camera prototypes were developed. This paper presents simulations of their characteristics, compares the obtained measurements, and discusses the positive and negative sides of each acoustic camera prototype.

Distinct inhibitory pathways control velocity and directional tuning in the mouse retina

The sensory periphery is responsible for detecting ethologically relevant features of the external world, using compact, predominantly feedforward circuits. Visual motion is a particularly prevalent sensory feature, the presence of which can be a signal to enact diverse behaviors ranging from gaze stabilization reflexes to predator avoidance or prey capture. To understand how the retina constructs the distinct neural representations required for these behaviors, we investigated two circuits responsible for encoding different aspects of image motion: ON and ON-OFF direction-selective ganglion cells (DSGCs). Using a combination of two-photon targeted whole-cell electrophysiology, pharmacology, and conditional knockout mice, we show that distinct inhibitory pathways independently control tuning for motion velocity and motion direction in these two cell types. We further employ dynamic clamp and numerical modeling techniques to show that asymmetric inhibition provides a velocity-invariant mechanism of directional tuning, despite the strong velocity dependence of classical models of direction selectivity. We therefore demonstrate that invariant representations of motion features by inhibitory interneurons act as computational building blocks to construct distinct, behaviorally relevant signals at the earliest stages of the visual system.

Anatomical distribution and functional roles of electrical synapses in Drosophila

Electrical synapses are present in almost all organisms that have a nervous system. However, their brain-wide expression patterns and the full range of contributions to neural function are unknown in most species. Here, we first provide a light-microscopic, immunohistochemistry-based anatomical map of all innexin gap junction proteins-the building blocks of electrical synapses-in the central nervous system of Drosophila melanogaster. Of those innexin types that are expressed in the nervous system, some localize to glial cells, whereas others are predominantly expressed in neurons, with shakB being the most widely expressed neuronal innexin. We then focus on the function of shakB in VS/HS cells-a class of visual projection neurons-thereby uncovering an unexpected role for electrical synapses. Removing shakB from these neurons leads to spontaneous, cell-autonomous voltage and calcium oscillations, demonstrating that electrical synapses are required for these cells' intrinsic stability. Furthermore, we investigate the role of shakB-type electrical synapses in early visual processing. We find that the loss of shakB from the visual circuits upstream of VS/HS cells differentially impairs ON and OFF visual motion processing pathways but is not required for the computation of direction selectivity per se. Taken together, our study demonstrates that electrical synapses are widespread across the Drosophila nervous system and that they play essential roles in neuronal function and visual information processing.

Directional Stockwell transform in L 2(ℝ n )

In the present article, we propose a directionally tuned variant of the continuous Stockwell transform in the context of multi-dimensional signal analysis. Owing to the directional selectivity coupled with a frequency adaptable window, the proposed transform serves as a bridge between the directional short-time Fourier and wavelet transforms. Besides the formulation of all the fundamental results, including the orthogonality relation and reconstruction formula, we also obtain several uncertainty inequalities associated with the directional Stockwell transform.

A Class of Directional Zero-Phase 2D Filters Designed Using Analytical Approach

This paper proposes an analytical design procedure for a class of 2D filters with a directional characteristic in the frequency plane. The method starts from two types of low-pass prototypes, namely a Gaussian filter and a wide-band filter. The two prototypes and the resulted 2D filters are zero-phase, a very useful property in image processing tasks. The prototypes are parametric and can be scaled along the frequency axis, thus resulting narrower or wider. A 1D to 2D frequency mapping, based on accurate approximations, is derived and applied to each prototype, obtaining the desired directional 2D frequency response with specified selectivity and orientation. The designed filters are adjustable, with a frequency response in factored matrix form depending on specifications. The Gaussian prototype yields very selective directional filters, used in detecting oriented straight lines in images, as show simulation results on several test images. Using oriented wide-band filters, other useful 2D filters result, namely square and parallelogram filters. The designed filters have accurate frequency responses, good directional selectivity and high linearity at relatively low order. An advantage of this analytical approach is that the filter transfer function results in parametric form and allows for easy tunability.

Orientation and direction tuning align with dendritic morphology and spatial connectivity in mouse visual cortex

The functional properties of neocortical pyramidal cells (PCs), such as direction and orientation selectivity in visual cortex, predominantly derive from their excitatory and inhibitory inputs. For layer 2/3 (L2/3) PCs, the detailed relationship between their functional properties and how they sample and integrate information across cortical space is not fully understood. Here, we study this relationship by combining functional invivotwo-photon calcium imaging, invitro functional circuit mapping, and dendritic reconstruction of the same L2/3 PCs in mouse visual cortex. Our work reveals direct correlations between dendritic morphology and functional input connectivity and the orientation as well as direction tuning of L2/3 PCs. First, the apical dendritic tree is elongated along the postsynaptic preferred orientation, considering the representation of visual space in the cortex as determined by its retinotopic organization. Additionally, sharply orientation-tuned cells show a less complex apical tree compared with broadly tuned cells. Second, in direction-selective L2/3 PCs, the spatial distribution of presynaptic partners is offset from the soma opposite to the preferred direction. Importantly, although the presynaptic excitatory and inhibitory input distributions spatially overlap on average, the excitatory input distribution is spatially skewed along the preferred direction, in contrast to the inhibitory distribution. Finally, the degree of asymmetry is positively correlated with the direction selectivity of the postsynaptic L2/3 PC. These results show that the dendritic architecture and the spatial arrangement of excitatory and inhibitory presynaptic cells of L2/3 PCs play important roles in shaping their orientation and direction tuning.

Dual-angle rotation two-dimensional wavelet transform profilometry.

The two-dimensional continuous wavelet transform (2D CWT) has been widely used in single-shot fringe projection profilometry (FPP) because of its multi-resolution characteristics and anti-noise ability. This Letter aims to develop a novel 2D wavelet transform model in FPP. Dual-angle rotation operation on a 2D wavelet is performed to improve the directional selectivity and frequency localization of the wavelet. The proposed method improves the accuracy of the phase calculation of wavelet transform profilometry (WTP) for higher accuracy reconstruction from the single-shot fringe. We present mathematical expressions, theoretical analysis, and the comparison to traditional 2D WTP. The experiments demonstrate the effectiveness of the proposed method.

A Computational Model of Direction Selectivity in Macaque V1 Cortex Based on Dynamic Differences between On and Off Pathways.

This paper is about neural mechanisms of direction selectivity (DS) in macaque primary visual cortex, V1. We present data (on male macaque) showing strong DS in a majority of simple cells in V1 layer 4Cα, the cortical layer that receives direct afferent input from the magnocellular division of the lateral geniculate nucleus (LGN). Magnocellular LGN cells are not direction-selective. To understand the mechanisms of DS, we built a large-scale, recurrent model of spiking neurons called DSV1. Like its predecessors, DSV1 reproduces many visual response properties of V1 cells including orientation selectivity. Two important new features of DSV1 are (1) DS is initiated by small, consistent dynamic differences in the visual responses of OFF and ON Magnocellular LGN cells, and (2) DS in the responses of most model simple cells is increased over those of their feedforward inputs; this increase is achieved through dynamic interaction of feedforward and intracortical synaptic currents without the use of intracortical direction-specific connections. The DSV1 model emulates experimental data in the following ways: (1) most 4Cα Simple cells were highly direction-selective but 4Cα Complex cells were not; (2) the preferred directions of the model's direction-selective Simple cells were invariant with spatial and temporal frequency (TF); (3) the distribution of the preferred/opposite ratio across the model's population of cells was very close to that found in experiments. The strong quantitative agreement between DS in data and in model simulations suggests that the neural mechanisms of DS in DSV1 may be similar to those in the real visual cortex.SIGNIFICANCE STATEMENT Motion perception is a vital part of our visual experience of the world. In monkeys, whose vision resembles that of humans, the neural computation of the direction of a moving target starts in the primary visual cortex, V1, in layer 4Cα that receives input from the eye through the lateral geniculate nucleus (LGN). How direction selectivity (DS) is generated in layer 4Cα is an outstanding unsolved problem in theoretical neuroscience. In this paper, we offer a solution based on plausible biological mechanisms. We present a new large-scale circuit model in which DS originates from slightly different LGN ON/OFF response time-courses and is enhanced in cortex without the need for direction-specific intracortical connections. The model's DS is in quantitative agreement with experiments.