Orientation-selective Mechanisms Research Articles

Orientation selectivity based visual pattern for reduced-reference image quality assessment

Image quality assessment (IQA) is in great demand for high quality image selection in the big data era. The challenge of reduced-reference (RR) IQA is how to use limited data to effectively represent the visual content of an image in the context of IQA. Research on neuroscience indicates that the human visual system (HVS) exhibits obvious orientation selectivity (OS) mechanism for visual content extraction. Inspired by this, an OS based visual pattern (OSVP) is proposed to extract visual content for RR IQA in this paper. The OS arises from the arrangement of the excitatory and inhibitory interactions among connected cortical neurons in a local receptive field. According to the OS mechanism, the similarity of preferred orientations between two nearby pixels is first analyzed. Then, the orientation similarities of pixels in a local neighborhood are arranged, and the OSVP is built for visual information representation. With the help of OSVP, the visual content of an image is extracted and mapped into a histogram. By calculating the changes between the two histograms of reference and distorted images, a quality score is produced. Experimental results on five public databases demonstrate that the proposed RR IQA method has performance consistent with the human perception under a small amount of reference data (only 9 values).

Visual Orientation Selectivity Based Structure Description.

The human visual system is highly adaptive to extract structure information for scene perception, and structure character is widely used in perception-oriented image processing works. However, the existing structure descriptors mainly describe the luminance contrast of a local region, but cannot effectively represent the spatial correlation of structure. In this paper, we introduce a novel structure descriptor according to the orientation selectivity mechanism in the primary visual cortex. Research on cognitive neuroscience indicate that the arrangement of excitatory and inhibitory cortex cells arise orientation selectivity in a local receptive field, within which the primary visual cortex performs visual information extraction for scene understanding. Inspired by the orientation selectivity mechanism, we compute the correlations among pixels in a local region based on the similarities of their preferred orientation. By imitating the arrangement of the excitatory/inhibitory cells, the correlations between a central pixel and its local neighbors are binarized, and the spatial correlation is represented with a set of binary values, which is named the orientation selectivity-based pattern. Then, taking both the gradient magnitude and the orientation selectivity-based pattern into account, a rotation invariant structure descriptor is introduced. The proposed structure descriptor is applied in texture classification and reduced reference image quality assessment, as two different application domains to verify its generality and robustness. Experimental results demonstrate that the orientation selectivity-based structure descriptor is robust to disturbance, and can effectively represent the structure degradation caused by different types of distortion.

Content-based image retrieval using computational visual attention model

It is a very challenging problem to well simulate visual attention mechanisms for content-based image retrieval. In this paper, we propose a novel computational visual attention model, namely saliency structure model, for content-based image retrieval. First, a novel visual cue, namely color volume, with edge information together is introduced to detect saliency regions instead of using the primary visual features (e.g., color, intensity and orientation). Second, the energy feature of the gray-level co-occurrence matrices is used for globally suppressing maps, instead of the local maxima normalization operator in Itti׳s model. Third, a novel image representation method, namely saliency structure histogram, is proposed to stimulate orientation-selective mechanism for image representation within CBIR framework. We have evaluated the performances of the proposed algorithm on two datasets. The experimental results clearly demonstrate that the proposed algorithm significantly outperforms the standard BOW baseline and micro-structure descriptor.

Localizing the Neural Substrate of Reflexive Covert Orienting

The capture of covert spatial attention by salient visual events influences subsequent gaze behavior. A task irrelevant stimulus (cue) can reduce (Attention capture) or prolong (Inhi-bition of return) saccade reaction time to a subsequent target stimulus depending on the cue-target delay. Here we investigated the mechanisms that underlie the sensory-based account of AC/IOR by manipulating the visual processing stage where the cue and target interact. In Experiment 1, liquid crystal shutter goggles were used to test whether AC/IOR occur at a monocular versus binocular processing stage (before versus after signals from both eyes converge). In Experiment 2, we tested whether visual orientation selective mechanisms are critical for AC/IOR by using oriented “Gabor” stimuli. We found that the magnitude of AC and IOR was not different between monocular and interocular viewing conditions, or between iso- and ortho-oriented cue-target interactions. The results suggest that the visual mechanisms that contribute to AC/IOR arise at an orientation-independent binocular processing stage.

Feedforward Origins of Response Variability Underlying Contrast Invariant Orientation Tuning in Cat Visual Cortex

Contrast invariant orientation tuning in simple cells of the visual cortex depends critically on contrast dependent trial-to-trial variability in their membrane potential responses. This observation raises the question of whether this variability originates from within the cortical circuit or the feedforward inputs from the lateral geniculate nucleus (LGN). To distinguish between these two sources of variability, we first measured membrane potential responses while inactivating the surrounding cortex, and found that response variability was nearly unaffected. We then studied variability in the LGN, including contrast dependence, and the trial-to-trial correlation in responses between nearby neurons. Variability decreased significantly with contrast, whereas correlation changed little. When these experimentally measured parameters of variability were applied to a feedforward model of simple cells that included realistic mechanisms of synaptic integration, contrast-dependent, orientation independent variability emerged in the membrane potential responses. Analogous mechanisms might contribute to the stimulus dependence and propagation of variability throughout the neocortex.

The mechanism of orientation selectivity in primary visual cortex without a functional map.

Neurons in primary visual cortex (V1) display substantial orientation selectivity even in species where V1 lacks an orientation map, such as in mice and rats. The mechanism underlying orientation selectivity in V1 with such a salt-and-pepper organization is unknown; it is unclear whether a connectivity that depends on feature similarity is required, or a random connectivity suffices. Here we argue for the latter. We study the response to a drifting grating of a network model of layer 2/3 with random recurrent connectivity and feedforward input from layer 4 neurons with random preferred orientations. We show that even though the total feedforward and total recurrent excitatory and inhibitory inputs all have a very weak orientation selectivity, strong selectivity emerges in the neuronal spike responses if the network operates in the balanced excitation/inhibition regime. This is because in this regime the (large) untuned components in the excitatory and inhibitory contributions approximately cancel. As a result the untuned part of the input into a neuron as well as its modulation with orientation and time all have a size comparable to the neuronal threshold. However, the tuning of the F0 and F1 components of the input are uncorrelated and the high-frequency fluctuations are not tuned. This is reflected in the subthreshold voltage response. Remarkably, due to the nonlinear voltage-firing rate transfer function, the preferred orientation of the F0 and F1 components of the spike response are highly correlated.

Global feature-based attention to orientation

Selective attention to motion direction can modulate the strength of direction-selective sensory responses regardless of their spatial locations. Although such spatially global modulation is thought to be a general property of feature-based attention, few studies have examined visual features other than motion. Here, we used an adaptation protocol combined with attentional instructions to assess whether attention to orientation, a prominent feature in early visual processing, also exhibit such spatially global modulation. We adapted observers to an orientation by cuing them to attend to the orientation in a compound grating that was presented at a peripheral location. We then assessed the size of the tilt aftereffect at three locations that were never stimulated by the adapter. Attending to orientation produced a tilt aftereffect in these locations, indicating that attention modulated orientation-selective mechanisms in remote locations from the adapter. Furthermore, there was no difference in the magnitude of the tilt aftereffect for test stimuli that were located at different distances and hemifields to the adapter. These results suggest that attention to orientation spreads uniformly across the visual field. Thus, spatially global modulation seems to be a general property of feature-based attention, and it provides a flexible mechanism to modulate feature salience across the visual field.

A biological plausible recurrent model of V1 hypercolumns

A biological plausible model of hypercolumn of V1 layer in the Primary Visual Cortex, modeled in the NEST Environment [1], is presented. The model addresses experimental findings on emergence of orientation selectivity which occurs in the V1 [2]. The network model is derived from the Bayesian confidence propagation neural network, which was presented earlier [3,4]. It is hypothesized that a modular recurrent network model can be used to address orientation selectivity mechanism [2]. Thus, the columnar organization of primary visual cortex is assumed [5]. The network consists of 16 minicolumn models each representing an orientation, ranging from 0o to 168.75o, with the angular distance of 11.25o between two adjacent minicolumn models. LGN input is broadly tuned, half-width of half-height (HWHH) is 40 o. Excitatory->Excitatory network targets all neurons with the probability of 60% inside the host minicolumn with a HWHH of 25o as a function of distance (ESPSs = 3.15 mV). Inhibitory->Excitatory is connected with the probability of 40% (ISPSs = -5.85mV). Excitatory->Inhibitory connections target all neurons with the probability of 40%, and HWHH of 67.5o as a function of distance (ESPSs = 1.35 mV). Furthermore, LGN input is 1/3 of cortical excitation. Hypercolumn model also reflects biological phenomenon of background activity caused by random cortical inputs, as suggested by the experimental findings. In the absence of LGN input, background activity of the population is around 0.5-2 spikes/sec.

Laminar and Orientation-Dependent Characteristics of Spatial Nonlinearities: Implications for the Computational Architecture of Visual Cortex

A full understanding of the computations performed in primary visual cortex is an important yet elusive goal. Receptive field models consisting of cascades of linear filters and static nonlinearities may be adequate to account for responses to simple stimuli such as gratings and random checkerboards, but their predictions of responses to complex stimuli such as natural scenes are only approximately correct. It is unclear whether these discrepancies are limited to quantitative inaccuracies that reflect well-recognized mechanisms such as response normalization, gain controls, and cross-orientation suppression or, alternatively, imply additional qualitative features of the underlying computations. To address this question, we examined responses of V1 and V2 neurons in the monkey and area 17 neurons in the cat to two-dimensional Hermite functions (TDHs). TDHs are intermediate in complexity between traditional analytic stimuli and natural scenes and have mathematical properties that facilitate their use to test candidate models. By exploiting these properties, along with the laminar organization of V1, we identify qualitative aspects of neural computations beyond those anticipated from the above-cited model framework. Specifically, we find that V1 neurons receive signals from orientation-selective mechanisms that are highly nonlinear: they are sensitive to phase correlations, not just spatial frequency content. That is, the behavior of V1 neurons departs from that of linear-nonlinear cascades with standard modulatory mechanisms in a qualitative manner: even relatively simple stimuli evoke responses that imply complex spatial nonlinearities. The presence of these findings in the input layers suggests that these nonlinearities act in a feedback fashion.

Dissociation of Neural Mechanisms Underlying Orientation Processing in Humans

Orientation selectivity is a fundamental, emergent property of neurons in early visual cortex, and the discovery of that property has dramatically shaped how we conceptualize visual processing. However, much remains unknown about the neural substrates of this basic building block of perception, and what is known primarily stems from animal physiology studies. To probe the neural concomitants of orientation processing in humans, we employed repetitive transcranial magnetic stimulation (rTMS), which can significantly attenuate neuronal spiking activity, hemodynamic responses, and local field potentials within a focused cortical region. Using rTMS to suppress neural responses evoked by stimuli falling within a local region of the visual field, we were able to dissociate two distinct components of the neural circuitry underlying orientation processing: selectivity and contextual effects. Orientation selectivity gauged by masking was unchanged by rTMS, whereas an otherwise robust orientation repulsion illusion was weakened after rTMS. This dissociation implies that orientation processing in humans relies on distinct mechanisms, only one of which was impacted by rTMS. These results are consistent with models positing that orientation selectivity is governed by patterns of convergence of thalamic afferents onto cortical neurons, with intracortical activity then shaping population responses amongst those cortical neurons.

The effect of aging on the orientational selectivity of the human visual system

Leventhal et al. ( Science, 2003, 300(5620), 812–815) reported that orientation selectivity of V1 neurons was significantly reduced in older macaque monkeys, which suggests that mechanisms that encode orientation in humans may become more broadly tuned in old age. We examined this hypothesis in two experiments that used sine-wave masking and notched-noise masking to estimate the bandwidth of orientation-selective mechanisms in younger (age ≈ 23 years) and older (age ≈ 68 years) human adults. In both experiments, the orientation selectivity of masking was essentially identical in younger and older subjects.

Cellular Mechanisms Underlying Stimulus-Dependent Gain Modulation in Primary Visual Cortex Neurons In Vivo

Gain modulation is a widespread neuronal phenomenon that modifies response amplitude without changing selectivity. Computational and in vitro studies have proposed cellular mechanisms of gain modulation based on the postsynaptic effects of background synaptic activation, but these mechanisms have not been studied in vivo. Here, we used intracellular recordings from cat primary visual cortex to measure neuronal gain while changing background synaptic activity with visual stimulation. We found that increases in the membrane fluctuations associated with increases in synaptic input do not obligatorily result in gain modulation in vivo. However, visual stimuli that evoked sustained changes in resting membrane potential, input resistance, and membrane fluctuations robustly modulated neuronal gain. The magnitude of gain modulation depended critically on the spatiotemporal properties of the visual stimulus. Gain modulation in vivo may thus be determined on a moment-to-moment basis by sensory context and the consequent dynamics of synaptic activation.

Neuronal Selectivity and Local Map Structure in Visual Cortex

The organization of primary visual cortex (V1) into functional maps makes individual cells operate in a variety of contexts. For instance, some neurons lie in regions of fairly homogeneous orientation preference (iso-orientation domains), while others lie in regions with a variety of preferences (e.g., pinwheel centers). We asked whether this diversity in local map structure correlates with the degree of selectivity of spike responses. We used a combination of imaging and electrophysiology to reveal that neurons in regions of homogeneous orientation preference have much sharper tuning. Moreover, in both monkeys and cats, a common principle links the structure of the orientation map, on the spatial scale of dendritic integration, to the degree of selectivity of individual cells. We conclude that neural computation is not invariant across the cortical surface. This finding must factor into future theories of receptive field wiring and map development.

Dynamics of Response to Perceptual Pop-Out Stimuli in Macaque V1

Contextual modulation due to feature contrast between the receptive field and surrounding region has been reported for numerous stimuli in primary visual cortex. One type of this modulation, iso-orientation surround suppression, has been studied extensively. The degree to which surround suppression is related to other forms of contextual modulation remains unknown. We used shape-from-shading stimuli in a field of distractors to test the latency and magnitude of contextual modulation to a stimulus that cannot be distinguished with an orientation-selective mechanism. This stimulus configuration readily elicits perceptual pop-out in human observers and induces a long-latency contextual modulation response in neurons in macaque early visual cortex. We found that animals trained to detect the location of a pop-out stimulus were better at finding a sphere that appeared to be lit from below in the presence of distractors that were lit from above. Furthermore, neuronal responses were stronger and had shorter latency in the condition where behavioral performance was best. This asymmetry is compatible with earlier psychophysical findings in human observers. In the population of V1 neurons, the latency of the contextual modulation response is 145 ms on average (ranging from 70 to 230 ms). This is much longer than the latency for iso-orientation surround suppression, indicating that the underlying circuitry is distinct. Our results support the idea that a feature-specific feedback signal generates the pop-out responses we observe and suggest that V1 neurons actively participate in the computation of perceptual salience.

The Emergence of Contrast-Invariant Orientation Tuning in Simple Cells of Cat Visual Cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.

Neuronal mechanisms of three-dimensional surface orientation selectivity in early visual cortex

Neuronal mechanisms of three-dimensional surface orientation selectivity in early visual cortex

Pattern detection: interactions between oriented and concentric patterns

Target threshold vs. pedestal contrast (TvC) functions for a vertical and a concentric target were measured on a vertical, a horizontal, a plaid or a concentric Gabor pedestal. All patterns had Guassian envelopes. All except one of the TvC functions had a dipper shape, that is, the target threshold first decreased and then increased with the pedestal contrast. The TvC function for a vertical target on a horizontal pedestal was monotonically increasing. A divisive inhibition model with two orientation selective mechanisms, sensitive to vertical and horizontal, fits the data reasonably well. A significant improvement in fit is obtained by adding one or two more mechanisms. These additional mechanisms are different for different observers. Some are consistent with oblique receptive fields, some with concentric receptive fields, and some are indeterminate.

Orientation and Direction Selectivity of Synaptic Inputs in Visual Cortical Neurons: A Diversity of Combinations Produces Spike Tuning

This intracellular study investigates synaptic mechanisms of orientation and direction selectivity in cat area 17. Visually evoked inhibition was analyzed in 88 cells by detecting spike suppression, hyperpolarization, and reduction of trial-to-trial variability of membrane potential. In 25 of these cells, inhibition visibility was enhanced by depolarization and spike inactivation and by direct measurement of synaptic conductances. We conclude that excitatory and inhibitory inputs share the tuning preference of spiking output in 60% of cases, whereas inhibition is tuned to a different orientation in 40% of cases. For this latter type of cells, conductance measurements showed that excitation shared either the preference of the spiking output or that of the inhibition. This diversity of input combinations may reflect inhomogeneities in functional intracortical connectivity regulated by correlation-based activity-dependent processes.

Dual oriented mechanisms in contour interaction

Foveal visual acuity is impaired by the presence of contours that surround the target (contour interaction (CI)). In order to determine the roles of various surrounding contours, visual acuities for a square C were measured in the presence of four and two flanking bars. Bars of different orientations relative to the gap of the C produced different CI patterns. The CI produced by a pair of bars was alleviated by adding another pair of bars of an orthogonal orientation. These results indicate that CI is mediated by not one, but at least two orientation selective mechanisms that actively inhibit each other.

Neural mechanisms of orientation selectivity in the visual cortex.

The origin of orientation selectivity in the responses of simple cells in cat visual cortex serves as a model problem for understanding cortical circuitry and computation. The feed-forward model posits that this selectivity arises simply from the arrangement of thalamic inputs to a simple cell. Much evidence, including a number of recent intracellular studies, supports a primary role of the thalamic inputs in determining simple cell response properties, including orientation tuning. This mechanism alone, however, cannot explain the invariance of orientation tuning to changes in stimulus contrast. Simple cells receive push-pull inhibition: ON inhibition in OFF subregions and vice versa. Addition of such inhibition to the feed-forward model can account for this contrast invariance, provided the inhibition is sufficiently strong. The predictions of "normalization" and "feedback" models are reviewed and compared with the predictions of this modified feed-forward model and with experimental results. The modified feed-forward and the feedback models ascribe fundamentally different functions to cortical processing.