Functional organization of envelope-responsive neurons in early visual cortex: organization of carrier tuning properties

New Evidence of Central Nervous System Damage in Diabetes: Impairment of Fine Visual Discrimination

Diabetes can damage both the peripheral sensory organs, causing retinopathy, and the central visual system, leading to contrast sensitivity and impaired color vision in patients without retinopathy. Orientation discrimination is important for shape recognition by the visual system. Our psychophysical findings in this study show diminished orientation discrimination in patients with diabetes without retinopathy. To reveal the underlying mechanism, we established a diabetic mouse model and recorded in vivo electrophysiological data in the dorsal lateral geniculate nucleus (dLGN) and primary visual cortex (V1). Reduced orientation selectivity was observed in both individual and populations of neurons in V1 and dLGN, which increased in severity with disease duration. This diabetes-associated neuronal dysfunction appeared earlier in the V1 than dLGN. Additionally, neuronal activity and signal-to-noise ratio are reduced in V1 neurons of diabetic mice, leading to a decreased capacity for information processing by V1 neurons. Notably, the V1 in diabetic mice exhibits reduced excitatory neuronal activity and lower levels of phosphorylated mammalian target of rapamycin (mTOR). Our findings show that altered responses of both populations of and single V1 neurons may impair fine vision, thus expanding our understanding of the underlying causes of diabetes-related impairment of the central nervous system.

Bisphenol A exposure inhibits contrast sensitivity in cats involving increased response noise and inhibitory synaptic transmission

Contrast sensitivity (CS) is one of the primary fundamental factors determining how well we can see, and it directly influences object recognition. Whether bisphenol-A (BPA, an environmental xenoestrogen) can perturb contrast detection in the visual system has yet to be elucidated. In the present study, we analyzed CS of single neurons in the primary visual cortex (area 17, A17) of cats before and after BPA exposure using a multiple-channel recording technique. The results showed that CS of A17 neurons was markedly depressed with an increased contrast threshold after two hour of intravenous BPA administration, which had a positive correlation with decreased firing rates of A17 neurons. Additionally, responses of these neurons presented an overt increase in the trial-to-trail response variability (a kind of neuronal noise), which could disturb the information-filtering function of single neurons. We also found that neuronal CS in the visual relay station was not disturbed after BPA administration, which rules out the contribution of CS alteration in the optical pathway. Importantly, acute BPA treatment obviously increased the inhibitory innervation to the visual pyramidal neurons. This implies that alteration of intracortical inhibitory regulation contributes to the compromised contrast detection in the visual system after BPA treatment.

Modeling second-order boundary perception: A machine learning approach

Visual pattern detection and discrimination are essential first steps for scene analysis. Numerous human psychophysical studies have modeled visual pattern detection and discrimination by estimating linear templates for classifying noisy stimuli defined by spatial variations in pixel intensities. However, such methods are poorly suited to understanding sensory processing mechanisms for complex visual stimuli such as second-order boundaries defined by spatial differences in contrast or texture. We introduce a novel machine learning framework for modeling human perception of second-order visual stimuli, using image-computable hierarchical neural network models fit directly to psychophysical trial data. This framework is applied to modeling visual processing of boundaries defined by differences in the contrast of a carrier texture pattern, in two different psychophysical tasks: (1) boundary orientation identification, and (2) fine orientation discrimination. Cross-validation analysis is employed to optimize model hyper-parameters, and demonstrate that these models are able to accurately predict human performance on novel stimulus sets not used for fitting model parameters. We find that, like the ideal observer, human observers take a region-based approach to the orientation identification task, while taking an edge-based approach to the fine orientation discrimination task. How observers integrate contrast modulation across orientation channels is investigated by fitting psychophysical data with two models representing competing hypotheses, revealing a preference for a model which combines multiple orientations at the earliest possible stage. Our results suggest that this machine learning approach has much potential to advance the study of second-order visual processing, and we outline future steps towards generalizing the method to modeling visual segmentation of natural texture boundaries. This study demonstrates how machine learning methodology can be fruitfully applied to psychophysical studies of second-order visual processing.

Many naturally occurring visual boundaries are defined by spatial differences in features other than luminance, for example by differences in texture or contrast. Quantitative models of such “second-order” boundary perception cannot be estimated using the standard regression techniques (known as “classification images”) commonly applied to “first-order”, luminance-defined stimuli. Here we present a novel machine learning approach to modeling second-order boundary perception using hierarchical neural networks. In contrast to previous quantitative studies of second-order boundary perception, we directly estimate network model parameters using psychophysical trial data. We demonstrate that our method can reveal different spatial summation strategies that human observers utilize for different kinds of second-order boundary perception tasks, and can be used to compare competing hypotheses of how contrast modulation is integrated across orientation channels. We outline extensions of the methodology to other kinds of second-order boundaries, including those in natural images.

Cross-orientation suppression in visual area V2

Object recognition relies on a series of transformations among which only the first cortical stage is relatively well understood. Already at the second stage, the visual area V2, the complexity of the transformation precludes a clear understanding of what specifically this area computes. Previous work has found multiple types of V2 neurons, with neurons of each type selective for multi-edge features. Here we analyse responses of V2 neurons to natural stimuli and find three organizing principles. First, the relevant edges for V2 neurons can be grouped into quadrature pairs, indicating invariance to local translation. Second, the excitatory edges have nearby suppressive edges with orthogonal orientations. Third, the resulting multi-edge patterns are repeated in space to form textures or texture boundaries. The cross-orientation suppression increases the sparseness of responses to natural images based on these complex forms of feature selectivity while allowing for multiple scales of position invariance.

V2 neurons exhibit complex and diverse selectivity for visual features. Here the authors use a statistical analytical framework to model V2 responses to natural stimuli and find three organizing principles, chief among them is the cross-orientation suppression that increases response selectivity.

Neural Processing of Second-Order Motion in the Suprasylvian Cortex of the Cat

Neuronal responses to second-order motion, that is, to spatiotemporal variations of texture or contrast, have been reported in several cortical areas of mammals, including the middle-temporal (MT) area in primates. In this study, we investigated whether second-order responses are present in the cat posteromedial lateral suprasylvian (PMLS) cortex, a possible homolog of the primate area MT. The stimuli used were luminance-based sine-wave gratings (first-order) and contrast-modulated carrier stimuli (second-order), which consisted of a high-spatial-frequency static grating (carrier) whose contrast was modulated by a low-spatial-frequency drifting grating (envelope). Results indicate that most PMLS neurons responded to second-order motion and for the vast majority of cells, first- and second-order preferred directions were conserved. However, responses to second-order stimuli were significantly reduced when compared to those evoked by first-order gratings. Circular variance was increased for second-order stimuli, indicating that PMLS direction selectivity was weaker for this type of stimulus. Finally, carrier orientation selectivity was either absent or very broad and had no influence on the envelope's orientation selectivity. In conclusion, our data show that PMLS neurons exhibit similar first- and second-order response profiles and that, akin primate area MT cells, they perform a form-cue invariant analysis of motion signals.

Form-cue invariant second-order neuronal responses to contrast modulation in primate area V2

A fundamental task of the visual system is to extract figure-ground boundaries between images of objects, which in natural scenes are often defined not only by luminance differences but also by "second-order" contrast or texture differences. Responses to contrast modulation (CM) and other second-order stimuli have been extensively studied in human psychophysics, but the neuronal substrates of second-order responses in nonhuman primates remain poorly understood. In this study, we have recorded single neurons in area V2 of macaque monkeys, using both CM patterns as well as conventional luminance modulation (LM) gratings. CM stimuli were constructed from stationary sine wave grating carrier patterns, which were modulated by drifting envelope gratings of a lower spatial frequency. We found approximately one-third of visually responsive V2 neurons responded to CM stimuli with a pronounced selectivity to carrier spatial frequencies, and often orientations, that were clearly outside the neurons' passbands for LM gratings. These neurons were "form-cue invariant" in that their tuning to CM envelope spatial frequency and orientation was very similar to that for LM gratings. Neurons were tuned to carrier spatial frequencies that were typically 2-4 octaves higher than their optimal envelope spatial frequencies, similar to results from human psychophysics. These results are distinct from CM responses arising from surround suppression, but could be understood in terms of a filter-rectify-filter model. Such neurons could provide a functionally useful and explicit representation of segmentation boundaries as well as a plausible neural substrate for human perception of second-order boundaries.

Surround suppression supports second-order feature encoding by macaque V1 and V2 neurons

Single neurons in areas V1 and V2 of macaque visual cortex respond selectively to luminance-modulated stimuli. These responses are often influenced by context, for example when stimuli extend outside the classical receptive field (CRF). These contextual phenomena, observed in many sensory areas, reflect a fundamental cortical computation and may inform perception by signaling second-order visual features which are defined by spatial relationships of contrast, orientation and spatial frequency. In the anesthetized, paralyzed macaque, we measured single-unit responses to a drifting preferred sinusoidal grating; low spatial frequency sinusoidal contrast modulations were applied to the grating, creating contrast-modulated, second-order forms. Most neurons responded selectively to the orientation of the contrast modulation of the preferred grating and were therefore second-order orientation-selective. Second-order selectivity was created by the asymmetric spatial organization of the excitatory CRF and suppressive extraclassical surround. We modeled these receptive field subregions using spatial Gaussians, sensitive to the modulation of contrast (not luminance) of the preferred carrier grating, that summed linearly and were capable of recovering asymmetrical receptive field organizations. Our modeling suggests that second-order selectivity arises both from elongated excitatory CRFs, asymmetrically organized extraclassical surround suppression, or both. We validated the model by successfully testing its predictions against conventional surround suppression measurements and spike-triggered analysis of second-order form responses. Psychophysical adaptation measurements on human observers revealed a pattern of second-order form selectivity consistent with neural response patterns. We therefore propose that cortical cells in primates do double duty, providing signals about both first- and second-order forms.

Contextual modulation as de-texturizer

Contextual modulation refers to the effect of texture placed outside of a neuron's classical receptive field as well as the effect of surround texture on the perceptual properties of variegated regions within. In this minireview, we argue that one role of contextual modulation is to enhance the perception of contours at the expense of textures, in short to de-texturize the image. The evidence for this role comes mainly from three sources: psychophysical studies of shape after-effects, computational models of neurons that exhibit iso-orientation surround inhibition, and fMRI studies revealing specialized areas for contour as opposed to texture processing. The relationship between psychophysical studies that support the notion of contextual modulation as de-texturizer and those that investigate contour integration and crowding is discussed.

Depth perception from dynamic occlusion in motion parallax: roles of expansion-compression versus accretion-deletion

Motion parallax, or differential retinal image motion from observer movement, provides important information for depth perception. We previously measured the contribution of shear motion parallax to depth, which is only composed of relative motion information. Here, we examine the roles of relative motion and accretion-deletion information in dynamic occlusion motion parallax. Observers performed two-alternative forced choice depth-ordering tasks in response to low spatial frequency patterns of horizontal random dot motion that were synchronized to the observer's head movements. We examined conditions that isolated or combined expansion-compression and accretion-deletion across a range of simulated relative depths. At small depths, expansion-compression provided reliable depth perception while accretion-deletion had a minor contribution: When the two were in conflict, the perceived depth was dominated by expansion-compression. At larger depths in the cue-conflict experiment, accretion-deletion determined the depth-ordering performance. Accretion-deletion in isolation did not yield any percept of depth even though, in theory, it provided sufficient information for depth ordering. Thus, accretion-deletion can substantially enhance depth perception at larger depths but only in the presence of relative motion. The results indicate that expansion-compression contributes to depth from motion parallax across a broad range of depths whereas accretion-deletion contributes primarily at larger depths.