Mixing of Chromatic and Luminance Retinal Signals in Primate Area V1

In primary visual cortex fMRI responses to chromatic and achromatic stimuli are interdependent and predict contrast detection thresholds

Chromatic and achromatic signals in primary visual cortex have historically been considered independent of each other but have since shown evidence of interdependence. Here, we investigated the combination of two components of a stimulus; an achromatic dynamically changing check background and a chromatic (L-M or S cone) target grating. We found that combinations of chromatic and achromatic signals in primary visual cortex were interdependent, with the dynamic range of responses to chromatic contrast decreasing as achromatic contrast increased. A contrast detection threshold study also revealed interdependence of background and target, with increasing chromatic contrast detection thresholds as achromatic background contrast increased. A model that incorporated a normalising effect of achromatic contrast on chromatic responses, but not vice versa, best predicted our V1 data as well as behavioural thresholds. Further along the visual hierarchy, the dynamic range of chromatic responses was maintained when compared to achromatic responses, which became increasingly compressive.

Brain activity characteristics of RGB stimulus: an EEG study

The perception of color is a fundamental cognitive feature of our psychological experience, with an essential role in many aspects of human behavior. Several studies used magnetoencephalography, functional magnetic resonance imaging, and electroencephalography (EEG) approaches to investigate color perception. Their methods includes the event-related potential and spectral power activity of different color spaces, such as Derrington-Krauskopf-Lennie and red-green-blue (RGB), in addition to exploring the psychological and emotional effects of colors. However, we found insufficient studies in RGB space that considered combining all aspects of EEG signals. Thus, in the present study, focusing on RGB stimuli and using a data-driven approach, we investigated significant differences in the perception of colors. Our findings show that beta oscillation of green compared to red and blue colors occurs in early sensory periods with a latency shifting in the occipital region. Furthermore, in the occipital region, the theta power of the blue color decreases noticeably compared to the other colors. Concurrently, in the prefrontal area, we observed an increase in phase consistency in response to the green color, while the blue color showed a decrease. Therefore, our results can be used to interpret the brain activity mechanism of color perception in RGB color space and to choose suitable colors for more efficient performance in cognitive activities.

Predictive coding of natural images by V1 firing rates and rhythmic synchronization

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quantify stimulus predictability for natural images based on self-supervised, generative neural networks. We find that neuronal firing rates were mainly modulated by the contextual predictability of higher-order image features, which correlated strongly with human perceptual similarity judgments. By contrast, V1 gamma (γ)-synchronization increased monotonically with the contextual predictability of low-level image features and emerged exclusively for larger stimuli. Consequently, γ-synchronization was induced by natural images that are highly compressible and low-dimensional. Natural stimuli with low predictability induced prominent, late-onset beta (β)-synchronization, likely reflecting cortical feedback. Our findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

Differences in chromatic noise suppression of luminance contrast discrimination in young and elderly people

Aging causes impairment of contrast sensitivity and chromatic discrimination, leading to changes in the perceptual interactions between color and luminance information. We aimed to investigate the influence of chromatic noise on luminance contrast thresholds in young and older adults. Forty participants were divided equally into Young (29.6 ± 6.3-year-old) and Elderly Groups (57.8 ± 6.6-year-old). They performed a luminance contrast discrimination task in the presence of chromatic noise maskers using a mosaic stimulus in a mosaic background. Four chromatic noise masking protocols were applied (protan, deutan, tritan, and no-noise protocols). We found that luminance contrast thresholds were significantly elevated by the addition of chromatic noise in both age groups (P < 0.05). In the Elderly group, but not the younger group, thresholds obtained in the tritan protocol were lower than those obtained from protan and deutan protocols (P < 0.05). For all protocols, the luminance contrast thresholds of elderly participants were higher than in young people (P < 0.01). Tritan chromatic noise was less effective in inhibiting luminance discrimination in elderly participants.

Quantitative and objective diagnosis of color vision deficiencies based on steady-state visual evoked potentials

PURPOSE

Traditional color vision tests depend on subjective judgments and are not suitable for infant children and subjects with cognitive dysfunction. We aimed to explore an objective and quantitative color vision testing method based on sweep steady-state visual evoked potentials (sweep SSVEPs) and compare the results with subjective Farnsworth-Munsell (FM) 100-hue test results.

METHODS

A red-green SSVEP pattern reversal checkboard paradigm at different luminance ratios was used to induce visual evoked potentials (VEPs) from 15 color vision deficiencies (CVDs) and 11 normal color vision subjects. After electroencephalography signals were processed by canonical correlation analysis, an equiluminance turning curve corresponding to the activation of the L-cones and M-cones at different levels of color vision was established. Then, we obtained different equiluminance T and proposed the SSVEP color vision severity index (I_CVD) to quantify color vision function and the severity of CVDs. In addition, the FM 100-hue test was used to obtain subjective data for the diagnosis of color vision.

RESULTS

The value of I_CVD can be an indicator of the level of color vision. Both the total error scores (TES) and confusion index (C-index) of the FM 100-hue test were significantly correlated with I_CVD values (P < 0.001, respectively). I_CVD also had a good classification effect in detecting normals, anomalous trichromats and dichromats. Moreover, equiluminance T had a good effect on classifying protans and deutans in subjects with CVDs.

CONCLUSION

Color vision evaluation with sweep SSVEPs showed a good correlation with subjective psychophysical methods. SSVEPs can be an objective and quantitative method to test color vision and diagnose CVDs.

Adaptation Modulates Spike-Phase Coupling Tuning Curve in the Rat Primary Auditory Cortex

Adaptation is an important mechanism that causes a decrease in the neural response both in terms of local field potentials (LFP) and spiking activity. We previously showed this reduction effect in the tuning curve of the primary auditory cortex. Moreover, we revealed that a repeated stimulus reduces the neural response in terms of spike-phase coupling (SPC). In the current study, we examined the effect of adaptation on the SPC tuning curve. To this end, employing the phase-locking value (PLV) method, we estimated the spike-LFP coupling. The data was obtained by a simultaneous recording from four single-electrodes in the primary auditory cortex of 15 rats. We first investigated whether the neural system may use spike-LFP phase coupling in the primary auditory cortex to encode sensory information. Secondly, we investigated the effect of adaptation on this potential SPC tuning. Our data showed that the coupling between spikes’ times and the LFP phase in beta oscillations represents sensory information (different stimulus frequencies), with an inverted bell-shaped tuning curve. Furthermore, we showed that adaptation to a specific frequency modulates SPC tuning curve of the adapter and its neighboring frequencies. These findings could be useful for interpretation of feature representation in terms of SPC and the underlying neural mechanism of adaptation.

Multiple-target tracking in human and machine vision

Humans are able to track multiple objects at any given time in their daily activities—for example, we can drive a car while monitoring obstacles, pedestrians, and other vehicles. Several past studies have examined how humans track targets simultaneously and what underlying behavioral and neural mechanisms they use. At the same time, computer-vision researchers have proposed different algorithms to track multiple targets automatically. These algorithms are useful for video surveillance, team-sport analysis, video analysis, video summarization, and human–computer interaction. Although there are several efficient biologically inspired algorithms in artificial intelligence, the human multiple-target tracking (MTT) ability is rarely imitated in computer-vision algorithms. In this paper, we review MTT studies in neuroscience and biologically inspired MTT methods in computer vision and discuss the ways in which they can be seen as complementary.

Multiple-target tracking (MTT) is a challenging task vital for both a human’s daily life and for many artificial intelligent systems, such as those used for urban traffic control. Neuroscientists are interested in discovering the underlying neural mechanisms that successfully exploit cognitive resources, e.g., spatial attention or memory, during MTT. Computer-vision specialists aim to develop powerful MTT algorithms based on advanced models or data-driven computational methods. In this paper, we review MTT studies from both communities and discuss how findings from cognitive studies can inspire developers to construct higher performing MTT algorithms. Moreover, some directions have been proposed through which MTT algorithms could raise new questions in the cognitive science domain, and answering them can shed light on neural processes underlying MTT.

Stimulus-Specific Adaptation Decreases the Coupling of Spikes to LFP Phase

Stimulus repetition suppresses the neural activity in different sensory areas of the brain. This mechanism of so-called stimulus-specific adaptation (SSA) has been observed in both spiking activity and local field potential (LFP) responses. However, much remains to be known about the effect of SSA on the spike–LFP relation. In this study, we approached this issue by investigating the spike-phase coupling (SPC) in control and adapting paradigms. For the control paradigm, pure tones were presented in a random unbiased sequence. In the adapting paradigm, the same stimuli were presented in a random pattern but it was biased to an adapter stimulus. In fact, the adapter occupied 80% of the adapting sequence. During the tasks, LFP and multi-unit activity were recorded simultaneously from the primary auditory cortex of 15 anesthetized rats. To clarify the effect of adaptation on the relation between spike and LFP responses, the SPC of the adapter stimulus in these two paradigms was evaluated. Here, we employed phase locking value method for calculating the SPC. Our data show a strong coupling of spikes to LFP phase most prominently in beta band. This coupling was observed to decrease in the adapting condition compared to the control one. Importantly, we found that adaptation reduces spikes dominantly from the preferred phase of LFP in which spikes are more likely to be present there. As a result, the preferred phase of LFP may play a key role in coordinating neuronal spiking activity in neural adaptation mechanism. This finding is important for interpretation of the underlying neural mechanism of adaptation and also can be used in the context of the network and related connectivity models.

Surface color and predictability determine contextual modulation of V1 firing and gamma oscillations

The integration of direct bottom-up inputs with contextual information is a core feature of neocortical circuits. In area V1, neurons may reduce their firing rates when their receptive field input can be predicted by spatial context. Gamma-synchronized (30–80 Hz) firing may provide a complementary signal to rates, reflecting stronger synchronization between neuronal populations receiving mutually predictable inputs. We show that large uniform surfaces, which have high spatial predictability, strongly suppressed firing yet induced prominent gamma synchronization in macaque V1, particularly when they were colored. Yet, chromatic mismatches between center and surround, breaking predictability, strongly reduced gamma synchronization while increasing firing rates. Differences between responses to different colors, including strong gamma-responses to red, arose from stimulus adaptation to a full-screen background, suggesting prominent differences in adaptation between M- and L-cone signaling pathways. Thus, synchrony signaled whether RF inputs were predicted from spatial context, while firing rates increased when stimuli were unpredicted from context.

Multifractal detrended fluctuation analysis of continuous neural time series in primate visual cortex

BACKGROUND

Local field potential (LFP) recordings have become an important tool to study the activity of populations of neurons. The functional activity of LFPs is usually compared with the activity of neighboring single spike neurons with sampling rates much higher than those of the continuous field potential channel (5 kHz). However, comparison of these signals generated with the lower sampling rate technique is important.

NEW METHOD

In this study, we provide an analysis of extracellular field potential time series using the sophisticated nonlinear multifractal detrended fluctuation analysis (MF-DFA). Using the MF-DFA, we demonstrate that the integral of the singularity spectrum is a powerful new method to measure the response tuning of spikes in the continuous field potential channel.

RESULTS

Results show that the spikes in the continuous channel at frequency ranges above the LFP component signals were consistently tuned similar to those in the spike channel. Our results also show that using a low-pass filter (<250 Hz), which is commonly applied as a preprocessing step to insulate LFPs from spikes, significantly influences the nonlinearity of the multifractal time series.

COMPARISON WITH EXISTING METHODS AND CONCLUSIONS

Our approach for inferring the tuning curve of spiking activity from the continuous channel has some advantages compared to conventional methods such as spike trains. The MF-DFA does not require any preprocessing of the raw signal data and makes no assumptions about the time series characteristics. This method is robust and can be applied to short time series of continuous raw signals.

Visual evoked cortical potential elicited by pseudoisochromatic stimulus

PURPOSE

Visual evoked cortical potentials (VECPs) are useful for investigating the mechanisms and dysfunctions of color vision. Chromatic sinusoidal gratings are generally used to elicit VECPs, but they require long psychophysical measurements to match the perceptual luminance between their stripes. An alternative method is to use pseudoisochromatic stimuli, which makes use of luminance noise to mask luminance clues and force the target perception to be dependent on chromatic contrast. In this study, we compared VECPs generated by sinusoidal gratings and pseudoisochromatic gratings. Contrary to chromatic sinusoidal gratings, pseudoisochromatic stimuli do not require the use of previous methods to find the equiluminance of the stimulus.

METHODS

Normal trichromats were recruited to be tested with red-green chromatic sinusoidal gratings and pseudoisochromatic gratings presented by pattern onset-offset and pattern reversal modes in five spatial frequencies. In addition, we also tested four different chromatic contrast pairs in pattern onset-offset mode presentation in five trichromats and one colorblind subject (deuteranope).

RESULTS

Pattern onset-offset VECPs elicited by sinusoidal gratings had a larger amplitude than those obtained with pseudoisochromatic stimuli, whereas pattern reversal VECPs elicited by pseudoisochromatic gratings had similar amplitudes compared to those elicited by sinusoidal gratings. We found no difference between the VECP amplitudes elicited by sinusoidal and pseudoisochromatic gratings containing different chromatic contrast. Color-blind subjects displayed absent or small responses to the stimuli.

CONCLUSION

Pseudoisochromatic stimulus can be an alternative stimulus to generate VECPs dominated by the chromatic mechanism.

Functional architecture of the foveola revealed in the living primate

The primate foveola, with its high cone density and magnified cortical representation, is exquisitely specialized for high-resolution spatial vision. However, uncovering the wiring of retinal circuitry responsible for this performance has been challenging due to the difficulty in recording receptive fields of foveal retinal ganglion cells (RGCs) in vivo. In this study, we use adaptive optics scanning laser ophthalmoscopy (AOSLO) to image the calcium responses of RGCs in the living primate, with a stable, high precision visual stimulus that allowed us to localize the receptive fields of hundreds of foveal ganglion cells. This approach revealed a precisely radial organization of foveal RGCs, despite the many distortions possible during the extended developmental migration of foveal cells. By back projecting the line connecting RGC somas to their receptive fields, we have been able to define the ‘physiological center’ of the foveola, locating the vertical meridian separating left and right hemifields in vivo.

Early Visual Processing of Feature Saliency Tasks: A Review of Psychophysical Experiments

The visual system is constantly bombarded with information originating from the outside world, but it is unable to process all the received information at any given time. In fact, the most salient parts of the visual scene are chosen to be processed involuntarily and immediately after the first glance along with endogenous signals in the brain. Vision scientists have shown that the early visual system, from retina to lateral geniculate nucleus (LGN) and then primary visual cortex, selectively processes the low-level features of the visual scene. Everything we perceive from the visual scene is based on these feature properties and their subsequent combination in higher visual areas. Different experiments have been designed to investigate the impact of these features on saliency and understand the relative visual mechanisms. In this paper, we review the psychophysical experiments which have been published in the last decades to indicate how the low-level salient features are processed in the early visual cortex and extract the most important and basic information of the visual scene. Important and open questions are discussed in this review as well and one might pursue these questions to investigate the impact of higher level features on saliency in complex scenes or natural images.

Cortical summation and attentional modulation of combined chromatic and luminance signals

Cortical networks that process colour and luminance signals are often studied separately, although colour appearance depends on both colour and luminance. In fact, objects in everyday life are very rarely defined by only colour or only luminance, necessitating an investigation into combined processing of these signals. We used steady-state visual evoked potentials (SSVEPs) to investigate (1) cortical summation of luminance and chromatic contrast and (2) attentional modulation of neural activity driven by competing stimuli that differ in chromoluminant content. Our stimuli combined fixed amounts of chromatic contrast from either of the two cone-opponent mechanisms (bluish and yellowish; reddish and greenish) with two different levels of positive luminance contrast. Our experiments found evidence of non-linear processing of combined colour and luminance signals, which most likely originates in V1-V3 neurons tuned to both colour and luminance. Differences between luminance contrast of stimuli were found to be a key determinant for the size of feature-based voluntary attentional effects in SSVEPs, with colours of lower contrast than the colour they were presented with receiving the highest level of attentional modulation. Our results indicate that colour and luminance contrast are processed interdependently, both in terms of perception and in terms of attentional selection, with a potential candidate mediating their link being stimulus appearance, which depends on both chromaticity and luminance.

Long-wavelength (reddish) hues induce unusually large gamma oscillations in the primate primary visual cortex

Electrophysiological signals recorded from the brain exhibit prominent gamma oscillations (∼30–80 Hz) under sensory stimulation. These oscillations are modulated by stimulus properties and behavioral state, and implicated to play a role in cognitive functions, such as attention and object-binding. In visual areas, gamma oscillations have mainly been studied using achromatic gratings/gabors. Here we show that color stimuli generate unprecedented levels of gamma oscillations in the local field potentials recorded from primate area V1. The strongest oscillations are induced by long-wavelength (reddish) hues. Importantly, their strength depends on color saturation but not on luminance, and is strongly correlated with the L−M cone contrast produced by stimuli, suggesting that gamma oscillations may represent key components of the processing of visual chromatic information.

Gamma oscillations (∼30–80 Hz) are a prominent signature of electrophysiological signals, with a purported role in natural vision. Previous studies in the primary visual cortex (area V1) have shown that achromatic gratings or gabor stimuli generate salient gamma oscillations, whose strength and frequency depend on stimulus properties such as their size, contrast, and orientation. Surprisingly, although natural images are rarely achromatic, the effect of chromatic input on gamma has not been thoroughly investigated. Recording from primate V1, we show that gamma oscillations of extremely high magnitude (peak increase of ∼300-fold in some cases), far exceeding the gamma generated by optimally tuned achromatic gratings, are induced in the local field potentials by full-field color stimuli of different hues. Furthermore, gamma oscillations are sensitive to the hue of the chromatic input, with the strongest oscillations for long-wavelength (reddish) hues and another, smaller gamma response peak for hues in the short-wavelength (bluish) range, which lie approximately on the two cardinal chromatic response axes of the upstream lateral geniculate nucleus neurons. These oscillations depended critically on the purity of the hue, decreasing with hue desaturation, but remained robust for pure hue stimuli even at reduced luminance. Importantly, the magnitude of gamma oscillations was highly correlated with positive L−M cone contrast produced by the stimuli, suggesting that gamma could be a marker of the specific mechanisms underlying this computation. These findings provide insights into the generation of gamma oscillations, as well as the processing of color along the visual pathway.

Influence of Spatial and Chromatic Noise on Luminance Discrimination

Pseudoisochromatic figures are designed to base discrimination of a chromatic target from a background solely on the chromatic differences. This is accomplished by the introduction of luminance and spatial noise thereby eliminating these two dimensions as cues. The inverse rationale could also be applied to luminance discrimination, if spatial and chromatic noise are used to mask those cues. In this current study estimate of luminance contrast thresholds were conducted using a novel stimulus, based on the use of chromatic and spatial noise to mask the use of these cues in a luminance discrimination task. This was accomplished by presenting stimuli composed of a mosaic of circles colored randomly. A Landolt-C target differed from the background only by the luminance. The luminance contrast thresholds were estimated for different chromatic noise saturation conditions and compared to luminance contrast thresholds estimated using the same target in a non-mosaic stimulus. Moreover, the influence of the chromatic content in the noise on the luminance contrast threshold was also investigated. Luminance contrast threshold was dependent on the chromaticity noise strength. It was 10-fold higher than thresholds estimated from non-mosaic stimulus, but they were independent of colour space location in which the noise was modulated. The present study introduces a new method to investigate luminance vision intended for both basic science and clinical applications.

The selectivity of responses to red-green colour and achromatic contrast in the human visual cortex: an fMRI adaptation study

There is controversy as to how responses to colour in the human brain are organized within the visual pathways. A key issue is whether there are modular pathways that respond selectively to colour or whether there are common neural substrates for both colour and achromatic (Ach) contrast. We used functional magnetic resonance imaging (fMRI) adaptation to investigate the responses of early and extrastriate visual areas to colour and Ach contrast. High-contrast red-green (RG) and Ach sinewave rings (0.5 cycles/degree, 2 Hz) were used as both adapting stimuli and test stimuli in a block design. We found robust adaptation to RG or Ach contrast in all visual areas. Cross-adaptation between RG and Ach contrast occurred in all areas indicating the presence of integrated, colour and Ach responses. Notably, we revealed contrasting trends for the two test stimuli. For the RG test, unselective processing (robust adaptation to both RG and Ach contrast) was most evident in the early visual areas (V1 and V2), but selective responses, revealed as greater adaptation between the same stimuli than cross-adaptation between different stimuli, emerged in the ventral cortex, in V4 and VO in particular. For the Ach test, unselective responses were again most evident in early visual areas but Ach selectivity emerged in the dorsal cortex (V3a and hMT+). Our findings support a strong presence of integrated mechanisms for colour and Ach contrast across the visual hierarchy, with a progression towards selective processing in extrastriate visual areas.

Boundary detection using double-opponency and spatial sparseness constraint

Brightness and color are two basic visual features integrated by the human visual system (HVS) to gain a better understanding of color natural scenes. Aiming to combine these two cues to maximize the reliability of boundary detection in natural scenes, we propose a new framework based on the color-opponent mechanisms of a certain type of color-sensitive double-opponent (DO) cells in the primary visual cortex (V1) of HVS. This type of DO cells has oriented receptive field with both chromatically and spatially opponent structure. The proposed framework is a feedforward hierarchical model, which has direct counterpart to the color-opponent mechanisms involved in from the retina to V1. In addition, we employ the spatial sparseness constraint (SSC) of neural responses to further suppress the unwanted edges of texture elements. Experimental results show that the DO cells we modeled can flexibly capture both the structured chromatic and achromatic boundaries of salient objects in complex scenes when the cone inputs to DO cells are unbalanced. Meanwhile, the SSC operator further improves the performance by suppressing redundant texture edges. With competitive contour detection accuracy, the proposed model has the additional advantage of quite simple implementation with low computational cost.

Brightness-color interactions in human early visual cortex

The interaction between brightness and color causes there to be different color appearance when one and the same object is viewed against surroundings of different brightness. Brightness contrast causes color to be desaturated, as has been found in perceptual experiments on color induction and color-gamut expansion in human vision. However, it is not clear yet where in the cerebral cortex the brightness-color interaction that causes these major perceptual effects is located. One hypothesis is that brightness and color signals are processed separately and in parallel within the primary visual cortex V1 and only interact in extrastriate cortex. Another hypothesis is that color and brightness contrast interact strongly already within V1. We localized the brightness-color interaction in human V1 by means of recording the chromatic visual-evoked potential. The chromatic visual-evoked potential measurements decisively support the idea that brightness-color interaction arises in a recurrent inhibitory network in V1. Furthermore, our results show that the inhibitory signal for brightness-color interaction is generated by local brightness contrast at the boundary between target and surround, instead of by the luminance difference between the interior of the color target and its large background.

Cortical responses elicited by luminance and compound stimuli modulated by pseudo-random sequences: comparison between normal trichromats and congenital red-green color blinds

Conventional pattern-reversal visual evoked cortical potential (VECP) shows positivity for luminance and chromatic equiluminant stimuli while conventional pattern-onset VECP shows positivity for luminance pattern-onset and negativity for chromatic pattern-onset. We evaluated how the presentation mode affects VECPs elicited by luminance and compound (luminance plus chromatic) pseudo-random stimulation. Eleven normal trichromats and 17 red-green color-blinds were studied. Pattern-reversal and pattern-onset luminance and compound (luminance plus red-green) gratings were temporally modulated by m-sequence. We used a cross-correlation routine to extract the first order kernel (K1) and the first and second slices of the second order kernel (K2.1 and K2.2, respectively) from the VECP response. We integrated the amplitude of VECP components as a function of time in order to estimate its magnitude for each stimulus condition. We also used a normalized cross-correlation method in order to test the similarity of the VECP components. The VECP components varied with the presentation mode and the presence of red-green contrast in the stimuli. In trichromats, for compound conditions, pattern-onset K1, K2.1, and K2.2, and pattern-reversal K2.1 and K2.2 had negative-dominated waveforms at 100 ms. Small negativity or small positivity were observed in dichromats. Trichromats had larger VECP magnitude than color-blinds for compound pattern-onset K1 (with large variability across subjects), compound pattern-onset and pattern-reversal K2.1, and compound pattern-reversal K2.2. Trichromats and color-blinds had similar VECP amplitude for compound pattern-reversal K1 and compound pattern-onset K2.2, as well as for all luminance conditions. The cross-correlation analysis showed high similarity between waveforms of compound pattern-onset K2.1 and pattern-reversal K2.2 as well as pattern-reversal K2.1 and K2.2. We suggest that compound pattern-reversal K2.1 is an appropriate response to study red-green color-opponent activity.

Low number of luminance levels in the luminance noise increases color discrimination thresholds estimated with pseudoisochromatic stimuli

In pseudoisochromatic stimuli the presence of spatial and luminance noise forces the subject to discriminate the target from the background solely on the basis of chromaticity difference. Color-blind subjects may show difficulty to identify the target due to the elimination of borders and brightness clues caused by the luminance and spatial noise. Few studies have fully described the features of pseudoisochromatic stimuli. Fewer investigators have focused their studies in the effects of specific pseudoisochromatic parameters on color discrimination. We used the Cambridge Color Test (CCT) to investigate the influence on color discrimination thresholds due to the number of luminance levels present in the luminance noise. The CCT default has six luminance steps; however, in our investigation a total of eight different conditions were tested from 2 to 16 luminance steps. It was found that the CCT provided very robust values for color discrimination thresholds, which were degraded only for very small number of luminance steps. When the number of steps was increased, the color discrimination thresholds improved from 2 to 6 luminance steps and gradually reached a plateau for 10 or more luminance steps. The area of color discrimination ellipses as a function of luminance steps matches the relative proportion of ineffective contrasts between mosaic patches as a function of luminance steps, assuming that contrast becomes ineffective for values 18.6% or less. The lower number of color and luminance interactions in these conditions could explain the measured increase of color discrimination thresholds. The primary conclusion from this investigation was that results from pseudoisochromatic tests should have their parameters described in more detail. This type of description would allow a better understanding of the results provided, interpretations, and therefore cross study comparison of results obtained from different laboratories.

Chromatic and Achromatic Spatial Resolution of Local Field Potentials in Awake Cortex

Local field potentials (LFPs) have become an important measure of neuronal population activity in the brain and could provide robust signals to guide the implant of visual cortical prosthesis in the future. However, it remains unclear whether LFPs can detect weak cortical responses (e.g., cortical responses to equiluminant color) and whether they have enough visual spatial resolution to distinguish different chromatic and achromatic stimulus patterns. By recording from awake behaving macaques in primary visual cortex, here we demonstrate that LFPs respond robustly to pure chromatic stimuli and exhibit ∼2.5 times lower spatial resolution for chromatic than achromatic stimulus patterns, a value that resembles the ratio of achromatic/chromatic resolution measured with psychophysical experiments in humans. We also show that, although the spatial resolution of LFP decays with visual eccentricity as is also the case for single neurons, LFPs have higher spatial resolution and show weaker response suppression to low spatial frequencies than spiking multiunit activity. These results indicate that LFP recordings are an excellent approach to measure spatial resolution from local populations of neurons in visual cortex including those responsive to color.