Orientation discrimination in human vision: Psychophysics and modeling

Quantifying population-level neural tuning functions using Ricker wavelets and the Bayesian bootstrap

BACKGROUND

Experience changes visuo-cortical tuning. In humans, re-tuning has been studied during aversive generalization learning, in which the similarity of generalization stimuli (GSs) with a conditioned threat cue (CS+) is used to quantify tuning functions. Previous work utilized pre-defined tuning shapes (generalization and sharpening patterns). This approach may constrain the ways in which re-tuning can be characterized since the tuning patterns may not match the prototypical functions.

NEW METHOD

The present study proposes a flexible and data-driven method for precisely quantifying changes in tuning based on the Ricker wavelet function and the Bayesian bootstrap. This method was applied to EEG and psychophysics data from an aversive generalization learning paradigm.

RESULTS

The Ricker wavelet model fitted the steady-state visual event potentials (ssVEP), alpha-band power, and detection accuracy data well. A Morlet wavelet function was used for comparison and fit the data better in some situations, but was more challenging to interpret. The pattern of re-tuning in the EEG data, predicted by the Ricker model, resembled the shapes of the best fitting a-priori patterns.

COMPARISON WITH EXISTING METHODS

Although the re-tuning shape modeled by the Ricker function resembled the pre-defined shapes, the Ricker approach led to greater Bayes factors and more interpretable results compared to a-priori models. The Ricker approach was more easily fit and led to more interpretable results than a Morlet wavelet model.

CONCLUSION

This work highlights the promise of the current method for capturing the precise nature of visuo-cortical tuning, unconstrained by the implementation of a-priori models.

How does V1 population activity inform perceptual certainty?

Neural population activity in sensory cortex informs our perceptual interpretation of the environment. Oftentimes, this population activity will support multiple alternative interpretations. The larger the spread of probability over different alternatives, the more uncertain the selected perceptual interpretation. We test the hypothesis that the reliability of perceptual interpretations can be revealed through simple transformations of sensory population activity. We recorded V1 population activity in fixating macaques while presenting oriented stimuli under different levels of nuisance variability and signal strength. We developed a decoding procedure to infer from V1 activity the most likely stimulus orientation as well as the certainty of this estimate. Our analysis shows that response magnitude, response dispersion, and variability in response gain all offer useful proxies for orientation certainty. Of these three metrics, the last one has the strongest association with the decoder's uncertainty estimates. These results clarify that the nature of neural population activity in sensory cortex provides downstream circuits with multiple options to assess the reliability of perceptual interpretations.

Excitation creates a distributed pattern of cortical suppression due to varied recurrent input

Dense local, recurrent connections are a major feature of cortical circuits, yet how they affect neurons' responses has been unclear, with some studies reporting weak recurrent effects, some reporting amplification, and others indicating local suppression. Here, we show that optogenetic input to mouse V1 excitatory neurons generates salt-and-pepper patterns of both excitation and suppression. Responses in individual neurons are not strongly predicted by that neuron's direct input. A balanced-state network model reconciles a set of diverse observations: the observed dynamics, suppressed responses, decoupling of input and output, and long tail of excited responses. The model shows recurrent excitatory-excitatory connections are strong and also variable across neurons. Together, these results demonstrate that excitatory recurrent connections can have major effects on cortical computations by shaping and changing neurons' responses to input.

Trend judgment as a perceptual building block of graphicacy and mathematics, across age, education, and culture

Data plots are widely used in science, journalism and politics, since they efficiently allow to depict a large amount of information. Graphicacy, the ability to understand graphs, has thus become a fundamental cultural skill comparable to literacy or numeracy. Here, we introduce a measure of intuitive graphicacy that assesses the perceptual ability to detect a trend in noisy scatterplots ("does this graph go up or down?"). In 3943 educated participants, responses vary as a sigmoid function of the t-value that a statistician would compute to detect a significant trend. We find a minimum level of core intuitive graphicacy even in unschooled participants living in remote Namibian villages (N = 87) and 6-year-old 1st-graders who never read a graph (N = 27). The sigmoid slope that we propose as a proxy of intuitive graphicacy increases with education and tightly correlates with statistical and mathematical knowledge, showing that experience contributes to refining graphical intuitions. Our tool, publicly available online, allows to quickly evaluate and formally quantify a perceptual building block of graphicacy.

Cortical recurrence supports resilience to sensory variance in the primary visual cortex

Our daily endeavors occur in a complex visual environment, whose intrinsic variability challenges the way we integrate information to make decisions. By processing myriads of parallel sensory inputs, our brain is theoretically able to compute the variance of its environment, a cue known to guide our behavior. Yet, the neurobiological and computational basis of such variance computations are still poorly understood. Here, we quantify the dynamics of sensory variance modulations of cat primary visual cortex neurons. We report two archetypal neuronal responses, one of which is resilient to changes in variance and co-encodes the sensory feature and its variance, improving the population encoding of orientation. The existence of these variance-specific responses can be accounted for by a model of intracortical recurrent connectivity. We thus propose that local recurrent circuits process uncertainty as a generic computation, advancing our understanding of how the brain handles naturalistic inputs.

Weak evidence for neural correlates of task-switching in macaque V1

A central goal of systems neuroscience is to understand how populations of sensory neurons encode and relay information to the rest of the brain. Three key quantities of interest are 1) how mean neural activity depends on the stimulus (sensitivity), 2) how neural activity (co)varies around the mean (noise correlations), and 3) how predictive these variations are of the subject's behavior (choice probability). Previous empirical work suggests that both choice probability and noise correlations are affected by task training, with decision-related information fed back to sensory areas and aligned to neural sensitivity on a task-by-task basis. We used Utah arrays to record activity from populations of primary visual cortex (V1) neurons from two macaque monkeys that were trained to switch between two coarse orientation-discrimination tasks. Surprisingly, we find no evidence for significant trial-by-trial changes in noise covariance between tasks, nor do we find a consistent relationship between neural sensitivity and choice probability, despite recording from well-tuned task-sensitive neurons, many of which were histologically confirmed to be in supragranular V1, and despite behavioral evidence that the monkeys switched their strategy between tasks. Thus our data at best provide weak support for the hypothesis that trial-by-trial task-switching induces changes to noise correlations and choice probabilities in V1. However, our data agree with a recent finding of a single "choice axis" across tasks. They also raise the intriguing possibility that choice-related signals in early sensory areas are less indicative of task learning per se and instead reflect perceptual learning that occurs in highly overtrained subjects.NEW & NOTEWORTHY Converging evidence suggests that decision processes affect sensory neural activity, and this has informed numerous theories of neural processing. We set out to replicate and extend previous results on decision-related information and noise correlations in V1 of macaque monkeys. However, in our data, we find little evidence for a number of expected effects. Our null results therefore call attention to differences in task training, stimulus design, recording, and analysis techniques between our and prior studies.

Coding of chromatic spatial contrast by macaque V1 neurons

Color perception relies on comparisons between adjacent lights, but how the brain performs these comparisons is poorly understood. To elucidate the underlying neural mechanisms, we recorded spiking responses of individual V1 neurons in macaque monkeys to pairs of stimuli within the classical receptive field (RF). We estimated the spatial-chromatic RF of each neuron and then presented customized colored edges using a novel closed-loop technique. We found that many double-opponent (DO) cells, which have spatially and chromatically opponent RFs, responded to chromatic contrast as a weighted sum, akin to how other V1 cells responded to luminance contrast. Yet other neurons integrated chromatic signals non-linearly, confirming that linear signal integration is not an obligate property of V1 neurons. The functional similarity of cone-opponent DO cells and cone non-opponent simple cells suggests that these two groups may share a common underlying neural circuitry, promotes the construction of image-computable models for full-color image representation, and sheds new light on V1 complex cells.

Stimulus uncertainty predicts serial dependence in orientation judgements

How is what you see influenced by what you saw? The visual system may use recent perception to inform responses to current stimuli. This can cause the perception of current stimuli to be attracted toward previous observations, an effect termed serial dependence. This misperception might well be useful in a noisy visual environment, where minor image distortions over time may not actually represent meaningful change. Previous work has suggested that Bayesian perceptual inference may underlie serial dependence. For this to be true, the relative uncertainty associated with both prior and current sensory input should be taken into account. In an experiment manipulating the level of noise present in orientation stimuli, we found an effect of current stimulus uncertainty on serial dependence. We found no good evidence for an effect of previous stimulus uncertainty. Our results provide only partial evidence for the Bayesian interpretation of serial dependence. Non-Bayesian models may provide a better account of the phenomenon.

A robust confidence-accuracy dissociation via criterion attraction

Many studies have shown that confidence and accuracy can be dissociated in a variety of tasks. However, most of these dissociations involve small effect sizes, occur only in a subset of participants, and include a reaction time (RT) confound. Here, I develop a new method for inducing confidence-accuracy dissociations that overcomes these limitations. The method uses an external noise manipulation and relies on the phenomenon of criterion attraction where criteria for different tasks become attracted to each other. Subjects judged the identity of stimuli generated with either low or high external noise. The results showed that the two conditions were matched on accuracy and RT but produced a large difference in confidence (effect appeared for 25 of 26 participants, effect size: Cohen's d = 1.9). Computational modeling confirmed that these results are consistent with a mechanism of criterion attraction. These findings establish a new method for creating conditions with large differences in confidence without differences in accuracy or RT. Unlike many previous studies, however, the current method does not lead to differences in subjective experience and instead produces robust confidence-accuracy dissociations by exploiting limitations in post-perceptual, cognitive processes.

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Making good decisions requires updating beliefs according to new evidence. This is a dynamical process that is prone to biases: in some cases, beliefs become entrenched and resistant to new evidence (leading to primacy effects), while in other cases, beliefs fade over time and rely primarily on later evidence (leading to recency effects). How and why either type of bias dominates in a given context is an important open question. Here, we study this question in classic perceptual decision-making tasks, where, puzzlingly, previous empirical studies differ in the kinds of biases they observe, ranging from primacy to recency, despite seemingly equivalent tasks. We present a new model, based on hierarchical approximate inference and derived from normative principles, that not only explains both primacy and recency effects in existing studies, but also predicts how the type of bias should depend on the statistics of stimuli in a given task. We verify this prediction in a novel visual discrimination task with human observers, finding that each observer's temporal bias changed as the result of changing the key stimulus statistics identified by our model. The key dynamic that leads to a primacy bias in our model is an overweighting of new sensory information that agrees with the observer's existing belief-a type of 'confirmation bias'. By fitting an extended drift-diffusion model to our data we rule out an alternative explanation for primacy effects due to bounded integration. Taken together, our results resolve a major discrepancy among existing perceptual decision-making studies, and suggest that a key source of bias in human decision-making is approximate hierarchical inference.

Variance-dependent neural activity in an unvoluntary averaging task

Ensemble statistics of a visual scene can be estimated to provide a gist of the scene without detailed analysis of all individual items. The simplest and most widely studied ensemble statistic is mean estimation, which requires averaging an ensemble of elements. Averaging is useful to estimate the mean of an ensemble and discard the variance. The source of variance can be external (i.e., variance across the physical elements) or internal (i.e., imprecisions in the estimates of the elements by the visual system). The equivalent noise paradigm is often used to measure the impact of the internal variance (i.e., the equivalent input noise). This paradigm relies on the assumption that the averaging process is equally effective independently of the main source of variance, internal or external, so any difference between the processing when the main source of variance is internal or external must be assumed not to affect the averaging efficiency. The current fMRI study compared the neural activity when the main variance is caused by the stimulus (i.e., high variance) and when it is caused by imprecisions in the estimates of the elements by the visual system (i.e., low variance). The results showed that the right superior frontal and left middle frontal gyri can be significantly more activated when the variance in the orientation of the Gabors was high than when it was low. Consequently, the use of the equivalent noise paradigm requires the assumption that such additional neural activity in high variance does not affect the averaging efficiency.

Migraine understood as a sensory threshold disease

Migraine encompasses a broader spectrum of sensory symptoms than just headache. These "other" symptoms, eg, sensory phobias, cognitive and mood changes, allodynia, and many others indicate an altered sensitivity to sensory input which can be measured, in principle, by quantifying sensory threshold changes longitudinally over time. Photophobia, for example, can be quantified by investigating the discomfort thresholds towards the luminance of light. The aim of this review is to look into how thresholds change in patients with migraine. We performed a PubMed search up to June 2018 targeting all peer-reviewed articles evaluating the changes in threshold, sensory phobia, or sensitivity in patients with migraine. Migraineurs, in general, exhibit lower sensory thresholds compared with healthy controls. These threshold changes seem to follow the different phases during a migraine cycle. In general, thresholds reach a nadir when the headache starts (the ictal phase), rise after the headache ends, and then gradually descend towards the next attack. The sensory modality of measurement-mechanical, thermal, or nociceptive-and the location of measurement-trigeminal vs somatic dermatome-also influence the sensory threshold. Functional imaging studies provide evidence that the hypothalamo-thalamo-brainstem network may be the driving force behind the periodic threshold changes. In summary, there is evidence in the literature that migraine could be understood as a periodic sensory dysregulation originating from the brain. Nevertheless, the interstudy discrepancy is still high due to different study designs and a lack of focus on distinct migraine phases. Further well-designed and harmonized studies with an emphasis on the cyclic changes still need to be conducted.

Representation of visual uncertainty through neural gain variability

Uncertainty is intrinsic to perception. Neural circuits which process sensory information must therefore also represent the reliability of this information. How they do so is a topic of debate. We propose a model of visual cortex in which average neural response strength encodes stimulus features, while cross-neuron variability in response gain encodes the uncertainty of these features. To test this model, we studied spiking activity of neurons in macaque V1 and V2 elicited by repeated presentations of stimuli whose uncertainty was manipulated in distinct ways. We show that gain variability of individual neurons is tuned to stimulus uncertainty, that this tuning is specific to the features encoded by these neurons and largely invariant to the source of uncertainty. We demonstrate that this behavior naturally arises from known gain-control mechanisms, and illustrate how downstream circuits can jointly decode stimulus features and their uncertainty from sensory population activity.

Contingent adaptation in masking and surround suppression

Adaptation is the process that changes a neuron's response based on recent inputs. In the traditional model, a neuron's state of adaptation depends on the recent input to that neuron alone, whereas in a recently introduced model (Hebbian normalization), adaptation depends on the structure of neural correlated firing. In particular, increased response products between pairs of neurons leads to increased mutual suppression. We test a psychophysical prediction of this model: adaptation should depend on 2nd-order statistics of input stimuli. That is, if two stimuli excite two distinct sub-populations of neurons, then presenting those stimuli simultaneously during adaptation should strengthen mutual suppression between those subpopulations. We confirm this prediction in two experiments. In the first, pairing two gratings synchronously during adaptation (i.e., a plaid) rather than asynchronously (interleaving the two gratings in time) leads to increased effectiveness of one pattern for masking the other. In the second, pairing the gratings in a center-surround configuration results in reduced apparent contrast for the central grating when paired with the same surround (as compared with a condition in which the central grating appears with a different surround at test than during adaptation). These results are consistent with the prediction that an increase in response covariance leads to greater mutual suppression between neurons. This effect is detectable both at threshold (masking) and well above threshold (apparent contrast).

Iconic Memories Die a Sudden Death

Iconic memory is characterized by its large storage capacity and brief storage duration, whereas visual working memory is characterized by its small storage capacity. The limited information stored in working memory is often modeled as an all-or-none process in which studied information is either successfully stored or lost completely. This view raises a simple question: If almost all viewed information is stored in iconic memory, yet one second later most of it is completely absent from working memory, what happened to it? Here, I characterized how the precision and capacity of iconic memory changed over time and observed a clear dissociation: Iconic memory suffered from a complete loss of visual items, while the precision of items retained in memory was only marginally affected by the passage of time. These results provide new evidence for the discrete-capacity view of working memory and a new characterization of iconic memory decay.

Measuring Early Cortical Visual Processing in the Clinic

We describe a mobile app that measures early cortical visual processing suitable for use in clinics. The app is called Component Extraction and Motion Integration Test (CEMIT). Observers are asked to respond to the direction of translating plaids that move in one of two very different directions. The plaids have been selected so that the plaid components move in one of the directions and the plaid pattern moves in the other direction. In addition to correctly responding to the pattern motion, observers demonstrate their ability to correctly extract the movement (and therefore the orientation) of the underlying components at specific spatial frequencies. We wanted to test CEMIT by seeing if we could replicate the broader tuning observed at low spatial frequencies for this type of plaid. Results from CEMIT were robust and successfully replicated this result for 50 typical observers. We envisage that it will be of use to researchers and clinicians by allowing them to investigate specific deficits at this fundamental level of cortical visual processing. CEMIT may also be used for screening purposes where visual information plays an important role, for example, air traffic controllers.

Spatial precision of population activity in primate area MT

The middle temporal (MT) area is a cortical area integral to the "where" pathway of primate visual processing, signaling the movement and position of objects in the visual world. The receptive field of a single MT neuron is sensitive to the direction of object motion but is too large to signal precise spatial position. Here, we asked if the activity of MT neurons could be combined to support the high spatial precision required in the where pathway. With the use of multielectrode arrays, we recorded simultaneously neural activity at 24-65 sites in area MT of anesthetized marmoset monkeys. We found that although individual receptive fields span more than 5° of the visual field, the combined population response can support fine spatial discriminations (<0.2°). This is because receptive fields at neighboring sites overlapped substantially, and changes in spatial position are therefore projected onto neural activity in a large ensemble of neurons. This fine spatial discrimination is supported primarily by neurons with receptive fields flanking the target locations. Population performance is degraded (by 13-22%) when correlations in neural activity are ignored, further reflecting the contribution of population neural interactions. Our results show that population signals can provide high spatial precision despite large receptive fields, allowing area MT to represent both the motion and the position of objects in the visual world.

The efficiency of second order orientation coherence detection

Neurons in early visual cortex respond to both luminance- (1st order) and contrast-modulated (2nd order) local features in the visual field. In later extra-striate areas neurons with larger receptive fields integrate information across the visual field. For example, local luminance-defined features can be integrated into contours and shapes. Evidence for the global integration of features defined by contrast-modulation is less well established. While good performance in some shape tasks has been demonstrated with 2nd order stimuli, the integration of contours fails with 2nd order elements. Recently we developed a global orientation coherence task that is more basic than contour integration, bearing similarity to the well-established global motion coherence task. Similar to our previous 1st order result for this task, we find 2nd order coherence detection to be scale-invariant. There was a small but significant threshold elevation for 2nd order relative to 1st order. We used a noise masking approach to compare the efficiency of orientation integration for the 1st and 2nd order. We find a significant deficit for 2nd order detection at both the local and global level, however the small size of this effect stands in stark contrast against previous results from contour-integration experiments, which are almost impossible with 2nd order stimuli.

Decision-related activity in sensory neurons may depend on the columnar architecture of cerebral cortex

Many studies have reported correlations between the activity of sensory neurons and animals' judgments in discrimination tasks. Here, we suggest that such neuron-behavior correlations may require a cortical map for the task relevant features. This would explain why studies using discrimination tasks based on disparity in area V1 have not found these correlations: V1 contains no map for disparity. This scheme predicts that activity of V1 neurons correlates with decisions in an orientation-discrimination task. To test this prediction, we trained two macaque monkeys in a coarse orientation discrimination task using band-pass-filtered dynamic noise. The two orientations were always 90° apart and task difficulty was controlled by varying the orientation bandwidth of the filter. While the trained animals performed this task, we recorded from orientation-selective V1 neurons (n = 82, n = 31 for Monkey 1, n = 51 for Monkey 2). For both monkeys, we observed significant correlation (quantified as "choice probabilities") of the V1 activity with the monkeys' perceptual judgments (mean choice probability 0.54, p = 10(-5)). In one of these animals, we had previously measured choice probabilities in a disparity discrimination task in V1, which had been at chance (0.49, not significantly different from 0.5). The choice probabilities in this monkey for the orientation discrimination task were significantly larger than those for the disparity discrimination task (p = 0.032). These results are predicted by our suggestion that choice probabilities are only observed for cortical sensory neurons that are organized in maps for the task-relevant feature.

Age-related changes in fine motion direction discriminations

The present study used an equivalent noise method to characterize the sources of reduced performance in fine discrimination of motion with age. We varied the density of the displays, the speed and speed variability and the temporal correlation of dots' motion in successive frames to assess their effect on the sensitivity to motion direction. The results showed that, in all experimental conditions, the older observers had higher levels of internal noise. Both age groups used the stimulus information less efficiently at slow speed and most efficiently when the moving elements were uncorrelated across frames. The older observers were less efficient than the younger observers in all conditions except at high speed where the efficiency of the two age groups was the same. We fitted two biologically plausible models to the experimental data: a modified version of the local-to-global direction encoding model (Dakin et al. in Vis Res 45:3027-3049, 2005) and a model for pooling of motion information in medial temporal area (MT) where the neuronal responses were correlated (Huang and Lisberger in J Neurophysiol 101:3012-3030, 2009). The modeling results indicate that the correlation in neuronal responses is essential to characterize the influence of speed and speed variability on the sensitivity to direction information. For the younger observers, a single set of parameters can account for the effect of noise and the spatio-temporal parameters of the stimuli, while, for the older observers, a change in the correlation of neuronal activity and the directional tuning bandwidth with the levels of external noise is needed. The findings are discussed with respect to optimal use of the dynamic information to overcome the negative effect of aging.

Global processing of orientation in amblyopia

We set out to determine whether extra-striate ventral stream function was compromised in amblyopia and to compare any observed deficit with previous data on comparable dorsal stream function. We devised a multi-element orientation task where orientation coherence sensitivity could be measured in a comparable way to motion coherence. The use of spatial frequency narrowband elements allowed for accurate correction of any upstream contrast sensitivity influence and ensured that the orientation bandwidth of our elements did not covary with the measured coherence. Using a standard equivalent noise analysis, we varied both the local orientation bandwidth of individual elements as well as the global orientation bandwidth of the element array to obtain estimates of both local and global internal noise and efficiency. The results show that for this ventral stream task there is only a subtle amblyopic deficit in processing global orientation relative to control observers. This deficit is present for both amblyopic and fixing eyes, and appears to reflect poorer efficiency in processing local orientation, suggesting a subtle deficit at the input stage to extra-striate cortex where orientation coherence is processed.

Advances in color science: from retina to behavior

Color has become a premier model system for understanding how information is processed by neural circuits, and for investigating the relationships among genes, neural circuits, and perception. Both the physical stimulus for color and the perceptual output experienced as color are quite well characterized, but the neural mechanisms that underlie the transformation from stimulus to perception are incompletely understood. The past several years have seen important scientific and technical advances that are changing our understanding of these mechanisms. Here, and in the accompanying minisymposium, we review the latest findings and hypotheses regarding color computations in the retina, primary visual cortex, and higher-order visual areas, focusing on non-human primates, a model of human color vision.

Evaluation of objective uncertainty in the visual system

The role of sensory systems is to provide an organism with information about its environment. Because sensory information is noisy and insufficient to uniquely determine the environment, natural perceptual systems have to cope with systematic uncertainty. The extent of that uncertainty is often crucial to the organism: for instance, in judging the potential threat in a stimulus. Inducing uncertainty by using visual noise, we had human observers perform a task where they could improve their performance by choosing the less uncertain among pairs of visual stimuli. Results show that observers had access to a reliable measure of visual uncertainty in their decision-making, showing that subjective uncertainty in this case is connected to objective uncertainty. Based on a Bayesian model of the task, we discuss plausible computational schemes for that ability.

Most work in vision science focuses on the question of why we perceive what we do, and we now have many models explaining what physical properties of a stimulus make us see depth, colour, etc. Here we ask instead what makes us feel confident in our visual perception: in the context of a visual task, what are the physical properties of the stimulus that will make us think we are doing the task well? The mathematical framework of Bayesian statistics provides an elegant way to frame the problem, by assuming that the visual system is trying to estimate physical properties of the world from incomplete, sometimes unreliable visual information. Objective uncertainty will therefore depend on the quality of the information available in the stimulus. In our experiments we compare objective uncertainty—as computed using the Bayesian framework—with subjective uncertainty, the confidence observers report about their visual percepts. To this end, we use a visual task with well-defined statistical properties, discrimination under noise. We report a surprising degree of agreement between objective and subjective uncertainty, and discuss possible computational models that could explain this ability of the visual system.

Contrast adaptation contributes to contrast-invariance of orientation tuning of primate V1 cells

Background

Studies in rodents and carnivores have shown that orientation tuning width of single neurons does not change when stimulus contrast is modified. However, in these studies, stimuli were presented for a relatively long duration (e. g., 4 seconds), making it possible that contrast adaptation contributed to contrast-invariance of orientation tuning. Our first purpose was to determine, in marmoset area V1, whether orientation tuning is still contrast-invariant with the stimulation duration is comparable to that of a visual fixation.

Methodology/Principal Findings

We performed extracellular recordings and examined orientation tuning of single-units using static sine-wave gratings that were flashed for 200 msec. Sixteen orientations and three contrast levels, representing low, medium and high values in the range of effective contrasts for each neuron, were randomly intermixed. Contrast adaptation being a slow phenomenon, cells did not have enough time to adapt to each contrast individually. With this stimulation protocol, we found that the tuning width obtained at intermediate contrast was reduced to 89% (median), and that at low contrast to 76%, of that obtained at high contrast. Therefore, when probed with briefly flashed stimuli, orientation tuning is not contrast-invariant in marmoset V1. Our second purpose was to determine whether contrast adaptation contributes to contrast-invariance of orientation tuning. Stationary gratings were presented, as previously, for 200 msec with randomly varying orientations, but the contrast was kept constant within stimulation blocks lasting >20 sec, allowing for adaptation to the single contrast in use. In these conditions, tuning widths obtained at low contrast were still significantly less than at high contrast (median 85%). However, tuning widths obtained with medium and high contrast stimuli no longer differed significantly.

Conclusions/Significance

Orientation tuning does not appear to be contrast-invariant when briefly flashed stimuli vary in both contrast and orientation, but contrast adaptation partially restores contrast-invariance of orientation tuning.

Foveal and extra-foveal orientation discrimination

Performance can often be made equal across the visual field by scaling peripherally presented stimuli according to F = 1 + E/E (2) where E (2) is the eccentricity at which stimulus size must double to maintain foveal performance levels. Sally and Gurnsey (Vision Res 43:1375-1385, 2003 and Vision Res 44:2719-2727, 2004) have previously shown that estimates of E (2) for orientation discrimination are significantly larger (i.e., less spatial scaling is required) at stimulus contrasts near detection threshold than at contrasts well above detection threshold. To examine the nature of this effect parametrically we measured orientation discrimination thresholds at 0 degrees and 10 degrees eccentricity for three levels of Michelson contrast (3, 12 and 48%) and three stimulus length-to-width aspect ratios (36.4, 9.1 and 2.3) for a range of line sizes (0.19 degrees -36 degrees visual angle). On average, E (2) values decreased as stimulus contrast decreased, consistent with the previous results of Sally and Gurnsey (Vision Res 43:1375-1385, 2003 and Vision Res 44:2719-2727, 2004). It is proposed that contrast reductions have a proportionally larger effect on small orientation-selective units than large ones and thus produce a greater rightward shift of acuity functions (orientation threshold vs. size) at the fovea than in the periphery. This explains why less spatial scaling is required to equate foveal and peripheral acuity functions at low contrasts than at high contrasts.

Spatial versus temporal grouping in a modified Ternus display

The Ternus display can induce a percept of 'element motion' or 'group motion'. Conventionally, this has been attributed to two different motion processes, with different spatial and temporal ranges. In contrast, recent studies have emphasised spatial and temporal grouping principles as underlying the apparent motion percepts in the Ternus display. The present study explored effects of spatial and temporal grouping on the apparent motion percept in a novel Ternus display of oriented Gabor elements with no inter-frame interval. Each frame of this stimulus could be further divided into 'sub-frames', and the orientation of the carriers was changed across these sub-frames. In four experiments transitions were found between the motion percepts with changes in orientation across time (Experiment 1) and space (Experiment 2), and with a temporal offset in the orientation change of the outer element (Experiment 3) to the extent that group motion was not perceived even with large orientation changes over time that previously led to group motion (Experiment 4). Collectively, these results indicate that while spatial properties have an influence in determining the percept of the Ternus display, temporal properties also have a strong influence, and can override spatial grouping. However, these temporal effects cannot be attributed to spatio-temporal limits of low-level motion processes. Some aspects of the observed spatial grouping effects can be accounted for in terms of a modified association field, which may occur through connectivity of orientation selective units in V1. The temporal effects observed are considered in terms of temporal integration, the transitional value at a temporal offset of 40ms being remarkably similar to psychophysical and neurophysiological estimates of the peak temporal impulse response. These temporal responses could be detected at a higher level in the system, providing a basis for apparent motion perception.