Bi-stable depth ordering of superimposed moving gratings

Prefrontal cortex represents heuristics that shape choice bias and its integration into future behavior

Goal-directed behavior requires integrating sensory information with prior knowledge about the environment. Behavioral biases that arise from these priors could increase positive outcomes when the priors match the true structure of the environment, but mismatches also happen frequently and could cause unfavorable outcomes. Biases that reduce gains and fail to vanish with training indicate fundamental suboptimalities arising from ingrained heuristics of the brain. Here, we report systematic, gain-reducing choice biases in highly trained monkeys performing a motion direction discrimination task where only the current stimulus is behaviorally relevant. The monkey's bias fluctuated at two distinct time scales: slow, spanning tens to hundreds of trials, and fast, arising from choices and outcomes of the most recent trials. Our findings enabled single trial prediction of biases, which influenced the choice especially on trials with weak stimuli. The pre-stimulus activity of neuronal ensembles in the monkey prearcuate gyrus represented these biases as an offset along the decision axis in the state space. This offset persisted throughout the stimulus viewing period, when sensory information was integrated, leading to a biased choice. The pre-stimulus representation of history-dependent bias was functionally indistinguishable from the neural representation of upcoming choice before stimulus onset, validating our model of single-trial biases and suggesting that pre-stimulus representation of choice could be fully defined by biases inferred from behavioral history. Our results indicate that the prearcuate gyrus reflects intrinsic heuristics that compute bias signals, as well as the mechanisms that integrate them into the oculomotor decision-making process.

The conceptual understanding of depth rather than the low-level processing of spatial frequencies drives the corridor illusion

Our objective was to determine how different spatial frequencies affect the perceptual size rescaling of stimuli in the corridor illusion. Two experiments were performed using the method of constant stimuli. In experiment 1, the task required participants to compare the size of comparison and standard rings displayed over the same background image. ANOVA on the points of subject equality (PSEs) revealed that the perceived size of the top and bottom standard rings changed as a function of the availability of the high, medium, and low spatial frequency information. In experiment 2, the task required participants to compare the size of a comparison ring presented outside of the background image with a standard ring presented inside it. ANOVA on the PSEs revealed that the apparent size of the top and not the bottom standard ring changed depending on the availability of medium spatial frequency information. Eye-tracking revealed that the spatial frequency range of the background image in the periphery affected participants' eye positioning, which may explain why the effects of different spatial frequencies fluctuated across experiments. Nonetheless, when we consider these findings together, we propose that the conceptual understanding of depth plays a more important role in explaining the corridor illusion than the low-level processing of depth information extracted from different spatial frequencies along separate channels.

Circular inference in bistable perception

When facing ambiguous images, the brain switches between mutually exclusive interpretations, a phenomenon known as bistable perception. Despite years of research, a consensus on whether bistability is driven primarily by bottom-up or top-down mechanisms has not been achieved. Here, we adopted a Bayesian approach to reconcile these two theories. Fifty-five healthy participants were exposed to an adaptation of the Necker cube paradigm, in which we manipulated sensory evidence and prior knowledge. Manipulations of both sensory evidence and priors significantly affected the way participants perceived the Necker cube. However, we observed an interaction between the effect of the cue and the effect of the instructions, a finding that is incompatible with Bayes-optimal integration. In contrast, the data were well predicted by a circular inference model. In this model, ambiguous sensory evidence is systematically biased in the direction of current expectations, ultimately resulting in a bistable percept.

Two paradigms of bistable plaid motion reveal independent mutual inhibition processes

Perception is sometimes bistable, switching between two possible interpretations. Levelt developed several propositions to explain bistable perception in binocular rivalry, based on a model of competing neural populations connected through reciprocal inhibition. Here we test Levelt's laws with bistable plaid motion. Plaids are typically tristable, either a coherent pattern, transparent with one component in front, or transparent with the opposite depth order. In Experiment 1, we use a large angle between component directions to prevent plaid coherence, limiting the ambiguity to alternations of grating depth order. Similar to increasing contrast in binocular rivalry, increasing component speed led to higher switch rates (analogous to Levelt's fourth proposition). In Experiment 2, we used occlusion cues to prevent one depth order and limit bistability to one transparent depth order alternating with coherence. Increasing grating speed shortened coherent motion periods but left transparent periods largely unchanged (analogous to Levelt's second proposition). Switch dynamics showed no correlation between the experiments. These data suggest that plaid component speed acts like contrast in binocular rivalry to vary switch dynamics through a mutual inhibition model. The lack of correlation between both experiments suggests reciprocal inhibition mediates bistability between a variety of neural populations across the visual system.

Attention model of binocular rivalry

When the corresponding retinal locations in the two eyes are presented with incompatible images, a stable percept gives way to perceptual alternations in which the two images compete for perceptual dominance. As perceptual experience evolves dynamically under constant external inputs, binocular rivalry has been used for studying intrinsic cortical computations and for understanding how the brain regulates competing inputs. Converging behavioral and EEG results have shown that binocular rivalry and attention are intertwined: binocular rivalry ceases when attention is diverted away from the rivalry stimuli. In addition, the competing image in one eye suppresses the target in the other eye through a pattern of gain changes similar to those induced by attention. These results require a revision of the current computational theories of binocular rivalry, in which the role of attention is ignored. Here, we provide a computational model of binocular rivalry. In the model, competition between two images in rivalry is driven by both attentional modulation and mutual inhibition, which have distinct selectivity (feature vs. eye of origin) and dynamics (relatively slow vs. relatively fast). The proposed model explains a wide range of phenomena reported in rivalry, including the three hallmarks: (i) binocular rivalry requires attention; (ii) various perceptual states emerge when the two images are swapped between the eyes multiple times per second; (iii) the dominance duration as a function of input strength follows Levelt's propositions. With a bifurcation analysis, we identified the parameter space in which the model's behavior was consistent with experimental results.

Cortical activation associated with determination of depth order during transparent motion perception: A normalized integrative fMRI-MEG study

When visual patterns drifting in different directions and/or at different speeds are superimposed on the same plane, observers perceive transparent surfaces on planes of different depths. This phenomenon is known as transparent motion perception. In this study, cortical activities were measured using functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) to reveal the cortical dynamics associated with determination of depth order during transparent motion perception. In addition, offline eye movement measurements were performed to determine the latencies of the start of both pursuit eye movements and depth attention that are important in determination of the depth order. MEG and fMRI data were analyzed by a normalized integrative fMRI-MEG method that enables reconstruction of time-varying dipole moments of activated regions from MEG signals. Statistical analysis of fMRI data was performed to identify activated regions. The activated regions were used as spatial constraints for the reconstruction using the integrative fMRI-MEG method. We focused on the period between latencies (216-405 ms) determined by eye movement experiment, which are related to determination of the depth order. The results of integrative analysis revealed that significant neural activities were observed in the visual association area, the human middle temporal area, the intraparietal sulcus, the lateral occipital cortex, and the anterior cingulate cortex between 216 and 405 ms. These results suggest that initial eye movement and accompanying cortical activations during focused duration play an important role in determining the depth order during transparent motion perception.

The initial phase of auditory and visual scene analysis

Auditory streaming and visual plaids have been used extensively to study perceptual organization in each modality. Both stimuli can produce bistable alternations between grouped (one object) and split (two objects) interpretations. They also share two peculiar features: (i) at the onset of stimulus presentation, organization starts with a systematic bias towards the grouped interpretation; (ii) this first percept has 'inertia'; it lasts longer than the subsequent ones. As a result, the probability of forming different objects builds up over time, a landmark of both behavioural and neurophysiological data on auditory streaming. Here we show that first percept bias and inertia are independent. In plaid perception, inertia is due to a depth ordering ambiguity in the transparent (split) interpretation that makes plaid perception tristable rather than bistable: experimental manipulations removing the depth ambiguity suppressed inertia. However, the first percept bias persisted. We attempted a similar manipulation for auditory streaming by introducing level differences between streams, to bias which stream would appear in the perceptual foreground. Here both inertia and first percept bias persisted. We thus argue that the critical common feature of the onset of perceptual organization is the grouping bias, which may be related to the transition from temporally/spatially local to temporally/spatially global computation.

Relative luminance and binocular disparity preferences are correlated in macaque primary visual cortex, matching natural scene statistics

Humans excel at inferring information about 3D scenes from their 2D images projected on the retinas, using a wide range of depth cues. One example of such inference is the tendency for observers to perceive lighter image regions as closer. This psychophysical behavior could have an ecological basis because nearer regions tend to be lighter in natural 3D scenes. Here, we show that an analogous association exists between the relative luminance and binocular disparity preferences of neurons in macaque primary visual cortex. The joint coding of relative luminance and binocular disparity at the neuronal population level may be an integral part of the neural mechanisms for perceptual inference of depth from images.

Bayesian sampling in visual perception

It is well-established that some aspects of perception and action can be understood as probabilistic inferences over underlying probability distributions. In some situations, it would be advantageous for the nervous system to sample interpretations from a probability distribution rather than commit to a particular interpretation. In this study, we asked whether visual percepts correspond to samples from the probability distribution over image interpretations, a form of sampling that we refer to as Bayesian sampling. To test this idea, we manipulated pairs of sensory cues in a bistable display consisting of two superimposed moving drifting gratings, and we asked subjects to report their perceived changes in depth ordering. We report that the fractions of dominance of each percept follow the multiplicative rule predicted by Bayesian sampling. Furthermore, we show that attractor neural networks can sample probability distributions if input currents add linearly and encode probability distributions with probabilistic population codes.

Alternation rate in perceptual bistability is maximal at and symmetric around equi-dominance

When an ambiguous stimulus is viewed for a prolonged time, perception alternates between the different possible interpretations of the stimulus. The alternations seem haphazard, but closer inspection of their dynamics reveals systematic properties in many bistable phenomena. Parametric manipulations result in gradual changes in the fraction of time a given interpretation dominates perception, often over the entire possible range of zero to one. The mean dominance durations of the competing interpretations can also vary over wide ranges (from less than a second to dozens of seconds or more), but finding systematic relations in how they vary has proven difficult. Following the pioneering work of W. J. M. Levelt (1968) in binocular rivalry, previous studies have sought to formulate a relation in terms of the effect of physical parameters of the stimulus, such as image contrast in binocular rivalry. However, the link between external parameters and "stimulus strength" is not as obvious for other bistable phenomena. Here we show that systematic relations readily emerge when the mean dominance durations are examined instead as a function of "percept strength," as measured by the fraction of dominance time, and provide theoretical rationale for this observation. For three different bistable phenomena, plotting the mean dominance durations of the two percepts against the fraction of dominance time resulted in complementary curves with near-perfect symmetry around equi-dominance (the point where each percept dominates half the time). As a consequence, the alternation rate reaches a maximum at equi-dominance. We next show that the observed behavior arises naturally in simple double-well energy models and in neural competition models with cross-inhibition and input normalization. Finally, we discuss the possibility that bistable perceptual switches reflect a perceptual "exploratory" strategy, akin to foraging behavior, which leads naturally to maximal alternation rate at equi-dominance if perceptual switches come with a cost.

Balance between noise and adaptation in competition models of perceptual bistability

Perceptual bistability occurs when a physical stimulus gives rise to two distinct interpretations that alternate irregularly. Noise and adaptation processes are two possible mechanisms for switching in neuronal competition models that describe the alternating behaviors. Either of these processes, if strong enough, could alone cause the alternations in dominance. We examined their relative role in producing alternations by studying models where by smoothly varying the parameters, one can change the rhythmogenesis mechanism from being adaptation-driven to noise-driven. In consideration of the experimental constraints on the statistics of the alternations (mean and shape of the dominance duration distribution and correlations between successive durations) we ask whether we can rule out one of the mechanisms. We conclude that in order to comply with the observed mean of the dominance durations and their coefficient of variation, the models must operate within a balance between the noise and adaptation strength-both mechanisms are involved in producing alternations, in such a way that the system operates near the boundary between being adaptation-driven and noise-driven.