Visual perception of ambiguous figures: synchronization based neural models

Bistable perception: neural bases and usefulness in psychological research

Bistable images have the possibility of being perceived in two different ways. Due to their physical characteristics, these visual stimuli allow two different perceptions, associated with top-down and bottom-up modulating processes. Based on an extensive literature review, the present article aims to gather the conceptual models and the foundations of perceptual bistability. This theoretical article compiles not only notions that are intertwined with the understanding of this perceptual phenomenon, but also the diverse classification and uses of bistable images in psychological research, along with a detailed explanation of the neural correlates that are involved in perceptual reversibility. We conclude that the use of bistable images as a paradigmatic resource in psychological research might be extensive. In addition, due to their characteristics, visual bistable stimuli have the potential to be implemented as a resource in experimental tasks that seek to understand diverse concerns linked essentially to attention, sensory, perceptual and memory processes.

Stimulus Pauses and Perturbations Differentially Delay or Promote the Segregation of Auditory Objects: Psychoacoustics and Modeling

Segregating distinct sound sources is fundamental for auditory perception, as in the cocktail party problem. In a process called the build-up of stream segregation, distinct sound sources that are perceptually integrated initially can be segregated into separate streams after several seconds. Previous research concluded that abrupt changes in the incoming sounds during build-up—for example, a step change in location, loudness or timing—reset the percept to integrated. Following this reset, the multisecond build-up process begins again. Neurophysiological recordings in auditory cortex (A1) show fast (subsecond) adaptation, but unified mechanistic explanations for the bias toward integration, multisecond build-up and resets remain elusive. Combining psychoacoustics and modeling, we show that initial unadapted A1 responses bias integration, that the slowness of build-up arises naturally from competition downstream, and that recovery of adaptation can explain resets. An early bias toward integrated perceptual interpretations arising from primary cortical stages that encode low-level features and feed into competition downstream could also explain similar phenomena in vision. Further, we report a previously overlooked class of perturbations that promote segregation rather than integration. Our results challenge current understanding for perturbation effects on the emergence of sound source segregation, leading to a new hypothesis for differential processing downstream of A1. Transient perturbations can momentarily redirect A1 responses as input to downstream competition units that favor segregation.

The 'laws' of binocular rivalry: 50 years of Levelt's propositions

It has been fifty years since Levelt's monograph On Binocular Rivalry (1965) was published, but its four propositions that describe the relation between stimulus strength and the phenomenology of binocular rivalry remain a benchmark for theorists and experimentalists even today. In this review, we will revisit the original conception of the four propositions and the scientific landscape in which this happened. We will also provide a brief update concerning distributions of dominance durations, another aspect of Levelt's monograph that has maintained a prominent presence in the field. In a critical evaluation of Levelt's propositions against current knowledge of binocular rivalry we will then demonstrate that the original propositions are not completely compatible with what is known today, but that they can, in a straightforward way, be modified to encapsulate the progress that has been made over the past fifty years. The resulting modified, propositions are shown to apply to a broad range of bistable perceptual phenomena, not just binocular rivalry, and they allow important inferences about the underlying neural systems. We argue that these inferences reflect canonical neural properties that play a role in visual perception in general, and we discuss ways in which future research can build on the work reviewed here to attain a better understanding of these properties.

Simulating bistable perception with interrupted ambiguous stimulus using self-oscillator dynamics with percept choice bifurcation

A behavioral stochastic self-oscillator model is used for simulating interrupted ambiguous stimulus-induced percept reversals. The results provide further support for a dynamical systems foundation of cognitive and psychological problems as discussed in detail within the context of Gestalt psychology by Wagemans et al. (Concept Theor Found Psychol Bull 138(6):1218-1252, 2012), and for coordination dynamics of the brain (Kelso in Philos Trans R Soc B 367:906-918, 2012). Statistical evaluation of simulated reversal time series predicts a maximum of the percept reversal rate that conforms with a number of results in the literature. The macroscopic model is based on two inhibitorily coupled sets of three coupled nonlinear equations, one triplet for each percept. The derivation of our specific dynamics equations is based on a drastically simplified field theoretical approach using well-known phase synchronization for explaining brain dynamics on the macroscopic EEG level. The degree of coherence (contrast μ, 0 ≤ μ ≤ 1) of the superimposed fields required for onset of bistable dynamics is related to a phase synchronization index of EEG fields, and it is used in the present context as ambiguity control parameter. For quantitative agreement with the experimental data, the addition of a stochastic Langevin force term in the attention equation proved essential. Formal analysis leads to a quantification of well-known "cognitive inertia" and supports the interplay between percept choice (bifurcation) dynamics during stimulus onset and adaptive gain (attention fatigue) driven quasiperiodic percept reversals.

Critical slowing down and noise-induced intermittency in bistable perception: bifurcation analysis

Stochastic dynamics and critical slowing down were studied experimentally and numerically near the onset of dynamical bistability in visual perception under the influence of noise. Exploring the Necker cube as the essential example of an ambiguous figure, and using its wire contrast as a control parameter, we measured dynamical hysteresis in two coexisting percepts as a function of both the velocity of the parameter change and the background luminance. The bifurcation analysis allowed us to estimate the level of cognitive noise inherent to brain neural cells activity, which induced intermittent switches between different perception states. The results of numerical simulations with a simple energy model are in good qualitative agreement with psychological experiments.

Bifurcation study of a neural field competition model with an application to perceptual switching in motion integration

Perceptual multistability is a phenomenon in which alternate interpretations of a fixed stimulus are perceived intermittently. Although correlates between activity in specific cortical areas and perception have been found, the complex patterns of activity and the underlying mechanisms that gate multistable perception are little understood. Here, we present a neural field competition model in which competing states are represented in a continuous feature space. Bifurcation analysis is used to describe the different types of complex spatio-temporal dynamics produced by the model in terms of several parameters and for different inputs. The dynamics of the model was then compared to human perception investigated psychophysically during long presentations of an ambiguous, multistable motion pattern known as the barberpole illusion. In order to do this, the model is operated in a parameter range where known physiological response properties are reproduced whilst also working close to bifurcation. The model accounts for characteristic behaviour from the psychophysical experiments in terms of the type of switching observed and changes in the rate of switching with respect to contrast. In this way, the modelling study sheds light on the underlying mechanisms that drive perceptual switching in different contrast regimes. The general approach presented is applicable to a broad range of perceptual competition problems in which spatial interactions play a role.

Generation of slow phase-locked oscillation and variability of the interspike intervals in globally coupled neuronal oscillators

To elucidate how a biological rhythm is regulated, the extended (three-dimensional) Bonhoeffer-van der Pol or FitzHugh-Nagumo equations are employed to investigate the dynamics of a population of neuronal oscillators globally coupled through a common buffer (mean field). Interesting phenomena, such as extraordinarily slow phase-locked oscillations (compared to the natural period of each neuronal oscillator) and the death of all oscillations, are observed. We demonstrate that the slow synchronization is due mainly to the existence of "fast" oscillators. Additionally, we examine the effect of noise on the synchronization and variability of the interspike intervals. Peculiar phenomena, such as noise-induced acceleration and deceleration, are observed. The results herein suggest that very small noise may significantly influence a biological rhythm.

Spiking neural network model for memorizing sequences with forward and backward recall

We present an oscillatory network of conductance based spiking neurons of Hodgkin-Huxley type as a model of memory storage and retrieval of sequences of events (or objects). The model is inspired by psychological and neurobiological evidence on sequential memories. The building block of the model is an oscillatory module which contains excitatory and inhibitory neurons with all-to-all connections. The connection architecture comprises two layers. A lower layer represents consecutive events during their storage and recall. This layer is composed of oscillatory modules. Plastic excitatory connections between the modules are implemented using an STDP type learning rule for sequential storage. Excitatory neurons in the upper layer project star-like modifiable connections toward the excitatory lower layer neurons. These neurons in the upper layer are used to tag sequences of events represented in the lower layer. Computer simulations demonstrate good performance of the model including difficult cases when different sequences contain overlapping events. We show that the model with STDP type or anti-STDP type learning rules can be applied for the simulation of forward and backward replay of neural spikes respectively.

Theta-alpha cross-frequency synchronization facilitates working memory control - a modeling study

Despite decades of research, the neural mechanism of central executive and working memory is still unclear. In this paper, we propose a new neural network model for the real-time control of working memory. The key idea is to consider separately the role of neural activation from that of oscillatory phase. Neural populations encoding different information would not confuse each other when the populations have different oscillatory phases. Depending on the current situation, relevant memories bind together through phase-locking between theta-frequency oscillation of a Central Unit and alpha-frequency oscillations of the relevant group of Memory Units. The Central Unit dynamically controls which Memory Units should be synchronized (and the encoded memory would be processed), and which units should be out of phase (the encoded memory is standby and would not be processed yet). Simulations of two working memory tasks are provided as examples. The model is in agreement with many recent experimental results of human scalp EEG analysis, which reported observations of neural synchronization and cross-frequency coupling during working memory tasks. This model offers a possible explanation of the underlying mechanism for these experiments.

Role of mutual inhibition in binocular rivalry

Binocular rivalry is a phenomenon that occurs when a different image is presented to each eye. The observer generally perceives just one image at a time, with perceptual switches occurring every few seconds. A natural assumption is that this perceptual mutual exclusivity is achieved via mutual inhibition between populations of neurons that encode for either percept. Theoretical models that incorporate mutual inhibition have been largely successful at capturing experimental features of rivalry, including Levelt's propositions, which characterize perceptual dominance durations as a function of image contrasts. However, basic mutual inhibition models do not fully comply with Levelt's fourth proposition, which states that percepts alternate faster as the stimulus contrasts to both eyes are increased simultaneously. This theory-experiment discrepancy has been taken as evidence against the role of mutual inhibition for binocular rivalry. Here, we show how various biophysically plausible modifications to mutual inhibition models can resolve this problem.

Ambiguous figures and binding: EEG frequency modulations during multistable perception

Ambiguous figures induce sudden transitions between rivaling percepts. We investigated electroencephalogram frequency modulations of accompanying change-related de- and rebinding processes. Presenting the stimuli discontinously, we synchronized perceptual reversals with stimulus onset, which served as a time reference for averaging. The resultant gain in temporal resolution revealed a sequence of time-frequency correlates of the reversal process. Most conspicuous was a transient right-hemispheric gamma modulation preceding endogenous reversals by at least 200 ms. No such modulation occurred with exogenously induced reversals of unambiguous stimulus variants. Post-onset components were delayed for ambiguous compared to unambiguous stimuli. The time course of oscillatory activity differed in several respects from predictions based on binding-related hypotheses. The gamma modulation preceding endogenous reversals may indicate an unstable brain state, ready to switch.

Stochastic variations in sensory awareness are driven by noisy neuronal adaptation: evidence from serial correlations in perceptual bistability

When the sensory system is subjected to ambiguous input, perception alternates between interpretations in a seemingly random fashion. Although neuronal noise obviously plays a role, the neural mechanism for the generation of randomness at the slow time scale of the percept durations (multiple seconds) is unresolved. Here significant nonzero serial correlations are reported in series of visual percept durations (to the author's knowledge for the first time accounting for duration impurities caused by reaction time, drift, and incomplete percepts). Serial correlations for perceptual rivalry using structure-from-motion ambiguity were smaller than for binocular rivalry using orthogonal gratings. A spectrum of computational models is considered, and it is concluded that noise in adaptation of percept-related neurons causes the serial correlations. This work bridges, in a physiologically plausible way, widely appreciated deterministic modeling and randomness in experimental observations of visual rivalry.