Introduction to research topic – binocular rivalry: a gateway to studying consciousness

In 1593, Neapolitan polymath Giambattista della Porta publicly lamented that he was unable to improve his impressive productivity (he had published in areas as diverse as cryptography, hydraulics, pharmacology, optics, and classic fiction). Della Porta was trying to read two books simultaneously by placing both volumes side-by-side, and using each eye independently. To his great surprise, his setup allowed him to only read one book at a time. This discovery arguably marks the first written account of binocular rivalry (Wade, 2000) – a perceptual phenomenon that more than 400 years later still both serves to intrigue as well as to illuminate the limits of scientific knowledge. At first glance, binocular rivalry is an oddball. In every day vision, our eyes receive largely matching views of the world. The brain combines the two images into a cohesive scene, and concurrently, perception is stable. However, when showing two very different images (such as two different books) to each eye, the brain resolves the conflict by adopting a “diplomatic” strategy. Rather than mixing the views of the two eyes into an insensible visual percept, observers perceive a dynamically changing series of perceptual snapshots, with one eye’s view dominating for a few seconds before being replaced by its rival from the other eye. With prolonged viewing of a rivalrous stimulus, one inevitably experiences a sequence of subjective perceptual reversals, separated by random time intervals, and this process continues for as long as the sensory conflict is present

Cortical Microcircuit Dynamics Mediating Binocular Rivalry: The Role of Adaptation in Inhibition

Perceptual bistability arises when two conflicting interpretations of an ambiguous stimulus or images in binocular rivalry (BR) compete for perceptual dominance. From a computational point of view, competition models based on cross-inhibition and adaptation have shown that noise is a crucial force for rivalry, and operates in balance with adaptation. In particular, noise-driven transitions and adaptation-driven oscillations define two dynamical regimes and the system explains the observed alternations in perception when it operates near their boundary. In order to gain insights into the microcircuit dynamics mediating spontaneous perceptual alternations, we used a reduced recurrent attractor-based biophysically realistic spiking network, well known for working memory, attention, and decision making, where a spike-frequency adaptation mechanism is implemented to account for perceptual bistability. We thus derived a consistently reduced four-variable population rate model using mean-field techniques, and we tested it on BR data collected from human subjects. Our model accounts for experimental data parameters such as mean time dominance, coefficient of variation, and gamma distribution fit. In addition, we show that our model operates near the bifurcation that separates the noise-driven transitions regime from the adaptation-driven oscillations regime, and agrees with Levelt’s second revised and fourth propositions. These results demonstrate for the first time that a consistent reduction of a biophysically realistic spiking network of leaky integrate-and-fire neurons with spike-frequency adaptation could account for BR. Moreover, we demonstrate that BR can be explained only through the dynamics of competing neuronal pools, without taking into account the adaptation of inhibitory interneurons. However, the adaptation of interneurons affects the optimal parametric space of the system by decreasing the overall adaptation necessary for the bifurcation to occur, and introduces oscillations in the spontaneous state

Desynchronization and rebound of beta oscillations during conscious and unconscious local neuronal processing in the macaque lateral prefrontal cortex

Accumulating evidence indicates that control mechanisms are not tightly bound to conscious perception since both conscious and unconscious information can trigger control processes, probably through the activation of higher-order association areas like the prefrontal cortex. Studying the modulation of control-related prefrontal signals in a microscopic, neuronal level during conscious and unconscious neuronal processing, and under control-free conditions could provide an elementary understanding of these interactions. Here we performed extracellular electrophysiological recordings in the macaque lateral prefrontal cortex (LPFC) during monocular physical alternation (PA) and binocular flash suppression (BFS) and studied the local scale relationship between beta (15–30 Hz) oscillations, a rhythmic signal believed to reflect the current sensory, motor, or cognitive state (status-quo), and conscious or unconscious neuronal processing. First, we show that beta oscillations are observed in the LPFC during resting state. Both PA and BFS had a strong impact on the power of this spontaneous rhythm with the modulation pattern of beta power being identical across these two conditions. Specifically, both perceptual dominance and suppression of local neuronal populations in BFS were accompanied by a transient beta desynchronization followed by beta activity rebound, a pattern also observed when perception occurred without any underlying visual competition in PA. These results indicate that under control-free conditions, at least one rhythmic signal known to reflect control processes in the LPFC (i.e., beta oscillations) is not obstructed by local neuronal, and accordingly perceptual, suppression, thus being independent from temporally co-existing conscious and unconscious local neuronal representations. Future studies could reveal the additive effects of motor or cognitive control demands on prefrontal beta oscillations during conscious and unconscious processing

A common neurodynamical mechanism could mediate externally induced and intrinsically generated transitions in visual awareness

The neural correlates of conscious visual perception are commonly studied in paradigms of perceptual multistability that/nallow multiple perceptual interpretations during unchanged sensory stimulation. What is the source of this multistability in/nthe content of perception? From a theoretical perspective, a fine balance between deterministic and stochastic forces has/nbeen suggested to underlie the spontaneous, intrinsically driven perceptual transitions observed during multistable/nperception. Deterministic forces are represented by adaptation of feature-selective neuronal populations encoding the/ncompeting percepts while stochastic forces are modeled as noise-driven processes. Here, we used a unified neuronal/ncompetition model to study the dynamics of adaptation and noise processes in binocular flash suppression (BFS), a form of/nexternally induced perceptual suppression, and compare it with the dynamics of intrinsically driven alternations in binocular/nrivalry (BR). For the first time, we use electrophysiological, biologically relevant data to constrain a model of perceptual/nrivalry. Specifically, we show that the mean population discharge pattern of a perceptually modulated neuronal population/ndetected in electrophysiological recordings in the lateral prefrontal cortex (LPFC) during BFS, constrains the dynamical/nrange of externally induced perceptual transitions to a region around the bifurcation separating a noise-driven attractor/nregime from an adaptation-driven oscillatory regime. Most interestingly, the dynamical range of intrinsically driven/nperceptual transitions during BR is located in the noise-driven attractor regime, where it overlaps with BFS. Our results/nsuggest that the neurodynamical mechanisms of externally induced and spontaneously generated perceptual alternations/noverlap in a narrow, noise-driven region just before a bifurcation where the system becomes adaptation-driven

Parallel and functionally segregated processing of task phase and conscious content in the prefrontal cortex

Vishal Kapoor et al. identify a population of cells in the lateral prefrontal cortex that exhibits task phase-related activity during a no-report task. This cell population is functionally segregated from the population encoding conscious perception, although the two operate in parallel