Adversarial testing of global neuronal workspace and integrated information theories of consciousness.

Different theories explain how subjective experience arises from brain activity. These theories have independently accrued evidence, but have not been directly compared. Here we present an open science adversarial collaboration directly juxtaposing integrated information theory (IIT) and global neuronal workspace theory (GNWT) via a theory-neutral consortium.

Statistical learning of target and distractor spatial probability shape a common attentional priority computation.

Converging evidence recently put forward the notion that dedicated neurocognitive mechanisms do exist for the suppression of salient, but irrelevant distractors. Along this line, it is plausible to hypothesize that, in appropriate contexts, experience-dependent forms of attentional learning might selectively induce plastic changes within this dedicated circuitry, thus allowing an independent shaping of priorities at the service of attentional filtering. Conversely, previous work suggested that statistical learning (SL) of both target and distractor spatial probability distributions converge in adjusting only the overall attentional priority of locations: in fact, in the presence of an independent manipulation, either related to the target or to the distractor only, SL induces indirect effects (e.

Prefrontal cortex oscillations update and stabilize consciousness during binocular rivalry.

In this issue of Neuron, Dwarakanath et al. demonstrate that perceptual changes in binocular rivalry are predicted by low-frequency activity and beta-band oscillations in the prefrontal cortex, speaking to access consciousness being gated by oscillatory neuronal dynamics in the prefrontal cortex.

Statistical Learning of Distractor Suppression Downregulates Prestimulus Neural Excitability in Early Visual Cortex.

Visual attention is highly influenced by past experiences. Recent behavioral research has shown that expectations about the spatial location of distractors within a search array are implicitly learned, with expected distractors becoming less interfering. Little is known about the neural mechanism supporting this form of statistical learning.

An adversarial collaboration protocol for testing contrasting predictions of global neuronal workspace and integrated information theory.

The relationship between conscious experience and brain activity has intrigued scientists and philosophers for centuries. In the last decades, several theories have suggested different accounts for these relationships. These theories have developed in parallel, with little to no cross-talk among them.

FLUX: A pipeline for MEG analysis.

Magnetoencephalography (MEG) allows for quantifying modulations of human neuronal activity on a millisecond time scale while also making it possible to estimate the location of the underlying neuronal sources. The technique relies heavily on signal processing and source modelling. To this end, there are several open-source toolboxes developed by the community.

Body-Space Interactions: Same Spatial Encoding but Different Influence of Valence for Reaching and Defensive Purposes.

The space around our body, the so-called peripersonal space, is where interactions with nearby objects may occur. "Defensive space" and "Reaching space", respectively, refer to two opposite poles of interaction between our body and the external environment: protecting the body and performing a goal-directed action. Here, we hypothesized that mechanisms underlying these two action spaces are differentially modulated by the valence of visual stimuli, as stimuli with negative valence are more likely to activate protective actions whereas stimuli with positive valence may activate approaching actions.

Modulating the influence of recent trial history on attentional capture via transcranial magnetic stimulation (TMS) of right TPJ.

In visual search, salient yet task-irrelevant distractors in the stimulus array interfere with target selection. This is due to the unwanted shift of attention towards the salient stimulus-the so-called attentional capture effect, which delays deployment of attention onto the target. Although powerful and automatic, attentional capture by a salient distractor is nonetheless antagonized by distractor-filtering mechanisms and is further modulated by cross-trial contingencies: The distractor cost is typically more robust when no distraction has been experienced in the immediate past, compared to when a distractor was present on the immediately preceding trial.

Probing the Neural Mechanisms for Distractor Filtering and Their History-Contingent Modulation by Means of TMS.

In visual search, the presence of a salient, yet task-irrelevant, distractor in the stimulus array interferes with target selection and slows down performance. Neuroimaging data point to a key role of the frontoparietal dorsal attention network in dealing with visual distractors; however, the respective roles of different nodes within the network and their hemispheric specialization are still unresolved. Here, we used transcranial magnetic stimulation (TMS) to evaluate the causal role of two key regions of the dorsal attention network in resisting attentional capture by a salient singleton distractor: the frontal eye field (FEF) and the cortex within the intraparietal sulcus (IPS).

Altering spatial priority maps via statistical learning of target selection and distractor filtering.

The cognitive system has the capacity to learn and make use of environmental regularities - known as statistical learning (SL), including for the implicit guidance of attention. For instance, it is known that attentional selection is biased according to the spatial probability of targets; similarly, changes in distractor filtering can be triggered by the unequal spatial distribution of distractors. Open questions remain regarding the cognitive/neuronal mechanisms underlying SL of target selection and distractor filtering.