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Ferrante, O.

Publications and source records attributed to Ferrante, O..

3 recordsLinked to original sources

Predictive distractor processing relies on integrated proactive and reactive attentional mechanisms

Visual attention is shaped by statistical regularities in the environment, with spatially predictable distractors being proactively suppressed. The neural mechanisms underpinning this suppression remain poorly understood. In this study, we employed magnetoencephalography (MEG) and multivariate decoding analysis to investigate how predicted distractor locations are proactively processed in the human brain. Male and female human participants engaged in a statistical learning visual search task that required them to identify a target stimulus while ignoring a colour-singleton distractor. Critically, the distractor appeared more frequently on one side of the visual field, creating an implicit spatial prediction. Our results revealed that distractor locations were encoded in temporo-occipital brain regions prior to the presentation of the search array, supporting the hypothesis that proactive suppression guides visual attention away from predictable distractors. The neural activity patterns corresponding to this pre-search distractor processing extended to post-search activity during late attentional stages ([~]200 ms), suggesting an integrated suppressive mechanism. Notably, this generalization from pre- to post- search phases was absent in the early sensory processing stages ([~]100 ms), suggesting that post-search distractor processing is not merely a continuation of sustained proactive processing, but involves re-engagement of the same mechanism at distinct stages. These findings establish a mechanistic link between proactive and reactive processing of predictable distractors, demonstrating both shared and unique contributions to attentional selection.

neuroscience↗

An adversarial collaboration to critically evaluate theories of consciousness

Different theories explain how subjective experience arises from brain activity1,2. These theories have independently accrued evidence, yet, confirmation bias and dependence on design choices hamper progress in the field3. Here, we present an open science adversarial collaboration which directly juxtaposes Integrated Information Theory (IIT)4,5 and Global Neuronal Workspace Theory (GNWT)6-10, employing a theory-neutral consortium approach11,12. We investigate neural correlates of the content and duration of visual experience. The theory proponents and the consortium developed and preregistered the experimental design, divergent predictions, expected outcomes, and their interpretation12. 256 human subjects viewed suprathreshold stimuli for variable durations while neural activity was measured with functional magnetic resonance imaging, magnetoencephalography, and electrocorticography. We find information about conscious content in visual, ventro-temporal and inferior frontal cortex, with sustained responses in occipital and lateral temporal cortex reflecting stimulus duration, and content-specific synchronization between frontal and early visual areas. These results confirm some predictions of IIT and GNWT, while substantially challenging both theories: for IIT, a lack of sustained synchronization within posterior cortex contradicts the claim that network connectivity specifies consciousness. GNWT is challenged by the general lack of ignition at stimulus offset and limited representation of certain conscious dimensions in prefrontal cortex. Beyond challenging the theories themselves, we present an alternative approach to advance cognitive neuroscience through a principled, theory-driven, collaborative effort. We highlight the challenges to change peoples mind 13 and the need for a quantitative framework integrating evidence for systematic theory testing and building.

neuroscience↗

Statistical Learning of Distractor Suppression Down-regulates Pre-Stimulus 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. Here we used magnetoencephalography (MEG) to measure human brain activity to test whether proactive mechanisms are involved in the statistical learning of distractor locations. Specifically, we used a new technique called rapid invisible frequency tagging (RIFT) to assess neural excitability in early visual cortex during statistical learning of distractor suppression, while concurrently investigating the modulation of posterior alpha-band activity (8-12 Hz). Male and female human participants performed a visual search task in which a target was occasionally presented alongside a color-singleton distractor. Unbeknown to the participants, the distracting stimuli were presented with different probabilities across the two hemifields. RIFT analysis showed that early visual cortex exhibited reduced neural excitability in the pre-stimulus interval at retinotopic locations associated with higher distractor probabilities. In contrast, we did not find any evidence of expectation-driven distractor suppression in alpha-band activity. These findings indicate that proactive mechanisms of attention are involved in predictive distractor suppression and that these mechanisms are associated with altered neural excitability in early visual cortex. Moreover, our findings indicate that RIFT and alpha-band activity might subtend different and possibly independent attentional mechanisms.

neuroscience↗