The normal variability in alertness we experience in daily tasks is rarely taking into account in cognitive neuroscience. Here we studied neurobehavioral dynamics of cognitive control with decreasing alertness. We used the classic Simon Task where participants hear the word "left" or "right" in the right or left ear, eliciting slower responses when the word and the side are incongruent -the conflict effect. Participants performed the task both while fully awake and while getting drowsy, allowing for the characterisation of alertness modulating cognitive control. The changes in the neural signatures of conflict from local theta oscillations to a longdistance distributed theta network suggests a reconfiguration of the underlying neural processes subserving cognitive control when affected by alertness fluctuations.
We report the results of an academic survey into the theoretical and methodological foundations, common assumptions and the current state of the field of consciousness science. The survey consisted of 22 questions, was distributed online and at two different occasions of the annual meeting of the Association of the Scientific Study of Consciousness (ASSC, 2018 and 2019), targeting active scientists in the field only. We examined responses from 232 consciousness scientists with different backgrounds (e.g., philosophy, neuroscience, psychology, computer science) and at various stages of their careers (e.g., junior/senior faculty, graduate/undergraduate students). The results reveal that while respondents answer related questions quite consistently, there remains considerable discussion and debate between researchers about the definition of consciousness and the way it should be studied. To highlight a few observations, a majority of respondents believe that machines could have consciousness, that consciousness is a gradual phenomenon in the animal kingdom and that unconscious processing is extensive, encompassing both low-level as well as high-level cognitive functions. Further, we show which theories of consciousness are currently considered most promising and how supposedly different theories cluster together, which dependent measures are best used to index the presence or absence of consciousness, and which neural measures are the most likely signatures of consciousness. These findings provide us with a snapshot of the current, dominant views of professional researchers in the field and therefore may help to prioritise research and theoretical approaches to foster progress.
We report the results of an academic survey into the theoretical and methodological foundations, common assumptions, and the current state of the field of consciousness research. The survey consisted of 22 questions and was distributed on two different occasions of the annual meeting of the Association of the Scientific Study of Consciousness (2018 and 2019). We examined responses from 166 consciousness researchers with different backgrounds (e.g. philosophy, neuroscience, psychology, and computer science) and at various stages of their careers (e.g. junior/senior faculty and graduate/undergraduate students). The results reveal that there remains considerable discussion and debate between the surveyed researchers about the definition of consciousness and the way it should be studied. To highlight a few observations, a majority of respondents believe that machines could have consciousness, that consciousness is a gradual phenomenon in the animal kingdom, and that unconscious processing is extensive, encompassing both low-level and high-level cognitive functions. Further, we show which theories of consciousness are currently considered most promising by respondents and how supposedly different theories cluster together, which dependent measures are considered best to index the presence or absence of consciousness, and which neural measures are thought to be the most likely signatures of consciousness. These findings provide us with a snapshot of the current views of researchers in the field and may therefore help prioritize research and theoretical approaches to foster progress.
In the search for the neural basis of conscious experience, perception and its cognitive consequences are typically confounded as neural activity is recorded while participants explicitly report what they experience. Here we present a novel way to disentangle perception from report using eye-movement analysis techniques based on convolutional neural networks and neurodynamical analyses based on information theory. We use a visual bistable stimulus that instantiates two well-known properties of conscious perception: integration and differentiation. At any given moment, observers either experience the stimulus as one integrated unitary percept or as two differentiated objects that are clearly distinct from each other. Using electroencephalography, we show that measures of neural information dynamics of directed information integration and differentiation closely follow participants experience when perceptual transitions were reported. We observed increased directed information from anterior to posterior electrodes (front to back) leading up to the moment the stimulus was reported to switch to the integrated percept and higher information differentiation of anterior signals leading up to reporting the differentiated percept. Crucially, neural integration dynamics were closely linked to perception and even observed in a no-report condition when perceptual transitions were inferred from eye-movements. In contrast, the link between perceptual transitions and neural differentiation was observed solely in the active report condition. Our results therefore suggest a differential role of anterior-posterior network communication vs anterior information differentiation during perception and reporting: while front to back directed information is associated with changes in the content of perception, frontal information differentiation reflects cognitive processes that are consequential of perceptual transitions, not perception per se.
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