Consciousness Arrives Neurophysiological measures in human adults correspond to the transition between very brief, “unnoticeable,” and slightly longer-lived visual stimuli that penetrate deeply enough to leave a conscious imprint that subjects report they can “see.” Kouider et al. (p. 376 ) have performed parallel behavioral and neurophysiological studies in infants to identify a similar neural signal that appears to mark the development of visual consciousness.

Prior expectations shape neural responses in sensory regions of the brain, consistent with a Bayesian predictive coding account of perception. Yet, it remains unclear whether such a mechanism is already functional during early stages of development. To address this issue, we study how the infant brain responds to prediction violations using a cross-modal cueing paradigm. We record electroencephalographic responses to expected and unexpected visual events preceded by auditory cues in 12-month-old infants. We find an increased response for unexpected events. However, this effect of prediction error is only observed during late processing stages associated with conscious access mechanisms. In contrast, early perceptual components reveal an amplification of neural responses for predicted relative to surprising events, suggesting that selective attention enhances perceptual processing for expected events. Taken together, these results demonstrate that cross-modal statistical regularities are used to generate predictions that differentially influence early and late neural responses in infants.

The Integrated Information Theory (IIT) of consciousness starts from essential phenomenological properties, which are then translated into postulates that any physical system must satisfy in order to specify the physical substrate of consciousness. We recently introduced an information measure (Barbosa et al., 2020) that captures three postulates of IIT—existence, intrinsicality and information—and is unique. Here we show that the new measure also satisfies the remaining postulates of IIT—integration and exclusion— and create the framework that identifies maximally irreducible mechanisms. These mechanisms can then form maximally irreducible systems, which in turn will specify the physical substrate of conscious experience.

SummaryFalling asleep leads to a loss of sensory awareness and to the inability to interact with the environment [1]. While this was traditionally thought as a consequence of the brain shutting down to external inputs, it is now acknowledged that incoming stimuli can still be processed, at least to some extent, during sleep [2]. For instance, sleeping participants can create novel sensory associations between tones and odors [3] or reactivate existing semantic associations, as evidenced by event-related potentials [4–7]. Yet, the extent to which the brain continues to process external stimuli remains largely unknown. In particular, it remains unclear whether sensory information can be processed in a flexible and task-dependent manner by the sleeping brain, all the way up to the preparation of relevant actions. Here, using semantic categorization and lexical decision tasks, we studied task-relevant responses triggered by spoken stimuli in the sleeping brain. Awake participants classified words as either animals or objects (experiment 1) or as either words or pseudowords (experiment 2) by pressing a button with their right or left hand, while transitioning toward sleep. The lateralized readiness potential (LRP), an electrophysiological index of response preparation, revealed that task-specific preparatory responses are preserved during sleep. These findings demonstrate that despite the absence of awareness and behavioral responsiveness, sleepers can still extract task-relevant information from external stimuli and covertly prepare for appropriate motor responses.

We introduce an information measure that reflects the intrinsic perspective of a receiver or sender of a single symbol, who has no access to the communication channel and its source or target. The measure satisfies three desired properties—causality, specificity, intrinsicality—and is shown to be unique. Causality means that symbols must be transmitted with probability greater than chance. Specificity means that information must be transmitted by an individual symbol. Intrinsicality means that a symbol must be taken as such and cannot be decomposed into signal and noise. It follows that the intrinsic information carried by a specific symbol increases if the repertoire of symbols increases without noise (expansion) and decreases if it does so without signal (dilution). An optimal balance between expansion and dilution is relevant for systems whose elements must assess their inputs and outputs from the intrinsic perspective, such as neurons in a network.

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Stimulus repetition induces attenuated brain responses. This phenomenon, termed repetition suppression (RS), is classically held to stem from bottom-up neuronal adaptation. However, recent studies suggest that RS is driven by top-down predictive mechanisms. It remains controversial whether these top-down mechanisms of RS rely on conscious strategies, or if they represent a more fundamental aspect of perception, coding for physical properties of the repeated feature. The presence of top-down effects in the absence of perceptual awareness would indicate that conscious strategies are not sufficient to explain top-down mechanisms of RS. We combined an unconscious priming paradigm with EEG recordings and tested whether RS can be modulated by the probability of encountering a repetition, even in the absence of awareness. Our results show that both behavioural priming and RS near occipital areas are modulated by repetition probability, regardless of prime awareness. This contradicts previous findings that have argued that RS modulation is a by-product of conscious strategies. In contrast, we found that the increase in theta-band power following unrepeated trials – an index of conflict detection – is modulated only by expectations during conscious primes, implicating the use of conscious strategies. Together, our results suggest that the influence of predictions on RS can be either automatic in sensory brain regions or dependent on conscious strategies.