Brain Mechanisms Underlying the Brief Maintenance of Seen and Unseen Sensory Information

Pharmacological Elevation of Catecholamine Levels Improves Perceptual Decisions, But Not Metacognitive Insight

Perceptual decisions are often accompanied by a feeling of decision confidence. Where the parietal cortex is known for its crucial role in shaping such perceptual decisions, metacognitive evaluations are thought to additionally rely on the (pre)frontal cortex. Because of this supposed neural differentiation between these processes, perceptual and metacognitive decisions may be divergently affected by changes in internal (e.g., attention, arousal) and external (e.g., task and environmental demands) factors. Although intriguing, causal evidence for this hypothesis remains scarce. Here, we investigated the causal effect of two neuromodulatory systems on behavioral and neural measures of perceptual and metacognitive decision-making. Specifically, we pharmacologically elevated levels of catecholamines (with atomoxetine) and acetylcholine (with donepezil) in healthy adult human participants performing a visual discrimination task in which we gauged decision confidence, while electroencephalography was measured. Where cholinergic effects were not robust, catecholaminergic enhancement improved perceptual sensitivity, while at the same time leaving metacognitive sensitivity unaffected. Neurally, catecholaminergic elevation did not affect sensory representations of task-relevant visual stimuli but instead enhanced well-known decision signals measured over the centroparietal cortex, reflecting the accumulation of sensory evidence over time. Crucially, catecholaminergic enhancement concurrently impoverished neural markers measured over the frontal cortex linked to the formation of metacognitive evaluations. Enhanced catecholaminergic neuromodulation thus improves perceptual but not metacognitive decision-making.

A measure centrality index for systematic empirical comparison of consciousness theories

Consciousness science is marred by disparate constructs and methodologies, making it challenging to systematically compare theories. This foundational crisis casts doubts on the scientific character of the field itself. Addressing it, we propose a framework for systematically comparing consciousness theories by introducing a novel inter-theory classification interface, the Measure Centrality Index (MCI). Recognizing its gradient distribution, the MCI assesses the degree of importance a specific empirical measure has for a given consciousness theory. We apply the MCI to probe how the empirical measures of the Global Neuronal Workspace Theory (GNW), Integrated Information Theory (IIT), and Temporospatial Theory of Consciousness (TTC) would fare within the context of the other two. We demonstrate that direct comparison of IIT, GNW, and TTC is meaningful and valid for some measures like Lempel-Ziv Complexity (LZC), Autocorrelation Window (ACW), and possibly Mutual Information (MI). In contrast, it is problematic for others like the anatomical and physiological neural correlates of consciousness (NCC) due to their MCI-based differential weightings within the structure of the theories. In sum, we introduce and provide proof-of-principle of a novel systematic method for direct inter-theory empirical comparisons, thereby addressing isolated evolution of theories and confirmatory bias issues in the state-of-the-art neuroscience of consciousness.

Negation mitigates rather than inverts the neural representations of adjectives

Combinatoric linguistic operations underpin human language processes, but how meaning is composed and refined in the mind of the reader is not well understood. We address this puzzle by exploiting the ubiquitous function of negation. We track the online effects of negation ("not") and intensifiers ("really") on the representation of scalar adjectives (e.g., "good") in parametrically designed behavioral and neurophysiological (MEG) experiments. The behavioral data show that participants first interpret negated adjectives as affirmative and later modify their interpretation towards, but never exactly as, the opposite meaning. Decoding analyses of neural activity further reveal significant above chance decoding accuracy for negated adjectives within 600 ms from adjective onset, suggesting that negation does not invert the representation of adjectives (i.e., "not bad" represented as "good"); furthermore, decoding accuracy for negated adjectives is found to be significantly lower than that for affirmative adjectives. Overall, these results suggest that negation mitigates rather than inverts the neural representations of adjectives. This putative suppression mechanism of negation is supported by increased synchronization of beta-band neural activity in sensorimotor areas. The analysis of negation provides a steppingstone to understand how the human brain represents changes of meaning over time.

Temporal attention recruits fronto-cingulate cortex to amplify stimulus representations

The human brain receives a continuous stream of input, but it faces significant constraints in its ability to process every item in a sequence of stimuli. Voluntary temporal attention can alleviate these constraints by using information about upcoming stimulus timing to selectively prioritize a task-relevant item over others in a sequence. But the neural mechanisms underlying this ability remain unclear. Here, we manipulated temporal attention to successive stimuli in a two-target temporal cueing task, while controlling for temporal expectation by using fully predictable stimulus timing. We recorded magnetoencephalography (MEG) in human observers and measured the effects of temporal attention on orientation representations of each stimulus using time-resolved multivariate decoding in both sensor and source space. Voluntary temporal attention enhanced the orientation representation of the first target 235-300 milliseconds after target onset. Unlike previous studies that did not isolate temporal attention from temporal expectation, we found no evidence that temporal attention enhanced early visual evoked responses. Instead, and unexpectedly, the primary source of enhanced decoding for attended stimuli in the critical time window was a contiguous region spanning left frontal cortex and cingulate cortex. The results suggest that voluntary temporal attention recruits cortical regions beyond the ventral stream at an intermediate processing stage to amplify the representation of a target stimulus, which may serve to protect it from subsequent interference by a temporal competitor.

Feedforward connectivity patterns from visual areas to the front of the brain contain information about sensory stimuli regardless of awareness or report

Current theories of consciousness can be categorized to some extent by their predictions about the putative role of the prefrontal cortex (PFC) in conscious perception. One family of the theories proposes that the PFC is necessary for conscious perception. The other postulates that the PFC is not necessary and that other areas (e.g., posterior cortical areas) are more important for conscious perception. No-report paradigms could potentially arbitrate the debate as they disentangle task reporting from conscious perception. While previous no-report paradigms tend to point to a reduction in PFC activity, they have not examined the critical role of the PFC in "monitoring" or "reading out" the patterns of activity in the sensory cortex to generate conscious perception. To address this, we reanalysed electroencephalography (EEG) data from a no-report inattentional blindness paradigm (Shafto & Pitts, 2015). We examined the role of feedforward input patterns to the PFC from sensory cortices. We employed nonparametric spectral Granger causality and quantified the amount of information that reflected the contents of consciousness using multivariate classifiers. Unexpectedly, regardless of whether the stimulus was consciously seen or not, we found that information relating to the current sensory stimulus was present in the pattern of inputs from visual areas to the PFC. In light of these findings, we suggest various theories of consciousness need to be revised to accommodate the fact that the contents of consciousness are decodable from the input patterns from posterior sensory regions to the PFC, regardless of awareness (or report).

Geometry of visuospatial working memory information in miniature gaze patterns

Stimulus-dependent eye movements have been recognized as a potential confound in decoding visual working memory information from neural signals. Here we combined eye-tracking with representational geometry analyses to uncover the information in miniature gaze patterns while participants (n = 41) were cued to maintain visual object orientations. Although participants were discouraged from breaking fixation by means of real-time feedback, small gaze shifts (<1°) robustly encoded the to-be-maintained stimulus orientation, with evidence for encoding two sequentially presented orientations at the same time. The orientation encoding on stimulus presentation was object-specific, but it changed to a more object-independent format during cued maintenance, particularly when attention had been temporarily withdrawn from the memorandum. Finally, categorical reporting biases increased after unattended storage, with indications of biased gaze geometries already emerging during the maintenance periods before behavioural reporting. These findings disclose a wealth of information in gaze patterns during visuospatial working memory and indicate systematic changes in representational format when memory contents have been unattended.

Early language dissociation in bilingual minds: magnetoencephalography evidence through a machine learning approach

Does neural activity reveal how balanced bilinguals choose languages? Despite using diverse neuroimaging techniques, prior studies haven't provided a definitive solution to this problem. Nonetheless, studies involving direct brain stimulation in bilinguals have identified distinct brain regions associated with language production in different languages. In this magnetoencephalography study with 45 proficient Spanish-Basque bilinguals, we investigated language selection during covert picture naming and word reading tasks. Participants were prompted to name line drawings or read words if the color of the stimulus changed to green, in 10% of trials. The task was performed either in Spanish or Basque. Despite similar sensor-level evoked activity for both languages in both tasks, decoding analyses revealed language-specific classification ~100 ms post-stimulus onset. During picture naming, right occipital-temporal sensors predominantly contributed to language decoding, while left occipital-temporal sensors were crucial for decoding during word reading. Cross-task decoding analysis unveiled robust generalization effects from picture naming to word reading. Our methodology involved a fine-grained examination of neural responses using magnetoencephalography, offering insights into the dynamics of language processing in bilinguals. This study refines our understanding of the neural underpinnings of language selection and bridges the gap between non-invasive and invasive experimental evidence in bilingual language production.

Mapping the dynamics of visual feature coding: Insights into perception and integration

The basic computations performed in the human early visual cortex are the foundation for visual perception. While we know a lot about these computations, a key missing piece is how the coding of visual features relates to our perception of the environment. To investigate visual feature coding, interactions, and their relationship to human perception, we investigated neural responses and perceptual similarity judgements to a large set of visual stimuli that varied parametrically along four feature dimensions. We measured neural responses using electroencephalography (N = 16) to 256 grating stimuli that varied in orientation, spatial frequency, contrast, and colour. We then mapped the response profiles of the neural coding of each visual feature and their interactions, and related these to independently obtained behavioural judgements of stimulus similarity. The results confirmed fundamental principles of feature coding in the visual system, such that all four features were processed simultaneously but differed in their dynamics, and there was distinctive conjunction coding for different combinations of features in the neural responses. Importantly, modelling of the behaviour revealed that every stimulus feature contributed to perceptual judgements, despite the untargeted nature of the behavioural task. Further, the relationship between neural coding and behaviour was evident from initial processing stages, signifying that the fundamental features, not just their interactions, contribute to perception. This study highlights the importance of understanding how feature coding progresses through the visual hierarchy and the relationship between different stages of processing and perception.

Diabetic Encephalopathy: Role of Oxidative and Nitrosative Factors in Type 2 Diabetes

Diabetes mellitus is a set of complex metabolic disorders characterized by chronic hyperglycaemic condition due to defective insulin secretion (Type 1) and action (Type 2), which leads to serious micro and macro-vascular damage, inflammation, oxidative and nitrosative stress and a deranged energy homeostasis due to imbalance in the glucose and lipid metabolism. Moreover, patient with diabetes mellitus often showed the nervous system disorders known as diabetic encephalopathy. The precise pathological mechanism of diabetic encephalopathy by which it effects the central nervous system directly or indirectly causing the cognitive and motor impairment, is not completely understood. However, it has been speculated that like other extracerebellar tissues, oxidative and nitrosative stress may play significant role in the pathogenesis of diabetic encephalopathy. Therefore, the present review aimed to explain the possible association of the oxidative and nitrosative stress caused by the chronic hyperglycaemic condition with the central nervous system complications of the type 2 diabetes mellitus induced diabetic encephalopathy.

Spatiotemporal dynamics of successive activations across the human brain during simple arithmetic processing

Previous neuroimaging studies have offered unique insights about the spatial organization of activations and deactivations across the brain, however these were not powered to explore the exact timing of events at the subsecond scale combined with precise anatomical source information at the level of individual brains. As a result, we know little about the order of engagement across different brain regions during a given cognitive task. Using experimental arithmetic tasks as a prototype for human-unique symbolic processing, we recorded directly across 10,076 brain sites in 85 human subjects (52% female) using intracranial electroencephalography (iEEG). Our data revealed a remarkably distributed change of activity in almost half of the sampled sites. Notably, an orderly successive activation of a set of brain regions - anatomically consistent across subjects-was observed in individual brains. Furthermore, the temporal order of activations across these sites was replicable across subjects and trials. Moreover, the degree of functional connectivity between the sites decreased as a function of temporal distance between regions, suggesting that information is partially leaked or transformed along the processing chain. Furthermore, in each activated region, distinct neuronal populations with opposite activity patterns during target and control conditions were juxtaposed in an anatomically orderly manner. Our study complements the prior imaging studies by providing hitherto unknown information about the timing of events in the brain during arithmetic processing. Such findings can be a basis for developing mechanistic computational models of human-specific cognitive symbolic systems.

Significance statement

Our study elucidates the spatiotemporal dynamics and anatomical specificity of brain activations across >10,000 sites during arithmetic tasks, as captured by intracranial EEG. We discovered an orderly, successive activation of brain regions, consistent across individuals, and a decrease in functional connectivity as a function of temporal distance between regions. Our findings provide unprecedented insights into the sequence of cognitive processing and regional interactions, offering a novel perspective for enhancing computational models of cognitive symbolic systems.

Neural population dynamics of human working memory

The activity of neurons in macaque prefrontal cortex (PFC) persists during working memory (WM) delays, providing a mechanism for memory.1,2,3,4,5,6,7,8,9,10,11 Although theory,11,12 including formal network models,13,14 assumes that WM codes are stable over time, PFC neurons exhibit dynamics inconsistent with these assumptions.15,16,17,18,19 Recently, multivariate reanalyses revealed the coexistence of both stable and dynamic WM codes in macaque PFC.20,21,22,23 Human EEG studies also suggest that WM might contain dynamics.24,25 Nonetheless, how WM dynamics vary across the cortical hierarchy and which factors drive dynamics remain unknown. To elucidate WM dynamics in humans, we decoded WM content from fMRI responses across multiple cortical visual field maps.26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48 We found coexisting stable and dynamic neural representations of WM during a memory-guided saccade task. Geometric analyses of neural subspaces revealed that early visual cortex exhibited stronger dynamics than high-level visual and frontoparietal cortex. Leveraging models of population receptive fields, we visualized and made the neural dynamics interpretable. We found that during WM delays, V1 population initially encoded a narrowly tuned bump of activation centered on the peripheral memory target. Remarkably, this bump then spread inward toward foveal locations, forming a vector along the trajectory of the forthcoming memory-guided saccade. In other words, the neural code transformed into an abstraction of the stimulus more proximal to memory-guided behavior. Therefore, theories of WM must consider both sensory features and their task-relevant abstractions because changes in the format of memoranda naturally drive neural dynamics.

Testing the generalization of neural representations

Multivariate analysis methods are widely used in neuroscience to investigate the presence and structure of neural representations. Representational similarities across time or contexts are often investigated using pattern generalization, e.g. by training and testing multivariate decoders in different contexts, or by comparable pattern-based encoding methods. It is however unclear what conclusions can be validly drawn on the underlying neural representations when significant pattern generalization is found in mass signals such as LFP, EEG, MEG, or fMRI. Using simulations, we show how signal mixing and dependencies between measurements can drive significant pattern generalization even though the true underlying representations are orthogonal. We suggest that, using an accurate estimate of the expected pattern generalization given identical representations, it is nonetheless possible to test meaningful hypotheses about the generalization of neural representations. We offer such an estimate of the expected magnitude of pattern generalization and demonstrate how this measure can be used to assess the similarity and differences of neural representations across time and contexts.

Prior Knowledge Uses Prestimulus Alpha Band Oscillations and Persistent Poststimulus Neural Templates for Conscious Perception

Prior knowledge has a profound impact on the way we perceive the world. However, it remains unclear how the prior knowledge is maintained in our brains and thereby influences the subsequent conscious perception. The Dalmatian dog illusion is a perfect tool to study prior knowledge, where the picture is initially perceived as noise. Once the prior knowledge was introduced, a Dalmatian dog could be consciously seen, and the picture immediately became meaningful. Using pictures with hidden objects as standard stimuli and similar pictures without hidden objects as deviant stimuli, we investigated the neural representation of prior knowledge and its impact on conscious perception in an oddball paradigm using electroencephalogram (EEG) in both male and female human subjects. We found that the neural patterns between the prestimulus alpha band oscillations and poststimulus EEG activity were significantly more similar for the standard stimuli than for the deviant stimuli after prior knowledge was provided. Furthermore, decoding analysis revealed that persistent neural templates were evoked after the introduction of prior knowledge, similar to that evoked in the early stages of visual processing. In conclusion, the current study suggests that prior knowledge uses alpha band oscillations in a multivariate manner in the prestimulus period and induces specific persistent neural templates in the poststimulus period, enabling the conscious perception of the hidden objects.SIGNIFICANCE STATEMENT The visual world we live in is not always optimal. In dark or noisy environments, prior knowledge can help us interpret imperfect sensory signals and enable us to consciously perceive hidden objects. However, we still know very little about how prior knowledge works at the neural level. Using the Dalmatian dog illusion and multivariate methods, we found that prior knowledge uses prestimulus alpha band oscillations to carry information about the hidden object and exerts a persistent influence in the poststimulus period by inducing specific neural templates. Our findings provide a window into the neural underpinnings of prior knowledge and offer new insights into the role of alpha band oscillations and neural templates associated with conscious perception.

Illusory object recognition is either perceptual or cognitive in origin depending on decision confidence

We occasionally misinterpret ambiguous sensory input or report a stimulus when none is presented. It is unknown whether such errors have a sensory origin and reflect true perceptual illusions, or whether they have a more cognitive origin (e.g., are due to guessing), or both. When participants performed an error-prone and challenging face/house discrimination task, multivariate electroencephalography (EEG) analyses revealed that during decision errors (e.g., mistaking a face for a house), sensory stages of visual information processing initially represent the presented stimulus category. Crucially however, when participants were confident in their erroneous decision, so when the illusion was strongest, this neural representation flipped later in time and reflected the incorrectly reported percept. This flip in neural pattern was absent for decisions that were made with low confidence. This work demonstrates that decision confidence arbitrates between perceptual decision errors, which reflect true illusions of perception, and cognitive decision errors, which do not.

Confidence in consciousness research

To study (un)conscious perception and test hypotheses about consciousness, researchers need procedures for determining whether subjects consciously perceive stimuli or not. This article is an introduction to a family of procedures called "confidence-based procedures," which consist in interpreting metacognitive indicators as indicators of consciousness. I assess the validity and accuracy of these procedures, and answer a series of common objections to their use in consciousness research. I conclude that confidence-based procedures are valid for assessing consciousness, and, in most cases, accurate enough for our practical and scientific purposes. This article is categorized under: Psychology > Perception and Psychophysics Philosophy > Consciousness.

Nonconscious information can be identified as task-relevant but not prioritized in working memory

Two critical features of working memory are the identification and appropriate use of task-relevant information while avoiding distraction. Here, in 3 experiments, we explored if these features can be achieved also for nonconscious stimuli. Participants performed a delayed match-to-sample task in which task relevance of 2 competing stimuli was indicated by a cue, and continuous flash suppression was used to manipulate the conscious/nonconscious visual experience. Experiment 1 revealed better-than-chance performance with nonconscious stimuli, demonstrating goal-directed use of nonconscious task-relevant information. Experiment 2 demonstrated that the cue that defined task relevance must be conscious to allow such goal-directed use. In Experiment 3, multi-voxel pattern analyses of brain activity revealed that only the target was prioritized and maintained during conscious trials. Conversely, during nonconscious trials, both target and distractor were maintained. However, decoding of task relevance during the probe/test phase demonstrated identification of both target and distractor information. These results show that identification of task-relevant information can operate also on nonconscious material. However, they do not support the prioritization of nonconscious task-relevant information, thus suggesting a mismatch in the attentional mechanisms involved during conscious and nonconscious working memory.

Magnetoencephalography recordings reveal the neural mechanisms of auditory contributions to improved visual detection

Sounds enhance the detection of visual stimuli while concurrently biasing an observer's decisions. To investigate the neural mechanisms that underlie such multisensory interactions, we decoded time-resolved Signal Detection Theory sensitivity and criterion parameters from magneto-encephalographic recordings of participants that performed a visual detection task. We found that sounds improved visual detection sensitivity by enhancing the accumulation and maintenance of perceptual evidence over time. Meanwhile, criterion decoding analyses revealed that sounds induced brain activity patterns that resembled the patterns evoked by an actual visual stimulus. These two complementary mechanisms of audiovisual interplay differed in terms of their automaticity: Whereas the sound-induced enhancement in visual sensitivity depended on participants being actively engaged in a detection task, we found that sounds activated the visual cortex irrespective of task demands, potentially inducing visual illusory percepts. These results challenge the classical assumption that sound-induced increases in false alarms exclusively correspond to decision-level biases.

Attentional capture mediates the emergence and suppression of intrusive memories

Intrusive memories hijack consciousness and their control may lead to forgetting. However, the contribution of reflexive attention to qualifying a memory signal as interfering is unknown. We used machine learning to decode the brain's electrical activity and pinpoint the otherwise hidden emergence of intrusive memories reported during a memory suppression task. Importantly, the algorithm was trained on an independent attentional model of visual activity, mimicking either the abrupt and interfering appearance of visual scenes into conscious awareness or their deliberate exploration. Intrusion of memories into conscious awareness were decoded above chance. The decoding accuracy increased when the algorithm was trained using a model of reflexive attention. Conscious detection of intrusive activity decoded from the brain signal was central to the future silencing of suppressed memories and later forgetting. Unwanted memories require the reflexive orienting of attention and access to consciousness to be suppressed effectively by inhibitory control.

Dissociable rhythmic mechanisms enhance memory for conscious and nonconscious perceptual contents

Understanding the neural mechanisms of conscious and unconscious experience is a major goal of fundamental and translational neuroscience. Here, we target the early visual cortex with a protocol of noninvasive, high-resolution alternating current stimulation while participants performed a delayed target–probe discrimination task and reveal dissociable mechanisms of mnemonic processing for conscious and unconscious perceptual contents. Entraining β-rhythms in bilateral visual areas preferentially enhanced short-term memory for seen information, whereas α-entrainment in the same region preferentially enhanced short-term memory for unseen information. The short-term memory improvements were frequency-specific and long-lasting. The results add a mechanistic foundation to existing theories of consciousness, call for revisions to these theories, and contribute to the development of nonpharmacological therapeutics for improving visual cortical processing.

Decoding perceptual awareness across the brain with a no-report fMRI masking paradigm

Does perceptual awareness arise within the sensory regions of the brain or within higher-level regions (e.g., the frontal lobe)? To answer this question, researchers traditionally compare neural activity when observers report being aware versus being unaware of a stimulus. However, it is unclear whether the resulting activations are associated with the conscious perception of the stimulus or the post-perceptual processes associated with reporting that stimulus. To address this limitation, we used both report and no-report conditions in a visual masking paradigm while participants were scanned using functional MRI (fMRI). We found that the overall univariate response to visible stimuli in the frontal lobe was robust in the report condition but disappeared in the no-report condition. However, using multivariate patterns, we could still decode in both conditions whether a stimulus reached conscious awareness across the brain, including in the frontal lobe. These results help reconcile key discrepancies in the recent literature and provide a path forward for identifying the neural mechanisms associated with perceptual awareness.

An academic survey on theoretical foundations, common assumptions and the current state of consciousness science

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.

Neuroscientific Evidence for Processing Without Awareness

The extent to which we are affected by perceptual input of which we are unaware is widely debated. By measuring neural responses to sensory stimulation, neuroscientific data could complement behavioral results with valuable evidence. Here we review neuroscientific findings of processing of high-level information, as well as interactions with attention and memory. Although the results are mixed, we find initial support for processing object categories and words, possibly to the semantic level, as well as emotional expressions. Robust neural evidence for face individuation and integration of sentences or scenes is lacking. Attention affects the processing of stimuli that are not consciously perceived, and such stimuli may exogenously but not endogenously capture attention when relevant, and be maintained in memory over time. Sources of inconsistency in the literature include variability in control for awareness as well as individual differences, calling for future studies that adopt stricter measures of awareness and probe multiple processes within subjects.

Unconscious Visual Working Memory: A critical review and Bayesian meta-analysis

The relationship between consciousness and working memory (WM) has been recently debated both at the theoretical and methodological levels (Persuh et al., 2018; Velichkovsky, 2017). While there is behavioral and neural evidence that argues for the existence of unconscious WM, several methodological concerns have been raised, rendering this issue highly controversial. To address the robustness of the previous findings, here we adopt a meta-analytic approach to estimate the effect size and heterogeneity of the previously reported unconscious WM results, also including unpublished results. We used meta-regression to isolate relevant experimental variables, in particular, consciousness manipulation and the WM paradigm to identify the source of the heterogeneity in the reported effect size of the unconscious WM. Our meta-analysis supports the existence of the unconscious WM effect and critically reveals several experimental variables that contribute to relevant heterogeneity. Our analysis clarifies several theoretical and methodological issues. We recommend that future studies explicitly operationalize the definition of consciousness, standardize the methodology and systematically explore the role of critical variables for the unconscious WM effect.

Perceptual filling-in dispels the veridicality problem of conscious perception research

Conscious perceptual experiences are expected to correlate with content-specific brain activity. A veridicality problem arises when attempting to disentangle unconscious and conscious brain processes if conscious perceptual contents accurately match the physical nature of the stimulus. We argue that perceptual filling-in, a phenomenon whereby visual information inaccurately spreads across visual space, is a promising approach to circumvent the veridicality problem. Filling-in generates non-veridical although unambiguous percepts dissociated from stimulus input. In particular, the radial uniformity illusion induces a filling-in experience between a central disk and the surrounding periphery. We discuss how this illusion facilitates both the detection of neurophysiological responses and subjective phenomenological monitoring. We report behavioral effects from a large-sample (n = 200) psychophysics study and examine key stimulus parameters that drive the conscious filling-in experience. We propose that these data underpin future hypothesis-driven studies of filling-in to further delineate the neural mechanisms of conscious perception.

A window of subliminal perception

Under labels such as unconscious processing and subliminal perception, identification of stimuli falling below the subjective threshold (whether truly unconscious or not) has been found remarkably accurate in some experiments while completely at chance in others. Here, we first identify that an apparent window of subliminal perception arises in humans under specific stimulus conditions using different experimental paradigms and analysis methods. We then show that the standard signal detection theory (SDT) model is unable to account for this window and extend it until it is. We finally compare a range of models on empirical data. The models performing best are notable for their absence of hierarchical levels, indicating that the window could be a base property of any phenomenally conscious system. The models explain previously incompatible findings in the literature, and they allow for estimations of peaks in subthreshold perception across the spectrum of stimulus saliency, which may be used in further studies of subliminal perception.

Information in Explaining Cognition: How to Evaluate It?

The claims that “The brain processes information” or “Cognition is information processing” are accepted as truisms in cognitive science. However, it is unclear how to evaluate such claims absent a specification of “information” as it is used by neurocognitive theories. The aim of this article is, thus, to identify the key features of information that information-based neurocognitive theories posit. A systematic identification of these features can reveal the explanatory role that information plays in specific neurocognitive theories, and can, therefore, be both theoretically and practically important. These features can be used, in turn, as desiderata against which candidate theories of information may be evaluated. After discussing some characteristics of explanation in cognitive science and their implications for “information”, three notions are briefly introduced: natural, sensory, and endogenous information. Subsequently, six desiderata are identified and defended based on cognitive scientific practices. The global workspace theory of consciousness is then used as a specific case study that arguably posits either five or six corresponding features of information.

Decoding rapidly presented visual stimuli from prefrontal ensembles without report nor post-perceptual processing

The role of the primate prefrontal cortex (PFC) in conscious perception is debated. The global neuronal workspace theory of consciousness predicts that PFC neurons should contain a detailed code of the current conscious contents. Previous research showed that PFC is indeed activated in paradigms of conscious visual perception, including no-report paradigms where no voluntary behavioral report of the percept is given, thus avoiding a conflation of signals related to visual consciousness with signals related to the report. Still, it has been argued that prefrontal modulation could reflect post-perceptual processes that may be present even in the absence of report, such as thinking about the perceived stimulus, therefore reflecting a consequence rather than a direct correlate of conscious experience. Here, we investigate these issues by recording neuronal ensemble activity from the macaque ventrolateral PFC during briefly presented visual stimuli, either in isolated trials in which stimuli were clearly perceived or in sequences of rapid serial visual presentation (RSVP) in which perception and post-perceptual processing were challenged. We report that the identity of each stimulus could be decoded from PFC population activity even in the RSVP condition. The first visual signals could be detected at 60 ms after stimulus onset and information was maximal at 150 ms. However, in the RSVP condition, 200 ms after the onset of a stimulus, the decoding accuracy quickly dropped to chance level and the next stimulus started to be decodable. Interestingly, decoding in the ventrolateral PFC was stronger compared to posterior parietal cortex for both isolated and RSVP stimuli. These results indicate that neuronal populations in the macaque PFC reliably encode visual stimuli even under conditions that have been shown to challenge conscious perception and/or substantially reduce the probability of post-perceptual processing in humans. We discuss whether the observed activation reflects conscious access, phenomenal consciousness, or merely a preconscious bottom-up wave.

Chinese Character Processing in Visual Masking

It has not been clarified if attention influences perception of targets in visual masking. Three forms of common masks (random pattern, para-/metacontrast, and four dots) were thus chosen in the present study and presented with character targets in three temporal sequences (forward, backward, and sandwiched mask or forward-backward mask combination). In order to pinpoint the level of processing where masking arises, character targets were varied in depth of processing from random arrangements of strokes up to real Chinese characters. The attentional influence was examined under perceptual discrimination and lexical decision tasks, respectively. The results revealed significant interactions among four factors (mask form, temporal sequence, depth of processing, and task). Identification of character targets in each form of mask sequence varied with task demand, with greater suppression in the perceptual discrimination task. These findings suggested that attentional demand can bias processing in favor of task-related information in visual masking. Variations in masking effects may be contributed by both attentional demand and spatio-temporal interaction.

An active inference model of conscious access: How cognitive action selection reconciles the results of report and no-report paradigms

Cognitive theories of consciousness, such as global workspace theory and higher-order theories, posit that frontoparietal circuits play a crucial role in conscious access. However, recent studies using no-report paradigms have posed a challenge to cognitive theories by demonstrating conscious accessibility in the apparent absence of prefrontal cortex (PFC) activation. To address this challenge, this paper presents a computational model of conscious access, based upon active inference, that treats working memory gating as a cognitive action. We simulate a visual masking task and show that late P3b-like event-related potentials (ERPs), and increased PFC activity, are induced by the working memory demands of self-report generation. When reporting demands are removed, these late ERPs vanish and PFC activity is reduced. These results therefore reproduce, and potentially explain, results from no-report paradigms. However, even without reporting demands, our model shows that simulated PFC activity on visible stimulus trials still crosses the threshold for reportability - maintaining the link between PFC and conscious access. Therefore, our simulations show that evidence provided by no-report paradigms does not necessarily contradict cognitive theories of consciousness.

Ongoing neural oscillations influence behavior and sensory representations by suppressing neuronal excitability

The ability to process and respond to external input is critical for adaptive behavior. Why, then, do neural and behavioral responses vary across repeated presentations of the same sensory input? Ongoing fluctuations of neuronal excitability are currently hypothesized to underlie the trial-by-trial variability in sensory processing. To test this, we capitalized on intracranial electrophysiology in neurosurgical patients performing an auditory discrimination task with visual cues: specifically, we examined the interaction between prestimulus alpha oscillations, excitability, task performance, and decoded neural stimulus representations. We found that strong prestimulus oscillations in the alpha+ band (i.e., alpha and neighboring frequencies), rather than the aperiodic signal, correlated with a low excitability state, indexed by reduced broadband high-frequency activity. This state was related to slower reaction times and reduced neural stimulus encoding strength. We propose that the alpha+ rhythm modulates excitability, thereby resulting in variability in behavior and sensory representations despite identical input.

Reward Rapidly Enhances Visual Perception

Rewards exert a deep influence on our cognition and behavior. Here, we used a paradigm in which reward information was provided at either encoding or retrieval of a brief, masked stimulus to show that reward can also rapidly modulate perceptual encoding of visual information. Experiment 1 (n = 30 adults) showed that participants' response accuracy was enhanced when a to-be-encoded grating signaled high reward relative to low reward, but only when the grating was presented very briefly and participants reported that they were not consciously aware of it. Experiment 2 (n = 29 adults) showed that there was no difference in participants' response accuracy when reward information was instead provided at the stage of retrieval, ruling out an explanation of the reward-modulation effect in terms of differences in motivated retrieval. Taken together, our findings provide behavioral evidence consistent with a rapid reward modulation of visual perception, which may not require consciousness.

Binding the Acoustic Features of an Auditory Source through Temporal Coherence

Numerous studies have suggested that the perception of a target sound stream (or source) can only be segregated from a complex acoustic background mixture if the acoustic features underlying its perceptual attributes (e.g., pitch, location, and timbre) induce temporally modulated responses that are mutually correlated (or coherent), and that are uncorrelated (incoherent) from those of other sources in the mixture. This "temporal coherence" hypothesis asserts that attentive listening to one acoustic feature of a target enhances brain responses to that feature but would also concomitantly (1) induce mutually excitatory influences with other coherently responding neurons, thus enhancing (or binding) them all as they respond to the attended source; by contrast, (2) suppressive interactions are hypothesized to build up among neurons driven by temporally incoherent sound features, thus relatively reducing their activity. In this study, we report on EEG measurements in human subjects engaged in various sound segregation tasks that demonstrate rapid binding among the temporally coherent features of the attended source regardless of their identity (pure tone components, tone complexes, or noise), harmonic relationship, or frequency separation, thus confirming the key role temporal coherence plays in the analysis and organization of auditory scenes.

No Evidence for Neural Overlap between Unconsciously Processed and Imagined Stimuli

Visual representations can be generated via feedforward or feedback processes. The extent to which these processes result in overlapping representations remains unclear. Previous work has shown that imagined stimuli elicit similar representations as perceived stimuli throughout the visual cortex. However, while representations during imagery are indeed only caused by feedback processing, neural processing during perception is an interplay of both feedforward and feedback processing. This means that any representational overlap could be because of overlap in feedback processes. In the current study, we aimed to investigate this issue by characterizing the overlap between feedforward- and feedback-initiated category representations during imagined stimuli, conscious perception, and unconscious processing using fMRI in humans of either sex. While all three conditions elicited stimulus representations in left lateral occipital cortex (LOC), significant similarities were observed only between imagery and conscious perception in this area. Furthermore, connectivity analyses revealed stronger connectivity between frontal areas and left LOC during conscious perception and in imagery compared with unconscious processing. Together, these findings can be explained by the idea that long-range feedback modifies visual representations, thereby reducing representational overlap between purely feedforward- and feedback-initiated stimulus representations measured by fMRI. Neural representations influenced by feedback, either stimulus driven (perception) or purely internally driven (imagery), are, however, relatively similar.

The Human Brain Encodes a Chronicle of Visual Events at Each Instant of Time Through the Multiplexing of Traveling Waves

The human brain continuously processes streams of visual input. Yet, a single image typically triggers neural responses that extend beyond 1s. To understand how the brain encodes and maintains successive images, we analyzed with electroencephalography the brain activity of human subjects while they watched ∼5000 visual stimuli presented in fast sequences. First, we confirm that each stimulus can be decoded from brain activity for ∼1s, and we demonstrate that the brain simultaneously represents multiple images at each time instant. Second, we source localize the corresponding brain responses in the expected visual hierarchy and show that distinct brain regions represent, at each time instant, different snapshots of past stimulations. Third, we propose a simple framework to further characterize the dynamical system of these traveling waves. Our results show that a chain of neural circuits, which each consist of (1) a hidden maintenance mechanism and (2) an observable update mechanism, accounts for the dynamics of macroscopic brain representations elicited by visual sequences. Together, these results detail a simple architecture explaining how successive visual events and their respective timings can be simultaneously represented in the brain.SIGNIFICANCE STATEMENT Our retinas are continuously bombarded with a rich flux of visual input. Yet, how our brain continuously processes such visual streams is a major challenge to neuroscience. Here, we developed techniques to decode and track, from human brain activity, multiple images flashed in rapid succession. Our results show that the brain simultaneously represents multiple successive images at each time instant by multiplexing them along a neural cascade. Dynamical modeling shows that these results can be explained by a hierarchy of neural assemblies that continuously propagate multiple visual contents. Overall, this study sheds new light on the biological basis of our visual experience.

Comparing theories of consciousness: why it matters and how to do it

The theoretical landscape of scientific studies of consciousness has flourished. Today, even multiple versions of the same theory are sometimes available. To advance the field, these theories should be directly compared to determine which are better at predicting and explaining empirical data. Systematic inquiries of this sort are seen in many subfields in cognitive psychology and neuroscience, e.g. in working memory. Nonetheless, when we surveyed publications on consciousness research, we found that most focused on a single theory. When 'comparisons' happened, they were often verbal and non-systematic. This fact in itself could be a contributing reason for the lack of convergence between theories in consciousness research. In this paper, we focus on how to compare theories of consciousness to ensure that the comparisons are meaningful, e.g. whether their predictions are parallel or contrasting. We evaluate how theories are typically compared in consciousness research and related subdisciplines in cognitive psychology and neuroscience, and we provide an example of our approach. We then examine the different reasons why direct comparisons between theories are rarely seen. One possible explanation is the unique nature of the consciousness phenomenon. We conclude that the field should embrace this uniqueness, and we set out the features that a theory of consciousness should account for.

Orthogonal neural codes for speech in the infant brain

Creating invariant representations from an everchanging speech signal is a major challenge for the human brain. Such an ability is particularly crucial for preverbal infants who must discover the phonological, lexical, and syntactic regularities of an extremely inconsistent signal in order to acquire language. Within the visual domain, an efficient neural solution to overcome variability consists in factorizing the input into a reduced set of orthogonal components. Here, we asked whether a similar decomposition strategy is used in early speech perception. Using a 256-channel electroencephalographic system, we recorded the neural responses of 3-mo-old infants to 120 natural consonant-vowel syllables with varying acoustic and phonetic profiles. Using multivariate pattern analyses, we show that syllables are factorized into distinct and orthogonal neural codes for consonants and vowels. Concerning consonants, we further demonstrate the existence of two stages of processing. A first phase is characterized by orthogonal and context-invariant neural codes for the dimensions of manner and place of articulation. Within the second stage, manner and place codes are integrated to recover the identity of the phoneme. We conclude that, despite the paucity of articulatory motor plans and speech production skills, pre-babbling infants are already equipped with a structured combinatorial code for speech analysis, which might account for the rapid pace of language acquisition during the first year.

Larger capacity for unconscious versus conscious episodic memory

Episodic memory is the memory for experienced events. A peak competence of episodic memory is the mental combination of events to infer commonalities. Inferring commonalities may proceed with and without consciousness of events. Yet what distinguishes conscious from unconscious inference? This question inspired nine experiments that featured strongly and weakly masked cartoon clips presented for unconscious and conscious inference. Each clip featured a scene with a visually impenetrable hiding place. Five animals crossed the scene one-by-one consecutively. One animal trajectory represented one event. The animals moved through the hiding place, where they might linger or not. The participants' task was to observe the animals' entrances and exits to maintain a mental record of which animals hid simultaneously. We manipulated information load to explore capacity limits. Memory of inferences was tested immediately, 3.5 or 6 min following encoding. The participants retrieved inferences well when encoding was conscious. When encoding was unconscious, the participants needed to respond intuitively. Only habitually intuitive decision makers exhibited a significant delayed retrieval of inferences drawn unconsciously. Their unconscious retrieval performance did not drop significantly with increasing information load, while conscious retrieval performance dropped significantly. A working memory network, including hippocampus, was activated during both conscious and unconscious inference and correlated with retrieval success. An episodic retrieval network, including hippocampus, was activated during both conscious and unconscious retrieval of inferences and correlated with retrieval success. Only conscious encoding/retrieval recruited additional brain regions outside these networks. Hence, levels of consciousness influenced the memories' behavioral impact, memory capacity, and the neural representational code.

Temporal uncertainty enhances suppression of neural responses to predictable visual stimuli

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Does stimulus timing impact the processing of predicted visual features?.

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We evaluated if expectation suppression effects are modulated by temporal predictability.

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Expectation suppression was robust in both visual ERFs and feature decoding accuracy.

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Visual responses to predictable stimuli are greater for predictable vs. unpredictable timing.

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Sensory evidence is given less weight when timing is uncertain.

Contextual information triggers predictions about the content (“what”) of environmental stimuli to update an internal generative model of the surrounding world. However, visual information dynamically changes across time, and temporal predictability (“when”) may influence the impact of internal predictions on visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information (“what”) is affected by temporal predictability (“when”). Participants (N = 16) were presented with four consecutive Gabor patches (entrainers) with constant spatial frequency but with variable orientation and temporal onset. A fifth target Gabor was presented after a longer delay and with higher or lower spatial frequency that participants had to judge. We compared the neural responses to entrainers where the Gabor orientation could, or could not be temporally predicted along the entrainer sequence, and with inter-entrainer timing that was constant (predictable), or variable (unpredictable). We observed suppression of evoked neural responses in the visual cortex for predictable stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early visual responses, with the feature specificity of early visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable visual stimuli. These findings converge to suggest that the cognitive system processes visual features of temporally predictable stimuli in higher detail, while processing temporally uncertain stimuli may rely more heavily on abstract internal expectations.

Semantic and spatial congruency mould audiovisual integration depending on perceptual awareness

Information integration is considered a hallmark of human consciousness. Recent research has challenged this tenet by showing multisensory interactions in the absence of awareness. This psychophysics study assessed the impact of spatial and semantic correspondences on audiovisual binding in the presence and absence of visual awareness by combining forward-backward masking with spatial ventriloquism. Observers were presented with object pictures and synchronous sounds that were spatially and/or semantically congruent or incongruent. On each trial observers located the sound, identified the picture and rated the picture's visibility. We observed a robust ventriloquist effect for subjectively visible and invisible pictures indicating that pictures that evade our perceptual awareness influence where we perceive sounds. Critically, semantic congruency enhanced these visual biases on perceived sound location only when the picture entered observers' awareness. Our results demonstrate that crossmodal influences operating from vision to audition and vice versa are interactively controlled by spatial and semantic congruency in the presence of awareness. However, when visual processing is disrupted by masking procedures audiovisual interactions no longer depend on semantic correspondences.

Cortical and subcortical signatures of conscious object recognition

The neural mechanisms underlying conscious recognition remain unclear, particularly the roles played by the prefrontal cortex, deactivated brain areas and subcortical regions. We investigated neural activity during conscious object recognition using 7 Tesla fMRI while human participants viewed object images presented at liminal contrasts. Here, we show both recognized and unrecognized images recruit widely distributed cortical and subcortical regions; however, recognized images elicit enhanced activation of visual, frontoparietal, and subcortical networks and stronger deactivation of the default-mode network. For recognized images, object category information can be decoded from all of the involved cortical networks but not from subcortical regions. Phase-scrambled images trigger strong involvement of inferior frontal junction, anterior cingulate cortex and default-mode network, implicating these regions in inferential processing under increased uncertainty. Our results indicate that content-specific activity in both activated and deactivated cortical networks and non-content-specific subcortical activity support conscious recognition.

Cortical and subcortical neural activity supporting conscious object recognition has not yet been well defined. Here, the authors describe these networks and show recognition-related category information can be decoded from widespread cortical activity but not subcortical activity.

The human visual system differentially represents subjectively and objectively invisible stimuli

The study of unconscious processing requires a measure of conscious awareness. Awareness measures can be either subjective (based on participant's report) or objective (based on perceptual performance). The preferred awareness measure depends on the theoretical position about consciousness and may influence conclusions about the extent of unconscious processing and about the neural correlates of consciousness. We obtained functional magnetic resonance imaging (fMRI) measurements from 43 subjects while they viewed masked faces and houses that were either subjectively or objectively invisible. Even for objectively invisible (perceptually indiscriminable) stimuli, we found significant category information in both early, lower-level visual areas and in higher-level visual cortex, although representations in anterior, category-selective ventrotemporal areas were less robust. For subjectively invisible stimuli, similar to visible stimuli, there was a clear posterior-to-anterior gradient in visual cortex, with stronger category information in ventrotemporal cortex than in early visual cortex. For objectively invisible stimuli, however, category information remained virtually unchanged from early visual cortex to object- and category-selective visual areas. These results demonstrate that although both objectively and subjectively invisible stimuli are represented in visual cortex, the extent of unconscious information processing is influenced by the measurement approach. Furthermore, our data show that subjective and objective approaches are associated with different neural correlates of consciousness and thus have implications for neural theories of consciousness.

The Discovery and Interpretation of Evidence Accumulation Stages

To improve the understanding of cognitive processing stages, we combined two prominent traditions in cognitive science: evidence accumulation models and stage discovery methods. While evidence accumulation models have been applied to a wide variety of tasks, they are limited to tasks in which decision-making effects can be attributed to a single processing stage. Here, we propose a new method that first uses machine learning to discover processing stages in EEG data and then applies evidence accumulation models to characterize the duration effects in the identified stages. To evaluate this method, we applied it to a previously published associative recognition task (Application 1) and a previously published random dot motion task with a speed-accuracy trade-off manipulation (Application 2). In both applications, the evidence accumulation models accounted better for the data when we first applied the stage-discovery method, and the resulting parameter estimates where generally in line with psychological theories. In addition, in Application 1 the results shed new light on target-foil effects in associative recognition, while in Application 2 the stage discovery method identified an additional stage in the accuracy-focused condition — challenging standard evidence accumulation accounts. We conclude that the new framework provides a powerful new tool to investigate processing stages.

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Sustained attention is a cognitive ability to maintain task focus over extended periods of time (Mackworth, 1948; Chun, Golomb, & Turk-Browne, 2011). In this study, scalp electroencephalography (EEG) signals were processed in real time using a 32 dry-electrode system during a sustained visual attention task. An attention training paradigm was implemented, as designed in DeBettencourt, Cohen, Lee, Norman, and Turk-Browne (2015) in which the composition of a sequence of blended images is updated based on the participant's decoded attentional level to a primed image category. It was hypothesized that a single neurofeedback training session would improve sustained attention abilities. Twenty-two participants were trained on a single neurofeedback session with behavioral pretraining and posttraining sessions within three consecutive days. Half of the participants functioned as controls in a double-blinded design and received sham neurofeedback. During the neurofeedback session, attentional states to primed categories were decoded in real time and used to provide a continuous feedback signal customized to each participant in a closed-loop approach. We report a mean classifier decoding error rate of 34.3% (chance = 50%). Within the neurofeedback group, there was a greater level of task-relevant attentional information decoded in the participant's brain before making a correct behavioral response than before an incorrect response. This effect was not visible in the control group (interaction p=7.23e-4), which strongly indicates that we were able to achieve a meaningful measure of subjective attentional state in real time and control participants' behavior during the neurofeedback session. We do not provide conclusive evidence whether the single neurofeedback session per se provided lasting effects in sustained attention abilities. We developed a portable EEG neurofeedback system capable of decoding attentional states and predicting behavioral choices in the attention task at hand. The neurofeedback code framework is Python based and open source, and it allows users to actively engage in the development of neurofeedback tools for scientific and translational use.

How expectations of pain elicited by consciously and unconsciously perceived cues unfold over time

Expectation can shape the perception of pain within a fraction of time, but little is known about how perceived expectation unfolds over time and modulates pain perception. Here, we combine magnetoencephalography (MEG) and machine learning approaches to track the neural dynamics of expectations of pain in healthy participants with both sexes. We found that the expectation of pain, as conditioned by facial cues, can be decoded from MEG as early as 150 ms and up to 1100 ms after cue onset, but decoding expectation elicited by unconsciously perceived cues requires more time and decays faster compared to consciously perceived ones. Also, results from temporal generalization suggest that neural dynamics of decoding cue-based expectation were predominately sustained during cue presentation but transient after cue presentation. Finally, although decoding expectation elicited by consciously perceived cues were based on a series of time-restricted brain regions during cue presentation, decoding relied on the medial prefrontal cortex and anterior cingulate cortex after cue presentation for both consciously and unconsciously perceived cues. These findings reveal the conscious and unconscious processing of expectation during pain anticipation and may shed light on enhancing clinical care by demonstrating the impact of expectation cues.

Bifurcation in brain dynamics reveals a signature of conscious processing independent of report

An outstanding challenge for consciousness research is to characterize the neural signature of conscious access independently of any decisional processes. Here we present a model-based approach that uses inter-trial variability to identify the brain dynamics associated with stimulus processing. We demonstrate that, even in the absence of any task or behavior, the electroencephalographic response to auditory stimuli shows bifurcation dynamics around 250–300 milliseconds post-stimulus. Namely, the same stimulus gives rise to late sustained activity on some trials, and not on others. This late neural activity is predictive of task-related reports, and also of reports of conscious contents that are randomly sampled during task-free listening. Source localization further suggests that task-free conscious access recruits the same neural networks as those associated with explicit report, except for frontal executive components. Studying brain dynamics through variability could thus play a key role for identifying the core signatures of conscious access, independent of report.

Current knowledge on the neural basis of consciousness mostly relies on situations where people report their perception. Here, the authors provide evidence for the idea that bifurcation in brain dynamics reflects conscious perception independent of report.

Feature-Based Attentional Weighting and Re-weighting in the Absence of Visual Awareness

Visual attention evolved as an adaptive mechanism allowing us to cope with a rapidly changing environment. It enables the facilitated processing of relevant information, often automatically and governed by implicit motives. However, despite recent advances in understanding the relationship between consciousness and visual attention, the functional scope of unconscious attentional control is still under debate. Here, we present a novel masking paradigm in which volunteers were to distinguish between varying orientations of a briefly presented, masked grating stimulus. Combining signal detection theory and subjective measures of awareness, we show that performance on unaware trials was consistent with visual selection being weighted towards repeated orientations of Gabor patches and reallocated in response to a novel unconsciously processed orientation. This was particularly present in trials in which the prior feature was strongly weighted and only if the novel feature was invisible. Thus, our results provide evidence that invisible orientation stimuli can trigger the reallocation of history-guided visual selection weights.

High-pass filtering artifacts in multivariate classification of neural time series data

BACKGROUND

Traditionally, EEG/MEG data are high-pass filtered and baseline-corrected to remove slow drifts. Minor deleterious effects of high-pass filtering in traditional time-series analysis have been well-documented, including temporal displacements. However, its effects on time-resolved multivariate pattern classification analyses (MVPA) are largely unknown.

NEW METHOD

To prevent potential displacement effects, we extend an alternative method of removing slow drift noise - robust detrending - with a procedure in which we mask out all cortical events from each trial. We refer to this method as trial-masked robust detrending.

RESULTS

In both real and simulated EEG data of a working memory experiment, we show that both high-pass filtering and standard robust detrending create artifacts that result in the displacement of multivariate patterns into activity silent periods, particularly apparent in temporal generalization analyses, and especially in combination with baseline correction. We show that trial-masked robust detrending is free from such displacements.

COMPARISON WITH EXISTING METHOD(S)

Temporal displacement may emerge even with modest filter cut-off settings such as 0.05 Hz, and even in regular robust detrending. However, trial-masked robust detrending results in artifact-free decoding without displacements. Baseline correction may unwittingly obfuscate spurious decoding effects and displace them to the rest of the trial.

CONCLUSIONS

Decoding analyses benefit from trial-masked robust detrending, without the unwanted side effects introduced by filtering or regular robust detrending. However, for sufficiently clean data sets and sufficiently strong signals, no filtering or detrending at all may work adequately. Implications for other types of data are discussed, followed by a number of recommendations.

Representational dynamics preceding conscious access

Our senses are continuously bombarded with more information than our brain can process up to the level of awareness. The present study aimed to enhance understanding on how attentional selection shapes conscious access under conditions of rapidly changing input. Using an attention task, EEG, and multivariate decoding of individual target- and distractor-defining features, we specifically examined dynamic changes in the representation of targets and distractors as a function of conscious access and the task-relevance (target or distractor) of the preceding item in the RSVP stream. At the behavioral level, replicating previous work and suggestive of a flexible gating mechanism, we found a significant impairment in conscious access to targets (T2) that were preceded by a target (T1) followed by one or two distractors (i.e., the attentional blink), but striking facilitation of conscious access to targets shown directly after another target (i.e., lag-1 sparing and blink reversal). At the neural level, conscious access to T2 was associated with enhanced early- and late-stage T1 representations and enhanced late-stage D1 representations, and interestingly, could be predicted based on the pattern of EEG activation well before T1 was presented. Yet, across task conditions, we did not find convincing evidence for the notion that conscious access is affected by rapid top-down selection-related modulations of the strength of early sensory representations induced by the preceding visual event. These results cannot easily be explained by existing accounts of how attentional selection shapes conscious access under rapidly changing input conditions, and have important implications for theories of the attentional blink and consciousness more generally.

Perceptually unidentifiable stimuli influence cortical processing and behavioral performance

Our daily behavior is dynamically influenced by conscious and unconscious processes. Although the neural bases of conscious experience have been extensively investigated over the past several decades, how unconscious information impacts neural circuitry and behavior remains unknown. Here, we recorded populations of neurons in macaque primary visual cortex (V1) to find that perceptually unidentifiable stimuli repeatedly presented in the absence of awareness are encoded by neural populations in a way that facilitates their future processing in the context of a behavioral task. Such exposure increases stimulus sensitivity and information encoded in cell populations, even though animals are unaware of stimulus identity. This phenomenon is consistent with a Hebbian mechanism underlying an increase in functional connectivity specifically for the neurons activated by subthreshold stimuli. This form of unsupervised adaptation may constitute a vestigial pre-attention system using the mere frequency of stimulus occurrence to change stimulus representations even when sensory inputs are perceptually invisible.

Classification of evoked responses to inverted faces reveals both spatial and temporal cortical response abnormalities in Autism spectrum disorder

The neurophysiology of face processing has been studied extensively in the context of social impairments associated with autism spectrum disorder (ASD), but the existing studies have concentrated mainly on univariate analyses of responses to upright faces, and, less frequently, inverted faces. The small number of existing studies on neurophysiological responses to inverted face in ASD have used univariate approaches, with divergent results. Here, we used a data-driven, classification-based, multivariate machine learning decoding approach to investigate the temporal and spatial properties of the neurophysiological evoked response for upright and inverted faces, relative to the neurophysiological evoked response for houses, a neutral stimulus. 21 (2 females) ASD and 29 (4 females) TD participants ages 7 to 19 took part in this study. Group level classification accuracies were obtained for each condition, using first the temporal domain of the evoked responses, and then the spatial distribution of the evoked responses on the cortical surface, each separately. We found that classification of responses to inverted neutral faces vs. houses was less accurate in ASD compared to TD, in both the temporal and spatial domains. In contrast, there were no group differences in the classification of evoked responses to upright neutral faces relative to houses. Using the classification in the temporal domain, lower decoding accuracies in ASD were found around 120 ms and 170 ms, corresponding the known components of the evoked responses to faces. Using the classification in the spatial domain, lower decoding accuracies in ASD were found in the right superior marginal gyrus (SMG), intra-parietal sulcus (IPS) and posterior superior temporal sulcus (pSTS), but not in core face processing areas. Importantly, individual classification accuracies from both the temporal and spatial classifiers correlated with ASD severity, confirming the relevance of the results to the ASD phenotype.