Feedback information transfer in the human brain reflects bistable perception in the absence of report.

In the search for the neural basis of conscious experience, perception and the cognitive processes associated with reporting perception 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 bistable visual stimulus that instantiates two well-known properties of conscious perception: integration and differentiation. At any given moment, observers either perceive the stimulus as one integrated unitary object or as two differentiated objects that are clearly distinct from each other. Using electroencephalography, we show that measures of integration and differentiation based on information theory closely follow participants' perceptual experience of those contents when switches were reported. We observed increased information integration between anterior to posterior electrodes (front to back) prior to a switch to the integrated percept, and higher information differentiation of anterior signals leading up to reporting the differentiated percept. Crucially, information integration was closely linked to perception and even observed in a no-report condition when perceptual transitions were inferred from eye movements alone. In contrast, the link between neural differentiation and perception was observed solely in the active report condition. Our results, therefore, suggest that perception and the processes associated with report require distinct amounts of anterior-posterior network communication and anterior information differentiation. While front-to-back directed information is associated with changes in the content of perception when viewing bistable visual stimuli, regardless of report, frontal information differentiation was absent in the no-report condition and therefore is not directly linked to perception per se.

Broadband Dynamics Rather than Frequency-Specific Rhythms Underlie Prediction Error in the Primate Auditory Cortex.

Detection of statistical irregularities, measured as a prediction error response, is fundamental to the perceptual monitoring of the environment. We studied whether prediction error response is associated with neural oscillations or asynchronous broadband activity. Electrocorticography was conducted in three male monkeys, who passively listened to the auditory roving oddball stimuli. Local field potentials (LFPs) recorded over the auditory cortex underwent spectral principal component analysis, which decoupled broadband and rhythmic components of the LFP signal. We found that the broadband component captured the prediction error response, whereas none of the rhythmic components were associated with statistical irregularities of sounds. The broadband component displayed more stochastic, asymmetrical multifractal properties than the rhythmic components, which revealed more self-similar dynamics. We thus conclude that the prediction error response is captured by neuronal populations generating asynchronous broadband activity, defined by irregular dynamic states, which, unlike oscillatory rhythms, appear to enable the neural representation of auditory prediction error response.SIGNIFICANCE STATEMENT This study aimed to examine the contribution of oscillatory and asynchronous components of auditory local field potentials in the generation of prediction error responses to sensory irregularities, as this has not been directly addressed in the previous studies. Here, we show that mismatch negativity-an auditory prediction error response-is driven by the asynchronous broadband component of potentials recorded in the auditory cortex. This finding highlights the importance of nonoscillatory neural processes in the predictive monitoring of the environment. At a more general level, the study demonstrates that stochastic neural processes, which are often disregarded as neural noise, do have a functional role in the processing of sensory information.

Ketamine and sleep modulate neural complexity dynamics in cats.

There is increasing evidence that the level of consciousness can be captured by neural informational complexity: for instance, complexity, as measured by the Lempel Ziv (LZ) compression algorithm, decreases during anaesthesia and non-rapid eye movement (NREM) sleep in humans and rats, when compared with LZ in awake and REM sleep. In contrast, LZ is higher in humans under the effect of psychedelics, including subanaesthetic doses of ketamine. However, it is both unclear how this result would be modulated by varying ketamine doses, and whether it would extend to other species. Here, we studied LZ with and without auditory stimulation during wakefulness and different sleep stages in five cats implanted with intracranial electrodes, as well as under subanaesthetic doses of ketamine (5, 10, and 15 mg/kg i.m.). In line with previous results, LZ was lowest in NREM sleep, but similar in REM and wakefulness. Furthermore, we found an inverted U-shaped curve following different levels of ketamine doses in a subset of electrodes, primarily in prefrontal cortex. However, it is worth noting that the variability in the ketamine dose-response curve across cats and cortices was larger than that in the sleep-stage data, highlighting the differential local dynamics created by two different ways of modulating conscious state. These results replicate previous findings, both in humans and other species, demonstrating that neural complexity is highly sensitive to capture state changes between wake and sleep stages while adding a local cortical description. Finally, this study describes the differential effects of ketamine doses, replicating a rise in complexity for low doses, and further fall as doses approach anaesthetic levels in a differential manner depending on the cortex.

Decreased Alertness Reconfigures Cognitive Control Networks.

Humans' remarkable capacity to flexibly adapt their behavior based on rapid situational changes is termed cognitive control. Intuitively, cognitive control is thought to be affected by the state of alertness; for example, when drowsy, we feel less capable of adequately implementing effortful cognitive tasks. Although scientific investigations have focused on the effects of sleep deprivation and circadian time, little is known about how natural daily fluctuations in alertness in the regular awake state affect cognitive control. Here we combined a conflict task in the auditory domain with EEG neurodynamics to test how neural and behavioral markers of conflict processing are affected by fluctuations in alertness. Using a novel computational method, we segregated alert and drowsy trials from two testing sessions and observed that, although participants (both sexes) were generally sluggish, the typical conflict effect reflected in slower responses to conflicting information compared with nonconflicting information, as well as the moderating effect of previous conflict (conflict adaptation), were still intact. However, the typical neural markers of cognitive control-local midfrontal theta-band power changes-that participants show during full alertness were no longer noticeable when alertness decreased. Instead, when drowsy, we found an increase in long-range information sharing (connectivity) between brain regions in the same frequency band. These results show the resilience of the human cognitive control system when affected by internal fluctuations of alertness and suggest that there are neural compensatory mechanisms at play in response to physiological pressure during diminished alertness.SIGNIFICANCE STATEMENT The normal variability in alertness we experience in daily tasks is rarely taken 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 characterization of alertness modulating cognitive control. The changes in the neural signatures of conflict from local theta oscillations to a long-distance distributed theta network suggest a reconfiguration of the underlying neural processes subserving cognitive control when affected by alertness fluctuations.

Beyond imagination: Hypnotic visual hallucination induces greater lateralised brain activity than visual mental imagery.

Hypnotic suggestions can produce a broad range of perceptual experiences, including hallucinations. Visual hypnotic hallucinations differ in many ways from regular mental images. For example, they are usually experienced as automatic, vivid, and real images, typically compromising the sense of reality. While both hypnotic hallucination and mental imagery are believed to mainly rely on the activation of the visual cortex via top-down mechanisms, it is unknown how they differ in the neural processes they engage. Here we used an adaptation paradigm to test and compare top-down processing between hypnotic hallucination, mental imagery, and visual perception in very highly hypnotisable individuals whose ability to hallucinate was assessed. By measuring the N170/VPP event-related complex and using multivariate decoding analysis, we found that hypnotic hallucination of faces involves greater top-down activation of sensory processing through lateralised neural mechanisms in the right hemisphere compared to mental imagery. Our findings suggest that the neural signatures that distinguish hypnotically hallucinated faces from imagined faces lie in the right brain hemisphere.

Neural Dynamics of Associative Learning during Human Sleep.

Recent evidence indicates that humans can learn entirely new information during sleep. To elucidate the neural dynamics underlying sleep-learning, we investigated brain activity during auditory-olfactory discriminatory associative learning in human sleep. We found that learning-related delta and sigma neural changes are involved in early acquisition stages, when new associations are being formed. In contrast, learning-related theta activity emerged in later stages of the learning process, after tone-odor associations were already established. These findings suggest that learning new associations during sleep is signaled by a dynamic interplay between slow-waves, sigma, and theta activity.

Dissociable Neural Information Dynamics of Perceptual Integration and Differentiation during Bistable Perception.

At any given moment, we experience a perceptual scene as a single whole and yet we may distinguish a variety of objects within it. This phenomenon instantiates two properties of conscious perception: integration and differentiation. Integration is the property of experiencing a collection of objects as a unitary percept and differentiation is the property of experiencing these objects as distinct from each other. Here, we evaluated the neural information dynamics underlying integration and differentiation of perceptual contents during bistable perception. Participants listened to a sequence of tones (auditory bistable stimuli) experienced either as a single stream (perceptual integration) or as two parallel streams (perceptual differentiation) of sounds. We computed neurophysiological indices of information integration and information differentiation with electroencephalographic and intracranial recordings. When perceptual alternations were endogenously driven, the integrated percept was associated with an increase in neural information integration and a decrease in neural differentiation across frontoparietal regions, whereas the opposite pattern was observed for the differentiated percept. However, when perception was exogenously driven by a change in the sound stream (no bistability), neural oscillatory power distinguished between percepts but information measures did not. We demonstrate that perceptual integration and differentiation can be mapped to theoretically motivated neural information signatures, suggesting a direct relationship between phenomenology and neurophysiology.

Alertness fluctuations when performing a task modulate cortical evoked responses to transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) has been widely used in human cognitive neuroscience to examine the causal role of distinct cortical areas in perceptual, cognitive and motor functions. However, it is widely acknowledged that the effects of focal cortical stimulation can vary substantially between participants and even from trial to trial within individuals. Recent work from resting state functional magnetic resonance imaging (fMRI) studies has suggested that spontaneous fluctuations in alertness over a testing session can modulate the neural dynamics of cortical processing, even when participants remain awake and responsive to the task at hand. Here we investigated the extent to which spontaneous fluctuations in alertness during wake-to-sleep transition can account for the variability in neurophysiological responses to TMS. We combined single-pulse TMS with neural recording via electroencephalography (EEG) to quantify changes in motor and cortical reactivity with fluctuating levels of alertness defined objectively on the basis of ongoing brain activity. We observed rapid, non-linear changes in TMS-evoked responses with decreasing levels of alertness, even while participants remained responsive in the behavioural task. Specifically, we found that the amplitude of motor evoked potentials peaked during periods of EEG flattening, whereas TMS-evoked potentials increased and remained stable during EEG flattening and the subsequent occurrence of theta ripples that indicate the onset of NREM stage 1 sleep. Our findings suggest a rapid and complex reorganization of active neural networks in response to spontaneous fluctuations of alertness over relatively short periods of behavioural testing during wake-to-sleep transition.

Auditory Feedback Differentially Modulates Behavioral and Neural Markers of Objective and Subjective Performance When Tapping to Your Heartbeat.

Interoception, the perception of our body internal signals, plays a key role in maintaining homeostasis and guiding our behavior. Sometimes, we become aware of our body signals and use them in planning and strategic thinking. Here, we show behavioral and neural dissociations between learning to follow one's own heartbeat and metacognitive awareness of one's performance, in a heartbeat-tapping task performed before and after auditory feedback. The electroencephalography amplitude of the heartbeat-evoked potential in interoceptive learners, that is, participants whose accuracy of tapping to their heartbeat improved after auditory feedback, was higher compared with non-learners. However, an increase in gamma phase synchrony (30-45 Hz) after the heartbeat auditory feedback was present only in those participants showing agreement between objective interoceptive performance and metacognitive awareness. Source localization in a group of participants and direct cortical recordings in a single patient identified a network hub for interoceptive learning in the insular cortex. In summary, interoceptive learning may be mediated by the right insular response to the heartbeat, whereas metacognitive awareness of learning may be mediated by widespread cortical synchronization patterns.

Spectral signatures of reorganised brain networks in disorders of consciousness.

Theoretical advances in the science of consciousness have proposed that it is concomitant with balanced cortical integration and differentiation, enabled by efficient networks of information transfer across multiple scales. Here, we apply graph theory to compare key signatures of such networks in high-density electroencephalographic data from 32 patients with chronic disorders of consciousness, against normative data from healthy controls. Based on connectivity within canonical frequency bands, we found that patient networks had reduced local and global efficiency, and fewer hubs in the alpha band. We devised a novel topographical metric, termed modular span, which showed that the alpha network modules in patients were also spatially circumscribed, lacking the structured long-distance interactions commonly observed in the healthy controls. Importantly however, these differences between graph-theoretic metrics were partially reversed in delta and theta band networks, which were also significantly more similar to each other in patients than controls. Going further, we found that metrics of alpha network efficiency also correlated with the degree of behavioural awareness. Intriguingly, some patients in behaviourally unresponsive vegetative states who demonstrated evidence of covert awareness with functional neuroimaging stood out from this trend: they had alpha networks that were remarkably well preserved and similar to those observed in the controls. Taken together, our findings inform current understanding of disorders of consciousness by highlighting the distinctive brain networks that characterise them. In the significant minority of vegetative patients who follow commands in neuroimaging tests, they point to putative network mechanisms that could support cognitive function and consciousness despite profound behavioural impairment.

[Validity evidence of the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in Chile]. / Evidencia de validez en Chile del Alcohol, Smoking and Substance Involvement Screening Test (ASSIST).

This study aims to psychometrically validate the Chilean version of the Alcohol, Smoking and Substance Involvement Screening Test ASSIST. Specifically, this study is interested in evaluating the reliability, consistency and concurrent and discriminant validity of this instrument. The sample was composed for a total of 400 people from four different settings: treatment centers (residential and ambulatories), primary health care, police stations and companies. The reliability of the ASSIST was high (α = .86 for Alcohol, α = .84 for marijuana and α = .90 for cocaine). The intra class correlation coefficient (ICC) with test-retest comparison was statistically significant for Alcohol (ICC = .66), marijuana (ICC = .74) and cocaine (ICC = .80). There were statistically significant correlations between the ASSIST and the AUDIT score (Pearson’s r = .85), the ASSIST and the ASI-Lite score (r between .66 and .83 for tobacco, alcohol, marijuana and cocaine), and the ASSIST and the SDS score (r = .65). The original cutoff point for high risk detection was 27 points, however, in order to have a better balance between sensitivity and specificity the cut was changed to 21 points. The ASSIST presents good psychometric properties and therefore is a reliable and valid instrument to be used as a mechanism to detect risk levels of substance use in the Chilean population.

Staying in control: Characterizing the mechanisms underlying cognitive control in high and low arousal states.

Throughout the day, humans show natural fluctuations in arousal that impact cognitive function. To study the behavioural dynamics of cognitive control during high and low arousal states, healthy participants performed an auditory conflict task during high-intensity physical exercise (N = 39) or drowsiness (N = 33). In line with the pre-registered hypotheses, conflict and conflict adaptation effects were preserved during both altered arousal states. Overall task performance was markedly poorer during low arousal, but not for high arousal. Modelling behavioural dynamics with drift diffusion analysis revealed evidence accumulation and non-decision time decelerated, and decisional boundaries became wider during low arousal, whereas high arousal was unexpectedly associated with a decrease in the interference of task-irrelevant information processing. These findings show how arousal differentially modulates cognitive control at both sides of normal alertness, and further validate drowsiness and physical exercise as key experimental models to disentangle the interaction between physiological fluctuations on cognitive dynamics.

Slow-wave brain connectivity predicts executive functioning and group belonging in socially vulnerable individuals.

Important efforts have been made to describe the neural and cognitive features of healthy and clinical populations. However, the neural and cognitive features of socially vulnerable individuals remain largely unexplored, despite their proneness to developing neurocognitive disorders. Socially vulnerable individuals can be characterised as socially deprived, having a low socioeconomic status, suffering from chronic social stress, and exhibiting poor social adaptation. While it is known that such individuals are likely to perform worse than their peers on executive function tasks, studies on healthy but socially vulnerable groups are lacking. In the current study, we explore whether neural power and connectivity signatures can characterise executive function performance in healthy but socially vulnerable individuals, shedding light on the impairing effects that chronic stress and social disadvantages have on cognition. We measured resting-state electroencephalography and executive functioning in 38 socially vulnerable participants and 38 matched control participants. Our findings indicate that while neural power was uninformative, lower delta and theta phase synchrony are associated with worse executive function performance in all participants, whereas delta phase synchrony is higher in the socially vulnerable group compared to the control group. Finally, we found that delta phase synchrony and years of schooling are the best predictors for belonging to the socially vulnerable group. Overall, these findings suggest that exposure to chronic stress due to socioeconomic factors and a lack of education are associated with changes in slow-wave neural connectivity and executive functioning.

Distributed representations of prediction error signals across the cortical hierarchy are synergistic.

A relevant question concerning inter-areal communication in the cortex is whether these interactions are synergistic. Synergy refers to the complementary effect of multiple brain signals conveying more information than the sum of each isolated signal. Redundancy, on the other hand, refers to the common information shared between brain signals. Here, we dissociated cortical interactions encoding complementary information (synergy) from those sharing common information (redundancy) during prediction error (PE) processing. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded synergistic and redundant information about PE processing. The information conveyed by ERPs and BB signals was synergistic even at lower stages of the hierarchy in the auditory cortex and between auditory and frontal regions. Using a brain-constrained neural network, we simulated the synergy and redundancy observed in the experimental results and demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback, and feedforward connections. These results indicate that distributed representations of PE signals across the cortical hierarchy can be highly synergistic.

Preliminary evidence about the effects of meditation on interoceptive sensitivity and social cognition.

BACKGROUND: Interoception refers to the conscious perception of body signals. Mindfulness is a meditation practice that encourages individuals to focus on their internal experiences such as bodily sensations, thoughts, and emotions. In this study, we selected a behavioral measure of interoceptive sensitivity (heartbeat detection task, HBD) to compare the effect of meditation practice on interoceptive sensitivity among long term practitioners (LTP), short term meditators (STM, subjects that completed a Mindfulness-Based Stress Reduction (MBSR) program) and controls (non-meditators). All participants were examined with a battery of different tasks including mood state, executive function and social cognition tests (emotion recognition, empathy and theory of mind). FINDINGS: Compared to controls, both meditators' groups showed lower levels of anxiety and depression, but no improvement in executive function or social cognition performance was observed (except for lower scores compared to controls only in the personal distress dimension of empathy). More importantly, meditators' performance did not differ from that of nonmeditators regarding cardiac interoceptive sensitivity. CONCLUSION: Results suggest no influence of meditation practice in cardiac interoception and in most related social cognition measures. These negative results could be partially due to the fact that awareness of heartbeat sensations is not emphasized during mindfulness/vipassana meditation and may not be the best index of the awareness supported by the practice of meditation.

[Francisco Varela's neurophenomenology of time: temporality of consciousness explained?]. / Neurofenomenologia del tiempo segun Francisco Varela: ¿la temporalidad de la conciencia explicada?

This article attempts to clarify Francisco Varela's proposal of a neurophenomenology of time consciousness in the light of distinctions based on the philosophical literature of phenomenology and recent advances of neurobiology. The analysis is carried out considering three aspects. In the first of them, we discuss the phenomenological aspect of consciousness, accessible in first-person, which describes time as a structure with three inseparable moments (past-present-future) and three levels of temporality, and not merely as the chronometric time or clock time. In the second one, we analyze the neurobiological aspect of consciousness that tends to "explain" the phenomenological time in terms of three possible levels of neuronal integration. Thus, we propose a correspondence between the levels of phenomenological time and neural integration processes. Finally, we try to analyze this "correspondence" and the issues that follow from this by considering that the notion of time in this correspondence is, in essence, the clock time and not the phenomenological time consciousness.

Cortical, muscular, and kinetic activity underpinning attentional focus strategies during visuomotor control.

Focusing internally on movement control or bodily sensations is frequently shown to disrupt the effectiveness and efficiency of motor control when compared to focusing externally on the outcome of movement. Whilst the behavioral consequences of these attentional strategies are well-documented, it is unclear how they are explained at the corticomuscular level. The aim of the present study was to investigate how attentional focus strategies affect kinetic, cortical, muscular, and corticomuscular activity during an isometric force precision task. In a repeated measures design, we measured force, EEG and EMG activity from twenty-seven participants who performed isometric contractions of the right hand whilst encouraged to adopt either an internal or external focus through a combination of instructions, secondary tasks, and self-report evaluations. Results indicated that focusing internally led to poorer force accuracy and steadiness compared to an external focus. An internal focus also increased muscle activity of the forearm flexor, increased EEG alpha activity across the parieto-occipital cortex, lowered frontal midline EEG theta activity, and lowered beta corticomuscular coherence between the forearm flexor and contralateral motor cortex. The results of this study provide a holistic understanding of how attentional focus strategies alter corticomuscular control during an isometric force precision task, paving the way for exploring how the behavioral consequences of attentional strategies can be explained at the corticomuscular levels across a wide range of motor tasks and contexts.

Principles of large-scale neural interactions.

What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-through-communication). We discuss major challenges for communication-through-coherence based on layer- and cell-type-specific analyses of spike phase-locking, heterogeneity of dynamics across networks and states, and computational models for selective communication. We argue that resonance and non-linear integration are viable alternative mechanisms that facilitate computation and selective communication in recurrent networks. Finally, we consider communication in relation to cortical hierarchy and critically examine the hypothesis that feedforward and feedback communication use fast (gamma) and slow (alpha/beta) frequencies, respectively. Instead, we propose that feedforward propagation of prediction errors relies on the non-linear amplification of aperiodic transients, whereas gamma and beta rhythms represent rhythmic equilibrium states that facilitate sustained and efficient information encoding and amplification of short-range feedback via resonance.

[Early evaluation of Alzheimer's disease: biomarkers and neuropsychological tests]. / Evaluación de la enfermedad de Alzheimer en etapa temprana: biomarcadores y pruebas neuropsicológicas.

BACKGROUND: Alzheimer disease is a neurodegenerative condition that affects cognitive, behavioral and global functioning of patients. Currently and due to the lack of conclusive biological testing, Alzheimer's disease diagnosis is based primarily on clinical criteria. Since its early diagnosis allows clinical interventions when neurological damage is relatively mild, the development of early detection tools has become a major topic of interest. In this article, we review the main neuro-biological and neuropsychological features of Alzheimer's disease, analyzing the use of biomarkers and neuropsychological testing for early detection.