Loss of consciousness is related to hyper-correlated gamma-band activity in anesthetized macaques and sleeping humans

Loss of consciousness can result from a wide range of causes, including natural sleep and pharmacologically induced anesthesia. Important insights might thus come from identifying neuronal mechanisms of loss and re-emergence of consciousness independent of a specific manipulation. Therefore, to seek neuronal signatures of loss of consciousness common to sleep and anesthesia we analyzed spontaneous electrophysiological activity recorded in two experiments. First, electrocorticography (ECoG) acquired from 4 macaque monkeys anesthetized with different anesthetic agents (ketamine, medetomidine, propofol) and, second, stereo-electroencephalography (sEEG) from 10 epilepsy patients in different wake-sleep stages (wakefulness, NREM, REM). Specifically, we investigated co-activation patterns among brain areas, defined as correlations between local amplitudes of gamma-band activity. We found that resting wakefulness was associated with intermediate levels of gamma-band coupling, indicating neither complete dependence, nor full independence among brain regions. In contrast, loss of consciousness during NREM sleep and propofol anesthesia was associated with excessively correlated brain activity, as indicated by a robust increase of number and strength of positive correlations. However, such excessively correlated brain signals were not observed during REM sleep, and were present only to a limited extent during ketamine anesthesia. This might be related to the fact that, despite suppression of behavioral responsiveness, REM sleep and ketamine anesthesia often involve presence of dream-like conscious experiences. We conclude that hyper-correlated gamma-band activity might be a signature of loss of consciousness common across various manipulations and independent of behavioral responsiveness.

Deficits in Neurite Density Underlie White Matter Structure Abnormalities in First-Episode Psychosis

BACKGROUND

Structural abnormalities across multiple white matter tracts are recognized in people with early psychosis, consistent with dysconnectivity as a neuropathological account of symptom expression. We applied advanced neuroimaging techniques to characterize microstructural white matter abnormalities for a deeper understanding of the developmental etiology of psychosis.

METHODS

Thirty-five first-episode psychosis patients, and 19 healthy controls, participated in a quantitative neuroimaging study using neurite orientation dispersion and density imaging, a multishell diffusion-weighted magnetic resonance imaging technique that distinguishes white matter fiber arrangement and geometry from changes in neurite density. Fractional anisotropy (FA) and mean diffusivity images were also derived. Tract-based spatial statistics compared white matter structure between patients and control subjects and tested associations with age, symptom severity, and medication.

RESULTS

Patients with first-episode psychosis had lower regional FA in multiple commissural, corticospinal, and association tracts. These abnormalities predominantly colocalized with regions of reduced neurite density, rather than aberrant fiber bundle arrangement (orientation dispersion index). There was no direct relationship with active symptoms. FA decreased and orientation dispersion index increased with age in patients, but not control subjects, suggesting accelerated effects of white matter geometry change.

CONCLUSIONS

Deficits in neurite density appear fundamental to abnormalities in white matter integrity in early psychosis. In the first application of neurite orientation dispersion and density imaging in psychosis, we found that processes compromising axonal fiber number, density, and myelination, rather than processes leading to spatial disruption of fiber organization, are implicated in the etiology of psychosis. This accords with a neurodevelopmental origin of aberrant brain-wide structural connectivity predisposing individuals to psychosis.

Conscious visual memory with minimal attention

Is conscious visual perception limited to the locations that a person attends? The remarkable phenomenon of change blindness, which shows that people miss nearly all unattended changes in a visual scene, suggests the answer is yes. However, change blindness is found after visual interference (a mask or a new scene), so that subjects have to rely on working memory (WM), which has limited capacity, to detect the change. Before such interference, however, a much larger capacity store, called fragile memory (FM), which is easily overwritten by newly presented visual information, is present. Whether these different stores depend equally on spatial attention is central to the debate on the role of attention in conscious vision. In 2 experiments, we found that minimizing spatial attention almost entirely erases visual WM, as expected. Critically, FM remains largely intact. Moreover, minimally attended FM responses yield accurate metacognition, suggesting that conscious memory persists with limited spatial attention. Together, our findings help resolve the fundamental issue of how attention affects perception: Both visual consciousness and memory can be supported by only minimal attention. (PsycINFO Database Record

Theta-burst transcranial magnetic stimulation to the prefrontal or parietal cortex does not impair metacognitive visual awareness

Neuroimaging studies commonly associate dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex with conscious perception. However, such studies only investigate correlation, rather than causation. In addition, many studies conflate objective performance with subjective awareness. In an influential recent paper, Rounis and colleagues addressed these issues by showing that continuous theta burst transcranial magnetic stimulation (cTBS) applied to the DLPFC impaired metacognitive (subjective) awareness for a perceptual task, while objective performance was kept constant. We attempted to replicate this finding, with minor modifications, including an active cTBS control site. Using a between-subjects design for both DLPFC and posterior parietal cortices, we found no evidence of a cTBS-induced metacognitive impairment. In a second experiment, we devised a highly rigorous within-subjects cTBS design for DLPFC, but again failed to find any evidence of metacognitive impairment. One crucial difference between our results and the Rounis study is our strict exclusion of data deemed unsuitable for a signal detection theory analysis. Indeed, when we included this unstable data, a significant, though invalid, metacognitive impairment was found. These results cast doubt on previous findings relating metacognitive awareness to DLPFC, and inform the current debate concerning whether or not prefrontal regions are preferentially implicated in conscious perception.

Global and local complexity of intracranial EEG decreases during NREM sleep

Key to understanding the neuronal basis of consciousness is the characterization of the neural signatures of changes in level of consciousness during sleep. Here we analysed three measures of dynamical complexity on spontaneous depth electrode recordings from 10 epilepsy patients during wakeful rest (WR) and different stages of sleep: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability over time of the set of channels active above a threshold; (iii) synchrony coalition entropy, which measures the variability over time of the set of synchronous channels. When computed across sets of channels that are broadly distributed across multiple brain regions, all three measures decreased substantially in all participants during early-night non-rapid eye movement (NREM) sleep. This decrease was partially reversed during late-night NREM sleep, while the measures scored similar to WR during rapid eye movement (REM) sleep. This global pattern was in almost all cases mirrored at the local level by groups of channels located in a single region. In testing for differences between regions, we found elevated signal complexity in the frontal lobe. These differences could not be attributed solely to changes in spectral power between conditions. Our results provide further evidence that the level of consciousness correlates with neural dynamical complexity.

Allostatic Self-efficacy: A Metacognitive Theory of Dyshomeostasis-Induced Fatigue and Depression

This paper outlines a hierarchical Bayesian framework for interoception, homeostatic/allostatic control, and meta-cognition that connects fatigue and depression to the experience of chronic dyshomeostasis. Specifically, viewing interoception as the inversion of a generative model of viscerosensory inputs allows for a formal definition of dyshomeostasis (as chronically enhanced surprise about bodily signals, or, equivalently, low evidence for the brain's model of bodily states) and allostasis (as a change in prior beliefs or predictions which define setpoints for homeostatic reflex arcs). Critically, we propose that the performance of interoceptive-allostatic circuitry is monitored by a metacognitive layer that updates beliefs about the brain's capacity to successfully regulate bodily states (allostatic self-efficacy). In this framework, fatigue and depression can be understood as sequential responses to the interoceptive experience of dyshomeostasis and the ensuing metacognitive diagnosis of low allostatic self-efficacy. While fatigue might represent an early response with adaptive value (cf. sickness behavior), the experience of chronic dyshomeostasis may trigger a generalized belief of low self-efficacy and lack of control (cf. learned helplessness), resulting in depression. This perspective implies alternative pathophysiological mechanisms that are reflected by differential abnormalities in the effective connectivity of circuits for interoception and allostasis. We discuss suitably extended models of effective connectivity that could distinguish these connectivity patterns in individual patients and may help inform differential diagnosis of fatigue and depression in the future.

Active interoceptive inference and the emotional brain

We review a recent shift in conceptions of interoception and its relationship to hierarchical inference in the brain. The notion of interoceptive inference means that bodily states are regulated by autonomic reflexes that are enslaved by descending predictions from deep generative models of our internal and external milieu. This re-conceptualization illuminates several issues in cognitive and clinical neuroscience with implications for experiences of selfhood and emotion. We first contextualize interoception in terms of active (Bayesian) inference in the brain, highlighting its enactivist (embodied) aspects. We then consider the key role of uncertainty or precision and how this might translate into neuromodulation. We next examine the implications for understanding the functional anatomy of the emotional brain, surveying recent observations on agranular cortex. Finally, we turn to theoretical issues, namely, the role of interoception in shaping a sense of embodied self and feelings. We will draw links between physiological homoeostasis and allostasis, early cybernetic ideas of predictive control and hierarchical generative models in predictive processing. The explanatory scope of interoceptive inference ranges from explanations for autism and depression, through to consciousness. We offer a brief survey of these exciting developments.

This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’.

Fractionation of parietal function in bistable perception probed with concurrent TMS-EEG

When visual input has conflicting interpretations, conscious perception can alternate spontaneously between these possible interpretations. This is called bistable perception. Previous neuroimaging studies have indicated the involvement of two right parietal areas in resolving perceptual ambiguity (ant-SPLr and post-SPLr). Transcranial magnetic stimulation (TMS) studies that selectively interfered with the normal function of these regions suggest that they play opposing roles in this type of perceptual switch. In the present study, we investigated this fractionation of parietal function by use of combined TMS with electroencephalography (EEG). Specifically, while participants viewed either a bistable stimulus, a replay stimulus, or resting-state fixation, we applied single pulse TMS to either location independently while simultaneously recording EEG. Combined with participant’s individual structural magnetic resonance imaging (MRI) scans, this dataset allows for complex analyses of the effect of TMS on neural time series data, which may further elucidate the causal role of the parietal cortex in ambiguous perception.

Rhythmic Influence of Top-Down Perceptual Priors in the Phase of Prestimulus Occipital Alpha Oscillations

Prior expectations have a powerful influence on perception, biasing both decision and confidence. However, how this occurs at the neural level remains unclear. It has been suggested that spontaneous alpha-band neural oscillations represent rhythms of the perceptual system that periodically modulate perceptual judgments. We hypothesized that these oscillations instantiate the effects of expectations. While collecting scalp EEG, participants performed a detection task that orthogonally manipulated perceptual expectations and attention. Trial-by-trial retrospective confidence judgments were also collected. Results showed that, independent of attention, prestimulus occipital alpha phase predicted the weighting of expectations on yes/no decisions. Moreover, phase predicted the influence of expectations on confidence. Thus, expectations periodically bias objective and subjective perceptual decision-making together before stimulus onset. Our results suggest that alpha-band neural oscillations periodically transmit prior evidence to visual cortex, changing the baseline from which evidence accumulation begins. In turn, our results inform accounts of how expectations shape early visual processing.

Effect of coenzyme Q10 alone and its combination with metformin on streptozotocin-nicotinamide-induced diabetic nephropathy in rats

Objectives:

This study was aimed to investigate the therapeutic potential of coenzyme Q10 and its combination with metformin on streptozotocin (STZ)-nicotinamide-induced diabetic nephropathy (DN).

Materials and Methods:

Type 2 diabetes in rats was induced with STZ-nicotinamide. The diabetic rats were treated with coenzyme Q10 (10 mg/kg, p.o.) alone or coenzyme Q10 + metformin. Various parameters of renal function tests such as serum creatinine, urea, uric acid, and markers of oxidative stress such as renal malondialdehyde (MDA) level, superoxide dismutase (SOD), and catalase (CAT) activities were measured. Tumor necrosis factor-α (TNF-α), myeloperoxidase (MPO) activity, transforming growth factor-β (TGF-β), and nitrite content were estimated in renal tissues. All treated animal were subjected to histopathological changes of kidney.

Result:

Diabetic rats showed a significant reduction in renal function, which was reflected with an increase in serum urea, serum creatinine, uric acid. In addition, STZ-nicotinamide caused renal tubular damage with a higher MDA level, depletion of SOD and CAT activity and glutathione (GSH) level. Moreover, TNF-α, MPO activity, TGF-β, and nitrite content were significantly increased in diabetic rats, while treatment with coenzyme Q10 or metformin or their combination ameliorate STZ-nicotinamide induced renal damage due to improvement in renal function, oxidative stress, suppression of TNF-α, MPO activity, TGF-β and nitrite content along with histopathological changes.

Conclusions:

This finding suggests that the treatment with coenzyme Q10 or metformin showed significant renoprotective effect against STZ-nicotinamide-induced DN. However, concomitant administration of both showed a better renoprotective effect than coenzyme Q10 or metformin alone treatment.

Presence, objecthood, and the phenomenology of predictive perception

Can perceptual presence be explained by counterfactually-rich predictive models linking perception and action? Considering an unusually rich range of responses to this idea has led me to (1) re-emphasize the core conceptual commitment of "predictive processing of sensorimotor contingencies" (PPSMC) to predictive model-based perception, (2) reconsider the relationship between presence and objecthood, and (3) refine the phenomenological target by differentiating between perceptual presence and the phenomenology of absence-of-presence, or "phenomenal unreality." It turns out that this requires blue-sky thinking.

Granger causality for state-space models

Granger causality has long been a prominent method for inferring causal interactions between stochastic variables for a broad range of complex physical systems. However, it has been recognized that a moving average (MA) component in the data presents a serious confound to Granger causal analysis, as routinely performed via autoregressive (AR) modeling. We solve this problem by demonstrating that Granger causality may be calculated simply and efficiently from the parameters of a state-space (SS) model. Since SS models are equivalent to autoregressive moving average models, Granger causality estimated in this fashion is not degraded by the presence of a MA component. This is of particular significance when the data has been filtered, downsampled, observed with noise, or is a subprocess of a higher dimensional process, since all of these operations-commonplace in application domains as diverse as climate science, econometrics, and the neurosciences-induce a MA component. We show how Granger causality, conditional and unconditional, in both time and frequency domains, may be calculated directly from SS model parameters via solution of a discrete algebraic Riccati equation. Numerical simulations demonstrate that Granger causality estimators thus derived have greater statistical power and smaller bias than AR estimators. We also discuss how the SS approach facilitates relaxation of the assumptions of linearity, stationarity, and homoscedasticity underlying current AR methods, thus opening up potentially significant new areas of research in Granger causal analysis.

Blind insight: metacognitive discrimination despite chance task performance

Blindsight and other examples of unconscious knowledge and perception demonstrate dissociations between judgment accuracy and metacognition: Studies reveal that participants' judgment accuracy can be above chance while their confidence ratings fail to discriminate right from wrong answers. Here, we demonstrated the opposite dissociation: a reliable relationship between confidence and judgment accuracy (demonstrating metacognition) despite judgment accuracy being no better than chance. We evaluated the judgments of 450 participants who completed an AGL task. For each trial, participants decided whether a stimulus conformed to a given set of rules and rated their confidence in that judgment. We identified participants who performed at chance on the discrimination task, utilizing a subset of their responses, and then assessed the accuracy and the confidence-accuracy relationship of their remaining responses. Analyses revealed above-chance metacognition among participants who did not exhibit decision accuracy. This important new phenomenon, which we term blind insight, poses critical challenges to prevailing models of metacognition grounded in signal detection theory.

An extended case study on the phenomenology of sequence-space synesthesia

Investigation of synesthesia phenomenology in adults is needed to constrain accounts of developmental trajectories of this trait. We report an extended phenomenological investigation of sequence-space synesthesia in a single case (AB). We used the Elicitation Interview (EI) method to facilitate repeated exploration of AB's synesthetic experience. During an EI the subject's attention is selectively guided by the interviewer in order to reveal precise details about the experience. Detailed analysis of the resulting 9 h of interview transcripts provided a comprehensive description of AB's synesthetic experience, including several novel observations. For example, we describe a specific spatial reference frame (a “mental room”) in which AB's concurrents occur, and which overlays his perception of the real world (the “physical room”). AB is able to switch his attention voluntarily between this mental room and the physical room. Exemplifying the EI method, some of our observations were previously unknown even to AB. For example, AB initially reported to experience concurrents following visual presentation, yet we determined that in the majority of cases the concurrent followed an internal verbalization of the inducer, indicating an auditory component to sequence-space synesthesia. This finding is congruent with typical rehearsal of inducer sequences during development, implicating cross-modal interactions between auditory and visual systems in the genesis of this synesthetic form. To our knowledge, this paper describes the first application of an EI to synesthesia, and the first systematic longitudinal investigation of the first-person experience of synesthesia since the re-emergence of interest in this topic in the 1980's. These descriptions move beyond rudimentary graphical or spatial representations of the synesthetic spatial form, thereby providing new targets for neurobehavioral analysis.

Can grapheme-color synesthesia be induced by hypnosis?

Grapheme-color synesthesia is a perceptual experience where graphemes, letters or words evoke a specific color, which are experienced either as spatially coincident with the grapheme inducer (projector sub-type) or elsewhere, perhaps without a definite spatial location (associator sub-type). Here, we address the question of whether synesthesia can be rapidly produced using a hypnotic color suggestion to examine the possibility of "hypnotic synesthesia", i.e., subjectively experienced color hallucinations similar to those experienced by projector synesthetes. We assess the efficacy of this intervention using an "embedded figures" test, in which participants are required to detect a shape (e.g., a square) composed of local graphemic elements. For grapheme-color synesthetes, better performance on the task has been linked to a higher proportion of graphemes perceived as colored. We found no performance benefits on this test when using a hypnotic suggestion, as compared to a no-suggestion control condition. The same result was found when participants were separated according to the degree to which they were susceptible to the suggestion (number of colored trials perceived). However, we found a relationship between accuracy and subjective reports of color in those participants who reported a large proportion of colored trials: trials in which the embedded figure was accurately recognized (relative to trials in which it was not) were associated with reports of more intense colors occupying a greater spatial extent. Collectively, this implies that hypnotic color was only perceived after shape detection rather than aiding in shape detection via color-based perceptual grouping. The results suggest that hypnotically induced colors are not directly comparable to synesthetic ones.

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained ('random'), connection length preserving ('spatial'), and connection length optimised ('reduced') surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain.

Accurate metacognition for visual sensory memory representations

The capacity to attend to multiple objects in the visual field is limited. However, introspectively, people feel that they see the whole visual world at once. Some scholars suggest that this introspective feeling is based on short-lived sensory memory representations, whereas others argue that the feeling of seeing more than can be attended to is illusory. Here, we investigated this phenomenon by combining objective memory performance with subjective confidence ratings during a change-detection task. This allowed us to compute a measure of metacognition--the degree of knowledge that subjects have about the correctness of their decisions--for different stages of memory. We show that subjects store more objects in sensory memory than they can attend to but, at the same time, have similar metacognition for sensory memory and working memory representations. This suggests that these subjective impressions are not an illusion but accurate reflections of the richness of visual perception.

A predictive processing theory of sensorimotor contingencies: Explaining the puzzle of perceptual presence and its absence in synesthesia

Normal perception involves experiencing objects within perceptual scenes as real, as existing in the world. This property of "perceptual presence" has motivated "sensorimotor theories" which understand perception to involve the mastery of sensorimotor contingencies. However, the mechanistic basis of sensorimotor contingencies and their mastery has remained unclear. Sensorimotor theory also struggles to explain instances of perception, such as synesthesia, that appear to lack perceptual presence and for which relevant sensorimotor contingencies are difficult to identify. On alternative "predictive processing" theories, perceptual content emerges from probabilistic inference on the external causes of sensory signals, however, this view has addressed neither the problem of perceptual presence nor synesthesia. Here, I describe a theory of predictive perception of sensorimotor contingencies which (1) accounts for perceptual presence in normal perception, as well as its absence in synesthesia, and (2) operationalizes the notion of sensorimotor contingencies and their mastery. The core idea is that generative models underlying perception incorporate explicitly counterfactual elements related to how sensory inputs would change on the basis of a broad repertoire of possible actions, even if those actions are not performed. These "counterfactually-rich" generative models encode sensorimotor contingencies related to repertoires of sensorimotor dependencies, with counterfactual richness determining the degree of perceptual presence associated with a stimulus. While the generative models underlying normal perception are typically counterfactually rich (reflecting a large repertoire of possible sensorimotor dependencies), those underlying synesthetic concurrents are hypothesized to be counterfactually poor. In addition to accounting for the phenomenology of synesthesia, the theory naturally accommodates phenomenological differences between a range of experiential states including dreaming, hallucination, and the like. It may also lead to a new view of the (in)determinacy of normal perception.

The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference

BACKGROUND

Wiener-Granger causality ("G-causality") is a statistical notion of causality applicable to time series data, whereby cause precedes, and helps predict, effect. It is defined in both time and frequency domains, and allows for the conditioning out of common causal influences. Originally developed in the context of econometric theory, it has since achieved broad application in the neurosciences and beyond. Prediction in the G-causality formalism is based on VAR (vector autoregressive) modelling.

NEW METHOD

The MVGC Matlab© Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy.

RESULTS

In this paper we explain the theoretical basis, computational strategy and application to empirical G-causal inference of the MVGC Toolbox. We also show via numerical simulations the advantages of our Toolbox over previous methods in terms of computational accuracy and statistical inference.

COMPARISON WITH EXISTING METHOD(S)

The standard method of computing G-causality involves estimation of parameters for both a full and a nested (reduced) VAR model. The MVGC approach, by contrast, avoids explicit estimation of the reduced model, thus eliminating a source of estimation error and improving statistical power, and in addition facilitates fast and accurate estimation of the computationally awkward case of conditional G-causality in the frequency domain.

CONCLUSIONS

The MVGC Toolbox implements a flexible, powerful and efficient approach to G-causal inference.

Consciousness in humans and non-human animals: recent advances and future directions

This joint article reflects the authors' personal views regarding noteworthy advances in the neuroscience of consciousness in the last 10 years, and suggests what we feel may be promising future directions. It is based on a small conference at the Samoset Resort in Rockport, Maine, USA, in July of 2012, organized by the Mind Science Foundation of San Antonio, Texas. Here, we summarize recent advances in our understanding of subjectivity in humans and other animals, including empirical, applied, technical, and conceptual insights. These include the evidence for the importance of fronto-parietal connectivity and of “top-down” processes, both of which enable information to travel across distant cortical areas effectively, as well as numerous dissociations between consciousness and cognitive functions, such as attention, in humans. In addition, we describe the development of mental imagery paradigms, which made it possible to identify covert awareness in non-responsive subjects. Non-human animal consciousness research has also witnessed substantial advances on the specific role of cortical areas and higher order thalamus for consciousness, thanks to important technological enhancements. In addition, much progress has been made in the understanding of non-vertebrate cognition relevant to possible conscious states. Finally, major advances have been made in theories of consciousness, and also in their comparison with the available evidence. Along with reviewing these findings, each author suggests future avenues for research in their field of investigation.

The cognitive neuroscience of consciousness

The past decade has seen an explosion of interest in the neural mechanisms underlying consciousness. Experimental approaches from cognitive neuroscience that emphasize converging evidence from multiple methodologies have changed our understanding of how conscious mental states are associated with patterns of brain activity. In this special issue of Cognitive Neuroscience, we bring together five new empirical contributions to this literature plus a new theoretical discussion paper and associated peer commentaries.

Information flow in a kinetic Ising model peaks in the disordered phase

There is growing evidence that for a range of dynamical systems featuring complex interactions between large ensembles of interacting elements, mutual information peaks at order-disorder phase transitions. We conjecture that, by contrast, information flow in such systems will generally peak strictly on the disordered side of a phase transition. This conjecture is verified for a ferromagnetic 2D lattice Ising model with Glauber dynamics and a transfer entropy-based measure of systemwide information flow. Implications of the conjecture are considered, in particular, that for a complex dynamical system in the process of transitioning from disordered to ordered dynamics (a mechanism implicated, for example, in financial market crashes and the onset of some types of epileptic seizures); information dynamics may be able to predict an imminent transition.

What the heart forgets: Cardiac timing influences memory for words and is modulated by metacognition and interoceptive sensitivity

Mental functions are influenced by states of physiological arousal. Afferent neural activity from arterial baroreceptors at systole conveys the strength and timing of individual heartbeats to the brain. We presented words under limited attentional resources time-locked to different phases of the cardiac cycle, to test a hypothesis that natural baroreceptor stimulation influences detection and subsequent memory of words. We show memory for words presented around systole was decreased relative to words at diastole. The deleterious memory effect of systole was greater for words detected with low confidence and amplified in individuals with low interoceptive sensitivity, as indexed using a heartbeat counting task. Our observations highlight an important cardiovascular channel through which autonomic arousal impacts a cognitive function, an effect mitigated by metacognition (perceptual confidence) and interoceptive sensitivity.

Modes and models in disorders of consciousness science

The clinical assessment of non-communicative brain damaged patients is extremely difficult and there is a need for paraclinical diagnostic markers of the level of consciousness. In the last few years, progress within neuroimaging has led to a growing body of studies investigating vegetative state and minimally conscious state patients, which can be classified in two main approaches. Active neuroimaging paradigms search for a response to command without requiring a motor response. Passive neuroimaging paradigms investigate spontaneous brain activity and brain responses to external stimuli and aim at identifying neural correlates of consciousness. Other passive paradigms eschew neuroimaging in favour of behavioural markers which reliably distinguish conscious and unconscious conditions in healthy controls. In order to furnish accurate diagnostic criteria, a mechanistic explanation of how the brain gives rise to consciousness seems desirable. Mechanistic and theoretical approaches could also ultimately lead to a unification of passive and active paradigms in a coherent diagnostic approach. In this paper, we survey current passive and active paradigms available for diagnosis of residual consciousness in vegetative state and minimally conscious patients. We then review the current main theories of consciousness and see how they can apply in this context. Finally, we discuss some avenues for future research in this domain.

Analysing connectivity with Granger causality and dynamic causal modelling

This review considers state-of-the-art analyses of functional integration in neuronal macrocircuits. We focus on detecting and estimating directed connectivity in neuronal networks using Granger causality (GC) and dynamic causal modelling (DCM). These approaches are considered in the context of functional segregation and integration and--within functional integration--the distinction between functional and effective connectivity. We review recent developments that have enjoyed a rapid uptake in the discovery and quantification of functional brain architectures. GC and DCM have distinct and complementary ambitions that are usefully considered in relation to the detection of functional connectivity and the identification of models of effective connectivity. We highlight the basic ideas upon which they are grounded, provide a comparative evaluation and point to some outstanding issues.

A study on knowledge, beliefs and attitude towards leprosy in students of Jaipur, Rajasthan

The objective of this study was to determine the knowledge, beliefs and attitudes regarding leprosy in school students of Jaipur district. A cross-sectional study was conducted from August 2010 to February 2011 on 1199 students (rural and urban) studying in class 10th and above. The findings of this study showed fair knowledge in students about cause, signs and symptoms of leprosy but less knowledge about prevention and treatment of the disease. Myths and beliefs were more prevalent in rural students as compared to urban ones. Both the groups showed positive attitude toward leprosy with 30-50% students showing neutral approach but negative reaction was more in rural students. In conclusion the study highlights to emphasize on health education in students and improving knowledge to develop positive attitude towards leprosy.

Multi-neuronal refractory period adapts centrally generated behaviour to reward

Oscillating neuronal circuits, known as central pattern generators (CPGs), are responsible for generating rhythmic behaviours such as walking, breathing and chewing. The CPG model alone however does not account for the ability of animals to adapt their future behaviour to changes in the sensory environment that signal reward. Here, using multi-electrode array (MEA) recording in an established experimental model of centrally generated rhythmic behaviour we show that the feeding CPG of Lymnaea stagnalis is itself associated with another, and hitherto unidentified, oscillating neuronal population. This extra-CPG oscillator is characterised by high population-wide activity alternating with population-wide quiescence. During the quiescent periods the CPG is refractory to activation by food-associated stimuli. Furthermore, the duration of the refractory period predicts the timing of the next activation of the CPG, which may be minutes into the future. Rewarding food stimuli and dopamine accelerate the frequency of the extra-CPG oscillator and reduce the duration of its quiescent periods. These findings indicate that dopamine adapts future feeding behaviour to the availability of food by significantly reducing the refractory period of the brain's feeding circuitry.

Consciousness and the prefrontal parietal network: insights from attention, working memory, and chunking

Consciousness has of late become a “hot topic” in neuroscience. Empirical work has centered on identifying potential neural correlates of consciousness (NCCs), with a converging view that the prefrontal parietal network (PPN) is closely associated with this process. Theoretical work has primarily sought to explain how informational properties of this cortical network could account for phenomenal properties of consciousness. However, both empirical and theoretical research has given less focus to the psychological features that may account for the NCCs. The PPN has also been heavily linked with cognitive processes, such as attention. We describe how this literature is under-appreciated in consciousness science, in part due to the increasingly entrenched assumption of a strong dissociation between attention and consciousness. We argue instead that there is more common ground between attention and consciousness than is usually emphasized: although objects can under certain circumstances be attended to in the absence of conscious access, attention as a content selection and boosting mechanism is an important and necessary aspect of consciousness. Like attention, working memory and executive control involve the interlinking of multiple mental objects and have also been closely associated with the PPN. We propose that this set of cognitive functions, in concert with attention, make up the core psychological components of consciousness. One related process, chunking, exploits logical or mnemonic redundancies in a dataset so that it can be recoded and a given task optimized. Chunking has been shown to activate PPN particularly robustly, even compared with other cognitively demanding tasks, such as working memory or mental arithmetic. It is therefore possible that chunking, as a tool to detect useful patterns within an integrated set of intensely processed (attended) information, has a central role to play in consciousness. Following on from this, we suggest that a key evolutionary purpose of consciousness may be to provide innovative solutions to complex or novel problems.

An interoceptive predictive coding model of conscious presence

We describe a theoretical model of the neurocognitive mechanisms underlying conscious presence and its disturbances. The model is based on interoceptive prediction error and is informed by predictive models of agency, general models of hierarchical predictive coding and dopaminergic signaling in cortex, the role of the anterior insular cortex (AIC) in interoception and emotion, and cognitive neuroscience evidence from studies of virtual reality and of psychiatric disorders of presence, specifically depersonalization/derealization disorder. The model associates presence with successful suppression by top-down predictions of informative interoceptive signals evoked by autonomic control signals and, indirectly, by visceral responses to afferent sensory signals. The model connects presence to agency by allowing that predicted interoceptive signals will depend on whether afferent sensory signals are determined, by a parallel predictive-coding mechanism, to be self-generated or externally caused. Anatomically, we identify the AIC as the likely locus of key neural comparator mechanisms. Our model integrates a broad range of previously disparate evidence, makes predictions for conjoint manipulations of agency and presence, offers a new view of emotion as interoceptive inference, and represents a step toward a mechanistic account of a fundamental phenomenological property of consciousness.

Granger causality analysis of steady-state electroencephalographic signals during propofol-induced anaesthesia

Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal) connectivity as reflected in quantities such as 'integrated information' and 'causal density'. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG) signals using Granger causality (GC). Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness.

The Enactive Torch: A New Tool for the Science of Perception

The cognitive sciences are increasingly coming to terms with the embodied, embedded, extended, and experiential aspects of the mind. Exemplifying this shift, the enactive approach points to an essential role of goal-directed bodily activity in the generation of meaningful perceptual experience, i.e., sense-making. Here, building on recent insights into the transformative effects of practical tool-use, we make use of the enactive approach in order to provide a definition of an enactive interface in terms of augmented sense-making. We introduce such a custom-built interface, the Enactive Torch, and present a study of its experiential effects. The results demonstrate that the user experience is not adequately captured by any standardly assumed perceptual modality; rather, it is a new feeling that is mediated by the design of the device and shaped by the overall situation of the task. Taken together these findings show that there is much to be gained by synergies between engineering and the cognitive sciences in the creation of new experience-centered technology. We suggest that the guiding principle should be the design of interfaces that serve as a transparent medium for augmenting our natural skills of interaction with the world, instead of requiring conscious attention to the interface as an opaque object in the world.