Neuroscience of Consciousness 

About: Neuroscience of Consciousness is an academic journal published by University of Oxford. The journal publishes majorly in the area(s): Consciousness & Medicine. It has an ISSN identifier of 2057-2107. It is also open access. Over the lifetime, 187 publications have been published receiving 2972 citations.

HMeta-d: hierarchical Bayesian estimation of metacognitive efficiency from confidence ratings.

Abstract: Metacognition refers to the ability to reflect on and monitor one's cognitive processes, such as perception, memory and decision-making. Metacognition is often assessed in the lab by whether an observer's confidence ratings are predictive of objective success, but simple correlations between performance and confidence are susceptible to undesirable influences such as response biases. Recently, an alternative approach to measuring metacognition has been developed (Maniscalco and Lau 2012) that characterizes metacognitive sensitivity (meta-d') by assuming a generative model of confidence within the framework of signal detection theory. However, current estimation routines require an abundance of confidence rating data to recover robust parameters, and only provide point estimates of meta-d'. In contrast, hierarchical Bayesian estimation methods provide opportunities to enhance statistical power, incorporate uncertainty in group-level parameter estimates and avoid edge-correction confounds. Here I introduce such a method for estimating metacognitive efficiency (meta-d'/d') from confidence ratings and demonstrate its application for assessing group differences. A tutorial is provided on both the meta-d' model and the preparation of behavioural data for model fitting. Through numerical simulations I show that a hierarchical approach outperforms alternative fitting methods in situations where limited data are available, such as when quantifying metacognition in patient populations. In addition, the model may be flexibly expanded to estimate parameters encoding other influences on metacognitive efficiency. MATLAB software and documentation for implementing hierarchical meta-d' estimation (HMeta-d) can be downloaded at https://github.com/smfleming/HMeta-d.

New directions in hypnosis research: strategies for advancing the cognitive and clinical neuroscience of hypnosis

Abstract: This article summarizes key advances in hypnosis research during the past two decades, including (i) clinical research supporting the efficacy of hypnosis for managing a number of clinical symptoms and conditions, (ii) research supporting the role of various divisions in the anterior cingulate and prefrontal cortices in hypnotic responding, and (iii) an emerging finding that high hypnotic suggestibility is associated with atypical brain connectivity profiles. Key recommendations for a research agenda for the next decade include the recommendations that (i) laboratory hypnosis researchers should strongly consider how they assess hypnotic suggestibility in their studies, (ii) inclusion of study participants who score in the middle range of hypnotic suggestibility, and (iii) use of expanding research designs that more clearly delineate the roles of inductions and specific suggestions. Finally, we make two specific suggestions for helping to move the field forward including (i) the use of data sharing and (ii) redirecting resources away from contrasting state and nonstate positions toward studying (a) the efficacy of hypnotic treatments for clinical conditions influenced by central nervous system processes and (b) the neurophysiological underpinnings of hypnotic phenomena. As we learn more about the neurophysiological mechanisms underlying hypnosis and suggestion, we will strengthen our knowledge of both basic brain functions and a host of different psychological functions.

The signal processing architecture underlying subjective reports of sensory awareness.

Abstract: What is the relationship between perceptual information processing and subjective perceptual experience? Empirical dissociations between stimulus identification performance and subjective reports of stimulus visibility are crucial for shedding light on this question. We replicated a finding that metacontrast masking can produce such a dissociation (Lau and Passingham, 2006), and report a novel finding that this paradigm can also dissociate stimulus identification performance from the efficacy with which visibility ratings predict task performance. We explored various hypotheses about the relationship between perceptual task performance and visibility rating by implementing them in computational models and using formal model comparison techniques to assess which ones best captured the unusual patterns in the data. The models fell into three broad categories: Single Channel models, which hold that task performance and visibility ratings are based on the same underlying source of information; Dual Channel models, which hold that there are two independent processing streams that differentially contribute to task performance and visibility rating; and Hierarchical models, which hold that a late processing stage generates visibility ratings by evaluating the quality of early perceptual processing. Taking into account the quality of data fitting and model complexity, we found that Hierarchical models perform best at capturing the observed behavioral dissociations. Because current theories of visual awareness map well onto these different model structures, a formal comparison between them is a powerful approach for arbitrating between the different theories.

Self unbound: ego dissolution in psychedelic experience

Abstract: Users of psychedelic drugs often report that their sense of being a self or ‘I’ distinct from the rest of the world has diminished or altogether dissolved. Neuroscientific study of such ‘ego dissolution’ experiences offers a window onto the nature of self-awareness. We argue that ego dissolution is best explained by an account that explains self-awareness as resulting from the integrated functioning of hierarchical predictive models which posit the existence of a stable and unchanging entity to which representations are bound. Combining recent work on the ‘integrative self' and the phenomenon of self-binding with predictive processing principles yields an explanation of ego dissolution according to which self-representation is a useful Cartesian fiction: an ultimately false representation of a simple and enduring substance to which attributes are bound which serves to integrate and unify cognitive processing across levels and domains. The self-model is not a mere narrative posit, as some have suggested; it has a more robust and ubiquitous cognitive function than that. But this does not mean, as others have claimed, that the self-model has the right attributes to qualify as a self. It performs some of the right kinds of functions, but it is not the right kind of entity. Ego dissolution experiences reveal that the self-model plays an important binding function in cognitive processing, but the self does not exist.

Global and local complexity of intracranial EEG decreases during NREM sleep.

Abstract: Key to understanding the neuronal basis of consciousness is the characterisation 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 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 3 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 wakeful rest 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.