Approaches and experiences implementing remote, electronic consent at the Leeds Clinical Trials Research Unit.

BACKGROUND: Use of electronic methods to support informed consent ('eConsent') is increasingly popular in clinical research. This commentary reports the approach taken to implement electronic consent methods and subsequent experiences from a range of studies at the Leeds Clinical Trials Research Unit (CTRU), a large clinical trials unit in the UK. MAIN TEXT: We implemented a remote eConsent process using the REDCap platform. The process can be used in trials of investigational medicinal products and other intervention types or research designs. Our standard eConsent system focuses on documenting informed consent, with other aspects of consent (e.g. providing information to potential participants and a recruiter discussing the study with each potential participant) occurring outside the system, though trial teams can use electronic methods for these activities where they have ethical approval. Our overall process includes a verbal consent step prior to confidential information being entered onto REDCap and an identity verification step in line with regulator guidance. We considered the regulatory requirements around the system's generation of source documents, how to ensure data protection standards were upheld and how to monitor informed consent within the system. We present four eConsent case studies from the CTRU: two randomised clinical trials and two other health research studies. These illustrate the ways eConsent can be implemented, and lessons learned, including about differences in uptake. CONCLUSIONS: We successfully implemented a remote eConsent process at the CTRU across multiple studies. Our case studies highlight benefits of study participants being able to give consent without having to be present at the study site. This may better align with patient preferences and trial site needs and therefore improve recruitment and resilience against external shocks (such as pandemics). Variation in uptake of eConsent may be influenced more by site-level factors than patient preferences, which may not align well with the aspiration towards patient-centred research. Our current process has some limitations, including the provision of all consent-related text in more than one language, and scalability of implementing more than one consent form version at a time. We consider how enhancements in CTRU processes, or external developments, might affect our approach.

Effects of External Stimulation on Psychedelic State Neurodynamics.

Recent findings have shown that psychedelics reliably enhance brain entropy (understood as neural signal diversity), and this effect has been associated with both acute and long-term psychological outcomes, such as personality changes. These findings are particularly intriguing, given that a decrease of brain entropy is a robust indicator of loss of consciousness (e.g., from wakefulness to sleep). However, little is known about how context impacts the entropy-enhancing effect of psychedelics, which carries important implications for how it can be exploited in, for example, psychedelic psychotherapy. This article investigates how brain entropy is modulated by stimulus manipulation during a psychedelic experience by studying participants under the effects of lysergic acid diethylamide (LSD) or placebo, either with gross state changes (eyes closed vs open) or different stimuli (no stimulus vs music vs video). Results show that while brain entropy increases with LSD under all of the experimental conditions, it exhibits the largest changes when subjects have their eyes closed. Furthermore, brain entropy changes are consistently associated with subjective ratings of the psychedelic experience, but this relationship is disrupted when participants are viewing a video─potentially due to a "competition" between external stimuli and endogenous LSD-induced imagery. Taken together, our findings provide strong quantitative evidence of the role of context in modulating neural dynamics during a psychedelic experience, underlining the importance of performing psychedelic psychotherapy in a suitable environment.

Iron(II)-Catalyzed Activation of Si-N and Si-O Bonds Using Hydroboranes.

We report the activation and functionalization of Si-N bonds with pinacol borane catalyzed by a three-coordinate iron(II) ß-diketiminate complex. The reactions proceed via the mild activation of silazanes to yield useful hydrosilanes and aminoboranes. The reaction is studied by kinetic analysis, along with a detailed investigation of decomposition pathways using catecholborane as an analogue of the pinacol borane used in catalysis. We have extended the methodology to develop a polycarbosilazane depolymerization strategy, which generates hydrosilane quantitatively along with complete conversion to the Bpin-protected diamine. The analogous Si-O bond cleavage can also be achieved with heating, using silyl ether starting materials to generate hydrosilane and alkoxyborane products. Depolymerization of poly(silyl ether)s using our strategy successfully converts the polymer to 90% Bpin-protected alcohols.

An Iron-Catalyzed Route to Dewar 1,3,5-Triphosphabenzene and Subsequent Reactivity.

The application of an alkyne cyclotrimerization regime with an [Fe(salen)]2 -µ-oxo (1) catalyst to triphenylmethylphosphaalkyne (2) yields gram-scale quantities of 2,4,6-tris(triphenylmethyl)-Dewar-1,3,5-triphosphabenzene (3). Bulky lithium salt LiHMDS facilitates a rearrangement of 3 to the 1,3,5-triphosphabenzene valence isomer (3'), which subsequently undergoes an intriguing phosphorus migration reaction to form the ring-contracted species (3''). Density functional theory calculations provide a plausible mechanism for this rearrangement. Given the stability of 3, a diverse array of unprecedented transformations was investigated. We report novel crystallographically characterized products of successful nucleophilic/electrophilic addition and protonation/oxidation reactions.

The strength of weak integrated information theory.

The integrated information theory of consciousness (IIT) is divisive: while some believe it provides an unprecedentedly powerful approach to address the 'hard problem', others dismiss it on grounds that it is untestable. We argue that the appeal and applicability of IIT can be greatly widened if we distinguish two flavours of the theory: strong IIT, which identifies consciousness with specific properties associated with maxima of integrated information; and weak IIT, which tests pragmatic hypotheses relating aspects of consciousness to broader measures of information dynamics. We review challenges for strong IIT, explain how existing empirical findings are well explained by weak IIT without needing to commit to the entirety of strong IIT, and discuss the outlook for both flavours of IIT.

Greater than the parts: a review of the information decomposition approach to causal emergence.

Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advance theories. Here, we summarize, elaborate on, and extend a recent formal theory of causal emergence based on information decomposition, which is quantifiable and amenable to empirical testing. This theory relates emergence with information about a system's temporal evolution that cannot be obtained from the parts of the system separately. This article provides an accessible but rigorous introduction to the framework, discussing the merits of the approach in various scenarios of interest. We also discuss several interpretation issues and potential misunderstandings, while highlighting the distinctive benefits of this formalism. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Integrated information as a common signature of dynamical and information-processing complexity.

The apparent dichotomy between information-processing and dynamical approaches to complexity science forces researchers to choose between two diverging sets of tools and explanations, creating conflict and often hindering scientific progress. Nonetheless, given the shared theoretical goals between both approaches, it is reasonable to conjecture the existence of underlying common signatures that capture interesting behavior in both dynamical and information-processing systems. Here, we argue that a pragmatic use of integrated information theory (IIT), originally conceived in theoretical neuroscience, can provide a potential unifying framework to study complexity in general multivariate systems. By leveraging metrics put forward by the integrated information decomposition framework, our results reveal that integrated information can effectively capture surprisingly heterogeneous signatures of complexity-including metastability and criticality in networks of coupled oscillators as well as distributed computation and emergent stable particles in cellular automata-without relying on idiosyncratic, ad hoc criteria. These results show how an agnostic use of IIT can provide important steps toward bridging the gap between informational and dynamical approaches to complex systems.

Hydrogen/Halogen Exchange of Phosphines for the Rapid Formation of Cyclopolyphosphines.

The hydrogen/halogen exchange of phosphines has been exploited to establish a truly useable substrate scope and straightforward methodology for the formation of cyclopolyphosphines. Starting from a single dichlorophosphine, a sacrificial proton "donor phosphine" makes the rapid, mild synthesis of cyclopolyphosphines possible: reactions are complete within 10 min at room temperature. Novel (aryl)cyclopentaphosphines (ArP)5 have been formed in good conversion, with the crystal structures presented. The use of catalytic quantities of iron(III) acetylacetonate provides significant improvements in conversion in the context of diphosphine (Ar2P)2 and alkyl-substituted cyclotetra- or cyclopentaphosphine ((AlkylP)n, where n = 4 or 5) formation. Both iron-free and iron-mediated reactions show high levels of selectivity for one specific ring size. Finally, investigations into the reactivity of Fe(acac)3 suggest that the iron species is acting as a sink for the hydrochloric acid byproduct of the reaction.

Decomposing Spectral and Phasic Differences in Nonlinear Features between Datasets.

When employing nonlinear methods to characterize complex systems, it is important to determine to what extent they are capturing genuine nonlinear phenomena that could not be assessed by simpler spectral methods. Specifically, we are concerned with the problem of quantifying spectral and phasic effects on an observed difference in a nonlinear feature between two systems (or two states of the same system). Here we derive, from a sequence of null models, a decomposition of the difference in an observable into spectral, phasic, and spectrum-phase interaction components. Our approach makes no assumptions about the structure of the data and adds nuance to a wide range of time series analyses.

Reconciling emergences: An information-theoretic approach to identify causal emergence in multivariate data.

The broad concept of emergence is instrumental in various of the most challenging open scientific questions-yet, few quantitative theories of what constitutes emergent phenomena have been proposed. This article introduces a formal theory of causal emergence in multivariate systems, which studies the relationship between the dynamics of parts of a system and macroscopic features of interest. Our theory provides a quantitative definition of downward causation, and introduces a complementary modality of emergent behaviour-which we refer to as causal decoupling. Moreover, the theory allows practical criteria that can be efficiently calculated in large systems, making our framework applicable in a range of scenarios of practical interest. We illustrate our findings in a number of case studies, including Conway's Game of Life, Reynolds' flocking model, and neural activity as measured by electrocorticography.

Response to Ruby et al: On a 'failed' attempt to manipulate conscious perception with transcranial magnetic stimulation to prefrontal cortex.

Does disruption of prefrontal cortical activity using transcranial magnetic stimulation (TMS) impair visual metacognition? An initial study supporting this idea (Rounis, Maniscalco, Rothwell, Passingham, & Lau, 2010) motivated an attempted replication and extension (Bor, Schwartzman, Barrett, & Seth, 2017). Bor et al. failed to replicate the initial study, concluding that there was not good evidence that TMS to dorsolateral prefrontal cortex impairs visual metacognition. This failed replication has recently been critiqued by some of the authors of the initial study (Ruby, Maniscalco, & Peters, 2018). Here we argue that these criticisms are misplaced. In our response, we encounter some more general issues concerning good practice in replication of cognitive neuroscience studies, and in setting criteria for excluding data when employing statistical analyses like signal detection theory. We look forward to further studies investigating the role of prefrontal cortex in metacognition, with increasingly refined methodologies, motivated by the discussions in this series of papers.

Solved problems for Granger causality in neuroscience: A response to Stokes and Purdon.

Granger-Geweke causality (GGC) is a powerful and popular method for identifying directed functional ('causal') connectivity in neuroscience. In a recent paper, Stokes and Purdon (2017b) raise several concerns about its use. They make two primary claims: (1) that GGC estimates may be severely biased or of high variance, and (2) that GGC fails to reveal the full structural/causal mechanisms of a system. However, these claims rest, respectively, on an incomplete evaluation of the literature, and a misconception about what GGC can be said to measure. Here we explain how existing approaches resolve the first issue, and discuss the frequently-misunderstood distinction between functional and effective neural connectivity which underlies Stokes and Purdon's second claim.

Measuring Integrated Information: Comparison of Candidate Measures in Theory and Simulation.

Integrated Information Theory (IIT) is a prominent theory of consciousness that has at its centre measures that quantify the extent to which a system generates more information than the sum of its parts. While several candidate measures of integrated information (" Φ ") now exist, little is known about how they compare, especially in terms of their behaviour on non-trivial network models. In this article, we provide clear and intuitive descriptions of six distinct candidate measures. We then explore the properties of each of these measures in simulation on networks consisting of eight interacting nodes, animated with Gaussian linear autoregressive dynamics. We find a striking diversity in the behaviour of these measures-no two measures show consistent agreement across all analyses. A subset of the measures appears to reflect some form of dynamical complexity, in the sense of simultaneous segregation and integration between system components. Our results help guide the operationalisation of IIT and advance the development of measures of integrated information and dynamical complexity that may have more general applicability.

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.

Increased spontaneous MEG signal diversity for psychoactive doses of ketamine, LSD and psilocybin.

What is the level of consciousness of the psychedelic state? Empirically, measures of neural signal diversity such as entropy and Lempel-Ziv (LZ) complexity score higher for wakeful rest than for states with lower conscious level like propofol-induced anesthesia. Here we compute these measures for spontaneous magnetoencephalographic (MEG) signals from humans during altered states of consciousness induced by three psychedelic substances: psilocybin, ketamine and LSD. For all three, we find reliably higher spontaneous signal diversity, even when controlling for spectral changes. This increase is most pronounced for the single-channel LZ complexity measure, and hence for temporal, as opposed to spatial, signal diversity. We also uncover selective correlations between changes in signal diversity and phenomenological reports of the intensity of psychedelic experience. This is the first time that these measures have been applied to the psychedelic state and, crucially, that they have yielded values exceeding those of normal waking consciousness. These findings suggest that the sustained occurrence of psychedelic phenomenology constitutes an elevated level of consciousness - as measured by neural signal diversity.

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.

Complexity of Multi-Dimensional Spontaneous EEG Decreases during Propofol Induced General Anaesthesia.

Emerging neural theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, causal interactions between brain regions are both integrated (all regions are to a certain extent connected) and differentiated (there is inhomogeneity and variety in the interactions). In support of this, recent work by Casali et al (2013) has shown that Lempel-Ziv complexity correlates strongly with conscious level, when computed on the EEG response to transcranial magnetic stimulation. Here we investigated complexity of spontaneous high-density EEG data during propofol-induced general anaesthesia. We consider three distinct measures: (i) Lempel-Ziv complexity, which is derived from how compressible the data are; (ii) amplitude coalition entropy, which measures the variability in the constitution of the set of active channels; and (iii) the novel synchrony coalition entropy (SCE), which measures the variability in the constitution of the set of synchronous channels. After some simulations on Kuramoto oscillator models which demonstrate that these measures capture distinct 'flavours' of complexity, we show that there is a robustly measurable decrease in the complexity of spontaneous EEG during general anaesthesia.