122 research outputs found
Information Theory for Complex Systems Scientists
In the 21st century, many of the crucial scientific and technical issues
facing humanity can be understood as problems associated with understanding,
modelling, and ultimately controlling complex systems: systems comprised of a
large number of non-trivially interacting components whose collective behaviour
can be difficult to predict. Information theory, a branch of mathematics
historically associated with questions about encoding and decoding messages,
has emerged as something of a lingua franca for those studying complex systems,
far exceeding its original narrow domain of communication systems engineering.
In the context of complexity science, information theory provides a set of
tools which allow researchers to uncover the statistical and effective
dependencies between interacting components; relationships between systems and
their environment; mereological whole-part relationships; and is sensitive to
non-linearities missed by commonly parametric statistical models.
In this review, we aim to provide an accessible introduction to the core of
modern information theory, aimed specifically at aspiring (and established)
complex systems scientists. This includes standard measures, such as Shannon
entropy, relative entropy, and mutual information, before building to more
advanced topics, including: information dynamics, measures of statistical
complexity, information decomposition, and effective network inference. In
addition to detailing the formal definitions, in this review we make an effort
to discuss how information theory can be interpreted and develop the intuition
behind abstract concepts like "entropy," in the hope that this will enable
interested readers to understand what information is, and how it is used, at a
more fundamental level
Generalized Decomposition of Multivariate Information
Since its introduction, the partial information decomposition (PID) has
emerged as a powerful, information-theoretic technique useful for studying the
structure of (potentially higher-order) interactions in complex systems.
Despite its utility, the applicability of the PID is restricted by the need to
assign elements as either inputs or targets, as well as the specific structure
of the mutual information itself. Here, we introduce a generalized information
decomposition that relaxes the source/target distinction while still satisfying
the basic intuitions about information. This approach is based on the
decomposition of the Kullback-Leibler divergence, and consequently allows for
the analysis of any information gained when updating from an arbitrary prior to
an arbitrary posterior. Consequently, any information-theoretic measure that
can be written in as a Kullback-Leibler divergence admits a decomposition in
the style of Williams and Beer, including the total correlation, the
negentropy, and the mutual information as special cases. In this paper, we
explore how the generalized information decomposition can reveal novel insights
into existing measures, as well as the nature of higher-order synergies. We
show that synergistic information is intimately related to the well-known
Tononi-Sporns-Edelman (TSE) complexity, and that synergistic information
requires a similar integration/segregation balance as a high TSE complexity.
Finally, we end with a discussion of how this approach fits into other attempts
to generalize the PID and the possibilities for empirical applications.Comment: 15 pages, 39 reference
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Serotonergic psychedelics LSD & psilocybin increase the fractal dimension of cortical brain activity in spatial and temporal domains.
Psychedelic drugs, such as psilocybin and LSD, represent unique tools for researchers investigating the neural origins of consciousness. Currently, the most compelling theories of how psychedelics exert their effects is by increasing the complexity of brain activity and moving the system towards a critical point between order and disorder, creating more dynamic and complex patterns of neural activity. While the concept of criticality is of central importance to this theory, few of the published studies on psychedelics investigate it directly, testing instead related measures such as algorithmic complexity or Shannon entropy. We propose using the fractal dimension of functional activity in the brain as a measure of complexity since findings from physics suggest that as a system organizes towards criticality, it tends to take on a fractal structure. We tested two different measures of fractal dimension, one spatial and one temporal, using fMRI data from volunteers under the influence of both LSD and psilocybin. The first was the fractal dimension of cortical functional connectivity networks and the second was the fractal dimension of BOLD time-series. In addition to the fractal measures, we used a well-established, non-fractal measure of signal complexity and show that they behave similarly. We were able to show that both psychedelic drugs significantly increased the fractal dimension of functional connectivity networks, and that LSD significantly increased the fractal dimension of BOLD signals, with psilocybin showing a non-significant trend in the same direction. With both LSD and psilocybin, we were able to localize changes in the fractal dimension of BOLD signals to brain areas assigned to the dorsal-attenion network. These results show that psychedelic drugs increase the fractal dimension of activity in the brain and we see this as an indicator that the changes in consciousness triggered by psychedelics are associated with evolution towards a critical zone.NIHR
Wellcome
NSF-NRT
MRC
Beckley Foundation
Alex Mosley Charitable Trust
Ad Astria Chandaria Foundation.
Neuro-psychoanalysis Foundation
Multidisplinary Association for Psychedelic Studies
The Heffter Research Institut
The serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in cortical neural circuits
Most of the recent work in psychedelic neuroscience has been done using
non-invasive neuroimaging, with data recorded from the brains of adult
volunteers under the influence of a variety of drugs. While this data provides
holistic insights into the effects of psychedelics on whole-brain dynamics, the
effects of psychedelics on the meso-scale dynamics of cortical circuits remains
much less explored. Here, we report the effects of the serotonergic psychedelic
N,N-diproptyltryptamine (DPT) on information-processing dynamics in a sample of
in vitro organotypic cultures made from rat cortical tissue. Three hours of
spontaneous activity were recorded: an hour of pre-drug control, and hour of
exposure to 10M DPT solution, and a final hour of washout, once again
under control conditions. We found that DPT reversibly alters information
dynamics in multiple ways: first, the DPT condition was associated with higher
entropy of spontaneous firing activity and reduced the amount of time
information was stored in individual neurons. Second, DPT also reduced the
reversibility of neural activity, increasing the entropy produced and
suggesting a drive away from equilibrium. Third, DPT altered the structure of
neuronal circuits, decreasing the overall information flow coming into each
neuron, but increasing the number of weak connections, creating a dynamic that
combines elements of integration and disintegration. Finally, DPT decreased the
higher-order statistical synergy present in sets of three neurons.
Collectively, these results paint a complex picture of how psychedelics
regulate information processing in meso-scale cortical tissue. Implications for
existing hypotheses of psychedelic action, such as the Entropic Brain
Hypothesis, are discussed.Comment: 19 pages, 2 figure
Fractal dimension of cortical functional connectivity networks & severity of disorders of consciousness.
Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies
The Mechanism of CO and CO<sub>2</sub> Hydrogenation to Methanol over Cu-Based Catalysts
Methanol, an important chemical, fuel additive, and precursor for clean fuels, is produced by hydrogenation of carbon oxides over Cu-based catalysts. Despite the technological maturity of this process, the understanding of this apparently simple reaction is still incomplete with regard to the reaction mechanism and the active sites. Regarding the latter, recent progress has shown that stepped and ZnOx-decorated Cu surfaces are crucial for the performance of industrial catalysts. Herein, we integrate this insight with additional experiments into a full microkinetic description of methanol synthesis. In particular, we show how the presence or absence of the Zn promoter dramatically changes not only the activity, but unexpectedly the reaction mechanism itself. The Janus-faced character of Cu with two different sites for methanol synthesis, Zn-promoted and unpromoted, resolves the long-standing controversy regarding the Cu/Zn synergy and adds methanol synthesis to the few major industrial catalytic processes that are described on an atomic level
Consciousness & Brain Functional Complexity in Propofol Anaesthesia
Funder: Oon Khye Beng Ch’Hia Tsio Studentship for Research in Preventive Medicine, administered via Downing CollegeFunder: L’Oréal-Unesco for Women in Science Excellence Research FellowshipFunder: Canadian Institute for Advanced research (CIFAR)Funder: Cambridge Biomedical Research Centre NIHR Senior Investigator AwardsFunder: Stephen Erskine Fellowship at Queens’ College, CambridgeAbstract: The brain is possibly the most complex system known to mankind, and its complexity has been called upon to explain the emergence of consciousness. However, complexity has been defined in many ways by multiple different fields: here, we investigate measures of algorithmic and process complexity in both the temporal and topological domains, testing them on functional MRI BOLD signal data obtained from individuals undergoing various levels of sedation with the anaesthetic agent propofol, replicating our results in two separate datasets. We demonstrate that the various measures are differently able to discriminate between levels of sedation, with temporal measures showing higher sensitivity. Further, we show that all measures are strongly related to a single underlying construct explaining most of the variance, as assessed by Principal Component Analysis, which we interpret as a measure of “overall complexity” of our data. This overall complexity was also able to discriminate between levels of sedation and serum concentrations of propofol, supporting the hypothesis that consciousness is related to complexity - independent of how the latter is measured
Loss of the Urothelial Differentiation Marker FOXA1 Is Associated with High Grade, Late Stage Bladder Cancer and Increased Tumor Proliferation
Approximately 50% of patients with muscle-invasive bladder cancer (MIBC) develop metastatic disease, which is almost invariably lethal. However, our understanding of pathways that drive aggressive behavior of MIBC is incomplete. Members of the FOXA subfamily of transcription factors are implicated in normal urogenital development and urologic malignancies. FOXA proteins are implicated in normal urothelial differentiation, but their role in bladder cancer is unknown. We examined FOXA expression in commonly used in vitro models of bladder cancer and in human bladder cancer specimens, and used a novel in vivo tissue recombination system to determine the functional significance of FOXA1 expression in bladder cancer. Logistic regression analysis showed decreased FOXA1 expression is associated with increasing tumor stage (p<0.001), and loss of FOXA1 is associated with high histologic grade (p<0.001). Also, we found that bladder urothelium that has undergone keratinizing squamous metaplasia, a precursor to the development of squamous cell carcinoma (SCC) exhibited loss of FOXA1 expression. Furthermore, 81% of cases of SCC of the bladder were negative for FOXA1 staining compared to only 40% of urothelial cell carcinomas. In addition, we showed that a subpopulation of FOXA1 negative urothelial tumor cells are highly proliferative. Knockdown of FOXA1 in RT4 bladder cancer cells resulted in increased expression of UPK1B, UPK2, UPK3A, and UPK3B, decreased E-cadherin expression and significantly increased cell proliferation, while overexpression of FOXA1 in T24 cells increased E-cadherin expression and significantly decreased cell growth and invasion. In vivo recombination of bladder cancer cells engineered to exhibit reduced FOXA1 expression with embryonic rat bladder mesenchyme and subsequent renal capsule engraftment resulted in enhanced tumor proliferation. These findings provide the first evidence linking loss of FOXA1 expression with histological subtypes of MIBC and urothelial cell proliferation, and suggest an important role for FOXA1 in the malignant phenotype of MIBC
Global wealth disparities drive adherence to COVID-safe pathways in head and neck cancer surgery
Peer reviewe
Global overview of the management of acute cholecystitis during the COVID-19 pandemic (CHOLECOVID study)
Background: This study provides a global overview of the management of patients with acute cholecystitis during the initial phase of the COVID-19 pandemic. Methods: CHOLECOVID is an international, multicentre, observational comparative study of patients admitted to hospital with acute cholecystitis during the COVID-19 pandemic. Data on management were collected for a 2-month study interval coincident with the WHO declaration of the SARS-CoV-2 pandemic and compared with an equivalent pre-pandemic time interval. Mediation analysis examined the influence of SARS-COV-2 infection on 30-day mortality. Results: This study collected data on 9783 patients with acute cholecystitis admitted to 247 hospitals across the world. The pandemic was associated with reduced availability of surgical workforce and operating facilities globally, a significant shift to worse severity of disease, and increased use of conservative management. There was a reduction (both absolute and proportionate) in the number of patients undergoing cholecystectomy from 3095 patients (56.2 per cent) pre-pandemic to 1998 patients (46.2 per cent) during the pandemic but there was no difference in 30-day all-cause mortality after cholecystectomy comparing the pre-pandemic interval with the pandemic (13 patients (0.4 per cent) pre-pandemic to 13 patients (0.6 per cent) pandemic; P = 0.355). In mediation analysis, an admission with acute cholecystitis during the pandemic was associated with a non-significant increased risk of death (OR 1.29, 95 per cent c.i. 0.93 to 1.79, P = 0.121). Conclusion: CHOLECOVID provides a unique overview of the treatment of patients with cholecystitis across the globe during the first months of the SARS-CoV-2 pandemic. The study highlights the need for system resilience in retention of elective surgical activity. Cholecystectomy was associated with a low risk of mortality and deferral of treatment results in an increase in avoidable morbidity that represents the non-COVID cost of this pandemic
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