Imaging the Creative Unconscious:Reflexive Neural Responses to Objects in the Visual and Parahippocampal Region Predicts State and Trait Creativity

Abstract What does it take to have a creative mind? Theories of creative cognition assert that the quantity of automatic associations places fundamental constraints on the probability of reaching creative solutions. Due to the difficulties inherent in isolating automated associative responses from cognitive control, the neural basis underlying this faculty remains unknown. Here we acquired fMRI data in an incidental-viewing paradigm in which subjects performed an attention-demanding task whilst viewing task-irrelevant objects. By assigning a standard creativity task on the same objects out of the scanner, as well as a battery of psychometric creativity tests, we could assess whether stimulus-bound neural activity was predictive of state or trait variability in creativity. We found that stimulus-bound responses in superior occipital regions were linearly predictive of trial-by-trial variability in creative performance (state-creativity), and that in more creative individuals (trait-creativity) this response was more strongly expressed in entorhinal cortex. Additionally, the mean response to the onset of objects in parahippocampal gyrus was predictive of trait differences in creativity. This work suggests that, creative individuals are endowed with occipital and medial temporal reflexes that generate a greater fluency in associative representations, making them more accessible for ideation even when no ideation is explicitly called for

Ergodicity-breaking reveals time optimal decision making in humans

Ergodicity describes an equivalence between the expectation value and the time average of observables. Applied to human behaviour, ergodic theories of decision-making reveal how individuals should tolerate risk in different environments. To optimise wealth over time, agents should adapt their utility function according to the dynamical setting they face. Linear utility is optimal for additive dynamics, whereas logarithmic utility is optimal for multiplicative dynamics. Whether humans approximate time optimal behavior across different dynamics is unknown. Here we compare the effects of additive versus multiplicative gamble dynamics on risky choice. We show that utility functions are modulated by gamble dynamics in ways not explained by prevailing decision theory. Instead, as predicted by time optimality, risk aversion increases under multiplicative dynamics, distributing close to the values that maximise the time average growth of wealth. We suggest that our findings motivate a need for explicitly grounding theories of decision-making on ergodic considerations.Comment: 43 pages including supplementary methods & material

Second waves, social distancing, and the spread of COVID-19 across America

We recently described a dynamic causal model of a COVID-19 outbreak within a single region. Here, we combine several of these (epidemic) models to create a (pandemic) model of viral spread among regions. Our focus is on a second wave of new cases that may result from loss of immunity--and the exchange of people between regions--and how mortality rates can be ameliorated under different strategic responses. In particular, we consider hard or soft social distancing strategies predicated on national (Federal) or regional (State) estimates of the prevalence of infection in the population. The modelling is demonstrated using timeseries of new cases and deaths from the United States to estimate the parameters of a factorial (compartmental) epidemiological model of each State and, crucially, coupling between States. Using Bayesian model reduction, we identify the effective connectivity between States that best explains the initial phases of the outbreak in the United States. Using the ensuing posterior parameter estimates, we then evaluate the likely outcomes of different policies in terms of mortality, working days lost due to lockdown and demands upon critical care. The provisional results of this modelling suggest that social distancing and loss of immunity are the two key factors that underwrite a return to endemic equilibrium.Comment: Technical report: 35 pages, 14 figures, 1 tabl

Effective immunity and second waves: a dynamic causal modelling study

This technical report addresses a pressing issue in the trajectory of the coronavirus outbreak; namely, the rate at which effective immunity is lost following the first wave of the pandemic. This is a crucial epidemiological parameter that speaks to both the consequences of relaxing lockdown and the propensity for a second wave of infections. Using a dynamic causal model of reported cases and deaths from multiple countries, we evaluated the evidence models of progressively longer periods of immunity. The results speak to an effective population immunity of about three months that, under the model, defers any second wave for approximately six months in most countries. This may have implications for the window of opportunity for tracking and tracing, as well as for developing vaccination programmes, and other therapeutic interventions.Comment: 20 pages, 8 figures, 3 tables (technical report

Checking the list: Can a model of Down syndrome help us explore the intellectual accessibility of Heritage sites?

There is currently a lack of provision for, and research into, the intellectual accessibility of heritage sites. This paper explores some possible ways forward. It examines recent research with people described as having Down syndrome and uses the syndrome's identified characteristics to create good practice guidelines. It assesses these guidelines against an audio tour written for people with learning difficulties. In conclusion, the paper suggests that drawing upon a generalised model of Down syndrome and these good practice guidelines will allow sites to identify some potential barriers and enablers to intellectual accessibility, but that fully to appreciate the effectiveness of their provision they must still institute site?specific research by people with learning difficulties

Patient profiling for success after weight loss surgery (GO Bypass study):An interdisciplinary study protocol

Despite substantial research efforts, the mechanisms proposed to explain weight loss after gastric bypass (RYGB) and sleeve gastrectomy (SL) do not explain the large individual variation seen after these treatments. A complex set of factors are involved in the onset and development of obesity and these may also be relevant for the understanding of why success with treatments vary considerably between individuals. This calls for explanatory models that take into account not only biological determinants but also behavioral, affective and contextual factors. In this prospective study, we recruited 47 women and 8 men, aged 25–56 years old, with a BMI of 45.8 ± 7.1 kg/m2 from the waiting list for RYGB and SL at Køge hospital, Denmark. Pre-surgery and 1.5, 6 and 18 months after surgery we assessed various endpoints spanning multiple domains. Endpoints were selected on basis of previous studies and include: physiological measures: anthropometrics, vital signs, biochemical measures and appetite hormones, genetics, gut microbiota, appetite sensation, food and taste preferences, neural sensitivity, sensory perception and movement behaviors; psychological measures: general psychiatric symptom-load, depression, eating disorders, ADHD, personality disorder, impulsivity, emotion regulation, attachment pattern, general self-efficacy, alexithymia, internalization of weight bias, addiction, quality of life and trauma; and sociological and anthropological measures: sociodemographic measures, eating behavior, weight control practices and psycho-social factors.Joining these many endpoints and methodologies from different scientific disciplines and creating a multi-dimensional predictive model has not previously been attempted. Data on the primary endpoint are expected to be published in 2018. Trial registration: Clinicaltrials. gov ID NCT02070081. Keywords: Gastric bypass (RYGB), Sleeve gastrectomy, Weight loss, Interdisciplinary, Study protoco

The Encoding of Temporally Irregular and Regular Visual Patterns in the Human Brain

In the work reported here, we set out to study the neural systems that detect predictable temporal patterns and departures from them. We used functional magnetic resonance imaging (fMRI) to locate activity in the brains of subjects when they viewed temporally regular and irregular patterns produced by letters, numbers, colors and luminance. Activity induced by irregular sequences was located within dorsolateral prefrontal cortex, including an area that was responsive to irregular patterns regardless of the type of visual stimuli producing them. Conversely, temporally regular arrangements resulted in activity in the right frontal lobe (medial frontal gyrus), in the left orbito-frontal cortex and in the left pallidum. The results show that there is an abstractive system in the brain for detecting temporal irregularity, regardless of the source producing it

Rapid Identification of Novel Psychoactive and Other Controlled Substances Using Low-Field 1H NMR Spectroscopy

An automated approach to the collection of 1H NMR (nuclear magnetic resonance) spectra using a benchtop NMR spectrometer and the subsequent analysis, processing, and elucidation of components present in seized drug samples are reported. An algorithm is developed to compare spectral data to a reference library of over 300 1H NMR spectra, ranking matches by a correlation-based score. A threshold for identification was set at 0.838, below which identification of the component present was deemed unreliable. Using this system, 432 samples were surveyed and validated against contemporaneously acquired GC–MS (gas chromatography–mass spectrometry) data. Following removal of samples which possessed no peaks in the GC–MS trace or in both the 1H NMR spectrum and GC–MS trace, the remaining 416 samples matched in 93% of cases. Thirteen of these samples were binary mixtures. A partial match (one component not identified) was obtained for 6% of samples surveyed whilst only 1% of samples did not match at all