There is an over-representation of neurons in early visual cortical areas that respond most strongly to cardinal  orientations and directions of visual stimuli, and cardinal- and oblique-preferring neurons are reported to have different tuning curves. Collectively, these neuronal anisotropies can explain two commonly-reported phenomena of motion perception – the oblique effect and reference repulsion – but it remains unclear whether neuronal anisotropies can simultaneously account for both perceptual effects. We show in psychophysical experiments that reference repulsion and the oblique effect do not depend on the duration of a moving stimulus, and that brief adaptation to a single direction simultaneously causes a reference repulsion in the orientation domain, and the inverse of the oblique effect in the direction domain. We attempted to link these results to underlying neuronal anisotropies by implementing a large family of neuronal decoding models with parametrically varied levels of anisotropy in neuronal direction-tuning preferences, tuning bandwidths and spiking rates. Surprisingly, no model instantiation was able to satisfactorily explain our perceptual data. We argue that the oblique effect arises from the anisotropic distribution of preferred directions evident in V1 and MT, but that reference repulsion occurs separately, perhaps reflecting a process of categorisation occurring in higher-order cortical areas. The sensory environment in which the brain finds itself is not altogether unpredictable. Certain categories of stimuli present themselves more frequently than others; for example, cardinal orientations and motion directions  are common in natural visual scenes, and ubiquitous in artificial environments. Reflecting these environmental anisotropies, measurable biases in human perception and discrimination are also anisotropic, with most observers better able to detect and discriminate near-cardinal stimuli than oblique stimuli. Anisotropies are also evident in the stimulus preferences of sensory systems We investigate two anisotropic phenomena that are prominent in motion perception: the oblique effect for motion, and reference repulsion attraction, the opposite of what is commonly reported Although the oblique effect and reference repulsion have been simultaneously demonstrated in psychophysical experiments both reference repulsion and the oblique effect. Sensibly, if a single population can account for both effects, it should be given prime consideration by lex parsimoniae, and physiological studies have not suggested the existence of multiple, parallel populations of motion-sensitive neurons that contribute to perception While previous modelling results have demonstrated that neural anisotropies can easily account for perceptual anisotropy, they have not attempted to simultaneously account for Twenty-two people with normal or corrected-to-normal visual acuity participated in the experiments – thirteen in Experiment 1 and twelve in Experiment 2, with three in common. Three experienced psychophysical observers (including the authors) participated in Experiment 1. The remaining participants were volunteers who received financial compensation for their participation and were naïve as to the procedures of the experiments. Experiments were approved by the Monash University Human Research Ethics Committee, and all participants gave informed written consent.Stimuli were generated using Matlab  and the Psychophysics Toolbox extensions 2) on a white background (115 cd/m2) displayed at 100 frames per second. Each dot was an anti-aliased circle of 4 pixel radius and displayed within an invisible aperture centred on the screen with a diameter that subtends a 15 deg viewing angle.  and “°” to indicate rotational angles on the screen (e.g. motion directions).) In the first frame of the stimulus, dots were randomly plotted within the aperture at a density of 3 dots/deg2. For each successive frame, a random 90% subset of the dots moved in the same direction with a speed of 5 deg/s. The remaining 10% of dots were randomly replotted within the 15 deg aperture, giving a median dot lifetime of 66 ms. Any dots that moved outside the aperture were replotted in a position reflected about the aperture centre, maintaining uniform dot density across time. The 90% signal coherence prevented participants from tracking the local motion of individual dots or clusters of dots.We used random-dot motion stimuli comprising black dots  a 1500 ms “adaptation” period with either static noise dots as a control , or moving dots as the adapting stimulus with speed 5 deg/s in direction 0° or 45°; (2) a 160 ms “blank” period; (3) a 160 ms “test” period containing a signal motion; and (4) a “response” period . The fixn = 180+180≥32162, p>0.05).Although we used quantised test directions, it is unlikely that observers could identify when a particular test direction was presented. In pilot studies with just three adjacent test directions, observers could not reliably identify the test direction. For each observer, the number of trials in which the reported direction was within ±2.5° of any test direction was not significantly greater than the number of trials in which the reported direction was >2.5° from a test direction . Second, the duration of the test stimulus was varied in 5 conditions . A pilot test involving the three experienced participants had 6 duration conditions . Blocks of 50 trials with each test duration were presented in random order and each participant completed 2–10 blocks of each condition . In the pilot test, a total of 8,520 trials was recorded; and in the proper experiment, a total of 13,785 trials was recorded.To evaluate each participant's performance, we initially calculated a “direction error” for each trial as the signed difference between the participant's response and the test direction. Our initial analyses indicated that when stimuli were of extremely short duration (<60 ms), many participants could reliably identify the orientation axis of motion, but not the true direction of motion. To simplify comparisons between stimuli with different durations, we primarily assessed “orientation errors”, focusing on deviations from the axis of stimulus motion. Thus, direction errors of 5° and 185° are both equivalent to an orientation error of 5°. Orientation errors are limited to the range ±90° relative to the axis of the test motion direction.We assessed perceptual performance using four metrics, which were applied to trials with the same test direction, with the possibility of averaging across a group of test directions:The “orientation bias” is the signed, circular median of the orientation errorsThe “orientation accuracy” is the median of the absolute values of orientation biasesThe “orientation precision” is the circular standard deviation of orientation errorsThe “reversal fraction” is the proportion of trials in which the absolute direction error was greater than 90°.In order to compare performance anisotropies across different stimulus durations, we defined three further metrics:The “relative orientation accuracy” is the ratio of orientation accuracies at non-cardinal directions relative to cardinal directionsThe “relative orientation precision” is the ratio of orientation precisions at non-cardinal directions relative to cardinal directionsThe “reversal fraction difference” is the difference between arcsine-transformed reversal fractions at non-cardinal directions from cardinal directions.We broadly explored how anisotropies in the tuning of a single population of modelled MT neurons might explain our human perceptual data in the absence of adaptation. Starting only with a population whose distribution of tuning characteristics was specified based on that of macaque MT cells, we systematically manipulated the anisotropy of the distributions of three classically defined parameters: preferred direction, peak spiking rate and tuning bandwidth . SpecifiPD) was described by a triangular function constrained to be symmetric about the cardinal axes:The distribution of preferred directions (θunip was the probability of each direction under assumptions of uniformity (1/36); and PDθ that ranged from strongly favouring cardinal directions  and tuning bandwidth (wBW). Both weights were limited to the range [−1 1]. For simplicity, positive levels of anisotropy correspond to those suggested by physiological literature k concentrates neurons with preferred directions around the cardinals; positive BWw concentrates narrow bandwidths around the cardinals; and positive Rw arbitrarily concentrates minimum peak firing rates around the cardinals.Our model allowed us to control the correlation between the cardinal distance of neuronal preferred directions and the anisotropic distributions of tuning bandwidths and response amplitudes. It was thus possible to systematically simulate different neuronal populations in which preferred directions, narrow tuning bandwidths and low response amplitudes are anisotropically distributed to either over-represent or under-represent cardinal directions. Each neuron was allocated a tuning width and spiking rate from the randomly generated pool based on the distance of its preferred direction from the nearest cardinal. While the parameter Based on these weights, the degree of correlation between a neuron's preferred direction and tuning bandwidth or response amplitude could be easily and independently manipulated. The algorithm we formulated for generating the tuning assignments is:dirR, Rank the neurons by the distance of their preferred direction from the nearest cardinal direction Rdir, ;randR, Assign each neuron a random value in the range [1 n], where n is the number of neurons Rrand, ;dirR and randR), Rw and BWwCalculate a weighted sum of the two sets of ranks (Rrand),  ; Note thassignR;Sort the neurons by assignR.Match the ordered pool of rate and width tuning parameter values to the order of the neurons, based on To relate the resulting anisotropy to a statistical measurement, we have found that the average Spearman rank correlation of such generated sequences could be approximated as a function of the anisotropy weighting:w = 0 and 0.5 produces a number series with a rank correlation coefficient of 0 and 0.7, respectively . Note that due to the four-fold rotational and mirror symmetry of our model, these test directions are sufficient to quantify reference repulsion and the oblique effect for any test direction. Total simulation time was approximately one computer-month on two workstation PCs (processors Intel Core2 Duo E8600 and Intel Core i5-2400) under the Windows 7 Professional operating system.We generated model populations of neurons in which parameters iμ and iσ are the bias and precision of the predicted perception for direction i, and we only considered the 5 test directions 0, 10, 20, 30 and 40°.The two neuronal decoding methods we tested were a vector averaging (VA) method and a maximum likelihood (ML) method. Our VA decoding method followed typical procedures Matlab code that implements the model framework described here is provided as Supporting Information , includiIn Experiment 1, we assessed how adaptation affected bias, precision and reversal fraction of direction judgments. We used both cardinal and oblique adaptation directions allowing us to compare the interaction between anisotropies induced by recently viewed stimuli and those associated with “innate” perceptual anisotropies arising from directions that are over-represented in the environment.35, 12 = 5.37, p<0.001) and precision . Notably, differences between individual participants were also significant for orientation precision . In Experiment 2, significant within-participants differences were observed in both orientation precision  and bias  for the 640 ms duration stimuli.Both reference repulsion and the oblique effect for motion were evident in our results, with cardinal directions  having the smallest biases and best precision (lowest standard deviation) in the control “no-adaptation” data . Due to The special performance at cardinal directions was further demonstrated with a cluster analysis, using a standardised Euclidean metric and Ward's minimum variance method . A distiWe now examine how the “innate” perceptual anisotropies described above interact with those induced by adaptation to stimuli with directions of 0 and 45° . Under t12 = 90, p<0.001). The strength of repulsion between 0° and 45° adaptation was not significantly different . Interestingly, the average repulsion within 5–25° of the direction opposite adaptation (180 or 225°) was also significantly greater than 0 , but was smaller than the repulsion associated with the adapting direction; again, there was no significant difference in repulsion between 0° and 45° adaptation . These results are reminiscent of the direction aftereffect, which depends on direction-selective, not just orientation-selective mechanisms As we only tested observers with directions separated by 10°, our 45° adaptor falls in between two test directions. Therefore, the following group-wide analyses followed linear interpolation of individual participant performances over test directions in 5° steps. Adaptation induced perceptual repulsion ; across 12 = 91, p<0.001), with 45° adaptation producing a significantly larger drop in precision than 0° adaptation . These precision drops could not be explained by just an increase in guessing because the reversed responses were clustered around the direction opposite the true direction and had standard deviation of 28±2°, smaller than that of a uniform distribution (52°).Orientation precision was significantly reduced (i.e. performance was impaired) for directions within 20° of the adaptation direction . The difference in reversals between 0° and 45° adaptation was not significant . Again, there was no observable change in reversal fraction in the direction opposite adaptation . Thus, for simplicity, we classify all direction errors exceeding ±90° as “reversals”; and to allow comparison of motion perception between short and long duration trials, we quantified performance using the measures of orientation error and fraction of reversals.In Experiment 2, we examined how the duration of the motion stimulus affected performance. All participants had little difficulty judging motion direction when stimulus duration exceeded 80 ms. 4, 10 = 10.6, p<0.001), orientation precision , and arcsine-transformed reversal fraction . Moreover, it was also clear that performance improved monotonically with increasing duration .Initial experiments with 3 experienced psychophysical observers demonstrated that longer stimulus durations led to improved accuracy and precision, and a reduction in the rate of reversals . ImpaireEven at the shortest stimulus duration of 20 ms (i.e. a single frame displacement of the stimulus dots), chance performance was not reached. For a large sample of trials with responses uniformly distributed in the range ±90°, accuracy and precision will approach 45° and ∼52°, respectively. However, to allow meaningful statistical testing, we defined probability distributions for chance-level accuracy, precision and reversal fraction separately for each participant using a resampling algorithm assuming errors distributed uniformly in the range ±90°. These probability distributions were computed over 5000 samples, assuming the same number of trials as actually tested for each participant, test direction and test duration. For all participants and for all stimulus durations of 30 ms or longer, orientation accuracy and precision were outside the 95% confidence interval of the resampled distributions. For the 20 ms duration, just 2 out of 11 participants had non-significant (p>0.05) orientation accuracy and 1 participant had non-significant orientation precision. However, for 6 out of 11 participants, the reversal fraction was not significantly different from chance.y(t) models the performance  at integration time t. Constants a and b control the lower and upper bounds, respectively, while λ and c are shaping parameters. For fitting accuracy and precision, we fixed b = 45° and 52°, respectively; for fitting reversals, we fixed a = 0 and b = 0.5. Equation 5 was fit to 100 bootstrap samples of the participant's raw data for each stimulus duration. The median R2 value of all fits was 0.88.At what stimulus duration does performance saturate? In order to estimate the integration time that gave 95% performance saturation, we fit modified Weibull cumulative distribution functions to each participant's data. In Equation 5, 2<0.5 were excluded due to minimally varying orientation accuracy. The geometric mean integration time for 95% maximum orientation precision was 56 ms (range 28.1–128 ms) and the geometric mean integration time for 95% maximum direction performance as measured by reversal fraction was 48 ms (range 22.7–80.2 ms).The median integration time for 95% maximum orientation accuracy was 26 ms with range 17–175 ms (n = 11), or range 24–91 ms (n = 7) when participants with fits with R4, 10 = 2.24, p = 0.082) and relative orientation precision . Reversal anisotropy, based on the arcsine-transformed difference between reversal fractions of cardinal and oblique directions, did significantly change with time . A post-hoc analysis with Scheffé's method The perceptual anisotropies evident in Experiment 1 did not depend on viewing duration. neuronal anisotropies could account for the observed perceptual anisotropies, and if the predicted level of neuronal anisotropy matches previously reported physiological data. We simulated a population of MT neurons in which we could systematically and independently vary the amount of anisotropy in the distributions of preferred directions, direction tuning bandwidths and peak firing rates. Decoding of this population activity was performed using both maximum-likelihood and vector averaging techniques. The resulting dataset is made available in Supporting Information , demonstrating that independently varying the distribution of neuronal preferred directions, firing rates or bandwidths can change perceptual anisotropy. As positive anisotropy metrics in the model  correspond with known neuronal anisotropies, we were surprised that the signs of the partial correlations were not always positive. Below, we primarily focus on the sign of the correlation, and whether changing the level of each type of neuronal anisotropy produces changes in cardinal repulsion and oblique effect consistent with perceptual data.For simplicity, we will first consider a single integration time for each model, chosen so that the orientation precision of an isotropic population was close to the ∼9° standard deviation observed for long viewing durations in our psychophysical data . These iFor ML decoding, the cardinal repulsion and oblique effects consistent with our perceptual data were driven by neuronal anisotropies of fewer cardinal-preferring neurons, with cardinal-preferring neurons having the highest spike rates and broadest tuning bandwidths. Critically, each anisotropy produced the same sign of change in both cardinal repulsion and oblique effect , Rw =  red (spiking rate), BWw =  green (bandwidth). To reiterate: positive k concentrates neurons with preferred directions around the cardinals; positive Rw concentrates minimum peak firing rates around the cardinals; and positive BWw concentrates narrow bandwidths around the cardinals. This modelling allows us to examine if there are specific forms of anisotropy that reproduce our perceptual data. Qualitative matches to our perceptual data required positive values for both the cardinal repulsion and oblique effect metrics, corresponding to data points falling in the upper-right quadrants of each panel. We further expect that as colour saturation increases, corresponding to increased strength of anisotropy, data points should move further into the upper-right quadrant. While this preliminary analysis indicates that a maximum likelihood decoder with anisotropy in spiking rate is the most realistic, this does not incorporate the possibility of a neural population with multiple anisotropies. A large family of ML decoders with red hue fall in the upper-right quadrant, suggesting that as long as anisotropies in peak spiking rate are present, neural decoding will match human perception and additional small changes in direction preference or tuning bandwidth will not strongly affect decoding. In contrast, for the VA decoder, points in the upper-right quadrant are relatively rare, primarily associated with red-magenta hues (spiking rate plus direction preference anisotropy). The orientation of the cloud of data points for the vector average decoder suggests that only specific combinations of anisotropy in direction preference and spiking rate can produce the expected perceptual effects. Thus, such a decoder would be relatively unstable in the face of small changes in neuronal anisotropy (as may be caused by adaptation), and is unlikely to underlie perception.k = ⅓, Rw = 0, and BWw = ⅓, corresponding to a small over-representation of cardinal-preferring neurons, with those cardinal-preferring neurons tending to have narrower tuning bandwidths (see Discussion). The predicted perceptual results, using the aforementioned integration times that gave precisions most similar to the psychophysical data, was: repulsion  = −0.02°, oblique effect  = 2−0.21 for ML; and repulsion  = −1.9°, oblique effect  = 20.10 for VA. With the realistic neuronal anisotropy, the only perceptual effect that could be qualitatively replicated (i.e. had positive sign) was the oblique effect under VA decoding.Drawing from known physiological anisotropies of primate visual area populations, the most realistic model configuration had 3, 3996≤17.4, padjusted<0.001).We explored how the predicted perceptual effects depend on the modelled neuronal integration time . As inteWe examined how stimulus duration and adaptation affect the perception of motion direction in the fronto-parallel plane using an analog report method that was free of priming cues Reference repulsion was evident following adaptation, both in the direction matching and opposing the adaptor. For example, adaptation to 45° led to repulsion from both 45° and 225° directions, whilst adaptation to 0° added to the repulsion already associated with the cardinal axes. Our data is equivalent to an increase in the slope of the psychometric curve for a 2AFC task involving fine discrimination judgments of directions near the adaptor, which is consistent with previous reports that adaptation improves direction discrimination both near the adaptor and in the opposite direction While longer viewing durations improved the accuracy and precision of direction perception, they did not systematically change the strength of cardinal repulsion and the oblique effect. This suggests that these perceptual anisotropies do not arise due to selective filtering of stimulus information over the duration of a single test stimulus (<160 ms), but reflect neuronal anisotropies that can change only on timescales of hundreds of milliseconds or longer. The integration time of motion direction perception across our participants was ∼50 ms, as measured by performance saturation of reversal fraction or orientation precision. This is comparable to integration times associated with motion streaks (∼77 ms), supporting a notion that motion streaks may contribute to the judgment of direction in our task simplest form of anisotropy that could account for our perceptual results, and conversely, to determine what perceptual phenomena would be expected given the known forms of neuronal anisotropy. Historically, the observation of anisotropic neural tuning for orientation and direction has been controversial. Studies in primary visual cortices showed strong preference for cardinal orientations among individual neurons in macaques The aims of our neuronal population modelling were to determine the different levels of activity. Some studies report lower activation for obliques In humans, fMRI studies routinely show that cardinal and oblique orientations and motion directions evoke For single neurons, cardinal-preferring simple cells have been reported to have the narrowest tuning, whereas cardinal-preferring complex cells have the broadest tuning While no systematic anisotropies have yet been reported in single MT neurons – for which area is nominally associated with motion perception more than V1 e.g.  – opticaFor our modelling investigation, we ignored the effects of adaptation and aimed to only model reference repulsion and the motion oblique effect at sufficiently long timescales for which direction reversals rarely occurred. The most important and surprising finding of our modelling was that known neuronal anisotropies in direction preference and tuning bandwidth  file format.(ZIP)Click here for additional data file.File S1Modelling framework code. Matlab code that implements the population modelling framework described in (ZIP)Click here for additional data file.


NAD is a key determinant of cellular energy metabolism. In contrast, its phosphorylated form, NADP, plays a central role in biosynthetic pathways and antioxidant defence. The reduced forms of both pyridine nucleotides are fluorescent in living cells but they cannot be distinguished, as they are spectrally identical. Here, using genetic and pharmacological approaches to perturb NAD(P)H metabolism, we find that fluorescence lifetime imaging (FLIM) differentiates quantitatively between the two cofactors. Systematic manipulations to change the balance between oxidative and glycolytic metabolism suggest that these states do not directly impact NAD(P)H fluorescence decay rates. The lifetime changes observed in cancers thus likely reflect shifts in the NADPH/NADH balance. Using a mathematical model, we use these experimental data to quantify the relative levels of NADH and NADPH in different cell types of a complex tissue, the mammalian cochlea. This reveals NADPH-enriched populations of cells, raising questions about their distinct metabolic roles. NAD and NADP play fundamentally different roles in cellular metabolism, and yet these pyridine nucleotides cannot be distinguished spectroscopically in living cells. Blacker et al. demonstrate that fluorescence lifetime imaging can be used to quantify NADPH/NADH balance in cultured cells and in the mammalian cochlea. However, these engage in distinct metabolic pathways. NAD drives ATP production in the cytosol by glycolysis and in the mitochondria by oxidative phosphorylation, while the phosphorylated analogue NADP governs lipid, amino acid and nucleotide biosynthetic pathways and the defence against reactive oxygen species by glutathione (GSH)The cellular redox state is the central regulator of energy production and intermediary metabolism, playing a crucial role in health and diseaseet al.68In the 1960s, Britton Chance Fluorescence lifetime imaging (FLIM) allows the study of NAD(P)H photochemistry inside living tissue10111314151617τfree) and enzyme-bound NAD(P)H (τbound) pools, respectively, confirmed by time-resolved anisotropy imaging studiesτbound is a weighted mean of the fluorescence lifetimes of enzyme-bound species, a conclusion supported by computational modelling H in live HEK293 cells in which NADPH levels were genetically and pharmacologically manipulated. In wild-type cells, the fluorescence decays obtained at each pixel required a two-component model to yield good fits H) and τfree=0.36±0.04 ns .Next, to understand the effect of varying [NADPH]/[NADH] ratios on ood fits , as expe±0.04 ns . Interesτbound, we hypothesized that, since NADH and NADPH are associated with different binding site structures inside the cellτbound value could reflect the proportion of the two cofactors present. We therefore measured NAD(P)H fluorescence lifetimes in HEK293 cell lines in which NAD+ kinase (NADK) was either overexpressed (NADK+) or knocked down (NADK−)τbound was significantly larger in the NADK+ cells  compared with the NADK− cells  on the NAD(P)H FLIM parameters. EGCG is a potent competitive inhibitor of NADPH bindingαbound should therefore be more sensitive to EGCG treatment in NADK+ cells than in NADK− cells, as bound NADPH will form a greater fraction of the total population of enzyme-bound NAD(P)H species. As predicted, αbound decreased significantly from 0.18±0.02 to 0.13±0.02 in both the mitochondria and cytosol  on EGCG treatment in NADK+ cells but remained constant in NADK− cells, confirming the NADPH specificity of this compound  and to 2.5±0.2 ns in their nuclei , and did not significantly affect NADK− cells  or uncoupling using FCCP (1 μM). The cells were driven to a more oxidative phenotype by inhibition of glycolysis by glucose deprivation in the presence of deoxyglucose (10 mM), while pyruvate (1 mM) or lactate (10 mM) were provided as mitochondrial-specific substrates.In previous workn=3). FLIM images were acquired at the steady-state fluorescence intensity levels following each treatment , suggesting that this treatment caused the concentration of NADH present in the cell to increase relative to the concentration of NADPH, following inhibition of NADH oxidation by complex I. In contrast, τbound did not change in response to FCCP . This lack of change in τbound suggested that uncoupling caused the oxidation of both NAD and NADP pools in equal measure. Increased oxidation of the NAD pool was to be expected on uncoupling due to the increased complex I activity, and the equal oxidation of the NADP pool was likely caused by the action of the mitochondrial transhydrogenase. In respiring mitochondria, this inner mitochondrial membrane protein transfers hydride from NADH to NADP+ powered by translocation of protons from the intermembrane space to the mitochondrial matrix+ to produce NADHτbound . However, the mean value of τbound in both the mitochondria and cytosol of 2.70±0.01 ns in the presence of pyruvate was significantly larger than its value of 2.57±0.04 ns in the presence of lactate . As lactate dehydrogenase promotes NADH production during the conversion of lactate to pyruvate, the significantly smaller τbound value in the presence of lactate relative to pyruvate supports the interpretation developed in this work that this parameter reflects NADPH/NADH ratio, assuming NADPH production was identical in the presence of the two substrates.Ultraviolet confocal microscopy was used to establish the time taken for the redox state of the NAD(P) pool to reach a new steady state following each treatment . Inhibitreatment . Rotenonτbound, and thus the NADPH/NADH ratio, reflected the specific treatment causing a defect in OXPHOS or glycolysis, we observed that each treatment causing a net oxidation of the combined NAD(P) pools caused αbound to increase H fluorescence decay cannot be simply attributed to alterations in the balance between oxidative and glycolytic metabolism. Accordingly, no correlation between τbound and the balance of ATP production by glycolytic or oxidative means was observed by measuring the rates of oxygen consumption and lactate release in the wild-type, NADK+ and NADK− HEK293 cell lines  exhibited an extended fluorescence lifetime of 3.5±0.1 ns, while the mean value of τbound measured in the neighbouring sensory receptors, the outer hair cells (OHCs), was significantly lower at 2.9±0.1 ns  to a mean of 2.9±0.2 ns, but by only 0.2±0.2 ns  to a mean of 2.7±0.1 ns in hair cells (To explore the application of NAD(P)H FLIM in multicellular specimens, the redox metabolism of the mammalian cochlea was investigated. The cochlea is a structure containing a highly ordered system of functionally distinct cell types, which are easily identifiable from their architecture . FLIM imir cells . These dP=4E−4, Wilcoxon signed-rank test, n=19), with a correspondingly smaller concentration of NADH . To assess the functional significance of this finding, we measured the distribution of GSH in the tissue using monochlorobimane (MCB) staining, since a major demand for NADPH in glial cells arises from GSH turnoverP=0.02, Wilcoxon signed-rank test, n=17, τbound is consistent with alternative indicators of cellular redox state.Application of the mathematical model developed in this work  implied τbound that are similar in magnitude across a range of cell types, including isolated ventricular cardiomyocytes and neurons in culture or in brain slices (data not shown).This work shows that FLIM can be used effectively to differentiate between NADH and NADPH at the level of the single cell or organelle. The results suggest that enzyme-bound NADPH possesses a significantly larger fluorescence lifetime than enzyme-bound NADH within the cellular environment, so that the proportion of enzyme-bound NADPH and NADH present in live tissue determines the lifetime of their combined fluorescence decay. By making the simplifying assumption that bound NADH and bound NADPH possess finite and distinct fluorescence lifetimes inside the cell, the relative contribution of each cofactor to the combined fluorescence signal could be calculated. With excitation at 700 nm and a 435–485 nm detection window, the intracellular fluorescence lifetimes of NADH and NADPH were predicted to be 1.5±0.2 and 4.4±0.2 ns respectively. It is reasonable to hypothesize that these conclusions can be extended to all cell types as the fluorescence lifetime of NAD(P)H when bound to an enzyme is determined by its local environment in the binding site36et al.Aspergillus fumigatus fungus. The parameter τbound was ~2 ns within the bulk cytosol of the granulocytes. However, localized subplasmalemmal regions of the cytosol in contact with the fungus displayed increased values of 3.7 ns. This was attributed to a unique fluorescence lifetime of NADPH when bound to the NADPH oxidase activated in response to pathogenic exposure. However, the computational simulations performed here showed that τbound is a weighted average of the fluorescence lifetimes of the enzyme-bound NAD(P)H species present. For NADPH oxidase alone to cause an increase in τbound as large as that observed in the granulocytes would require this enzyme to be present at a greater concentration than the NADH-binding enzymes of the cytosol. The Model Organism Protein Expression Database (MOPED)The analysis and model presented herein are consistent with previously published NAD(P)H FLIM studies. In 2008, Niesner τbound of the magnitude caused by an increased NADPH/NADH ratio, our results strongly suggest that NAD(P)H fluorescence lifetime differences observed between healthy and pathological states reflect shifts in the NADPH/NADH balance.Changes in the fluorescence decay of NAD(P)H have recently been observed in applications ranging from wound healing1143144546474849αbound. Changes in τbound will be induced by metabolic transitions that cause divergent effects on NAD- and NADP-associated pathways. Thus, neither parameter alone will permit the detection of oxidative or glycolytic states using NAD(P)H fluorescence decay measurements. However, a method for assessing the pathways used for ATP production by measuring autofluorescence may be possible by combining a number of observables, including αbound and τbound, alongside fluorescence intensity information and similar measurements from flavoprotein fluorescence as part of a spectrally resolved lifetime imaging toolIn this work, termination of oxidative phosphorylation by uncoupling and of glycolysis by glucose deprivation could not be resolved on the basis of the fluorescence decay parameters measured under these conditions. In addition, two of the cell lines studied here with similar fluorescence decay parameters were shown to differ in their reliance on aerobic and anaerobic metabolism (wild-type HEK293 and NADK−). This implies that changes in the NAD(P)H fluorescence decay do not simply report shifts between an oxidative or glycolytic phenotype, but reflect the differential response of the NAD and NADP pools following a metabolic alteration. For example, both uncoupling and electron transport chain inhibition terminate aerobic ATP production yet have opposing effects on the overall NAD(P) redox state and thus, perhaps on τfree and τbound, along with the weighting parameter αbound, are extracted by least-squares fitting of a biexponential decay at each pixel1124254–105 independent decay curves in a single image, difficulties in resolving decay components with closely spaced lifetimes and correlations between the fit parameterset al.et al.In the present study, we have investigated the canonical form of FLIM in which fluorescence lifetimes Altogether, we have shown that the fluorescence lifetime characteristics of NAD(P)H in live cells and tissues can be used to discriminate between NADH and NADPH fluorescence, providing, for the first time, a biochemical framework for interpretation of NAD(P)H FLIM studies. Such a technique permits the separation of NADH and NADPH redox signalling without disrupting the sample on the addition of external probes54−1 penicillin and 100 μg ml−1 streptomycin (Gibco). Production of the NADK+ and NADK− cell lines has been reported previously−1 G-418 selective antibiotic (Gibco). All cells were grown as monolayers in sterile 75 cm2 tissue culture flasks (Thermo Scientific Nunc) in a 37 °C, 5% CO2 incubator.HEK293 cells were obtained from the American Type Culture Collection and grown in advanced Dulbecco’s modified Eagle Medium (Gibco) supplemented with 10% fetal bovine serum, 2 mM GlutaMAX, 100 U ml−1 in 0.1 mM NaHCO3. The cochlear explants were incubated overnight in DMEM/F12 (Gibco), supplemented with 1% fetal bovine serum (Life Technologies) in a 37 °C, 5% CO2 incubator. The isolation was performed in accordance with the United Kingdom Animals (Scientific Procedures) Act of 1986 and in compliance with the Biological Services Management Group and the Biological Services Ethical Committee, University College London.Cochlear coils were isolated from male and female post-natal day 2–3 Sprague Dawley rats as previously describedOn the microscope stage, coverslips containing 300,000 cells were maintained at 37 °C in a metal ring and bathed in DMEM solution at pH 7.4 containing 10 mM HEPES and 2 mM GlutaMAX. Glucose (25 mM) was present under control conditions and during EGCG treatment . Pharmacological perturbations to metabolism were applied by the dropwise addition of working concentrations of each compound, diluted from stock solutions in DMEM recording medium.NAD(P)H FLIM was performed on an upright LSM 510 microscope (Carl Zeiss) with a 1.0 NA × 40 water-dipping objective using a 650-nm short-pass dichroic and 460±25 nm emission filter. Two-photon excitation was provided by a Chameleon (Coherent) Ti:sapphire laser tuned to 700 nm, with on-sample powers kept below 10 mW. Spectral controls see  confirmeNAD(P)H fluorescence intensity time series and MCB imaging were performed on an inverted LSM 510 laser scanning confocal microscope (Carl Zeiss) with 351 nm illumination from an argon ion laser (Coherent Enterprise UV). MCB (30 min loading at 50 μM) and NAD(P)H fluorescence were observed using a 351-nm long-pass dichroic and 460±25 nm band-pass emission filter with a × 40, 1.3 NA quartz oil immersion objective. Images (12-bit 512 × 512) were obtained with a pixel dwell time of 1.6 μs. Time series measurements were obtained at 1 min intervals. To reduce noise, the image recorded at each time point was a mean of four consecutive scans. Fluorescence intensity levels were extracted using ImageJ (NIH).For the measurement of oxygen consumption, cells were trypsinized and resuspended at ~1 million cells per ml in DMEM buffered with 10 mM HEPES and supplemented with 25 mM glucose and 2 mM GlutaMAX. Respiration rates were measured in triplicate at 37 °C with the high-resolution Oxygraph (Oroboros Oxygraph-2k). State 4 respiration values were obtained in the presence of 2.5 μM oligomycin, maximal oxidative capacities were determined in the presence of 2 μM FCCP and non-mitochondrial background oxygen consumption was determined in the presence of 2.5 μM antimycin A. Lactate release rates were measured in triplicate by removing a sample of serum-free DMEM from 70% confluent cell cultures at 1 h intervals for 5 h total and determining the concentration of lactate present using a commercially available plate-reader assay (Sigma Aldrich) in absorption mode. For normalization of both oxygen consumption and lactate release rates, final cell counts were performed using a haemocytometer.Following 5 × 5 binning of photon counts at each pixel, fluorescence decay curves of the formZ allows for time-uncorrelated background noise. The instrument response function of the FLIM system was obtained by measuring the fluorescence decay profile of second harmonic generation by a potassium dihydrogen phosphate (KDP) crystal at 920 nm, grown by leaving a molar solution of KDP in water on a coverslip to evaporate. Matrices of the fit parameters τfree, αbound and τbound, along with the total photons counted at each pixel, were exported from SPCImage. In MATLAB (The Mathworks), a 16-bit grayscale image was produced for each parameter matrix in which the intensity of each pixel was proportional to the parameter value at that location. ImageJ was then used to measure the grayscale intensity in the parameter images and the values obtained converted back to parameter values using the scaling factors applied in their production. Masks identifying the location of mitochondrial and cytosolic pixels were created by importing images of the TMRM distribution in the cell and a nuclear mask was defined by hand, allowing the parameters describing the fluorescence decay of NAD(P)H in each of these regions to be extracted separately (were fit to the FLIM images using iterative reconvolution in SPCImage (Becker & Hickl), where parately .P<0.05) using a two-tailed Student’s t-test. Statistically significant differences between data sets normalized to be expressed in relative arbitrary units  were assessed using a Wilcoxon signed-rank test. For the estimation of uncertainties in the predictions of the numerical model, the standard formula for the calculation of the error Z=Z was applied,NAD(P)H fluorescence lifetime parameters obtained using FLIM are reported as a mean over at least three regions of at least three separate cultures. Uncertainties in these values were taken as the s.d. of the measurements. Differences between the lifetime parameters measured under different conditions were tested for statistical significance .Supplementary Figures 1-4, Supplementary Tables 1-7, Supplementary Notes 1-6 and Supplementary References


This di➣ hepatitis C➣ cirrhosis of the liver abused with alcohol consumption➣ heterogenic metabolic liver dysfunctions such as steatosis hepatis, etc.➣ chronic inflammatory processes of different origin➣ genetic predisposition➣ toxic environmentall by its own way leading to primary liver carcinomas to be discriminated from completely different origin of the liver metastatic disease down-stream towards several cancer types primarily developed in colon, stomach, breast, prostate, pancreas, cervix, bronchus, skin, etc. On the other side this is the patient individuality as a kind of “complex biochemical reactor”, which strongly influences the disease onset and therapy outcomes. Hence, there are evident deficits in predictive molecular diagnostics and treatments tailored to the person to be considered for the field promotion.One hundred and six patients with primary liver malignancies and secondary liver metastatic disease have been recruited for a pilot study. The patients have been grouped according to a gender, type of primary tumour and an applied therapy . Blood samples have been taken before therapy, 1 day, 3 and 6 months after the therapy application. Each sample with full blood underwent immediate isolation of plasma and circulating leukocytes which got frozen and stored at -80°C for consequent analytical procedure. Individual as well as subgroup specific molecular profiles have been created using conventional technologies of clinical proteomics and sub-cellular imaging by quantitative “comet assay” analysis.Our results confirm the hypothesis concerning the divergent molecular profiles in corresponding subgroups. As proposed, all the above listed parameters strongly influence both the initial profiles before the therapy application and the reaction towards the applied therapy. Further, the molecular patterns are characteristic for each group created accordingly to the above nominated criteria. The most characteristic patterns have been identified for➣ detoxification pathways➣ microfilamental-network associated proteins➣ stress proteome➣ tissue remodelling enzymatic complex➣ DNA fragmentation (comet patterns)The principle of individual radiation sensitivity has been found to be the decisive parameter for choosing between SIRT and TACE.Large-scaled studies are highly recommended to validate preliminary results of the pilot study. Potential outcomes might be of highest value for developing of predictive diagnostics and personalisation of medical services in the cohort of patients with liver cancer.


Cervical intraepithelial neoplasias (CIN) represent precursor lesions of cervical cancer. These neoplastic lesions are traditionally subdivided into three categories CIN 1, CIN 2, and CIN 3, using microscopical criteria. The relation between grades of cervical intraepithelial neoplasia (CIN) and its fractal dimension was investigated to establish a basis for an objective diagnosis using the method proposed.Classical evaluation of the tissue samples was performed by an experienced gynecologic pathologist. Tissue samples were scanned and saved as digital images using Aperio scanner and software. After image segmentation the box counting method as well as multifractal methods were applied to determine the relation between fractal dimension and grades of CIN. A total of 46 images were used to compare the pathologist's neoplasia grades with the predicted groups obtained by fractal methods.Significant or highly significant differences between all grades of CIN could be found. The confusion matrix, comparing between pathologist's grading and predicted group by fractal methods showed a match of 87.1%. Multifractal spectra were able to differentiate between normal epithelium and low grade as well as high grade neoplasia.Fractal dimension can be considered to be an objective parameter to grade cervical intraepithelial neoplasia. Prior to becoming invasive, cervical cancer is preceded by progressively worsening lesions that remain inside of the epithelium, known as cervical intraepithelial neoplasia (CIN). These precursor lesions are typically classified into: CIN 1 (“mild dysplasia”) or low grade, CIN 2 (“moderate dysplasia”), and CIN 3 (for a spectrum that includes “severe dysplasia and carcinoma in situ”) also referred to as high grade squamous intraepithelial lesions For patients with CIN 1 lesions, the typical treatment is watchful waiting, because these lesions often turn back into normal tissue. In contrast, for patients with CIN 2 and 3 lesions, the recommended strategy is excision, intended to stop progress toward carcinoma, followed by intensified surveillance Currently, lesions are typically graded by pathologists using microscopes to assess tissue samples based on features such as the amount of dysplastic cells. CIN  is characterized by abnormal maturation and architectural abnormalities with atypical squamous cells showing nuclear atypia/pleomorphism. Based on the degree of architectural abnormalities and cytologic atypia, CIN is traditionally classified in low-grade (mild dysplasia), intermediate (moderate dysplasia) and high-grade (severe dysplasia/cancer in situ). While CIN 1 (mild dysplasia) shows low-grade architectural abnormality of atypical cells confined to the lower third epithelium, CIN 2 and CIN 3 are associated with markedly atypical squamous cells confined to more than half, but less than upper third of the epithelium (CIN 2) or even replace almost the entire native epithelium (CIN 3). Cervical intraepithelial neoplasia grade 2 (CIN 2) and grade 3 (CIN 3) are also regarded as high grade squamous intraepithelial lesions (HGSIL) according to the Bethesda- classification system In any case, grading depends on the expertise of the pathologist because these methods are semi-quantitative and not objective. Indeed there is no parameter in use that quantifies CIN grades based on an exact mathematical method One mathematical model that may be able to resolve this problem is fractal analysis. Fractal methods have been widely applied in medicine for many years and are especially relevant to the study of cancer due to the surface characteristics of the spreading tumor and tissue characteristics that may include protein deposits within the cytoplasm or staining anomalies with known stains or changes in nuclear morphology. Fractal dimensions have been used to assess tumor growth Some investigators have attempted to develop objective fractal analysis-based methods for grading CIN, but a practical and reliable method has not yet been found. Sedivy et al., for instance, concluded that the fractal dimension of single nuclei differed between CIN 1, CIN 2 and CIN 3 The current study proposes a new approach for using fractal methods to objectively grade CIN and normal tissue. Having a predefined ROI selected out of each tissue sample, we show how box counting can be applied to digital images of suspicious epithelium. In addition multifractal analysis was also investigated as differences in complexity throughout a biological image such as squamous epithelium can be attributed to multiple processes acting on the tissue during development and at different scales such that both microscopic and macroscopic influences determine the final structural attributes of the tissue. Fractal and multifractal analysis provide an easy, inexpensive and reliable method sensitive enough to establish an automated image diagnosis system from Haematoxylin-Eosin stained tissue samples.Tissue samples, already described in a previous study were used for this analysis Histological slices were digitally scanned using a digital whole slide scanner  at a magnification of 40 (100000 pixel/inch). Images were saved in 24 Bit RGB colour format. To obtain comparable extracts out of the whole images, tiles of 1024×1024 pixels showing the suspicious epithelium were saved as TIFF files using ImageScope Viewer (Aperio) separately. Initially, the complete image of a histological slice was about 700 MB, tiles reduced to approximately 3.5 MB.Segmentation and monofractal  fractal analysis was performed with the software IQM BOXd, the size r of the boxes building the grid is defined and the number of boxes N(r) covering the object in an image determined. The formal relation is:Theoretical fractals are self-similar objects following a scaling relationship or power law when certain measures are calculated at different scales. Biological objects may have fractal characteristics and are scale-invariant The limit cannot be calculated for digitized images, because of the discrete nature of the pixel grid. Therefore, an estimation of the fractal dimension is determined.r equals 1. In that case N(r) equals 1, too, because, certainly the object is inside this box. By halving the length (r  = 1/2), four boxes result and the object could be overlaid by 1 up to 4 boxes, yielding N(r) to be 1 up to 4. The box length can further be divided into quarters (r = 1/4), eighths (r = 1/8), and so on, increasing the resolution step by step. If N(r) and r are double logarithmically plotted a scatter plot can be produced. Linear regression gives an approximation with a straight line and finally, the negative slope of this line equals BOXd.If the size of the box is exactly the length of an image's margin, qD vs q, calculated using FracLac for ImageJ qD vs q spectra is calculated by setting an arbitrary range for q,  = −10 to +10.75 with 0.25 increments. The multifractal spectrum has been most often estimated using the box counting method:We also used the basic box counting data gathering method to calculate the multifractal spectra. Multifractal spectra assess how scaling varies over an image. The parameter we used was the generalized dimension spectra, denoted ε is the scaling factor, index υ labels the individual box and υ(ε)p denotes the relative weight of the υth box. For finite data sets υ(ε)p is approximated byυ(ε)N is the number of points falling into the υth box Here p-value was considered to be significant if p<0.05 or highly significant if p<0.01. To evaluate sensitivity and specificity of the new method a confusion matrix assuming the pathologist's grading being the correct one was constructed.Statistics were calculated using SPSS 20 . In some cases it was possible to extract more than one area from the histological slice of one patient. To keep statistics valid, the median was calculated and counted as one sample. T-tests, ANOVA, Tukey HSD post hoc tests and Kolmogorov Smirnov-tests were used where applicable. Student's t-tests were performed for comparing low grade neoplasia (including CIN 1) to high grade neoplasia (including CIN 2 and CIN 3). In every case a qD vs q multifractal spectra we generated for the images indicated that there was some variation in the degree of multifractal scaling in between the neoplasia groups and between the neoplasia groups and the normal epithelium group. Based on ANOVA for the scales of q applied, there were significant differences between all groups and also between low and high grade neoplasia and normal epithelium. Tukey HSD post hoc tests indicated that for the group comparisons , CIN°3 was significantly different to normal epithelium (p°<°0.001), CIN°1 (p°<°0.01) and CIN°2 (p°<°0.05), and normal epithelium further significantly different to CIN°1 (p°<°0.05) and CIN°2 (p°<°0.01). These results held for all comparisons between -10°≤°q°≤°10.75, up to q°>°−7 when CIN°2 ceased to be significantly different to CIN°3, and q°>°−4.25 when no so significant difference could be seen between normal epithelium and CIN°1  was found in normal epithelium and the highest (BOXd° = °1.9507) in CIN 3. BOXd, calculated out of n cases grouped in normal epithelium, low grade neoplasia, high grade neoplasia and CIN 1, CIN 2, CIN 3.The IN°1 see . Based oBOXd increase according to the grade of neoplasia from 1.59 in normal epithelium to 1.80 in CIN 3 and 1.78 in high grade neoplasia.The medians of BOX,d it can be seen that groups do overlap to some extent, e.g. the maximum of BOXd for normal epithelium reaches the median of BOXd for CIN 1.Considering minimum and maximum values of p<0.01), and normal epithelium was highly significantly different from both CIN 2 (p<0.01) and CIN 3 (p<0.01). In the significantly different category, CIN 1 differed from CIN 2 (p = 0.049) and CIN 2 from CIN 3 (p = 0.028).All groups were normally distributed. ANOVA and Tukey HSD post hoc tests yielded significant results: CIN 1 was highly significantly different from CIN 3 (The confusion matrix  gives dep°<°0.002) and is depicted in BOXd, Kolmogorov Smirnov-testing confirmed normal distributions and t°-°testing yielded a highly significant (p<0.01) difference between the two groups as can be seen in For further statistical examinations, two groups were formed: high-grade (CIN 2 and 3) and low-grade (CIN 1) neoplasia. Statistical comparison between low grade neoplasia and high grade neoplasia using multifractal spectra provided a highly significant result  also improves on the state of the art by presenting a high correspondence with the pathologist's grading despite a rather low number of images under investigation. It is a fact that there are actually only few cases, especially in the groups CIN 1 and CIN 2. However, the trend of increasing fractal dimension according to the grade of neoplasia is considerable and it can be assumed that further studies will confirm our findings. Multifractality is relevant to patterns in which a spectrum of fractal dimensions can be identified rather than a single global dimension. The theory and calculations behind multifractal measures are available elsewhere We have demonstrated that objective parameters for grading of CIN can be found by applying the proposed methods including image segmentation and fractal analyses. Compared to other approaches, the proposed methods are fast, easy and reliable. The next step in developing this technology is to establish a clinical standard based on fractal measures. Involvement of a larger number of pathologists as well as a larger number of images could help to reinforce this effort. Since the method seems to be very appropriate, a comparison study of the proposed objective method and the rather subjective grading in clinical practice could be performed. Another application could be the development of software that yields a specific prognosis, e.g. using fractal dimensions to predict if a CIN 1 lesion is more likely to turn into CIN 2 or might become normal tissue again, or to further characterize changes within the low grade neoplasia and specifically CIN 3 identified in multifractal spectra.


During social interactions, our own physiological responses influence those of others. Synchronization of physiological  responses can facilitate emotional understanding and group coherence through inter-subjectivity. Here we investigate if observing cues indicating a change in another's body temperature results in a corresponding temperature change in the observer.Thirty-six healthy participants  each observed, then rated, eight purpose-made videos (3 min duration) that depicted actors with either their right or left hand in visibly warm (warm videos) or cold water (cold videos). Four control videos with the actors' hand in front of the water were also shown. Temperature of participant observers' right and left hands was concurrently measured using a thermistor within a Wheatstone bridge with a theoretical temperature sensitivity of <0.0001°C. Temperature data were analysed in a repeated measures ANOVA (temperature × actor's hand × observer's hand). = 256.67, p<0.001. Participants' own hands also showed a significant temperature-dependent effect: hands were significantly colder when observing cold vs. warm videos F = 13.83, p = 0.001 with post-hoc t-test demonstrating a significant reduction in participants' own left (t(35) = −3.54, p = 0.001) and right (t(35) = −2.33, p = 0.026) hand temperature during observation of cold videos but no change to warm videos (p>0.1). There was however no evidence of left-right mirroring of these temperature effects p>0.1). Sensitivity to temperature contagion was also predicted by inter-individual differences in self-report empathy.Participants rated the videos showing hands immersed in cold water as being significantly cooler than hands immersed in warm water, FWe illustrate physiological contagion of temperature in healthy individuals, suggesting that empathetic understanding for primary low-level physiological challenges (as well as more complex emotions) are grounded in somatic simulation. Adaptive social behavior is dependent on the efficient communication of affective and motivational signals between individuals that together facilitate understanding of others' mental and emotional states. In humans, perception of these signals is associated with a marked tendency to mimic, which is well described for emotional facial expressions Following de Vignemont and Singer we define empathy as occurring if: ‘(i) one is in an affective state; (ii) this state is isomorphic to another person's affective state; (iii) this state is elicited by the observation or imagination of another person's affective state; (iv) one knows that the other person is the source of one's own affective state' Though somatically mediated motor signals have traditionally dominated research in this field, recent evidence has demonstrated that effects of emotion contagion can be observed for facial temperature Until a decade ago, neuroscientific approaches to the study of empathy were lacking. However, with the discovery of mirror neurons within the premotor cortex, which respond during both performance and observation of a conspecific performing the same action, a potential neural mechanism mediating how we understand other people's actions and intentions was proposed Subsequently, a huge number of human functional imaging studies have provided empirical support for such shared networks in the domain of feeling and emotional states. Most have been performed in the domain of pain and show an overlapping anterior insula and anterior midcingulate cortex (aMCC) network underlying both the first-hand experience of pain as well as its observation in others To date however, no study has asked whether sharing of autonomic physiological responses also extends to peripheral skin temperature. All homeothermic animals including humans rigidly regulate their core body temperature through a variety of involuntary thermoregulatory responses, such as shivering and non-shivering thermogenesis, cutaneous vasomotor responses, sweating, piloerection and panting To investigate emotional contagion in the domain of body temperature we measured the left and right hand temperature of thirty-six healthy volunteers while viewing videos of two actors placing their right or left hand in warm or cold water. We predicted: 1) that viewing another's hand in warm/cold water in the absence of any emotional cues would be associated with congruent temperature changes in the viewer's hand. 2) That viewed changes in the right hand would be associated with congruent (contagious) temperature changes in the viewer's left hand . 3) That these temperature changes would occur in the absence of more general measures of arousal e.g. change in heart rate. 4) That contagion of another's peripheral temperature change would be greater in participants with high emotional empathy as measured through psychological trait questionnaires.Thirty-eight healthy participants with normal or corrected to normal vision were recruited via advertisement on the UCL psychology online research website. Two participants were subsequently excluded from the analysis of temperature responses due to technical failure and 14 from the heart rate analysis due to battery failure. Thus a total of 36 participants  were included in analysis of temperature response and 22  in the combined analyses of heart rate and temperature responses. Written informed consent was obtained in accordance with the declaration of Helsinki (Helsinki 1991) and the procedures were approved by the joint Ethics Committee of the National Hospital and Institute of Neurology, London.Ten custom temperature stimuli videos were produced. Each video began with one of two actors  sitting in front of a transparent container partially filled with water. In four of the videos the actor then gradually added hot water from a steaming kettle into the container, checking the temperature of the water every few seconds with one hand. One video showed the male actor placing his right hand in the water and one his left. The other two videos showed the same procedure with the female actor. Four additional videos showed each actor filling the container with a bag of ice then testing the cold water with his/her left or right hand. The first 40 s of each video showed the actor cautiously filling the semi-filled transparent container with water from a steaming kettle or ice from a bag and intermittently testing the water temperature with his or her hand. The remainder of the videos used in subsequent analyses focused exclusively on the actor's hand placed in the water. These sections of the videos showed the water and the actor's hand only with no facial or other body movement cues that may communicate emotional state. Two additional control videos (each of 120 s duration) showed the same combination of factors i.e. bowl of water and actors hand, however in these videos no hot water/ice was added to the water and the actor's hand was held in front of the water container. One control video showed the female actor's left hand and the other the male actors' right hand  and the temperature of the actor's hand (“How Hot or Cold is the Actor's Hand?”) using a keyboard controlled visual analogue scale ranging from ‘Very Cold’ (far left) through ‘Neutral’ (centre) to ‘Very Hot’ (far right). Each video was separated by a 60 second inter-trial interval. The task was written and presented, and behavioural responses logged via a desktop computer running Cogent software on a Matlab platform . See All testing was performed in a dedicated testing room kept at a constant temperature of 21°C. Participant's right and left hand temperature and heart rate, as well as ambient room temperature, were recorded throughout the study. Minute (3×2 mm) thermistors were attached to the palmar distal phalanges on the fourth finger of each hand to measure temperature change. Convection and conductive heat transfer to the environment was minimised by attaching the thermistors with micropore tape and placing participant's hands palm upwards on cushions throughout video playback. Ambient temperature was recorded throughout using a third thermistor suspended 20–30 cm in front of the hands. To minimise muscle movement related temperature change participants were asked to keep their hands as still as possible during video payback and use the index finger of both hands to input responses once the video had finished playing. Heart rate was simultaneously monitored using a pulse oxymeter  attached to each participant's left small finger.Each thermistor was connected to a separate Wheatstone bridge (detailed below) with outputs, pulse oximetry signals and stimulus timing pulses all passed to a Cambridge Electrical Designs (CED) Power 1401 data acquisition interface then recorded at a rate of 100 Hz on a second PC running the program Spike2 see .0)  = 10 kΩ, B25/100 (beta)  = 3988K at a rated temperature (T0)  = 25°C) had a near linear resistance change  was connected to a custom Wheatstone bridge built using three additional 10 kΩ (+/− 1%) resisters balanced with a rheostat . Each ofThe 10 Volt range and 16 bit resolution of the CED 1401 data acquisition devise coupled with the 30-fold gain of the CED 1902 amplifier enabled us to achieve a theoretical temperature sensitivity in the order of 0.00002°C that was near linear over the physiological temperature range of interest (20–40°C).   = T+273.15, beta  = 3988 K, K0 = T0+273.15, Range1401  = 10 V, Gain1902  = 30, Rpd   = 10,000, Vpd   = 24 V.T =  temperature in °C, TLeft and right hand temperature recordings were first corrected for minor fluctuations in room temperature by subtracting ambient temperature recordings at the equivalent time-point then de-trended to remove linear drifts across the experimental session. The container-filling phase (40 s), plus the subsequent 10 s  was used to measure video specific baseline temperature recordings. Video induced changes in participants' own hand temperature over the remaining 130 s were then calculated in 10 s epochs by subtracting baseline temperature from ambient corrected left and right hand temperatures. Data were then averaged within subjects to obtain a mean response to each video type e.g. warm/neutral/cool and left/right observed hand then analysed in second level repeated measures ANOVAs using SPSS 21. Video induced changes in heart rate were analysed in an equivalent manner.Subjects completed two questionnaires: the Mehrabian Balanced Emotional Empathy Score (BEES) BEES and Davis IRI total empathy score as well as the Davis sub-scores were then used in a step-wise multiple regression analysis in SPSS21 to investigate whether inter-individual differences in empathy predicted contagion of another's temperature change. Temperature contagion was defined as an individual's mean increase in temperature to all warm videos minus their mean decrease in temperature to all cool videos (averaged across both left and right hands). = 449.25, p<0.001 and F = 256.67, p<0.001 respectively. There was no significant main effect of observed hand  or observed hand by temperature interaction for either rating demonstrating that the perceived temperature was equivalent for left and right hand video stimuli in both warm and cool conditions. We therefore collapsed ratings for observed  hand and repeated the ANOVAs including the neutral condition . This again confirmed that stimulus type  significantly affected ratings of the observed temperature for both the water and hand; F = 305.79, p<0.001 and F = 201.16, p<0.001 respectively. Post-hoc paired-sample t-tests confirmed significant differences  between each pair of stimuli  and observed hand  confirmed that our experimental manipulation significantly modulated participants' ratings of both the water and actors hand temperature, with both rated as appearing significantly warmer in the warm compared to cool conditions F stimuli . = 13.83, p = 0.001, with post-hoc t-test demonstrating a significant reduction in participants' own left (t(35) = −3.54, p = 0.001) and right (t(35) = −2.33, p = 0.026) hand temperature during observation of cool videos but no change to warm videos (p>0.1)  = 4.78, p = 0.036) and a significant participant hand × observed temperature interaction  = 13.49, p = 0.001). Post-hoc t-tests showed that this was driven by a significantly greater reduction in left versus right hand temperature when viewing cool videos (paired t(35) = −3.80, p = 0.001) demonstrating greater sensitivity of participants left hand to observed changes in temperature. Importantly, we did not observe significant observed × own hand or temperature × observed × own hand interactions (p>0.1) suggesting that induced changes in temperature were not influenced by laterality of the observed hand. Finally, there was no change in participants' own left or right hand temperature when they observed the neutral videos (p>0.1) , observed hand  and participants own hand  demonstrated a significant main effect of observed temperature on participants' own hand temperature F (p>0.1) . We alsoThe time scale of induced changes in participants' own hand temperature when viewing warm and videos are illustrated in Repeated measures ANOVA with factors observed temperature , observed hand  and participants own hand  demonstrated no significant effect of observed temperature on participants own heart rate . = 6.82, p<0.003) with an adjusted R2 = 0.25. Exploration of the factors within this model demonstrated a nuanced relationship between empathy and contagion of another's temperature change; specifically in this model the BEES (which provides a single composite measures of empathy) negatively predicted temperature contagion (t(35) = −3.68, p = 0.001, β = −0.92) while the EC sub-scale of the Davis (which selectively measures empathic concern) positively predicted temperature contagion (t(35) = 2.79, p = 0.009, β = 0.69)  sub-scale of the Davis IRI  significantly predicted contagion of observed temperature changes (F = 0.69) .Here we aimed to investigate emotional contagion in the domain of body temperature by showing healthy volunteers video clips of actors with their hands in warm or cold water while simultaneously recording their own right and left hand temperature. We show that healthy participants exhibit contagion of another's hand temperature even in the absence of visible emotional or facial cues. This temperature contagion was particularly prominent for cool stimuli and was more marked for the observers' left hand. However, it should be noted that ice cubes were clearly visible throughout the cool condition but steam visible only at the beginning of the warm videos which may have contributed to this finding. We found no interaction between the laterality of the hand observed and experiencing the change in temperature arguing against common rotational or mirror symmetry effects described in naturalistic social interactions Maintaining a stable internal thermal environment is critical to the life-preserving actions of bioactive proteins, such as enzymes and ion channels. As a consequence, core body temperature is rigidly regulated by the brains of all homeothermic animals including humans through a variety of involuntary thermoregulatory responses, such as shivering and non-shivering thermogenesis, cutaneous vasomotor responses, sweating, piloerection and panting Interestingly, different effectors mechanisms are associated with partially separable central control systems In addition to bottom-up feed-forward pathways triggered by changes in skin temperature, thermoregulatory responses are also sensitive to top-down influences for example though visual imagery, temperature biofeedback and hypnotic suggestion Direct cooling of the hand has been shown to increase blood flow  within the posterior insula Insight into the mechanism underlying temperature contagion may also be usefully informed by studies of disrupted body ownership induced either experimentally using the rubber hand illusion 2 = 0.65, p<0.001) across participants it was participants with relatively high EC compared to BEES scores that showed the greatest propensity to temperature contagion. Alternately this finding may relate to the nature of our experimental stimuli in which we were careful not to show discernable emotional cues. It would be important for future studies to clarify the precise nature of the relationship between individual differences in emotion contagion, empathic distress and concern particularly to such low-level contagion phenomena.Finally, in contrast to our prediction of a simple relationship between sensitivity to temperature contagion and empathy score we found a more nuanced relationship. Specifically, an inverse relationship between BEES emotional empathy score and sensitivity to temperature contagion. i.e. those individual who scored highest on the BEES showed the least sensitivity to temperature contagion. However, when we included both the BEES and the Davis IRI (including subscores) into a stepwise linear regression analysis we showed that though BEES continued to show a negative relationship to temperature contagion the empathic concern subscale of the IRI showed a positive relationship. The basis for these findings is currently unclear, though may relate to subtle differences in the concepts captured by the BEES and EC scales. For example, though we showed a tight positive correlation between BEES and EC scores (RTo conclude, here we show that healthy individuals are sensitive to observable signals of another's peripheral body temperature and further show contagion of their temperature, particularly in the context of cold. Inter-individual differences in temperature contagion are marked and show a complex relationship to inter-individual difference in empathy. Interestingly, abnormal temperature regulation is also observed in disorders of social cognition such as autism


Our results demonstrate that the roughness of oxide-derived copper catalysts plays only a partial role in determining the catalytic performance, while the presence of copper+ is key for lowering the onset potential and enhancing ethylene selectivity.There is an urgent need to develop technologies that use renewable energy to convert waste products such as carbon dioxide into hydrocarbon fuels. Carbon dioxide can be electrochemically reduced to hydrocarbons over copper catalysts, although higher efficiency is required. We have developed oxidized copper catalysts displaying lower overpotentials for carbon dioxide electroreduction and record selectivity towards ethylene (60%) through facile and tunable plasma treatments. Herein we provide insight into the improved performance of these catalysts by combining electrochemical measurements with microscopic and spectroscopic characterization techniques. Operando X-ray absorption spectroscopy and cross-sectional scanning transmission electron microscopy show that copper oxides are surprisingly resistant to reduction and copper Carbon dioxide electroreduction is a promising route to hydrocarbon synthesis, but more efficient and selective catalysts are needed. Here the authors show that plasma-activated copper can catalyse the reduction of carbon dioxide to ethylene with high efficiency and reveal cationic copper as the active site. The electrocatalytic reduction of CO2 (CO2RR) shows promise as a viable CO2 utilization process since it can occur under ambient conditions and low cost copper (Cu) catalysts can facilitate the reduction pathway to hydrocarbons12 to hydrocarbon products (methane and ethylene) while competing with the hydrogen evolution side reaction4567The development of technologies to capture and convert carbon dioxide CO—a greenh2RR. Nanostructured catalysts such as nanoparticles91011121315192 reduction efficiency at lower overpotentials2122232O), and in general display improved current density, enhanced CO2 reduction to carbon monoxide (CO) at low overpotentials, and a partial suppression of methane (CH4) in favour of ethylene (C2H4) at higher overpotentials. Despite these promising results, the mechanism behind the reactivity trends of oxide-derived CO2RR catalysts is still under dispute. Grain boundaries in oxide-derived Cu have been suggested to support unique surface sites which may be active for CO2RR22252829δ+ sites which may remain on the catalyst surface during the reaction have also been suggested to be the active sites31323334ex situ evidence has been presented. This ex situ evidence is complicated by the rapid formation of native oxides on metallic Cu surfaces upon removal from the reactor and exposure to air2RR potentials used ), and that the reaction occurs only on metallic Cu species.Investigations in recent years have led to the development of many interesting metal-based catalytic materials for CO2RR that has not yet been explored. Plasma treatment is a powerful method to activate catalysts, for example by removing capping ligands used in the synthesis of nanoparticles without sintering36382) and hydrogen (H2) plasmas to create novel nanostructured oxide layers and porous surfaces with tunable morphology and chemical state on polycrystalline Cu. These catalysts can lower the onset potential of CO2 reduction to ethylene by 350 mV compared with electropolished Cu, with a maximum faradaic selectivity of >60% at −0.9 V versus RHE. Here, using a combination of characterization techniques—including operando X-ray absorption fine-structure spectroscopy (XAFS), scanning transmission electron microscopy (STEM) equipped with energy dispersive X-ray spectroscopy (EDS)—we gain insight into the catalysts in their working state and find that Cu+ is the active species for reducing CO2 to ethylene. Through our results, we unravel the mechanism behind the improved activity and unique ethylene selectivity of oxide-derived Cu catalysts and lay out the design principles necessary for improved ethylene-selective CO2RR catalysts.Oxygen plasma treatment is a facile and scalable technique to controllably oxidize and nanostructure metal catalysts for CO2 and H2 plasmas of varying power and duration. 2 plasma at 20 W for 2 min (top row) and 100 W for 2 min (middle row) and 10 min (bottom row). By tuning the plasma conditions, the morphology of the surface and oxide thickness can be easily controlled. Growth of the Cu oxide begins at grain boundaries, forming micron-sized wires as shown in in situ during CO2RR, and the resulting surface morphology is shown in the last column of 2 plasma was used (100 W for 10 min), and is shown in To synthesize plasma-activated Cu, electropolished polycrystalline Cu foils were treated in O2RR are shown in 2 plasma treatment, the EDS maps show two well-defined oxide layers over the bulk metallic Cu film. Stoichiometric analysis using EDS data  oxide (CuO). It is also apparent that at grain boundaries and crystallographic domains with the fastest oxide growth, a thick 1.5-μm Cu2O interlayer grows with a thinner 100 nm CuO top layer, while in domains with slower oxide growth, the CuO layer is thicker at 260 nm—as clearly shown in 2 plasma treatment. A 100 nm layer at the surface is reduced entirely to metallic Cu, with the CuO and Cu2O oxide layers being still observed subsurface. After H2 plasma treatment, the sample was exposed to air for more than a week before TEM sample preparation and analysis, and the native Cu oxide layer, measured to be <3 nm thick, was insignificant compared with the thick oxide layers which formed from the plasma treatment and remained during the reaction. This indicates that the observed oxides in our samples before or after reaction are not simply due to surface oxidation in air during the ex situ sample transfer to the TEM. 2RR at −0.91 V versus RHE. Remarkably, after the reaction a single layer with O atom concentration ranging from 3 to 29 atomic % remains with porous and oxygen-rich regions observed. The Cu oxide species are present throughout the layer, indicating that the surface is rich in Cu+ sites which remain stable on the surface and near surface layers during the reaction. This finding challenges the conventional assumption that only metallic Cu (Cu0) is the active species during CO2RR and indicates that Cu+ plays a significant role in the unique reactivity of oxide-derived Cu.To gain further information on the structure and chemical state of the plasma-treated Cu films, cross-sections of the samples were measured using STEM combined with elemental mapping using EDS. Cross-sectional EDS maps of plasma-treated Cu samples before and after COEDS data  resulted2 20 W 2 min plasma-treated sample before and after the reaction. The diffraction analysis confirms that a CuO top layer and Cu2O interlayer exist before the reaction  species, which are not observed here.reaction . After treaction  with 19.2RR and gain insight into the chemical state of the active Cu species, operando X-ray absorption near-edge structure (XANES) and extended XAFS (EXAFS) were used. 2 100 W 2 min plasma-treated Cu measured in fluorescence at small incidence angle (for enhanced surface sensitivity) during CO2RR at −1.2 V versus RHE. Although the thickness of the sample caused dampening of the XAFS signals due to self-absorption, the XANES spectrum of the as-prepared plasma-oxidized Cu shows the features of Cu2O, in particular, the prominent shoulder at the edge marked with a green dashed line at ∼8,982 eV. The presence of metallic Cu and Cu oxide in the initial sample is also clear in the EXAFS data shown in 2O features are still present, and at 1 h, only metallic Cu features are discernable. Although an oxygen content of ∼25–28% is still present in the surface layer of the catalyst after 1 h of reaction according to STEM-EDS, XAFS probes further into the bulk, and when the films are partially reduced, the XAFS signals become dominated by the signal of the metallic Cu underlayer. Nevertheless, we have shown here unquestionably that for our plasma-oxidized Cu catalyst, Cu2O species are present and can participate in the reaction. It is clear that significant changes occur in the bulk of the Cu oxide layer during the first 15 min of reaction in which the initial CuO and Cu2O layers are reconstructed and some of the oxygen is depleted. After this initial change, it is likely that the Cu2O species remain relatively stable in the surface layer, since the activity and selectivity measured after 10 min and 1 h are unchanged for all the oxidized samples, see 2 20 W 2 min sample was observed to be stable over the course of 5 h, suggesting there is no significant change on the active phase during this time  at a constant potential and analysing the reaction products via chromatographic techniques. 2RR which can partially be attributed to the surface roughness. In general, longer and higher power O2 plasma treatment increases the roughness factor . Consistent with results from Kanan and co-workers−) is shifted to lower overpotentials. Furthermore, for our plasma-oxidized Cu, the selectivity towards CO reaches a maximum of 60% at −0.5 V versus RHE, which is three times higher than for electropolished Cu foil. In our study, the onset of ethylene production is also shifted from approximately −0.85 V versus RHE for metallic Cu foils to as low as −0.5 V versus RHE for the most oxidized Cu foils. In addition, we observe a remarkably high selectivity towards ethylene, reaching 60% at −0.9 V versus RHE for the O2 20 W 2 min plasma-treated sample. This value is higher than other oxide-derived Cu catalysts synthesized from thermal oxidation2O21232 plasma-treated samples, which have been exposed to a stronger oxygen plasma treatment and are characterized by the highest roughness factors, also produce trace amounts of ethane, but nonetheless exhibit lower C2H4 selectivities. These results indicate that there is an optimal oxidation treatment to favour ethylene formation, in agreement with results from Ren et alormation , while o2 100 W 2 min treated sample with the same sample which was exposed to an identical O2 plasma treatment plus H2 plasma. Despite their similar roughness . Furthermore, ethylene synthesis and methane suppression are due to the presence of these oxides. It is expected that the fundamental understanding extracted from our experimental study could aid the further design and optimization of oxide-derived Cu catalysts.In summary, we have synthesized superior oxygen-derived Cu catalysts using plasma treatments and used a synergistic combination of advanced 2 or O2 for the indicated plasma power and time. For the O2 100 W 2 min+H2-treated sample, 100 W 10 min of H2 plasma was used.All Cu foils were initially electropolished in 85% phosphoric acid at 3 V versus a titanium foil, then thoroughly rinsed with ultra-pure water and dried with nitrogen. Plasma treatments were performed in 400 mtorr of HSEM images were obtained using a Quanta 200 FEG microscope from FEI with a field emitter as electron source. A secondary electron (Everhart-Thornley) detector was used for the image acquisition. An electron acceleration voltage of 10 kV and a working distance of 10 mm were chosen for the measurements. TEM cross-section samples were prepared using a FEI Helios 600 Dual Beam Focused Ion Beam (FIB) at the Center for Functional Nanomaterials (CFN) at Brookhaven National Laboratory (BNL). The FIB sectioning was performed at 30 keV with final milling at 5 KeV. Spatially resolved elemental maps were acquired using a FEI Titan TEM/STEM microscope with ChemiSTEM technology (X-FEG and SuperX with four windowless silicon drift EDS detectors) operated at 200 kV, at the National Center for Electron Microscopy (NCEM), Molecular Foundry at Lawrence Berkeley National Laboratory (LBL). A Hitachi 9500 TEM at the Nanoscale Fabrication and Characterization Facility (NFCF), University of Pittsburgh operated at 200 keV was used to acquire HRTEM images and SAED patterns.3) was circulated between the cell and a reservoir in which CO2 was continuously bubbled. Measurements were performed in fluorescence at small incidence angle using a passivated implanted planar silicon (PIPS) detector. The acquisition of each spectrum took 15 min, and they were acquired during the first 15 min and after 1 h of reaction.XANES and EXAFS spectra were measured at beamline 2–2 of the Stanford Synchrotron Light Source. A home-built operando electrochemical cell was used, with a platinum foil counter electrode and silver/silver chloride (Ag/AgCl) reference electrode. The samples were mounted behind an X-ray kapton window with 1 mm of electrolyte between the sample and window. The electrolyte . Before and during the electrochemical reaction the cell was purged continuously with CO2 (30 ml min−1), reaching a stable pH value of 6.8.Electrochemical measurements were carried out in a custom made two compartment cell, separated by a Nafion membrane. The glassware was cleaned in a ‘nochromix' bath and afterwards in concentrated HNO−1 between E=+0.05 V/RHE and the working potential (between −0.45 V and −1.0 V/RHE) followed by a chronoamperometric step for 60 min. All reported potentials are corrected for Ohmic drop determined by electrochemical impedance spectroscopy.A platinum mesh 100 (Sigma-Aldrich 99.9%) was used as counter electrode and a leak-free Ag/AgCl electrode as reference electrode (Hugo Sachs Elektronik Harvard apparatus GmbH). The plasma-treated Cu foils were used as working electrode and contacted by a gold clamp. Every measurement was started with a linear voltammetric sweep, performed with a scan rate of −5 mV sAfter 10 and 60 min of bulk electrolysis at constant potential, a sample of the gas was analysed by gas chromatography (Shimadzu GC 2016) to determine the production rate and faradaic selectivity of the gaseous products. In addition, an aliquot of the electrolyte was analysed by a high-performance liquid chromatograph (Agilent 1200 series).The data supporting the findings of this study are available within the article and its How to cite this article: Mistry, H. et al. Highly selective plasma-activated copper catalysts for carbon dioxide reduction to ethylene. Nat. Commun. 7:12123 doi: 10.1038/ncomms12123 (2016).Supplementary Figures 1-9, Supplementary Tables 1-3 and Supplementary References.


The Schrodinger's cat thought experiment highlights the counterintuitive concept of entanglement in macroscopically distinguishable systems. The hallmark of entanglement is the detection of strong correlations between systems, most starkly demonstrated by the violation of a Bell inequality. No violation of a Bell inequality has been observed for a system entangled with a superposition of coherent states, known as a cat state. Here we use the Clauser–Horne–Shimony–Holt formulation of a Bell test to characterize entanglement between an artificial atom and a cat state, or a Bell-cat. Using superconducting circuits with high-fidelity measurements and real-time feedback, we detect correlations that surpass the classical maximum of the Bell inequality. We investigate the influence of decoherence with states up to 16 photons in size and characterize the system by introducing joint Wigner tomography. Such techniques demonstrate that information stored in superpositions of coherent states can be extracted efficiently, a crucial requirement for quantum computing with resonators. Qubit-cavity entanglement can be used for quantum information processing and for investigating the quantum-to-classical transition with high control. Here, the authors characterize the entanglement between an artificial atom and a cat state and its susceptibility to decoherence through Bell test witnesses. Quantum information processing necessitates the creation and detection of complex entangled states. Many physical implementations aim to encode quantum information into large registers of entangled two-level systems, or qubits. Although originally proposed to investigate local hidden variable theory4691314181419202122β. We measure a range in which correlations surpass the Bell inequality threshold and observe its reduction due to decoherence, benchmarking the efficiency of our encoding and detection schemes with cat state qubits.A resonator state can be completely described by direct measurements in the continuous variable basis with the cavity state Wigner functionτs=55 μms) is used for quantum information storage, while the other cavity, with fast field decay (relaxation time τr=30 ns), is used to realize repeated measurements. A transmon qubit  is coupled to both cavity modes and mediates entanglement and measurement of the storage cavity state. All modes have transition frequencies between 5–8 GHz and are off-resonantly coupled. The storage cavity and qubit mode are well described by the dispersive Hamiltonian:This experiment utilizes a circuit quantum electrodynamics architecture1622a is the storage cavity ladder operator, ωs and ωq are the storage cavity and qubit transition frequencies, and χ is the dispersive interaction strength between the two modes (1.4 MHz). This interaction creates a shift in the transition frequency of one mode dependent on the other's excitation number, resulting in qubit–cavity entanglementwhere which we call a Bell-cat state2229Correlating sequential high-fidelity measurements of the qubit and cavity allows state tomography of this composite system. We use a Josephson bifurcation amplifier32X, Y, Z}. This value is recorded and the qubit is reset to Pα of the cavity is subsequently mapped onto the qubit using Ramsey interferometryDα is the displacement operator and P the photon number parity operator, is detected with 95.5% fidelity. The Wigner function α. The correlations between the qubit and cavity states make up what we refer to as the joint Wigner functions:The first measurement detects the qubit along one of its basis vectors {σi is an observable in the qubit Pauli set {I, X, Y, Z}. These four distributions are a complete representation of the combined qubit–cavity quantum state (343536Wi(α) is directly measured with this detection scheme and does not require a density matrix reconstruction. By an overlap integral (Wi(α) are the measured joint Wigner functions , yielding a state fidelity where um state . While ointegral , we deten events . The parW(α) are required to reconstruct the state, known as a DFE25The number of measurement settings required to perform cavity state tomography can be resource intensive. Restricting to an encoded qubit subspace, only four values of the cavity Wigner function Ic, Xc, Yc, Zc} form the Pauli set for the encoded qubit state in the cavity =Xcos(θ/2)+Zsin(θ/2), Z(θ)=Zcos(θ/2)−Xsin(θ/2), Xc, Zc and sweep both qubit detector angle θ  and P(e|e) are the probabilities to get P(g|g)=0.985). Likewise, we find P(e|e)=0.975 by preparing Fq=98%. We find our cavity parity measurement fidelity by purifying the storage cavity thermal state into n=0 photons as P(g|E1) and (P(e|E2)) are the probabilities to measure Fc to decrease with increasing numbers of photons in the cavity due to single-photon loss during the measurement sequence.We define single-shot measurement fidelity as surement . We repoDirectly from these readout fidelities, the estimated visibilityfunction , which wτwait ∼740 ns between the time at which photons first enter the readout resonator and the time at which the feedback pulse resets the qubit.As shown in τwait before feedback can be applied, the cavity state will acquire an additional phase χqsτwait if the qubit is in Feedback is used three times during a single iteration of the experiment. Before the state preparation , we puriMq∈{X, Y, Z}. For each measurement, we observe one of two possible outcomes of the projected cavity state The sequential measurement protocol allows us to observe the result of quantum measurement back action of the qubit on the cavity state. We prepare the system in a Bell-cat state as in See How to cite this article: Vlastakis, B. et al. Characterizing entanglement of an artificial atom and a cavity cat state with Bell's inequality. Nat. Commun. 6:8970 doi: 10.1038/ncomms9970 (2015).Supplementary Figures 1-9, Supplementary Tables 1-3, Supplementary Notes 1-15 and Supplementary References