Theory and generalization of Monte Carlo models of the BOLD signal source

The dependency of the blood oxygenation level dependent (BOLD) signal on underlying hemodynamics is not well understood. Building a forward biophysical model of this relationship is important for the quantitative estimation of the hemodynamic changes and neural activity underlying functional magnetic resonance imaging (fMRI) signals. We have developed a general model of the BOLD signal which can model both intra- and extravascular signals for an arbitrary tissue model across a wide range of imaging parameters. The model of the BOLD signal was instantiated as a look-up-table (LuT), and was verified against concurrent fMRI and optical imaging measurements of activation induced hemodynamics. Magn Reson Med, 2008. © 2008 Wiley-Liss, Inc.

Differentiating core and co-opted mechanisms in calculation: The neuroimaging of calculation in aphasia

The role of language in exact calculation is the subject of debate. Some behavioral and functional neuroimaging investigations of healthy participants suggest that calculation requires language resources. However, there are also reports of individuals with severe aphasic language impairment who retain calculation ability. One possibility in resolving these discordant findings is that the neural basis of calculation has undergone significant reorganization in aphasic calculators. Using fMRI, we examined brain activations associated with exact addition and subtraction in two patients with severe agrammatic aphasia and retained calculation ability. Behavior and brain activations during two-digit addition and subtraction were compared to those of a group of 11 healthy, age-matched controls. Behavioral results confirmed that both patients retained calculation ability. Imaging findings revealed individual differences in processing, but also a similar activation pattern across patients and controls in bilateral parietal cortices. Patients differed from controls in small areas of increased activation in peri-lesional regions, a shift from left fronto-temporal activation to the contralateral region, and increased activations in bilateral superior parietal regions. Our results suggest that bilateral parietal cortex represents the core of the calculation network and, while healthy controls may recruit language resources to support calculation, these mechanisms are not mandatory in adult cognition.

The resting-state neurovascular coupling relationship: rapid changes in spontaneous neural activity in the somatosensory cortex are associated with haemodynamic fluctuations that resemble stimulus-evoked haemodynamics

Although promise exists for patterns of resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) brain connectivity to be used as biomarkers of early brain pathology, a full understanding of the nature of the relationship between neural activity and spontaneous fMRI BOLD fluctuations is required before such data can be correctly interpreted. To investigate this issue, we combined electrophysiological recordings of rapid changes in multi-laminar local field potentials from the somatosensory cortex of anaesthetized rats with concurrent two-dimensional optical imaging spectroscopy measurements of resting-state haemodynamics that underlie fluctuations in the BOLD fMRI signal. After neural ‘events’ were identified, their time points served to indicate the start of an epoch in the accompanying haemodynamic fluctuations. Multiple epochs for both neural ‘events’ and the accompanying haemodynamic fluctuations were averaged. We found that the averaged epochs of resting-state haemodynamic fluctuations taken after neural ‘events’ closely resembled the temporal profile of stimulus-evoked cortical haemodynamics. Furthermore, we were able to demonstrate that averaged epochs of resting-state haemodynamic fluctuations resembling the temporal profile of stimulus-evoked haemodynamics could also be found after peaks in neural activity filtered into specific electroencephalographic frequency bands (theta, alpha, beta, and gamma). This technique allows investigation of resting-state neurovascular coupling using methodologies that are directly comparable to that developed for investigating stimulus-evoked neurovascular responses.

Updating existing emotional memories involves the frontopolar/orbitofrontal cortex in ways that acquiring new emotional memories does not

In life, we must often learn new associations to people, places, or things we already know. The current fMRI study investigated the neural mechanisms underlying emotional memory updating. Nineteen participants first viewed negative and neutral pictures and learned associations between those pictures and other neutral stimuli, such as neutral objects and encoding tasks. This initial learning phase was followed by a memory updating phase, during which participants learned picture-location associations for old pictures (i.e., pictures previously associated with other neutral stimuli) and new pictures (i.e., pictures not seen in the first phase). There was greater frontopolar/orbito-frontal (OFC) activity when people learned picture–location associations for old negative pictures than for new negative pictures, but frontopolar OFC activity did not significantly differ during learning locations of old versus new neutral pictures. In addition, frontopolar activity was more negatively correlated with the amygdala when participants learned picture–location associations for old negative pictures than for new negative or old neutral pictures. Past studies revealed that the frontopolar OFC allows for updating the affective values of stimuli in reversal learning or extinction of conditioning [e.g., Izquierdo, A., & Murray, E. A. Opposing effects of amygdala and orbital PFC lesions on the extinction of instrumental responding in macaque monkeys. European Journal of Neuroscience, 22, 2341–2346, 2005]; our findings suggest that it plays a more general role in updating associations to emotional stimuli.

Amygdala functional connectivity with medial prefrontal cortex at rest predicts the positivity effect in older adults’ memory

As people get older, they tend to remember more positive than negative information. This age-by-valence interaction has been called “positivity effect.” The current study addressed the hypotheses that baseline functional connectivity at rest is predictive of older adults' brain activity when learning emotional information and their positivity effect in memory. Using fMRI, we examined the relationship among resting-state functional connectivity, subsequent brain activity when learning emotional faces, and individual differences in the positivity effect (the relative tendency to remember faces expressing positive vs. negative emotions). Consistent with our hypothesis, older adults with a stronger positivity effect had increased functional coupling between amygdala and medial PFC (MPFC) during rest. In contrast, younger adults did not show the association between resting connectivity and memory positivity. A similar age-by-memory positivity interaction was also found when learning emotional faces. That is, memory positivity in older adults was associated with (a) enhanced MPFC activity when learning emotional faces and (b) increased negative functional coupling between amygdala and MPFC when learning negative faces. In contrast, memory positivity in younger adults was related to neither enhanced MPFC activity to emotional faces, nor MPFC–amygdala connectivity to negative faces. Furthermore, stronger MPFC–amygdala connectivity during rest was predictive of subsequent greater MPFC activity when learning emotional faces. Thus, emotion–memory interaction in older adults depends not only on the task-related brain activity but also on the baseline functional connectivity.

Sex differences in reward-related decision processing under stress

Recent research indicates gender differences in the impact of stress on decision behavior, but little is known about the brain mechanisms involved in these gender-specific stress effects. The current study used functional magnetic resonance imaging (fMRI) to determine whether induced stress resulted in gender-specific patterns of brain activation during a decision task involving monetary reward. Specifically, we manipulated physiological stress levels using a cold pressor task, prior to a risky decision making task. Healthy men (n = 24, 12 stressed) and women (n = 23, 11 stressed) completed the decision task after either cold pressor stress or a control task during the period of cortisol response to the cold pressor. Gender differences in behavior were present in stressed participants but not controls, such that stress led to greater reward collection and faster decision speed in males but less reward collection and slower decision speed in females. A gender-by-stress interaction was observed for the dorsal striatum and anterior insula. With cold stress, activation in these regions was increased in males but decreased in females. The findings of this study indicate that the impact of stress on reward-related decision processing differs depending on gender.

Primary evolving networks and the comparative analysis of robust and fragile structures

In this paper we consider the structure of dynamically evolving networks modelling information and activity moving across a large set of vertices. We adopt the communicability concept that generalizes that of centrality which is defined for static networks. We define the primary network structure within the whole as comprising of the most influential vertices (both as senders and receivers of dynamically sequenced activity). We present a methodology based on successive vertex knockouts, up to a very small fraction of the whole primary network,that can characterize the nature of the primary network as being either relatively robust and lattice-like (with redundancies built in) or relatively fragile and tree-like (with sensitivities and few redundancies). We apply these ideas to the analysis of evolving networks derived from fMRI scans of resting human brains. We show that the estimation of performance parameters via the structure tests of the corresponding primary networks is subject to less variability than that observed across a very large population of such scans. Hence the differences within the population are significant.

Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe

Aim  Species distribution models (SDMs) based on current species ranges underestimate the potential distribution when projected in time and/or space. A multi-temporal model calibration approach has been suggested as an alternative, and we evaluate this using 13,000 years of data. Location  Europe. Methods  We used fossil-based records of presence for Picea abies, Abies alba and Fagus sylvatica and six climatic variables for the period 13,000 to 1000 yr bp. To measure the contribution of each 1000-year time step to the total niche of each species (the niche measured by pooling all the data), we employed a principal components analysis (PCA) calibrated with data over the entire range of possible climates. Then we projected both the total niche and the partial niches from single time frames into the PCA space, and tested if the partial niches were more similar to the total niche than random. Using an ensemble forecasting approach, we calibrated SDMs for each time frame and for the pooled database. We projected each model to current climate and evaluated the results against current pollen data. We also projected all models into the future. Results  Niche similarity between the partial and the total-SDMs was almost always statistically significant and increased through time. SDMs calibrated from single time frames gave different results when projected to current climate, providing evidence of a change in the species realized niches through time. Moreover, they predicted limited climate suitability when compared with the total-SDMs. The same results were obtained when projected to future climates. Main conclusions  The realized climatic niche of species differed for current and future climates when SDMs were calibrated considering different past climates. Building the niche as an ensemble through time represents a way forward to a better understanding of a species' range and its ecology in a changing climate.

Habitual energy expenditure modifies the association between NOS3 gene polymorphisms and blood pressue

BACKGROUND: The endothelial nitric-oxide synthase (NOS3) gene encodes the enzyme (eNOS) that synthesizes the molecule nitric oxide, which facilitates endothelium-dependent vasodilation in response to physical activity. Thus, energy expenditure may modify the association between the genetic variation at NOS3 and blood pressure. METHODS: To test this hypothesis, we genotyped 11 NOS3 polymorphisms, capturing all common variations, in 726 men and women from the Medical Research Council (MRC) Ely Study (age (mean +/- s.d.): 55 +/- 10 years, body mass index: 26.4 +/- 4.1 kg/m(2)). Habitual/non-resting energy expenditure (NREE) was assessed via individually calibrated heart rate monitoring over 4 days. RESULTS: The intronic variant, IVS25+15 [G-->A], was significantly associated with blood pressure; GG homozygotes had significantly lower levels of diastolic blood pressure (DBP) (-2.8 mm Hg; P = 0.016) and systolic blood pressure (SBP) (-1.9 mm Hg; P = 0.018) than A-allele carriers. The interaction between NREE and IVS25+15 was also significant for both DBP (P = 0.006) and SBP (P = 0.026), in such a way that the effect of the GG-genotype on blood pressure was stronger in individuals with higher NREE (DBP: -4.9 mm Hg, P = 0.02. SBP: -3.8 mm Hg, P= 0.03 for the third tertile). Similar results were observed when the outcome was dichotomously defined as hypertension. CONCLUSIONS: In summary, the NOS3 IVS25+15 is directly associated with blood pressure and hypertension in white Europeans. However, the associations are most evident in the individuals with the highest NREE. These results need further replication and have to be ideally tested in a trial before being informative for targeted disease prevention. Eventually, the selection of individuals for lifestyle intervention programs could be guided by knowledge of genotype.

Linking urban water balance and energy balance models to analyse urban design options

Using a water balance modelling framework, this paper analyses the effects of urban design on the water balance, with a focus on evapotranspiration and storm water. First, two quite different urban water balance models are compared: Aquacycle which has been calibrated for a suburban catchment in Canberra, Australia, and the single-source urban evapotranspiration-interception scheme (SUES), an energy-based approach with a biophysically advanced representation of interception and evapotranspiration. A fair agreement between the two modelled estimates of evapotranspiration was significantly improved by allowing the vegetation cover (leaf area index, LAI) to vary seasonally, demonstrating the potential of SUES to quantify the links between water sensitive urban design and microclimates and the advantage of comparing the two modelling approaches. The comparison also revealed where improvements to SUES are needed, chiefly through improved estimates of vegetation cover dynamics as input to SUES, and more rigorous parameterization of the surface resistance equations using local-scale suburban flux measurements. Second, Aquacycle is used to identify the impact of an array of water sensitive urban design features on the water balance terms. This analysis confirms the potential to passively control urban microclimate by suburban design features that maximize evapotranspiration, such as vegetated roofs. The subsequent effects on daily maximum air temperatures are estimated using an atmospheric boundary layer budget. Potential energy savings of about 2% in summer cooling are estimated from this analysis. This is a clear ‘return on investment’ of using water to maintain urban greenspace, whether as parks distributed throughout an urban area or individual gardens or vegetated roofs.

Effects of temporal resolution of input precipitation on the performance of hydrological forecasting

Flood prediction systems rely on good quality precipitation input data and forecasts to drive hydrological models. Most precipitation data comes from daily stations with a good spatial coverage. However, some flood events occur on sub-daily time scales and flood prediction systems could benefit from using models calibrated on the same time scale. This study compares precipitation data aggregated from hourly stations (HP) and data disaggregated from daily stations (DP) with 6-hourly forecasts from ECMWF over the time period 1 October 2006–31 December 2009. The HP and DP data sets were then used to calibrate two hydrological models, LISFLOOD-RR and HBV, and the latter was used in a flood case study. The HP scored better than the DP when evaluated against the forecast for lead times up to 4 days. However, this was not translated in the same way to the hydrological modelling, where the models gave similar scores for simulated runoff with the two datasets. The flood forecasting study showed that both datasets gave similar hit rates whereas the HP data set gave much smaller false alarm rates (FAR). This indicates that using sub-daily precipitation in the calibration and initiation of hydrological models can improve flood forecasting.

Updated radiative forcing estimates of 65 halocarbons and nonmethane hydrocarbons

The direct radiative forcing of 65 chlorofluorocarbons, hydrochlorofluorocarbons, hydrofluorocarbons, hydrofluoroethers, halons, iodoalkanes, chloroalkanes, bromoalkanes, perfluorocarbons and nonmethane hydrocarbons has been evaluated using a consistent set of infrared absorption cross sections. For the radiative transfer models, both line-by-line and random band model approaches were employed for each gas. The line-by-line model was first validated against measurements taken by the Airborne Research Interferometer Evaluation System (ARIES) of the U.K. Meteorological Office; the computed spectrally integrated radiance of agreed to within 2% with experimental measurements. Three model atmospheres, derived from a three-dimensional climatology, were used in the radiative forcing calculations to more accurately represent hemispheric differences in water vapor, ozone concentrations, and cloud cover. Instantaneous, clear-sky radiative forcing values calculated by the line-by-line and band models were in close agreement. The band model values were subsequently modified to ensure exact agreement with the line-by-line model values. Calibrated band model radiative forcing values, for atmospheric profiles with clouds and using stratospheric adjustment, are reported and compared with previous literature values. Fourteen of the 65 molecules have forcings that differ by more than 15% from those in the World Meteorological Organization [1999] compilation. Eleven of the molecules have not been reported previously. The 65-molecule data set reported here is the most comprehensive and consistent database yet available to evaluate the relative impact of halocarbons and hydrocarbons on climate change.

Evaluating the Bank of England density forecasts of inflation

We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per annum. Finally, we discuss the decision-based approach to forecast evaluation in relation to the MPC forecasts

Making an effort to feel positive: insecure attachment in infancy predicts the neural underpinnings of emotion regulation in adulthood

Background: Animal research indicates that the neural substrates of emotion regulation may be persistently altered by early environmental exposures. If similar processes operate in human development then this is significant, as the capacity to regulate emotional states is fundamental to human adaptation. Methods: We utilised a 22-year longitudinal study to examine the influence of early infant attachment to the mother, a key marker of early experience, on neural regulation of emotional states in young adults. Infant attachment status was measured via objective assessment at 18-months, and the neural underpinnings of the active regulation of affect were studied using fMRI at age 22 years. Results: Infant attachment status at 18-months predicted neural responding during the regulation of positive affect 20-years later. Specifically, while attempting to up-regulate positive emotions, adults who had been insecurely versus securely attached as infants showed greater activation in prefrontal regions involved in cognitive control and reduced co-activation of prefrontal cortex and nucleus accumbens, consistent with relative inefficiency in the neural regulation of positive affect. Conclusions: Disturbances in the mother-infant relationship may persistently alter the neural circuitry of emotion regulation, with potential implications for adjustment in adulthood.

Reducing inconsistencies in point observations of maximum flood inundation level

Flood simulation models and hazard maps are only as good as the underlying data against which they are calibrated and tested. However, extreme flood events are by definition rare, so the observational data of flood inundation extent are limited in both quality and quantity. The relative importance of these observational uncertainties has increased now that computing power and accurate lidar scans make it possible to run high-resolution 2D models to simulate floods in urban areas. However, the value of these simulations is limited by the uncertainty in the true extent of the flood. This paper addresses that challenge by analyzing a point dataset of maximum water extent from a flood event on the River Eden at Carlisle, United Kingdom, in January 2005. The observation dataset is based on a collection of wrack and water marks from two postevent surveys. A smoothing algorithm for identifying, quantifying, and reducing localized inconsistencies in the dataset is proposed and evaluated showing positive results. The proposed smoothing algorithm can be applied in order to improve flood inundation modeling assessment and the determination of risk zones on the floodplain.