The temporal impulse response underlying saccadic decisions

Models of perceptual decision making often assume that sensory evidence is accumulated over time in favor of the various possible decisions, until the evidence in favor of one of them outweighs the evidence for the others. Saccadic eye movements are among the most frequent perceptual decisions that the human brain performs. We used stochastic visual stimuli to identify the temporal impulse response underlying saccadic eye movement decisions. Observers performed a contrast search task, with temporal variability in the visual signals. In experiment 1, we derived the temporal filter observers used to integrate the visual information. The integration window was restricted to the first similar to 100 ms after display onset. In experiment 2, we showed that observers cannot perform the task if there is no useful information to distinguish the target from the distractor within this time epoch. We conclude that (1) observers did not integrate sensory evidence up to a criterion level, (2) observers did not integrate visual information up to the start of the saccadic dead time, and (3) variability in saccade latency does not correspond to variability in the visual integration period. Instead, our results support a temporal filter model of saccadic decision making. The temporal impulse response identified by our methods corresponds well with estimates of integration times of V1 output neurons.

The effects of mass loading the ossicles with a floating mass transducer on middle ear transfer function

Hypothesis: The aim of this study was to measure the mass loading effect of an active middle-ear implant (the Vibrant Soundbridge) in cadaver temporal bones. Background: Implantable middle ear hearing devices such as Vibrant Soundbridge have been used as an alternative to conventional hearing aids for the rehabilitation of sensorineural hearing loss. Other than the obvious disadvantage of requiring implantation middle ear surgery, it also applies a direct weight on the ossicular chain which, in turn, may have an impact on residual hearing. Previous studies have shown that applying a mass directly on the ossicular chain has a damping effect on its response to sound. However, little has been done to investigate the magnitude and the frequency characteristics of the mass loading effect in devices such as the Vibrant Soundbridge. Methods: Five fresh cadaver temporal bones were used. The stapes displacement was measured using laser Doppler vibrometry before and after the placement of a Vibrant Sound-bridge floating mass transducer. The effects of mass and attachment site were compared with the unloaded response. Measurements were obtained at frequencies between 0.1 and 10 kHz and at acoustic input levels of 100 dB sound pressure level. Each temporal bone acted as its own control. Results: Placement of the floating mass transducer caused a reduction of the stapes displacement. There were variations between the bones. The change of the stapes displacement varied from 0 dB to 28 dB. The effect was more prominent at frequencies above 1,000 Hz. Placing the floating mass transducer close to the incudostapedial joint reduced the mass loading effect. Conclusion: The floating mass transducer produces a measurable reduction of the stapes displacement in the temporal bone model. The effect is more prominent at high frequencies.

A compositional framework for hardware/software co-design

We describe a compositional framework, together with its supporting toolset, for hardware/software co-design. Our framework is an integration of a formal approach within a traditional design flow. The formal approach is based on Interval Temporal Logic and its executable subset, Tempura. Refinement is the key element in our framework because it will derive from a single formal specification of the system the software and hardware parts of the implementation, while preserving all properties of the system specification. During refinement simulation is used to choose the appropriate refinement rules, which are applied automatically in the HOL system. The framework is illustrated with two case studies. The work presented is part of a UK collaborative research project between the Software Technology Research Laboratory at the De Montfort University and the Oxford University Computing Laboratory.

Modeling building semantics: providing feedback and sustainability

Even minor changes in user activity can bring about significant energy savings within built space. Many building performance assessment methods have been developed, however these often disregard the impact of user behavior (i.e. the social, cultural and organizational aspects of the building). Building users currently have limited means of determining how sustainable they are, in context of the specific building structure and/or when compared to other users performing similar activities, it is therefore easy for users to dismiss their energy use. To support sustainability, buildings must be able to monitor energy use, identify areas of potential change in the context of user activity and provide contextually relevant information to facilitate persuasion management. If the building is able to provide users with detailed information about how specific user activity that is wasteful, this should provide considerable motivation to implement positive change. This paper proposes using a dynamic and temporal semantic model, to populate information within a model of persuasion, to manage user change. By semantically mapping a building, and linking this to persuasion management we suggest that: i) building energy use can be monitored and analyzed over time; ii) persuasive management can be facilitated to move user activity towards sustainability.

Temporal constraints on linear BRDF model parameters

Linear models of bidirectional reflectance distribution are useful tools for understanding the angular variability of surface reflectance as observed by medium-resolution sensors such as the Moderate Resolution Imaging Spectrometer. These models are operationally used to normalize data to common view and illumination geometries and to calculate integral quantities such as albedo. Currently, to compensate for noise in observed reflectance, these models are inverted against data collected during some temporal window for which the model parameters are assumed to be constant. Despite this, the retrieved parameters are often noisy for regions where sufficient observations are not available. This paper demonstrates the use of Lagrangian multipliers to allow arbitrarily large windows and, at the same time, produce individual parameter sets for each day even for regions where only sparse observations are available.

Assessing the spatial and temporal variation in the skill of precipitation forecasts from an NWP model

It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques.

Technical note: a simple procedure for removing temporal discontinuities in ERA-Interim upper stratospheric temperatures for use in nudged chemistry-climate model simulations

This note describes a simple procedure for removing unphysical temporal discontinuities in ERA-Interim upper stratospheric global mean temperatures in March 1985 and August 1998 that have arisen due to changes in satellite radiance data used in the assimilation. The derived temperature adjustments (offsets) are suitable for use in stratosphere-resolving chemistry-climate models that are nudged (relaxed) to ERA-Interim winds and temperatures. Simulations using a nudged version of the Canadian Middle Atmosphere Model (CMAM) show that the inclusion of the temperature adjustments produces temperature time series that are devoid of the large jumps in 1985 and 1998. Due to its strong temperature dependence, the simulated upper stratospheric ozone is also shown to vary smoothly in time, unlike in a nudged simulation without the adjustments where abrupt changes in ozone occur at the times of the temperature jumps. While the adjustments to the ERA-Interim temperatures remove significant artefacts in the nudged CMAM simulation, spurious transient effects that arise due to water vapour and persist for about 5 yr after the 1979 switch to ERA-Interim data are identified, underlining the need for caution when analysing trends in runs nudged to reanalyses.

Analysis of convectively-generated gravity waves in mesoscale model simulations and wind profiler observations

The characteristics of convectively-generated gravity waves during an episode of deep convection near the coast of Wales are examined in both high resolution mesoscale simulations [with the (UK) Met Oce Unified Model] and in observations from a Mesosphere-Stratosphere-Troposphere (MST) wind profiling Doppler radar. Deep convection reached the tropopause and generated vertically propagating, high frequency waves in the lower stratosphere that produced vertical velocity perturbations O(1 m/s). Wavelet analysis is applied in order to determine the characteristic periods and wavelengths of the waves. In both the simulations and observations, the wavelet spectra contain several distinct preferred scales indicated by multiple spectral peaks. The peaks are most pronounced in the horizontal spectra at several wavelengths less than 50 km. Although these peaks are most clear and of largest amplitude in the highest resolution simulations (with 1 km horizontal grid length), they are also evident in coarser simulations (with 4 km horizontal grid length). Peaks also exist in the vertical and temporal spectra (between approximately 2.5 and 4.5 km, and 10 to 30 minutes, respectively) with good agreement between simulation and observation. Two-dimensional (wavenumber-frequency) spectra demonstrate that each of the selected horizontal scales contains peaks at each of preferred temporal scales revealed by the one- dimensional spectra alone.

Uncertainty assessment of a process-based integrated catchment model of phosphorus

Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.

Impulsiveness as a timing disturbance: neurocognitive abnormalities in attention-deficit hyperactivity disorder during temporal processes and normalization with methylphenidate.

We argue that impulsiveness is characterized by compromised timing functions such as premature motor timing, decreased tolerance to delays, poor temporal foresight and steeper temporal discounting. A model illustration for the association between impulsiveness and timing deficits is the impulsiveness disorder of attention-deficit hyperactivity disorder (ADHD). Children with ADHD have deficits in timing processes of several temporal domains and the neural substrates of these compromised timing functions are strikingly similar to the neuropathology of ADHD. We review our published and present novel functional magnetic resonance imaging data to demonstrate that ADHD children show dysfunctions in key timing regions of prefrontal, cingulate, striatal and cerebellar location during temporal processes of several time domains including time discrimination of milliseconds, motor timing to seconds and temporal discounting of longer time intervals. Given that impulsiveness, timing abnormalities and more specifically ADHD have been related to dopamine dysregulation, we tested for and demonstrated a normalization effect of all brain dysfunctions in ADHD children during time discrimination with the dopamine agonist and treatment of choice, methylphenidate. This review together with the new empirical findings demonstrates that neurocognitive dysfunctions in temporal processes are crucial to the impulsiveness disorder of ADHD and provides first evidence for normalization with a dopamine reuptake inhibitor.

Development and assessment of a coupled crop-climate model

It is well established that crop production is inherently vulnerable to variations in the weather and climate. More recently the influence of vegetation on the state of the atmosphere has been recognized. The seasonal growth of crops can influence the atmosphere and have local impacts on the weather, which in turn affects the rate of seasonal crop growth and development. Considering the coupled nature of the crop-climate system, and the fact that a significant proportion of land is devoted to the cultivation of crops, important interactions may be missed when studying crops and the climate system in isolation, particularly in the context of land use and climate change. To represent the two-way interactions between seasonal crop growth and atmospheric variability, we integrate a crop model developed specifically to operate at large spatial scales (General Large Area Model for annual crops) into the land surface component of a global climate model (GCM; HadAM3). In the new coupled crop-climate model, the simulated environment (atmosphere and soil states) influences growth and development of the crop, while simultaneously the temporal variations in crop leaf area and height across its growing season alter the characteristics of the land surface that are important determinants of surface fluxes of heat and moisture, as well as other aspects of the land-surface hydrological cycle. The coupled model realistically simulates the seasonal growth of a summer annual crop in response to the GCM's simulated weather and climate. The model also reproduces the observed relationship between seasonal rainfall and crop yield. The integration of a large-scale single crop model into a GCM, as described here, represents a first step towards the development of fully coupled crop and climate models. Future development priorities and challenges related to coupling crop and climate models are discussed.