Towards the automatic reconstruction of dendritic trees using particle filters

The 3D reconstruction of a Golgi-stained dendritic tree from a serial stack of images captured with a transmitted light bright-field microscope is investigated. Modifications to the bootstrap filter are discussed such that the tree structure may be estimated recursively as a series of connected segments. The tracking performance of the bootstrap particle filter is compared against Differential Evolution, an evolutionary global optimisation method, both in terms of robustness and accuracy. It is found that the particle filtering approach is significantly more robust and accurate for the data considered.

Robustness of mutual information to inter-subject variability for automatic artefact removal from EEG

The externally recorded electroencephalogram (EEG) is contaminated with signals that do not originate from the brain, collectively known as artefacts. Thus, EEG signals must be cleaned prior to any further analysis. In particular, if the EEG is to be used in online applications such as Brain-Computer Interfaces (BCIs) the removal of artefacts must be performed in an automatic manner. This paper investigates the robustness of Mutual Information based features to inter-subject variability for use in an automatic artefact removal system. The system is based on the separation of EEG recordings into independent components using a temporal ICA method, RADICAL, and the utilisation of a Support Vector Machine for classification of the components into EEG and artefact signals. High accuracy and robustness to inter-subject variability is achieved.

Semi-automatic knowledge extraction, representation and context-sensitive intelligent retrieval of video content using collateral context modelling with scalable ontological networks

Automatic indexing and retrieval of digital data poses major challenges. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions, or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. For a number of years research has been ongoing in the field of ontological engineering with the aim of using ontologies to add such (meta) knowledge to information. In this paper, we describe the architecture of a system (Dynamic REtrieval Analysis and semantic metadata Management (DREAM)) designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval. The DREAM Demonstrator has been evaluated as deployed in the film post-production phase to support the process of storage, indexing and retrieval of large data sets of special effects video clips as an exemplar application domain. This paper provides its performance and usability results and highlights the scope for future enhancements of the DREAM architecture which has proven successful in its first and possibly most challenging proving ground, namely film production, where it is already in routine use within our test bed Partners' creative processes. (C) 2009 Published by Elsevier B.V.

Automatic nonlinear predictive model-construction algorithm using forward regression and the PRESS statistic

An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.

Automatic artefact removal from event-related potentials via clustering

This paper outlines a method for automatic artefact removal from multichannel recordings of event-related potentials (ERPs). The proposed method is based on, firstly, separation of the ERP recordings into independent components using the method of temporal decorrelation source separation (TDSEP). Secondly, the novel lagged auto-mutual information clustering (LAMIC) algorithm is used to cluster the estimated components, together with ocular reference signals, into clusters corresponding to cerebral and non-cerebral activity. Thirdly, the components in the cluster which contains the ocular reference signals are discarded. The remaining components are then recombined to reconstruct the clean ERPs.

Association between feeding rate and parasitoid resistance in Drosophila melanogaster

Replicate lines of Drosophila melanogaster have been selected for increased resistance against one of two species of parasitoid wasp, Asobara tabida and Leptopilina boulardi. In both cases, it has been shown that an improved ability to mount an immunological defense against the parasitoid's egg is associated with reduced survival when the larvae are reared under conditions of low resource availability and thus high competition. We show here that in both sets of selected lines, lower competitive ability is associated with reduced rates of larval feeding, as measured by the frequency of retractions of the cephalopharyngeal skeleton. This suggests that the same or similar physiological processes are involved in the trade-off between competition and resistance against either parasitoid and shows how the interaction between adaptations for competition and natural enemy resistance may be mediated.

Acquisition of automatic imitation is sensitive to sensorimotor contingency

The associative sequence learning model proposes that the development of the mirror system depends on the same mechanisms of associative learning that mediate Pavlovian and instrumental conditioning. To test this model, two experiments used the reduction of automatic imitation through incompatible sensorimotor training to assess whether mirror system plasticity is sensitive to contingency (i.e., the extent to which activation of one representation predicts activation of another). In Experiment 1, residual automatic imitation was measured following incompatible training in which the action stimulus was a perfect predictor of the response (contingent) or not at all predictive of the response (noncontingent). A contingency effect was observed: There was less automatic imitation indicative of more learning in the contingent group. Experiment 2 replicated this contingency effect and showed that, as predicted by associative learning theory, it can be abolished by signaling trials in which the response occurs in the absence of an action stimulus. These findings support the view that mirror system development depends on associative learning and indicate that this learning is not purely Hebbian. If this is correct, associative learning theory could be used to explain, predict, and intervene in mirror system development.

Effect of feeding fat or intrajugular infusion of glucagon-like peptide-1 and cholecystokinin on dry matter intake, digestibility, and digesta rate of passage in growing wethers

A cause and effect relationship between glucagon-like peptide 1 (7, 36) amide (GLP-1) and cholecystokinin (CCK) and DMI regulation has not been established in ruminants. Three randomized complete block experiments were conducted to determine the effect of feeding fat or infusing GLP-1 or CCK intravenously on DMI, nutrient digestibility, and Cr rate of passage (using Cr(2)O(3) as a marker) in wethers. A total of 18 Targhee × Hampshire wethers (36.5 ± 2.5 kg of BW) were used, and each experiment consisted of four 21-d periods (14 d for adaptation and 7 d for infusion and sampling). Wethers allotted to the control treatments served as the controls for all 3 experiments; experiments were performed simultaneously. The basal diet was 60% concentrate and 40% forage. In Exp. 1, treatments were the control (0% added fat) and addition of 4 or 6% Ca salts of palm oil fatty acids (DM basis). Treatments in Exp. 2 and 3 were the control and 3 jugular vein infusion dosages of GLP-1 (0.052, 0.103, or 0.155 µg•kg of BW(-1)•d(-1)) or CCK (0.069, 0.138, or 0.207 µg•kg of BW(-1)•d(-1)), respectively. Increases in plasma GLP-1 and CCK concentrations during hormone infusions were comparable with increases observed when increasing amounts of fat were fed. Feeding fat and infusion of GLP-1 tended (linear, P = 0.12; quadratic, P = 0.13) to decrease DMI. Infusion of CCK did not affect (P > 0.21) DMI. Retention time of Cr in the total gastrointestinal tract decreased (linear, P < 0.01) when fat was fed, but was not affected by GLP-1 or CCK infusion. In conclusion, jugular vein infusion produced similar plasma CCK and GLP-1 concentrations as observed when fat was fed. The effects of feeding fat on DMI may be partially regulated by plasma concentration of GLP-1, but are not likely due solely to changes in a single hormone concentration.