Categorization in IT and PFC: Model and Experiments

In a recent experiment, Freedman et al. recorded from inferotemporal (IT) and prefrontal cortices (PFC) of monkeys performing a "cat/dog" categorization task (Freedman 2001 and Freedman, Riesenhuber, Poggio, Miller 2001). In this paper we analyze the tuning properties of view-tuned units in our HMAX model of object recognition in cortex (Riesenhuber 1999) using the same paradigm and stimuli as in the experiment. We then compare the simulation results to the monkey inferotemporal neuron population data. We find that view-tuned model IT units that were trained without any explicit category information can show category-related tuning as observed in the experiment. This suggests that the tuning properties of experimental IT neurons might primarily be shaped by bottom-up stimulus-space statistics, with little influence of top-down task-specific information. The population of experimental PFC neurons, on the other hand, shows tuning properties that cannot be explained just by stimulus tuning. These analyses are compatible with a model of object recognition in cortex (Riesenhuber 2000) in which a population of shape-tuned neurons provides a general basis for neurons tuned to different recognition tasks.

Sc1 investigation for key stage 1 and key stage 2 : a bank of differentiated investigations for primary schools.

Este documento es un intento de dar orientación y apoyo a los profesores en la organización de la enseñanza de las ciencias de investigación, en el nivel primario. Se presentan distintas actividades, flexibles para los docentes, a fin de que los niños participen en las distintas etapas del proceso de investigación: planificación, obtención y visualización de resultados y, conclusión y evaluación. Así, desarrolla unos conceptos que permitan la progresión en los conocimientos y en las pruebas prácticas de los alumnos, a nivel individual y, para los diferentes niveles educativos. Se incluyen hojas en blanco para ser rellenadas por los alumnos con sus conclusiones de cada uno de los procesos investigados.

Geostatistical Tools for Validation of Satellite and NWP Model Rainfall

Identifying the critical parameters of a cyanobacterial growth and movement model by using generalised sensitivity analysis

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting the location and timing of the bloom events in lakes and rivers. A new deterministic-mathematical model was developed, which simulates the growth and movement of cyanobacterial blooms in river systems. The model focuses on the mathematical description of the bloom formation, vertical migration and lateral transport of colonies within river environments by taking into account the major factors that affect the cyanobacterial bloom formation in rivers including, light, nutrients and temperature. A technique called generalised sensitivity analysis was applied to the model to identify the critical parameter uncertainties in the model and investigates the interaction between the chosen parameters of the model. The result of the analysis suggested that 8 out of 12 parameters were significant in obtaining the observed cyanobacterial behaviour in a simulation. It was found that there was a high degree of correlation between the half-saturation rate constants used in the model.

Comparative analysis by protocol and key of seed storage behaviour of sixty Vietnamese tree species

Seed storage behaviour of 5 1 native and 9 introduced tree species in Vietnam was investigated using a brief protocol developed to aid biodiversity conservation in circumstances where little is known about the seeds. Of the 60 species, 34 appeared to show orthodox (Acacia auriculaeformis, Adenanthera pavonina, Afzelia xylocarpa, Bauhinia purpurea, Callistemon lanceolatus, Cananga odorata, Canarium nigrum, Cassia fistula, Cassia javanica, Cassia splendida, Chukrasia tabularis, Dalbergia bariaensis, Dialium cochinchinensis, Diospyros mollis, Diospyros mun, Dracuntomelon duperreanum, Erythrophleum fordii, Khaya senegalensis, Lagerstroemia speciosa, Leucaena leucocephala, Livistona cochinchinensis, Markhamia stipulata, Melaleuca cajuputi, Millettia ichthyotona, Peltophorum pterocarpum, Peltophorum tonkinensis, Pinus khasya, Pinus massoniana, Pinus merkusii, Pterocarpus macrocarpus, Sindora siamensis, Sophora tonkinense, Sterculia foetida, Swietenia macrophylla), 13 recalcitrant (Avicennia alba, Beilschmiedia roxburghiana, Caryota mitis, Dimocarpus sp., Diospyros malabarica, Dipterocarpus chartaceus, Dypsis pinnatifrons, Hopea odorata, Lithocarpus gigantophylla, Machilus odoratissimus, Melanorrhoea laccifera, Melanorrhea usitata, Syzygium cinereum) and 13 intermediate (Anisoptera cochinchinensis, Aphanamixis polystachya, Averrhoa carambola, Carissa carandas, Chrysopylum cainito, Cinnamomum camphora, Citrofortunella microcarpa, Citrus grandis var. grandis, Elaeis guineensis, Hydnocarpus anthelmintica, Madhuca floribunda, Manilkara achras, Mimusops elengi) seed storage behaviour. A double-criteria key to estimate likely seed storage behaviour showed good agreement with the above: the key can reduce the workload of seed storage behaviour identification considerably.

Prediction of global and local model quality in CASP8 using the ModFOLD server

The development of effective methods for predicting the quality of three-dimensional (3D) models is fundamentally important for the success of tertiary structure (TS) prediction strategies. Since CASP7, the Quality Assessment (QA) category has existed to gauge the ability of various model quality assessment programs (MQAPs) at predicting the relative quality of individual 3D models. For the CASP8 experiment, automated predictions were submitted in the QA category using two methods from the ModFOLD server-ModFOLD version 1.1 and ModFOLDclust. ModFOLD version 1.1 is a single-model machine learning based method, which was used for automated predictions of global model quality (QMODE1). ModFOLDclust is a simple clustering based method, which was used for automated predictions of both global and local quality (QMODE2). In addition, manual predictions of model quality were made using ModFOLD version 2.0-an experimental method that combines the scores from ModFOLDclust and ModFOLD v1.1. Predictions from the ModFOLDclust method were the most successful of the three in terms of the global model quality, whilst the ModFOLD v1.1 method was comparable in performance to other single-model based methods. In addition, the ModFOLDclust method performed well at predicting the per-residue, or local, model quality scores. Predictions of the per-residue errors in our own 3D models, selected using the ModFOLD v2.0 method, were also the most accurate compared with those from other methods. All of the MQAPs described are publicly accessible via the ModFOLD server at: http://www.reading.ac.uk/bioinf/ModFOLD/. The methods are also freely available to download from: http://www.reading.ac.uk/bioinf/downloads/.

Measurement of acrylamide and its precursors in potato, wheat, and rye model systems

The relationship between acrylamide and its precursors, namely, free asparagine and reducing sugars, was studied in cakes made from potato flake, wholemeal wheat, and wholemeal rye, cooked at 180 degreesC, from 5 to 60 min. Between 5 and 20 min, major losses of asparagine, water, and total reducing sugars were accompanied by large increases in acrylamide, which maximized in all three products between 25 and 30 min, followed by a slow linear reduction. Acrylamide formation did not occur to a large degree until the moisture contents of the cakes fell below 5%. Linear relationships were observed for acrylamide formation with the residual levels of asparagine and reducing sugars for all three food materials.