Simulation of associative learning with the replaced elements model

Associative learning theories can be categorised according to whether they treat the representation of stimulus compounds in an elemental or configural manner. Since it is clear that a simple elemental approach to stimulus representation is inadequate there have been several attempts to produce more elaborate elemental models. One recent approach, the Replaced Elements Model (Wagner, 2003), reproduces many results that have until recently been uniquely predicted by Pearce’s Configural Theory (Pearce, 1994). Although it is possible to simulate the Replaced Elements Model using “standard” simulation programs the generation of the correct stimulus representation is complex. The current paper describes a method for simulation of the Replaced Elements Model and presents the results of two example simulations that show differential predictions of Replaced Elements and Pearce’s Configural Theor

Theoretical studies of the historical development of the accounting discipline: a review and evidence

Many existing studies of the development of accounting thought have either been atheoretical or have adopted Kuhn's model of scientific growth. The limitations of this 35-year-old model are discussed. Four different general neo-Kuhnian models of scholarly knowledge development are reviewed and compared with reference to an analytical matrix. The models are found to be mutually consistent, with each focusing on a different aspect of development. A composite model is proposed. Based on a hand-crafted database, author co-citation analysis is used to map empirically the entire literature structure of the accounting discipline during two consecutive time periods, 1972–81 and 1982–90. The changing structure of the accounting literature is interpreted using the proposed composite model of scholarly knowledge development

AutoEPG: software for the analysis of electrical activity in the microcircuit underpinning feeding behaviour of caenorhabditis elegans

BackgroundThe pharyngeal microcircuit of the nematode Caenorhabditis elegans serves as a model for analysing neural network activity and is amenable to electrophysiological recording techniques. One such technique is the electropharyngeogram (EPG) which has provided insight into the genetic basis of feeding behaviour, neurotransmission and muscle excitability. However, the detailed manual analysis of the digital recordings necessary to identify subtle differences in activity that reflect modulatory changes within the underlying network is time consuming and low throughput. To address this we have developed an automated system for the high-throughput and discrete analysis of EPG recordings (AutoEPG).Methodology/Principal FindingsAutoEPG employs a tailor made signal processing algorithm that automatically detects different features of the EPG signal including those that report on the relaxation and contraction of the muscle and neuronal activity. Manual verification of the detection algorithm has demonstrated AutoEPG is capable of very high levels of accuracy. We have further validated the software by analysing existing mutant strains with known pharyngeal phenotypes detectable by the EPG. In doing so, we have more precisely defined an evolutionarily conserved role for the calcium-dependent potassium channel, SLO-1, in modulating the rhythmic activity of neural networks.Conclusions/SignificanceAutoEPG enables the consistent analysis of EPG recordings, significantly increases analysis throughput and allows the robust identification of subtle changes in the electrical activity of the pharyngeal nervous system. It is anticipated that AutoEPG will further add to the experimental tractability of the C. elegans pharynx as a model neural circuit

Responses to alcoholic drink cues in human subjects

SIGLEAvailable from British Library Document Supply Centre- DSC:DX183078 / BLDSC - British Library Document Supply CentreGBUnited Kingdo