Modulation of network oscillatory activity and GABAergic synaptic transmission by CB1 cannabinoid receptors in the rat medial entorhinal cortex

Cannabinoids modulate inhibitory GABAergic neurotransmission in many brain regions. Within the temporal lobe, cannabinoid receptors are highly expressed, and are located presynaptically at inhibitory terminals. Here, we have explored the role of type-1 cannabinoid receptors (CB1Rs) at the level of inhibitory synaptic currents and field-recorded network oscillations. We report that arachidonylcyclopropylamide, an agonist at CB1R, inhibits GABAergic synaptic transmission onto both superficial and deep medial entorhinal (mEC) neurones, but this has little effect on network oscillations in beta/gamma frequency bands. By contrast, the CB1R antagonist/inverse agonist LY320135 (500?nM), increased GABAergic synaptic activity and beta/gamma oscillatory activity in superficial mEC, was suppressed, whilst that in deep mEC was enhanced. These data indicate that cannabinoid-mediated effects on inhibitory synaptic activity may be constitutively active in vitro, and that modulation of CB1R activation using inverse agonists unmasks complex effects of CBR function on network activity.

Case based design of knitwear

In the developed world we are surrounded by man-made objects, but most people give little thought to the complex processes needed for their design. The design of hand knitting is complex because much of the domain knowledge is tacit. The objective of this thesis is to devise a methodology to help designers to work within design constraints, whilst facilitating creativity. A hybrid solution including computer aided design (CAD) and case based reasoning (CBR) is proposed. The CAD system creates designs using domain-specific rules and these designs are employed for initial seeding of the case base and the management of constraints. CBR reuses the designer's previous experience. The key aspects in the CBR system are measuring the similarity of cases and adapting past solutions to the current problem. Similarity is measured by asking the user to rank the importance of features; the ranks are then used to calculate weights for an algorithm which compares the specifications of designs. A novel adaptation operator called rule difference replay (RDR) is created. When the specifications to a new design is presented, the CAD program uses it to construct a design constituting an approximate solution. The most similar design from the case-base is then retrieved and RDR replays the changes previously made to the retrieved design on the new solution. A measure of solution similarity that can validate subjective success scores is created. Specification similarity can be used as a guide whether to invoke CBR, in a hybrid CAD-CBR system. If the newly resulted design is suffciently similar to a previous design, then CBR is invoked; otherwise CAD is used. The application of RDR to knitwear design has demonstrated the flexibility to overcome deficiencies in rules that try to automate creativity, and has the potential to be applied to other domains such as interior design.

Case-based reasoning enabling database mining for cryo-preserving algae applications

Case-based Reasoning's (CBR) origins were stimulated by a desire to understand how people remember information and are in turn reminded of information, and that subsequently it was recognized that people commonly solve problems by remembering how they solved similar problems in the past. Thus CBR became an appropriate way to find out the most suitable solution method for a new problem based on the old methods for the same or even similar problems. The research highlights how to use CBR to aid biologists in finding the best method to cryo preserve algae. The study found CBR could be used successfully to find the similarity percentage between the new algae and old cases in the case base. The prediction result showed approximately 93.75% accuracy, which proves the CBR system can offer appropriate recommendations for most situations. © 2011 IEEE.