The Role of G Protein In Alcohol Related Behaviours Using Drosophila melanogaster As A Model

Ethanol, classified as a drug, affects the central nervous system, and its consumption has been linked to the development of several behaviours including tolerance and dependence. Alcohol tolerance is defined as the need for higher doses of alcohol to induce the same changes observed in the initial exposure or where repetitive exposures of the same alcohol dose induce a lower response. Ethanol has been shown to interact with numerous targets and ultimately influence both short and long term adaptation at the cellular and molecular level in brain [1]. These adaptation processes are likely to involve signalling molecules: our work has focussed on G proteins gene expression. Using both wild type and several mutant fruit fly (Drosophila melanogaster) as a model for behaviour and molecular studies, we observed significant increases in sedation time (ST50) in response to alcohol (P<0.001) Fig.A. We also observed a consistent and significant decrease of Gq protein mRNA expression in Drosophila dUNC and DopR2 mutants chronically exposed to alcohol (*P<0.05). Fig B. Method: Six male flies were observed in drosophila polystyrene 25 x 95mm transparent vial in between cotton plugs. To the top plug, 500uL of 100% ethanol was added. Time till 50% of the flies were sedated was recorded on each day following the schedule. Fig. C (n=4-6). Using RT-PCR, we also quantified G protein mRNA expression levels one hour post initial 30 minutes of ethanol expression on day 1 and day 3 relative to expression in naïve flies.(n=2) [A] Increase in sedation time indicative of tolerance in different mutant lines and wild type flies. Six male flies were used in each experiment and (n= 4-6. ***P<0.001 unpaired t tests). [B] RT-PCR results showing significant reduction in Gq mRNA in flies chronically exposed to alcohol. (n=2. *P<0.05) [C] Alcohol exposure schedule. (1) Kaun K.R., R. Azanchi, Z. Maung, J. Hirsh, U. Heberlein. (2011). A Drosophila model for alcohol reward. Nature Neuroscience. 14 (5), 612–619.

A Spiking Neural Network Model of the Medial Superior Olive using Spike Timing Dependent Plasticity for Sound Localisation

Sound localization can be defined as the ability to identify the position of an input sound source and is considered a powerful aspect of mammalian perception. For low frequency sounds, i.e., in the range 270 Hz-1.5 KHz, the mammalian auditory pathway achieves this by extracting the Interaural Time Difference between sound signals being received by the left and right ear. This processing is performed in a region of the brain known as the Medial Superior Olive (MSO). This paper presents a Spiking Neural Network (SNN) based model of the MSO. The network model is trained using the Spike Timing Dependent Plasticity learning rule using experimentally observed Head Related Transfer Function data in an adult domestic cat. The results presented demonstrate how the proposed SNN model is able to perform sound localization with an accuracy of 91.82% when an error tolerance of +/-10 degrees is used. For angular resolutions down to 2.5 degrees , it will be demonstrated how software based simulations of the model incur significant computation times. The paper thus also addresses preliminary implementation on a Field Programmable Gate Array based hardware platform to accelerate system performance.