Search for dissertations about: "receptor computer modeling"
Showing result 1 - 5 of 13 swedish dissertations containing the words receptor computer modeling.
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1. Beyond AMPA and NMDA: Slow synaptic mGlu/TRPC currents : Implications for dendritic integration
Abstract : In order to understand how the brain functions, under normal as well as pathological conditions, it is important to study the mechanisms underlying information integration. Depending on the nature of an input arriving at a synapse, different strategies may be used by the neuron to integrate and respond to the input. READ MORE
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2. Free energy calculations of G protein-coupled receptor modulation : New methods and applications
Abstract : G protein-coupled receptors (GPCRs) are membrane proteins that transduce the signals of extracellular ligands, such as hormones, neurotransmitters and metabolites, through an intracellular response via G proteins. They are abundant in human physiology and approximately 34% of the marketed drugs target a GPCR. READ MORE
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3. Dendritic and axonal ion channels supporting neuronal integration : From pyramidal neurons to peripheral nociceptors
Abstract : The nervous system, including the brain, is a complex network with billions of complex neurons. Ion channels mediate the electrical signals that neurons use to integrate input and produce appropriate output, and could thus be thought of as key instruments in the neuronal orchestra. READ MORE
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4. Modeling receptor induced signaling in MSNs : Interaction between molecules involved in striatal synaptic plasticity
Abstract : Basal Ganglia are evolutionarily conserved brain nuclei involved in several physiologically important animal behaviors like motor control and reward learning. Striatum, which is the input nuclei of basal ganglia, integrates inputs from several neurons, like cortical and thalamic glutamatergic input and local GABAergic inputs. READ MORE
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5. Modeling Biochemical Network Involved in Striatal Dopamine Signaling
Abstract : In this thesis, I studied the molecular integration of reward-learning related neuromodulatory inputs by striatal medium-sized projection neurons (MSNs) using mass-action kinetic modeling.It is known that, in reward learning, an unexpected reward results in transient elevation in dopamine (peak) whereas omission of an expected reward leads to transient dopamine decrease (dip). READ MORE
