Search for dissertations about: "dendritic integration"
Showing result 1 - 5 of 9 swedish dissertations containing the words dendritic integration.
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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. A-type Potassium Channels in Dendritic Integration : Role in Epileptogenesis
Abstract : During cognitive tasks, synchronicity of neural activity varies and is correlated with performance. However, there may be an upper limit to normal synchronised activity – specifically, epileptogenic activity is characterized byexcess spiking at high synchronicity. 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. Non-linear synaptic integration on dendrites of striatal medium-spiny neuron : a computational study
Abstract : Striatum is the main input nucleus of basal ganglia. Medium-spiny neurons (MSNs), the principal neurons of the striatum, receive convergent excitatory inputs from cortex and thalamus, thus “gate” the information flow to the basal ganglia. READ MORE
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5. Using Inhomogeneous Neuronal–Synaptic Dynamics for Spatiotemporal Pattern Recognition in Neuromorphic Processors
Abstract : Mixed-signal neuromorphic processors emulate the electrochemical dynamics of neurons and synapses using conventional analog CMOS-transistor technology and have potential for ultra-low-power machine learning and inference. However, the energy-efficiency of such systems is dependent on sparse, time-based information encoding and processing, and they are, furthermore, subject to imprecision from “device mismatch” in the analog circuitry. READ MORE