Essays about: "neurovetenskap"
Showing result 1 - 5 of 36 essays containing the word neurovetenskap.
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1. A comparison of neuron touch detection algorithms utilising voxelization and the data structures octree, k-d tree and R-tree
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Simulations of biologically detailed neuronal networks have become an essential tool in the study of the brain. An important step in the creation of these types of simulations is the detection of the connections between the nerve cells. This paper analyses the efficiency of four algorithms used for such purposes. READ MORE
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2. Development of a Closed-loop for Measuring and Stimulating Peripheral Nervous System
University essay from KTH/Skolan för kemi, bioteknologi och hälsa (CBH)Abstract : Bioelectronic medicine is an emerging discipline being a intersection of neu- roscience, immunology and electrical engineering. Chronic inflammation is linked to disorders such as diabetes, rheumatoid arthritis, asthma, atheroscle- rosis, obesity and inflammatory bowel disease. READ MORE
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3. Optimisation of parallel k-d trees using heuristics for neuron touch detection task
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Neuroscience has benefited from neuronal network simulation and an important task in the simulation is finding points in space where two neurites approach each other so a synapse could be formed. The task of finding the touching points could be seen as similar to the ray collision in ray tracing in computer graphics. READ MORE
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4. Analysis and modelling of grooming behaviour of mice
University essay from KTH/FysikAbstract : Mapping dynamical motion to neural brain activity is one of many challenges in the field of neuroscience. Further knowledge in this area could provide useful insights in fields such as medical treatment of brain disorders. READ MORE
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5. Spiking Reinforcement Learning for Robust Robot Control Under Varying Operating Conditions
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over the last few years, deep reinforcement learning (RL) has gained increasing popularity for its successful application to a variety of complex control and decision-making tasks. As the demand for deep RL algorithms deployed in challenging real-world environments grows, their robustness towards uncertainty, disturbances and perturbations of the environment becomes more and more important. READ MORE
