Inferring structure in neural time series data: dynamics and connectivity
The ability to derive insights from complex high-dimensional data, such as neural data, is important to improve our understanding of the underlying system. In this thesis, we approach this by studying two aspects of neural data: dynamics and connectivity. First, we analyze the dynamics of the sponta...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/170411 |