Thesis
State-switching models of human brain activity using recurrent neural networks
- Abstract:
-
It has been shown that spatiotemporal dynamics of neuronal activity can be well described using state-related behaviour, comprising a discrete set of reoccurring quasi-stable states associated with distinct patterns of spatial and functional connectivity. Most methods of analysis will either assume stationarity of these states, as in ICA; or constrain the dynamics to be Markovian, as in hidden Markov models (HMMs). These tools lack the capability to explicitly model the higher order tempor...
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Funding
+ Engineering and Physical Sciences Research Council
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Name:
Engineering and Physical Sciences Research Council
Funder identifier:
http://dx.doi.org/10.13039/501100000266
Funding agency for:
Skates, A
Grant:
EP/L016044/1
Bibliographic Details
- Type of award:
- DPhil
- Level of award:
- Doctoral
- Awarding institution:
- University of Oxford
Item Description
- Language:
- English
- Keywords:
- Subjects:
- Deposit date:
- 2022-02-15
Terms of use
- Copyright holder:
- Alexander Skates
- Copyright date:
- 2019
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