Understanding the effective dynamics of the human brain.
While the cellular structure and behaviour of single neurons is well understood, how groups of neurons work together to perform a certain brain function is not. With its sensitivity to external stimuli and dense interconnectedness, the mapping of these functional groups of neurons within th...
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sg-ntu-dr.10356-488432023-02-28T23:13:11Z Understanding the effective dynamics of the human brain. Teo, Wei Ren. Cheong Siew Ann School of Physical and Mathematical Sciences DRNTU::Science While the cellular structure and behaviour of single neurons is well understood, how groups of neurons work together to perform a certain brain function is not. With its sensitivity to external stimuli and dense interconnectedness, the mapping of these functional groups of neurons within the human brain represents a signi cant research challenge. Thet invasive nature of direct neuronal observation presents an ethical barrier to research. Even with technological advancements in brain imaging, data is inherently noisy and subject to numerous statistical procedures before meaningful inferences can be made. In this study, we utilise the complete-link algorithm of hierarchical clustering which is a mathematical method designed to nd similar groups of data. The algorithm will be used to nd clusters of neurons which may be seen as the functional areas of the brain. Following clustering, the dynamics of these functional areas will be studied by adopting a cluster synchronisation based approach to provide insight into the workings of the brain. Two sets of data will be analysed. The rst will be the simulated neuronal activity of a semantic dyslexic to test the feasibility of the approach. The second will be a time series of fMRI scans of a single subject performing a visual task under conditions of attention or no attention. Bachelor of Science in Physics 2012-05-10T03:16:01Z 2012-05-10T03:16:01Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48843 en 62 p. application/pdf |
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DRNTU::Science Teo, Wei Ren. Understanding the effective dynamics of the human brain. |
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While the cellular structure and behaviour of single neurons is well understood, how groups
of neurons work together to perform a certain brain function is not. With its sensitivity to
external stimuli and dense interconnectedness, the mapping of these functional groups of neurons
within the human brain represents a signi cant research challenge. Thet invasive nature of
direct neuronal observation presents an ethical barrier to research. Even with technological
advancements in brain imaging, data is inherently noisy and subject to numerous statistical
procedures before meaningful inferences can be made. In this study, we utilise the complete-link
algorithm of hierarchical clustering which is a mathematical method designed to nd similar
groups of data. The algorithm will be used to nd clusters of neurons which may be seen as
the functional areas of the brain. Following clustering, the dynamics of these functional areas
will be studied by adopting a cluster synchronisation based approach to provide insight into
the workings of the brain. Two sets of data will be analysed. The rst will be the simulated
neuronal activity of a semantic dyslexic to test the feasibility of the approach. The second will
be a time series of fMRI scans of a single subject performing a visual task under conditions of
attention or no attention. |
author2 |
Cheong Siew Ann |
author_facet |
Cheong Siew Ann Teo, Wei Ren. |
format |
Final Year Project |
author |
Teo, Wei Ren. |
author_sort |
Teo, Wei Ren. |
title |
Understanding the effective dynamics of the human brain. |
title_short |
Understanding the effective dynamics of the human brain. |
title_full |
Understanding the effective dynamics of the human brain. |
title_fullStr |
Understanding the effective dynamics of the human brain. |
title_full_unstemmed |
Understanding the effective dynamics of the human brain. |
title_sort |
understanding the effective dynamics of the human brain. |
publishDate |
2012 |
url |
http://hdl.handle.net/10356/48843 |
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1759854406353813504 |