bicentennial
Senior Member (Voting Rights)
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What Do We Know about Spatial Navigation, and What Else Could Model-Based fMRI Tell Us?
Spatial navigation, or the ability to remember and navigate environments, is an important skill for humans and animals.
It has inspired a great deal of research, including neuroimaging studies of humans and single-unit recordings of animals.
Recent advances in computational modeling have enabled spatial navigation in humans and animals to be investigated in a more precise and detailed manner.
More specifically, computational models allow us to estimate theoretical parameters associated with spatial navigation, and model-based fMRI can be used to investigate the neural correlates of these parameters.
This review addresses the literature on spatial navigation beginning with reviewing lesion and animal studies of spatial cognition.
Imaging studies of spatial memory and navigation in humans, including structural imaging, and more complex functional imaging studies involving virtual reality are then discussed.
Particular emphasis is placed on computational studies of behavior involving reinforcement learning models and model-based fMRI.
Finally, the advantages of model-based fMRI for investigating the neural basis of spatial navigation in humans are discussed
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Recommended citation:
Tyson, A. L. (2013).
"What do we know about spatial navigation, and what else could model-based fMRI tell us?"
Einstein J. Biol. Med. v29 p32.
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Adam Tyson, Neuroscientist and software developer
MSc Faculty of Mathematical and Physical Sciences,
University College London, Gower Street, London, United Kingdom
Head Research Engineer
and Head of the Neuroinformatics Unit
at the Sainsbury Wellcome Centre
and Gatsby Computational Neuroscience Unit
.
EDIT: removed quote boxes
What Do We Know about Spatial Navigation, and What Else Could Model-Based fMRI Tell Us?
Spatial navigation, or the ability to remember and navigate environments, is an important skill for humans and animals.
It has inspired a great deal of research, including neuroimaging studies of humans and single-unit recordings of animals.
Recent advances in computational modeling have enabled spatial navigation in humans and animals to be investigated in a more precise and detailed manner.
More specifically, computational models allow us to estimate theoretical parameters associated with spatial navigation, and model-based fMRI can be used to investigate the neural correlates of these parameters.
This review addresses the literature on spatial navigation beginning with reviewing lesion and animal studies of spatial cognition.
Imaging studies of spatial memory and navigation in humans, including structural imaging, and more complex functional imaging studies involving virtual reality are then discussed.
Particular emphasis is placed on computational studies of behavior involving reinforcement learning models and model-based fMRI.
Finally, the advantages of model-based fMRI for investigating the neural basis of spatial navigation in humans are discussed
----------------------
Recommended citation:
Tyson, A. L. (2013).
"What do we know about spatial navigation, and what else could model-based fMRI tell us?"
Einstein J. Biol. Med. v29 p32.
----------------------
Adam Tyson, Neuroscientist and software developer
MSc Faculty of Mathematical and Physical Sciences,
University College London, Gower Street, London, United Kingdom
Head Research Engineer
and Head of the Neuroinformatics Unit
at the Sainsbury Wellcome Centre
and Gatsby Computational Neuroscience Unit
.
EDIT: removed quote boxes
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