fMRI machine learning methods and application of multi-voxel pattern analysis View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2011-2013

FUNDING AMOUNT

200000 CNY

ABSTRACT

Tensor and other multiplexed data description method of modeling fMRI temporal data, research and more whole brain fMRI voxels model representation; use of manifold learning, Zhang quantum characteristic spatial learning machine learning methods study high-dimensional space-time data extraction and dimension reduction algorithm research applies fMRI new algorithm for multi-voxel pattern classification to small sample; combining fMRI imaging characteristics, research unsupervised learning algorithm and noise data manifold learning methods; development and improvement based on machine learning fMRI multibody pattern classification prime theoretical framework. The research methodology used in visual object recognition experiments fMRI cognitive visual cortex activity pattern analysis to calculate the primary / secondary visual cortex (V1 / V2 region) and higher visual cortex (area such as IT multi-voxel pattern analysis method ) neural signals in response mode, exploring the visual cortex in the brain regions encoding target identification and target shape invariance of information processing. Expected project outcomes will propose a new efficient algorithm for complex or unknown fMRI pattern detection field, and made new progress in the study of neural coding of visual targets. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=61003202

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