Sciweavers

Share
TNN
2010
205views Management» more  TNN 2010»
8 years 6 months ago
Behavior-constrained support vector machines for fMRI data analysis
Statistical learning methods are emerging as a valuable tool for decoding information from neural imaging data. The noisy signal and the limited number of training patterns that ar...
Danmei Chen, Sheng Li, Zoe Kourtzi, Si Wu
JOCN
2011
95views more  JOCN 2011»
8 years 7 months ago
Differential Hemodynamic Response in Affective Circuitry with Aging: An fMRI Study of Novelty, Valence, and Arousal
■ Emerging evidence indicates that stimulus novelty is affectively potent and reliably engages the amygdala and other portions of the affective workspace in the brain. Using fun...
Yoshiya Moriguchi, Alyson Negreira, Mariann Weieri...
ICONFERENCE
2011
8 years 7 months ago
Icons: pictures or logograms?
The author proposed three studies (i.e. a large-N survey, a behavioral experiment, and a functional magnetic resonance imaging research) to investigate whether people read icons a...
Sheng-Cheng Huang
CORR
2011
Springer
151views Education» more  CORR 2011»
8 years 7 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
ICASSP
2009
IEEE
8 years 9 months ago
Modelling the neurovascular habituation effect on fMRI time series
In this paper, a novel non-stationary model of functional Magnetic Resonance Imaging (fMRI) time series is proposed. It allows us to account for some putative habituation effect a...
Philippe Ciuciu, Stéphane Sockeel, Thomas V...
ACL
2009
8 years 9 months ago
Quantitative modeling of the neural representation of adjective-noun phrases to account for fMRI activation
Recent advances in functional Magnetic Resonance Imaging (fMRI) offer a significant new approach to studying semantic representations in humans by making it possible to directly o...
Kai-min K. Chang, Vladimir Cherkassky, Tom M. Mitc...
IJON
2008
114views more  IJON 2008»
8 years 12 months ago
A robust model for spatiotemporal dependencies
Real-world data sets such as recordings from functional magnetic resonance imaging often possess both spatial and temporal structure. Here, we propose an algorithm including such ...
Fabian J. Theis, Peter Gruber, Ingo R. Keck, Elmar...
HAIS
2008
Springer
9 years 1 months ago
Extracting Multi-knowledge from fMRI Data through Swarm-Based Rough Set Reduction
Abstract. Functional Magnetic Resonance Imaging (fMRI) data is collected ceaselessly during brain research, which implicates some important information. It need to be extracted and...
Hongbo Liu, Ajith Abraham, Hong Ye
NIPS
2007
9 years 1 months ago
Continuous Time Particle Filtering for fMRI
We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...
Lawrence Murray, Amos J. Storkey
NIPS
2008
9 years 1 months ago
Nonparametric sparse hierarchical models describe V1 fMRI responses to natural images
We propose a novel hierarchical, nonlinear model that predicts brain activity in area V1 evoked by natural images. In the study reported here brain activity was measured by means ...
Pradeep Ravikumar, Vincent Q. Vu, Bin Yu, Thomas N...
books