■ Previous studies suggested that the observation of other individualsʼ somatosensory experiences also activates brain circuits processing oneʼs own somatosensory experiences....
Sjoerd J. H. Ebisch, Francesca Ferri, Anatolia Sal...
Functional magnetic resonance imaging (fMRI) is a popular tool for studying brain activity due to its non-invasiveness. Conventionally an expected response needs to be available f...
Sarah Lee, Fernando Zelaya, Yohan Samarasinghe, St...
Real-time functional magnetic resonance imaging (rtfMRI) enables classification of brain activity during data collection thus making inference results accessible to both the subj...
Hao Xu, Yongxin Taylor Xi, Ray Lee, Peter J. Ramad...
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Classification of brain images obtained through functional magnetic resonance imaging (fMRI) poses a serious challenge to pattern recognition and machine learning due to the extrem...
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...
This paper presents a development and testing of a haptic interface compatible with a functional magnetic resonance imaging (fMRI) environment for neuroscience human motor control ...
Due to the complex noise structure of functional magnetic resonance imaging (fMRI) data, methods that rely on information within a single subject often results in unsatisfactory fu...
Since the functional magnetic resonance imaging (fMRI) signal is likely to re ect a spatial average of the activity of neurons with partly dissimilar response properties, its inte...
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...