Learn More
While magnetoencephalography (MEG) is widely used to identify spatial locations of brain activations associated with various tasks, classification of single trials in stimulus-locked experiments remains an open subject. Very significant single-trial classification results have been published using electroencephalogram (EEG) data, but in the MEG case, the(More)
The idea of a hierarchical structure of language constituents of phonemes, syllables, words, and sentences is robust and widely accepted. Empirical similarity differences at every level of this hierarchy have been analyzed in the form of confusion matrices for many years. By normalizing such data so that differences are represented by conditional(More)
In brain-imaging research, we are often interested in making quantitative claims about effects across subjects. Given that most imaging data consist of tens to thousands of spatially correlated time series, inter-subject comparisons are typically accomplished with simple combinations of inter-subject data, for example methods relying on group means.(More)
We have previously shown that classification of single-trial electroencephalographic (EEG) recordings is improved by the use of either a niultichannel classifier or the best independent component over a single channel classifier. In this paper, we introduce a classifier that makes explicit use of multiple independent components. Two models are compared. The(More)
Continuous amperometry was used to monitor noradrenaline (NA) release from sympathetic nerves supplying rat mesenteric arteries in vitro. During electrical stimulation the amplitude of oxidation currents evoked by successive stimuli varied over a small range, with occasional events of larger amplitude. In the absence of stimulation, spontaneous oxidation(More)
  • 1