Vladimir Cherkassky

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The brain activation of a group of high-functioning autistic participants was measured using functional MRI during sentence comprehension and the results compared with those of a Verbal IQ-matched control group. The groups differed in the distribution of activation in two of the key language areas. The autism group produced reliably more activation than the(More)
We investigate practical selection of hyper-parameters for support vector machines (SVM) regression (that is, epsilon-insensitive zone and regularization parameter C). The proposed methodology advocates analytic parameter selection directly from the training data, rather than re-sampling approaches commonly used in SVM applications. In particular, we(More)
This paper treats support vector machine (SVM) classification applied to block design fMRI, extending our previous work with linear discriminant analysis [LaConte, S., Anderson, J., Muley, S., Ashe, J., Frutiger, S., Rehm, K., Hansen, L.K., Yacoub, E., Hu, X., Rottenberg, D., Strother S., 2003a. The evaluation of preprocessing choices in single-subject BOLD(More)
The brain activation of a group of high-functioning autistic participants was measured using functional magnetic resonance imaging during the performance of a Tower of London task, in comparison with a control group matched with respect to intelligent quotient, age, and gender. The 2 groups generally activated the same cortical areas to similar degrees.(More)
Brain activity in people with high-functioning autism has been shown to be atypical in a number of ways, including reduced synchronization across areas of activation measured by functional magnetic resonance imaging. This activation atypicality has been observed mostly during the performance of cognitive tasks. This study compares the resting-state network(More)
An fMRI study was used to measure the brain activation of a group of adults with high-functioning autism compared to a Full Scale and Verbal IQ and age-matched control group during an n-back working memory task with letters. The behavioral results showed comparable performance, but the fMRI results suggested that the normal controls might use verbal codes(More)
Comprehending high-imagery sentences like The number eight when rotated 90 degrees looks like a pair of eyeglasses involves the participation and integration of several cortical regions. The linguistic content must be processed to determine what is to be mentally imaged, and then the mental image must be evaluated and related to the sentence. A theory of(More)
Brain activation and functional connectivity were investigated in high functioning autism using functional magnetic resonance imaging in an n-back working memory task involving photographic face stimuli. The autism group showed reliably lower activation compared with controls in the inferior left prefrontal area (involved in verbal processing and working(More)
This study used fMRI to investigate the functioning of the Theory of Mind (ToM) cortical network in autism during the viewing of animations that in some conditions entailed the attribution of a mental state to animated geometric figures. At the cortical level, mentalizing (attribution of metal states) is underpinned by the coordination and integration of(More)
It is well known that for a given sample size there exists a model of optimal complexity corresponding to the smallest prediction (generalization) error. Hence, any method for learning from finite samples needs to have some provisions for complexity control. Existing implementations of complexity control include penalization (or regularization), weight(More)