Robert Savoy

YNIMG Journal 2005 Journal Article

Processing of sub-syllabic speech units in the posterior temporal lobe: An fMRI study

• Lars M. Rimol
• Karsten Specht
• Susanne Weis
• Robert Savoy
• Kenneth Hugdahl

The objective of this study was to investigate phonological processing in the brain by using sub-syllabic speech units with rapidly changing frequency spectra. We used isolated stop consonants extracted from natural speech consonant–vowel (CV) syllables, which were digitized and presented through headphones in a functional magnetic resonance imaging (fMRI) paradigm. The stop consonants were contrasted with CV syllables. In order to control for general auditory activation, we used duration- and intensity-matched noise as a third stimulus category. The subjects were seventeen right-handed, healthy male volunteers. BOLD activation responses were acquired on a 1. 5-T MR scanner. The auditory stimuli were presented through MR compatible headphones, using an fMRI paradigm with clustered volume acquisition and 12 s repetition time. The consonant vs. noise comparison resulted in unilateral left lateralized activation in the posterior part of the middle temporal gyrus and superior temporal sulcus (MTG/STS). The CV syllable vs. noise comparison resulted in bilateral activation in the same regions, with a leftward asymmetry. The reversed comparisons, i. e. , noise vs. speech stimuli, resulted in right hemisphere activation in the supramarginal and superior temporal gyrus, as well as right prefrontal activation. Since the consonant stimuli are unlikely to have activated a semantic–lexical processing system, it seems reasonable to assume that the MTG/STS activation represents phonetic/phonological processing. This may involve the processing of both spectral and temporal features considered important for phonetic encoding.

YNIMG Journal 2001 Journal Article

Event-related FMRI of tactile stimulus detection

• Christopher Moore
• Emilie Crosier
• Gary Jasdzewski
• Doug Greve
• Bruce Fischl
• Robert Savoy
• Andrew Siegel
• Dylan Stiles

YNIMG Journal 1999 Journal Article

Generalizable Patterns in Neuroimaging: How Many Principal Components?

• Lars Kai Hansen
• Jan Larsen
• Finn Årup Nielsen
• Stephen C. Strother
• Egill Rostrup
• Robert Savoy
• Nicholas Lange
• John Sidtis

Generalization can be defined quantitatively and can be used to assess the performance of principal component analysis (PCA). The generalizability of PCA depends on the number of principal components retained in the analysis. We provide analytic and test set estimates of generalization. We show how the generalization error can be used to select the number of principal components in two analyses of functional magnetic resonance imaging activation sets.

YNIMG Journal 1999 Journal Article

Plurality and Resemblance in fMRI Data Analysis

• Nicholas Lange
• Stephen C. Strother
• Jon R. Anderson
• Finn Å. Nielsen
• Andrew P. Holmes
• Thomas Kolenda
• Robert Savoy
• Lars Kai Hansen

We apply nine analytic methods employed currently in imaging neuroscience to simulated and actual BOLD fMRI signals and compare their performances under each signal type. Starting with baseline time series generated by a resting subject during a null hypothesis study, we compare method performance with embedded focal activity in these series of three different types whose magnitudes and time courses are simple, convolved with spatially varying hemodynamic responses, and highly spatially interactive. We then apply these same nine methods to BOLD fMRI time series from contralateral primary motor cortex and ipsilateral cerebellum collected during a sequential finger opposition study. Paired comparisons of results across methods include a voxel-specific concordance correlation coefficient for reproducibility and a resemblance measure that accommodates spatial autocorrelation of differences in activity surfaces. Receiver-operating characteristic curves show considerable model differences in ranges less than 10% significance level (false positives) and greater than 80% power (true positives). Concordance and resemblance measures reveal significant differences between activity surfaces in both data sets. These measures can assist researchers by identifying groups of models producing similar and dissimilar results, and thereby help to validate, consolidate, and simplify reports of statistical findings. A pluralistic strategy for fMRI data analysis can uncover invariant and highly interactive relationships between local activity foci and serve as a basis for further discovery of organizational principles of the brain. Results also suggest that a pluralistic empirical strategy coupled formally with substantive prior knowledge can help to uncover new brain–behavior relationships that may remain hidden if only a single method is employed.