Four Functionally Distinct Regions in the Left Supramarginal Gyrus Support Word Processing.

We used fMRI in 85 healthy participants to investigate whether different parts of the left supramarginal gyrus (SMG) are involved in processing phonological inputs and outputs. The experiment involved 2 tasks (speech production (SP) and one-back (OB) matching) on 8 different types of stimuli that systematically varied the demands on sensory processing (visual vs. auditory), sublexical phonological input (words and pseudowords vs. nonverbal stimuli), and semantic content (words and objects vs. pseudowords and meaningless baseline stimuli). In ventral SMG, we found an anterior subregion associated with articulatory sequencing (for SP > OB matching) and a posterior subregion associated with auditory short-term memory (for all auditory > visual stimuli and written words and pseudowords > objects). In dorsal SMG, a posterior subregion was most highly activated by words, indicating a role in the integration of sublexical and lexical cues. In anterior dorsal SMG, activation was higher for both pseudoword reading and object naming compared with word reading, which is more consistent with executive demands than phonological processing. The dissociation of these four "functionally-distinct" regions, all within left SMG, has implications for differentiating between different types of phonological processing, understanding the functional anatomy of language and predicting the effect of brain damage.

Predicting IQ change from brain structure: a cross-validation study.

Procedures that can predict cognitive abilities from brain imaging data are potentially relevant to educational assessments and studies of functional anatomy in the developing brain. Our aim in this work was to quantify the degree to which IQ change in the teenage years could be predicted from structural brain changes. Two well-known k-fold cross-validation analyses were applied to data acquired from 33 healthy teenagers - each tested at Time 1 and Time 2 with a 3.5 year interval. One approach, a Leave-One-Out procedure, predicted IQ change for each subject on the basis of structural change in a brain region that was identified from all other subjects (i.e., independent data). This approach predicted 53% of verbal IQ change and 14% of performance IQ change. The other approach used half the sample, to identify regions for predicting IQ change in the other half (i.e., a Split half approach); however--unlike the Leave-One-Out procedure--regions identified using half the sample were not significant. We discuss how these out-of-sample estimates compare to in-sample estimates; and draw some recommendations for k-fold cross-validation procedures when dealing with small datasets that are typical in the neuroimaging literature.