Michael J. Martinez

Bias between MNI and talairach coordinates analyzed using the ICBM-152 brain template

MNI coordinates determined using SPM2 and FSL/FLIRT with the ICBM‐152 template were compared to Talairach coordinates determined using a landmark‐based Talairach registration method (TAL). Analysis revealed a clear‐cut bias in reference frames (origin, orientation) and scaling (brain size). Accordingly, ICBM‐152 fitted brains were consistently larger, oriented more nose down, and translated slightly down relative to TAL fitted brains. Whole brain analysis of MNI/Talairach coordinate disparity revealed an ellipsoidal pattern with disparity ranging from zero at a point deep within the left hemisphere to greater than 1‐cm for some anterior brain areas. MNI/Talairach coordinate disparity was generally less for brains fitted using FSL. The mni2tal transform generally reduced MNI/Talairach coordinate disparity for inferior brain areas but increased disparity for anterior, posterior, and superior areas. Coordinate disparity patterns differed for brain templates (MNI‐305, ICBM‐152) using the same fitting method (FSL/FLIRT) and for different fitting methods (SPM2, FSL/FLIRT) using the same template (ICBM‐152). An MNI‐to‐Talairach (MTT) transform to correct for bias between MNI and Talairach coordinates was formulated using a best‐fit analysis in one hundred high‐resolution 3‐D MR brain images. MTT transforms optimized for SPM2 and FSL were shown to reduced group mean MNI/Talairach coordinate disparity from a 5‐13 mm to 1‐2 mm for both deep and superficial brain sites. MTT transforms provide a validated means to convert MNI coordinates to Talairach compatible coordinates for studies using either SPM2 or FSL/FLIRT with the ICBM‐152 template. Hum Brain Mapp 2007.

Passive music listening spontaneously engages limbic and paralimbic systems

In this PET study, non-musicians passively listened to unfamiliar instrumental music revealed afterward to elicit strongly pleasant feelings. Activations were observed in the subcallosal cingulate gyrus, prefrontal anterior cingulate, retrosplenial cortex, hippocampus, anterior insula, and nucleus accumbens. This is the first observation of spontaneous responses in such limbic and paralimbic areas during passive listening to unfamiliar although liked music. Activations were also seen in primary auditory, secondary auditory, and temporal polar areas known to respond to music. Our findings complement neuroimaging studies of aesthetic responses to music that have used stimuli selected by subjects or designed by experimenters. The observed pattern of activity is discussed in terms of a model synthesizing emotional and cognitive responses to music.

Music and language side by side in the brain: a PET study of the generation of melodies and sentences

Parallel generational tasks for music and language were compared using positron emission tomography. Amateur musicians vocally improvised melodic or linguistic phrases in response to unfamiliar, auditorily presented melodies or phrases. Core areas for generating melodic phrases appeared to be in left Brodmann area (BA) 45, right BA 44, bilateral temporal planum polare, lateral BA 6, and pre‐SMA. Core areas for generating sentences seemed to be in bilateral posterior superior and middle temporal cortex (BA 22, 21), left BA 39, bilateral superior frontal (BA 8, 9), left inferior frontal (BA 44, 45), anterior cingulate, and pre‐SMA. Direct comparisons of the two tasks revealed activations in nearly identical functional brain areas, including the primary motor cortex, supplementary motor area, Brocas area, anterior insula, primary and secondary auditory cortices, temporal pole, basal ganglia, ventral thalamus, and posterior cerebellum. Most of the differences between melodic and sentential generation were seen in lateralization tendencies, with the language task favouring the left hemisphere. However, many of the activations for each modality were bilateral, and so there was significant overlap. While clarification of this overlapping activity awaits higher‐resolution measurements and interventional assessments, plausible accounts for it include component sharing, interleaved representations, and adaptive coding. With these and related findings, we outline a comparative model of shared, parallel, and distinctive features of the neural systems supporting music and language. The model assumes that music and language show parallel combinatoric generativity for complex sound structures (phonology) but distinctly different informational content (semantics).

The Role of the Insular Cortex in Pitch Pattern Perception: The Effect of Linguistic Contexts

Auditory pitch patterns are significant ecological features to which nervous systems have exquisitely adapted. Pitch patterns are found embedded in many contexts, enabling different information-processing goals. Do the psychological functions of pitch patterns determine the neural mechanisms supporting their perception, or do all pitch patterns, regardless of function, engage the same mechanisms? This issue is pursued in the present study by using 150-water positron emission tomography to study brain activations when two subject groups discriminate pitch patterns in their respective native languages, one of which is a tonal language and the other of which is not. In a tonal language, pitch patterns signal lexical meaning. Native Mandarin-speaking and English-speaking listeners discriminated pitch patterns embedded in Mandarin and English words and also passively listened to the same stimuli. When Mandarin listeners discriminated pitch embedded in Mandarin lexical tones, the left anterior insular cortex was the most active. When they discriminated pitch patterns embedded in English words, the homologous area in the right hemisphere activated as it did in English-speaking listeners discriminating pitch patterns embedded in either Mandarin or English words. These results support the view that neural responses to physical acoustic stimuli depend on the function of those stimuli and implicate anterior insular cortex in auditory processing, with the left insular cortex especially responsive to linguistic stimuli.

Activation of premotor vocal areas during musical discrimination

Two same/different discrimination tasks were performed by amateur-musician subjects in this functional magnetic resonance imaging study: Melody Discrimination and Harmony Discrimination. Both tasks led to activations not only in classic working memory areas--such as the cingulate gyrus and dorsolateral prefrontal cortex--but in a series of premotor areas involved in vocal-motor planning and production, namely the somatotopic mouth region of the primary and lateral premotor cortices, Brocas area, the supplementary motor area, and the anterior insula. A perceptual control task involving passive listening alone to monophonic melodies led to activations exclusively in temporal-lobe auditory areas. These results show that, compared to passive listening tasks, discrimination tasks elicit activation in vocal-motor planning areas.

Automated regional behavioral analysis for human brain images

Behavioral categories of functional imaging experiments along with standardized brain coordinates of associated activations were used to develop a method to automate regional behavioral analysis of human brain images. Behavioral and coordinate data were taken from the BrainMap database (http://www.brainmap.org/), which documents over 20 years of published functional brain imaging studies. A brain region of interest (ROI) for behavioral analysis can be defined in functional images, anatomical images or brain atlases, if images are spatially normalized to MNI or Talairach standards. Results of behavioral analysis are presented for each of BrainMaps 51 behavioral sub-domains spanning five behavioral domains (Action, Cognition, Emotion, Interoception, and Perception). For each behavioral sub-domain the fraction of coordinates falling within the ROI was computed and compared with the fraction expected if coordinates for the behavior were not clustered, i.e., uniformly distributed. When the difference between these fractions is large behavioral association is indicated. A z-score ≥ 3.0 was used to designate statistically significant behavioral association. The left-right symmetry of ~100K activation foci was evaluated by hemisphere, lobe, and by behavioral sub-domain. Results highlighted the classic left-side dominance for language while asymmetry for most sub-domains (~75%) was not statistically significant. Use scenarios were presented for anatomical ROIs from the Harvard-Oxford cortical (HOC) brain atlas, functional ROIs from statistical parametric maps in a TMS-PET study, a task-based fMRI study, and ROIs from the ten “major representative” functional networks in a previously published resting state fMRI study. Statistically significant behavioral findings for these use scenarios were consistent with published behaviors for associated anatomical and functional regions.

Automated Analysis of Fundamental Features of Brain Structures

Automated image analysis of the brain should include measures of fundamental structural features such as size and shape. We used principal axes (P-A) measurements to measure overall size and shape of brain structures segmented from MR brain images. The rationale was that quantitative volumetric studies of brain structures would benefit from shape standardization as had been shown for whole brain studies. P-A analysis software was extended to include controls for variability in position and orientation to support individual structure spatial normalization (ISSN). The rationale was that ISSN would provide a bias-free means to remove elementary sources of a structure’s spatial variability in preparation for more detailed analyses. We studied nine brain structures (whole brain, cerebral hemispheres, cerebellum, brainstem, caudate, putamen, hippocampus, inferior frontal gyrus, and precuneus) from the 40-brain LPBA40 atlas. This paper provides the first report of anatomical positions and principal axes orientations within a standard reference frame, in addition to “shape/size related” principal axes measures, for the nine brain structures from the LPBA40 atlas. Analysis showed that overall size (mean volume) for internal brain structures was preserved using shape standardization while variance was reduced by more than 50%. Shape standardization provides increased statistical power for between-group volumetric studies of brain structures compared to volumetric studies that control only for whole brain size. To test ISSN’s ability to control for spatial variability of brain structures we evaluated the overlap of 40 regions of interest (ROIs) in a standard reference frame for the nine different brain structures before and after processing. Standardizations of orientation or shape were ineffective when not combined with position standardization. The greatest reduction in spatial variability was seen for combined standardizations of position, orientation and shape. These results show that ISSNs automated processing can be a valuable asset for measuring and controlling variability of fundamental features of brain structures.