Wilkin Chau

Effect of bilingualism on cognitive control in the Simon task: evidence from MEG

The present study used magneto-encephalography (MEG) to determine the neural correlates of the bilingual advantage previously reported for behavioral measures in conflict tasks. Bilingual Cantonese-English, bilingual French-English, and monolingual English speakers, performed the Simon task in the MEG. Reaction times were faster for congruent than for incongruent trials, and the Cantonese group was faster than the other two groups, which did not differ from each other. Analyses of the MEG data using synthetic aperture magnetometry (SAM) and partial last squares (PLS) showed that the same pattern of activity, involving signal changes in left and medial prefrontal areas, characterized all three groups. Correlations between activated regions and reaction times, however, showed that the two bilingual groups demonstrated faster reaction times with greater activity in superior and middle temporal, cingulate, and superior and inferior frontal regions, largely in the left hemisphere. The monolinguals demonstrated faster reaction times with activation in middle frontal regions. The interpretation is that the management of two language systems led to systematic changes in frontal executive functions.

Spatiotemporal analysis of event-related fMRI data using partial least squares

Partial least squares (PLS) has proven to be a important multivariate analytic tool for positron emission tomographic and, more recently, event-related potential (ERP) data. The application to ERP incorporates the ability to analyze space and time together, a feature that has obvious appeal for event-related functional magnetic resonance imaging (fMRI) data. This paper presents the extension of spatiotemporal PLS (ST-PLS) to fMRI, explaining the theoretical foundation and application to an fMRI study of auditory and visual perceptual memory. Analysis of activation effects with ST-PLS was compared with conventional univariate random effects analysis, showing general consensus for both methods, but several unique observations by ST-PLS, including enhanced statistical power. The application of ST-PLS for assessment of task-dependent brain-behavior relationships is also presented. Singular features of ST-PLS include (1) no assumptions about the shape of the hemodynamic response functions (HRFs); (2) robust statistical assessment at the image level through permutation tests; (3) protection against outlier influences at the voxel level through bootstrap resampling; (4) flexible analytic configurations that allow assessment of activation difference, brain-behavior relations, and functional connectivity. These features enable ST-PLS to act as an important complement to other multivariate and univariate approaches used in neuroimaging research.

Neuroimaging evidence for cortical involvement in the preparation and in the act of swallowing

This study employed whole head magnetoencephalography and synthetic aperture magnetometry to investigate the cortical topography of the preparation and the execution of volitional and reflexive water swallowing and of a simple tongue movement. Concerning movement execution, activation of the mid-lateral primary sensorimotor cortex was strongly lateralized to the left during volitional water swallowing, less strongly lateralized to the left during reflexive water swallowing, and not lateralized at all during tongue movement. In contrast, the preparation for both volitional water swallowing and tongue movement showed a bilateral activation of the primary sensorimotor cortex. No activation was seen prior to reflexive water swallowing. Activation of the left insula and frontal operculum was observed only during both the preparation and the execution of volitional water swallowing. These new findings suggest a left hemispheric dominance for the cortical control of swallowing in humans.

An Empirical Comparison of SPM Preprocessing Parameters to the Analysis of fMRI Data

We present the results from two sets of Monte Carlo simulations aimed at evaluating the robustness of some preprocessing parameters of SPM99 for the analysis of functional magnetic resonance imaging (fMRI). Statistical robustness was estimated by implementing parametric and nonparametric simulation approaches based on the images obtained from an event-related fMRI experiment. Simulated datasets were tested for combinations of the following parameters: basis function, global scaling, low-pass filter, high-pass filter and autoregressive modeling of serial autocorrelation. Based on single-subject SPM analysis, we derived the following conclusions that may serve as a guide for initial analysis of fMRI data using SPM99: (1) The canonical hemodynamic response function is a more reliable basis function to model the fMRI time series than HRF with time derivative. (2) Global scaling should be avoided since it may significantly decrease the power depending on the experimental design. (3) The use of a high-pass filter may be beneficial for event-related designs with fixed interstimulus intervals. (4) When dealing with fMRI time series with short interstimulus intervals (<8 s), the use of first-order autoregressive model is recommended over a low-pass filter (HRF) because it reduces the risk of inferential bias while providing a relatively good power. For datasets with interstimulus intervals longer than 8 seconds, temporal smoothing is not recommended since it decreases power. While the generalizability of our results may be limited, the methods we employed can be easily implemented by other scientists to determine the best parameter combination to analyze their data.

Determination of activation areas in the human auditory cortex by means of synthetic aperture magnetometry

In this study we applied synthetic aperture magnetometry (SAM) to investigate active cortical areas associated with magnetically recorded transient and steady-state auditory evoked responses. For transient evoked responses, SAM images reveal an activated volume of cortical tissue within the lateral aspect of the superior temporal plane. The volume of cortical activation for steady-state responses was located more medially than that for transient evoked responses. Additionally, SAM also reveals a small overlap of activated areas between transient and steady-state evoked responses, which has not be demonstrated when using equivalent current dipole (ECD) source modeling. Source waveforms from SAM and ECD analyses show comparable temporal information. Results from this study suggest that SAM is a useful technique for imaging cortical structures involved in processing perceptual information.

Improving permutation test power for group analysis of spatially filtered MEG data.

Non-parametric statistical methods, such as permutation, are flexible tools to analyze data when the population distribution is not known. With minimal assumptions and better statistical power compared to the parametric tests, permutation tests have recently been applied to the spatially filtered magnetoencephalography (MEG) data for group analysis. To perform permutation tests on neuroimaging data, an empirical maximal null distribution has to be found, which is free from any activated voxels, to determine the threshold to classify the voxels as active at a given probability level. An iterative procedure is used to determine the distribution by computing the null distribution, which is recomputed when a possible activated voxel is found within the current distributions. Besides the high computational costs associated with this approach, there is no guarantee that all activated voxels are excluded when constructing the maximal null distribution, which may reduce the statistical power. In this study, we propose a novel way to construct the maximal null distribution from the data of the resting period. The approach is tested on the MEG data from a somatosensory experiment, and demonstrated that the approach could improve the power of the permutation test while reducing the computational cost at the same time.

Music training leads to the development of timbre-specific gamma band activity

Oscillatory gamma band activity (GBA, 30-100 Hz) has been shown to correlate with perceptual and cognitive phenomena including feature binding, template matching, and learning and memory formation. We hypothesized that if GBA reflects highly learned perceptual template matching, we should observe its development in musicians specific to the timbre of their instrument of practice. EEG was recorded in adult professional violinists and amateur pianists as well as in 4- and 5-year-old children studying piano in the Suzuki method before they commenced music lessons and 1 year later. The adult musicians showed robust enhancement of induced (non-time-locked) GBA, specifically to their instrument of practice, with the strongest effect in professional violinists. Consistent with this result, the children receiving piano lessons exhibited increased power of induced GBA for piano tones with 1 year of training, while children not taking lessons showed no effect. In comparison to induced GBA, evoked (time-locked) gamma band activity (30-90 Hz, approximately 80 ms latency) was present only in adult groups. Evoked GBA was more pronounced in musicians than non-musicians, with synchronization equally exhibited for violin and piano tones but enhanced for these tones compared to pure tones. Evoked gamma activity may index the physical properties of a sound and is modulated by acoustical training, while induced GBA may reflect higher perceptual learning and is shaped by specific auditory experiences.

The Talairach coordinate of a point in the MNI space: how to interpret it.

To perform group studies using functional imaging data, the individual brain images are usually transformed into a common coordinate space. The two most widely used spaces in the neuroscience community are the Talairach space and the Montreal Neurological Institute (MNI) space. The Talairach coordinate system has become the standard reference for reporting the brain locations in scientific publication, even when the data have been spatially transformed into different brain templates (e.g., MNI space). When expressed in terms of individual subjects, the mapping of a coordinate in MNI space to the Talairach space generates distinct coordinates for different subjects. In this paper, we describe two approaches to derive the Talairach coordinates from the MNI space, which is based on the ICBM152 template from the International Consortium of Brain Mapping. One approach is the Talairach Method of Piecewise Linear Scaling (TMPLS) as implemented in the AFNI software package; and the other is a template-matching approach using the linear transformation in SPM99. The uncertainty measurements of the mapping results are presented. This may allow researchers to better interpret results reporting in the Talairach coordinates obtained from the MNI space. This study also examines the discrepancy between the derived Talairach coordinates and those obtained from the mni2tal script, a tool commonly used by the neuroimaging community. Large discrepancies are found in the inferior regions, superior frontal and occipital regions.

An integrative MEG-fMRI study of the primary somatosensory cortex using cross-modal correspondence analysis.

We develop a novel approach of cross-modal correspondence analysis (CMCA) to address whether brain activities observed in magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) represent a common neuronal subpopulation, and if so, which frequency band obtained by MEG best fits the common brain areas. Fourteen adults were investigated by whole-head MEG using a single equivalent current dipole (ECD) and synthetic aperture magnetometry (SAM) approaches and by fMRI at 1.5 T using linear time-invariant modeling to generate statistical maps. The same somatosensory stimulus sequences consisting of tactile impulses to the right sided: digit 1, digit 4 and lower lip were used in both neuroimaging modalities. To evaluate the reproducibility of MEG and fMRI results, one subject was measured repeatedly. Despite different MEG dipole locations and locations of maximum activation in SAM and fMRI, CMCA revealed a common subpopulation of the primary somatosensory cortex, which displays a clear homuncular organization. MEG activity in the frequency range between 30 and 60 Hz, followed by the ranges of 20-30 and 60-100 Hz, explained best the defined subrepresentation given by both MEG and fMRI. These findings have important implications for improving and understanding of the biophysics underlying both neuroimaging techniques, and for determining the best strategy to combine MEG and fMRI data to study the spatiotemporal nature of brain activity.

Modulation of effective connectivity by cognitive demand in phonological verbal fluency

Verbal fluency is a classic neuropsychological measure of language production. Phonological verbal fluency involves the generation of words beginning with a specified letter, and its functional neuroanatomy is comprised of a distributed network of regions which is modulated by cognitive load. In order to investigate the functional relationship of these regions, the effective connectivity was analyzed with covariance structural equation modeling under conditions of varying cognitive load. Significant path coefficients were evident between the anterior cingulate, left middle frontal gyrus, and precuneus. The left middle frontal gyrus showed a facilitory projection to the precuneus which had a suppressive influence on anterior cingulate activation. With increasing cognitive demand, the left middle frontal projection to the precuneus became suppressive, and the path coefficient from the precuneus to the anterior cingulate showed a marked diminution in strength. The path analysis suggests that the lead-in process for letter verbal fluency may primarily involve an orthographic visual strategy. The marked changes in path coefficients with the increased cognitive load may reflect the greater demands placed on executive function. The significant changes in path coefficient values with increased cognitive demand indicate the importance of accounting for task difficulty not only in the interpretation of brain activation maps but also for effective connectivity measurements.