Spatial normalization of neuroimaging data is a standard step when assessing group effects. As a result of divergent analysis procedures due to different normalization algorithms or templates, not all published coordinates refer to the same neuroanatomical region. Specifically, the literature is populated with results in the form of MNI or Talairach coordinates, and their disparity can impede the comparison of results across different studies. This becomes particularly problematic in coordinate-based meta-analyses, wherein coordinate disparity should be corrected to reduce error and facilitate literature reviews. In this study, a quantitative comparison was performed on two corrections, the Brett transform (i.e., "mni2tal"), and the Lancaster transform (i.e., "icbm2tal"). Functional magnetic resonance imaging (fMRI) data acquired during a standard paired associates task indicated that the disparity between MNI and Talairach coordinates was better reduced via the Lancaster transform, as compared to the Brett transform. In addition, an activation likelihood estimation (ALE) meta-analysis of the paired associates literature revealed that a higher degree of concordance was obtained when using the Lancaster transform in the form of fewer, smaller, and more intense clusters. Based on these results, we recommend that the Lancaster transform be adopted as the community standard for reducing disparity between results reported as MNI or Talairach coordinates, and suggest that future spatial normalization strategies be designed to minimize this variability in the literature.

LSVT® LOUD (Lee Silverman Voice Treatment) is efficacious in the treatment of speech disorders in idiopathic Parkinson’s disease (IPD), particularly hypophonia. Functional imaging in patients with IPD has shown abnormalities in several speech regions and changes in these areas immediately following treatment. This study serves to extend the analysis by correlating changes of regional neural activity with the main behavioral change following treatment, namely, increased vocal intensity. Ten IPD participants with hypophonia were studied before and after LSVT LOUD. Cerebral blood flow during rest and reading conditions were measured by H215O-positron emission tomography. Z-score images were generated by contrasting reading with rest conditions for pre- and post-LSVT LOUD sessions. Neuronal activity during reading in the pre- versus post-LSVT LOUD contrast was correlated with corresponding change in vocal intensity to generate correlation images. Behaviorally, vocal intensity for speech tasks increased significantly after LSVT LOUD. The contrast and correlation analyses indicate a treatment-dependent shift to the right hemisphere with modification in the speech motor regions as well as in prefrontal and temporal areas. We interpret the modification of activity in these regions to be a top–down effect of LSVT LOUD. The absence of an effect of LSVT LOUD on the basal ganglion supports this argument. Our findings indicate that the therapeutic effect of LSVT LOUD in IPD hypophonia results from a shift in cortical activity to the right hemisphere. These findings demonstrate that the short-term changes in the speech motor and multimodal integration areas can occur in a top–down manner.

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1(hand)). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1(hand) region, and (3) that remote effects must be caused, either directly or indirectly, by the M1(hand) excitation. The path model thus derived exhibited an exceptional level of goodness (chi(2)=22.150, df=38, P=0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity.

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