In both diagnostic and research applications, the interpretation of MR images of the human brain is facilitated when different data sets can be compared by visual inspection of equivalent anatomical planes. Quantitative analysis with predefined atlas templates often requires the initial alignment of atlas and image planes. Unfortunately, the axial planes acquired during separate scanning sessions are often different in their relative position and orientation, and these slices are not coplanar with those in the atlas. We have developed a completely automatic method to register a given volumetric data set with Talairach stereotaxic coordinate system.
The registration method is based on multi-scale, three-dimensional (3D) cross-correlation with an average (n > 300) MR brain image volume aligned with the Talariach stereotaxic space. Once the data set is re-sampled by the transformation recovered by the algorithm, atlas slices can be directly superimposed on the corresponding slices of the re-sampled volume. the use of such a standardized space also allows the direct comparison, voxel to voxel, of two or more data sets brought into stereotaxic space.
With use of a two-tailed Student t test for paired samples, there was no significant difference in the transformation parameters recovered by the automatic algorithm when compared with two manual landmark-based methods (p > 0.1 for all parameters except y-scale, where p > 0.05). Using root-mean-square difference between normalized voxel intensities as an unbiased measure of registration, we show that when estimated and averaged over 60 volumetric MR images in standard space, this measure was 30% lower for the automatic technique than the manual method, indicating better registrations. Likewise, the automatic method showed a 57% reduction in standard deviation, implying a more stable technique. The algorithm is able to recover the transformation even when data are missing from the top or bottom of the volume.
We present a fully automatic registration method to map volumetric data into stereotaxic space that yields results comparable with those of manually based techniques. The method requires no manual identification of points or contours and therefore does not suffer the drawbacks involved in user intervention such as reproducibility and interobserver variability.
"classified as gray matter, white matter, or cerebrospinal fluid (Collins et al. 1995). The three-dimensional gray matter maps created by the classification algorithm were subsequently blurred using an 8 mm isotropic Gaussian kernel in preparation for second-level analyses (Collins et al. 1994). No significant between-group differences were found for gray matter ( "
[Show abstract][Hide abstract] ABSTRACT: We compared the brain structure of highly proficient simultaneous (two languages from birth) and sequential (second language after age 5) bilinguals, who differed only in their degree of native-like accent, to determine how the brain develops when a skill is acquired from birth versus later in life. For the simultaneous bilin-guals, gray matter density was increased in the left puta-men, as well as in the left posterior insula, right dorsolateral prefrontal cortex, and left and right occipital cortex. For the sequential bilinguals, gray matter density was increased in the bilateral premotor cortex. Sequential bilinguals with better accents also showed greater gray matter density in the left putamen, and in several additional brain regions important for sensorimotor integration and speech–motor control. Our findings suggest that second language learning results in enhanced brain structure of specific brain areas, which depends on whether two languages are learned simultaneously or sequentially, and on the extent to which native-like proficiency is acquired.
Brain Structure and Function 09/2015; DOI:10.1007/s00429-015-1121-9 · 5.62 Impact Factor
"We used the CIVET pipeline to generate measurements of cortical thickness and cortical surface area, as previously described (Gong et al., 2012). Briefly, the T1-weighted MR images were linearly aligned in stereotaxic space using a 9-parameter linear transformation (Collins et al., 1994); subsequently, these images were corrected for non- Table 1 Demographics, intelligence and reading performance of the typically developing ( "
[Show abstract][Hide abstract] ABSTRACT: Abnormalities in large-scale brain networks have been recently reported in dyslexia; however, it remains unclear whether these abnormalities are congenital (due to dyslexia per se) or arise later in development. Here, structural magnetic resonance imaging data of 17 Chinese reading disabled (RD) and 17 age-matched typically developing (TD) children were used to construct cortical thickness (sensitive to postnatal development) and surface area (sensitive to prenatal development) networks. In the thickness network, compared to TD, RD showed reduced nodal network properties (e.g., degree and betweenness) in the left hemisphere along with enhanced nodal properties mainly in the right hemisphere. As for the surface area network, compared to TD, RD demonstrated lower nodal properties in posterior brain regions and higher nodal properties in anterior brain regions. Furthermore, hubs in both the thickness and surface area networks in RD were more distributed in frontal areas and less distributed in parietal areas, whereas TD showed the opposite pattern. Altogether, these findings indicate that the aberrant structural connectivity in the dyslexic individuals was not only due to a late developmental effect reflected in the altered thickness network, but may also be a congenital effect during prenatal development, reflected in the altered surface network.
"Memory in the parahippocampal cortex FIGURE 7 | Overall experimental design of the fMRI oddball task showing the correct response that should be made by participants when viewing the standard condition , spatial and object change " oddball " conditions . in - house software ( Collins et al . , 1994 ) . Each scan consisted of four blocs , each having ( a ) baseline control ; ( b ) object or spatial task ; and ( c ) baseline control , with different sets of stimuli for each of the blocs ( see Figures 6 – 8 ) ."
[Show abstract][Hide abstract] ABSTRACT: The parahippocampal cortex and hippocampus are brain structures known to be involved in memory. However, the unique contribution of the parahippocampal cortex remains unclear. The current study investigates memory for object identity and memory of the configuration of objects in patients with small thermo-coagulation lesions to the hippocampus or the parahippocampal cortex. Results showed that in contrast to control participants and patients with damage to the hippocampus leaving the parahippocampal cortex intact, patients with lesions that included the right parahippocampal cortex (RPH) were severely impaired on a task that required learning the spatial configuration of objects on a computer screen; these patients, however, were not impaired at learning the identity of objects. Conversely, we found that patients with lesions to the right hippocampus (RH) or left hippocampus (LH), sparing the parahippocampal cortex, performed just as well as the control participants. Furthermore, they were not impaired on the object identity task. In the functional Magnetic Resonance Imaging (fMRI) experiment, healthy young adults performed the same tasks. Consistent with the findings of the lesion study, the fMRI results showed significant activity in the RPH in the memory for the spatial configuration condition, but not memory for object identity. Furthermore, the pattern of fMRI activity measured in the baseline control conditions decreased specifically in the parahippocampal cortex as a result of the experimental task, providing evidence for task specific repetition suppression. In summary, while our previous studies demonstrated that the hippocampus is critical to the construction of a cognitive map, both the lesion and fMRI studies have shown an involvement of the RPH for learning spatial configurations of objects but not object identity, and that this takes place independent of the hippocampus.
Frontiers in Human Neuroscience 08/2015; 9:431. DOI:10.3389/fnhum.2015.00431 · 2.99 Impact Factor
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