2017 |
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Fahimeh Darki, Satu Massinen, Elina Salmela, Hans Matsson, Myriam Peyrard-Janvid, Torkel Klingberg, Juha Kere Human ROBO1 regulates white matter structure in corpus callosum Journal Article Brain Structure and Function, 222 (2), pp. 707–716, 2017, ISSN: 18632661. @article{Darki2017, title = {Human ROBO1 regulates white matter structure in corpus callosum}, author = {Fahimeh Darki and Satu Massinen and Elina Salmela and Hans Matsson and Myriam Peyrard-Janvid and Torkel Klingberg and Juha Kere}, doi = {10.1007/s00429-016-1240-y}, issn = {18632661}, year = {2017}, date = {2017-01-01}, journal = {Brain Structure and Function}, volume = {222}, number = {2}, pages = {707--716}, publisher = {Springer Berlin Heidelberg}, abstract = {textcopyright 2016, The Author(s). The axon guidance receptor, Robo1, controls the pathfinding of callosal axons in mice. To determine whether the orthologous ROBO1 gene is involved in callosal development also in humans, we studied polymorphisms in the ROBO1 gene and variation in the white matter structure in the corpus callosum using both structural magnetic resonance imaging and diffusion tensor magnetic resonance imaging. We found that five polymorphisms in the regulatory region of ROBO1 were associated with white matter density in the posterior part of the corpus callosum pathways. One of the polymorphisms, rs7631357, was also significantly associated with the probability of connections to the parietal cortical regions. Our results demonstrate that human ROBO1 may be involved in the regulation of the structure and connectivity of posterior part of corpus callosum.}, keywords = {}, pubstate = {published}, tppubtype = {article} } textcopyright 2016, The Author(s). The axon guidance receptor, Robo1, controls the pathfinding of callosal axons in mice. To determine whether the orthologous ROBO1 gene is involved in callosal development also in humans, we studied polymorphisms in the ROBO1 gene and variation in the white matter structure in the corpus callosum using both structural magnetic resonance imaging and diffusion tensor magnetic resonance imaging. We found that five polymorphisms in the regulatory region of ROBO1 were associated with white matter density in the posterior part of the corpus callosum pathways. One of the polymorphisms, rs7631357, was also significantly associated with the probability of connections to the parietal cortical regions. Our results demonstrate that human ROBO1 may be involved in the regulation of the structure and connectivity of posterior part of corpus callosum. | |
Henrik Ullman, Torkel Klingberg Timing of white matter development determines cognitive abilities at school entry but not in late adolescence Journal Article Cerebral Cortex, 27 (9), pp. 4516–4522, 2017, ISSN: 14602199. @article{Ullman2017, title = {Timing of white matter development determines cognitive abilities at school entry but not in late adolescence}, author = {Henrik Ullman and Torkel Klingberg}, doi = {10.1093/cercor/bhw256}, issn = {14602199}, year = {2017}, date = {2017-01-01}, journal = {Cerebral Cortex}, volume = {27}, number = {9}, pages = {4516--4522}, abstract = {The primary aim of this study was to investigate to what degree the age-related white matter development, here called " brain age " , is associated with working memory (WM) and numeric abilities in 6-year-old children. We measured white matter development using diffusion tensor imaging to calculate fractional anisotropy (FA). A " brain age " model was created using multivariate statistics, which described association between FA and age in a sample of 6-to 20-year-old children. This age model was then applied to predict " brain age " in a second sample of 6-year-old children. The predicted brain age correlated with WM performance and numerical ability (NA) (P textless 0.01, P textless 0.05) in the 6-year-old children. More than 50% of the stable variance in WM performance was explained. We found that in children older than 13 years of age, this association between brain age and WM was no longer significant (P textgreater 0.5). The results bear theoretical implications as they suggest that the variability in individual developmental timing strongly affects WM and NA at school start but badly predicts adolescent cognitive functioning. Furthermore, it bears practical implications as one may differentiate maturation lags from persistent low cognitive abilities in school children, complementing cognitive tests.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The primary aim of this study was to investigate to what degree the age-related white matter development, here called " brain age " , is associated with working memory (WM) and numeric abilities in 6-year-old children. We measured white matter development using diffusion tensor imaging to calculate fractional anisotropy (FA). A " brain age " model was created using multivariate statistics, which described association between FA and age in a sample of 6-to 20-year-old children. This age model was then applied to predict " brain age " in a second sample of 6-year-old children. The predicted brain age correlated with WM performance and numerical ability (NA) (P textless 0.01, P textless 0.05) in the 6-year-old children. More than 50% of the stable variance in WM performance was explained. We found that in children older than 13 years of age, this association between brain age and WM was no longer significant (P textgreater 0.5). The results bear theoretical implications as they suggest that the variability in individual developmental timing strongly affects WM and NA at school start but badly predicts adolescent cognitive functioning. Furthermore, it bears practical implications as one may differentiate maturation lags from persistent low cognitive abilities in school children, complementing cognitive tests. | |
2016 |
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Margot A Schel, Torkel Klingberg Specialization of the Right Intraparietal Sulcus for Processing Mathematics During Development Journal Article Cerebral Cortex, 27 (9), pp. 4436–4446, 2016, ISSN: 1047-3211. @article{Schel2017, title = {Specialization of the Right Intraparietal Sulcus for Processing Mathematics During Development}, author = {Margot A Schel and Torkel Klingberg}, url = {http://cercor.oxfordjournals.org/cgi/doi/10.1093/cercor/bhw246}, doi = {10.1093/cercor/bhw246}, issn = {1047-3211}, year = {2016}, date = {2016-08-01}, journal = {Cerebral Cortex}, volume = {27}, number = {9}, pages = {4436--4446}, abstract = {Mathematical ability, especially perception of numbers and performance of arithmetics, is known to rely on the activation of intraparietal sulcus (IPS). However, reasoning ability and working memory, 2 highly associated abilities also activate partly overlapping regions. Most studies aimed at localizing mathematical function have used group averages, where individual variability is averaged out, thus confounding the anatomical specificity when localizing cognitive functions. Here, we analyze the functional anatomy of the intraparietal cortex by using individual analysis of subregions of IPS based on how they are structurally connected to frontal, parietal, and occipital cortex. Analysis of cortical thickness showed that the right anterior IPS, defined by its connections to the frontal lobe, was associated with both visuospatial working memory, and mathematics in 6-year-old children. This region specialized during development to be specifically related to mathematics, but not visuospatial working memory in adolescents and adults. This could be an example of interactive specialization, where interacting with the environment in combination with interactions between cortical regions leads from a more general role of right anterior IPS in spatial processing, to a specialization of this region for mathematics.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Mathematical ability, especially perception of numbers and performance of arithmetics, is known to rely on the activation of intraparietal sulcus (IPS). However, reasoning ability and working memory, 2 highly associated abilities also activate partly overlapping regions. Most studies aimed at localizing mathematical function have used group averages, where individual variability is averaged out, thus confounding the anatomical specificity when localizing cognitive functions. Here, we analyze the functional anatomy of the intraparietal cortex by using individual analysis of subregions of IPS based on how they are structurally connected to frontal, parietal, and occipital cortex. Analysis of cortical thickness showed that the right anterior IPS, defined by its connections to the frontal lobe, was associated with both visuospatial working memory, and mathematics in 6-year-old children. This region specialized during development to be specifically related to mathematics, but not visuospatial working memory in adolescents and adults. This could be an example of interactive specialization, where interacting with the environment in combination with interactions between cortical regions leads from a more general role of right anterior IPS in spatial processing, to a specialization of this region for mathematics. | |
2015 |
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Fahimeh Darki, Torkel Klingberg The role of fronto-parietal and fronto-striatal networks in the development of working memory: A longitudinal study Journal Article Cerebral Cortex, 25 (6), pp. 1587–1595, 2015, ISSN: 14602199. @article{Darki2015, title = {The role of fronto-parietal and fronto-striatal networks in the development of working memory: A longitudinal study}, author = {Fahimeh Darki and Torkel Klingberg}, url = {https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bht352}, doi = {10.1093/cercor/bht352}, issn = {14602199}, year = {2015}, date = {2015-06-01}, journal = {Cerebral Cortex}, volume = {25}, number = {6}, pages = {1587--1595}, abstract = {The increase in working memory (WM) capacity is an important part of cognitive development during childhood and adolescence. Cross-sectional analyses have associated this development with higher activity, thinner cortex, and white matter maturation in fronto-parietal networks. However, there is still a lack of longitudinal data showing the dynamics of this development and the role of subcortical structures. We included 89 individuals, aged 6-25 years, who were scanned 1-3 times at 2-year intervals. Functional magnetic resonance imaging (fMRI) was used to identify activated areas in superior frontal, intraparietal cortices, and caudate nucleus during performance on a visuo-spatial WM task. Probabilistic tractography determined the anatomical pathways between these regions. In the cross-sectional analysis, WM capacity correlated with activity in frontal and parietal regions, cortical thickness in parietal cortex, and white matter structure [both fractional anisotropy (FA) and white matter volume] of fronto-parietal and fronto-striatal tracts. However, in the longitudinal analysis, FA in white matter tracts and activity in caudate predicted future WM capacity. The results show a dynamic of neural networks underlying WM development in which cortical activity and structure relate to current capacity, while white matter tracts and caudate activity predict future WM capacity.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The increase in working memory (WM) capacity is an important part of cognitive development during childhood and adolescence. Cross-sectional analyses have associated this development with higher activity, thinner cortex, and white matter maturation in fronto-parietal networks. However, there is still a lack of longitudinal data showing the dynamics of this development and the role of subcortical structures. We included 89 individuals, aged 6-25 years, who were scanned 1-3 times at 2-year intervals. Functional magnetic resonance imaging (fMRI) was used to identify activated areas in superior frontal, intraparietal cortices, and caudate nucleus during performance on a visuo-spatial WM task. Probabilistic tractography determined the anatomical pathways between these regions. In the cross-sectional analysis, WM capacity correlated with activity in frontal and parietal regions, cortical thickness in parietal cortex, and white matter structure [both fractional anisotropy (FA) and white matter volume] of fronto-parietal and fronto-striatal tracts. However, in the longitudinal analysis, FA in white matter tracts and activity in caudate predicted future WM capacity. The results show a dynamic of neural networks underlying WM development in which cortical activity and structure relate to current capacity, while white matter tracts and caudate activity predict future WM capacity. |
2017 |
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Human ROBO1 regulates white matter structure in corpus callosum Journal Article Brain Structure and Function, 222 (2), pp. 707–716, 2017, ISSN: 18632661. | |
Timing of white matter development determines cognitive abilities at school entry but not in late adolescence Journal Article Cerebral Cortex, 27 (9), pp. 4516–4522, 2017, ISSN: 14602199. | |
2016 |
|
Specialization of the Right Intraparietal Sulcus for Processing Mathematics During Development Journal Article Cerebral Cortex, 27 (9), pp. 4436–4446, 2016, ISSN: 1047-3211. | |
2015 |
|
The role of fronto-parietal and fronto-striatal networks in the development of working memory: A longitudinal study Journal Article Cerebral Cortex, 25 (6), pp. 1587–1595, 2015, ISSN: 14602199. |