Gender and age effects in structural brain asymmetry as measured by MRI texture analysis

Effects of gender and age on structural brain asymmetry were studied by 3D texture analysis in 380 adults. Asymmetry is detected by comparing the complex 3D gray-scale image patterns in the left and right cerebral hemispheres as revealed by anatomical T1-weighted MRI datasets. The Talairach and Tournoux parcellation system was applied to study the asymmetry on five levels: the whole cerebrum, nine coronal sections, 12 axial sections, boxes resulting from both coronal and axial subdivisions, and by a sliding spherical window of 9 mm diameter. The analysis revealed that the brain asymmetry increases in the anterior-posterior direction starting from the central region onward. Male brains were found to be more asymmetric than female. This gender-related effect is noticeable in all brain areas but is most significant in the superior temporal gyrus, Heschl's gyrus, the adjacent white matter regions in the temporal stem and the knee of the optic radiation, the thalamus, and the posterior cingulate. The brain asymmetry increases significantly with age in the inferior frontal gyrus, anterior insula, anterior cingulate, parahippocampal gyrus, retrosplenial cortex, coronal radiata, and knee region of the internal capsule. Asymmetry decreases with age in the optic radiation, precentral gyrus, and angular gyrus. The texture-based method reported here is based on extended multisort cooccurrence matrices that employ intensity, gradient, and anisotropy features in a uniform way. It is sensitive, simple to reproduce, robust, and unbiased in the sense that segmentation of brain compartments and spatial transformations are not necessary. Thus, it should be considered as another tool for digital morphometry in neuroscience

Effects of pallidal deep brain stimulation and levodopa treatment on reaction-time performance in Parkinson's disease

Basal ganglia-thalamocortical circuits play an important role in movement preparation and execution. Tracer, single-cell, and lesion studies in monkeys suggest the existence of topologically segregated motor and nonmotor basal ganglia cortical circuits. In this study we used deep brain stimulation (DBS) of the posteroventrolateral globus pallidus internus (GPi) in patients with Parkinson's disease to elucidate the function of the GPi in human sensorimotor behavior. This question was investigated by comparing the influence of DBS on patients' performance in various reaction-time tasks that differed with respect to cognitive but not motor requirements. As a main result, DBS improved performance on the different tasks independently of the complexity of the involved cognitive processing functions. Furthermore, the observed effects did not depend on the modality of the processed information. These results suggest that the functional state of the posteroventrolateral GPi selectively affects the motor stage in simple sensorimotor acts, because this stage was the only stage involved in all investigated tasks. In addition to DBS, we manipulated the levodopa medication state of the PD patients. In contrast to DBS, levodopa effects on reaction times were less consistent. Levodopa improved reaction times in choice reaction tasks significantly, while affecting reaction times in a simple reaction task to a lesser extent. Error analysis revealed that the medication-dependent reaction-time improvement in the choice reaction tasks was accompanied by an increase in errors, suggesting a shift of the speed-accuracy criteria of the patients. A similar pattern of results was not observed for the DBS effects. Taken together, our data are in agreement with recent findings in monkeys that indicate a topological organization of the GPi in which motor functions are localized in posterolateral regions apart from cognitive regions. Furthermore, our data show a way to uncover the subcortical-cortical circuitry serving human sensorimotor behavior

Dating the Origin of Language Using Phonemic Diversity

Language is a key adaptation of our species, yet we do not know when it evolved. Here, we use data on language phonemic diversity to estimate a minimum date for the origin of language. We take advantage of the fact that phonemic diversity evolves slowly and use it as a clock to calculate how long the oldest African languages would have to have been around in order to accumulate the number of phonemes they possess today. We use a natural experiment, the colonization of Southeast Asia and Andaman Islands, to estimate the rate at which phonemic diversity increases through time. Using this rate, we estimate that present-day languages date back to the Middle Stone Age in Africa. Our analysis is consistent with the archaeological evidence suggesting that complex human behavior evolved during the Middle Stone Age in Africa, and does not support the view that language is a recent adaptation that has sparked the dispersal of humans out of Africa. While some of our assumptions require testing and our results rely at present on a single case-study, our analysis constitutes the first estimate of when language evolved that is directly based on linguistic data

Ancient DNA reveals prehistoric gene-flow from Siberia in the complex human population history of north east Europe

North East Europe harbors a high diversity of cultures and languages, suggesting a complex genetic history. Archaeological, anthropological, and genetic research has revealed a series of influences from Western and Eastern Eurasia in the past. While genetic data from modern-day populations is commonly used to make inferences about their origins and past migrations, ancient DNA provides a powerful test of such hypotheses by giving a snapshot of the past genetic diversity. In order to better understand the dynamics that have shaped the gene pool of North East Europeans, we generated and analyzed 34 mitochondrial genotypes from the skeletal remains of three archaeological sites in northwest Russia. These sites were dated to the Mesolithic and the Early Metal Age (7,500 and 3,500 uncalibrated years Before Present). We applied a suite of population genetic analyses (principal component analysis, genetic distance mapping, haplotype sharing analyses) and compared past demographic models through coalescent simulations using Bayesian Serial SimCoal and Approximate Bayesian Computation. Comparisons of genetic data from ancient and modern-day populations revealed significant changes in the mitochondrial makeup of North East Europeans through time. Mesolithic foragers showed high frequencies and diversity of haplogroups U (U2e, U4, U5a), a pattern observed previously in European hunter-gatherers from Iberia to Scandinavia. In contrast, the presence of mitochondrial DNA haplogroups C, D, and Z in Early Metal Age individuals suggested discontinuity with Mesolithic hunter-gatherers and genetic influx from central/eastern Siberia. We identified remarkable genetic dissimilarities between prehistoric and modern-day North East Europeans/Saami, which suggests an important role of post-Mesolithic migrations from Western Europe and subsequent population replacement/extinctions. This work demonstrates how ancient DNA can improve our understanding of human population movements across Eurasia. It contributes to the description of the spatio-temporal distribution of mitochondrial diversity and will be of significance for future reconstructions of the history of Europeans.Clio Der Sarkissian, Oleg Balanovsky, Guido Brandt, Valery Khartanovich, Alexandra Buzhilova, Sergey Koshel, Valery Zaporozhchenko, Detlef Gronenborn, Vyacheslav Moiseyev, Eugen Kolpakov, Vladimir Shumkin, Kurt W. Alt, Elena Balanovska, Alan Cooper, Wolfgang Haak, the Genographic Consortiu

Three-dimensional texture analysis of MRI brain datasets

A method is proposed for three-dimensional (3-D) texture analysis of magnetic resonance imaging brain datasets. It is based on extended, multisort co-occurrence matrices that employ intensity, gradient and anisotropy image features in a uniform way. Basic properties of matrices as well as their sensitivity and dependence on spatial image scaling are evaluated. The ability of the suggested 3-D texture descriptors is demonstrated on nontrivial classification tasks for pathologic findings in brain datasets

What have Klingon letters and faces in common? An fMRI study on content-specific working memory systems

Neuroimaging studies show that prefrontal, premotor, and parietal cortical regions are part of a working memory network that supports the active retention of information. In two experiments we used fMRI to examine whether prefrontal and posterior cortical areas are organized in a content-specific way for object and spatial working memory. Subjects performed a delayed matching-to-sample task modified to allow the examination of content-specific retention processes, independent of perceptual and decision-related processes. In Experiment 1, either unfamiliar geometrical objects (Klingon letters from an artificial alphabet unknown to the participants) or their spatial locations had to be memorized, whereas in Experiment 2, either unfamiliar faces or biological objects (butterflies) were actively memorized. All tasks activated a similar cortical network including posterior parietal (banks of the intraparietal sulcus), premotor (banks of the inferior precentral sulcus) and prefrontal regions (banks of the inferior frontal sulcus), and the presupplementary motor area (pre-SMA). For geometrical objects and faces for which strategic semantic processing can be assumed, this activation was larger in the left than in the right hemisphere, whereas a bilateral or right dominant distribution was obtained for butterflies and spatial locations. The present results do not support the process-specific or content-specific view of the role of the prefrontal cortex in working memory task. Rather, they suggest that the inferior prefrontal cortex houses nonmemonic strategic processing systems required for response selection and task management that can flexibly be used across a variety of tasks and informational domains