BECon: a tool for interpreting DNA methylation findings from blood in the context of brain.

PubMed

Edgar, R D; Jones, M J; Meaney, M J; Turecki, G; Kobor, M S

2017-08-01

Tissue differences are one of the largest contributors to variability in the human DNA methylome. Despite the tissue-specific nature of DNA methylation, the inaccessibility of human brain samples necessitates the frequent use of surrogate tissues such as blood, in studies of associations between DNA methylation and brain function and health. Results from studies of surrogate tissues in humans are difficult to interpret in this context, as the connection between blood-brain DNA methylation is tenuous and not well-documented. Here, we aimed to provide a resource to the community to aid interpretation of blood-based DNA methylation results in the context of brain tissue. We used paired samples from 16 individuals from three brain regions and whole blood, run on the Illumina 450 K Human Methylation Array to quantify the concordance of DNA methylation between tissues. From these data, we have made available metrics on: the variability of cytosine-phosphate-guanine dinucleotides (CpGs) in our blood and brain samples, the concordance of CpGs between blood and brain, and estimations of how strongly a CpG is affected by cell composition in both blood and brain through the web application BECon (Blood-Brain Epigenetic Concordance; https://redgar598.shinyapps.io/BECon/). We anticipate that BECon will enable biological interpretation of blood-based human DNA methylation results, in the context of brain.

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

PubMed

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

NASA Astrophysics Data System (ADS)

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

PubMed

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-03-22

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry

PubMed Central

Meier, Raphael; Knecht, Urspeter; Loosli, Tina; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2016-01-01

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83–0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments. PMID:27001047

Differences in amyloid-β clearance across mouse and human blood-brain barrier models: kinetic analysis and mechanistic modeling.

PubMed

Qosa, Hisham; Abuasal, Bilal S; Romero, Ignacio A; Weksler, Babette; Couraud, Pierre-Oliver; Keller, Jeffrey N; Kaddoumi, Amal

2014-04-01

Alzheimer's disease (AD) has a characteristic hallmark of amyloid-β (Aβ) accumulation in the brain. This accumulation of Aβ has been related to its faulty cerebral clearance. Indeed, preclinical studies that used mice to investigate Aβ clearance showed that efflux across blood-brain barrier (BBB) and brain degradation mediate efficient Aβ clearance. However, the contribution of each process to Aβ clearance remains unclear. Moreover, it is still uncertain how species differences between mouse and human could affect Aβ clearance. Here, a modified form of the brain efflux index method was used to estimate the contribution of BBB and brain degradation to Aβ clearance from the brain of wild type mice. We estimated that 62% of intracerebrally injected (125)I-Aβ40 is cleared across BBB while 38% is cleared by brain degradation. Furthermore, in vitro and in silico studies were performed to compare Aβ clearance between mouse and human BBB models. Kinetic studies for Aβ40 disposition in bEnd3 and hCMEC/D3 cells, representative in vitro mouse and human BBB models, respectively, demonstrated 30-fold higher rate of (125)I-Aβ40 uptake and 15-fold higher rate of degradation by bEnd3 compared to hCMEC/D3 cells. Expression studies showed both cells to express different levels of P-glycoprotein and RAGE, while LRP1 levels were comparable. Finally, we established a mechanistic model, which could successfully predict cellular levels of (125)I-Aβ40 and the rate of each process. Established mechanistic model suggested significantly higher rates of Aβ uptake and degradation in bEnd3 cells as rationale for the observed differences in (125)I-Aβ40 disposition between mouse and human BBB models. In conclusion, current study demonstrates the important role of BBB in the clearance of Aβ from the brain. Moreover, it provides insight into the differences between mouse and human BBB with regards to Aβ clearance and offer, for the first time, a mathematical model that describes Aβ clearance across BBB. Copyright © 2014 Elsevier Ltd. All rights reserved.

Differences in amyloid-β clearance across mouse and human blood-brain barrier models: Kinetic analysis and mechanistic modeling

PubMed Central

Qosa, Hisham; Abuasal, Bilal S.; Romero, Ignacio A.; Weksler, Babette; Couraud, Pierre-Oliver; Keller, Jeffrey N.; Kaddoumi, Amal

2014-01-01

Alzheimer’s disease (AD) has a characteristic hallmark of amyloid-β (Aβ) accumulation in the brain. This accumulation of Aβ has been related to its faulty cerebral clearance. Indeed, preclinical studies that used mice to investigate Aβ clearance showed that efflux across blood-brain barrier (BBB) and brain degradation mediate efficient Aβ clearance. However, the contribution of each process to Aβ clearance remains unclear. Moreover, it is still uncertain how species differences between mouse and human could affect Aβ clearance. Here, a modified form of the brain efflux index method was used to estimate the contribution of BBB and brain degradation to Aβ clearance from the brain of wild type mice. We estimated that 62% of intracerebrally injected 125I-Aβ40 is cleared across BBB while 38% is cleared by brain degradation. Furthermore, in vitro and in silico studies were performed to compare Aβ clearance between mouse and human BBB models. Kinetic studies for Aβ40 disposition in bEnd3 and hCMEC/D3 cells, representative in vitro mouse and human BBB models, respectively, demonstrated 30-fold higher rate of 125I-Aβ40 uptake and 15-fold higher rate of degradation by bEnd3 compared to hCMEC/D3 cells. Expression studies showed both cells to express different levels of P-glycoprotein and RAGE, while LRP1 levels were comparable. Finally, we established a mechanistic model, which could successfully predict cellular levels of 125I-Aβ40 and the rate of each process. Established mechanistic model suggested significantly higher rates of Aβ uptake and degradation in bEnd3 cells as rationale for the observed differences in 125I-Aβ40 disposition between mouse and human BBB models. In conclusion, current study demonstrates the important role of BBB in the clearance of Aβ from the brain. Moreover, it provides insight into the differences between mouse and human BBB with regards to Aβ clearance and offer, for the first time, a mathematical model that describes Aβ clearance across BBB. PMID:24467845

Measuring specific receptor binding of a PET radioligand in human brain without pharmacological blockade: The genomic plot.

PubMed

Veronese, Mattia; Zanotti-Fregonara, Paolo; Rizzo, Gaia; Bertoldo, Alessandra; Innis, Robert B; Turkheimer, Federico E

2016-04-15

PET studies allow in vivo imaging of the density of brain receptor species. The PET signal, however, is the sum of the fraction of radioligand that is specifically bound to the target receptor and the non-displaceable fraction (i.e. the non-specifically bound radioligand plus the free ligand in tissue). Therefore, measuring the non-displaceable fraction, which is generally assumed to be constant across the brain, is a necessary step to obtain regional estimates of the specific fractions. The nondisplaceable binding can be directly measured if a reference region, i.e. a region devoid of any specific binding, is available. Many receptors are however widely expressed across the brain, and a true reference region is rarely available. In these cases, the nonspecific binding can be obtained after competitive pharmacological blockade, which is often contraindicated in humans. In this work we introduce the genomic plot for estimating the nondisplaceable fraction using baseline scans only. The genomic plot is a transformation of the Lassen graphical method in which the brain maps of mRNA transcripts of the target receptor obtained from the Allen brain atlas are used as a surrogate measure of the specific binding. Thus, the genomic plot allows the calculation of the specific and nondisplaceable components of radioligand uptake without the need of pharmacological blockade. We first assessed the statistical properties of the method with computer simulations. Then we sought ground-truth validation using human PET datasets of seven different neuroreceptor radioligands, where nonspecific fractions were either obtained separately using drug displacement or available from a true reference region. The population nondisplaceable fractions estimated by the genomic plot were very close to those measured by actual human blocking studies (mean relative difference between 2% and 7%). However, these estimates were valid only when mRNA expressions were predictive of protein levels (i.e. there were no significant post-transcriptional changes). This condition can be readily established a priori by assessing the correlation between PET and mRNA expression. Copyright © 2016 Elsevier Inc. All rights reserved.

Measuring specific receptor binding of a PET radioligand in human brain without pharmacological blockade: The genomic plot

PubMed Central

Veronese, Mattia; Zanotti-Fregonara, Paolo; Rizzo, Gaia; Bertoldo, Alessandra; Innis, Robert B.; Turkheimer, Federico E.

2016-01-01

PET studies allow in vivo imaging of the density of brain receptor species. The PET signal, however, is the sum of the fraction of radioligand that is specifically bound to the target receptor and the non-displaceable fraction (i.e. the non-specifically bound radioligand plus the free ligand in tissue). Therefore, measuring the non-displaceable fraction, which is generally assumed to be constant across the brain, is a necessary step to obtain regional estimates of the specific fractions. The nondisplaceable binding can be directly measured if a reference region, i.e. a region devoid of any specific binding, is available. Many receptors are however widely expressed across the brain, and a true reference region is rarely available. In these cases, the nonspecific binding can be obtained after competitive pharmacological blockade, which is often contraindicated in humans. In this work we introduce the genomic plot for estimating the nondisplaceable fraction using baseline scans only. The genomic plot is a transformation of the Lassen graphical method in which the brain maps of mRNA transcripts of the target receptor obtained from the Allen brain atlas are used as a surrogate measure of the specific binding. Thus, the genomic plot allows the calculation of the specific and nondisplaceable components of radioligand uptake without the need of pharmacological blockade. We first assessed the statistical properties of the method with computer simulations. Then we sought ground-truth validation using human PET datasets of seven different neuroreceptor radioligands, where nonspecific fractions were either obtained separately using drug displacement or available from a true reference region. The population nondisplaceable fractions estimated by the genomic plot were very close to those measured by actual human blocking studies (mean relative difference between 2% and 7%). However, these estimates were valid only when mRNA expressions were predictive of protein levels (i.e. there were no significant post-transcriptional changes). This condition can be readily established a priori by assessing the correlation between PET and mRNA expression. PMID:26850512

Individual differences in GABA content are reliable but are not uniform across the human cortex

PubMed Central

Greenhouse, Ian; Noah, Sean; Maddock, Richard J; Ivry, Richard B

2016-01-01

1H magnetic resonance spectroscopy (MRS) provides a powerful tool to measure gamma-aminobutyric acid (GABA), the principle inhibitory neurotransmitter in the human brain. We asked whether individual differences in MRS estimates of GABA are uniform across the cortex or vary between regions. In two sessions, resting GABA concentrations in the lateral prefrontal, sensorimotor, dorsal premotor, and occipital cortices were measured in twenty-eight healthy individuals. GABA estimates within each region were stable across weeks, with low coefficients of variation. Despite this stability, the GABA estimates were not correlated between regions. In contrast, the percentage of brain tissue per volume, a control measure, was correlated between the three anterior regions. These results provide an interesting dissociation between an anatomical measure of individual differences and a neurochemical measure. The different patterns of anatomy and GABA concentrations have implications for understanding regional variation in the molecular topography of the brain in health and disease. PMID:27288552

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach.

PubMed

Xu, Nan; Spreng, R Nathan; Doerschuk, Peter C

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the "common driver" problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain.

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

Robust estimation of fractal measures for characterizing the structural complexity of the human brain: optimization and reproducibility

PubMed Central

Goñi, Joaquín; Sporns, Olaf; Cheng, Hu; Aznárez-Sanado, Maite; Wang, Yang; Josa, Santiago; Arrondo, Gonzalo; Mathews, Vincent P; Hummer, Tom A; Kronenberger, William G; Avena-Koenigsberger, Andrea; Saykin, Andrew J.; Pastor, María A.

2013-01-01

High-resolution isotropic three-dimensional reconstructions of human brain gray and white matter structures can be characterized to quantify aspects of their shape, volume and topological complexity. In particular, methods based on fractal analysis have been applied in neuroimaging studies to quantify the structural complexity of the brain in both healthy and impaired conditions. The usefulness of such measures for characterizing individual differences in brain structure critically depends on their within-subject reproducibility in order to allow the robust detection of between-subject differences. This study analyzes key analytic parameters of three fractal-based methods that rely on the box-counting algorithm with the aim to maximize within-subject reproducibility of the fractal characterizations of different brain objects, including the pial surface, the cortical ribbon volume, the white matter volume and the grey matter/white matter boundary. Two separate datasets originating from different imaging centers were analyzed, comprising, 50 subjects with three and 24 subjects with four successive scanning sessions per subject, respectively. The reproducibility of fractal measures was statistically assessed by computing their intra-class correlations. Results reveal differences between different fractal estimators and allow the identification of several parameters that are critical for high reproducibility. Highest reproducibility with intra-class correlations in the range of 0.9–0.95 is achieved with the correlation dimension. Further analyses of the fractal dimensions of parcellated cortical and subcortical gray matter regions suggest robustly estimated and region-specific patterns of individual variability. These results are valuable for defining appropriate parameter configurations when studying changes in fractal descriptors of human brain structure, for instance in studies of neurological diseases that do not allow repeated measurements or for disease-course longitudinal studies. PMID:23831414

Interpretation of the Precision Matrix and Its Application in Estimating Sparse Brain Connectivity during Sleep Spindles from Human Electrocorticography Recordings

PubMed Central

Das, Anup; Sampson, Aaron L.; Lainscsek, Claudia; Muller, Lyle; Lin, Wutu; Doyle, John C.; Cash, Sydney S.; Halgren, Eric; Sejnowski, Terrence J.

2017-01-01

The correlation method from brain imaging has been used to estimate functional connectivity in the human brain. However, brain regions might show very high correlation even when the two regions are not directly connected due to the strong interaction of the two regions with common input from a third region. One previously proposed solution to this problem is to use a sparse regularized inverse covariance matrix or precision matrix (SRPM) assuming that the connectivity structure is sparse. This method yields partial correlations to measure strong direct interactions between pairs of regions while simultaneously removing the influence of the rest of the regions, thus identifying regions that are conditionally independent. To test our methods, we first demonstrated conditions under which the SRPM method could indeed find the true physical connection between a pair of nodes for a spring-mass example and an RC circuit example. The recovery of the connectivity structure using the SRPM method can be explained by energy models using the Boltzmann distribution. We then demonstrated the application of the SRPM method for estimating brain connectivity during stage 2 sleep spindles from human electrocorticography (ECoG) recordings using an 8 × 8 electrode array. The ECoG recordings that we analyzed were from a 32-year-old male patient with long-standing pharmaco-resistant left temporal lobe complex partial epilepsy. Sleep spindles were automatically detected using delay differential analysis and then analyzed with SRPM and the Louvain method for community detection. We found spatially localized brain networks within and between neighboring cortical areas during spindles, in contrast to the case when sleep spindles were not present. PMID:28095202

Investigation of the cortical activation by touching fabric actively using fingers.

PubMed

Wang, Q; Yu, W; He, N; Chen, K

2015-11-01

Human subjects can tactually estimate the perception of touching fabric. Although many psychophysical and neurophysiological experiments have elucidated the peripheral neural mechanisms that underlie fabric hand estimation, the associated cortical mechanisms are not well understood. To identify the brain regions responsible for the tactile stimulation of fabric against human skin, we used the technology of functional magnetic resonance imaging (fMRI), to observe brain activation when the subjects touched silk fabric actively using fingers. Consistent with previous research about brain cognition on sensory stimulation, large activation in the primary somatosensory cortex (SI), the secondary somatosensory cortex (SII) and moto cortex, and little activation in the posterior insula cortex and Broca's Area were observed when the subjects touched silk fabric. The technology of fMRI is a promising tool to observe and characterize the brain cognition on the tactile stimulation of fabric quantitatively. The intensity and extent of activation in the brain regions, especially the primary somatosensory cortex (SI) and the secondary somatosensory cortex (SII), can represent the perception of stimulation of fabric quantitatively. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A pairwise maximum entropy model accurately describes resting-state human brain networks

PubMed Central

Watanabe, Takamitsu; Hirose, Satoshi; Wada, Hiroyuki; Imai, Yoshio; Machida, Toru; Shirouzu, Ichiro; Konishi, Seiki; Miyashita, Yasushi; Masuda, Naoki

2013-01-01

The resting-state human brain networks underlie fundamental cognitive functions and consist of complex interactions among brain regions. However, the level of complexity of the resting-state networks has not been quantified, which has prevented comprehensive descriptions of the brain activity as an integrative system. Here, we address this issue by demonstrating that a pairwise maximum entropy model, which takes into account region-specific activity rates and pairwise interactions, can be robustly and accurately fitted to resting-state human brain activities obtained by functional magnetic resonance imaging. Furthermore, to validate the approximation of the resting-state networks by the pairwise maximum entropy model, we show that the functional interactions estimated by the pairwise maximum entropy model reflect anatomical connexions more accurately than the conventional functional connectivity method. These findings indicate that a relatively simple statistical model not only captures the structure of the resting-state networks but also provides a possible method to derive physiological information about various large-scale brain networks. PMID:23340410

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

Initial Validation for the Estimation of Resting-State fMRI Effective Connectivity by a Generalization of the Correlation Approach

PubMed Central

Xu, Nan; Spreng, R. Nathan; Doerschuk, Peter C.

2017-01-01

Resting-state functional MRI (rs-fMRI) is widely used to noninvasively study human brain networks. Network functional connectivity is often estimated by calculating the timeseries correlation between blood-oxygen-level dependent (BOLD) signal from different regions of interest (ROIs). However, standard correlation cannot characterize the direction of information flow between regions. In this paper, we introduce and test a new concept, prediction correlation, to estimate effective connectivity in functional brain networks from rs-fMRI. In this approach, the correlation between two BOLD signals is replaced by a correlation between one BOLD signal and a prediction of this signal via a causal system driven by another BOLD signal. Three validations are described: (1) Prediction correlation performed well on simulated data where the ground truth was known, and outperformed four other methods. (2) On simulated data designed to display the “common driver” problem, prediction correlation did not introduce false connections between non-interacting driven ROIs. (3) On experimental data, prediction correlation recovered the previously identified network organization of human brain. Prediction correlation scales well to work with hundreds of ROIs, enabling it to assess whole brain interregional connectivity at the single subject level. These results provide an initial validation that prediction correlation can capture the direction of information flow and estimate the duration of extended temporal delays in information flow between regions of interest ROIs based on BOLD signal. This approach not only maintains the high sensitivity to network connectivity provided by the correlation analysis, but also performs well in the estimation of causal information flow in the brain. PMID:28559793

Bayesian estimation inherent in a Mexican-hat-type neural network

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2016-05-01

Brain functions, such as perception, motor control and learning, and decision making, have been explained based on a Bayesian framework, i.e., to decrease the effects of noise inherent in the human nervous system or external environment, our brain integrates sensory and a priori information in a Bayesian optimal manner. However, it remains unclear how Bayesian computations are implemented in the brain. Herein, I address this issue by analyzing a Mexican-hat-type neural network, which was used as a model of the visual cortex, motor cortex, and prefrontal cortex. I analytically demonstrate that the dynamics of an order parameter in the model corresponds exactly to a variational inference of a linear Gaussian state-space model, a Bayesian estimation, when the strength of recurrent synaptic connectivity is appropriately stronger than that of an external stimulus, a plausible condition in the brain. This exact correspondence can reveal the relationship between the parameters in the Bayesian estimation and those in the neural network, providing insight for understanding brain functions.

Gorilla and Orangutan Brains Conform to the Primate Cellular Scaling Rules: Implications for Human Evolution

PubMed Central

Herculano-Houzel, Suzana; Kaas, Jon H.

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they apply to simians, great apes and modern humans alike), the Colobinae and Pongidae lineages favored marked increases in body size rather than brain size from the common ancestor with the Homo lineage, while the Homo lineage seems to have favored a large brain instead of a large body, possibly due to the metabolic limitations to having both. PMID:21228547

Gorilla and orangutan brains conform to the primate cellular scaling rules: implications for human evolution.

PubMed

Herculano-Houzel, Suzana; Kaas, Jon H

2011-01-01

Gorillas and orangutans are primates at least as large as humans, but their brains amount to about one third of the size of the human brain. This discrepancy has been used as evidence that the human brain is about 3 times larger than it should be for a primate species of its body size. In contrast to the view that the human brain is special in its size, we have suggested that it is the great apes that might have evolved bodies that are unusually large, on the basis of our recent finding that the cellular composition of the human brain matches that expected for a primate brain of its size, making the human brain a linearly scaled-up primate brain in its number of cells. To investigate whether the brain of great apes also conforms to the primate cellular scaling rules identified previously, we determine the numbers of neuronal and other cells that compose the orangutan and gorilla cerebella, use these numbers to calculate the size of the brain and of the cerebral cortex expected for these species, and show that these match the sizes described in the literature. Our results suggest that the brains of great apes also scale linearly in their numbers of neurons like other primate brains, including humans. The conformity of great apes and humans to the linear cellular scaling rules that apply to other primates that diverged earlier in primate evolution indicates that prehistoric Homo species as well as other hominins must have had brains that conformed to the same scaling rules, irrespective of their body size. We then used those scaling rules and published estimated brain volumes for various hominin species to predict the numbers of neurons that composed their brains. We predict that Homo heidelbergensis and Homo neanderthalensis had brains with approximately 80 billion neurons, within the range of variation found in modern Homo sapiens. We propose that while the cellular scaling rules that apply to the primate brain have remained stable in hominin evolution (since they apply to simians, great apes and modern humans alike), the Colobinae and Pongidae lineages favored marked increases in body size rather than brain size from the common ancestor with the Homo lineage, while the Homo lineage seems to have favored a large brain instead of a large body, possibly due to the metabolic limitations to having both. Copyright © 2011 S. Karger AG, Basel.

Estimation of bio-signal based on human motion for integrated visualization of daily-life.

PubMed

Umetani, Tomohiro; Matsukawa, Tsuyoshi; Yokoyama, Kiyoko

2007-01-01

This paper describes a method for the estimation of bio-signals based on human motion in daily life for an integrated visualization system. The recent advancement of computers and measurement technology has facilitated the integrated visualization of bio-signals and human motion data. It is desirable to obtain a method to understand the activities of muscles based on human motion data and evaluate the change in physiological parameters according to human motion for visualization applications. We suppose that human motion is generated by the activities of muscles reflected from the brain to bio-signals such as electromyograms. This paper introduces a method for the estimation of bio-signals based on neural networks. This method can estimate the other physiological parameters based on the same procedure. The experimental results show the feasibility of the proposed method.

The Search for True Numbers of Neurons and Glial Cells in the Human Brain: A Review of 150 Years of Cell Counting

PubMed Central

von Bartheld, Christopher S.; Bahney, Jami; Herculano-Houzel, Suzana

2016-01-01

For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40–130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. PMID:27187682

The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting.

PubMed

von Bartheld, Christopher S; Bahney, Jami; Herculano-Houzel, Suzana

2016-12-15

For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40-130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. J. Comp. Neurol. 524:3865-3895, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Toward a standardized structural-functional group connectome in MNI space.

PubMed

Horn, Andreas; Blankenburg, Felix

2016-01-01

The analysis of the structural architecture of the human brain in terms of connectivity between its subregions has provided profound insights into its underlying functional organization and has coined the concept of the "connectome", a structural description of the elements forming the human brain and the connections among them. Here, as a proof of concept, we introduce a novel group connectome in standard space based on a large sample of 169 subjects from the Enhanced Nathan Kline Institute-Rockland Sample (eNKI-RS). Whole brain structural connectomes of each subject were estimated with a global tracking approach, and the resulting fiber tracts were warped into standard stereotactic (MNI) space using DARTEL. Employing this group connectome, the results of published tracking studies (i.e., the JHU white matter and Oxford thalamic connectivity atlas) could be largely reproduced directly within MNI space. In a second analysis, a study that examined structural connectivity between regions of a functional network, namely the default mode network, was reproduced. Voxel-wise structural centrality was then calculated and compared to others' findings. Furthermore, including additional resting-state fMRI data from the same subjects, structural and functional connectivity matrices between approximately forty thousand nodes of the brain were calculated. This was done to estimate structure-function agreement indices of voxel-wise whole brain connectivity. Taken together, the combination of a novel whole brain fiber tracking approach and an advanced normalization method led to a group connectome that allowed (at least heuristically) performing fiber tracking directly within MNI space. Such an approach may be used for various purposes like the analysis of structural connectivity and modeling experiments that aim at studying the structure-function relationship of the human connectome. Moreover, it may even represent a first step toward a standard DTI template of the human brain in stereotactic space. The standardized group connectome might thus be a promising new resource to better understand and further analyze the anatomical architecture of the human brain on a population level. Copyright © 2015 Elsevier Inc. All rights reserved.

Age, gender, and hemispheric differences in iron deposition in the human brain: an in vivo MRI study.

PubMed

Xu, Xiaojun; Wang, Qidong; Zhang, Minming

2008-03-01

It is well known that iron accumulates in the brains of patients with various neurodegenerative diseases. To better understand disease-related iron changes, it is necessary to know the physiological distribution and accumulation of iron in the human brain. Studies have shown that brain iron levels increase with aging. However, the effects of gender and hemispheric laterality on iron accumulation and distribution are not well established. In this study, we estimated the brain iron levels in vivo in 78 healthy adults ranging in age 22 to 78 years using magnetic susceptibility-weighted phase imaging. The effects of age, gender, and hemispheric location on brain iron levels were evaluated within the framework of a general linear model. We found that the left hemisphere had higher iron levels than the right in the putamen, globus pallidus, substantia nigra, thalamus, and frontal white matter. We argue that the hemispheric asymmetry of iron content may underlie that of the dopaminergic system and may be related to motor lateralization in humans. In addition, significant age-related iron accumulation occurred in the putamen, red nucleus, and frontal white matter, but no gender-related differences in iron levels were detected. The results of this study extend our knowledge of the physiological distribution and accumulation of iron in the human brain.

Red-backed vole brain promotes highly efficient in vitro amplification of abnormal prion protein from macaque and human brains infected with variant Creutzfeldt-Jakob disease agent.

USGS Publications Warehouse

Nemecek, Julie; Nag, Nabanita; Carlson, Christina M.; Schneider, Jay R.; Heisey, Dennis M.; Johnson, Christopher J.; Asher, David M.; Gregori, Luisa

2013-01-01

Rapid antemortem tests to detect individuals with transmissible spongiform encephalopathies (TSE) would contribute to public health. We investigated a technique known as protein misfolding cyclic amplification (PMCA) to amplify abnormal prion protein (PrPTSE) from highly diluted variant Creutzfeldt-Jakob disease (vCJD)-infected human and macaque brain homogenates, seeking to improve the rapid detection of PrPTSE in tissues and blood. Macaque vCJD PrPTSE did not amplify using normal macaque brain homogenate as substrate (intraspecies PMCA). Next, we tested interspecies PMCA with normal brain homogenate of the southern red-backed vole (RBV), a close relative of the bank vole, seeded with macaque vCJD PrPTSE. The RBV has a natural polymorphism at residue 170 of the PrP-encoding gene (N/N, S/S, and S/N). We investigated the effect of this polymorphism on amplification of human and macaque vCJD PrPTSE. Meadow vole brain (170N/N PrP genotype) was also included in the panel of substrates tested. Both humans and macaques have the same 170S/S PrP genotype. Macaque PrPTSE was best amplified with RBV 170S/S brain, although 170N/N and 170S/N were also competent substrates, while meadow vole brain was a poor substrate. In contrast, human PrPTSE demonstrated a striking narrow selectivity for PMCA substrate and was successfully amplified only with RBV 170S/S brain. These observations suggest that macaque PrPTSE was more permissive than human PrPTSE in selecting the competent RBV substrate. RBV 170S/S brain was used to assess the sensitivity of PMCA with PrPTSE from brains of humans and macaques with vCJD. PrPTSE signals were reproducibly detected by Western blot in dilutions through 10-12 of vCJD-infected 10% brain homogenates. This is the first report showing PrPTSE from vCJD-infected human and macaque brains efficiently amplified with RBV brain as the substrate. Based on our estimates, PMCA showed a sensitivity that might be sufficient to detect PrPTSE in vCJD-infected human and macaque blood.

Prediction of a Therapeutic Dose for Buagafuran, a Potent Anxiolytic Agent by Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling Starting from Pharmacokinetics in Rats and Human.

PubMed

Yang, Fen; Wang, Baolian; Liu, Zhihao; Xia, Xuejun; Wang, Weijun; Yin, Dali; Sheng, Li; Li, Yan

2017-01-01

Physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) models can contribute to animal-to-human extrapolation and therapeutic dose predictions. Buagafuran is a novel anxiolytic agent and phase I clinical trials of buagafuran have been completed. In this paper, a potentially effective dose for buagafuran of 30 mg t.i.d. in human was estimated based on the human brain concentration predicted by a PBPK/PD modeling. The software GastroPlus TM was used to build the PBPK/PD model for buagafuran in rat which related the brain tissue concentrations of buagafuran and the times of animals entering the open arms in the pharmacological model of elevated plus-maze. Buagafuran concentrations in human plasma were fitted and brain tissue concentrations were predicted by using a human PBPK model in which the predicted plasma profiles were in good agreement with observations. The results provided supportive data for the rational use of buagafuran in clinic.

Investigation of the electric field distribution in the human brain based on MRI and EEG data

NASA Astrophysics Data System (ADS)

Kistenev, Yu. V.; Borisov, A. V.; Knyazkova, A. I.; Shapovalova, A. V.; Ilyasova, E. E.; Sandykova, E. A.

2018-04-01

This work is devoted to the development of the approach to restoration of the spatial-temporal distribution of electric field in the human brain. This field was estimated from the model derived from the Maxwell's equations with boundary conditions corresponding to electric potentials at the EEG electrodes, which are located on the surface of the head according to the standard "10-20" scheme. The MRI data were used for calculation of the spatial distribution of the electrical conductivity of biotissues in the human brain. The study of the electric field distribution using our approach was carried out for the healthy child and the child with autism. The research was carried out using the equipment of the Tomsk Regional Common Use Center of Tomsk State University.

Occupancy of Norepinephrine Transporter by Duloxetine in Human Brains Measured by Positron Emission Tomography with (S,S)-[18F]FMeNER-D2.

PubMed

Moriguchi, Sho; Takano, Harumasa; Kimura, Yasuyuki; Nagashima, Tomohisa; Takahata, Keisuke; Kubota, Manabu; Kitamura, Soichiro; Ishii, Tatsuya; Ichise, Masanori; Zhang, Ming-Rong; Shimada, Hitoshi; Mimura, Masaru; Meyer, Jeffrey H; Higuchi, Makoto; Suhara, Tetsuya

2017-12-01

The norepinephrine transporter in the brain has been targeted in the treatment of psychiatric disorders. Duloxetine is a serotonin and norepinephrine reuptake inhibitor that has been widely used for the treatment of depression. However, the relationship between dose and plasma concentration of duloxetine and norepinephrine transporter occupancy in the human brain has not been determined. In this study, we examined norepinephrine transporter occupancy by different doses of duloxetine. We calculated norepinephrine transporter occupancies from 2 positron emission tomography scans using (S,S)-[18F]FMeNER-D2 before and after a single oral dose of duloxetine (20 mg, n = 3; 40 mg, n = 3; 60 mg, n =2). Positron emission tomography scans were performed from 120 to 180 minutes after an i.v. bolus injection of (S,S)-[18F]FMeNER-D2. Venous blood samples were taken to measure the plasma concentration of duloxetine just before and after the second positron emission tomography scan. Norepinephrine transporter occupancy by duloxetine was 29.7% at 20 mg, 30.5% at 40 mg, and 40.0% at 60 mg. The estimated dose of duloxetine inducing 50% norepinephrine transporter occupancy was 76.8 mg, and the estimated plasma drug concentration inducing 50% norepinephrine transporter occupancy was 58.0 ng/mL. Norepinephrine transporter occupancy by clinical doses of duloxetine was approximately 30% to 40% in human brain as estimated using positron emission tomography with (S,S)-[18F]FMeNER-D2. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Segmentation of human brain using structural MRI.

PubMed

Helms, Gunther

2016-04-01

Segmentation of human brain using structural MRI is a key step of processing in imaging neuroscience. The methods have undergone a rapid development in the past two decades and are now widely available. This non-technical review aims at providing an overview and basic understanding of the most common software. Starting with the basis of structural MRI contrast in brain and imaging protocols, the concepts of voxel-based and surface-based segmentation are discussed. Special emphasis is given to the typical contrast features and morphological constraints of cortical and sub-cortical grey matter. In addition to the use for voxel-based morphometry, basic applications in quantitative MRI, cortical thickness estimations, and atrophy measurements as well as assignment of cortical regions and deep brain nuclei are briefly discussed. Finally, some fields for clinical applications are given.

Magnetic Resonance Elastography of the Brain using Multi-Shot Spiral Readouts with Self-Navigated Motion Correction

PubMed Central

Johnson, Curtis L.; McGarry, Matthew D. J.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.; Sutton, Bradley P.; Georgiadis, John G.

2012-01-01

MRE has been introduced in clinical practice as a possible surrogate for mechanical palpation, but its application to study the human brain in vivo has been limited by low spatial resolution and the complexity of the inverse problem associated with biomechanical property estimation. Here, we report significant improvements in brain MRE data acquisition by reporting images with high spatial resolution and signal-to-noise ratio as quantified by octahedral shear strain metrics. Specifically, we have developed a sequence for brain MRE based on multi-shot, variable-density spiral imaging and three-dimensional displacement acquisition, and implemented a correction scheme for any resulting phase errors. A Rayleigh damped model of brain tissue mechanics was adopted to represent the parenchyma, and was integrated via a finite element-based iterative inversion algorithm. A multi-resolution phantom study demonstrates the need for obtaining high-resolution MRE data when estimating focal mechanical properties. Measurements on three healthy volunteers demonstrate satisfactory resolution of grey and white matter, and mechanical heterogeneities correspond well with white matter histoarchitecture. Together, these advances enable MRE scans that result in high-fidelity, spatially-resolved estimates of in vivo brain tissue mechanical properties, improving upon lower resolution MRE brain studies which only report volume averaged stiffness values. PMID:23001771

Influence of O-methylated metabolite penetrating the blood-brain barrier to estimation of dopamine synthesis capacity in human L-[β-(11)C]DOPA PET.

PubMed

Matsubara, Keisuke; Ikoma, Yoko; Okada, Maki; Ibaraki, Masanobu; Suhara, Tetsuya; Kinoshita, Toshibumi; Ito, Hiroshi

2014-02-01

O-methyl metabolite (L-[β-(11)C]OMD) of (11)C-labeled L-3,4-dihydroxyphenylalanine (L-[β-(11)C]DOPA) can penetrate into brain tissue through the blood-brain barrier, and can complicate the estimation of dopamine synthesis capacity by positron emission tomography (PET) study with L-[β-(11)C]DOPA. We evaluated the impact of L-[β-(11)C]OMD on the estimation of the dopamine synthesis capacity in a human L-[β-(11)C]DOPA PET study. The metabolite correction with mathematical modeling of L-[β-(11)C]OMD kinetics in a reference region without decarboxylation and further metabolism, proposed by a previous [(18)F]FDOPA PET study, were implemented to estimate radioactivity of tissue L-[β-(11)C]OMD in 10 normal volunteers. The component of L-[β-(11)C]OMD in tissue time-activity curves (TACs) in 10 regions were subtracted by the estimated radioactivity of L-[β-(11)C]OMD. To evaluate the influence of omitting blood sampling and metabolite correction, relative dopamine synthesis rate (kref) was estimated by Gjedde-Patlak analysis with reference tissue input function, as well as the net dopamine synthesis rate (Ki) by Gjedde-Patlak analysis with the arterial input function and TAC without and with metabolite correction. Overestimation of Ki was observed without metabolite correction. However, the kref and Ki with metabolite correction were significantly correlated. These data suggest that the influence of L-[β-(11)C]OMD is minimal for the estimation of kref as dopamine synthesis capacity.

[Fractal characteristics of the functional state of the brain in patients with anxious phobic disorders].

PubMed

Dik, O E; Sviatogor, I A; Ishinova, V A; Nozdrachev, A D

2012-01-01

The task of estimation of the functional state of the human brain during psychotherapeutic treatment of psychogenic pain in patients with anxious phobic disorders is examined. For solving the task the methods of spectral and multifractal analyses of EEG fragments are applied during the perception of psychogenic pain and its removal by the psychorelaxation technique. Contrary to power spectra singularity spectra allow to distinguish EEGs quanitatively in the examined functional states of the human brain. The pain suppression in patients with anxious phobic disorders during psychorelaxation is accompanied by changing the width of the singularity spectrum and approximation of this multifractal partameter to the value corresponding to a healthy subject.

Function-specific and Enhanced Brain Structural Connectivity Mapping via Joint Modeling of Diffusion and Functional MRI.

PubMed

Chu, Shu-Hsien; Parhi, Keshab K; Lenglet, Christophe

2018-03-16

A joint structural-functional brain network model is presented, which enables the discovery of function-specific brain circuits, and recovers structural connections that are under-estimated by diffusion MRI (dMRI). Incorporating information from functional MRI (fMRI) into diffusion MRI to estimate brain circuits is a challenging task. Usually, seed regions for tractography are selected from fMRI activation maps to extract the white matter pathways of interest. The proposed method jointly analyzes whole brain dMRI and fMRI data, allowing the estimation of complete function-specific structural networks instead of interactively investigating the connectivity of individual cortical/sub-cortical areas. Additionally, tractography techniques are prone to limitations, which can result in erroneous pathways. The proposed framework explicitly models the interactions between structural and functional connectivity measures thereby improving anatomical circuit estimation. Results on Human Connectome Project (HCP) data demonstrate the benefits of the approach by successfully identifying function-specific anatomical circuits, such as the language and resting-state networks. In contrast to correlation-based or independent component analysis (ICA) functional connectivity mapping, detailed anatomical connectivity patterns are revealed for each functional module. Results on a phantom (Fibercup) also indicate improvements in structural connectivity mapping by rejecting false-positive connections with insufficient support from fMRI, and enhancing under-estimated connectivity with strong functional correlation.

Functional Brain Networks: Does the Choice of Dependency Estimator and Binarization Method Matter?

NASA Astrophysics Data System (ADS)

Jalili, Mahdi

2016-07-01

The human brain can be modelled as a complex networked structure with brain regions as individual nodes and their anatomical/functional links as edges. Functional brain networks are constructed by first extracting weighted connectivity matrices, and then binarizing them to minimize the noise level. Different methods have been used to estimate the dependency values between the nodes and to obtain a binary network from a weighted connectivity matrix. In this work we study topological properties of EEG-based functional networks in Alzheimer’s Disease (AD). To estimate the connectivity strength between two time series, we use Pearson correlation, coherence, phase order parameter and synchronization likelihood. In order to binarize the weighted connectivity matrices, we use Minimum Spanning Tree (MST), Minimum Connected Component (MCC), uniform threshold and density-preserving methods. We find that the detected AD-related abnormalities highly depend on the methods used for dependency estimation and binarization. Topological properties of networks constructed using coherence method and MCC binarization show more significant differences between AD and healthy subjects than the other methods. These results might explain contradictory results reported in the literature for network properties specific to AD symptoms. The analysis method should be seriously taken into account in the interpretation of network-based analysis of brain signals.

Scaling of Brain Metabolism with a Fixed Energy Budget per Neuron: Implications for Neuronal Activity, Plasticity and Evolution

PubMed Central

Herculano-Houzel, Suzana

2011-01-01

It is usually considered that larger brains have larger neurons, which consume more energy individually, and are therefore accompanied by a larger number of glial cells per neuron. These notions, however, have never been tested. Based on glucose and oxygen metabolic rates in awake animals and their recently determined numbers of neurons, here I show that, contrary to the expected, the estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates (including humans). The estimated average glucose use per neuron does not correlate with neuronal density in any structure. This suggests that the energy budget of the whole brain per neuron is fixed across species and brain sizes, such that total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone are linear functions of the number of neurons in the structures across the species (although the average glucose consumption per neuron is at least 10× higher in the cerebral cortex than in the cerebellum). These results indicate that the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of body mass is explained simply by its large number of neurons. Because synaptic activity is considered the major determinant of metabolic cost, a conserved energy budget per neuron has several profound implications for synaptic homeostasis and the regulation of firing rates, synaptic plasticity, brain imaging, pathologies, and for brain scaling in evolution. PMID:21390261

Scaling of brain metabolism with a fixed energy budget per neuron: implications for neuronal activity, plasticity and evolution.

PubMed

Herculano-Houzel, Suzana

2011-03-01

It is usually considered that larger brains have larger neurons, which consume more energy individually, and are therefore accompanied by a larger number of glial cells per neuron. These notions, however, have never been tested. Based on glucose and oxygen metabolic rates in awake animals and their recently determined numbers of neurons, here I show that, contrary to the expected, the estimated glucose use per neuron is remarkably constant, varying only by 40% across the six species of rodents and primates (including humans). The estimated average glucose use per neuron does not correlate with neuronal density in any structure. This suggests that the energy budget of the whole brain per neuron is fixed across species and brain sizes, such that total glucose use by the brain as a whole, by the cerebral cortex and also by the cerebellum alone are linear functions of the number of neurons in the structures across the species (although the average glucose consumption per neuron is at least 10× higher in the cerebral cortex than in the cerebellum). These results indicate that the apparently remarkable use in humans of 20% of the whole body energy budget by a brain that represents only 2% of body mass is explained simply by its large number of neurons. Because synaptic activity is considered the major determinant of metabolic cost, a conserved energy budget per neuron has several profound implications for synaptic homeostasis and the regulation of firing rates, synaptic plasticity, brain imaging, pathologies, and for brain scaling in evolution.

Transcranial magnetic stimulation of mouse brain using high-resolution anatomical models

NASA Astrophysics Data System (ADS)

Crowther, L. J.; Hadimani, R. L.; Kanthasamy, A. G.; Jiles, D. C.

2014-05-01

Transcranial magnetic stimulation (TMS) offers the possibility of non-invasive treatment of brain disorders in humans. Studies on animals can allow rapid progress of the research including exploring a variety of different treatment conditions. Numerical calculations using animal models are needed to help design suitable TMS coils for use in animal experiments, in particular, to estimate the electric field induced in animal brains. In this paper, we have implemented a high-resolution anatomical MRI-derived mouse model consisting of 50 tissue types to accurately calculate induced electric field in the mouse brain. Magnetic field measurements have been performed on the surface of the coil and compared with the calculations in order to validate the calculated magnetic and induced electric fields in the brain. Results show how the induced electric field is distributed in a mouse brain and allow investigation of how this could be improved for TMS studies using mice. The findings have important implications in further preclinical development of TMS for treatment of human diseases.

Brain temperature changes during selective cooling with endovascular intracarotid cold saline infusion: simulation using human data fitted with an integrated mathematical model.

PubMed

Neimark, Matthew Aaron Harold; Konstas, Angelos Aristeidis; Lee, Leslie; Laine, Andrew Francis; Pile-Spellman, John; Choi, Jae

2013-03-01

The feasibility of rapid cerebral hypothermia induction in humans with intracarotid cold saline infusion (ICSI) was investigated using a hybrid approach of jugular venous bulb temperature (JVBT) sampling and mathematical modeling of transient and steady state brain temperature distribution. This study utilized both forward mathematical modeling, in which brain temperatures were predicted based on input saline temperatures, and inverse modeling, where brain temperatures were inferred based on JVBT. Changes in ipsilateral anterior circulation territory temperature (IACT) were estimated in eight patients as a result of 10 min of a cold saline infusion of 33 ml/min. During ICSI, the measured JVBT dropped by 0.76±0.18°C while the modeled JVBT decreased by 0.86±0.18°C. The modeled IACT decreased by 2.1±0.23°C. In the inverse model, IACT decreased by 1.9±0.23°C. The results of this study suggest that mild cerebral hypothermia can be induced rapidly and safely with ICSI in the neuroangiographical setting. The JVBT corrected mathematical model can be used as a non-invasive estimate of transient and steady state cerebral temperature changes.

Improved estimates of partial volume coefficients from noisy brain MRI using spatial context.

PubMed

Manjón, José V; Tohka, Jussi; Robles, Montserrat

2010-11-01

This paper addresses the problem of accurate voxel-level estimation of tissue proportions in the human brain magnetic resonance imaging (MRI). Due to the finite resolution of acquisition systems, MRI voxels can contain contributions from more than a single tissue type. The voxel-level estimation of this fractional content is known as partial volume coefficient estimation. In the present work, two new methods to calculate the partial volume coefficients under noisy conditions are introduced and compared with current similar methods. Concretely, a novel Markov Random Field model allowing sharp transitions between partial volume coefficients of neighbouring voxels and an advanced non-local means filtering technique are proposed to reduce the errors due to random noise in the partial volume coefficient estimation. In addition, a comparison was made to find out how the different methodologies affect the measurement of the brain tissue type volumes. Based on the obtained results, the main conclusions are that (1) both Markov Random Field modelling and non-local means filtering improved the partial volume coefficient estimation results, and (2) non-local means filtering was the better of the two strategies for partial volume coefficient estimation. Copyright 2010 Elsevier Inc. All rights reserved.

Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex.

PubMed

Guadalupe, Tulio; Mathias, Samuel R; vanErp, Theo G M; Whelan, Christopher D; Zwiers, Marcel P; Abe, Yoshinari; Abramovic, Lucija; Agartz, Ingrid; Andreassen, Ole A; Arias-Vásquez, Alejandro; Aribisala, Benjamin S; Armstrong, Nicola J; Arolt, Volker; Artiges, Eric; Ayesa-Arriola, Rosa; Baboyan, Vatche G; Banaschewski, Tobias; Barker, Gareth; Bastin, Mark E; Baune, Bernhard T; Blangero, John; Bokde, Arun L W; Boedhoe, Premika S W; Bose, Anushree; Brem, Silvia; Brodaty, Henry; Bromberg, Uli; Brooks, Samantha; Büchel, Christian; Buitelaar, Jan; Calhoun, Vince D; Cannon, Dara M; Cattrell, Anna; Cheng, Yuqi; Conrod, Patricia J; Conzelmann, Annette; Corvin, Aiden; Crespo-Facorro, Benedicto; Crivello, Fabrice; Dannlowski, Udo; de Zubicaray, Greig I; de Zwarte, Sonja M C; Deary, Ian J; Desrivières, Sylvane; Doan, Nhat Trung; Donohoe, Gary; Dørum, Erlend S; Ehrlich, Stefan; Espeseth, Thomas; Fernández, Guillén; Flor, Herta; Fouche, Jean-Paul; Frouin, Vincent; Fukunaga, Masaki; Gallinat, Jürgen; Garavan, Hugh; Gill, Michael; Suarez, Andrea Gonzalez; Gowland, Penny; Grabe, Hans J; Grotegerd, Dominik; Gruber, Oliver; Hagenaars, Saskia; Hashimoto, Ryota; Hauser, Tobias U; Heinz, Andreas; Hibar, Derrek P; Hoekstra, Pieter J; Hoogman, Martine; Howells, Fleur M; Hu, Hao; Hulshoff Pol, Hilleke E; Huyser, Chaim; Ittermann, Bernd; Jahanshad, Neda; Jönsson, Erik G; Jurk, Sarah; Kahn, Rene S; Kelly, Sinead; Kraemer, Bernd; Kugel, Harald; Kwon, Jun Soo; Lemaitre, Herve; Lesch, Klaus-Peter; Lochner, Christine; Luciano, Michelle; Marquand, Andre F; Martin, Nicholas G; Martínez-Zalacaín, Ignacio; Martinot, Jean-Luc; Mataix-Cols, David; Mather, Karen; McDonald, Colm; McMahon, Katie L; Medland, Sarah E; Menchón, José M; Morris, Derek W; Mothersill, Omar; Maniega, Susana Munoz; Mwangi, Benson; Nakamae, Takashi; Nakao, Tomohiro; Narayanaswaamy, Janardhanan C; Nees, Frauke; Nordvik, Jan E; Onnink, A Marten H; Opel, Nils; Ophoff, Roel; Paillère Martinot, Marie-Laure; Papadopoulos Orfanos, Dimitri; Pauli, Paul; Paus, Tomáš; Poustka, Luise; Reddy, Janardhan Yc; Renteria, Miguel E; Roiz-Santiáñez, Roberto; Roos, Annerine; Royle, Natalie A; Sachdev, Perminder; Sánchez-Juan, Pascual; Schmaal, Lianne; Schumann, Gunter; Shumskaya, Elena; Smolka, Michael N; Soares, Jair C; Soriano-Mas, Carles; Stein, Dan J; Strike, Lachlan T; Toro, Roberto; Turner, Jessica A; Tzourio-Mazoyer, Nathalie; Uhlmann, Anne; Hernández, Maria Valdés; van den Heuvel, Odile A; van der Meer, Dennis; van Haren, Neeltje E M; Veltman, Dick J; Venkatasubramanian, Ganesan; Vetter, Nora C; Vuletic, Daniella; Walitza, Susanne; Walter, Henrik; Walton, Esther; Wang, Zhen; Wardlaw, Joanna; Wen, Wei; Westlye, Lars T; Whelan, Robert; Wittfeld, Katharina; Wolfers, Thomas; Wright, Margaret J; Xu, Jian; Xu, Xiufeng; Yun, Je-Yeon; Zhao, JingJing; Franke, Barbara; Thompson, Paul M; Glahn, David C; Mazoyer, Bernard; Fisher, Simon E; Francks, Clyde

2017-10-01

The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.

Brain-computer interface on the basis of EEG system Encephalan

NASA Astrophysics Data System (ADS)

Maksimenko, Vladimir; Badarin, Artem; Nedaivozov, Vladimir; Kirsanov, Daniil; Hramov, Alexander

2018-04-01

We have proposed brain-computer interface (BCI) for the estimation of the brain response on the presented visual tasks. Proposed BCI is based on the EEG recorder Encephalan-EEGR-19/26 (Medicom MTD, Russia) supplemented by a special home-made developed acquisition software. BCI is tested during experimental session while subject is perceiving the bistable visual stimuli and classifying them according to the interpretation. We have subjected the participant to the different external conditions and observed the significant decrease in the response, associated with the perceiving the bistable visual stimuli, during the presence of distraction. Based on the obtained results we have proposed possibility to use of BCI for estimation of the human alertness during solving the tasks required substantial visual attention.

A Dense Poly(ethylene glycol) Coating Improves Penetration of Large Polymeric Nanoparticles within Brain Tissue

PubMed Central

Nance, Elizabeth A.; Woodworth, Graeme F.; Sailor, Kurt A.; Shih, Ting-Yu; Xu, Qingguo; Swaminathan, Ganesh; Xiang, Dennis; Eberhart, Charles; Hanes, Justin

2013-01-01

Prevailing opinion suggests that only substances up to 64 nm in diameter can move at appreciable rates through the brain extracellular space (ECS). This size range is large enough to allow diffusion of signaling molecules, nutrients, and metabolic waste products, but too small to allow efficient penetration of most particulate drug delivery systems and viruses carrying therapeutic genes, thereby limiting effectiveness of many potential therapies. We analyzed the movements of nanoparticles of various diameters and surface coatings within fresh human and rat brain tissue ex vivo and mouse brain in vivo. Nanoparticles as large as 114-nm in diameter diffused within the human and rat brain, but only if they were densely coated with poly(ethylene glycol) (PEG). Using these minimally adhesive PEG-coated particles, we estimated that human brain tissue ECS has some pores larger than 200 nm, and that more than one-quarter of all pores are ≥100 nm. These findings were confirmed in vivo in mice, where 40- and 100-nm, but not 200-nm, nanoparticles, spread rapidly within brain tissue, only if densely coated with PEG. Similar results were observed in rat brain tissue with paclitaxel-loaded biodegradable nanoparticles of similar size (85 nm) and surface properties. The ability to achieve brain penetration with larger nanoparticles is expected to allow more uniform, longer-lasting, and effective delivery of drugs within the brain, and may find use in the treatment of brain tumors, stroke, neuroinflammation, and other brain diseases where the blood-brain barrier is compromised or where local delivery strategies are feasible. PMID:22932224

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain

PubMed Central

Krienen, Fenna M.; Yeo, B. T. Thomas; Ge, Tian; Buckner, Randy L.; Sherwood, Chet C.

2016-01-01

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute’s human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections. PMID:26739559

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain.

PubMed

Krienen, Fenna M; Yeo, B T Thomas; Ge, Tian; Buckner, Randy L; Sherwood, Chet C

2016-01-26

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute's human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor.

PubMed

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor

PubMed Central

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application. PMID:27445783

Improved Determination of the Myelin Water Fraction in Human Brain using Magnetic Resonance Imaging through Bayesian Analysis of mcDESPOT

PubMed Central

Bouhrara, Mustapha; Spencer, Richard G.

2015-01-01

Myelin water fraction (MWF) mapping with magnetic resonance imaging has led to the ability to directly observe myelination and demyelination in both the developing brain and in disease. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) has been proposed as a rapid approach for multicomponent relaxometry and has been applied to map MWF in human brain. However, even for the simplest two-pool signal model consisting of MWF and non-myelin-associated water, the dimensionality of the parameter space for obtaining MWF estimates remains high. This renders parameter estimation difficult, especially at low-to-moderate signal-to-noise ratios (SNR), due to the presence of local minima and the flatness of the fit residual energy surface used for parameter determination using conventional nonlinear least squares (NLLS)-based algorithms. In this study, we introduce three Bayesian approaches for analysis of the mcDESPOT signal model to determine MWF. Given the high dimensional nature of mcDESPOT signal model, and, thereby, the high dimensional marginalizations over nuisance parameters needed to derive the posterior probability distribution of MWF parameter, the introduced Bayesian analyses use different approaches to reduce the dimensionality of the parameter space. The first approach uses normalization by average signal amplitude, and assumes that noise can be accurately estimated from signal-free regions of the image. The second approach likewise uses average amplitude normalization, but incorporates a full treatment of noise as an unknown variable through marginalization. The third approach does not use amplitude normalization and incorporates marginalization over both noise and signal amplitude. Through extensive Monte Carlo numerical simulations and analysis of in-vivo human brain datasets exhibiting a range of SNR and spatial resolution, we demonstrated the markedly improved accuracy and precision in the estimation of MWF using these Bayesian methods as compared to the stochastic region contraction (SRC) implementation of NLLS. PMID:26499810

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

NASA Astrophysics Data System (ADS)

O'Neill, George C.; Barratt, Eleanor L.; Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Brookes, Matthew J.

2015-11-01

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5 mm) spatial resolution and excellent (~1 ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including (i) projection of MEG data into source space, (ii) removing confounds introduced by the MEG inverse problem and (iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease.

New insights into differences in brain organization between Neanderthals and anatomically modern humans

PubMed Central

Pearce, Eiluned; Stringer, Chris; Dunbar, R. I. M.

2013-01-01

Previous research has identified morphological differences between the brains of Neanderthals and anatomically modern humans (AMHs). However, studies using endocasts or the cranium itself are limited to investigating external surface features and the overall size and shape of the brain. A complementary approach uses comparative primate data to estimate the size of internal brain areas. Previous attempts to do this have generally assumed that identical total brain volumes imply identical internal organization. Here, we argue that, in the case of Neanderthals and AMHs, differences in the size of the body and visual system imply differences in organization between the same-sized brains of these two taxa. We show that Neanderthals had significantly larger visual systems than contemporary AMHs (indexed by orbital volume) and that when this, along with their greater body mass, is taken into account, Neanderthals have significantly smaller adjusted endocranial capacities than contemporary AMHs. We discuss possible implications of differing brain organization in terms of social cognition, and consider these in the context of differing abilities to cope with fluctuating resources and cultural maintenance. PMID:23486442

Physiological neuronal decline in healthy aging human brain - An in vivo study with MRI and short echo-time whole-brain (1)H MR spectroscopic imaging.

PubMed

Ding, Xiao-Qi; Maudsley, Andrew A; Sabati, Mohammad; Sheriff, Sulaiman; Schmitz, Birte; Schütze, Martin; Bronzlik, Paul; Kahl, Kai G; Lanfermann, Heinrich

2016-08-15

Knowledge of physiological aging in healthy human brain is increasingly important for neuroscientific research and clinical diagnosis. To investigate neuronal decline in normal aging brain eighty-one healthy subjects aged between 20 and 70years were studied with MRI and whole-brain (1)H MR spectroscopic imaging. Concentrations of brain metabolites N-acetyl-aspartate (NAA), choline (Cho), total creatine (tCr), myo-inositol (mI), and glutamine+glutamate (Glx) in ratios to internal water, and the fractional volumes of brain tissue were estimated simultaneously in eight cerebral lobes and in cerebellum. Results demonstrated that an age-related decrease in gray matter volume was the largest contribution to changes in brain volume. Both lobar NAA and the fractional volume of gray matter (FVGM) decreased with age in all cerebral lobes, indicating that the decreased NAA was predominantly associated with decreased gray matter volume and neuronal density or metabolic activity. In cerebral white matter Cho, tCr, and mI increased with age in association with increased fractional volume, showing altered cellular membrane turn-over, energy metabolism, and glial activity in human aging white matter. In cerebellum tCr increased while brain tissue volume decreased with age, showing difference to cerebral aging. The observed age-related metabolic and microstructural variations suggest that physiological neuronal decline in aging human brain is associated with a reduction of gray matter volume and neuronal density, in combination with cellular aging in white matter indicated by microstructural alterations and altered energy metabolism in the cerebellum. Copyright © 2016 Elsevier Inc. All rights reserved.

Evaluation method for in situ electric field in standardized human brain for different transcranial magnetic stimulation coils

NASA Astrophysics Data System (ADS)

Iwahashi, Masahiro; Gomez-Tames, Jose; Laakso, Ilkka; Hirata, Akimasa

2017-03-01

This study proposes a method to evaluate the electric field induced in the brain by transcranial magnetic stimulation (TMS) to realize focal stimulation in the target area considering the inter-subject difference of the brain anatomy. The TMS is a non-invasive technique used for treatment/diagnosis, and it works by inducing an electric field in a specific area of the brain via a coil-induced magnetic field. Recent studies that report on the electric field distribution in the brain induced by TMS coils have been limited to simplified human brain models or a small number of detailed human brain models. Until now, no method has been developed that appropriately evaluates the coil performance for a group of subjects. In this study, we first compare the magnetic field and the magnetic vector potential distributions to determine if they can be used as predictors of the TMS focality derived from the electric field distribution. Next, the hotspots of the electric field on the brain surface of ten subjects using six coils are compared. Further, decisive physical factors affecting the focality of the induced electric field by different coils are discussed by registering the computed electric field in a standard brain space for the first time, so as to evaluate coil characteristics for a large population of subjects. The computational results suggest that the induced electric field in the target area cannot be generalized without considering the morphological variability of the human brain. Moreover, there was no remarkable difference between the various coils, although focality could be improved to a certain extent by modifying the coil design (e.g., coil radius). Finally, the focality estimated by the electric field was more correlated with the magnetic vector potential than the magnetic field in a homogeneous sphere.

Evaluation method for in situ electric field in standardized human brain for different transcranial magnetic stimulation coils.

PubMed

Iwahashi, Masahiro; Gomez-Tames, Jose; Laakso, Ilkka; Hirata, Akimasa

2017-03-21

This study proposes a method to evaluate the electric field induced in the brain by transcranial magnetic stimulation (TMS) to realize focal stimulation in the target area considering the inter-subject difference of the brain anatomy. The TMS is a non-invasive technique used for treatment/diagnosis, and it works by inducing an electric field in a specific area of the brain via a coil-induced magnetic field. Recent studies that report on the electric field distribution in the brain induced by TMS coils have been limited to simplified human brain models or a small number of detailed human brain models. Until now, no method has been developed that appropriately evaluates the coil performance for a group of subjects. In this study, we first compare the magnetic field and the magnetic vector potential distributions to determine if they can be used as predictors of the TMS focality derived from the electric field distribution. Next, the hotspots of the electric field on the brain surface of ten subjects using six coils are compared. Further, decisive physical factors affecting the focality of the induced electric field by different coils are discussed by registering the computed electric field in a standard brain space for the first time, so as to evaluate coil characteristics for a large population of subjects. The computational results suggest that the induced electric field in the target area cannot be generalized without considering the morphological variability of the human brain. Moreover, there was no remarkable difference between the various coils, although focality could be improved to a certain extent by modifying the coil design (e.g., coil radius). Finally, the focality estimated by the electric field was more correlated with the magnetic vector potential than the magnetic field in a homogeneous sphere.

Human Exploration of Enclosed Spaces through Echolocation.

PubMed

Flanagin, Virginia L; Schörnich, Sven; Schranner, Michael; Hummel, Nadine; Wallmeier, Ludwig; Wahlberg, Magnus; Stephan, Thomas; Wiegrebe, Lutz

2017-02-08

Some blind humans have developed echolocation, as a method of navigation in space. Echolocation is a truly active sense because subjects analyze echoes of dedicated, self-generated sounds to assess space around them. Using a special virtual space technique, we assess how humans perceive enclosed spaces through echolocation, thereby revealing the interplay between sensory and vocal-motor neural activity while humans perform this task. Sighted subjects were trained to detect small changes in virtual-room size analyzing real-time generated echoes of their vocalizations. Individual differences in performance were related to the type and number of vocalizations produced. We then asked subjects to estimate virtual-room size with either active or passive sounds while measuring their brain activity with fMRI. Subjects were better at estimating room size when actively vocalizing. This was reflected in the hemodynamic activity of vocal-motor cortices, even after individual motor and sensory components were removed. Activity in these areas also varied with perceived room size, although the vocal-motor output was unchanged. In addition, thalamic and auditory-midbrain activity was correlated with perceived room size; a likely result of top-down auditory pathways for human echolocation, comparable with those described in echolocating bats. Our data provide evidence that human echolocation is supported by active sensing, both behaviorally and in terms of brain activity. The neural sensory-motor coupling complements the fundamental acoustic motor-sensory coupling via the environment in echolocation. SIGNIFICANCE STATEMENT Passive listening is the predominant method for examining brain activity during echolocation, the auditory analysis of self-generated sounds. We show that sighted humans perform better when they actively vocalize than during passive listening. Correspondingly, vocal motor and cerebellar activity is greater during active echolocation than vocalization alone. Motor and subcortical auditory brain activity covaries with the auditory percept, although motor output is unchanged. Our results reveal behaviorally relevant neural sensory-motor coupling during echolocation. Copyright © 2017 the authors 0270-6474/17/371614-14$15.00/0.

A neonatal perspective on Homo erectus brain growth.

PubMed

Cofran, Zachary; DeSilva, Jeremy M

2015-04-01

The Mojokerto calvaria has been central to assessment of brain growth in Homo erectus, but different analytical approaches and uncertainty in the specimen's age at death have hindered consensus on the nature of H. erectus brain growth. We simulate average annual rates (AR) of absolute endocranial volume (ECV) growth and proportional size change (PSC) in H. erectus, utilizing estimates of H. erectus neonatal ECV and a range of ages for Mojokerto. These values are compared with resampled ARs and PSCs from ontogenetic series of humans, chimpanzees, and gorillas from birth to six years. Results are consistent with other studies of ECV growth in extant taxa. There is extensive overlap in PSC between all living species through the first postnatal year, with continued but lesser overlap between humans and chimpanzees to age six. Human ARs are elevated above those of apes, although there is modest overlap up to 0.50 years. Ape ARs overlap throughout the sequence, with gorillas slightly elevated over chimpanzees up to 0.50 years. Simulated H. erectus PSCs can be found in all living species by 0.50 years, and the median falls below the human and chimpanzee ranges after 2.5 years. H. erectus ARs are elevated above those of all extant taxa prior to 0.50 years, and after two years they fall out of the human range but are still above ape ranges. A review of evidence for the age at death of Mojokerto supports an estimate of around one year, indicating absolute brain growth rates in the lower half of the human range. These results point to secondary altriciality in H. erectus, implying that key human adaptations for increasing the energy budget of females may have been established by at least 1 Ma. Copyright © 2015 Elsevier Ltd. All rights reserved.

From Complex B1 Mapping to Local SAR Estimation for Human Brain MR Imaging Using Multi-channel Transceiver Coil at 7T

PubMed Central

Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortel, Pierre-François; Liu, Jiaen

2014-01-01

Elevated Specific Absorption Rate (SAR) associated with increased main magnetic field strength remains as a major safety concern in ultra-high-field (UHF) Magnetic Resonance Imaging (MRI) applications. The calculation of local SAR requires the knowledge of the electric field induced by radiofrequency (RF) excitation, and the local electrical properties of tissues. Since electric field distribution cannot be directly mapped in conventional MR measurements, SAR estimation is usually performed using numerical model-based electromagnetic simulations which, however, are highly time consuming and cannot account for the specific anatomy and tissue properties of the subject undergoing a scan. In the present study, starting from the measurable RF magnetic fields (B1) in MRI, we conducted a series of mathematical deduction to estimate the local, voxel-wise and subject-specific SAR for each single coil element using a multi-channel transceiver array coil. We first evaluated the feasibility of this approach in numerical simulations including two different human head models. We further conducted experimental study in a physical phantom and in two human subjects at 7T using a multi-channel transceiver head coil. Accuracy of the results is discussed in the context of predicting local SAR in the human brain at UHF MRI using multi-channel RF transmission. PMID:23508259

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies

NASA Astrophysics Data System (ADS)

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-01

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

The estimation of 3D SAR distributions in the human head from mobile phone compliance testing data for epidemiological studies.

PubMed

Wake, Kanako; Varsier, Nadège; Watanabe, Soichi; Taki, Masao; Wiart, Joe; Mann, Simon; Deltour, Isabelle; Cardis, Elisabeth

2009-10-07

A worldwide epidemiological study called 'INTERPHONE' has been conducted to estimate the hypothetical relationship between brain tumors and mobile phone use. In this study, we proposed a method to estimate 3D distribution of the specific absorption rate (SAR) in the human head due to mobile phone use to provide the exposure gradient for epidemiological studies. 3D SAR distributions due to exposure to an electromagnetic field from mobile phones are estimated from mobile phone compliance testing data for actual devices. The data for compliance testing are measured only on the surface in the region near the device and in a small 3D region around the maximum on the surface in a homogeneous phantom with a specific shape. The method includes an interpolation/extrapolation and a head shape conversion. With the interpolation/extrapolation, SAR distributions in the whole head are estimated from the limited measured data. 3D SAR distributions in the numerical head models, where the tumor location is identified in the epidemiological studies, are obtained from measured SAR data with the head shape conversion by projection. Validation of the proposed method was performed experimentally and numerically. It was confirmed that the proposed method provided good estimation of 3D SAR distribution in the head, especially in the brain, which is the tissue of major interest in epidemiological studies. We conclude that it is possible to estimate 3D SAR distributions in a realistic head model from the data obtained by compliance testing measurements to provide a measure for the exposure gradient in specific locations of the brain for the purpose of exposure assessment in epidemiological studies. The proposed method has been used in several studies in the INTERPHONE.

The evolution of the complex sensory and motor systems of the human brain.

PubMed

Kaas, Jon H

2008-03-18

Inferences about how the complex sensory and motor systems of the human brain evolved are based on the results of comparative studies of brain organization across a range of mammalian species, and evidence from the endocasts of fossil skulls of key extinct species. The endocasts of the skulls of early mammals indicate that they had small brains with little neocortex. Evidence from comparative studies of cortical organization from small-brained mammals of the six major branches of mammalian evolution supports the conclusion that the small neocortex of early mammals was divided into roughly 20-25 cortical areas, including primary and secondary sensory fields. In early primates, vision was the dominant sense, and cortical areas associated with vision in temporal and occipital cortex underwent a significant expansion. Comparative studies indicate that early primates had 10 or more visual areas, and somatosensory areas with expanded representations of the forepaw. Posterior parietal cortex was also expanded, with a caudal half dominated by visual inputs, and a rostral half dominated by somatosensory inputs with outputs to an array of seven or more motor and visuomotor areas of the frontal lobe. Somatosensory areas and posterior parietal cortex became further differentiated in early anthropoid primates. As larger brains evolved in early apes and in our hominin ancestors, the number of cortical areas increased to reach an estimated 200 or so in present day humans, and hemispheric specializations emerged. The large human brain grew primarily by increasing neuron number rather than increasing average neuron size.

[Concentration of glutathione (GSH), ascorbic acid (vitamin C) and substances reacting with thiobarbituric acid (TBA-rs) in single human brain metastases].

PubMed

Dudek, Henryk; Farbiszewski, Ryszard; Rydzewska, Maria; Michno, Tadeusz; Kozłowski, Andrzej

2005-01-01

The aim of the study was to estimate the concentration of glutathione (GSH), ascorbic acid (vitamin C) and thiobarbituric acid (TBA-rs) in single human brain metastases and histologically unchanged nerve tissue. The research was conducted on fragments of neoplasmatic tissue collected from 45 patients undergoing surgery in the Department of Neurosurgery, Medical University of Białystok in years 1996-2002. Concentration of GSH was evaluated using the GSH-400 method, vitamin C using the method of Kyaw and TBA-rs using the method of Salaris and Babs. It has been found that there is a decrease of concentration of GSH and vitamin C and a considerable increase (p < 0.05) of concentration of TBA-rs in investigated single brain human metastasis in correlation to the concentration of the mentioned above substances in unchanged nerve tissue.

INVESTIGATING DIFFERENCES IN BRAIN FUNCTIONAL NETWORKS USING HIERARCHICAL COVARIATE-ADJUSTED INDEPENDENT COMPONENT ANALYSIS.

PubMed

Shi, Ran; Guo, Ying

2016-12-01

Human brains perform tasks via complex functional networks consisting of separated brain regions. A popular approach to characterize brain functional networks in fMRI studies is independent component analysis (ICA), which is a powerful method to reconstruct latent source signals from their linear mixtures. In many fMRI studies, an important goal is to investigate how brain functional networks change according to specific clinical and demographic variabilities. Existing ICA methods, however, cannot directly incorporate covariate effects in ICA decomposition. Heuristic post-ICA analysis to address this need can be inaccurate and inefficient. In this paper, we propose a hierarchical covariate-adjusted ICA (hc-ICA) model that provides a formal statistical framework for estimating covariate effects and testing differences between brain functional networks. Our method provides a more reliable and powerful statistical tool for evaluating group differences in brain functional networks while appropriately controlling for potential confounding factors. We present an analytically tractable EM algorithm to obtain maximum likelihood estimates of our model. We also develop a subspace-based approximate EM that runs significantly faster while retaining high accuracy. To test the differences in functional networks, we introduce a voxel-wise approximate inference procedure which eliminates the need of computationally expensive covariance matrix estimation and inversion. We demonstrate the advantages of our methods over the existing method via simulation studies. We apply our method to an fMRI study to investigate differences in brain functional networks associated with post-traumatic stress disorder (PTSD).

Towards real-time diffuse optical tomography for imaging brain functions cooperated with Kalman estimator

NASA Astrophysics Data System (ADS)

Wang, Bingyuan; Zhang, Yao; Liu, Dongyuan; Ding, Xuemei; Dan, Mai; Pan, Tiantian; Wang, Yihan; Li, Jiao; Zhou, Zhongxing; Zhang, Limin; Zhao, Huijuan; Gao, Feng

2018-02-01

Functional near-infrared spectroscopy (fNIRS) is a non-invasive neuroimaging method to monitor the cerebral hemodynamic through the optical changes measured at the scalp surface. It has played a more and more important role in psychology and medical imaging communities. Real-time imaging of brain function using NIRS makes it possible to explore some sophisticated human brain functions unexplored before. Kalman estimator has been frequently used in combination with modified Beer-Lamber Law (MBLL) based optical topology (OT), for real-time brain function imaging. However, the spatial resolution of the OT is low, hampering the application of OT in exploring some complicated brain functions. In this paper, we develop a real-time imaging method combining diffuse optical tomography (DOT) and Kalman estimator, much improving the spatial resolution. Instead of only presenting one spatially distributed image indicating the changes of the absorption coefficients at each time point during the recording process, one real-time updated image using the Kalman estimator is provided. Its each voxel represents the amplitude of the hemodynamic response function (HRF) associated with this voxel. We evaluate this method using some simulation experiments, demonstrating that this method can obtain more reliable spatial resolution images. Furthermore, a statistical analysis is also conducted to help to decide whether a voxel in the field of view is activated or not.

Functional Specialization in the Human Brain Estimated By Intrinsic Hemispheric Interaction

PubMed Central

Wang, Danhong; Buckner, Randy L.

2014-01-01

The human brain demonstrates functional specialization, including strong hemispheric asymmetries. Here specialization was explored using fMRI by examining the degree to which brain networks preferentially interact with ipsilateral as opposed to contralateral networks. Preferential within-hemisphere interaction was prominent in the heteromodal association cortices and minimal in the sensorimotor cortices. The frontoparietal control network exhibited strong within-hemisphere interactions but with distinct patterns in each hemisphere. The frontoparietal control network preferentially coupled to the default network and language-related regions in the left hemisphere but to attention networks in the right hemisphere. This arrangement may facilitate control of processing functions that are lateralized. Moreover, the regions most linked to asymmetric specialization also display the highest degree of evolutionary cortical expansion. Functional specialization that emphasizes processing within a hemisphere may allow the expanded hominin brain to minimize between-hemisphere connectivity and distribute domain-specific processing functions. PMID:25209275

Human induced rotation and reorganization of the brain of domestic dogs.

PubMed

Roberts, Taryn; McGreevy, Paul; Valenzuela, Michael

2010-07-26

Domestic dogs exhibit an extraordinary degree of morphological diversity. Such breed-to-breed variability applies equally to the canine skull, however little is known about whether this translates to systematic differences in cerebral organization. By looking at the paramedian sagittal magnetic resonance image slice of canine brains across a range of animals with different skull shapes (N = 13), we found that the relative reduction in skull length compared to width (measured by Cephalic Index) was significantly correlated to a progressive ventral pitching of the primary longitudinal brain axis (r = 0.83), as well as with a ventral shift in the position of the olfactory lobe (r = 0.81). Furthermore, these findings were independent of estimated brain size or body weight. Since brachycephaly has arisen from generations of highly selective breeding, this study suggests that the remarkable diversity in domesticated dogs' body shape and size appears to also have led to human-induced adaptations in the organization of the canine brain.

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks

PubMed Central

Colon-Perez, Luis M.; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R.; Price, Catherine; Mareci, Thomas H.

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime. PMID:26173147

Dimensionless, Scale Invariant, Edge Weight Metric for the Study of Complex Structural Networks.

PubMed

Colon-Perez, Luis M; Spindler, Caitlin; Goicochea, Shelby; Triplett, William; Parekh, Mansi; Montie, Eric; Carney, Paul R; Price, Catherine; Mareci, Thomas H

2015-01-01

High spatial and angular resolution diffusion weighted imaging (DWI) with network analysis provides a unique framework for the study of brain structure in vivo. DWI-derived brain connectivity patterns are best characterized with graph theory using an edge weight to quantify the strength of white matter connections between gray matter nodes. Here a dimensionless, scale-invariant edge weight is introduced to measure node connectivity. This edge weight metric provides reasonable and consistent values over any size scale (e.g. rodents to humans) used to quantify the strength of connection. Firstly, simulations were used to assess the effects of tractography seed point density and random errors in the estimated fiber orientations; with sufficient signal-to-noise ratio (SNR), edge weight estimates improve as the seed density increases. Secondly to evaluate the application of the edge weight in the human brain, ten repeated measures of DWI in the same healthy human subject were analyzed. Mean edge weight values within the cingulum and corpus callosum were consistent and showed low variability. Thirdly, using excised rat brains to study the effects of spatial resolution, the weight of edges connecting major structures in the temporal lobe were used to characterize connectivity in this local network. The results indicate that with adequate resolution and SNR, connections between network nodes are characterized well by this edge weight metric. Therefore this new dimensionless, scale-invariant edge weight metric provides a robust measure of network connectivity that can be applied in any size regime.

In vivo correlation between axon diameter and conduction velocity in the human brain.

PubMed

Horowitz, Assaf; Barazany, Daniel; Tavor, Ido; Bernstein, Moran; Yovel, Galit; Assaf, Yaniv

2015-01-01

The understanding of the relationship between structure and function has always characterized biology in general and neurobiology in particular. One such fundamental relationship is that between axon diameter and the axon's conduction velocity (ACV). Measurement of these neuronal properties, however, requires invasive procedures that preclude direct elucidation of this relationship in vivo. Here we demonstrate that diffusion-based MRI is sensitive to the fine microstructural elements of brain wiring and can be used to quantify axon diameter in vivo. Moreover, we demonstrate the in vivo correlation between the diameter of an axon and its conduction velocity in the human brain. Using AxCaliber, a novel magnetic resonance imaging technique that enables us to estimate in vivo axon diameter distribution (ADD) and by measuring the interhemispheric transfer time (IHTT) by electroencephalography, we found significant linear correlation, across a cohort of subjects, between brain microstructure morphology (ADD) and its physiology (ACV) in the tactile and visual sensory domains. The ability to make a quantitative assessment of a fundamental physiological property in the human brain from in vivo measurements of ADD may shed new light on neurological processes occurring in neuroplasticity as well as in neurological disorders and neurodegenerative diseases.

Linking neuronal brain activity to the glucose metabolism.

PubMed

Göbel, Britta; Oltmanns, Kerstin M; Chung, Matthias

2013-08-29

Energy homeostasis ensures the functionality of the entire organism. The human brain as a missing link in the global regulation of the complex whole body energy metabolism is subject to recent investigation. The goal of this study is to gain insight into the influence of neuronal brain activity on cerebral and peripheral energy metabolism. In particular, the tight link between brain energy supply and metabolic responses of the organism is of interest. We aim to identifying regulatory elements of the human brain in the whole body energy homeostasis. First, we introduce a general mathematical model describing the human whole body energy metabolism. It takes into account the two central roles of the brain in terms of energy metabolism. The brain is considered as energy consumer as well as regulatory instance. Secondly, we validate our mathematical model by experimental data. Cerebral high-energy phosphate content and peripheral glucose metabolism are measured in healthy men upon neuronal activation induced by transcranial direct current stimulation versus sham stimulation. By parameter estimation we identify model parameters that provide insight into underlying neurophysiological processes. Identified parameters reveal effects of neuronal activity on regulatory mechanisms of systemic glucose metabolism. Our examinations support the view that the brain increases its glucose supply upon neuronal activation. The results indicate that the brain supplies itself with energy according to its needs, and preeminence of cerebral energy supply is reflected. This mechanism ensures balanced cerebral energy homeostasis. The hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported.

Linking neuronal brain activity to the glucose metabolism

PubMed Central

2013-01-01

Background Energy homeostasis ensures the functionality of the entire organism. The human brain as a missing link in the global regulation of the complex whole body energy metabolism is subject to recent investigation. The goal of this study is to gain insight into the influence of neuronal brain activity on cerebral and peripheral energy metabolism. In particular, the tight link between brain energy supply and metabolic responses of the organism is of interest. We aim to identifying regulatory elements of the human brain in the whole body energy homeostasis. Methods First, we introduce a general mathematical model describing the human whole body energy metabolism. It takes into account the two central roles of the brain in terms of energy metabolism. The brain is considered as energy consumer as well as regulatory instance. Secondly, we validate our mathematical model by experimental data. Cerebral high-energy phosphate content and peripheral glucose metabolism are measured in healthy men upon neuronal activation induced by transcranial direct current stimulation versus sham stimulation. By parameter estimation we identify model parameters that provide insight into underlying neurophysiological processes. Identified parameters reveal effects of neuronal activity on regulatory mechanisms of systemic glucose metabolism. Results Our examinations support the view that the brain increases its glucose supply upon neuronal activation. The results indicate that the brain supplies itself with energy according to its needs, and preeminence of cerebral energy supply is reflected. This mechanism ensures balanced cerebral energy homeostasis. Conclusions The hypothesis of the central role of the brain in whole body energy homeostasis as active controller is supported. PMID:23988084

Thalamic inflammation after brain trauma is associated with thalamo-cortical white matter damage.

PubMed

Scott, Gregory; Hellyer, Peter J; Ramlackhansingh, Anil F; Brooks, David J; Matthews, Paul M; Sharp, David J

2015-12-01

Traumatic brain injury can trigger chronic neuroinflammation, which may predispose to neurodegeneration. Animal models and human pathological studies demonstrate persistent inflammation in the thalamus associated with axonal injury, but this relationship has never been shown in vivo. Using [(11)C]-PK11195 positron emission tomography, a marker of microglial activation, we previously demonstrated thalamic inflammation up to 17 years after traumatic brain injury. Here, we use diffusion MRI to estimate axonal injury and show that thalamic inflammation is correlated with thalamo-cortical tract damage. These findings support a link between axonal damage and persistent inflammation after brain injury.

Measurements and models of electric fields in the in vivo human brain during transcranial electric stimulation

PubMed Central

Huang, Yu; Liu, Anli A; Lafon, Belen; Friedman, Daniel; Dayan, Michael; Wang, Xiuyuan; Bikson, Marom; Doyle, Werner K; Devinsky, Orrin; Parra, Lucas C

2017-01-01

Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimated electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.8 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r = 0.86) and depth (r = 0.88) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials. DOI: http://dx.doi.org/10.7554/eLife.18834.001 PMID:28169833

Estimation of electrical conductivity distribution within the human head from magnetic flux density measurement.

PubMed

Gao, Nuo; Zhu, S A; He, Bin

2005-06-07

We have developed a new algorithm for magnetic resonance electrical impedance tomography (MREIT), which uses only one component of the magnetic flux density to reconstruct the electrical conductivity distribution within the body. The radial basis function (RBF) network and simplex method are used in the present approach to estimate the conductivity distribution by minimizing the errors between the 'measured' and model-predicted magnetic flux densities. Computer simulations were conducted in a realistic-geometry head model to test the feasibility of the proposed approach. Single-variable and three-variable simulations were performed to estimate the brain-skull conductivity ratio and the conductivity values of the brain, skull and scalp layers. When SNR = 15 for magnetic flux density measurements with the target skull-to-brain conductivity ratio being 1/15, the relative error (RE) between the target and estimated conductivity was 0.0737 +/- 0.0746 in the single-variable simulations. In the three-variable simulations, the RE was 0.1676 +/- 0.0317. Effects of electrode position uncertainty were also assessed by computer simulations. The present promising results suggest the feasibility of estimating important conductivity values within the head from noninvasive magnetic flux density measurements.

Weighted minimum-norm source estimation of magnetoencephalography utilizing the temporal information of the measured data

NASA Astrophysics Data System (ADS)

Iwaki, Sunao; Ueno, Shoogo

1998-06-01

The weighted minimum-norm estimation (wMNE) is a popular method to obtain the source distribution in the human brain from magneto- and electro- encephalograpic measurements when detailed information about the generator profile is not available. We propose a method to reconstruct current distributions in the human brain based on the wMNE technique with the weighting factors defined by a simplified multiple signal classification (MUSIC) prescanning. In this method, in addition to the conventional depth normalization technique, weighting factors of the wMNE were determined by the cost values previously calculated by a simplified MUSIC scanning which contains the temporal information of the measured data. We performed computer simulations of this method and compared it with the conventional wMNE method. The results show that the proposed method is effective for the reconstruction of the current distributions from noisy data.

Time resolved dosimetry of human brain exposed to low frequency pulsed magnetic fields.

PubMed

Paffi, Alessandra; Camera, Francesca; Lucano, Elena; Apollonio, Francesca; Liberti, Micaela

2016-06-21

An accurate dosimetry is a key issue to understanding brain stimulation and related interaction mechanisms with neuronal tissues at the basis of the increasing amount of literature revealing the effects on human brain induced by low-level, low frequency pulsed magnetic fields (PMFs). Most literature on brain dosimetry estimates the maximum E field value reached inside the tissue without considering its time pattern or tissue dispersivity. Nevertheless a time-resolved dosimetry, accounting for dispersive tissues behavior, becomes necessary considering that the threshold for an effect onset may vary depending on the pulse waveform and that tissues may filter the applied stimulatory fields altering the predicted stimulatory waveform's size and shape. In this paper a time-resolved dosimetry has been applied on a realistic brain model exposed to the signal presented in Capone et al (2009 J. Neural Transm. 116 257-65), accounting for the broadband dispersivity of brain tissues up to several kHz, to accurately reconstruct electric field and current density waveforms inside different brain tissues. The results obtained by exposing the Duke's brain model to this PMF signal show that the E peak in the brain is considerably underestimated if a simple monochromatic dosimetry is carried out at the pulse repetition frequency of 75 Hz.

Time resolved dosimetry of human brain exposed to low frequency pulsed magnetic fields

NASA Astrophysics Data System (ADS)

Paffi, Alessandra; Camera, Francesca; Lucano, Elena; Apollonio, Francesca; Liberti, Micaela

2016-06-01

An accurate dosimetry is a key issue to understanding brain stimulation and related interaction mechanisms with neuronal tissues at the basis of the increasing amount of literature revealing the effects on human brain induced by low-level, low frequency pulsed magnetic fields (PMFs). Most literature on brain dosimetry estimates the maximum E field value reached inside the tissue without considering its time pattern or tissue dispersivity. Nevertheless a time-resolved dosimetry, accounting for dispersive tissues behavior, becomes necessary considering that the threshold for an effect onset may vary depending on the pulse waveform and that tissues may filter the applied stimulatory fields altering the predicted stimulatory waveform’s size and shape. In this paper a time-resolved dosimetry has been applied on a realistic brain model exposed to the signal presented in Capone et al (2009 J. Neural Transm. 116 257-65), accounting for the broadband dispersivity of brain tissues up to several kHz, to accurately reconstruct electric field and current density waveforms inside different brain tissues. The results obtained by exposing the Duke’s brain model to this PMF signal show that the E peak in the brain is considerably underestimated if a simple monochromatic dosimetry is carried out at the pulse repetition frequency of 75 Hz.

Targeting the ecology within: The role of the gut-brain axis and human microbiota in drug addiction.

PubMed

Skosnik, Patrick D; Cortes-Briones, Jose A

2016-08-01

Despite major advances in our understanding of the brain using traditional neuroscience, reliable and efficacious treatments for drug addiction have remained elusive. Hence, the time has come to utilize novel approaches, particularly those drawing upon contemporary advances in fields outside of established neuroscience and psychiatry. Put another way, the time has come for a paradigm shift in the addiction sciences. Apropos, a revolution in the area of human health is underway, which is occurring at the nexus between enteric microbiology and neuroscience. It has become increasingly clear that the human microbiota (the vast ecology of bacteria residing within the human organism), plays an important role in health and disease. This is not surprising, as it has been estimated that bacteria living in the human body (approximately 1kg of mass, roughly equivalent to that of the human brain) outnumber human cells 10 to 1. While advances in the understanding of the role of microbiota in other areas of human health have yielded intriguing results (e.g., Clostridium difficile, irritable bowel syndrome, autism, etc.), to date, no systematic programs of research have examined the role of microbiota in drug addiction. The current hypothesis, therefore, is that gut dysbiosis plays a key role in addictive disorders. In the context of this hypothesis, this paper provides a rationale for future research to target the "gut-brain axis" in addiction. A brief background of the gut-brain axis is provided, along with a series of hypothesis-driven ideas outlining potential treatments for addiction via manipulations of the "ecology within." Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain.

PubMed

Mohanty, Vaibhav; McKinnon, Emilie T; Helpern, Joseph A; Jensen, Jens H

2018-05-01

To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging. For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm 2 . For the QS estimates, b-values ranging from 0 up to 10,000s/mm 2 were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions. The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values. Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel. Copyright © 2018 Elsevier Inc. All rights reserved.

The evolution of the complex sensory and motor systems of the human brain

PubMed Central

Kaas, Jon H.

2008-01-01

Inferences about how the complex sensory and motor systems of the human brain evolved are based on the results of comparative studies of brain organization across a range of mammalian species, and evidence from the endocasts of fossil skulls of key extinct species. The endocasts of the skulls of early mammals indicate that they had small brains with little neocortex. Evidence from comparative studies of cortical organization from small-brained mammals of the six major branches of mammalian evolution supports the conclusion that the small neocortex of early mammals was divided into roughly 20–25 cortical areas, including primary and secondary sensory fields. In early primates, vision was the dominant sense, and cortical areas associated with vision in temporal and occipital cortex underwent a significant expansion. Comparative studies indicate that early primates had 10 or more visual areas, and somatosensory areas with expanded representations of the forepaw. Posterior parietal cortex was also expanded, with a caudal half dominated by visual inputs, and a rostral half dominated by somatosensory inputs with outputs to an array of seven or more motor and visuomotor areas of the frontal lobe. Somatosensory areas and posterior parietal cortex became further differentiated in early anthropoid primates. As larger brains evolved in early apes and in our hominin ancestors, the number of cortical areas increased to reach an estimated 200 or so in present day humans, and hemispheric specializations emerged. The large human brain grew primarily by increasing neuron number rather than increasing average neuron size. PMID:18331903

Statistical evaluation of time-dependent metabolite concentrations: estimation of post-mortem intervals based on in situ 1H-MRS of the brain.

PubMed

Scheurer, Eva; Ith, Michael; Dietrich, Daniel; Kreis, Roland; Hüsler, Jürg; Dirnhofer, Richard; Boesch, Chris

2005-05-01

Knowledge of the time interval from death (post-mortem interval, PMI) has an enormous legal, criminological and psychological impact. Aiming to find an objective method for the determination of PMIs in forensic medicine, 1H-MR spectroscopy (1H-MRS) was used in a sheep head model to follow changes in brain metabolite concentrations after death. Following the characterization of newly observed metabolites (Ith et al., Magn. Reson. Med. 2002; 5: 915-920), the full set of acquired spectra was analyzed statistically to provide a quantitative estimation of PMIs with their respective confidence limits. In a first step, analytical mathematical functions are proposed to describe the time courses of 10 metabolites in the decomposing brain up to 3 weeks post-mortem. Subsequently, the inverted functions are used to predict PMIs based on the measured metabolite concentrations. Individual PMIs calculated from five different metabolites are then pooled, being weighted by their inverse variances. The predicted PMIs from all individual examinations in the sheep model are compared with known true times. In addition, four human cases with forensically estimated PMIs are compared with predictions based on single in situ MRS measurements. Interpretation of the individual sheep examinations gave a good correlation up to 250 h post-mortem, demonstrating that the predicted PMIs are consistent with the data used to generate the model. Comparison of the estimated PMIs with the forensically determined PMIs in the four human cases shows an adequate correlation. Current PMI estimations based on forensic methods typically suffer from uncertainties in the order of days to weeks without mathematically defined confidence information. In turn, a single 1H-MRS measurement of brain tissue in situ results in PMIs with defined and favorable confidence intervals in the range of hours, thus offering a quantitative and objective method for the determination of PMIs. Copyright 2004 John Wiley & Sons, Ltd.

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface.

PubMed

Kamrunnahar, M; Schiff, S J

2011-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%-90% for the hand movements and 70%-90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models.

Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model

PubMed Central

Abdelnour, A. Farras; Huppert, Theodore

2009-01-01

Near-infrared spectroscopy is a non-invasive neuroimaging method which uses light to measure changes in cerebral blood oxygenation associated with brain activity. In this work, we demonstrate the ability to record and analyze images of brain activity in real-time using a 16-channel continuous wave optical NIRS system. We propose a novel real-time analysis framework using an adaptive Kalman filter and a state–space model based on a canonical general linear model of brain activity. We show that our adaptive model has the ability to estimate single-trial brain activity events as we apply this method to track and classify experimental data acquired during an alternating bilateral self-paced finger tapping task. PMID:19457389

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization

PubMed Central

Mankiw, Catherine; Park, Min Tae M.; Reardon, P.K.; Fish, Ari M.; Clasen, Liv S.; Greenstein, Deanna; Blumenthal, Jonathan D.; Lerch, Jason P.; Chakravarty, M. Mallar

2017-01-01

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences—including their spatial distribution, potential biological determinants, and independence from brain volume variation—lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male–female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. PMID:28314818

Background field removal technique based on non-regularized variable kernels sophisticated harmonic artifact reduction for phase data for quantitative susceptibility mapping.

PubMed

Kan, Hirohito; Arai, Nobuyuki; Takizawa, Masahiro; Omori, Kazuyoshi; Kasai, Harumasa; Kunitomo, Hiroshi; Hirose, Yasujiro; Shibamoto, Yuta

2018-06-11

We developed a non-regularized, variable kernel, sophisticated harmonic artifact reduction for phase data (NR-VSHARP) method to accurately estimate local tissue fields without regularization for quantitative susceptibility mapping (QSM). We then used a digital brain phantom to evaluate the accuracy of the NR-VSHARP method, and compared it with the VSHARP and iterative spherical mean value (iSMV) methods through in vivo human brain experiments. Our proposed NR-VSHARP method, which uses variable spherical mean value (SMV) kernels, minimizes L2 norms only within the volume of interest to reduce phase errors and save cortical information without regularization. In a numerical phantom study, relative local field and susceptibility map errors were determined using NR-VSHARP, VSHARP, and iSMV. Additionally, various background field elimination methods were used to image the human brain. In a numerical phantom study, the use of NR-VSHARP considerably reduced the relative local field and susceptibility map errors throughout a digital whole brain phantom, compared with VSHARP and iSMV. In the in vivo experiment, the NR-VSHARP-estimated local field could sufficiently achieve minimal boundary losses and phase error suppression throughout the brain. Moreover, the susceptibility map generated using NR-VSHARP minimized the occurrence of streaking artifacts caused by insufficient background field removal. Our proposed NR-VSHARP method yields minimal boundary losses and highly precise phase data. Our results suggest that this technique may facilitate high-quality QSM. Copyright © 2017. Published by Elsevier Inc.

Body size, body proportions, and encephalization in a Middle Pleistocene archaic human from northern China.

PubMed

Rosenberg, Karen R; Zuné, Lü; Ruff, Christopher B

2006-03-07

The unusual discovery of associated cranial and postcranial elements from a single Middle Pleistocene fossil human allows us to calculate body proportions and relative cranial capacity (encephalization quotient) for that individual rather than rely on estimates based on sample means from unassociated specimens. The individual analyzed here (Jinniushan) from northeastern China at 260,000 years ago is the largest female specimen yet known in the human fossil record and has body proportions (body height relative to body breadth and relative limb length) typical of cold-adapted populations elsewhere in the world. Her encephalization quotient of 4.15 is similar to estimates for late Middle Pleistocene humans that are based on mean body size and mean brain size from unassociated specimens.

Ex vivo diffusion MRI of the human brain: Technical challenges and recent advances.

PubMed

Roebroeck, Alard; Miller, Karla L; Aggarwal, Manisha

2018-06-04

This review discusses ex vivo diffusion magnetic resonance imaging (dMRI) as an important research tool for neuroanatomical investigations and the validation of in vivo dMRI techniques, with a focus on the human brain. We review the challenges posed by the properties of post-mortem tissue, and discuss state-of-the-art tissue preparation methods and recent advances in pulse sequences and acquisition techniques to tackle these. We then review recent ex vivo dMRI studies of the human brain, highlighting the validation of white matter orientation estimates and the atlasing and mapping of large subcortical structures. We also give particular emphasis to the delineation of layered gray matter structure with ex vivo dMRI, as this application illustrates the strength of its mesoscale resolution over large fields of view. We end with a discussion and outlook on future and potential directions of the field. © 2018 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

Human brain imaging and radiation dosimetry of 11C-N-desmethyl-loperamide, a PET radiotracer to measure the function of P-glycoprotein.

PubMed

Seneca, Nicholas; Zoghbi, Sami S; Liow, Jeih-San; Kreisl, William; Herscovitch, Peter; Jenko, Kimberly; Gladding, Robert L; Taku, Andrew; Pike, Victor W; Innis, Robert B

2009-05-01

P-glycoprotein (P-gp) is a membrane-bound efflux pump that limits the distribution of drugs to several organs of the body. At the blood-brain barrier, P-gp blocks the entry of both loperamide and its metabolite, N-desmethyl-loperamide (N-dLop), and thereby prevents central opiate effects. Animal studies have shown that (11)C-dLop, compared with (11)C-loperamide, is an especially promising radiotracer because it generates negligible radiometabolites that enter the brain. The purposes of this study were to determine whether (11)C-dLop is a substrate for P-gp at the blood-brain barrier in humans and to measure the distribution of radioactivity in the entire body to estimate radiation exposure. Brain PET scans were acquired in 4 healthy subjects for 90 min and included concurrent measurements of the plasma concentration of unchanged radiotracer. Time-activity data from the whole brain were quantified using a 1-tissue-compartment model to estimate the rate of entry (K(1)) of radiotracer into the brain. Whole-body PET scans were acquired in 8 healthy subjects for 120 min. For brain imaging, after the injection of (11)C-dLop the concentration of radioactivity in the brain was low (standardized uptake value, approximately 15%) and stable after approximately 20 min. In contrast, uptake of radioactivity in the pituitary was about 50-fold higher than that in the brain. The plasma concentration of (11)C-dLop declined rapidly, but the percentage composition of plasma was unusually stable, with the parent radiotracer constituting 85% of total radioactivity after approximately 5 min. The rate of brain entry was low (K(1) = 0.009 +/- 0.002 mL.cm(-3).min(-1); n = 4). For whole-body imaging, as a measure of radiation exposure to the entire body the effective dose of (11)C-dLop was 7.8 +/- 0.6 muSv/MBq (n = 8). The low brain uptake of radioactivity is consistent with (11)C-dLop being a substrate for P-gp in humans and confirms that this radiotracer generates negligible quantities of brain-penetrant radiometabolites. In addition, the low rate of K(1) is consistent with P-gp rapidly effluxing substrates while they transit through the lipid bilayer. The radiation exposure of (11)C-dLop is similar to that of many other (11)C-radiotracers. Thus, (11)C-dLop is a promising radiotracer to study the function of P-gp at the blood-brain barrier, at which impaired function would allow increased uptake into the brain.

A cytoarchitecture-driven myelin model reveals area-specific signatures in human primary and secondary areas using ultra-high resolution in-vivo brain MRI.

PubMed

Dinse, J; Härtwich, N; Waehnert, M D; Tardif, C L; Schäfer, A; Geyer, S; Preim, B; Turner, R; Bazin, P-L

2015-07-01

This work presents a novel approach for modelling laminar myelin patterns in the human cortex in brain MR images on the basis of known cytoarchitecture. For the first time, it is possible to estimate intracortical contrast visible in quantitative ultra-high resolution MR images in specific primary and secondary cytoarchitectonic areas. The presented technique reveals different area-specific signatures which may help to study the spatial distribution of cortical T1 values and the distribution of cortical myelin in general. It may lead to a new discussion on the concordance of cyto- and myeloarchitectonic boundaries, given the absence of such concordance atlases. The modelled myelin patterns are quantitatively compared with data from human ultra-high resolution in-vivo 7T brain MR images (9 subjects). In the validation, the results are compared to one post-mortem brain sample and its ex-vivo MRI and histological data. Details of the analysis pipeline are provided. In the context of the increasing interest in advanced methods in brain segmentation and cortical architectural studies, the presented model helps to bridge the gap between the microanatomy revealed by classical histology and the macroanatomy visible in MRI. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

The roadmap for estimation of cell-type-specific neuronal activity from non-invasive measurements

PubMed Central

Uhlirova, Hana; Kılıç, Kıvılcım; Tian, Peifang; Sakadžić, Sava; Thunemann, Martin; Desjardins, Michèle; Saisan, Payam A.; Nizar, Krystal; Yaseen, Mohammad A.; Hagler, Donald J.; Vandenberghe, Matthieu; Djurovic, Srdjan; Andreassen, Ole A.; Silva, Gabriel A.; Masliah, Eliezer; Vinogradov, Sergei; Buxton, Richard B.; Einevoll, Gaute T.; Boas, David A.; Dale, Anders M.; Devor, Anna

2016-01-01

The computational properties of the human brain arise from an intricate interplay between billions of neurons connected in complex networks. However, our ability to study these networks in healthy human brain is limited by the necessity to use non-invasive technologies. This is in contrast to animal models where a rich, detailed view of cellular-level brain function with cell-type-specific molecular identity has become available due to recent advances in microscopic optical imaging and genetics. Thus, a central challenge facing neuroscience today is leveraging these mechanistic insights from animal studies to accurately draw physiological inferences from non-invasive signals in humans. On the essential path towards this goal is the development of a detailed ‘bottom-up’ forward model bridging neuronal activity at the level of cell-type-specific populations to non-invasive imaging signals. The general idea is that specific neuronal cell types have identifiable signatures in the way they drive changes in cerebral blood flow, cerebral metabolic rate of O2 (measurable with quantitative functional Magnetic Resonance Imaging), and electrical currents/potentials (measurable with magneto/electroencephalography). This forward model would then provide the ‘ground truth’ for the development of new tools for tackling the inverse problem—estimation of neuronal activity from multimodal non-invasive imaging data. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574309

Bayesian estimation of optical properties of the human head via 3D structural MRI

NASA Astrophysics Data System (ADS)

Barnett, Alexander H.; Culver, Joseph P.; Sorensen, A. Gregory; Dale, Anders M.; Boas, David A.

2003-10-01

Knowledge of the baseline optical properties of the tissues of the human head is essential for absolute cerebral oximetry, and for quantitative studies of brain activation. In this work we numerically model the utility of signals from a small 6-optode time-resolved diffuse optical tomographic apparatus for inferring baseline scattering and absorption coefficients of the scalp, skull and brain, when complete geometric information is available from magnetic resonance imaging (MRI). We use an optical model where MRI-segmented tissues are assumed homogeneous. We introduce a noise model capturing both photon shot noise and forward model numerical accuracy, and use Bayesian inference to predict errorbars and correlations on the measurments. We also sample from the full posterior distribution using Markov chain Monte Carlo. We conclude that ~ 106 detected photons are sufficient to measure the brain"s scattering and absorption to a few percent. We present preliminary results using a fast multi-layer slab model, comparing the case when layer thicknesses are known versus unknown.

Identification of substance P precursor forms in human brain tissue.

PubMed Central

Nyberg, F; le Grevés, P; Terenius, L

1985-01-01

Substance P prohormones were identified in the caudate nucleus, hypothalamus, and substantia nigra of human brain. A polypeptide fraction of acidic brain extracts was fractionated on Sephadex G-50. The lyophilized fractions were sequentially treated with trypsin and a substance P-degrading enzyme with strong preference toward the Phe7-Phe8 and Phe8-Gly9 bonds. The released substance P(1-7) fragment was isolated by ion-exchange chromatography and quantitated by a specific radioimmunoassay. Confirmation of the structure of the isolated radioimmunoassay-active fragment was achieved by electrophoresis and HPLC. By using this enzymatic/radioimmunoassay procedure, two polypeptide fractions of apparent Mr 5000 and 15,000, respectively, were identified. The latter component was the major one of the two but was estimated to account for only about 5% of total substance P radioimmunoassay activity. Because it is of the size predicted from the nucleotide sequences of cDNA for substance P prohormones in bovine brain, the Mr 15,000 component may represent the full-length prohormone. PMID:2408270

A biometric analysis of brain size in micrencephalics.

PubMed

Hofman, M A

1984-01-01

Brain weight and head circumference in micrencephalic patients were analysed as a function of age, height and sex in relation to normal human standards. A quantitative definition of micrencephaly is proposed, which is based on these analyses. Evidence is presented, furthermore, that micrencephalics have a significantly lower brain weight in adolescence than in early childhood, and that this cerebral dystrophy continues throughout adulthood, leading to death in more than 85% of the males and 78% of the females before they reach the age of 30 years. Since this decline in brain weight after approximately 3-5 years of age is not accompanied by a similar reduction in head circumference, the brains of elderly micrencephalic patients no longer occupy the entire cranial cavity. It is evident, therefore, that head circumference in the case of micrencephaly is an unsuitable parameter for estimating brain size.

Characterization in humans of 18F-MNI-444, a PET radiotracer for brain adenosine 2A receptors.

PubMed

Barret, Olivier; Hannestad, Jonas; Vala, Christine; Alagille, David; Tavares, Adriana; Laruelle, Marc; Jennings, Danna; Marek, Ken; Russell, David; Seibyl, John; Tamagnan, Gilles

2015-04-01

PET with selective adenosine 2A receptor (A2A) radiotracers can be used to study a variety of neurodegenerative and neuropsychiatric disorders in vivo and to support drug-discovery studies targeting A2A. The aim of this study was to describe the first in vivo evaluation of (18)F-MNI-444, a novel PET radiotracer for imaging A2A, in healthy human subjects. Ten healthy human volunteers were enrolled in this study; 6 completed the brain PET studies and 4 participated in the whole-body PET studies. Arterial blood was collected for invasive kinetic modeling of the brain PET data. Noninvasive methods of data quantification were also explored. Test-retest reproducibility was evaluated in 5 subjects. Radiotracer distribution and dosimetry was determined using serial whole-body PET images acquired over 6 h post-radiotracer injection. Urine samples were collected to calculate urinary excretion. After intravenous bolus injection, (18)F-MNI-444 rapidly entered the brain and displayed a distribution consistent with known A2A densities in the brain. Binding potentials ranging from 2.6 to 4.9 were measured in A2A-rich regions, with an average test-retest variability of less than 10%. The estimated whole-body radiation effective dose was approximately 0.023 mSv/MBq. (18)F-MNI-444 is a useful PET radiotracer for imaging A2A in the human brain. The superior in vivo brain kinetic properties of (18)F-MNI-444, compared with previously developed A2A radiotracers, provide the opportunity to foster global use of in vivo A2A PET imaging in neuroscience research. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Age-related apparent diffusion coefficient changes in the normal brain.

PubMed

Watanabe, Memi; Sakai, Osamu; Ozonoff, Al; Kussman, Steven; Jara, Hernán

2013-02-01

To measure the mean diffusional age-related changes of the brain over the full human life span by using diffusion-weighted spin-echo single-shot echo-planar magnetic resonance (MR) imaging and sequential whole-brain apparent diffusion coefficient (ADC) histogram analysis and, secondarily, to build mathematical models of these normal age-related changes throughout human life. After obtaining institutional review board approval, a HIPAA-compliant retrospective search was conducted for brain MR imaging studies performed in 2007 for various clinical indications. Informed consent was waived. The brain data of 414 healthy subjects (189 males and 225 females; mean age, 33.7 years; age range, 2 days to 89.3 years) were obtained with diffusion-weighted spin-echo single-shot echo-planar MR imaging. ADC histograms of the whole brain were generated. ADC peak values, histogram widths, and intracranial volumes were plotted against age, and model parameters were estimated by using nonlinear regression. Four different stages were identified for aging changes in ADC peak values, as characterized by specific mathematical terms: There were age-associated exponential decays for the maturation period and the development period, a constant term for adulthood, and a linear increase for the senescence period. The age dependency of ADC peak value was simulated by using four-term six-coefficient function, including biexponential and linear terms. This model fit the data very closely (R(2) = 0.91). Brain diffusivity as a whole demonstrated age-related changes through four distinct periods of life. These results could contribute to establishing an ADC baseline of the normal brain, covering the full human life span.

AGE-RELATED BRAIN CHOLINESTERASE INHIBITION KINETICS FOLLOWING IN VITRO INCUBATION WITH CHLORPYRIFOS-OXON AND DIAZINON-OXON

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kousba, Ahmed A.; Poet, Torka S.; Timchalk, Chuck

2007-01-01

Chlorpyrifos and diazinon are two commonly used organophosphorus (OP) insecticides, and their primary mechanism of action involves the inhibition of acetylcholinesterase (AChE) by their metabolites chlorpyrifos-oxon (CPO) and diazinon-oxon (DZO), respectively. The study objectives were to assess the in vitro age-related inhibition kinetics of neonatal rat brain cholinesterase (ChE) by estimating the bimolecular inhibitory rate constant (ki) values for CPO and DZO. Brain ChE inhibition and ki values following CPO and DZO incubation with neonatal Sprague-Dawley rats rat brain homogenates were determined at post natal day (PND) -5, -12 and -17 and compared with the corresponding inhibition and ki valuesmore » obtained in the adult rat. A modified Ellman method was utilized for measuring the ChE activity. Chlorpyrifos-oxon resulted in greater ChE inhibition than DZO consistent with the estimated ki values of both compounds. Neonatal brain ChE inhibition kinetics exhibited a marked age-related sensitivity to CPO, where the order of ChE inhibition was PND-5 > PND-7 > PND-17 with ki values of 0.95, 0.50 and 0.22 nM-1hr-1, respectively. In contrast, DZO did not exhibit an age-related inhibition of neonatal brain ChE, and the estimated ki value at all PND ages was 0.02 nM-1hr-1. These results demonstrated an age- and chemical-related OP-selective inhibition of rat brain ChE which may be critically important in understanding the potential sensitivity of juvenile humans to specific OP exposures.« less

A square root ensemble Kalman filter application to a motor-imagery brain-computer interface

PubMed Central

Kamrunnahar, M.; Schiff, S. J.

2017-01-01

We here investigated a non-linear ensemble Kalman filter (SPKF) application to a motor imagery brain computer interface (BCI). A square root central difference Kalman filter (SR-CDKF) was used as an approach for brain state estimation in motor imagery task performance, using scalp electroencephalography (EEG) signals. Healthy human subjects imagined left vs. right hand movements and tongue vs. bilateral toe movements while scalp EEG signals were recorded. Offline data analysis was conducted for training the model as well as for decoding the imagery movements. Preliminary results indicate the feasibility of this approach with a decoding accuracy of 78%–90% for the hand movements and 70%–90% for the tongue-toes movements. Ongoing research includes online BCI applications of this approach as well as combined state and parameter estimation using this algorithm with different system dynamic models. PMID:22255799

Autonomous Vehicle Systems: Implications for Maritime Operations, Warfare Capabilities, and Command and Control

DTIC Science & Technology

2010-06-01

speed doubles approximately every 18 months, Nick Bostrom published a study in 1998 that equated computer processing power to that of the human...bits, this equates to 1017 operations per second, or 1011 millions of instructions per second (MIPS), for human brain performance ( Bostrom , 1998). In...estimates based off Moore’s Law put realistic, affordable computer processing power equal to that of humans somewhere in the 2020–2025 timeframe ( Bostrom

Inferring Selective Constraint from Population Genomic Data Suggests Recent Regulatory Turnover in the Human Brain

PubMed Central

Schrider, Daniel R.; Kern, Andrew D.

2015-01-01

The comparative genomics revolution of the past decade has enabled the discovery of functional elements in the human genome via sequence comparison. While that is so, an important class of elements, those specific to humans, is entirely missed by searching for sequence conservation across species. Here we present an analysis based on variation data among human genomes that utilizes a supervised machine learning approach for the identification of human-specific purifying selection in the genome. Using only allele frequency information from the complete low-coverage 1000 Genomes Project data set in conjunction with a support vector machine trained from known functional and nonfunctional portions of the genome, we are able to accurately identify portions of the genome constrained by purifying selection. Our method identifies previously known human-specific gains or losses of function and uncovers many novel candidates. Candidate targets for gain and loss of function along the human lineage include numerous putative regulatory regions of genes essential for normal development of the central nervous system, including a significant enrichment of gain of function events near neurotransmitter receptor genes. These results are consistent with regulatory turnover being a key mechanism in the evolution of human-specific characteristics of brain development. Finally, we show that the majority of the genome is unconstrained by natural selection currently, in agreement with what has been estimated from phylogenetic methods but in sharp contrast to estimates based on transcriptomics or other high-throughput functional methods. PMID:26590212

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sawada, Y.; Kawai, R.; McManaway, M.

(3H)Cyclofoxy (CF: 17-cyclopropylmethyl-3,14-dihydroxy-4,5-alpha-epoxy-6-beta-fluoromorp hinan) is an opioid antagonist with affinity to both mu and kappa subtypes that was synthesized for quantitative evaluation of opioid receptor binding in vivo. Two sets of experiments in rats were analyzed. The first involved determining the metabolite-corrected blood concentration and tissue distribution of CF in brain 1 to 60 min after i.v. bolus injection. The second involved measuring brain washout for 15 to 120 s following intracarotid artery injection of CF. A physiologically based model and a classical compartmental pharmacokinetic model were compared. The models included different assumptions for transport across the blood-brain barrier (BBB);more » estimates of nonspecific tissue binding and specific binding to a single opiate receptor site were found to be essentially the same with both models. The nonspecific binding equilibrium constant varied modestly in different brain structures (Keq = 3-9), whereas the binding potential (BP) varied over a much broader range (BP = 0.6-32). In vivo estimates of the opioid receptor dissociation constant were similar for different brain structures (KD = 2.1-5.2 nM), whereas the apparent receptor density (Bmax) varied between 1 (cerebellum) and 78 (thalamus) pmol/g of brain. The receptor dissociation rate constants in cerebrum (k4 = 0.08-0.16 min-1; koff = 0.16-0.23 min-1) and brain vascular permeability (PS = 1.3-3.4 ml/min/g) are sufficiently high to achieve equilibrium conditions within a reasonable period of time. Graphical analysis of the data is inappropriate due to the high tissue-loss rate constant for CF in brain. From these findings, CF should be a very useful opioid receptor ligand for the estimation of the receptor binding parameters in human subjects using (18F)CF and positron emission tomography.« less

A brain-controlled lower-limb exoskeleton for human gait training.

PubMed

Liu, Dong; Chen, Weihai; Pei, Zhongcai; Wang, Jianhua

2017-10-01

Brain-computer interfaces have been a novel approach to translate human intentions into movement commands in robotic systems. This paper describes an electroencephalogram-based brain-controlled lower-limb exoskeleton for gait training, as a proof of concept towards rehabilitation with human-in-the-loop. Instead of using conventional single electroencephalography correlates, e.g., evoked P300 or spontaneous motor imagery, we propose a novel framework integrated two asynchronous signal modalities, i.e., sensorimotor rhythms (SMRs) and movement-related cortical potentials (MRCPs). We executed experiments in a biologically inspired and customized lower-limb exoskeleton where subjects (N = 6) actively controlled the robot using their brain signals. Each subject performed three consecutive sessions composed of offline training, online visual feedback testing, and online robot-control recordings. Post hoc evaluations were conducted including mental workload assessment, feature analysis, and statistics test. An average robot-control accuracy of 80.16% ± 5.44% was obtained with the SMR-based method, while estimation using the MRCP-based method yielded an average performance of 68.62% ± 8.55%. The experimental results showed the feasibility of the proposed framework with all subjects successfully controlled the exoskeleton. The current paradigm could be further extended to paraplegic patients in clinical trials.

A brain-controlled lower-limb exoskeleton for human gait training

NASA Astrophysics Data System (ADS)

Liu, Dong; Chen, Weihai; Pei, Zhongcai; Wang, Jianhua

2017-10-01

Brain-computer interfaces have been a novel approach to translate human intentions into movement commands in robotic systems. This paper describes an electroencephalogram-based brain-controlled lower-limb exoskeleton for gait training, as a proof of concept towards rehabilitation with human-in-the-loop. Instead of using conventional single electroencephalography correlates, e.g., evoked P300 or spontaneous motor imagery, we propose a novel framework integrated two asynchronous signal modalities, i.e., sensorimotor rhythms (SMRs) and movement-related cortical potentials (MRCPs). We executed experiments in a biologically inspired and customized lower-limb exoskeleton where subjects (N = 6) actively controlled the robot using their brain signals. Each subject performed three consecutive sessions composed of offline training, online visual feedback testing, and online robot-control recordings. Post hoc evaluations were conducted including mental workload assessment, feature analysis, and statistics test. An average robot-control accuracy of 80.16% ± 5.44% was obtained with the SMR-based method, while estimation using the MRCP-based method yielded an average performance of 68.62% ± 8.55%. The experimental results showed the feasibility of the proposed framework with all subjects successfully controlled the exoskeleton. The current paradigm could be further extended to paraplegic patients in clinical trials.

Analysis and asynchronous detection of gradually unfolding errors during monitoring tasks

NASA Astrophysics Data System (ADS)

Omedes, Jason; Iturrate, Iñaki; Minguez, Javier; Montesano, Luis

2015-10-01

Human studies on cognitive control processes rely on tasks involving sudden-onset stimuli, which allow the analysis of these neural imprints to be time-locked and relative to the stimuli onset. Human perceptual decisions, however, comprise continuous processes where evidence accumulates until reaching a boundary. Surpassing the boundary leads to a decision where measured brain responses are associated to an internal, unknown onset. The lack of this onset for gradual stimuli hinders both the analyses of brain activity and the training of detectors. This paper studies electroencephalographic (EEG)-measurable signatures of human processing for sudden and gradual cognitive processes represented as a trajectory mismatch under a monitoring task. Time-locked potentials and brain-source analysis of the EEG of sudden mismatches revealed the typical components of event-related potentials and the involvement of brain structures related to cognitive control processing. For gradual mismatch events, time-locked analyses did not show any discernible EEG scalp pattern, despite related brain areas being, to a lesser extent, activated. However, and thanks to the use of non-linear pattern recognition algorithms, it is possible to train an asynchronous detector on sudden events and use it to detect gradual mismatches, as well as obtaining an estimate of their unknown onset. Post-hoc time-locked scalp and brain-source analyses revealed that the EEG patterns of detected gradual mismatches originated in brain areas related to cognitive control processing. This indicates that gradual events induce latency in the evaluation process but that similar brain mechanisms are present in sudden and gradual mismatch events. Furthermore, the proposed asynchronous detection model widens the scope of applications of brain-machine interfaces to other gradual processes.

Brain regions with mirror properties: a meta-analysis of 125 human fMRI studies.

PubMed

Molenberghs, Pascal; Cunnington, Ross; Mattingley, Jason B

2012-01-01

Mirror neurons in macaque area F5 fire when an animal performs an action, such as a mouth or limb movement, and also when the animal passively observes an identical or similar action performed by another individual. Brain-imaging studies in humans conducted over the last 20 years have repeatedly attempted to reveal analogous brain regions with mirror properties in humans, with broad and often speculative claims about their functional significance across a range of cognitive domains, from language to social cognition. Despite such concerted efforts, the likely neural substrates of these mirror regions have remained controversial, and indeed the very existence of a distinct subcategory of human neurons with mirroring properties has been questioned. Here we used activation likelihood estimation (ALE), to provide a quantitative index of the consistency of patterns of fMRI activity measured in human studies of action observation and action execution. From an initial sample of more than 300 published works, data from 125 papers met our strict inclusion and exclusion criteria. The analysis revealed 14 separate clusters in which activation has been consistently attributed to brain regions with mirror properties, encompassing 9 different Brodmann areas. These clusters were located in areas purported to show mirroring properties in the macaque, such as the inferior parietal lobule, inferior frontal gyrus and the adjacent ventral premotor cortex, but surprisingly also in regions such as the primary visual cortex, cerebellum and parts of the limbic system. Our findings suggest a core network of human brain regions that possess mirror properties associated with action observation and execution, with additional areas recruited during tasks that engage non-motor functions, such as auditory, somatosensory and affective components. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Shared sensory estimates for human motion perception and pursuit eye movements.

PubMed

Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio; Osborne, Leslie C

2015-06-03

Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. Copyright © 2015 the authors 0270-6474/15/358515-16$15.00/0.

Shared Sensory Estimates for Human Motion Perception and Pursuit Eye Movements

PubMed Central

Mukherjee, Trishna; Battifarano, Matthew; Simoncini, Claudio

2015-01-01

Are sensory estimates formed centrally in the brain and then shared between perceptual and motor pathways or is centrally represented sensory activity decoded independently to drive awareness and action? Questions about the brain's information flow pose a challenge because systems-level estimates of environmental signals are only accessible indirectly as behavior. Assessing whether sensory estimates are shared between perceptual and motor circuits requires comparing perceptual reports with motor behavior arising from the same sensory activity. Extrastriate visual cortex both mediates the perception of visual motion and provides the visual inputs for behaviors such as smooth pursuit eye movements. Pursuit has been a valuable testing ground for theories of sensory information processing because the neural circuits and physiological response properties of motion-responsive cortical areas are well studied, sensory estimates of visual motion signals are formed quickly, and the initiation of pursuit is closely coupled to sensory estimates of target motion. Here, we analyzed variability in visually driven smooth pursuit and perceptual reports of target direction and speed in human subjects while we manipulated the signal-to-noise level of motion estimates. Comparable levels of variability throughout viewing time and across conditions provide evidence for shared noise sources in the perception and action pathways arising from a common sensory estimate. We found that conditions that create poor, low-gain pursuit create a discrepancy between the precision of perception and that of pursuit. Differences in pursuit gain arising from differences in optic flow strength in the stimulus reconcile much of the controversy on this topic. PMID:26041919

Brain networks for confidence weighting and hierarchical inference during probabilistic learning.

PubMed

Meyniel, Florent; Dehaene, Stanislas

2017-05-09

Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences.

Allometric Analysis Detects Brain Size-Independent Effects of Sex and Sex Chromosome Complement on Human Cerebellar Organization.

PubMed

Mankiw, Catherine; Park, Min Tae M; Reardon, P K; Fish, Ari M; Clasen, Liv S; Greenstein, Deanna; Giedd, Jay N; Blumenthal, Jonathan D; Lerch, Jason P; Chakravarty, M Mallar; Raznahan, Armin

2017-05-24

The cerebellum is a large hindbrain structure that is increasingly recognized for its contribution to diverse domains of cognitive and affective processing in human health and disease. Although several of these domains are sex biased, our fundamental understanding of cerebellar sex differences-including their spatial distribution, potential biological determinants, and independence from brain volume variation-lags far behind that for the cerebrum. Here, we harness automated neuroimaging methods for cerebellar morphometrics in 417 individuals to (1) localize normative male-female differences in raw cerebellar volume, (2) compare these to sex chromosome effects estimated across five rare sex (X/Y) chromosome aneuploidy (SCA) syndromes, and (3) clarify brain size-independent effects of sex and SCA on cerebellar anatomy using a generalizable allometric approach that considers scaling relationships between regional cerebellar volume and brain volume in health. The integration of these approaches shows that (1) sex and SCA effects on raw cerebellar volume are large and distributed, but regionally heterogeneous, (2) human cerebellar volume scales with brain volume in a highly nonlinear and regionally heterogeneous fashion that departs from documented patterns of cerebellar scaling in phylogeny, and (3) cerebellar organization is modified in a brain size-independent manner by sex (relative expansion of total cerebellum, flocculus, and Crus II-lobule VIIIB volumes in males) and SCA (contraction of total cerebellar, lobule IV, and Crus I volumes with additional X- or Y-chromosomes; X-specific contraction of Crus II-lobule VIIIB). Our methods and results clarify the shifts in human cerebellar organization that accompany interwoven variations in sex, sex chromosome complement, and brain size. SIGNIFICANCE STATEMENT Cerebellar systems are implicated in diverse domains of sex-biased behavior and pathology, but we lack a basic understanding of how sex differences in the human cerebellum are distributed and determined. We leverage a rare neuroimaging dataset to deconvolve the interwoven effects of sex, sex chromosome complement, and brain size on human cerebellar organization. We reveal topographically variegated scaling relationships between regional cerebellar volume and brain size in humans, which (1) are distinct from those observed in phylogeny, (2) invalidate a traditional neuroimaging method for brain volume correction, and (3) allow more valid and accurate resolution of which cerebellar subcomponents are sensitive to sex and sex chromosome complement. These findings advance understanding of cerebellar organization in health and sex chromosome aneuploidy. Copyright © 2017 the authors 0270-6474/17/375222-11$15.00/0.

CEREBRA: a 3-D visualization tool for brain network extracted from fMRI data.

PubMed

Nasir, Baris; Yarman Vural, Fatos T

2016-08-01

In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active brain regions and the interactions among them by using graph theoretic measures, such as, the edge weight and node degree distributions. CEREBRA provides an interactive interface with basic display and editing options for the researchers to study their hypotheses about the connectivity of the brain network. CEREBRA interactively simplifies the network by selecting the active voxels and the most correlated edge weights. The researchers may remove the voxels and edges by using local and global thresholds selected on the window. The built-in graph reduction algorithms are then eliminate the irrelevant regions, voxels and edges and display various properties of the network. The toolbox is capable of space-time representation of the voxel time series and estimated arc weights by using the animated heat maps.

Evolution of Siglec-11 and Siglec-16 Genes in Hominins

PubMed Central

Wang, Xiaoxia; Mitra, Nivedita; Cruz, Pedro; Deng, Liwen; Varki, Nissi; Angata, Takashi; Green, Eric D.; Mullikin, Jim; Hayakawa, Toshiyuki; Varki, Ajit

2012-01-01

We previously reported a human-specific gene conversion of SIGLEC11 by an adjacent paralogous pseudogene (SIGLEC16P), generating a uniquely human form of the Siglec-11 protein, which is expressed in the human brain. Here, we show that Siglec-11 is expressed exclusively in microglia in all human brains studied—a finding of potential relevance to brain evolution, as microglia modulate neuronal survival, and Siglec-11 recruits SHP-1, a tyrosine phosphatase that modulates microglial biology. Following the recent finding of a functional SIGLEC16 allele in human populations, further analysis of the human SIGLEC11 and SIGLEC16/P sequences revealed an unusual series of gene conversion events between two loci. Two tandem and likely simultaneous gene conversions occurred from SIGLEC16P to SIGLEC11 with a potentially deleterious intervening short segment happening to be excluded. One of the conversion events also changed the 5′ untranslated sequence, altering predicted transcription factor binding sites. Both of the gene conversions have been dated to ∼1–1.2 Ma, after the emergence of the genus Homo, but prior to the emergence of the common ancestor of Denisovans and modern humans about 800,000 years ago, thus suggesting involvement in later stages of hominin brain evolution. In keeping with this, recombinant soluble Siglec-11 binds ligands in the human brain. We also address a second-round more recent gene conversion from SIGLEC11 to SIGLEC16, with the latter showing an allele frequency of ∼0.1–0.3 in a worldwide population study. Initial pseudogenization of SIGLEC16 was estimated to occur at least 3 Ma, which thus preceded the gene conversion of SIGLEC11 by SIGLEC16P. As gene conversion usually disrupts the converted gene, the fact that ORFs of hSIGLEC11 and hSIGLEC16 have been maintained after an unusual series of very complex gene conversion events suggests that these events may have been subject to hominin-specific selection forces. PMID:22383531

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

PubMed Central

Eugster, Manuel J. A.; Ruotsalo, Tuukka; Spapé, Michiel M.; Barral, Oswald; Ravaja, Niklas; Jacucci, Giulio; Kaski, Samuel

2016-01-01

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications. PMID:27929077

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

NASA Astrophysics Data System (ADS)

Eugster, Manuel J. A.; Ruotsalo, Tuukka; Spapé, Michiel M.; Barral, Oswald; Ravaja, Niklas; Jacucci, Giulio; Kaski, Samuel

2016-12-01

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications.

Brain stem auditory evoked responses in human infants and adults

NASA Technical Reports Server (NTRS)

Hecox, K.; Galambos, R.

1974-01-01

Brain stem evoked potentials were recorded by conventional scalp electrodes in infants (3 weeks to 3 years of age) and adults. The latency of one of the major response components (wave V) is shown to be a function both of click intensity and the age of the subject; this latency at a given signal strength shortens postnatally to reach the adult value (about 6 msec) by 12 to 18 months of age. The demonstrated reliability and limited variability of these brain stem electrophysiological responses provide the basis for an optimistic estimate of their usefulness as an objective method for assessing hearing in infants and adults.

Recovering fNIRS brain signals: physiological interference suppression with independent component analysis

NASA Astrophysics Data System (ADS)

Zhang, Y.; Shi, M.; Sun, J.; Yang, C.; Zhang, Yajuan; Scopesi, F.; Makobore, P.; Chin, C.; Serra, G.; Wickramasinghe, Y. A. B. D.; Rolfe, P.

2015-02-01

Brain activity can be monitored non-invasively by functional near-infrared spectroscopy (fNIRS), which has several advantages in comparison with other methods, such as flexibility, portability, low cost and fewer physical restrictions. However, in practice fNIRS measurements are often contaminated by physiological interference arising from cardiac contraction, breathing and blood pressure fluctuations, thereby severely limiting the utility of the method. Hence, further improvement is necessary to reduce or eliminate such interference in order that the evoked brain activity information can be extracted reliably from fNIRS data. In the present paper, the multi-distance fNIRS probe configuration has been adopted. The short-distance fNIRS measurement is treated as the virtual channel and the long-distance fNIRS measurement is treated as the measurement channel. Independent component analysis (ICA) is employed for the fNIRS recordings to separate the brain signals and the interference. Least-absolute deviation (LAD) estimator is employed to recover the brain activity signals. We also utilized Monte Carlo simulations based on a five-layer model of the adult human head to evaluate our methodology. The results demonstrate that the ICA algorithm has the potential to separate physiological interference in fNIRS data and the LAD estimator could be a useful criterion to recover the brain activity signals.

A validation framework for brain tumor segmentation.

PubMed

Archip, Neculai; Jolesz, Ferenc A; Warfield, Simon K

2007-10-01

We introduce a validation framework for the segmentation of brain tumors from magnetic resonance (MR) images. A novel unsupervised semiautomatic brain tumor segmentation algorithm is also presented. The proposed framework consists of 1) T1-weighted MR images of patients with brain tumors, 2) segmentation of brain tumors performed by four independent experts, 3) segmentation of brain tumors generated by a semiautomatic algorithm, and 4) a software tool that estimates the performance of segmentation algorithms. We demonstrate the validation of the novel segmentation algorithm within the proposed framework. We show its performance and compare it with existent segmentation. The image datasets and software are available at http://www.brain-tumor-repository.org/. We present an Internet resource that provides access to MR brain tumor image data and segmentation that can be openly used by the research community. Its purpose is to encourage the development and evaluation of segmentation methods by providing raw test and image data, human expert segmentation results, and methods for comparing segmentation results.

Improved recovery of the hemodynamic response in Diffuse Optical Imaging using short optode separations and state-space modeling

PubMed Central

Gagnon, Louis; Perdue, Katherine; Greve, Douglas N.; Goldenholz, Daniel; Kaskhedikar, Gayatri; Boas, David A.

2011-01-01

Diffuse Optical Imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1 cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R2 coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p < 0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique. PMID:21385616

Methamphetamine Causes Microglial Activation in the Brains of Human Abusers

PubMed Central

Sekine, Yoshimoto; Ouchi, Yasuomi; Sugihara, Genichi; Takei, Nori; Yoshikawa, Etsuji; Nakamura, Kazuhiko; Iwata, Yasuhide; Tsuchiya, Kenji J.; Suda, Shiro; Suzuki, Katsuaki; Kawai, Masayoshi; Takebayashi, Kiyokazu; Yamamoto, Shigeyuki; Matsuzaki, Hideo; Ueki, Takatoshi; Mori, Norio; Gold, Mark S.; Cadet, Jean L.

2008-01-01

Methamphetamine is a popular addictive drug whose use is associated with multiple neuropsychiatric adverse events and toxic to the dopaminergic and serotonergic systems of the brain. Methamphetamine-induced neuropathology is associated with increased expression of microglial cells that are thought to participate in either pro-toxic or protective mechanisms in the brain. Although reactive microgliosis has been observed in animal models of methamphetamine neurotoxicity, no study has reported on the status of microglial activation in human methamphetamine abusers. The present study reports on 12 abstinent methamphetamine abusers and 12 age-, gender-, education-matched control subjects who underwent positron emission tomography using a radiotracer for activated microglia, [11C](R)-(1-[2-chlorophenyl]-N-methyl-N-[1-methylpropyl]-3-isoquinoline carboxamide) ([11C](R)-PK11195). Compartment analysis was used to estimate quantitative levels of binding potentials of [11C](R)-PK11195 in brain regions with dopaminergic and/or serotonergic innervation. The mean levels of [11C](R)-PK11195 binding were higher in methamphetamine abusers than those in control subjects in all brain regions (> 250% higher, p < 0.01 for all). In addition, the binding levels in the midbrain, striatum, thalamus, and orbitofrontal and insular cortices (p < 0.05) correlated inversely with the duration of methamphetamine abstinence. These results suggest that chronic self-administration of methamphetamine can cause reactive microgliosis in the brains of human methamphetamine abusers, a level of activation that appears to subside over longer periods of abstinence. PMID:18509037

Methamphetamine causes microglial activation in the brains of human abusers.

PubMed

Sekine, Yoshimoto; Ouchi, Yasuomi; Sugihara, Genichi; Takei, Nori; Yoshikawa, Etsuji; Nakamura, Kazuhiko; Iwata, Yasuhide; Tsuchiya, Kenji J; Suda, Shiro; Suzuki, Katsuaki; Kawai, Masayoshi; Takebayashi, Kiyokazu; Yamamoto, Shigeyuki; Matsuzaki, Hideo; Ueki, Takatoshi; Mori, Norio; Gold, Mark S; Cadet, Jean L

2008-05-28

Methamphetamine is a popular addictive drug whose use is associated with multiple neuropsychiatric adverse events and toxic to the dopaminergic and serotonergic systems of the brain. Methamphetamine-induced neuropathology is associated with increased expression of microglial cells that are thought to participate in either pro-toxic or protective mechanisms in the brain. Although reactive microgliosis has been observed in animal models of methamphetamine neurotoxicity, no study has reported on the status of microglial activation in human methamphetamine abusers. The present study reports on 12 abstinent methamphetamine abusers and 12 age-, gender-, and education-matched control subjects who underwent positron emission tomography using a radiotracer for activated microglia, [(11)C](R)-(1-[2-chlorophenyl]-N-methyl-N-[1-methylpropyl]-3-isoquinoline carboxamide) ([(11)C](R)-PK11195). Compartment analysis was used to estimate quantitative levels of binding potentials of [(11)C](R)-PK11195 in brain regions with dopaminergic and/or serotonergic innervation. The mean levels of [(11)C](R)-PK11195 binding were higher in methamphetamine abusers than those in control subjects in all brain regions (>250% higher; p < 0.01 for all). In addition, the binding levels in the midbrain, striatum, thalamus, and orbitofrontal and insular cortices (p < 0.05) correlated inversely with the duration of methamphetamine abstinence. These results suggest that chronic self-administration of methamphetamine can cause reactive microgliosis in the brains of human methamphetamine abusers, a level of activation that appears to subside over longer periods of abstinence.

Creating an anthropomorphic digital MR phantom—an extensible tool for comparing and evaluating quantitative imaging algorithms

NASA Astrophysics Data System (ADS)

Bosca, Ryan J.; Jackson, Edward F.

2016-01-01

Assessing and mitigating the various sources of bias and variance associated with image quantification algorithms is essential to the use of such algorithms in clinical research and practice. Assessment is usually accomplished with grid-based digital reference objects (DRO) or, more recently, digital anthropomorphic phantoms based on normal human anatomy. Publicly available digital anthropomorphic phantoms can provide a basis for generating realistic model-based DROs that incorporate the heterogeneity commonly found in pathology. Using a publicly available vascular input function (VIF) and digital anthropomorphic phantom of a normal human brain, a methodology was developed to generate a DRO based on the general kinetic model (GKM) that represented realistic and heterogeneously enhancing pathology. GKM parameters were estimated from a deidentified clinical dynamic contrast-enhanced (DCE) MRI exam. This clinical imaging volume was co-registered with a discrete tissue model, and model parameters estimated from clinical images were used to synthesize a DCE-MRI exam that consisted of normal brain tissues and a heterogeneously enhancing brain tumor. An example application of spatial smoothing was used to illustrate potential applications in assessing quantitative imaging algorithms. A voxel-wise Bland-Altman analysis demonstrated negligible differences between the parameters estimated with and without spatial smoothing (using a small radius Gaussian kernel). In this work, we reported an extensible methodology for generating model-based anthropomorphic DROs containing normal and pathological tissue that can be used to assess quantitative imaging algorithms.

Alterations of functional connectivities from early to middle adulthood: Clues from multivariate pattern analysis of resting-state fMRI data.

PubMed

Tian, Lixia; Ma, Lin; Wang, Linlin

2016-04-01

In contrast to extended research interests in the maturation and aging of human brain, alterations of brain structure and function from early to middle adulthood have been much less studied. The aim of the present study was to investigate the extent and pattern of the alterations of functional interactions between brain regions from early to middle adulthood. We carried out the study by multivariate pattern analysis of resting-state fMRI (RS-fMRI) data of 63 adults aged 18 to 45 years. Specifically, using elastic net, we performed brain age estimation and age-group classification (young adults aged 18-28 years vs. middle-aged adults aged 35-45 years) based on the resting-state functional connectivities (RSFCs) between 160 regions of interest (ROIs) evaluated on the RS-fMRI data of each subject. The results indicate that the estimated brain ages were significantly correlated with the chronological age (R=0.78, MAE=4.81), and a classification rate of 94.44% and area under the receiver operating characteristic curve (AUC) of 0.99 were obtained when classifying the young and middle-aged adults. These results provide strong evidence that functional interactions between brain regions undergo notable alterations from early to middle adulthood. By analyzing the RSFCs that contribute to brain age estimation/age-group classification, we found that a majority of the RSFCs were inter-network, and we speculate that inter-network RSFCs might mature late but age early as compared to intra-network ones. In addition, the strengthening/weakening of the RSFCs associated with the left/right hemispheric ROIs, the weakening of cortico-cerebellar RSFCs and the strengthening of the RSFCs between the default mode network and other networks contributed much to both brain age estimation and age-group classification. All these alterations might reflect that aging of brain function is already in progress in middle adulthood. Overall, the present study indicated that the RSFCs undergo notable alterations from early to middle adulthood and highlighted the necessity of careful considerations of possible influences of these alterations in related studies. Copyright © 2016 Elsevier Inc. All rights reserved.

Human arm stiffness and equilibrium-point trajectory during multi-joint movement.

PubMed

Gomi, H; Kawato, M

1997-03-01

By using a newly designed high-performance manipulandum and a new estimation algorithm, we measured human multi-joint arm stiffness parameters during multi-joint point-to-point movements on a horizontal plane. This manipulandum allows us to apply a sufficient perturbation to subject's arm within a brief period during movement. Arm stiffness parameters were reliably estimated using a new algorithm, in which all unknown structural parameters could be estimated independent of arm posture (i.e., constant values under any arm posture). Arm stiffness during transverse movement was considerably greater than that during corresponding posture, but not during a longitudinal movement. Although the ratios of elbow, shoulder, and double-joint stiffness were varied in time, the orientation of stiffness ellipses during the movement did not change much. Equilibrium-point trajectories that were predicted from measured stiffness parameters and actual trajectories were slightly sinusoidally curved in Cartesian space and their velocity profiles were quite different from the velocity profiles of actual hand trajectories. This result contradicts the hypothesis that the brain does not take the dynamics into account in movement control depending on the neuromuscular servo mechanism; rather, it implies that the brain needs to acquire some internal models of controlled objects.

Development of Open Brain Simulator for Human Biomechatronics

NASA Astrophysics Data System (ADS)

Otake, Mihoko; Takagi, Toshihisa; Asama, Hajime

Modeling and simulation based on mechanisms is important in order to design and control mechatronic systems. In particular, in-depth understanding and realistic modeling of biological systems is indispensable for biomechatronics. This paper presents open brain simulator, which estimates the neural state of human through external measurement for the purpose of improving motor and social skills. Macroscopic anatomical nervous systems model was built which can be connected to the musculoskeletal model. Microscopic anatomical and physiological neural models were interfaced to the macroscopic model. Neural activities of somatosensory area and Purkinje cell were calculated from motion capture data. The simulator provides technical infrastructure for human biomechatronics, which is promising for the novel diagnosis of neurological disorders and their treatments through medication and movement therapy, and for motor learning support system supporting acquisition of motor skill considering neural mechanism.

Correlation of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine Neurotoxicity with Blood-Brain Barrier Monoamine Oxidase Activity

NASA Astrophysics Data System (ADS)

Kalaria, Rajesh N.; Mitchell, Mary Jo; Harik, Sami I.

1987-05-01

Systemic administration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) causes parkinsonism in humans and subhuman primates, but not in rats and many other laboratory animals; mice are intermediate in their susceptibility. Since MPTP causes selective dopaminergic neurotoxicity when infused directly into rat substantia nigra, we hypothesized that systemic MPTP may be metabolized by monoamine oxidase and/or other enzymes in rat brain capillaries and possibly other peripheral organs and thus prevented from reaching its neuronal sites of toxicity. We tested this hypothesis by assessing monoamine oxidase in isolated cerebral microvessels of humans, rats, and mice by measuring the specific binding of [3H]pargyline, an irreversible monoamine oxidase inhibitor, and by estimating the rates of MPTP and benzylamine oxidation. [3H]Pargyline binding to rat cerebral microvessels was about 10-fold higher than to human or mouse microvessels. Also, MPTP oxidation by rat brain microvessels was about 30-fold greater than by human microvessels; mouse microvessels yielded intermediate values. These results may explain, at least in part, the marked species differences in susceptibility to systemic MPTP. They also suggest the potential importance of ``enzyme barriers'' at the blood-brain interface that can metabolize toxins not excluded by structural barriers, and may provide biological bases for developing therapeutic strategies for the prevention of MPTP-induced neurotoxicity and other neurotoxic conditions including, possibly, Parkinson disease.

Dipole estimation errors due to not incorporating anisotropic conductivities in realistic head models for EEG source analysis

NASA Astrophysics Data System (ADS)

Hallez, Hans; Staelens, Steven; Lemahieu, Ignace

2009-10-01

EEG source analysis is a valuable tool for brain functionality research and for diagnosing neurological disorders, such as epilepsy. It requires a geometrical representation of the human head or a head model, which is often modeled as an isotropic conductor. However, it is known that some brain tissues, such as the skull or white matter, have an anisotropic conductivity. Many studies reported that the anisotropic conductivities have an influence on the calculated electrode potentials. However, few studies have assessed the influence of anisotropic conductivities on the dipole estimations. In this study, we want to determine the dipole estimation errors due to not taking into account the anisotropic conductivities of the skull and/or brain tissues. Therefore, head models are constructed with the same geometry, but with an anisotropically conducting skull and/or brain tissue compartment. These head models are used in simulation studies where the dipole location and orientation error is calculated due to neglecting anisotropic conductivities of the skull and brain tissue. Results show that not taking into account the anisotropic conductivities of the skull yields a dipole location error between 2 and 25 mm, with an average of 10 mm. When the anisotropic conductivities of the brain tissues are neglected, the dipole location error ranges between 0 and 5 mm. In this case, the average dipole location error was 2.3 mm. In all simulations, the dipole orientation error was smaller than 10°. We can conclude that the anisotropic conductivities of the skull have to be incorporated to improve the accuracy of EEG source analysis. The results of the simulation, as presented here, also suggest that incorporation of the anisotropic conductivities of brain tissues is not necessary. However, more studies are needed to confirm these suggestions.

Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.

PubMed

Lin, P-Y; Chao, T-C; Wu, M-L

2015-03-01

Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites. In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared. Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed. The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility. © 2015 by American Journal of Neuroradiology.

A population MRI brain template and analysis tools for the macaque.

PubMed

Seidlitz, Jakob; Sponheim, Caleb; Glen, Daniel; Ye, Frank Q; Saleem, Kadharbatcha S; Leopold, David A; Ungerleider, Leslie; Messinger, Adam

2018-04-15

The use of standard anatomical templates is common in human neuroimaging, as it facilitates data analysis and comparison across subjects and studies. For non-human primates, previous in vivo templates have lacked sufficient contrast to reliably validate known anatomical brain regions and have not provided tools for automated single-subject processing. Here we present the "National Institute of Mental Health Macaque Template", or NMT for short. The NMT is a high-resolution in vivo MRI template of the average macaque brain generated from 31 subjects, as well as a neuroimaging tool for improved data analysis and visualization. From the NMT volume, we generated maps of tissue segmentation and cortical thickness. Surface reconstructions and transformations to previously published digital brain atlases are also provided. We further provide an analysis pipeline using the NMT that automates and standardizes the time-consuming processes of brain extraction, tissue segmentation, and morphometric feature estimation for anatomical scans of individual subjects. The NMT and associated tools thus provide a common platform for precise single-subject data analysis and for characterizations of neuroimaging results across subjects and studies. Copyright © 2017 ElsevierCompany. All rights reserved.

Application of State-Space Smoothing to fMRI Data for Calculation of Lagged Transinformation between Human Brain Activations

NASA Astrophysics Data System (ADS)

Watanabe, Jobu

2009-09-01

Mutual information can be given a directional sense by introducing a time lag in one of the variables. In an author's previous study, to investigate the network dynamics of human brain regions, lagged transinformation (LTI) was introduced using time delayed mutual information. The LTI makes it possible to quantify the time course of dynamic information transfer between regions in the temporal domain. The LTI was applied to functional magnetic resonance imaging (fMRI) data involved in neural processing of the transformation and comparison from three-dimensional (3D) visual information to a two-dimensional (2D) location to calculate directed information flows between the activated brain regions. In the present study, for more precise estimation of LTI, Kalman filter smoothing was applied to the same fMRI data. Because the smoothing method exploits the full length of the time series data for the estimation, its application increases the precision. Large information flows were found from the bilateral prefrontal cortices to the parietal cortices. The results suggest that information of the 3D images stored as working memory was retrieved and transferred from the prefrontal cortices to the parietal cortices for comparison with information of the 2D images.

A model for brain life history evolution.

PubMed

González-Forero, Mauricio; Faulwasser, Timm; Lehmann, Laurent

2017-03-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain's energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting ("me vs nature"), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model's parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills.

T156. IN VIVO CHARACTERIZATION OF THE FIRST AGONIST DOPAMINE D1 RECEPTORS PET IMAGING TRACER [18F]MNI-968 IN HUMAN

PubMed Central

Tamagnan, Gilles; Barret, Olivier; Alagille, David; Carroll, Vincent; Madonia, Jennifer; Constantinescu, Cristian; SanDiego, Christine; Papin, Caroline; Morley, Thomas; Russell, David; McCarthy, Timothy; Zhang, Lei; Gray, David; Villalobos, Anna; Lee, Chewah; Chen, Jianqing; Seibyl, John; Marek, Kenneth

2018-01-01

Abstract Background D1 receptors, which couple to inhibitory G-proteins, have been shown to regulate neuronal growth and development, mediate some behavioral responses. Its function has been shown to be altered in both neurologic and psychiatric disorders. To date, there is a lack of agonist PET tracers for the D1 receptors labeled with 18F with relevance in clinical studies. We report the evaluation in non-human primates of [18F]MNI-968 (PF-06730110), a novel PET radiotracer of the D1 receptors Methods Four brain PET studies, 2 baselines and 2 blockade studies using PF-2562, a D1 partial agonist compound, were conducted for 90 min in two rhesus monkeys with [18F]MNI-968 (169 ± 31 MBq). [18F]PF-06730110 was administered at the same dose level for both monkeys as a bolus followed by a 2-hour infusion, with [18F]MNI-968 administered 30 min into the infusion. Additionally, six brain PET studies were conducted over 180 min (317 ± 49 MBq) in 6 healthy human volunteers (3 test/retest and 3 test). PET data were modeled with 2-tissue compartmental model (2T), Logan graphical analysis (LGA), and non-invasive Logan graphical analysis (NI-LGA) with cerebellar cortex as reference region to estimate total distribution volume VT, and binding potential BPND. For the blockade studies in rhesus monkeys, occupancy was estimated from BPND at baseline and post blockade. Results In rhesus monkeys, [18F]MNI-968 (PF-06730110), penetrated the brain with a peak whole-brain uptake up to ~3% of the injected dose at ~ 6 min post injection and showed a fast washout. The highest signal was found in the caudate, putamen, with moderate extrastriatal uptake. The lowest signal was in the cerebellum. BPND values were up to ~1.4 in the putamen. All three quantification methods (2T, LGA and NI-LGA) were in excellent agreement, with a similar estimated D1 receptors occupancy of PF-06730110 of ~40% for both monkeys in the caudate and putamen. In human, [18F]MNI-968 kinetics appeared to be faster compared to non-human primates, with a BPND in the putamen of ~0.8. Initial measurement of test-retest reproducibility was ≤ 7% for BPND in the striatal regions. Discussion Our work showed that [18F]MNI-968 ([18F]PF-06730110), is a promising agonist PET radiotracer for imaging D1agnist receptors that can be quantified non-invasively. Studies are currently ongoing both in non-human and human primates to further characterize the tracer.

Brain waves-based index for workload estimation and mental effort engagement recognition

NASA Astrophysics Data System (ADS)

Zammouri, A.; Chraa-Mesbahi, S.; Ait Moussa, A.; Zerouali, S.; Sahnoun, M.; Tairi, H.; Mahraz, A. M.

2017-10-01

The advent of the communication systems and considering the complexity that some impose in their use, it is necessary to incorporate and equip these systems with a certain intelligence which takes into account the cognitive and mental capacities of the human operator. In this work, we address the issue of estimating the mental effort of an operator according to the cognitive tasks difficulty levels. Based on the Electroencephalogram (EEG) measurements, the proposed approach analyzes the user’s brain activity from different brain regions while performing cognitive tasks with several levels of difficulty. At a first time, we propose a variances comparison-based classifier (VCC) that makes use of the Power Spectral Density (PSD) of the EEG signal. The aim of using such a classifier is to highlight the brain regions that enter into interaction according to the cognitive task difficulty. In a second time, we present and describe a new EEG-based index for the estimation of mental efforts. The designed index is based on information recorded from two EEG channels. Results from the VCC demonstrate that powers of the Theta [4-7 Hz] (θ) and Alpha [8-12 Hz] (α) oscillations decrease while increasing the cognitive task difficulty. These decreases are mainly located in parietal and temporal brain regions. Based on the Kappa coefficients, decisions of the introduced index are compared to those obtained from an existing index. This performance assessment method revealed strong agreements. Hence the efficiency of the introduced index.

A novel approach to quantify different iron forms in ex-vivo human brain tissue

NASA Astrophysics Data System (ADS)

Kumar, Pravin; Bulk, Marjolein; Webb, Andrew; van der Weerd, Louise; Oosterkamp, Tjerk H.; Huber, Martina; Bossoni, Lucia

2016-12-01

We propose a novel combination of methods to study the physical properties of ferric ions and iron-oxide nanoparticles in post-mortem human brain, based on the combination of Electron Paramagnetic Resonance (EPR) and SQUID magnetometry. By means of EPR, we derive the concentration of the low molecular weight iron pool, as well as the product of its electron spin relaxation times. Additionally, by SQUID magnetometry we identify iron mineralization products ascribable to a magnetite/maghemite phase and a ferrihydrite (ferritin) phase. We further derive the concentration of magnetite/maghemite and of ferritin nanoparticles. To test out the new combined methodology, we studied brain tissue of an Alzheimer’s patient and a healthy control. Finally, we estimate that the size of the magnetite/maghemite nanoparticles, whose magnetic moments are blocked at room temperature, exceeds 40-50 nm, which is not compatible with the ferritin protein, the core of which is typically 6-8 nm. We believe that this methodology could be beneficial in the study of neurodegenerative diseases such as Alzheimer’s Disease which are characterized by abnormal iron accumulation in the brain.

The study of evolution and depression of the alpha-rhythm in the human brain EEG by means of wavelet-based methods

NASA Astrophysics Data System (ADS)

Runnova, A. E.; Zhuravlev, M. O.; Khramova, M. V.; Pysarchik, A. N.

2017-04-01

We study the appearance, development and depression of the alpha-rhythm in human EEG data during a psychophysiological experiment by stimulating cognitive activity with the perception of ambiguous object. The new method based on continuous wavelet transform allows to estimate the energy contribution of various components, including the alpha rhythm, in the general dynamics of the electrical activity of the projections of various areas of the brain. The decision-making process by observe ambiguous images is characterized by specific oscillatory alfa-rhytm patterns in the multi-channel EEG data. We have shown the repeatability of detected principles of the alpha-rhythm evolution in a data of group of 12 healthy male volunteers.

Detecting event-related changes of multivariate phase coupling in dynamic brain networks.

PubMed

Canolty, Ryan T; Cadieu, Charles F; Koepsell, Kilian; Ganguly, Karunesh; Knight, Robert T; Carmena, Jose M

2012-04-01

Oscillatory phase coupling within large-scale brain networks is a topic of increasing interest within systems, cognitive, and theoretical neuroscience. Evidence shows that brain rhythms play a role in controlling neuronal excitability and response modulation (Haider B, McCormick D. Neuron 62: 171-189, 2009) and regulate the efficacy of communication between cortical regions (Fries P. Trends Cogn Sci 9: 474-480, 2005) and distinct spatiotemporal scales (Canolty RT, Knight RT. Trends Cogn Sci 14: 506-515, 2010). In this view, anatomically connected brain areas form the scaffolding upon which neuronal oscillations rapidly create and dissolve transient functional networks (Lakatos P, Karmos G, Mehta A, Ulbert I, Schroeder C. Science 320: 110-113, 2008). Importantly, testing these hypotheses requires methods designed to accurately reflect dynamic changes in multivariate phase coupling within brain networks. Unfortunately, phase coupling between neurophysiological signals is commonly investigated using suboptimal techniques. Here we describe how a recently developed probabilistic model, phase coupling estimation (PCE; Cadieu C, Koepsell K Neural Comput 44: 3107-3126, 2010), can be used to investigate changes in multivariate phase coupling, and we detail the advantages of this model over the commonly employed phase-locking value (PLV; Lachaux JP, Rodriguez E, Martinerie J, Varela F. Human Brain Map 8: 194-208, 1999). We show that the N-dimensional PCE is a natural generalization of the inherently bivariate PLV. Using simulations, we show that PCE accurately captures both direct and indirect (network mediated) coupling between network elements in situations where PLV produces erroneous results. We present empirical results on recordings from humans and nonhuman primates and show that the PCE-estimated coupling values are different from those using the bivariate PLV. Critically on these empirical recordings, PCE output tends to be sparser than the PLVs, indicating fewer significant interactions and perhaps a more parsimonious description of the data. Finally, the physical interpretation of PCE parameters is straightforward: the PCE parameters correspond to interaction terms in a network of coupled oscillators. Forward modeling of a network of coupled oscillators with parameters estimated by PCE generates synthetic data with statistical characteristics identical to empirical signals. Given these advantages over the PLV, PCE is a useful tool for investigating multivariate phase coupling in distributed brain networks.

Asymmetry of Hemispheric Network Topology Reveals Dissociable Processes between Functional and Structural Brain Connectome in Community-Living Elders

PubMed Central

Sun, Yu; Li, Junhua; Suckling, John; Feng, Lei

2017-01-01

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. PMID:29209197

INVITED REVIEW – NEUROIMAGING RESPONSE ASSESSMENT CRITERIA FOR BRAIN TUMORS IN VETERINARY PATIENTS

PubMed Central

Rossmeisl, John H.; Garcia, Paulo A.; Daniel, Gregory B.; Bourland, John Daniel; Debinski, Waldemar; Dervisis, Nikolaos; Klahn, Shawna

2013-01-01

The evaluation of therapeutic response using cross-sectional imaging techniques, particularly gadolinium-enhanced MRI, is an integral part of the clinical management of brain tumors in veterinary patients. Spontaneous canine brain tumors are increasingly recognized and utilized as a translational model for the study of human brain tumors. However, no standardized neuroimaging response assessment criteria have been formulated for use in veterinary clinical trials. Previous studies have found that the pathophysiologic features inherent to brain tumors and the surrounding brain complicate the use of the Response Evaluation Criteria in Solid Tumors (RECIST) assessment system. Objectives of this review are to describe strengths and limitations of published imaging-based brain tumor response criteria and propose a system for use in veterinary patients. The widely used human Macdonald and Response Assessment in Neuro-oncology (RANO) criteria are reviewed and described as to how they can be applied to veterinary brain tumors. Discussion points will include current challenges associated with the interpretation of brain tumor therapeutic responses such as imaging pseudophenomena and treatment-induced necrosis, and how advancements in perfusion imaging, positron emission tomography, and magnetic resonance spectroscopy have shown promise in differentiating tumor progression from therapy-induced changes. Finally, although objective endpoints such as MR-imaging and survival estimates will likely continue to comprise the foundations for outcome measures in veterinary brain tumor clinical trials, we propose that in order to provide a more relevant therapeutic response metric for veterinary patients, composite response systems should be formulated and validated that combine imaging and clinical assessment criteria. PMID:24219161

MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner.

PubMed

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B; Michel, Christian J; El Fakhri, Georges; Schmand, Matthias; Sorensen, A Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MRI data can be used for motion tracking. In this work, a novel algorithm for data processing and rigid-body motion correction (MC) for the MRI-compatible BrainPET prototype scanner is described, and proof-of-principle phantom and human studies are presented. To account for motion, the PET prompt and random coincidences and sensitivity data for postnormalization were processed in the line-of-response (LOR) space according to the MRI-derived motion estimates. The processing time on the standard BrainPET workstation is approximately 16 s for each motion estimate. After rebinning in the sinogram space, the motion corrected data were summed, and the PET volume was reconstructed using the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed, and motion estimates were obtained using 2 high-temporal-resolution MRI-based motion-tracking techniques. After accounting for the misalignment between the 2 scanners, perfectly coregistered MRI and PET volumes were reproducibly obtained. The MRI output gates inserted into the PET list-mode allow the temporal correlation of the 2 datasets within 0.2 ms. The Hoffman phantom volume reconstructed by processing the PET data in the LOR space was similar to the one obtained by processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the procedure. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 s and 20 ms, respectively. Motion-deblurred PET images, with excellent delineation of specific brain structures, were obtained using these 2 MRI-based estimates. An MRI-based MC algorithm was implemented for an integrated MR-PET scanner. High-temporal-resolution MRI-derived motion estimates (obtained while simultaneously acquiring anatomic or functional MRI data) can be used for PET MC. An MRI-based MC method has the potential to improve PET image quality, increasing its reliability, reproducibility, and quantitative accuracy, and to benefit many neurologic applications.

A model for brain life history evolution

PubMed Central

Lehmann, Laurent

2017-01-01

Complex cognition and relatively large brains are distributed across various taxa, and many primarily verbal hypotheses exist to explain such diversity. Yet, mathematical approaches formalizing verbal hypotheses would help deepen the understanding of brain and cognition evolution. With this aim, we combine elements of life history and metabolic theories to formulate a metabolically explicit mathematical model for brain life history evolution. We assume that some of the brain’s energetic expense is due to production (learning) and maintenance (memory) of energy-extraction skills (or cognitive abilities, knowledge, information, etc.). We also assume that individuals use such skills to extract energy from the environment, and can allocate this energy to grow and maintain the body, including brain and reproductive tissues. The model can be used to ask what fraction of growth energy should be allocated at each age, given natural selection, to growing brain and other tissues under various biological settings. We apply the model to find uninvadable allocation strategies under a baseline setting (“me vs nature”), namely when energy-extraction challenges are environmentally determined and are overcome individually but possibly with maternal help, and use modern-human data to estimate model’s parameter values. The resulting uninvadable strategies yield predictions for brain and body mass throughout ontogeny and for the ages at maturity, adulthood, and brain growth arrest. We find that: (1) a me-vs-nature setting is enough to generate adult brain and body mass of ancient human scale and a sequence of childhood, adolescence, and adulthood stages; (2) large brains are favored by intermediately challenging environments, moderately effective skills, and metabolically expensive memory; and (3) adult skill is proportional to brain mass when metabolic costs of memory saturate the brain metabolic rate allocated to skills. PMID:28278153

MR-visible water content in human brain: a proton MRS study.

PubMed

Christiansen, P; Toft, P B; Gideon, P; Danielsen, E R; Ring, P; Henriksen, O

1994-01-01

In vivo measurement of metabolite concentrations in the human brain by means of proton-MRS contributes significantly to the clinical evaluation of patients with diseases of the brain. The fully relaxed water signal has been proposed as an internal standard for calibration of the MRS measurements. The major drawbacks are the necessity to make the assumptions that the water concentrations in the brain and that all tissue water is MR-visible. A number of in vivo measurements were carried out to estimate the concentration of MR-visible water in the brain of healthy volunteers divided into four age groups: newborn (0-23 days), adolescents (10-15 yr), adults (22-28 yr), and elderly people (60-74 yr). The examinations were carried out using a Siemens Helicon SP 63/84 MR-scanner operating at 1.5 T. Except for the newborn, four regions were studied in each subject using stimulated echo (STEAM) sequences without water suppression. In vitro measurements on a standard phantom were used for calibration. The calculated water concentrations ranged between 35.8 and 39.6 (mean 36.9) mol.[kg wet weight]-1 in the three groups, whereas it was 51.5 mol.[kg wet weight]-1 in the newborn, p < .01. The observed water concentration of neither the four regions nor of the three oldest age groups were significantly different. Comparisons between the water concentrations measured and those expected based on estimation of the content of grey and white matter in the region of interest from T1-weighted images and biochemical data published, suggest that only a small fraction (< 5%) of the tissue water may be MR-invisible.(ABSTRACT TRUNCATED AT 250 WORDS)

Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

PubMed Central

Vanacker, Gerolf; Millán, José del R.; Lew, Eileen; Ferrez, Pierre W.; Moles, Ferran Galán; Philips, Johan; Van Brussel, Hendrik; Nuttin, Marnix

2007-01-01

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair. PMID:18354739

The challenge of mapping the human connectome based on diffusion tractography.

PubMed

Maier-Hein, Klaus H; Neher, Peter F; Houde, Jean-Christophe; Côté, Marc-Alexandre; Garyfallidis, Eleftherios; Zhong, Jidan; Chamberland, Maxime; Yeh, Fang-Cheng; Lin, Ying-Chia; Ji, Qing; Reddick, Wilburn E; Glass, John O; Chen, David Qixiang; Feng, Yuanjing; Gao, Chengfeng; Wu, Ye; Ma, Jieyan; Renjie, H; Li, Qiang; Westin, Carl-Fredrik; Deslauriers-Gauthier, Samuel; González, J Omar Ocegueda; Paquette, Michael; St-Jean, Samuel; Girard, Gabriel; Rheault, François; Sidhu, Jasmeen; Tax, Chantal M W; Guo, Fenghua; Mesri, Hamed Y; Dávid, Szabolcs; Froeling, Martijn; Heemskerk, Anneriet M; Leemans, Alexander; Boré, Arnaud; Pinsard, Basile; Bedetti, Christophe; Desrosiers, Matthieu; Brambati, Simona; Doyon, Julien; Sarica, Alessia; Vasta, Roberta; Cerasa, Antonio; Quattrone, Aldo; Yeatman, Jason; Khan, Ali R; Hodges, Wes; Alexander, Simon; Romascano, David; Barakovic, Muhamed; Auría, Anna; Esteban, Oscar; Lemkaddem, Alia; Thiran, Jean-Philippe; Cetingul, H Ertan; Odry, Benjamin L; Mailhe, Boris; Nadar, Mariappan S; Pizzagalli, Fabrizio; Prasad, Gautam; Villalon-Reina, Julio E; Galvis, Justin; Thompson, Paul M; Requejo, Francisco De Santiago; Laguna, Pedro Luque; Lacerda, Luis Miguel; Barrett, Rachel; Dell'Acqua, Flavio; Catani, Marco; Petit, Laurent; Caruyer, Emmanuel; Daducci, Alessandro; Dyrby, Tim B; Holland-Letz, Tim; Hilgetag, Claus C; Stieltjes, Bram; Descoteaux, Maxime

2017-11-07

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

Estimation of State Transition Probabilities: A Neural Network Model

NASA Astrophysics Data System (ADS)

Saito, Hiroshi; Takiyama, Ken; Okada, Masato

2015-12-01

Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.

Sparse EEG/MEG source estimation via a group lasso

PubMed Central

Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

2017-01-01

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches. PMID:28604790

Risk and protective factors for structural brain ageing in the eighth decade of life.

PubMed

Ritchie, Stuart J; Tucker-Drob, Elliot M; Cox, Simon R; Dickie, David Alexander; Del C Valdés Hernández, Maria; Corley, Janie; Royle, Natalie A; Redmond, Paul; Muñoz Maniega, Susana; Pattie, Alison; Aribisala, Benjamin S; Taylor, Adele M; Clarke, Toni-Kim; Gow, Alan J; Starr, John M; Bastin, Mark E; Wardlaw, Joanna M; Deary, Ian J

2017-11-01

Individuals differ markedly in brain structure, and in how this structure degenerates during ageing. In a large sample of human participants (baseline n = 731 at age 73 years; follow-up n = 488 at age 76 years), we estimated the magnitude of mean change and variability in changes in MRI measures of brain macrostructure (grey matter, white matter, and white matter hyperintensity volumes) and microstructure (fractional anisotropy and mean diffusivity from diffusion tensor MRI). All indices showed significant average change with age, with considerable heterogeneity in those changes. We then tested eleven socioeconomic, physical, health, cognitive, allostatic (inflammatory and metabolic), and genetic variables for their value in predicting these differences in changes. Many of these variables were significantly correlated with baseline brain structure, but few could account for significant portions of the heterogeneity in subsequent brain change. Physical fitness was an exception, being correlated both with brain level and changes. The results suggest that only a subset of correlates of brain structure are also predictive of differences in brain ageing.

Uniform distributions of glucose oxidation and oxygen extraction in gray matter of normal human brain: No evidence of regional differences of aerobic glycolysis.

PubMed

Hyder, Fahmeed; Herman, Peter; Bailey, Christopher J; Møller, Arne; Globinsky, Ronen; Fulbright, Robert K; Rothman, Douglas L; Gjedde, Albert

2016-05-01

Regionally variable rates of aerobic glycolysis in brain networks identified by resting-state functional magnetic resonance imaging (R-fMRI) imply regionally variable adenosine triphosphate (ATP) regeneration. When regional glucose utilization is not matched to oxygen delivery, affected regions have correspondingly variable rates of ATP and lactate production. We tested the extent to which aerobic glycolysis and oxidative phosphorylation power R-fMRI networks by measuring quantitative differences between the oxygen to glucose index (OGI) and the oxygen extraction fraction (OEF) as measured by positron emission tomography (PET) in normal human brain (resting awake, eyes closed). Regionally uniform and correlated OEF and OGI estimates prevailed, with network values that matched the gray matter means, regardless of size, location, and origin. The spatial agreement between oxygen delivery (OEF≈0.4) and glucose oxidation (OGI ≈ 5.3) suggests that no specific regions have preferentially high aerobic glycolysis and low oxidative phosphorylation rates, with globally optimal maximum ATP turnover rates (VATP ≈ 9.4 µmol/g/min), in good agreement with (31)P and (13)C magnetic resonance spectroscopy measurements. These results imply that the intrinsic network activity in healthy human brain powers the entire gray matter with ubiquitously high rates of glucose oxidation. Reports of departures from normal brain-wide homogeny of oxygen extraction fraction and oxygen to glucose index may be due to normalization artefacts from relative PET measurements. © The Author(s) 2016.

Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization.

PubMed

Beckmann, Matthias; Johansen-Berg, Heidi; Rushworth, Matthew F S

2009-01-28

Whole-brain neuroimaging studies have demonstrated regional variations in function within human cingulate cortex. At the same time, regional variations in cingulate anatomical connections have been found in animal models. It has, however, been difficult to estimate the relationship between connectivity and function throughout the whole cingulate cortex within the human brain. In this study, magnetic resonance diffusion tractography was used to investigate cingulate probabilistic connectivity in the human brain with two approaches. First, an algorithm was used to search for regional variations in the probabilistic connectivity profiles of all cingulate cortex voxels with the whole of the rest of the brain. Nine subregions with distinctive connectivity profiles were identified. It was possible to characterize several distinct areas in the dorsal cingulate sulcal region. Several distinct regions were also found in subgenual and perigenual cortex. Second, the probabilities of connection between cingulate cortex and 11 predefined target regions of interest were calculated. Cingulate voxels with a high probability of connection with the different targets formed separate clusters within cingulate cortex. Distinct connectivity fingerprints characterized the likelihood of connections between the extracingulate target regions and the nine cingulate subregions. Last, a meta-analysis of 171 functional studies reporting cingulate activation was performed. Seven different cognitive conditions were selected and peak activation coordinates were plotted to create maps of functional localization within the cingulate cortex. Regional functional specialization was found to be related to regional differences in probabilistic anatomical connectivity.

Experimental considerations for fast kurtosis imaging.

PubMed

Hansen, Brian; Lund, Torben E; Sangill, Ryan; Stubbe, Ebbe; Finsterbusch, Jürgen; Jespersen, Sune Nørhøj

2016-11-01

The clinical use of kurtosis imaging is impeded by long acquisitions and postprocessing. Recently, estimation of mean kurtosis tensor W¯ and mean diffusivity ( D¯) was made possible from 13 distinct diffusion weighted MRI acquisitions (the 1-3-9 protocol) with simple postprocessing. Here, we analyze the effects of noise and nonideal diffusion encoding, and propose a new correction strategy. We also present a 1-9-9 protocol with increased robustness to experimental imperfections and minimal additional scan time. This refinement does not affect computation time and also provides a fast estimate of fractional anisotropy (FA). 1-3-9/1-9-9 data are acquired in rat and human brains, and estimates of D¯, FA, W¯ from human brains are compared with traditional estimates from an extensive diffusion kurtosis imaging data set. Simulations are used to evaluate the influence of noise and diffusion encodings deviating from the scheme, and the performance of the correction strategy. Optimal b-values are determined from simulations and data. Accuracy and precision in D¯ and W¯ are comparable to nonlinear least squares estimation, and is improved with the 1-9-9 protocol. The compensation strategy vastly improves parameter estimation in nonideal data. The framework offers a robust and compact method for estimating several diffusion metrics. The protocol is easily implemented. Magn Reson Med 76:1455-1468, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.

Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling

ERIC Educational Resources Information Center

Price, Larry R.; Laird, Angela R.; Fox, Peter T.; Ingham, Roger J.

2009-01-01

The aims of this study were to present a method for developing a path analytic network model using data acquired from positron emission tomography. Regions of interest within the human brain were identified through quantitative activation likelihood estimation meta-analysis. Using this information, a "true" or population path model was then…

A mathematical model for human brain cooling during cold-water near-drowning.

PubMed

Xu, X; Tikuisis, P; Giesbrecht, G

1999-01-01

A two-dimensional mathematical model was developed to estimate the contributions of different mechanisms of brain cooling during cold-water near-drowning. Mechanisms include 1) conductive heat loss through tissue to the water at the head surface and in the upper airway and 2) circulatory cooling to aspirated water via the lung and via venous return from the scalp. The model accounts for changes in boundary conditions, blood circulation, respiratory ventilation of water, and head size. Results indicate that conductive heat loss through the skull surface or the upper airways is minimal, although a small child-sized head will conductively cool faster than a large adult-sized head. However, ventilation of cold water may provide substantial brain cooling through circulatory cooling. Although it seems that water breathing is required for rapid "whole" brain cooling, it is possible that conductive cooling may provide some advantage by cooling the brain cortex peripherally and the brain stem centrally via the upper airway.

Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping.

PubMed

Zhang, Yuyao; Wei, Hongjiang; Cronin, Matthew J; He, Naying; Yan, Fuhua; Liu, Chunlei

2018-05-01

Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1-83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases. Copyright © 2018 Elsevier Inc. All rights reserved.

Appraising the Role of Iron in Brain Aging and Cognition: Promises and Limitations of MRI Methods

PubMed Central

Daugherty, Ana M; Raz, Naftali

2015-01-01

Age-related increase in frailty is accompanied by a fundamental shift in cellular iron homeostasis. By promoting oxidative stress, the intracellular accumulation of non-heme iron outside of binding complexes contributes to chronic inflammation and interferes with normal brain metabolism. In the absence of direct non-invasive biomarkers of brain oxidative stress, iron accumulation estimated in vivo may serve as its proxy indicator. Hence, developing reliable in vivo measurements of brain iron content via magnetic resonance imaging (MRI) is of significant interest in human neuroscience. To date, by estimating brain iron content through various MRI methods, significant age differences and age-related increases in iron content of the basal ganglia have been revealed across multiple samples. Less consistent are the findings that pertain to the relationship between elevated brain iron content and systemic indices of vascular and metabolic dysfunction. Only a handful of cross-sectional investigations have linked high iron content in various brain regions and poor performance on assorted cognitive tests. The even fewer longitudinal studies indicate that iron accumulation may precede shrinkage of the basal ganglia and thus predict poor maintenance of cognitive functions. This rapidly developing field will benefit from introduction of higher-field MRI scanners, improvement in iron-sensitive and -specific acquisition sequences and post-processing analytic and computational methods, as well as accumulation of data from long-term longitudinal investigations. This review describes the potential advantages and promises of MRI-based assessment of brain iron, summarizes recent findings and highlights the limitations of the current methodology. PMID:26248580

Epigenetic Age Acceleration Assessed with Human White-Matter Images.

PubMed

Hodgson, Karen; Carless, Melanie A; Kulkarni, Hemant; Curran, Joanne E; Sprooten, Emma; Knowles, Emma E; Mathias, Samuel; Göring, Harald H H; Yao, Nailin; Olvera, Rene L; Fox, Peter T; Almasy, Laura; Duggirala, Ravi; Blangero, John; Glahn, David C

2017-05-03

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample ( n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρ pheno = -0.119, p = 0.028), with evidence of shared genetic (ρ gene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging. SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging. Copyright © 2017 the authors 0270-6474/17/374735-09$15.00/0.

["Dieu et cerveau, rien que Dieu et cerveau!" Johann Gottfried von Herder (1744-1803) and the neurosciences of this time].

PubMed

Stahnisch, Frank

2007-01-01

The impact of Johann Gottfried von Herder on the broad spectrum of the history of ideas can hardly be estimated by separate categories derived from individual disciplines. It transcends the spheres of philosophy, theology, historiography and even medical anthropology--also because Herder, unlike many of his contemporary philosophers and hommes de lettres, was particularly interested in the neurophysiological and -anatomical investigations of his time. Herder's universal interest in human learning is reflected in numerous personal contacts to contemporary academic scholars and natural scientists, such as the Swiss theologian Johann Caspar Lavater, whose physiognomic doctrine mapped out a comprehensive research programme on character analysis, or the Mainz anatomist Samuel Thomas von Soemmering. Herder tightly received the latter's assumption about the interplay between the human soul and the anatomy of the brain. In this article, it shall be demonstrated that Herder's neurophilosophy was primarily influenced by a "pandynamic assumption of nature" and that it designated the brain centrally as a "working tool of God"--right between the human faculties of rationality, feeling and bodily development. The attractiveness of this concept to both basic brain research and clinical neurology was a result of his anthropological approach which combined latest developments in the natural sciences with a central perspective on the human sciences.

Joint Maximum Likelihood Time Delay Estimation of Unknown Event-Related Potential Signals for EEG Sensor Signal Quality Enhancement

PubMed Central

Kim, Kyungsoo; Lim, Sung-Ho; Lee, Jaeseok; Kang, Won-Seok; Moon, Cheil; Choi, Ji-Woong

2016-01-01

Electroencephalograms (EEGs) measure a brain signal that contains abundant information about the human brain function and health. For this reason, recent clinical brain research and brain computer interface (BCI) studies use EEG signals in many applications. Due to the significant noise in EEG traces, signal processing to enhance the signal to noise power ratio (SNR) is necessary for EEG analysis, especially for non-invasive EEG. A typical method to improve the SNR is averaging many trials of event related potential (ERP) signal that represents a brain’s response to a particular stimulus or a task. The averaging, however, is very sensitive to variable delays. In this study, we propose two time delay estimation (TDE) schemes based on a joint maximum likelihood (ML) criterion to compensate the uncertain delays which may be different in each trial. We evaluate the performance for different types of signals such as random, deterministic, and real EEG signals. The results show that the proposed schemes provide better performance than other conventional schemes employing averaged signal as a reference, e.g., up to 4 dB gain at the expected delay error of 10°. PMID:27322267

Sparse and Adaptive Diffusion Dictionary (SADD) for recovering intra-voxel white matter structure.

PubMed

Aranda, Ramon; Ramirez-Manzanares, Alonso; Rivera, Mariano

2015-12-01

On the analysis of the Diffusion-Weighted Magnetic Resonance Images, multi-compartment models overcome the limitations of the well-known Diffusion Tensor model for fitting in vivo brain axonal orientations at voxels with fiber crossings, branching, kissing or bifurcations. Some successful multi-compartment methods are based on diffusion dictionaries. The diffusion dictionary-based methods assume that the observed Magnetic Resonance signal at each voxel is a linear combination of the fixed dictionary elements (dictionary atoms). The atoms are fixed along different orientations and diffusivity profiles. In this work, we present a sparse and adaptive diffusion dictionary method based on the Diffusion Basis Functions Model to estimate in vivo brain axonal fiber populations. Our proposal overcomes the following limitations of the diffusion dictionary-based methods: the limited angular resolution and the fixed shapes for the atom set. We propose to iteratively re-estimate the orientations and the diffusivity profile of the atoms independently at each voxel by using a simplified and easier-to-solve mathematical approach. As a result, we improve the fitting of the Diffusion-Weighted Magnetic Resonance signal. The advantages with respect to the former Diffusion Basis Functions method are demonstrated on the synthetic data-set used on the 2012 HARDI Reconstruction Challenge and in vivo human data. We demonstrate that improvements obtained in the intra-voxel fiber structure estimations benefit brain research allowing to obtain better tractography estimations. Hence, these improvements result in an accurate computation of the brain connectivity patterns. Copyright © 2015 Elsevier B.V. All rights reserved.

Devices for noninvasive transcranial electrostimulation of the brain endorphinergic system: application for improvement of human psycho-physiological status.

PubMed

Lebedev, Valery P; Malygin, A V; Kovalevski, A V; Rychkova, S V; Sisoev, V N; Kropotov, S P; Krupitski, E M; Gerasimova, L I; Glukhov, D V; Kozlowski, G P

2002-03-01

It is well known that deficit of endorphins plays an important role in disturbances of human psycho-physiological status. Previously, we revealed that brain endorphinergic structures have quasiresonance characteristics. On the basis of these data, a method of activation of the brain endorphinergic structures by means of noninvasive and rather selective transcranial electrostimulation (TES) as a kind of functional electrical stimulation (FES) was elaborated. New models of TES devices (TRANSAIR) were developed for indoor and outdoor usage. To increase the efficacy of TES, the frequency modulation according to normal distribution in the limits of the quasiresonance characteristics was put into operation. The blind and placebo-controlled (passive and active placebo) study was produced to estimate the TES effects on stress events and accompanied psycho-physiological and autonomic disturbances of different intensities on volunteers and patients in the following groups: everyday stress and fatigue; stress in regular military service and in field conditions; stress in the relatives of those lost in mass disaster; posttraumatic stress (thermal burns); and affective disorders in a postabstinence period. Some subjective verbal and nonverbal tests and objective tests (including heart rate variability) were used for estimation of the initial level of psycho-physiological status, which changes after TES sessions. It was demonstrated that fatigue, stress, and other accompanied psycho-physiological disturbances were significantly improved or abolished after 2-5 TES sessions. The TES effects were more pronounced in cases of heavier disturbances. In conclusion, activation of the brain endorphinergic structures by TES is an effective homeostatic method of FES that sufficiently improves quality of life.

Brain networks for confidence weighting and hierarchical inference during probabilistic learning

PubMed Central

Meyniel, Florent; Dehaene, Stanislas

2017-01-01

Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This “confidence weighting” implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain’s learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences. PMID:28439014

Red and NIR light dosimetry in the human deep brain

NASA Astrophysics Data System (ADS)

Pitzschke, A.; Lovisa, B.; Seydoux, O.; Zellweger, M.; Pfleiderer, M.; Tardy, Y.; Wagnières, G.

2015-04-01

Photobiomodulation (PBM) appears promising to treat the hallmarks of Parkinson’s Disease (PD) in cellular or animal models. We measured light propagation in different areas of PD-relevant deep brain tissue during transcranial, transsphenoidal illumination (at 671 and 808 nm) of a cadaver head and modeled optical parameters of human brain tissue using Monte-Carlo simulations. Gray matter, white matter, cerebrospinal fluid, ventricles, thalamus, pons, cerebellum and skull bone were processed into a mesh of the skull (158 × 201 × 211 voxels; voxel side length: 1 mm). Optical parameters were optimized from simulated and measured fluence rate distributions. The estimated μeff for the different tissues was in all cases larger at 671 than at 808 nm, making latter a better choice for light delivery in the deep brain. Absolute values were comparable to those found in the literature or slightly smaller. The effective attenuation in the ventricles was considerably larger than literature values. Optimization yields a new set of optical parameters better reproducing the experimental data. A combination of PBM via the sphenoid sinus and oral cavity could be beneficial. A 20-fold higher efficiency of light delivery to the deep brain was achieved with ventricular instead of transcranial illumination. Our study demonstrates that it is possible to illuminate deep brain tissues transcranially, transsphenoidally and via different application routes. This opens therapeutic options for sufferers of PD or other cerebral diseases necessitating light therapy.

Idiothetic input into object-place configuration as the contribution to memory of the monkey and human hippocampus: a review.

PubMed

Gaffan, D

1998-11-01

Memory for object-place configurations appears to be a common function of the hippocampus in the human and monkey brain. The nature of the spatial information which enters into these object-configural memories in the primate, and the location of the memories themselves, have remained obscure, however. In the rat, much evidence indicates that the hippocampus processes idiothetic spatial information, an estimate of the animal's current environmental location derived from path integration. I propose that in primates the hippocampus provides idiothetic information about the environmental location of body parts, and that the main function of this information in the primate brain is to become configured with object-identity information provided by temporal lobe cortex outside the hippocampus.

Olfactory deposition of inhaled nanoparticles in humans

PubMed Central

Garcia, Guilherme J. M.; Schroeter, Jeffry D.; Kimbell, Julia S.

2016-01-01

Context Inhaled nanoparticles can migrate to the brain via the olfactory bulb, as demonstrated in experiments in several animal species. This route of exposure may be the mechanism behind the correlation between air pollution and human neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease. Objectives This manuscript aims to (1) estimate the dose of inhaled nanoparticles that deposit in the human olfactory epithelium during nasal breathing at rest and (2) compare the olfactory dose in humans with our earlier dose estimates for rats. Materials and methods An anatomically-accurate model of the human nasal cavity was developed based on computed tomography scans. The deposition of 1–100 nm particles in the whole nasal cavity and its olfactory region were estimated via computational fluid dynamics (CFD) simulations. Our CFD methods were validated by comparing our numerical predictions for whole-nose deposition with experimental data and previous CFD studies in the literature. Results In humans, olfactory dose of inhaled nanoparticles is highest for 1–2 nm particles with approximately 1% of inhaled particles depositing in the olfactory region. As particle size grows to 100 nm, olfactory deposition decreases to 0.01% of inhaled particles. Discussion and conclusion Our results suggest that the percentage of inhaled particles that deposit in the olfactory region is lower in humans than in rats. However, olfactory dose per unit surface area is estimated to be higher in humans due to their larger minute volume. These dose estimates are important for risk assessment and dose-response studies investigating the neurotoxicity of inhaled nanoparticles. PMID:26194036

A quantitative magnetic resonance histology atlas of postnatal rat brain development with regional estimates of growth and variability.

PubMed

Calabrese, Evan; Badea, Alexandra; Watson, Charles; Johnson, G Allan

2013-05-01

There has been growing interest in the role of postnatal brain development in the etiology of several neurologic diseases. The rat has long been recognized as a powerful model system for studying neuropathology and the safety of pharmacologic treatments. However, the complex spatiotemporal changes that occur during rat neurodevelopment remain to be elucidated. This work establishes the first magnetic resonance histology (MRH) atlas of the developing rat brain, with an emphasis on quantitation. The atlas comprises five specimens at each of nine time points, imaged with eight distinct MR contrasts and segmented into 26 developmentally defined brain regions. The atlas was used to establish a timeline of morphometric changes and variability throughout neurodevelopment and represents a quantitative database of rat neurodevelopment for characterizing rat models of human neurologic disease. Published by Elsevier Inc.

Hemicholinium-3 sensitive choline transport in human T lymphocytes: Evidence for use as a proxy for brain choline transporter (CHT) capacity.

PubMed

Koshy Cherian, Ajeesh; Parikh, Vinay; Wu, Qi; Mao-Draayer, Yang; Wang, Qin; Blakely, Randy D; Sarter, Martin

2017-09-01

The synaptic uptake of choline via the high-affinity, hemicholinium-3-dependent choline transporter (CHT) strongly influences the capacity of cholinergic neurons to sustain acetylcholine (ACh) synthesis and release. To advance research on the impact of CHT capacity in humans, we established the presence of the neuronal CHT protein in human T lymphocytes. Next, we demonstrated CHT-mediated choline transport in human T cells. To address the validity of T cell-based choline uptake as a proxy for brain CHT capacity, we isolated T cells from the spleen, and synaptosomes from cortex and striatum, of wild type and CHT-overexpressing mice (CHT-OXP). Choline uptake capacity in T cells from CHT-OXP mice was two-fold higher than in wild type mice, mirroring the impact of CHT over-expression on synaptosomal CHT-mediated choline uptake. Monitoring T lymphocyte CHT protein and activity may be useful for estimating human CNS cholinergic capacity and for testing hypotheses concerning the contribution of CHT and, more generally, ACh signaling in cognition, neuroinflammation and disease. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brain correlates of autonomic modulation: combining heart rate variability with fMRI.

PubMed

Napadow, Vitaly; Dhond, Rupali; Conti, Giulia; Makris, Nikos; Brown, Emery N; Barbieri, Riccardo

2008-08-01

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A.R., Melcher, J.R., et al., 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33-41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

Biomechanical Analysis of Normal Brain Development during the First Year of Life Using Finite Strain Theory.

PubMed

Kim, Jeong Chul; Wang, Li; Shen, Dinggang; Lin, Weili

2016-12-02

The first year of life is the most critical time period for structural and functional development of the human brain. Combining longitudinal MR imaging and finite strain theory, this study aimed to provide new insights into normal brain development through a biomechanical framework. Thirty-three normal infants were longitudinally imaged using MRI from 2 weeks to 1 year of age. Voxel-wise Jacobian determinant was estimated to elucidate volumetric changes while Lagrange strains (both normal and shear strains) were measured to reveal directional growth information every 3 months during the first year of life. Directional normal strain maps revealed that, during the first 6 months, the growth pattern of gray matter is anisotropic and spatially inhomogeneous with higher left-right stretch around the temporal lobe and interhemispheric fissure, anterior-posterior stretch in the frontal and occipital lobes, and superior-inferior stretch in right inferior occipital and right inferior temporal gyri. In contrast, anterior lateral ventricles and insula showed an isotropic stretch pattern. Volumetric and directional growth rates were linearly decreased with age for most of the cortical regions. Our results revealed anisotropic and inhomogeneous brain growth patterns of the human brain during the first year of life using longitudinal MRI and a biomechanical framework.

Fossil skulls reveal that blood flow rate to the brain increased faster than brain volume during human evolution

NASA Astrophysics Data System (ADS)

Seymour, Roger S.; Bosiocic, Vanya; Snelling, Edward P.

2016-08-01

The evolution of human cognition has been inferred from anthropological discoveries and estimates of brain size from fossil skulls. A more direct measure of cognition would be cerebral metabolic rate, which is proportional to cerebral blood flow rate (perfusion). The hominin cerebrum is supplied almost exclusively by the internal carotid arteries. The sizes of the foramina that transmitted these vessels in life can be measured in hominin fossil skulls and used to calculate cerebral perfusion rate. Perfusion in 11 species of hominin ancestors, from Australopithecus to archaic Homo sapiens, increases disproportionately when scaled against brain volume (the allometric exponent is 1.41). The high exponent indicates an increase in the metabolic intensity of cerebral tissue in later Homo species, rather than remaining constant (1.0) as expected by a linear increase in neuron number, or decreasing according to Kleiber's Law (0.75). During 3 Myr of hominin evolution, cerebral tissue perfusion increased 1.7-fold, which, when multiplied by a 3.5-fold increase in brain size, indicates a 6.0-fold increase in total cerebral blood flow rate. This is probably associated with increased interneuron connectivity, synaptic activity and cognitive function, which all ultimately depend on cerebral metabolic rate.

Rapid simultaneous high-resolution mapping of myelin water fraction and relaxation times in human brain using BMC-mcDESPOT.

PubMed

Bouhrara, Mustapha; Spencer, Richard G

2017-02-15

A number of central nervous system (CNS) diseases exhibit changes in myelin content and magnetic resonance longitudinal, T 1 , and transverse, T 2 , relaxation times, which therefore represent important biomarkers of CNS pathology. Among the methods applied for measurement of myelin water fraction (MWF) and relaxation times, the multicomponent driven equilibrium single pulse observation of T 1 and T 2 (mcDESPOT) approach is of particular interest. mcDESPOT permits whole brain mapping of multicomponent T 1 and T 2 , with data acquisition accomplished within a clinically realistic acquisition time. Unfortunately, previous studies have indicated the limited performance of mcDESPOT in the setting of the modest signal-to-noise range of high-resolution mapping, required for the depiction of small structures and to reduce partial volume effects. Recently, we showed that a new Bayesian Monte Carlo (BMC) analysis substantially improved determination of MWF from mcDESPOT imaging data. However, our previous study was limited in that it did not discuss determination of relaxation times. Here, we extend the BMC analysis to the simultaneous determination of whole-brain MWF and relaxation times using the two-component mcDESPOT signal model. Simulation analyses and in-vivo human brain studies indicate the overall greater performance of this approach compared to the stochastic region contraction (SRC) algorithm, conventionally used to derive parameter estimates from mcDESPOT data. SRC estimates of the transverse relaxation time of the long T 2 fraction, T 2,l , and the longitudinal relaxation time of the short T 1 fraction, T 1,s , clustered towards the lower and upper parameter search space limits, respectively, indicating failure of the fitting procedure. We demonstrate that this effect is absent in the BMC analysis. Our results also showed improved parameter estimation for BMC as compared to SRC for high-resolution mapping. Overall we find that the combination of BMC analysis and mcDESPOT, BMC-mcDESPOT, shows excellent performance for accurate high-resolution whole-brain mapping of MWF and bi-component transverse and longitudinal relaxation times within a clinically realistic acquisition time. Published by Elsevier Inc.

Physiological and modeling evidence for focal transcranial electrical brain stimulation in humans: A basis for high-definition tDCS

PubMed Central

Edwards, Dylan; Cortes, Mar; Datta, Abhishek; Minhas, Preet; Wassermann, Eric M.; Bikson, Marom

2015-01-01

Transcranial Direct Current Stimulation (tDCS) is a non-invasive, low-cost, well-tolerated technique producing lasting modulation of cortical excitability. Behavioral and therapeutic outcomes of tDCS are linked to the targeted brain regions, but there is little evidence that current reaches the brain as intended. We aimed to: (1) validate a computational model for estimating cortical electric fields in human transcranial stimulation, and (2) assess the magnitude and spread of cortical electric field with a novel High-Definition tDCS (HD-tDCS) scalp montage using a 4×1-Ring electrode configuration. In three healthy adults, Transcranial Electrical Stimulation (TES) over primary motor cortex (M1) was delivered using the 4×1 montage (4× cathode, surrounding a single central anode; montage radius ~3 cm) with sufficient intensity to elicit a discrete muscle twitch in the hand. The estimated current distribution in M1 was calculated using the individualized MRI-based model, and compared with the observed motor response across subjects. The response magnitude was quantified with stimulation over motor cortex as well as anterior and posterior to motor cortex. In each case the model data were consistent with the motor response across subjects. The estimated cortical electric fields with the 4×1 montage were compared (area, magnitude, direction) for TES and tDCS in each subject. We provide direct evidence in humans that TES with a 4×1-Ring configuration can activate motor cortex and that current does not substantially spread outside the stimulation area. Computational models predict that both TES and tDCS waveforms using the 4×1-Ring configuration generate electric fields in cortex with comparable gross current distribution, and preferentially directed normal (inward) currents. The agreement of modeling and experimental data for both current delivery and focality support the use of the HD-tDCS 4×1-Ring montage for cortically targeted neuromodulation. PMID:23370061

Heritability of volumetric brain changes and height in children entering puberty.

PubMed

van Soelen, Inge L C; Brouwer, Rachel M; van Baal, G Caroline M; Schnack, Hugo G; Peper, Jiska S; Chen, Lei; Kahn, René S; Boomsma, Dorret I; Hulshoff Pol, Hilleke E

2013-03-01

The human brain undergoes structural changes in children entering puberty, while simultaneously children increase in height. It is not known if brain changes are under genetic control, and whether they are related to genetic factors influencing the amount of overall increase in height. Twins underwent magnetic resonance imaging brain scans at age 9 (N = 190) and 12 (N = 125). High heritability estimates were found at both ages for height and brain volumes (49-96%), and high genetic correlation between ages were observed (r(g) > 0.89). With increasing age, whole brain (+1.1%), cerebellum (+4.2%), cerebral white matter (+5.1%), and lateral ventricle (+9.4%) volumes increased, and third ventricle (-4.0%) and cerebral gray matter (-1.6%) volumes decreased. Children increased on average 13.8 cm in height (9.9%). Genetic influences on individual difference in volumetric brain and height changes were estimated, both within and across traits. The same genetic factors influenced both cerebral (20% heritable) and cerebellar volumetric changes (45%). Thus, the extent to which changes in cerebral and cerebellar volumes are heritable in children entering puberty are due to the same genes that influence change in both structures. The increase in height was heritable (73%), and not associated with cerebral volumetric change, but positively associated with cerebellar volume change (r(p) = 0.24). This association was explained by a genetic correlation (r(g) = 0.48) between height and cerebellar change. Brain and body each expand at their own pace and through separate genetic pathways. There are distinct genetic processes acting on structural brain development, which cannot be explained by genetic increase in height. Copyright © 2011 Wiley Periodicals, Inc.

Safety evaluation of mercury based Ayurvedic formulation (Sidh Makardhwaj) on brain cerebrum, liver & kidney in rats

PubMed Central

Kumar, Gajendra; Srivastava, Amita; Sharma, Surinder Kumar; Gupta, Yogendra Kumar

2014-01-01

Background & objectives: Sidh Makardhwaj (SM) is a mercury based Ayurvedic formulation used in rheumatoid arthritis and neurological disorders. However, toxicity concerns due to mercury content are often raised. Therefore, the present study was carried out to evaluate the effect of SM on brain cerebrum, liver and kidney in rats. Methods: Graded doses of SM (10, 50, 100 mg/kg), mercuric chloride (1 mg/kg) and normal saline were administered orally to male Wistar rats for 28 days. Behavioural parameters were assessed on days 1, 7, 14 and 28 using Morris water maze, passive avoidance, elevated plus maze and rota rod. Liver and kidney function tests were done on day 28. Animals were sacrificed and brain cerebrum acetylcholinesterase activity, levels of malondialdehyde (MDA), reduced glutathione (GSH) in brain cerebrum, liver, kidney were estimated. The levels of mercury in brain cerebrum, liver and kidney were estimated and histopathology of these tissues was also performed. Results: SM in the doses used did not cause significant change in neurobehavioural parameters, brain cerebrum AChE activity, liver (ALT, AST, ALP bilirubin) and kidney (serum urea and creatinine) function tests as compared to control. The levels of mercury in brain cerebrum, liver, and kidney were found to be raised in dose dependent manner. However, the levels of MDA and GSH in these tissues did not show significant changes at doses of 10 and 50 mg/kg. Also, there was no histopathological change in cytoarchitecture of brain cerebrum, liver, and kidney tissues at doses of 10 and 50 mg/kg. Interpretation & conclusions: The findings of the present study suggest that Sidh Makardhwaj upto five times the equivalent human dose administered for 28 days did not show any toxicological effects on rat brain cerebrum, liver and kidney. PMID:24927349

Safety evaluation of mercury based Ayurvedic formulation (Sidh Makardhwaj) on brain cerebrum, liver & kidney in rats.

PubMed

Kumar, Gajendra; Srivastava, Amita; Sharma, Surinder Kumar; Gupta, Yogendra Kumar

2014-04-01

Sidh Makardhwaj (SM) is a mercury based Ayurvedic formulation used in rheumatoid arthritis and neurological disorders. However, toxicity concerns due to mercury content are often raised. Therefore, the present study was carried out to evaluate the effect of SM on brain cerebrum, liver and kidney in rats. Graded doses of SM (10, 50, 100 mg/kg), mercuric chloride (1 mg/kg) and normal saline were administered orally to male Wistar rats for 28 days. Behavioural parameters were assessed on days 1, 7, 14 and 28 using Morris water maze, passive avoidance, elevated plus maze and rota rod. Liver and kidney function tests were done on day 28. Animals were sacrificed and brain cerebrum acetylcholinesterase activity, levels of malondialdehyde (MDA), reduced glutathione (GSH) in brain cerebrum, liver, kidney were estimated. The levels of mercury in brain cerebrum, liver and kidney were estimated and histopathology of these tissues was also performed. SM in the doses used did not cause significant change in neurobehavioural parameters, brain cerebrum AChE activity, liver (ALT, AST, ALP bilirubin) and kidney (serum urea and creatinine) function tests as compared to control. The levels of mercury in brain cerebrum, liver, and kidney were found to be raised in dose dependent manner. However, the levels of MDA and GSH in these tissues did not show significant changes at doses of 10 and 50 mg/kg. Also, there was no histopathological change in cytoarchitecture of brain cerebrum, liver, and kidney tissues at doses of 10 and 50 mg/kg. The findings of the present study suggest that Sidh Makardhwaj upto five times the equivalent human dose administered for 28 days did not show any toxicological effects on rat brain cerebrum, liver and kidney.

Estimating the Proportion of Childhood Cancer Cases and Costs Attributable to the Environment in California.

PubMed

Nelson, Lauren; Valle, Jhaqueline; King, Galatea; Mills, Paul K; Richardson, Maxwell J; Roberts, Eric M; Smith, Daniel; English, Paul

2017-05-01

To estimate the proportion of cases and costs of the most common cancers among children aged 0 to 14 years (leukemia, lymphoma, and brain or central nervous system tumors) that were attributable to preventable environmental pollution in California in 2013. We conducted a literature review to identify preventable environmental hazards associated with childhood cancer. We combined risk estimates with California-specific exposure prevalence estimates to calculate hazard-specific environmental attributable fractions (EAFs). We combined hazard-specific EAFs to estimate EAFs for each cancer and calculated an overall EAF. Estimated economic costs included annual (indirect and direct medical) and lifetime costs. Hazards associated with childhood cancer risks included tobacco smoke, residential exposures, and parental occupational exposures. Estimated EAFs for leukemia, lymphoma, and brain or central nervous system cancer were 21.3% (range = 11.7%-30.9%), 16.1% (range = 15.0%-17.2%), and 2.0% (range = 1.7%-2.2%), respectively. The combined EAF was 15.1% (range = 9.4%-20.7%), representing $18.6 million (range = $11.6 to $25.5 million) in annual costs and $31 million in lifetime costs. Reducing environmental hazards and exposures in California could substantially reduce the human burden of childhood cancer and result in significant annual and lifetime savings.

Spiral MR fingerprinting at 7T with simultaneous B1 estimation.

PubMed

Buonincontri, Guido; Schulte, Rolf F; Cosottini, Mirco; Tosetti, Michela

2017-09-01

Magnetic resonance fingerprinting is an efficient, new approach for quantitative imaging with MR. We aimed to extend this technique to cases with B1+ inhomogeneities within the imaging volume. Previous approaches have used abrupt changes in flip angles to estimate the B1+ field simultaneously with T1 and T2, using a Cartesian approach in a small-animal scanner at 4.7T. Here, we evaluated whether a similar approach would be suitable for imaging human brains using spiral readouts with a 7T scanner. We found that our modified scheme could significantly reduce the adverse effects of B1+ inhomogeneities even in extreme cases, reducing both the bias and the variance in T2 estimations by an order of magnitude when compared to literature methods. Acquisitions used less than 1.5W/kg SAR and could be performed in 12s per slice. In conclusion, our approach can be used to perform quantitative imaging of the brain at 7T in a short time, simultaneously estimating the B1+ profile. Copyright © 2017 Elsevier Inc. All rights reserved.

Voxelwise Spectral Diffusional Connectivity and its Applications to Alzheimer’s Disease and Intelligence Prediction

PubMed Central

Li, Junning; Jin, Yan; Shi, Yonggang; Dinov, Ivo D.; Wang, Danny J.; Toga, Arthur W.; Thompson, Paul M.

2014-01-01

Human brain connectivity can be studied using graph theory. Many connectivity studies parcellate the brain into regions and count fibres extracted between them. The resulting network analyses require validation of the tractography, as well as region and parameter selection. Here we investigate whole brain connectivity from a different perspective. We propose a mathematical formulation based on studying the eigenvalues of the Laplacian matrix of the diffusion tensor field at the voxel level. This voxelwise matrix has over a million parameters, but we derive the Kirchhoff complexity and eigen-spectrum through elegant mathematical theorems, without heavy computation. We use these novel measures to accurately estimate the voxelwise connectivity in multiple biomedical applications such as Alzheimer’s disease and intelligence prediction. PMID:24505723

Cortical Hierarchies Perform Bayesian Causal Inference in Multisensory Perception

PubMed Central

Rohe, Tim; Noppeney, Uta

2015-01-01

To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the “causal inference problem.” Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI), and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation). At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion). Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world. PMID:25710328

Near-instant automatic access to visually presented words in the human neocortex: neuromagnetic evidence.

PubMed

Shtyrov, Yury; MacGregor, Lucy J

2016-05-24

Rapid and efficient processing of external information by the brain is vital to survival in a highly dynamic environment. The key channel humans use to exchange information is language, but the neural underpinnings of its processing are still not fully understood. We investigated the spatio-temporal dynamics of neural access to word representations in the brain by scrutinising the brain's activity elicited in response to psycholinguistically, visually and phonologically matched groups of familiar words and meaningless pseudowords. Stimuli were briefly presented on the visual-field periphery to experimental participants whose attention was occupied with a non-linguistic visual feature-detection task. The neural activation elicited by these unattended orthographic stimuli was recorded using multi-channel whole-head magnetoencephalography, and the timecourse of lexically-specific neuromagnetic responses was assessed in sensor space as well as at the level of cortical sources, estimated using individual MR-based distributed source reconstruction. Our results demonstrate a neocortical signature of automatic near-instant access to word representations in the brain: activity in the perisylvian language network characterised by specific activation enhancement for familiar words, starting as early as ~70 ms after the onset of unattended word stimuli and underpinned by temporal and inferior-frontal cortices.

A review of technical aspects of T1-weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in human brain tumors.

PubMed

Bergamino, M; Bonzano, L; Levrero, F; Mancardi, G L; Roccatagliata, L

2014-09-01

In the last few years, several imaging methods, such as magnetic resonance imaging (MRI) and computed tomography, have been used to investigate the degree of blood-brain barrier (BBB) permeability in patients with neurological diseases including multiple sclerosis, ischemic stroke, and brain tumors. One promising MRI method for assessing the BBB permeability of patients with neurological diseases in vivo is T1-weighted dynamic contrast-enhanced (DCE)-MRI. Here we review the technical issues involved in DCE-MRI in the study of human brain tumors. In the first part of this paper, theoretical models for the DCE-MRI analysis will be described, including the Toft-Kety models, the adiabatic approximation to the tissue homogeneity model and the two-compartment exchange model. These models can be used to estimate important kinetic parameters related to BBB permeability. In the second part of this paper, details of the data acquisition, issues related to the arterial input function, and procedures for DCE-MRI image analysis are illustrated. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

A novel approach to quantify different iron forms in ex-vivo human brain tissue

PubMed Central

Kumar, Pravin; Bulk, Marjolein; Webb, Andrew; van der Weerd, Louise; Oosterkamp, Tjerk H.; Huber, Martina; Bossoni, Lucia

2016-01-01

We propose a novel combination of methods to study the physical properties of ferric ions and iron-oxide nanoparticles in post-mortem human brain, based on the combination of Electron Paramagnetic Resonance (EPR) and SQUID magnetometry. By means of EPR, we derive the concentration of the low molecular weight iron pool, as well as the product of its electron spin relaxation times. Additionally, by SQUID magnetometry we identify iron mineralization products ascribable to a magnetite/maghemite phase and a ferrihydrite (ferritin) phase. We further derive the concentration of magnetite/maghemite and of ferritin nanoparticles. To test out the new combined methodology, we studied brain tissue of an Alzheimer’s patient and a healthy control. Finally, we estimate that the size of the magnetite/maghemite nanoparticles, whose magnetic moments are blocked at room temperature, exceeds 40–50 nm, which is not compatible with the ferritin protein, the core of which is typically 6–8 nm. We believe that this methodology could be beneficial in the study of neurodegenerative diseases such as Alzheimer’s Disease which are characterized by abnormal iron accumulation in the brain. PMID:27941952

New techniques for positron emission tomography in the study of human neurological disorders for the period June 15, 1987 through December 14, 1987

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1987-09-01

A brief progress report is presented describing the preparation of /sup 11/C-scopolamine, /sup 17/F-fluoromethane and /sup 18/F-tetraalkylammonium fluoride. The application of /sup 11/C-scopolamine to map cholinergic receptors in normal human brain. Additional studies entitled ''The Automated Arterial Blood Sampling Systems for PET'' and ''Investigations of Array Processor Based High-Speed Parameter Estimation for Tracer Kinetic Modeling'' are also described. (DT)

Estimating the mutual information of an EEG-based Brain-Computer Interface.

PubMed

Schlögl, A; Neuper, C; Pfurtscheller, G

2002-01-01

An EEG-based Brain-Computer Interface (BCI) could be used as an additional communication channel between human thoughts and the environment. The efficacy of such a BCI depends mainly on the transmitted information rate. Shannon's communication theory was used to quantify the information rate of BCI data. For this purpose, experimental EEG data from four BCI experiments was analyzed off-line. Subjects imaginated left and right hand movements during EEG recording from the sensorimotor area. Adaptive autoregressive (AAR) parameters were used as features of single trial EEG and classified with linear discriminant analysis. The intra-trial variation as well as the inter-trial variability, the signal-to-noise ratio, the entropy of information, and the information rate were estimated. The entropy difference was used as a measure of the separability of two classes of EEG patterns.

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

PubMed Central

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2014-01-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For OSEM, image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-fluorodeoxyglucose dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation GTM PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in CMRGlc estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters. PMID:24052021

Functional connectomics from resting-state fMRI

PubMed Central

Smith, Stephen M; Vidaurre, Diego; Beckmann, Christian F; Glasser, Matthew F; Jenkinson, Mark; Miller, Karla L; Nichols, Thomas E; Robinson, Emma; Salimi-Khorshidi, Gholamreza; Woolrich, Mark W; Barch, Deanna M; Uğurbil, Kamil; Van Essen, David C

2014-01-01

Spontaneous fluctuations in activity in different parts of the brain can be used to study functional brain networks. We review the use of resting-state functional MRI for the purpose of mapping the macroscopic functional connectome. After describing MRI acquisition and image processing methods commonly used to generate data in a form amenable to connectomics network analysis, we discuss different approaches for estimating network structure from that data. Finally, we describe new possibilities resulting from the high-quality rfMRI data being generated by the Human Connectome Project, and highlight some upcoming challenges in functional connectomics. PMID:24238796

Studying the Brain in a Dish: 3D Cell Culture Models of Human Brain Development and Disease.

PubMed

Brown, Juliana; Quadrato, Giorgia; Arlotta, Paola

2018-01-01

The study of the cellular and molecular processes of the developing human brain has been hindered by access to suitable models of living human brain tissue. Recently developed 3D cell culture models offer the promise of studying fundamental brain processes in the context of human genetic background and species-specific developmental mechanisms. Here, we review the current state of 3D human brain organoid models and consider their potential to enable investigation of complex aspects of human brain development and the underpinning of human neurological disease. © 2018 Elsevier Inc. All rights reserved.

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners.

PubMed

Luders, Eileen; Cherbuin, Nicolas; Gaser, Christian

2016-07-01

Normal aging is known to be accompanied by loss of brain substance. The present study was designed to examine whether the practice of meditation is associated with a reduced brain age. Specific focus was directed at age fifty and beyond, as mid-life is a time when aging processes are known to become more prominent. We applied a recently developed machine learning algorithm trained to identify anatomical correlates of age in the brain translating those into one single score: the BrainAGE index (in years). Using this validated approach based on high-dimensional pattern recognition, we re-analyzed a large sample of 50 long-term meditators and 50 control subjects estimating and comparing their brain ages. We observed that, at age fifty, brains of meditators were estimated to be 7.5years younger than those of controls. In addition, we examined if the brain age estimates change with increasing age. While brain age estimates varied only little in controls, significant changes were detected in meditators: for every additional year over fifty, meditators' brains were estimated to be an additional 1month and 22days younger than their chronological age. Altogether, these findings seem to suggest that meditation is beneficial for brain preservation, effectively protecting against age-related atrophy with a consistently slower rate of brain aging throughout life. Copyright © 2016 Elsevier Inc. All rights reserved.

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity.

PubMed

Jahanshad, Neda; Rajagopalan, Priya; Hua, Xue; Hibar, Derrek P; Nir, Talia M; Toga, Arthur W; Jack, Clifford R; Saykin, Andrew J; Green, Robert C; Weiner, Michael W; Medland, Sarah E; Montgomery, Grant W; Hansell, Narelle K; McMahon, Katie L; de Zubicaray, Greig I; Martin, Nicholas G; Wright, Margaret J; Thompson, Paul M

2013-03-19

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

Back to the future: estimating pre-injury brain volume in patients with traumatic brain injury.

PubMed

Ross, David E; Ochs, Alfred L; D Zannoni, Megan; Seabaugh, Jan M

2014-11-15

A recent meta-analysis by Hedman et al. allows for accurate estimation of brain volume changes throughout the life span. Additionally, Tate et al. showed that intracranial volume at a later point in life can be used to estimate reliably brain volume at an earlier point in life. These advancements were combined to create a model which allowed the estimation of brain volume just prior to injury in a group of patients with mild or moderate traumatic brain injury (TBI). This volume estimation model was used in combination with actual measurements of brain volume to test hypotheses about progressive brain volume changes in the patients. Twenty six patients with mild or moderate TBI were compared to 20 normal control subjects. NeuroQuant® was used to measure brain MRI volume. Brain volume after the injury (from MRI scans performed at t1 and t2) was compared to brain volume just before the injury (volume estimation at t0) using longitudinal designs. Groups were compared with respect to volume changes in whole brain parenchyma (WBP) and its 3 major subdivisions: cortical gray matter (GM), cerebral white matter (CWM) and subcortical nuclei+infratentorial regions (SCN+IFT). Using the normal control data, the volume estimation model was tested by comparing measured brain volume to estimated brain volume; reliability ranged from good to excellent. During the initial phase after injury (t0-t1), the TBI patients had abnormally rapid atrophy of WBP and CWM, and abnormally rapid enlargement of SCN+IFT. Rates of volume change during t0-t1 correlated with cross-sectional measures of volume change at t1, supporting the internal reliability of the volume estimation model. A logistic regression analysis using the volume change data produced a function which perfectly predicted group membership (TBI patients vs. normal control subjects). During the first few months after injury, patients with mild or moderate TBI have rapid atrophy of WBP and CWM, and rapid enlargement of SCN+IFT. The magnitude and pattern of the changes in volume may allow for the eventual development of diagnostic tools based on the volume estimation approach. Copyright © 2014 Elsevier Inc. All rights reserved.

Computational deconvolution of genome wide expression data from Parkinson's and Huntington's disease brain tissues using population-specific expression analysis

PubMed Central

Capurro, Alberto; Bodea, Liviu-Gabriel; Schaefer, Patrick; Luthi-Carter, Ruth; Perreau, Victoria M.

2015-01-01

The characterization of molecular changes in diseased tissues gives insight into pathophysiological mechanisms and is important for therapeutic development. Genome-wide gene expression analysis has proven valuable for identifying biological processes in neurodegenerative diseases using post mortem human brain tissue and numerous datasets are publically available. However, many studies utilize heterogeneous tissue samples consisting of multiple cell types, all of which contribute to global gene expression values, confounding biological interpretation of the data. In particular, changes in numbers of neuronal and glial cells occurring in neurodegeneration confound transcriptomic analyses, particularly in human brain tissues where sample availability and controls are limited. To identify cell specific gene expression changes in neurodegenerative disease, we have applied our recently published computational deconvolution method, population specific expression analysis (PSEA). PSEA estimates cell-type-specific expression values using reference expression measures, which in the case of brain tissue comprises mRNAs with cell-type-specific expression in neurons, astrocytes, oligodendrocytes and microglia. As an exercise in PSEA implementation and hypothesis development regarding neurodegenerative diseases, we applied PSEA to Parkinson's and Huntington's disease (PD, HD) datasets. Genes identified as differentially expressed in substantia nigra pars compacta neurons by PSEA were validated using external laser capture microdissection data. Network analysis and Annotation Clustering (DAVID) identified molecular processes implicated by differential gene expression in specific cell types. The results of these analyses provided new insights into the implementation of PSEA in brain tissues and additional refinement of molecular signatures in human HD and PD. PMID:25620908

Ion channels in EEG: isolating channel dysfunction in NMDA receptor antibody encephalitis.

PubMed

Symmonds, Mkael; Moran, Catherine H; Leite, M Isabel; Buckley, Camilla; Irani, Sarosh R; Stephan, Klaas Enno; Friston, Karl J; Moran, Rosalyn J

2018-06-01

See Roberts and Breakspear (doi:10.1093/brain/awy136) for a scientific commentary on this article.Neurological and psychiatric practice frequently lack diagnostic probes that can assess mechanisms of neuronal communication non-invasively in humans. In N-methyl-d-aspartate (NMDA) receptor antibody encephalitis, functional molecular assays are particularly important given the presence of NMDA antibodies in healthy populations, the multifarious symptomology and the lack of radiological signs. Recent advances in biophysical modelling techniques suggest that inferring cellular-level properties of neural circuits from macroscopic measures of brain activity is possible. Here, we estimated receptor function from EEG in patients with NMDA receptor antibody encephalitis (n = 29) as well as from encephalopathic and neurological patient controls (n = 36). We show that the autoimmune patients exhibit distinct fronto-parietal network changes from which ion channel estimates can be obtained using a microcircuit model. Specifically, a dynamic causal model of EEG data applied to spontaneous brain responses identifies a selective deficit in signalling at NMDA receptors in patients with NMDA receptor antibody encephalitis but not at other ionotropic receptors. Moreover, though these changes are observed across brain regions, these effects predominate at the NMDA receptors of excitatory neurons rather than at inhibitory interneurons. Given that EEG is a ubiquitously available clinical method, our findings suggest a unique re-purposing of EEG data as an assay of brain network dysfunction at the molecular level.

Joint penalized-likelihood reconstruction of time-activity curves and regions-of-interest from projection data in brain PET

NASA Astrophysics Data System (ADS)

Krestyannikov, E.; Tohka, J.; Ruotsalainen, U.

2008-06-01

This paper presents a novel statistical approach for joint estimation of regions-of-interest (ROIs) and the corresponding time-activity curves (TACs) from dynamic positron emission tomography (PET) brain projection data. It is based on optimizing the joint objective function that consists of a data log-likelihood term and two penalty terms reflecting the available a priori information about the human brain anatomy. The developed local optimization strategy iteratively updates both the ROI and TAC parameters and is guaranteed to monotonically increase the objective function. The quantitative evaluation of the algorithm is performed with numerically and Monte Carlo-simulated dynamic PET brain data of the 11C-Raclopride and 18F-FDG tracers. The results demonstrate that the method outperforms the existing sequential ROI quantification approaches in terms of accuracy, and can noticeably reduce the errors in TACs arising due to the finite spatial resolution and ROI delineation.

The protons of space and brain tumors: I. Clinical and dosimetric considerations

NASA Astrophysics Data System (ADS)

Dalrymple, G. V.; Nagle, W. A.; Moss, A. J.; Cavin, L. A.; Broadwater, J. R.; McGuire, E. L.; Eason, C. S.; Mitchell, J. C.; Hardy, K. A.; Wood, D. H.; Salmon, Y. A.; Yochmowitz, M. G.

1989-05-01

Almost 25 years ago a large group of Rhesus monkeys were irradiated with protons (32-2300 MeV). The experiments were designed: 1) To estimate the RBE of protons, per se, and 2) To provide some estimate of the hazards of the radiation environment of space. The initial results showed the RBE to be about 1.0 for acute radiation effects (mortality, hematologic changes, etc). The colony has been maintained at Brooks AFB, TX since irradiation. The survivors of 55 MeV proton irradiation have developed a very high incidence of Glioblastoma multiforme, a highly malignant primary brain tumor. These tumors appeared 1-20 yrs after surface doses of 400-800 rads. Reconstruction of the dosimetry suggests that some areas within the brain may have received doses of 1500-2500 rads. More than 30 radiation induced Glioblastomas have been reported in human patients who had received therapeutic head irradiation. The radiation doses required to induce Glioblastoma were of the same order of magnitude as required to induce Glioblastoma in the Rhesus monkey.

Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.

PubMed

Muthuraman, M; Galka, A; Hong, V N; Heute, U; Deuschl, G; Raethjen, J

2013-01-01

Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.

Investigating brain community structure abnormalities in bipolar disorder using path length associated community estimation.

PubMed

Gadelkarim, Johnson J; Ajilore, Olusola; Schonfeld, Dan; Zhan, Liang; Thompson, Paul M; Feusner, Jamie D; Kumar, Anand; Altshuler, Lori L; Leow, Alex D

2014-05-01

In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. Copyright © 2013 Wiley Periodicals, Inc.

The cost of health professionals' brain drain in Kenya.

PubMed

Kirigia, Joses Muthuri; Gbary, Akpa Raphael; Muthuri, Lenity Kainyu; Nyoni, Jennifer; Seddoh, Anthony

2006-07-17

Past attempts to estimate the cost of migration were limited to education costs only and did not include the lost returns from investment. The objectives of this study were: (i) to estimate the financial cost of emigration of Kenyan doctors to the United Kingdom (UK) and the United States of America (USA); (ii) to estimate the financial cost of emigration of nurses to seven OECD countries (Canada, Denmark, Finland, Ireland, Portugal, UK, USA); and (iii) to describe other losses from brain drain. The costs of primary, secondary, medical and nursing schools were estimated in 2005. The cost information used in this study was obtained from one non-profit primary and secondary school and one public university in Kenya. The cost estimates represent unsubsidized cost. The loss incurred by Kenya through emigration was obtained by compounding the cost of educating a medical doctor and a nurse over the period between the average age of emigration (30 years) and the age of retirement (62 years) in recipient countries. The total cost of educating a single medical doctor from primary school to university is 65,997 US dollars; and for every doctor who emigrates, a country loses about 517,931 US dollars worth of returns from investment. The total cost of educating one nurse from primary school to college of health sciences is 43,180 US dollars; and for every nurse that emigrates, a country loses about 338,868 US dollars worth of returns from investment. Developed countries continue to deprive Kenya of millions of dollars worth of investments embodied in her human resources for health. If the current trend of poaching of scarce human resources for health (and other professionals) from Kenya is not curtailed, the chances of achieving the Millennium Development Goals would remain bleak. Such continued plunder of investments embodied in human resources contributes to further underdevelopment of Kenya and to keeping a majority of her people in the vicious circle of ill-health and poverty. Therefore, both developed and developing countries need to urgently develop and implement strategies for addressing the health human resource crisis.

The cost of health professionals' brain drain in Kenya

PubMed Central

Kirigia, Joses Muthuri; Gbary, Akpa Raphael; Muthuri, Lenity Kainyu; Nyoni, Jennifer; Seddoh, Anthony

2006-01-01

Background Past attempts to estimate the cost of migration were limited to education costs only and did not include the lost returns from investment. The objectives of this study were: (i) to estimate the financial cost of emigration of Kenyan doctors to the United Kingdom (UK) and the United States of America (USA); (ii) to estimate the financial cost of emigration of nurses to seven OECD countries (Canada, Denmark, Finland, Ireland, Portugal, UK, USA); and (iii) to describe other losses from brain drain. Methods The costs of primary, secondary, medical and nursing schools were estimated in 2005. The cost information used in this study was obtained from one non-profit primary and secondary school and one public university in Kenya. The cost estimates represent unsubsidized cost. The loss incurred by Kenya through emigration was obtained by compounding the cost of educating a medical doctor and a nurse over the period between the average age of emigration (30 years) and the age of retirement (62 years) in recipient countries. Results The total cost of educating a single medical doctor from primary school to university is US$ 65,997; and for every doctor who emigrates, a country loses about US$ 517,931 worth of returns from investment. The total cost of educating one nurse from primary school to college of health sciences is US$ 43,180; and for every nurse that emigrates, a country loses about US$ 338,868 worth of returns from investment. Conclusion Developed countries continue to deprive Kenya of millions of dollars worth of investments embodied in her human resources for health. If the current trend of poaching of scarce human resources for health (and other professionals) from Kenya is not curtailed, the chances of achieving the Millennium Development Goals would remain bleak. Such continued plunder of investments embodied in human resources contributes to further underdevelopment of Kenya and to keeping a majority of her people in the vicious circle of ill-health and poverty. Therefore, both developed and developing countries need to urgently develop and implement strategies for addressing the health human resource crisis. PMID:16846492

Serotonin transporter occupancy by escitalopram and citalopram in the non-human primate brain: a [(11)C]MADAM PET study.

PubMed

Finnema, Sjoerd J; Halldin, Christer; Bang-Andersen, Benny; Bundgaard, Christoffer; Farde, Lars

2015-11-01

A number of serotonin receptor positron emission tomography (PET) radioligands have been shown to be sensitive to changes in extracellular serotonin concentration, in a generalization of the well-known dopamine competition model. High doses of selective serotonin reuptake inhibitors (SSRIs) decrease serotonin receptor availability in monkey brain, consistent with increased serotonin concentrations. However, two recent studies on healthy human subjects, using a single, lower and clinically relevant SSRI dose, showed increased cortical serotonin receptor radioligand binding, suggesting potential decreases in serotonin concentration in projection regions when initiating treatment. The cross-species differential SSRI effect may be partly explained by serotonin transporter (SERT) occupancy in monkey brain being higher than is clinically relevant. We here determine SERT occupancy after single doses of escitalopram or citalopram by conducting PET measurements with [(11)C]MADAM in monkeys. Relationships between dose, plasma concentration and SERT occupancy were estimated by one-site binding analyses. Binding affinity was expressed as dose (ID50) or plasma concentration (K i) where 50 % SERT occupancy was achieved. Estimated ID50 and K i values were 0.020 mg/kg and 9.6 nmol/L for escitalopram and 0.059 mg/kg and 9.7 nmol/L for citalopram, respectively. Obtained K i values are comparable to values reported in humans. Escitalopram or citalopram doses nearly saturated SERT in previous monkey studies which examined serotonin sensitivity of receptor radioligands. PET-measured cross-species differential effects of SSRI on cortical serotonin concentration may thus be related to SSRI dose. Future monkey studies using SSRI doses inducing clinically relevant SERT occupancy may further illuminate the delayed onset of SSRI therapeutic effects.

Prediction of CNS occupancy of dopamine D2 receptor based on systemic exposure and in vitro experiments.

PubMed

Kanamitsu, Kayoko; Arakawa, Ryosuke; Sugiyama, Yuichi; Suhara, Tetsuya; Kusuhara, Hiroyuki

2016-12-01

The effect of drugs in the central nervous system (CNS) is closely related to occupancy of their target receptor. In this study, we integrated plasma concentrations, in vitro/in vivo data for receptor or protein binding, and in silico data, using a physiologically based pharmacokinetic model, to examine the predictability of receptor occupancy in humans. The occupancy of the dopamine D2 receptor and the plasma concentrations of the antipsychotic drugs quetiapine and perospirone in humans were collected from the literature or produced experimentally. Association and dissociation rate constants and unbound fractions in the serum and brain were determined in vitro/in vivo using human D2 receptor-expressing membrane fractions, human serum and mouse brain. The permeability of drugs across the blood-brain barrier was estimated based on their physicochemical properties. The effect of a metabolite of perospirone, ID-15036, was also considered. The time profiles of D2 receptor occupancy following oral dose of quetiapine and perospirone predicted were similar to the observed values. This approach could assist in the design of clinical studies for drug development and the prediction of the impact of drug-drug interactions on CNS function in clinical settings. Copyright © 2016 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

The elephant brain in numbers

PubMed Central

Herculano-Houzel, Suzana; Avelino-de-Souza, Kamilla; Neves, Kleber; Porfírio, Jairo; Messeder, Débora; Mattos Feijó, Larissa; Maldonado, José; Manger, Paul R.

2014-01-01

What explains the superior cognitive abilities of the human brain compared to other, larger brains? Here we investigate the possibility that the human brain has a larger number of neurons than even larger brains by determining the cellular composition of the brain of the African elephant. We find that the African elephant brain, which is about three times larger than the human brain, contains 257 billion (109) neurons, three times more than the average human brain; however, 97.5% of the neurons in the elephant brain (251 billion) are found in the cerebellum. This makes the elephant an outlier in regard to the number of cerebellar neurons compared to other mammals, which might be related to sensorimotor specializations. In contrast, the elephant cerebral cortex, which has twice the mass of the human cerebral cortex, holds only 5.6 billion neurons, about one third of the number of neurons found in the human cerebral cortex. This finding supports the hypothesis that the larger absolute number of neurons in the human cerebral cortex (but not in the whole brain) is correlated with the superior cognitive abilities of humans compared to elephants and other large-brained mammals. PMID:24971054

MR-guided adaptive focusing of therapeutic ultrasound beams in the human head

PubMed Central

Marsac, Laurent; Chauvet, Dorian; Larrat, Benoît; Pernot, Mathieu; Robert, B.; Fink, Mathias; Boch, Anne-Laure; Aubry, Jean-François; Tanter, Mickaël

2012-01-01

Purpose This study aims to demonstrate, using human cadavers the feasibility of energy-based adaptive focusing of ultrasonic waves using Magnetic Resonance Acoustic Radiation Force Imaging (MR-ARFI) in the framework of non-invasive transcranial High Intensity Focused Ultrasound (HIFU) therapy. Methods Energy-based adaptive focusing techniques were recently proposed in order to achieve aberration correction. We evaluate this method on a clinical brain HIFU system composed of 512 ultrasonic elements positioned inside a full body 1.5 T clinical Magnetic Resonance (MR) imaging system. Cadaver heads were mounted onto a clinical Leksell stereotactic frame. The ultrasonic wave intensity at the chosen location was indirectly estimated by the MR system measuring the local tissue displacement induced by the acoustic radiation force of the ultrasound (US) beams. For aberration correction, a set of spatially encoded ultrasonic waves was transmitted from the ultrasonic array and the resulting local displacements were estimated with the MR-ARFI sequence for each emitted beam. A non-iterative inversion process was then performed in order to estimate the spatial phase aberrations induced by the cadaver skull. The procedure was first evaluated and optimized in a calf brain using a numerical aberrator mimicking human skull aberrations. The full method was then demonstrated using a fresh human cadaver head. Results The corrected beam resulting from the direct inversion process was found to focus at the targeted location with an acoustic intensity 2.2 times higher than the conventional non corrected beam. In addition, this corrected beam was found to give an acoustic intensity 1.5 times higher than the focusing pattern obtained with an aberration correction using transcranial acoustic simulation based on X-ray computed tomography (CT) scans. Conclusion The proposed technique achieved near optimal focusing in an intact human head for the first time. These findings confirm the strong potential of energy-based adaptive focusing of transcranial ultrasonic beams for clinical applications. PMID:22320825

Amyloid-β Plaques in Clinical Alzheimer’s Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity

PubMed Central

Wildburger, Norelle C.; Gyngard, Frank; Guillermier, Christelle; Patterson, Bruce W.; Elbert, Donald; Mawuenyega, Kwasi G.; Schneider, Theresa; Green, Karen; Roth, Robyn; Schmidt, Robert E.; Cairns, Nigel J.; Benzinger, Tammie L. S.; Steinhauser, Matthew L.; Bateman, Randall J.

2018-01-01

Alzheimer’s disease (AD) is a neurodegenerative disorder with clinical manifestations of progressive memory decline and loss of executive function and language. AD affects an estimated 5.3 million Americans alone and is the most common form of age-related dementia with a rapidly growing prevalence among the aging population—those 65 years of age or older. AD is characterized by accumulation of aggregated amyloid-beta (Aβ) in the brain, which leads to one of the pathological hallmarks of AD—Aβ plaques. As a result, Aβ plaques have been extensively studied after being first described over a century ago. Advances in brain imaging and quantitative measures of Aβ in biological fluids have yielded insight into the time course of plaque development decades before and after AD symptom onset. However, despite the fundamental role of Aβ plaques in AD, in vivo measures of individual plaque growth, growth distribution, and dynamics are still lacking. To address this question, we combined stable isotope labeling kinetics (SILK) and nanoscale secondary ion mass spectrometry (NanoSIMS) imaging in an approach termed SILK–SIMS to resolve plaque dynamics in three human AD brains. In human AD brain, plaques exhibit incorporation of a stable isotope tracer. Tracer enrichment was highly variable between plaques and the spatial distribution asymmetric with both quiescent and active nanometer sub-regions of tracer incorporation. These data reveal that Aβ plaques are dynamic structures with deposition rates over days indicating a highly active process. Here, we report the first, direct quantitative measures of in vivo deposition into plaques in human AD brain. Our SILK–SIMS studies will provide invaluable information on plaque dynamics in the normal and diseased brain and offer many new avenues for investigation into pathological mechanisms of the disease, with implications for therapeutic development. PMID:29623063

Amyloid-β Plaques in Clinical Alzheimer's Disease Brain Incorporate Stable Isotope Tracer In Vivo and Exhibit Nanoscale Heterogeneity.

PubMed

Wildburger, Norelle C; Gyngard, Frank; Guillermier, Christelle; Patterson, Bruce W; Elbert, Donald; Mawuenyega, Kwasi G; Schneider, Theresa; Green, Karen; Roth, Robyn; Schmidt, Robert E; Cairns, Nigel J; Benzinger, Tammie L S; Steinhauser, Matthew L; Bateman, Randall J

2018-01-01

Alzheimer's disease (AD) is a neurodegenerative disorder with clinical manifestations of progressive memory decline and loss of executive function and language. AD affects an estimated 5.3 million Americans alone and is the most common form of age-related dementia with a rapidly growing prevalence among the aging population-those 65 years of age or older. AD is characterized by accumulation of aggregated amyloid-beta (Aβ) in the brain, which leads to one of the pathological hallmarks of AD-Aβ plaques. As a result, Aβ plaques have been extensively studied after being first described over a century ago. Advances in brain imaging and quantitative measures of Aβ in biological fluids have yielded insight into the time course of plaque development decades before and after AD symptom onset. However, despite the fundamental role of Aβ plaques in AD, in vivo measures of individual plaque growth, growth distribution, and dynamics are still lacking. To address this question, we combined stable isotope labeling kinetics (SILK) and nanoscale secondary ion mass spectrometry (NanoSIMS) imaging in an approach termed SILK-SIMS to resolve plaque dynamics in three human AD brains. In human AD brain, plaques exhibit incorporation of a stable isotope tracer. Tracer enrichment was highly variable between plaques and the spatial distribution asymmetric with both quiescent and active nanometer sub-regions of tracer incorporation. These data reveal that Aβ plaques are dynamic structures with deposition rates over days indicating a highly active process. Here, we report the first, direct quantitative measures of in vivo deposition into plaques in human AD brain. Our SILK-SIMS studies will provide invaluable information on plaque dynamics in the normal and diseased brain and offer many new avenues for investigation into pathological mechanisms of the disease, with implications for therapeutic development.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series

PubMed Central

2011-01-01

Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html. PMID:21851598

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

PubMed

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Differences in Gaussian diffusion tensor imaging and non-Gaussian diffusion kurtosis imaging model-based estimates of diffusion tensor invariants in the human brain.

PubMed

Lanzafame, S; Giannelli, M; Garaci, F; Floris, R; Duggento, A; Guerrisi, M; Toschi, N

2016-05-01

An increasing number of studies have aimed to compare diffusion tensor imaging (DTI)-related parameters [e.g., mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD)] to complementary new indexes [e.g., mean kurtosis (MK)/radial kurtosis (RK)/axial kurtosis (AK)] derived through diffusion kurtosis imaging (DKI) in terms of their discriminative potential about tissue disease-related microstructural alterations. Given that the DTI and DKI models provide conceptually and quantitatively different estimates of the diffusion tensor, which can also depend on fitting routine, the aim of this study was to investigate model- and algorithm-dependent differences in MD/FA/RD/AD and anisotropy mode (MO) estimates in diffusion-weighted imaging of human brain white matter. The authors employed (a) data collected from 33 healthy subjects (20-59 yr, F: 15, M: 18) within the Human Connectome Project (HCP) on a customized 3 T scanner, and (b) data from 34 healthy subjects (26-61 yr, F: 5, M: 29) acquired on a clinical 3 T scanner. The DTI model was fitted to b-value =0 and b-value =1000 s/mm(2) data while the DKI model was fitted to data comprising b-value =0, 1000 and 3000/2500 s/mm(2) [for dataset (a)/(b), respectively] through nonlinear and weighted linear least squares algorithms. In addition to MK/RK/AK maps, MD/FA/MO/RD/AD maps were estimated from both models and both algorithms. Using tract-based spatial statistics, the authors tested the null hypothesis of zero difference between the two MD/FA/MO/RD/AD estimates in brain white matter for both datasets and both algorithms. DKI-derived MD/FA/RD/AD and MO estimates were significantly higher and lower, respectively, than corresponding DTI-derived estimates. All voxelwise differences extended over most of the white matter skeleton. Fractional differences between the two estimates [(DKI - DTI)/DTI] of most invariants were seen to vary with the invariant value itself as well as with MK/RK/AK values, indicating substantial anatomical variability of these discrepancies. In the HCP dataset, the median voxelwise percentage differences across the whole white matter skeleton were (nonlinear least squares algorithm) 14.5% (8.2%-23.1%) for MD, 4.3% (1.4%-17.3%) for FA, -5.2% (-48.7% to -0.8%) for MO, 12.5% (6.4%-21.2%) for RD, and 16.1% (9.9%-25.6%) for AD (all ranges computed as 0.01 and 0.99 quantiles). All differences/trends were consistent between the discovery (HCP) and replication (local) datasets and between estimation algorithms. However, the relationships between such trends, estimated diffusion tensor invariants, and kurtosis estimates were impacted by the choice of fitting routine. Model-dependent differences in the estimation of conventional indexes of MD/FA/MO/RD/AD can be well beyond commonly seen disease-related alterations. While estimating diffusion tensor-derived indexes using the DKI model may be advantageous in terms of mitigating b-value dependence of diffusivity estimates, such estimates should not be referred to as conventional DTI-derived indexes in order to avoid confusion in interpretation as well as multicenter comparisons. In order to assess the potential and advantages of DKI with respect to DTI as well as to standardize diffusion-weighted imaging methods between centers, both conventional DTI-derived indexes and diffusion tensor invariants derived by fitting the non-Gaussian DKI model should be separately estimated and analyzed using the same combination of fitting routines.

Effects of cell phone radiofrequency signal exposure on brain glucose metabolism.

PubMed

Volkow, Nora D; Tomasi, Dardo; Wang, Gene-Jack; Vaska, Paul; Fowler, Joanna S; Telang, Frank; Alexoff, Dave; Logan, Jean; Wong, Christopher

2011-02-23

The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with ((18)F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes ("on" condition) and once with both cell phones deactivated ("off" condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm(3)) and P < .05 (corrected for multiple comparisons) were considered significant. Brain glucose metabolism computed as absolute metabolism (μmol/100 g per minute) and as normalized metabolism (region/whole brain). Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 μmol/100 g per minute; mean difference, 2.4 [95% confidence interval, 0.67-4.2]; P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001). In healthy participants and compared with no exposure, 50-minute cell phone exposure was associated with increased brain glucose metabolism in the region closest to the antenna. This finding is of unknown clinical significance.

P-glycoprotein (ABCB1) inhibits the influx and increases the efflux of 11C-metoclopramide across the blood-brain barrier: a PET study on non-human primates.

PubMed

Auvity, Sylvain; Caillé, Fabien; Marie, Solène; Wimberley, Catriona; Bauer, Martin; Langer, Oliver; Buvat, Irène; Goutal, Sébastien; Tournier, Nicolas

2018-05-10

Rationale : PET imaging using radiolabeled high-affinity substrates of P-glycoprotein (ABCB1) has convincingly revealed the role of this major efflux transporter in limiting the influx of its substrates from blood into the brain across the blood-brain barrier (BBB). Many drugs, such as metoclopramide, are weak ABCB1 substrates and distribute into the brain even when ABCB1 is fully functional. In this study, we used kinetic modeling and validated simplified methods to highlight and quantify the impact of ABCB1 on the BBB influx and efflux of 11 C-metoclopramide, as a model weak ABCB1 substrate, in non-human primates. Methods : The regional brain kinetics of a tracer dose of 11 C-metoclopramide (298 ± 44 MBq) were assessed in baboons using PET without (n = 4) or with intravenous co-infusion of the ABCB1 inhibitor tariquidar (4 mg/kg/h, n = 4). Metabolite-corrected arterial input functions were generated to estimate the regional volume of distribution ( V T ) as well as the influx ( K 1 ) and efflux ( k 2 ) rate constants, using a one-tissue compartment model. Modeling outcome parameters were correlated with image-derived parameters, i.e. area under the curve AUC 0-30 min and AUC 30-60 min (SUV.min) as well as the elimination slope (k E ; min -1 ) from 30 to 60 min of the regional time-activity curves. Results : Tariquidar significantly increased the brain distribution of 11 C-metoclopramide ( V T = 4.3 ± 0.5 mL/cm 3 and 8.7 ± 0.5 mL/cm 3 for baseline and ABCB1 inhibition conditions, respectively, P<0.001), with a 1.28-fold increase in K 1 (P < 0.05) and a 1.64-fold decrease in k 2 (P < 0.001). The effect of tariquidar was homogeneous across different brain regions. The most sensitive parameters to ABCB1 inhibition were V T (2.02-fold increase) and AUC 30-60 min (2.02-fold increase). V T was significantly (P < 0.0001) correlated with AUC 30-60 min (r 2 = 0.95), AUC 0-30 min (r 2 = 0.87) and k E (r 2 = 0.62). Conclusion : 11 C-metoclopramide PET imaging revealed the relative importance of both the influx hindrance and efflux enhancement components of ABCB1 in a relevant model of the human BBB. The overall impact of ABCB1 on drug delivery to the brain can be non-invasively estimated from image-derived outcome parameters without the need for an arterial input function. Copyright © 2018 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Kinetic modeling of the monoamine oxidase B radioligand [¹¹C]SL25.1188 in human brain with high-resolution positron emission tomography.

PubMed

Rusjan, Pablo M; Wilson, Alan A; Miler, Laura; Fan, Ian; Mizrahi, Romina; Houle, Sylvain; Vasdev, Neil; Meyer, Jeffrey H

2014-05-01

This article describes the kinetic modeling of [(11)C]SL25.1188 ([(S)-5-methoxymethyl-3-[6-(4,4,4-trifluorobutoxy)-benzo[d]isoxazol-3-yl]-oxazolidin-2-[(11)C]one]) binding to monoamine oxidase B (MAO-B) in the human brain using high-resolution positron emission tomography (PET). Seven healthy subjects underwent two separate 90- minute PET scans after an intravenous injection of [(11)C]SL25.1188. Complementary arterial blood sampling was acquired. Radioactivity was quickly eliminated from plasma with 80% of parent compound remaining at 90 minutes. Metabolites were more polar than the parent compound. Time-activity curves showed high brain uptake, early peak and washout rate consistent with known regional MAO-B concentration. A two-tissue compartment model (2-TCM) provided better fits to the data than a 1-TCM. Measurement of total distribution volume (VT) showed very good identifiability (based on coefficient of variation (COV)) for all regions of interest (ROIs) (COV(VT)<8%), low between-subject variability (∼20%), and quick temporal convergence (within 5% of final value at 45 minutes). Logan graphical method produces very good estimation of VT. Regional VT highly correlated with previous postmortem report of MAO-B level (r(2)= ≥ 0.9). Specific binding would account from 70% to 90% of VT. Hence, VT measurement of [(11)C]SL25.1(1)88 PET is an excellent estimation of MAO-B concentration.

Population PKPD modeling of BACE1 inhibitor-induced reduction in Aβ levels in vivo and correlation to in vitro potency in primary cortical neurons from mouse and guinea pig.

PubMed

Janson, Juliette; Eketjäll, Susanna; Tunblad, Karin; Jeppsson, Fredrik; Von Berg, Stefan; Niva, Camilla; Radesäter, Ann-Cathrin; Fälting, Johanna; Visser, Sandra A G

2014-03-01

The aims were to quantify the in vivo time-course between the oral dose, the plasma and brain exposure and the inhibitory effect on Amyloid β (Aβ) in brain and cerebrospinal fluid, and to establish the correlation between in vitro and in vivo potency of novel β-secretase (BACE1) inhibitors. BACE1-mediated inhibition of Aβ was quantified in in vivo dose- and/or time-response studies and in vitro in SH-SY5Y cells, N2A cells, and primary cortical neurons (PCN). An indirect response model with inhibition on Aβ production rate was used to estimate unbound in vivo IC 50 in a population pharmacokinetic-pharmacodynamic modeling approach. Estimated in vivo inhibitory potencies varied between 1 and 1,000 nM. The turnover half-life of Aβ40 in brain was predicted to be 0.5 h in mouse and 1 h in guinea pig. An excellent correlation between PCN and in vivo potency was observed. Moreover, a strong correlation in potency was found between human SH-SY5Y cells and mouse PCN, being 4.5-fold larger in SH-SY5Y cells. The strong in vivo-in vitro correlation increased the confidence in using human cell lines for screening and optimization of BACE1 inhibitors. This can optimize the design and reduce the number of preclinical in vivo effect studies.

Quantitative analysis of transcranial and intraparenchymal light penetration in human cadaver brain tissue.

PubMed

Tedford, Clark E; DeLapp, Scott; Jacques, Steven; Anders, Juanita

2015-04-01

Photobiomodulation (PBM) also known as low-level light therapy has been used successfully for the treatment of injury and disease of the nervous system. The use of PBM to treat injury and diseases of the brain requires an in-depth understanding of light propagation through tissues including scalp, skull, meninges, and brain. This study investigated the light penetration gradients in the human cadaver brain using a Transcranial Laser System with a 30 mm diameter beam of 808 nm wavelength light. In addition, the wavelength-dependence of light scatter and absorbance in intraparenchymal brain tissue using 660, 808, and 940 nm wavelengths was investigated. Intact human cadaver heads (n = 8) were obtained for measurement of light propagation through the scalp/skull/meninges and into brain tissue. The cadaver heads were sectioned in either the transverse or mid-sagittal. The sectioned head was mounted into a cranial fixture with an 808 nm wavelength laser system illuminating the head from beneath with either pulsed-wave (PW) or continuous-wave (CW) laser light. A linear array of nine isotropic optical fibers on a 5 mm pitch was inserted into the brain tissue along the optical axis of the beam. Light collected from each fiber was delivered to a multichannel power meter. As the array was lowered into the tissue, the power from each probe was recorded at 5 mm increments until the inner aspect of the dura mater was reached. Intraparenchymal light penetration measurements were made by delivering a series of wavelengths (660, 808, and 940 nm) through a separate optical fiber within the array, which was offset from the array line by 5 mm. Local light penetration was determined and compared across the selected wavelengths. Unfixed cadaver brains provide good anatomical localization and reliable measurements of light scatter and penetration in the CNS tissues. Transcranial application of 808 nm wavelength light penetrated the scalp, skull, meninges, and brain to a depth of approximately 40 mm with an effective attenuation coefficient for the system of 2.22 cm(-1) . No differences were observed in the results between the PW and CW laser light. The intraparenchymal studies demonstrated less absorption and scattering for the 808 nm wavelength light compared to the 660 or 940 nm wavelengths. Transcranial light measurements of unfixed human cadaver brains allowed for determinations of light penetration variables. While unfixed human cadaver studies do not reflect all the conditions seen in the living condition, comparisons of light scatter and penetration and estimates of fluence levels can be used to establish further clinical dosing. The 808 nm wavelength light demonstrated superior CNS tissue penetration. © 2015 Wiley Periodicals, Inc.

Multiple Brain Markers are Linked to Age-Related Variation in Cognition

PubMed Central

Hedden, Trey; Schultz, Aaron P.; Rieckmann, Anna; Mormino, Elizabeth C.; Johnson, Keith A.; Sperling, Reisa A.; Buckner, Randy L.

2016-01-01

Age-related alterations in brain structure and function have been challenging to link to cognition due to potential overlapping influences of multiple neurobiological cascades. We examined multiple brain markers associated with age-related variation in cognition. Clinically normal older humans aged 65–90 from the Harvard Aging Brain Study (N = 186) were characterized on a priori magnetic resonance imaging markers of gray matter thickness and volume, white matter hyperintensities, fractional anisotropy (FA), resting-state functional connectivity, positron emission tomography markers of glucose metabolism and amyloid burden, and cognitive factors of processing speed, executive function, and episodic memory. Partial correlation and mediation analyses estimated age-related variance in cognition shared with individual brain markers and unique to each marker. The largest relationships linked FA and striatum volume to processing speed and executive function, and hippocampal volume to episodic memory. Of the age-related variance in cognition, 70–80% was accounted for by combining all brain markers (but only ∼20% of total variance). Age had significant indirect effects on cognition via brain markers, with significant markers varying across cognitive domains. These results suggest that most age-related variation in cognition is shared among multiple brain markers, but potential specificity between some brain markers and cognitive domains motivates additional study of age-related markers of neural health. PMID:25316342

Initial Evaluation of an Adenosine A2A Receptor Ligand, 11C-Preladenant, in Healthy Human Subjects.

PubMed

Sakata, Muneyuki; Ishibashi, Kenji; Imai, Masamichi; Wagatsuma, Kei; Ishii, Kenji; Zhou, Xiaoyun; de Vries, Erik F J; Elsinga, Philip H; Ishiwata, Kiichi; Toyohara, Jun

2017-09-01

11 C-preladenant is a selective antagonist for mapping of cerebral adenosine A 2A receptors (A 2A Rs) by PET. This is a first-in-human study to examine the safety, radiation dosimetry, and brain imaging of 11 C-preladenant in healthy human subjects. Methods: Dynamic 11 C-preladenant PET scans (90 min) were obtained in 5 healthy male subjects. During the scan, arterial blood was sampled at various time intervals, and the fraction of the parent compound in plasma was determined. For anatomic coregistration, T1-weighted MRI was performed. The total distribution volume ( V T ) was estimated using 1- and 2-tissue-compartment models (1T and 2T, respectively). The distribution volume ratio (DVR) was calculated from V T of target and reference region and obtained with a noninvasive Logan graphical reference tissue method ( t * = 30 min). The applicability of a shortened protocol as an alternative to the 90-min PET scan was investigated. Tracer biodistribution and dosimetry were determined in 3 healthy male subjects, using serial whole-body PET scans acquired over 2 h after 11 C-preladenant injection. Results: There were no serious adverse events in any of the subjects throughout the study period. 11 C-preladenat readily entered the brain, with a peak uptake in the putamen and head of the caudate nucleus 30-40 min after tracer injection. Other brain regions showed rapid clearance of radioactivity. The regional distribution of 11 C-preladenant was consistent with known A 2A R densities in the brain. At pseudoequilibrium (reached at 40 min after injection), stable target-to-cerebellar cortex ratios of around 3.8-10.0 were obtained. The 2T fit better than the 1T in the low-density A 2A R regions. In contrast, there were no significant differences between 1T and 2T in the high-A 2A R-density regions. DVRs in the putamen and head of the caudate nucleus were around 3.8-10.3 when estimated using a Logan graphical reference tissue method with cerebellum as the reference region. PET scanning at 50 or 70 min can provide the stable DVR estimates within 10% or 5% differences at most, respectively. The radioactivity was mainly excreted through the hepatobiliary system after 11 C-preladenant injection. As a result, the absorbed dose (μGy/MBq) was highest in the gallbladder wall (mean ± SD, 17.0 ± 2.5) and liver (11.7 ± 2.1). The estimated effective dose for 11 C-preladenant was 3.7 ± 0.4 μSv/MBq. Conclusion: This initial evaluation indicated that 11 C-preladenat is suitable for imaging of A 2A Rs in the brain. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Banking brain tissue for research.

PubMed

Klioueva, Natasja; Bovenberg, Jasper; Huitinga, Inge

2017-01-01

Well-characterized human brain tissue is crucial for scientific breakthroughs in research of the human brain and brain diseases. However, the collection, characterization, management, and accessibility of brain human tissue are rather complex. Well-characterized human brain tissue is often provided from private, sometimes small, brain tissue collections by (neuro)pathologic experts. However, to meet the increasing demand for human brain tissue from the scientific community, many professional brain-banking activities aiming at both neurologic and psychiatric diseases as well as healthy controls are currently being initiated worldwide. Professional biobanks are open-access and in many cases run donor programs. They are therefore costly and need effective business plans to guarantee long-term sustainability. Here we discuss the ethical, legal, managerial, and financial aspects of professional brain banks. Copyright © 2017 Elsevier B.V. All rights reserved.

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter

PubMed Central

Reddy, Chinthala P.; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts. PMID:27147956

Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter.

PubMed

Reddy, Chinthala P; Rathi, Yogesh

2016-01-01

Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.

Development of a practical image-based scatter correction method for brain perfusion SPECT: comparison with the TEW method.

PubMed

Shidahara, Miho; Watabe, Hiroshi; Kim, Kyeong Min; Kato, Takashi; Kawatsu, Shoji; Kato, Rikio; Yoshimura, Kumiko; Iida, Hidehiro; Ito, Kengo

2005-10-01

An image-based scatter correction (IBSC) method was developed to convert scatter-uncorrected into scatter-corrected SPECT images. The purpose of this study was to validate this method by means of phantom simulations and human studies with 99mTc-labeled tracers, based on comparison with the conventional triple energy window (TEW) method. The IBSC method corrects scatter on the reconstructed image I(mub)AC with Chang's attenuation correction factor. The scatter component image is estimated by convolving I(mub)AC with a scatter function followed by multiplication with an image-based scatter fraction function. The IBSC method was evaluated with Monte Carlo simulations and 99mTc-ethyl cysteinate dimer SPECT human brain perfusion studies obtained from five volunteers. The image counts and contrast of the scatter-corrected images obtained by the IBSC and TEW methods were compared. Using data obtained from the simulations, the image counts and contrast of the scatter-corrected images obtained by the IBSC and TEW methods were found to be nearly identical for both gray and white matter. In human brain images, no significant differences in image contrast were observed between the IBSC and TEW methods. The IBSC method is a simple scatter correction technique feasible for use in clinical routine.

Statistical quantifiers of memory for an analysis of human brain and neuro-system diseases

NASA Astrophysics Data System (ADS)

Demin, S. A.; Yulmetyev, R. M.; Panischev, O. Yu.; Hänggi, Peter

2008-03-01

On the basis of a memory function formalism for correlation functions of time series we investigate statistical memory effects by the use of appropriate spectral and relaxation parameters of measured stochastic data for neuro-system diseases. In particular, we study the dynamics of the walk of a patient who suffers from Parkinson's disease (PD), Huntington's disease (HD), amyotrophic lateral sclerosis (ALS), and compare against the data of healthy people (CO - control group). We employ an analytical method which is able to characterize the stochastic properties of stride-to-stride variations of gait cycle timing. Our results allow us to estimate quantitatively a few human locomotion function abnormalities occurring in the human brain and in the central nervous system (CNS). Particularly, the patient's gait dynamics are characterized by an increased memory behavior together with sizable fluctuations as compared with the locomotion dynamics of healthy patients. Moreover, we complement our findings with peculiar features as detected in phase-space portraits and spectral characteristics for the different data sets (PD, HD, ALS and healthy people). The evaluation of statistical quantifiers of the memory function is shown to provide a useful toolkit which can be put to work to identify various abnormalities of locomotion dynamics. Moreover, it allows one to diagnose qualitatively and quantitatively serious brain and central nervous system diseases.

[Toxoplasmosis and cancer: Current knowledge and research perspectives].

PubMed

Vittecoq, M; Thomas, F

2017-02-01

Toxoplasmosis, caused by Toxoplasma gondii, is one of the most prevalent parasitic diseases; it is estimated to affect a third of the world's human population. Many studies showed that latent toxoplasmosis may cause in some patients significant adverse effects including schizophrenia and bipolar disorders. In addition, two recent studies highlighted a positive correlation between the prevalence of brain tumors and that of T. gondii at national and international scale. These studies are correlative, thus they do not demonstrate a causal link between T. gondii and brain tumors. Yet, they call for further research that could shed light on the possible mechanisms underlying this association.

Magnetoencephalography - a noninvasive brain imaging method with 1 ms time resolution

NASA Astrophysics Data System (ADS)

DelGratta, Cosimo; Pizzella, Vittorio; Tecchio, Franca; Luca Romani, Gian

2001-12-01

The basics of magnetoencephalography (MEG), i.e. the measurement and the analysis of the tiny magnetic fields generated outside the scalp by the working human brain, are reviewed. Three main topics are discussed: (1) the relationship between the magnetic field and its generators, including on one hand the neurophysiological basis and the physical theory of magnetic field generation, and on the other hand the techniques for the estimation of the sources from the magnetic field measurements; (2) the instrumental techniques and the laboratory practice of neuromagnetic field measurement and (3) the main applications of MEG in basic neurophysiology as well as in clinical neurology.

A closed-loop anesthetic delivery system for real-time control of burst suppression

NASA Astrophysics Data System (ADS)

Liberman, Max Y.; Ching, ShiNung; Chemali, Jessica; Brown, Emery N.

2013-08-01

Objective. There is growing interest in using closed-loop anesthetic delivery (CLAD) systems to automate control of brain states (sedation, unconsciousness and antinociception) in patients receiving anesthesia care. The accuracy and reliability of these systems can be improved by using as control signals electroencephalogram (EEG) markers for which the neurophysiological links to the anesthetic-induced brain states are well established. Burst suppression, in which bursts of electrical activity alternate with periods of quiescence or suppression, is a well-known, readily discernible EEG marker of profound brain inactivation and unconsciousness. This pattern is commonly maintained when anesthetics are administered to produce a medically-induced coma for cerebral protection in patients suffering from brain injuries or to arrest brain activity in patients having uncontrollable seizures. Although the coma may be required for several hours or days, drug infusion rates are managed inefficiently by manual adjustment. Our objective is to design a CLAD system for burst suppression control to automate management of medically-induced coma. Approach. We establish a CLAD system to control burst suppression consisting of: a two-dimensional linear system model relating the anesthetic brain level to the EEG dynamics; a new control signal, the burst suppression probability (BSP) defining the instantaneous probability of suppression; the BSP filter, a state-space algorithm to estimate the BSP from EEG recordings; a proportional-integral controller; and a system identification procedure to estimate the model and controller parameters. Main results. We demonstrate reliable performance of our system in simulation studies of burst suppression control using both propofol and etomidate in rodent experiments based on Vijn and Sneyd, and in human experiments based on the Schnider pharmacokinetic model for propofol. Using propofol, we further demonstrate that our control system reliably tracks changing target levels of burst suppression in simulated human subjects across different epidemiological profiles. Significance. Our results give new insights into CLAD system design and suggest a control-theory framework to automate second-to-second control of burst suppression for management of medically-induced coma.

Assessment of the dynamics of human glymphatic system by near-infrared spectroscopy.

PubMed

Myllylä, Teemu; Harju, Markus; Korhonen, Vesa; Bykov, Alexander; Kiviniemi, Vesa; Meglinski, Igor

2017-08-12

Fluctuations in brain water content has attracted increasing interest, particularly as regards studies of the glymphatic system, which is connected with the complex organization of dural lymphatic vessels, responsible for cleaning tissue. Disturbances of glymphatic circulation are associated with several brain disorders, including dementia. This article introduces an approach to noninvasive measurement of water dynamics in the human brain utilizing near-infrared spectroscopy (NIRS). We demonstrate the possibility to sense dynamic variations of water content between the skull and grey matter, for instance, in the subarachnoid space. Measured fluctuations in water content, especially in the cerebrospinal fluid (CSF), are assumed to be correlated with the dynamics of glymphatic circulation. The sampling volume for the NIRS optode was estimated by Monte Carlo modelling for the wavelengths of 660, 740, 830 and 980 nm. In addition, using combinations of these wavelengths, this article presents the calculation models for quantifying water and haemodynamics. The presented NIRS technique allows long-term functional brain monitoring, including sleeping time. Furthermore, it is used in combination with different magnetic neuroimaging techniques, particularly magnetic resonance encephalography. Using the combined setup, we report the preliminary results on the interaction between CSF and blood oxygen level-dependent fluctuations. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Normative brain size variation and brain shape diversity in humans.

PubMed

Reardon, P K; Seidlitz, Jakob; Vandekar, Simon; Liu, Siyuan; Patel, Raihaan; Park, Min Tae M; Alexander-Bloch, Aaron; Clasen, Liv S; Blumenthal, Jonathan D; Lalonde, Francois M; Giedd, Jay N; Gur, Ruben C; Gur, Raquel E; Lerch, Jason P; Chakravarty, M Mallar; Satterthwaite, Theodore D; Shinohara, Russell T; Raznahan, Armin

2018-06-15

Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

I.V. infusion of brain-derived neurotrophic factor gene-modified human mesenchymal stem cells protects against injury in a cerebral ischemia model in adult rat.

PubMed

Nomura, T; Honmou, O; Harada, K; Houkin, K; Hamada, H; Kocsis, J D

2005-01-01

I.V. delivery of mesenchymal stem cells prepared from adult bone marrow reduces infarction size and ameliorates functional deficits in rat cerebral ischemia models. Administration of the brain-derived neurotrophic factor to the infarction site has also been demonstrated to be neuroprotective. To test the hypothesis that brain-derived neurotrophic factor contributes to the therapeutic benefits of mesenchymal stem cell delivery, we compared the efficacy of systemic delivery of human mesenchymal stem cells and human mesenchymal stem cells transfected with a fiber-mutant F/RGD adenovirus vector with a brain-derived neurotrophic factor gene (brain-derived neurotrophic factor-human mesenchymal stem cells). A permanent middle cerebral artery occlusion was induced by intraluminal vascular occlusion with a microfilament. Human mesenchymal stem cells and brain-derived neurotrophic factor-human mesenchymal stem cells were i.v. injected into the rats 6 h after middle cerebral artery occlusion. Lesion size was assessed at 6 h, 1, 3 and 7 days using MR imaging, and histological methods. Functional outcome was assessed using the treadmill stress test. Both human mesenchymal stem cells and brain-derived neurotrophic factor-human mesenchymal stem cells reduced lesion volume and elicited functional improvement compared with the control sham group, but the effect was greater in the brain-derived neurotrophic factor-human mesenchymal stem cell group. ELISA analysis of the infarcted hemisphere revealed an increase in brain-derived neurotrophic factor in the human mesenchymal stem cell groups, but a greater increase in the brain-derived neurotrophic factor-human mesenchymal stem cell group. These data support the hypothesis that brain-derived neurotrophic factor contributes to neuroprotection in cerebral ischemia and cellular delivery of brain-derived neurotrophic factor can be achieved by i.v. delivery of human mesenchymal stem cells.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Neural decoding of collective wisdom with multi-brain computing.

PubMed

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states. Copyright © 2011 Elsevier Inc. All rights reserved.

Validation of [(11) C]ORM-13070 as a PET tracer for alpha2c -adrenoceptors in the human brain.

PubMed

Lehto, Jussi; Hirvonen, Mika M; Johansson, Jarkko; Kemppainen, Jukka; Luoto, Pauliina; Naukkarinen, Tarja; Oikonen, Vesa; Arponen, Eveliina; Rouru, Juha; Sallinen, Jukka; Scheinin, Harry; Vuorilehto, Lauri; Finnema, Sjoerd J; Halldin, Christer; Rinne, Juha O; Scheinin, Mika

2015-03-01

This study explored the use of the α2C -adrenoceptor PET tracer [(11) C]ORM-13070 to monitor α2C -AR occupancy in the human brain. The subtype-nonselective α2 -AR antagonist atipamezole was administered to eight healthy volunteer subjects to determine its efficacy and potency (Emax and EC50 ) at inhibiting tracer uptake. We also explored whether the tracer could reveal changes in the synaptic concentrations of endogenous noradrenaline in the brain, in response to several pharmacological and sensory challenge conditions. We assessed occupancy from the bound-to-free ratio measured during 5-30 min post injection. Based on extrapolation of one-site binding, the maximal extent of inhibition of striatal [(11) C]ORM-13070 uptake (Emax ) achievable by atipamezole was 78% (95% CI 69-87%) in the caudate nucleus and 65% (53-77%) in the putamen. The EC50 estimates of atipamezole (1.6 and 2.5 ng/ml, respectively) were in agreement with the drug's affinity to α2C -ARs. These findings represent clear support for the use of [(11) C]ORM-13070 for monitoring drug occupancy of α2C -ARs in the living human brain. Three of the employed noradrenaline challenges were associated with small, approximately 10-16% average reductions in tracer uptake in the dorsal striatum (atomoxetine, ketamine, and the cold pressor test; P < 0.05 for all), but insulin-induced hypoglycemia did not affect tracer uptake. The tracer is suitable for studying central nervous system receptor occupancy by α2C -AR ligands in human subjects. [(11) C]ORM-13070 also holds potential as a tool for in vivo monitoring of synaptic concentrations of noradrenaline, but this remains to be further evaluated in future studies. © 2014 Wiley Periodicals, Inc.

Developing 3D microscopy with CLARITY on human brain tissue: Towards a tool for informing and validating MRI-based histology.

PubMed

Morawski, Markus; Kirilina, Evgeniya; Scherf, Nico; Jäger, Carsten; Reimann, Katja; Trampel, Robert; Gavriilidis, Filippos; Geyer, Stefan; Biedermann, Bernd; Arendt, Thomas; Weiskopf, Nikolaus

2017-11-28

Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Age estimation using cortical surface pattern combining thickness with curvatures

PubMed Central

Wang, Jieqiong; Li, Wenjing; Miao, Wen; Dai, Dai; Hua, Jing; He, Huiguang

2014-01-01

Brain development and healthy aging have been proved to follow a specific pattern, which, in turn, can be applied to help doctors diagnose mental diseases. In this paper, we design a cortical surface pattern (CSP) combining the cortical thickness with curvatures, which constructs an accurate human age estimation model with relevance vector regression. We test our model with two public databases. One is the IXI database (360 healthy subjects aging from 20 to 82 years old were selected), and the other is the INDI database (303 subjects aging from 7 to 22 years old were selected). The results show that our model can achieve as small as 4.57 years deviation in the IXI database and 1.38 years deviation in the INDI database. Furthermore, we employ this surface pattern to age groups classification, and get a remarkably high accuracy (97.77%) and a significantly high sensitivity/specificity (97.30%/98.10%). These results suggest that our designed CSP combining thickness with curvatures is stable and sensitive to brain development, and it is much more powerful than voxel-based morphometry used in previous methods for age estimation. PMID:24395657

Automatic Segmentation of the Cortical Grey and White Matter in MRI Using a Region-Growing Approach Based on Anatomical Knowledge

NASA Astrophysics Data System (ADS)

Wasserthal, Christian; Engel, Karin; Rink, Karsten; Brechmann, Andr'e.

We propose an automatic procedure for the correct segmentation of grey and white matter in MR data sets of the human brain. Our method exploits general anatomical knowledge for the initial segmentation and for the subsequent refinement of the estimation of the cortical grey matter. Our results are comparable to manual segmentations.

The hubs of the human connectome are generally implicated in the anatomy of brain disorders.

PubMed

Crossley, Nicolas A; Mechelli, Andrea; Scott, Jessica; Carletti, Francesco; Fox, Peter T; McGuire, Philip; Bullmore, Edward T

2014-08-01

Brain networks or 'connectomes' include a minority of highly connected hub nodes that are functionally valuable, because their topological centrality supports integrative processing and adaptive behaviours. Recent studies also suggest that hubs have higher metabolic demands and longer-distance connections than other brain regions, and therefore could be considered biologically costly. Assuming that hubs thus normally combine both high topological value and high biological cost, we predicted that pathological brain lesions would be concentrated in hub regions. To test this general hypothesis, we first identified the hubs of brain anatomical networks estimated from diffusion tensor imaging data on healthy volunteers (n = 56), and showed that computational attacks targeted on hubs disproportionally degraded the efficiency of brain networks compared to random attacks. We then prepared grey matter lesion maps, based on meta-analyses of published magnetic resonance imaging data on more than 20 000 subjects and 26 different brain disorders. Magnetic resonance imaging lesions that were common across all brain disorders were more likely to be located in hubs of the normal brain connectome (P < 10(-4), permutation test). Specifically, nine brain disorders had lesions that were significantly more likely to be located in hubs (P < 0.05, permutation test), including schizophrenia and Alzheimer's disease. Both these disorders had significantly hub-concentrated lesion distributions, although (almost completely) distinct subsets of cortical hubs were lesioned in each disorder: temporal lobe hubs specifically were associated with higher lesion probability in Alzheimer's disease, whereas in schizophrenia lesions were concentrated in both frontal and temporal cortical hubs. These results linking pathological lesions to the topological centrality of nodes in the normal diffusion tensor imaging connectome were generally replicated when hubs were defined instead by the meta-analysis of more than 1500 task-related functional neuroimaging studies of healthy volunteers to create a normative functional co-activation network. We conclude that the high cost/high value hubs of human brain networks are more likely to be anatomically abnormal than non-hubs in many (if not all) brain disorders. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

Causal network in a deafferented non-human primate brain.

PubMed

Balasubramanian, Karthikeyan; Takahashi, Kazutaka; Hatsopoulos, Nicholas G

2015-01-01

De-afferented/efferented neural ensembles can undergo causal changes when interfaced to neuroprosthetic devices. These changes occur via recruitment or isolation of neurons, alterations in functional connectivity within the ensemble and/or changes in the role of neurons, i.e., excitatory/inhibitory. In this work, emergence of a causal network and changes in the dynamics are demonstrated for a deafferented brain region exposed to BMI (brain-machine interface) learning. The BMI was controlling a robot for reach-and-grasp behavior. And, the motor cortical regions used for the BMI were deafferented due to chronic amputation, and ensembles of neurons were decoded for velocity control of the multi-DOF robot. A generalized linear model-framework based Granger causality (GLM-GC) technique was used in estimating the ensemble connectivity. Model selection was based on the AIC (Akaike Information Criterion).

Automatic user customization for improving the performance of a self-paced brain interface system.

PubMed

Fatourechi, Mehrdad; Bashashati, Ali; Birch, Gary E; Ward, Rabab K

2006-12-01

Customizing the parameter values of brain interface (BI) systems by a human expert has the advantage of being fast and computationally efficient. However, as the number of users and EEG channels grows, this process becomes increasingly time consuming and exhausting. Manual customization also introduces inaccuracies in the estimation of the parameter values. In this paper, the performance of a self-paced BI system whose design parameter values were automatically user customized using a genetic algorithm (GA) is studied. The GA automatically estimates the shapes of movement-related potentials (MRPs), whose features are then extracted to drive the BI. Offline analysis of the data of eight subjects revealed that automatic user customization improved the true positive (TP) rate of the system by an average of 6.68% over that whose customization was carried out by a human expert, i.e., by visually inspecting the MRP templates. On average, the best improvement in the TP rate (an average of 9.82%) was achieved for four individuals with spinal cord injury. In this case, the visual estimation of the parameter values of the MRP templates was very difficult because of the highly noisy nature of the EEG signals. For four able-bodied subjects, for which the MRP templates were less noisy, the automatic user customization led to an average improvement of 3.58% in the TP rate. The results also show that the inter-subject variability of the TP rate is also reduced compared to the case when user customization is carried out by a human expert. These findings provide some primary evidence that automatic user customization leads to beneficial results in the design of a self-paced BI for individuals with spinal cord injury.

The expression of '150-kDa oxygen regulated protein (ORP-150)' in human brain and its relationship with duration time until death.

PubMed

Ikematsu, Kazuya; Tsuda, Ryouichi; Kondo, Toshikazu; Kondo, Hisayoshi; Ozawa, Kentaro; Ogawa, Satoshi; Nakasono, Ichiro

2004-04-01

The expression of oxygen regulated protein 150-kDa (ORP-150) was strongly induced in human brain under the hypoxic conditions. We examined the expression of ORP-150 in the brain samples, and discussed its significance in forensic practice. The cerebral cortexes of 31 cases (asphyxia: 9 cases, hypothermia: 4, exsanguinations: 5, CO intoxication (CO): 6, sudden cardiac death (SCD): 7) were used for this study. Each tissue section was incubated with anti-ORP-150 polyclonal antibody and the number of ORP-150 positive cells were counted. In the multiple linear regression method, the estimated regression coefficient of ORP-150 on age was significant (P=0.039) thus, we could find that the ORP-150 expression level depended on age. Using analysis of covariance, we compared the means of ORP-150, LSMEAN, which means hypothetic average value excluding influence of age, for each cause of death. The LSMEAN+/-SE was 84.74+/-9.03 in hypothermia, 57.52+/-6.34 in asphyxia, 46.68+/-6.70 in CO, 24.84+/-8.05 in exsanguinations, and 16.24+/-7.35 in SCD. As a result of the analysis, the LSMEAN of the ORP-150 expression level was related to the cause of death. There might be differences in the duration of brain ischemia before death. For example, SCD is presumed to be instant death, while brain ischemia continues for several minutes in asphyxia, CO and exsanguinations, and for several hours in hypothermia cases. Therefore, the immunohistochemical and morphometrical analysis of ORP-150 in the brain may be very useful to determine the duration of brain ischemia before death in forensic autopsy cases.

Genome-wide scan of healthy human connectome discovers SPON1 gene variant influencing dementia severity

PubMed Central

Jahanshad, Neda; Rajagopalan, Priya; Hua, Xue; Hibar, Derrek P.; Nir, Talia M.; Toga, Arthur W.; Jack, Clifford R.; Saykin, Andrew J.; Green, Robert C.; Weiner, Michael W.; Medland, Sarah E.; Montgomery, Grant W.; Hansell, Narelle K.; McMahon, Katie L.; de Zubicaray, Greig I.; Martin, Nicholas G.; Wright, Margaret J.; Thompson, Paul M.; Weiner, Michael; Aisen, Paul; Weiner, Michael; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowski, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Liu, Enchi; Green, Robert C.; Montine, Tom; Petersen, Ronald; Aisen, Paul; Gamst, Anthony; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Gessert, Devon; Sather, Tamie; Beckett, Laurel; Harvey, Danielle; Gamst, Anthony; Donohue, Michael; Kornak, John; Jack, Clifford R.; Dale, Anders; Bernstein, Matthew; Felmlee, Joel; Fox, Nick; Thompson, Paul; Schuff, Norbert; Alexander, Gene; DeCarli, Charles; Jagust, William; Bandy, Dan; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Morris, John; Cairns, Nigel J.; Taylor-Reinwald, Lisa; Trojanowki, J.Q.; Shaw, Les; Lee, Virginia M.Y.; Korecka, Magdalena; Toga, Arthur W.; Crawford, Karen; Neu, Scott; Saykin, Andrew J.; Foroud, Tatiana M.; Potkin, Steven; Shen, Li; Khachaturian, Zaven; Frank, Richard; Snyder, Peter J.; Molchan, Susan; Kaye, Jeffrey; Quinn, Joseph; Lind, Betty; Dolen, Sara; Schneider, Lon S.; Pawluczyk, Sonia; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Heidebrink, Judith L.; Lord, Joanne L.; Petersen, Ronald; Johnson, Kris; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Morris, John C.; Ances, Beau; Carroll, Maria; Leon, Sue; Mintun, Mark A.; Schneider, Stacy; Marson, Daniel; Griffith, Randall; Clark, David; Grossman, Hillel; Mitsis, Effie; Romirowsky, Aliza; deToledo-Morrell, Leyla; Shah, Raj C.; Duara, Ranjan; Varon, Daniel; Roberts, Peggy; Albert, Marilyn; Onyike, Chiadi; Kielb, Stephanie; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Coleman, R. Edward; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Lopez, Oscar L.; Oakley, MaryAnn; Simpson, Donna M.; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Diaz-Arrastia, Ramon; King, Richard; Weiner, Myron; Martin-Cook, Kristen; DeVous, Michael; Levey, Allan I.; Lah, James J.; Cellar, Janet S.; Burns, Jeffrey M.; Anderson, Heather S.; Swerdlow, Russell H.; Apostolova, Liana; Lu, Po H.; Bartzokis, George; Silverman, Daniel H.S.; Graff-Radford, Neill R.; Parfitt, Francine; Johnson, Heather; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Herring, Scott; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Hsiung, Ging-Yuek Robin; Feldman, Howard; Mudge, Benita; Assaly, Michele; Kertesz, Andrew; Rogers, John; Trost, Dick; Bernick, Charles; Munic, Donna; Kerwin, Diana; Mesulam, Marek-Marsel; Lipowski, Kristina; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Martinez, Walter; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Frey, Meghan; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan; Belden, Christine; Jacobson, Sandra; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O.; Wolday, Saba; Bwayo, Salome K.; Lerner, Alan; Hudson, Leon; Ogrocki, Paula; Fletcher, Evan; Carmichael, Owen; Olichney, John; DeCarli, Charles; Kittur, Smita; Borrie, Michael; Lee, T.-Y.; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Potkin, Steven G.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Saykin, Andrew J.; Santulli, Robert B.; Schwartz, Eben S.; Sink, Kaycee M.; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Mintzer, Jacobo; Longmire, Crystal Flynn; Spicer, Kenneth; Finger, Elizabeth; Rachinsky, Irina; Rogers, John; Kertesz, Andrew; Drost, Dick

2013-01-01

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases. PMID:23471985

The functional connectome of cognitive reserve

PubMed Central

Marques, Paulo; Moreira, Pedro; Magalhães, Ricardo; Costa, Patrício; Santos, Nadine; Zihl, Josef; Soares, José

2016-01-01

Abstract Cognitive Reserve (CR) designates the brain's capacity to actively cope with insults through a more efficient use of its resources/networks. It was proposed in order to explain the discrepancies between the observed cognitive ability and the expected capacity for an individual. Typical proxies of CR include education and Intelligence Quotient but none totally account for the variability of CR and no study has shown if the brain's greater efficiency associated with CR can be measured. We used a validated model to estimate CR from the residual variance in memory and general executive functioning, accounting for both brain anatomical (i.e., gray matter and white matter signal abnormalities volume) and demographic variables (i.e., years of formal education and sex). Functional connectivity (FC) networks and topological properties were explored for associations with CR. Demographic characteristics, mainly accounted by years of formal education, were associated with higher FC, clustering, local efficiency and strength in parietal and occipital regions and greater network transitivity. Higher CR was associated with a greater FC, local efficiency and clustering of occipital regions, strength and centrality of the inferior temporal gyrus and higher global efficiency. Altogether, these findings suggest that education may facilitate the brain's ability to form segregated functional groups, reinforcing the view that higher education level triggers more specialized use of neural processing. Additionally, this study demonstrated for the first time that CR is associated with more efficient processing of information in the human brain and reinforces the existence of a fine balance between segregation and integration. Hum Brain Mapp 37:3310–3322, 2016.. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27144904

Effects of omega-3 polyunsaturated fatty acids on human brain morphology and function: What is the evidence?

PubMed

Bos, Dienke J; van Montfort, Simone J T; Oranje, Bob; Durston, Sarah; Smeets, Paul A M

2016-03-01

Public opinion and media coverage suggest that there are benefits of long-chain ω-3 polyunsaturated fatty acid (LC-PUFA) intake on brain functioning. However, it is an open question whether this is indeed the case. Therefore, we reviewed the evidence for effects of ω-3 LC-PUFA on human brain morphology and function. We included studies on (1) naturalistic long-term ω-3 LC-PUFA intake during life (2) the effects of short-term ω-3 LC-PUFA supplementation in healthy subjects and (3) the effects of ω-3 LC-PUFA supplementation as alternative or add-on treatment for psychiatric or neurological disorders. To date, 24 studies have been published on the effect of ω-3 LC-PUFA on brain function and structure. Findings from naturalistic studies and clinical trials in healthy individuals indicate that ω-3 LC-PUFA intake may be associated with increased functional activation of the prefrontal cortex in children, and greater gray matter volume and white matter integrity during aging. However, most naturalistic studies were cross-sectional or did not find any effect on cognition. As such, it is hard to estimate the magnitude of any beneficial effects. Furthermore, there is only limited evidence to support that ω-3 LC-PUFA supplementation is beneficial in brain disorders, such as Alzheimer's Disease, Attention Deficit/Hyperactivity Disorder, Major Depressive Disorder and schizophrenia. Overall, the literature suggests that sensitivity to supplementation may vary over development, and as a consequence of brain disorders. The biological mechanisms underlying any (beneficial) effects ω-3 LC-PUFAs on the brain are currently unknown and need to be investigated. Copyright © 2016 Elsevier B.V. and ECNP. All rights reserved.

Brain/MINDS: brain-mapping project in Japan

PubMed Central

Okano, Hideyuki; Miyawaki, Atsushi; Kasai, Kiyoto

2015-01-01

There is an emerging interest in brain-mapping projects in countries across the world, including the USA, Europe, Australia and China. In 2014, Japan started a brain-mapping project called Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS). Brain/MINDS aims to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain, and takes advantage of a unique non-human primate animal model, the common marmoset (Callithrix jacchus). In Brain/MINDS, the RIKEN Brain Science Institute acts as a central institute. The objectives of Brain/MINDS can be categorized into the following three major subject areas: (i) structure and functional mapping of a non-human primate brain (the marmoset brain); (ii) development of innovative neurotechnologies for brain mapping; and (iii) human brain mapping; and clinical research. Brain/MINDS researchers are highly motivated to identify the neuronal circuits responsible for the phenotype of neurological and psychiatric disorders, and to understand the development of these devastating disorders through the integration of these three subject areas. PMID:25823872

An in vivo model of functional and vascularized human brain organoids.

PubMed

Mansour, Abed AlFatah; Gonçalves, J Tiago; Bloyd, Cooper W; Li, Hao; Fernandes, Sarah; Quang, Daphne; Johnston, Stephen; Parylak, Sarah L; Jin, Xin; Gage, Fred H

2018-06-01

Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.

Age-related changes in the ease of dynamical transitions in human brain activity.

PubMed

Ezaki, Takahiro; Sakaki, Michiko; Watanabe, Takamitsu; Masuda, Naoki

2018-06-01

Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks. © 2018 Wiley Periodicals, Inc.

Genetic and environmental influences on the size of specific brain regions in midlife: the VETSA MRI study.

PubMed

Kremen, William S; Prom-Wormley, Elizabeth; Panizzon, Matthew S; Eyler, Lisa T; Fischl, Bruce; Neale, Michael C; Franz, Carol E; Lyons, Michael J; Pacheco, Jennifer; Perry, Michele E; Stevens, Allison; Schmitt, J Eric; Grant, Michael D; Seidman, Larry J; Thermenos, Heidi W; Tsuang, Ming T; Eisen, Seth A; Dale, Anders M; Fennema-Notestine, Christine

2010-01-15

The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individual-specific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study of Aging (VETSA). They were 51-59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00-0.75) as compared with subcortical and ventricular ROIs (0.48-0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.

Influence of the partial volume correction method on 18F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM

NASA Astrophysics Data System (ADS)

Bowen, Spencer L.; Byars, Larry G.; Michel, Christian J.; Chonde, Daniel B.; Catana, Ciprian

2013-10-01

Kinetic parameters estimated from dynamic 18F-fluorodeoxyglucose (18F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting 18F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Influence of the partial volume correction method on (18)F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM.

PubMed

Bowen, Spencer L; Byars, Larry G; Michel, Christian J; Chonde, Daniel B; Catana, Ciprian

2013-10-21

Kinetic parameters estimated from dynamic (18)F-fluorodeoxyglucose ((18)F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting (18)F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in most cases compared to the other PVC methods. The results indicate that the PVC implementation and choice of PSF modelling in the reconstruction can significantly impact model parameters.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other's Actions by Humans.

PubMed

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2017-01-01

The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants' ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert's abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert's self-estimation is explained only by considering a change in the individual's forward model, showing that an improvement in an expert's ability to predict outcomes of observed actions affects the individual's forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions.

Detection and mapping of delays in early cortical folding derived from in utero MRI

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Rajagopalan, Vidya; Scott, Julia A.; Kim, Kio; Roosta, Ahmad; Rousseau, Francois; Barkovich, A. James; Glenn, Orit A.; Studholme, Colin

2011-03-01

Understanding human brain development in utero and detecting cortical abnormalities related to specific clinical conditions is an important area of research. In this paper, we describe and evaluate methodology for detection and mapping of delays in early cortical folding from population-based studies of fetal brain anatomies imaged in utero. We use a general linear modeling framework to describe spatiotemporal changes in curvature of the developing brain and explore the ability to detect and localize delays in cortical folding in the presence of uncertainty in estimation of the fetal age. We apply permutation testing to examine which regions of the brain surface provide the most statistical power to detect a given folding delay at a given developmental stage. The presented methodology is evaluated using MR scans of fetuses with normal brain development and gestational ages ranging from 20.57 to 27.86 weeks. This period is critical in early cortical folding and the formation of the primary and secondary sulci. Finally, we demonstrate a clinical application of the framework for detection and localization of folding delays in fetuses with isolated mild ventriculomegaly.

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

PubMed

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

Human biodistribution and dosimetry of 18F-JNJ42259152, a radioligand for phosphodiesterase 10A imaging.

PubMed

Van Laere, Koen; Ahmad, Rawaha U; Hudyana, Hendra; Celen, Sofie; Dubois, Kristof; Schmidt, Mark E; Bormans, Guy; Koole, Michel

2013-01-01

Phosphodiesterase 10A (PDE10A) is a cAMP/cGMP-hydrolysing enzyme with a central role in striatal signalling and implicated in neuropsychiatric disorders such as Huntington's disease, Parkinson's disease, schizophrenia and addiction. We have developed a novel PDE10A PET ligand, (18)F-JNJ42259152, and describe here its human dynamic biodistribution, safety and dosimetry. Six male subjects (age range 23-67 years) underwent ten dynamic whole-body PET/CT scans over 6 h after bolus injection of 175.5 ± 9.4 MBq (18)F-JNJ42259152. Source organs were delineated on PET/CT and individual organ doses and effective dose were determined using the OLINDA software. F-JNJ42259152 was readily taken up by the brain and showed exclusive retention in the brain, especially in the striatum with good washout starting after 20 min. The tracer was cleared through both the hepatobiliary and the urinary routes. No defluorination was observed. Organ absorbed doses were largest for the gallbladder (239 μSv/MBq) and upper large intestine (138 μSv/MBq). The mean effective dose was 24.9 ± 4.1 μSv/MBq. No adverse events were encountered. In humans, (18)F-JNJ42259152 has an appropriate distribution, brain kinetics and safety. The estimated effective dose was within WHO class IIb with low interindividual variability. Therefore, the tracer is suitable for further kinetic evaluation in humans.

Regional selection of the brain size regulating gene CASC5 provides new insight into human brain evolution.

PubMed

Shi, Lei; Hu, Enzhi; Wang, Zhenbo; Liu, Jiewei; Li, Jin; Li, Ming; Chen, Hua; Yu, Chunshui; Jiang, Tianzi; Su, Bing

2017-02-01

Human evolution is marked by a continued enlargement of the brain. Previous studies on human brain evolution focused on identifying sequence divergences of brain size regulating genes between humans and nonhuman primates. However, the evolutionary pattern of the brain size regulating genes during recent human evolution is largely unknown. We conducted a comprehensive analysis of the brain size regulating gene CASC5 and found that in recent human evolution, CASC5 has accumulated many modern human specific amino acid changes, including two fixed changes and six polymorphic changes. Among human populations, 4 of the 6 amino acid polymorphic sites have high frequencies of derived alleles in East Asians, but are rare in Europeans and Africans. We proved that this between-population allelic divergence was caused by regional Darwinian positive selection in East Asians. Further analysis of brain image data of Han Chinese showed significant associations of the amino acid polymorphic sites with gray matter volume. Hence, CASC5 may contribute to the morphological and structural changes of the human brain during recent evolution. The observed between-population divergence of CASC5 variants was driven by natural selection that tends to favor a larger gray matter volume in East Asians.

Assessment of 10B concentration in boron neutron capture therapy: potential of image-guided therapy using 18FBPA PET.

PubMed

Shimosegawa, Eku; Isohashi, Kayako; Naka, Sadahiro; Horitsugi, Genki; Hatazawa, Jun

2016-12-01

In boron neutron capture therapy (BNCT) for cancer, the accurate estimation of 10 B tissue concentrations, especially in neighboring normal organs, is important to avoid adverse effects. The 10 B concentration in normal organs after loading with 10 B, however, has not been established in humans. In this study, we performed 4-borono-2-[ 18 F]-fluoro-phenylalanine ( 18 FBPA) PET in healthy volunteers and estimated the chronological changes in the 10 B concentrations of normal organs. In 6 healthy volunteers, whole-body 18 FBPA PET scans were repeated 7 times during 1 h, and the mean 18 FBPA distributions of 13 organs were measured. Based on the 18 FBPA PET data, we then estimated the changes in the 10 B concentrations of the organs when the injection of a therapeutic dose of 10 BPA-fructose complex ( 10 BPA-fr; 30 g, 500 mg/kg body weight) was assumed. The maximum mean 18 FBPA concentrations were reached at 2-6 min after injection in all the organs except the brain and urinary bladder. The mean 18 FBPA concentration in normal brain plateaued at 24 min after injection. When the injection of a therapeutic dose of 10 BPA-fr was assumed, the estimated mean 10 B concentration in the kidney increased to 126.1 ± 24.2 ppm at 3 min after injection and then rapidly decreased to 30.9 ± 7.4 ppm at 53 min. The estimated mean 10 B concentration in the bladder gradually increased and reached 383.6 ± 214.7 ppm at 51 min. The mean 10 B concentration in the brain was estimated to be 7.6 ± 1.5 ppm at 57 min. 18 FBPA PET has a potential to estimate 10 B concentration of normal organs before neutron irradiation of BNCT when several assumptions are validated in the future studies.

Influence of P-Glycoprotein Inhibition or Deficiency at the Blood-Brain Barrier on (18)F-2-Fluoro-2-Deoxy-D-glucose ( (18)F-FDG) Brain Kinetics.

PubMed

Tournier, Nicolas; Saba, Wadad; Goutal, Sébastien; Gervais, Philippe; Valette, Héric; Scherrmann, Jean-Michel; Bottlaender, Michel; Cisternino, Salvatore

2015-05-01

The fluorinated D-glucose analog (18)F-2-fluoro-2-deoxy-D-glucose ((18)F-FDG) is the most prevalent radiopharmaceutical for positron emission tomography (PET) imaging. P-Glycoprotein's (P-gp, MDR1, and ABCB1) function in various cancer cell lines and tumors was shown to impact (18)F-FDG incorporation, suggesting that P-gp function at the blood-brain barrier may also modulate (18)F-FDG brain kinetics. We tested the influence of P-gp inhibition using the cyclosporine analog valspodar (PSC833; 5 μM) on the uptake of (18)F-FDG in standardized human P-gp-overexpressing cells (MDCKII-MDR1). Consequences for (18)F-FDG brain kinetics were then assessed using (i) (18)F-FDG PET imaging and suitable kinetic modelling in baboons without or with P-gp inhibition by intravenous cyclosporine infusion (15 mg kg(-1) h(-1)) and (ii) in situ brain perfusion in wild-type and P-gp/Bcrp (breast cancer resistance protein) knockout mice and controlled D-glucose exposure to the brain. In vitro, the time course of (18)F-FDG uptake in MDR1 cells was influenced by the presence of valspodar in the absence of D-glucose but not in the presence of high D-glucose concentration. PET analysis revealed that P-gp inhibition had no significant impact on estimated brain kinetics parameters K 1, k 2, k 3, V T , and CMRGlc. The lack of P-gp effect on in vivo (18)F-FDG brain distribution was confirmed in P-gp/Bcrp-deficient mice. P-gp inhibition indirectly modulates (18)F-FDG uptake into P-gp-overexpressing cells, possibly through differences in the energetic cell level state. (18)F-FDG is not a P-gp substrate at the BBB and (18)F-FDG brain kinetics as well as estimated brain glucose metabolism are influenced by neither P-gp inhibition nor P-gp/Bcrp deficiencies in baboon and mice, respectively.

Accelerated recruitment of new brain development genes into the human genome.

PubMed

Zhang, Yong E; Landback, Patrick; Vibranovski, Maria D; Long, Manyuan

2011-10-01

How the human brain evolved has attracted tremendous interests for decades. Motivated by case studies of primate-specific genes implicated in brain function, we examined whether or not the young genes, those emerging genome-wide in the lineages specific to the primates or rodents, showed distinct spatial and temporal patterns of transcription compared to old genes, which had existed before primate and rodent split. We found consistent patterns across different sources of expression data: there is a significantly larger proportion of young genes expressed in the fetal or infant brain of humans than in mouse, and more young genes in humans have expression biased toward early developing brains than old genes. Most of these young genes are expressed in the evolutionarily newest part of human brain, the neocortex. Remarkably, we also identified a number of human-specific genes which are expressed in the prefrontal cortex, which is implicated in complex cognitive behaviors. The young genes upregulated in the early developing human brain play diverse functional roles, with a significant enrichment of transcription factors. Genes originating from different mechanisms show a similar expression bias in the developing brain. Moreover, we found that the young genes upregulated in early brain development showed rapid protein evolution compared to old genes also expressed in the fetal brain. Strikingly, genes expressed in the neocortex arose soon after its morphological origin. These four lines of evidence suggest that positive selection for brain function may have contributed to the origination of young genes expressed in the developing brain. These data demonstrate a striking recruitment of new genes into the early development of the human brain.

Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivity

NASA Astrophysics Data System (ADS)

Giancardo, Luca; Ellmore, Timothy M.; Suescun, Jessika; Ocasio, Laura; Kamali, Arash; Riascos-Castaneda, Roy; Schiess, Mya C.

2018-02-01

Methods to identify neuroplasticity patterns in human brains are of the utmost importance in understanding and potentially treating neurodegenerative diseases. Parkinson disease (PD) research will greatly benefit and advance from the discovery of biomarkers to quantify brain changes in the early stages of the disease, a prodromal period when subjects show no obvious clinical symptoms. Diffusion tensor imaging (DTI) allows for an in-vivo estimation of the structural connectome inside the brain and may serve to quantify the degenerative process before the appearance of clinical symptoms. In this work, we introduce a novel strategy to compute longitudinal structural connectomes in the context of a whole-brain data-driven pipeline. In these initial tests, we show that our predictive models are able to distinguish controls from asymptomatic subjects at high risk of developing PD (REM sleep behavior disorder, RBD) with an area under the receiving operating characteristic curve of 0.90 (p<0.001) and a longitudinal dataset of 46 subjects part of the Parkinson's Progression Markers Initiative. By analyzing the brain connections most relevant for the predictive ability of the best performing model, we find connections that are biologically relevant to the disease.

Compartmental analysis of [11C]flumazenil kinetics for the estimation of ligand transport rate and receptor distribution using positron emission tomography.

PubMed

Koeppe, R A; Holthoff, V A; Frey, K A; Kilbourn, M R; Kuhl, D E

1991-09-01

The in vivo kinetic behavior of [11C]flumazenil ([11C]FMZ), a non-subtype-specific central benzodiazepine antagonist, is characterized using compartmental analysis with the aim of producing an optimized data acquisition protocol and tracer kinetic model configuration for the assessment of [11C]FMZ binding to benzodiazepine receptors (BZRs) in human brain. The approach presented is simple, requiring only a single radioligand injection. Dynamic positron emission tomography data were acquired on 18 normal volunteers using a 60- to 90-min sequence of scans and were analyzed with model configurations that included a three-compartment, four-parameter model, a three-compartment, three-parameter model, with a fixed value for free plus nonspecific binding; and a two-compartment, two-parameter model. Statistical analysis indicated that a four-parameter model did not yield significantly better fits than a three-parameter model. Goodness of fit was improved for three- versus two-parameter configurations in regions with low receptor density, but not in regions with moderate to high receptor density. Thus, a two-compartment, two-parameter configuration was found to adequately describe the kinetic behavior of [11C]FMZ in human brain, with stable estimates of the model parameters obtainable from as little as 20-30 min of data. Pixel-by-pixel analysis yields functional images of transport rate (K1) and ligand distribution volume (DV"), and thus provides independent estimates of ligand delivery and BZR binding.

Pain anticipation: an activation likelihood estimation meta-analysis of brain imaging studies.

PubMed

Palermo, Sara; Benedetti, Fabrizio; Costa, Tommaso; Amanzio, Martina

2015-05-01

The anticipation of pain has been investigated in a variety of brain imaging studies. Importantly, today there is no clear overall picture of the areas that are involved in different studies and the exact role of these regions in pain expectation remains especially unexploited. To address this issue, we used activation likelihood estimation meta-analysis to analyze pain anticipation in several neuroimaging studies. A total of 19 functional magnetic resonance imaging were included in the analysis to search for the cortical areas involved in pain anticipation in human experimental models. During anticipation, activated foci were found in the dorsolateral prefrontal, midcingulate and anterior insula cortices, medial and inferior frontal gyri, inferior parietal lobule, middle and superior temporal gyrus, thalamus, and caudate. Deactivated foci were found in the anterior cingulate, superior frontal gyrus, parahippocampal gyrus and in the claustrum. The results of the meta-analytic connectivity analysis provide an overall view of the brain responses triggered by the anticipation of a noxious stimulus. Such a highly distributed perceptual set of self-regulation may prime brain regions to process information where emotion, action and perception as well as their related subcategories play a central role. Not only do these findings provide important information on the neural events when anticipating pain, but also they may give a perspective into nocebo responses, whereby negative expectations may lead to pain worsening. © 2014 Wiley Periodicals, Inc.

Comparison of Dolphins' Body and Brain Measurements with Four Other Groups of Cetaceans Reveals Great Diversity.

PubMed

Ridgway, Sam H; Carlin, Kevin P; Van Alstyne, Kaitlin R; Hanson, Alicia C; Tarpley, Raymond J

2016-01-01

We compared mature dolphins with 4 other groupings of mature cetaceans. With a large data set, we found great brain diversity among 5 different taxonomic groupings. The dolphins in our data set ranged in body mass from about 40 to 6,750 kg and in brain mass from 0.4 to 9.3 kg. Dolphin body length ranged from 1.3 to 7.6 m. In our combined data set from the 4 other groups of cetaceans, body mass ranged from about 20 to 120,000 kg and brain mass from about 0.2 to 9.2 kg, while body length varied from 1.21 to 26.8 m. Not all cetaceans have large brains relative to their body size. A few dolphins near human body size have human-sized brains. On the other hand, the absolute brain mass of some other cetaceans is only one-sixth as large. We found that brain volume relative to body mass decreases from Delphinidae to a group of Phocoenidae and Monodontidae, to a group of other odontocetes, to Balaenopteroidea, and finally to Balaenidae. We also found the same general trend when we compared brain volume relative to body length, except that the Delphinidae and Phocoenidae-Monodontidae groups do not differ significantly. The Balaenidae have the smallest relative brain mass and the lowest cerebral cortex surface area. Brain parts also vary. Relative to body mass and to body length, dolphins also have the largest cerebellums. Cortex surface area is isometric with brain size when we exclude the Balaenidae. Our data show that the brains of Balaenidae are less convoluted than those of the other cetaceans measured. Large vascular networks inside the cranial vault may help to maintain brain temperature, and these nonbrain tissues increase in volume with body mass and with body length ranging from 8 to 65% of the endocranial volume. Because endocranial vascular networks and other adnexa, such as the tentorium cerebelli, vary so much in different species, brain size measures from endocasts of some extinct cetaceans may be overestimates. Our regression of body length on endocranial adnexa might be used for better estimates of brain volume from endocasts or from endocranial volume of living species or extinct cetaceans. © 2017 The Author(s) Published by S. Karger AG, Basel.

Comparison of Dolphins' Body and Brain Measurements with Four Other Groups of Cetaceans Reveals Great Diversity

PubMed Central

Ridgway, Sam H.; Carlin, Kevin P.; Van Alstyne, Kaitlin R.; Hanson, Alicia C.; Tarpley, Raymond J.

2017-01-01

We compared mature dolphins with 4 other groupings of mature cetaceans. With a large data set, we found great brain diversity among 5 different taxonomic groupings. The dolphins in our data set ranged in body mass from about 40 to 6,750 kg and in brain mass from 0.4 to 9.3 kg. Dolphin body length ranged from 1.3 to 7.6 m. In our combined data set from the 4 other groups of cetaceans, body mass ranged from about 20 to 120,000 kg and brain mass from about 0.2 to 9.2 kg, while body length varied from 1.21 to 26.8 m. Not all cetaceans have large brains relative to their body size. A few dolphins near human body size have human-sized brains. On the other hand, the absolute brain mass of some other cetaceans is only one-sixth as large. We found that brain volume relative to body mass decreases from Delphinidae to a group of Phocoenidae and Monodontidae, to a group of other odontocetes, to Balaenopteroidea, and finally to Balaenidae. We also found the same general trend when we compared brain volume relative to body length, except that the Delphinidae and Phocoenidae-Monodontidae groups do not differ significantly. The Balaenidae have the smallest relative brain mass and the lowest cerebral cortex surface area. Brain parts also vary. Relative to body mass and to body length, dolphins also have the largest cerebellums. Cortex surface area is isometric with brain size when we exclude the Balaenidae. Our data show that the brains of Balaenidae are less convoluted than those of the other cetaceans measured. Large vascular networks inside the cranial vault may help to maintain brain temperature, and these nonbrain tissues increase in volume with body mass and with body length ranging from 8 to 65% of the endocranial volume. Because endocranial vascular networks and other adnexa, such as the tentorium cerebelli, vary so much in different species, brain size measures from endocasts of some extinct cetaceans may be overestimates. Our regression of body length on endocranial adnexa might be used for better estimates of brain volume from endocasts or from endocranial volume of living species or extinct cetaceans. PMID:28122370

Estimated maximal and current brain volume predict cognitive ability in old age

PubMed Central

Royle, Natalie A.; Booth, Tom; Valdés Hernández, Maria C.; Penke, Lars; Murray, Catherine; Gow, Alan J.; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E.; Deary, Ian J.; Wardlaw, Joanna M.

2013-01-01

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. PMID:23850342

Concept of an upright wearable positron emission tomography imager in humans.

PubMed

Bauer, Christopher E; Brefczynski-Lewis, Julie; Marano, Gary; Mandich, Mary-Beth; Stolin, Alexander; Martone, Peter; Lewis, James W; Jaliparthi, Gangadhar; Raylman, Raymond R; Majewski, Stan

2016-09-01

Positron Emission Tomography (PET) is traditionally used to image patients in restrictive positions, with few devices allowing for upright, brain-dedicated imaging. Our team has explored the concept of wearable PET imagers which could provide functional brain imaging of freely moving subjects. To test feasibility and determine future considerations for development, we built a rudimentary proof-of-concept prototype (Helmet_PET) and conducted tests in phantoms and four human volunteers. Twelve Silicon Photomultiplier-based detectors were assembled in a ring with exterior weight support and an interior mechanism that could be adjustably fitted to the head. We conducted brain phantom tests as well as scanned four patients scheduled for diagnostic F(18-) FDG PET/CT imaging. For human subjects the imager was angled such that field of view included basal ganglia and visual cortex to test for typical resting-state pattern. Imaging in two subjects was performed ~4 hr after PET/CT imaging to simulate lower injected F(18-) FDG dose by taking advantage of the natural radioactive decay of the tracer (F(18) half-life of 110 min), with an estimated imaging dosage of 25% of the standard. We found that imaging with a simple lightweight ring of detectors was feasible using a fraction of the standard radioligand dose. Activity levels in the human participants were quantitatively similar to standard PET in a set of anatomical ROIs. Typical resting-state brain pattern activation was demonstrated even in a 1 min scan of active head rotation. To our knowledge, this is the first demonstration of imaging a human subject with a novel wearable PET imager that moves with robust head movements. We discuss potential research and clinical applications that will drive the design of a fully functional device. Designs will need to consider trade-offs between a low weight device with high mobility and a heavier device with greater sensitivity and larger field of view.

A statistical framework for neuroimaging data analysis based on mutual information estimated via a gaussian copula.

PubMed

Ince, Robin A A; Giordano, Bruno L; Kayser, Christoph; Rousselet, Guillaume A; Gross, Joachim; Schyns, Philippe G

2017-03-01

We begin by reviewing the statistical framework of information theory as applicable to neuroimaging data analysis. A major factor hindering wider adoption of this framework in neuroimaging is the difficulty of estimating information theoretic quantities in practice. We present a novel estimation technique that combines the statistical theory of copulas with the closed form solution for the entropy of Gaussian variables. This results in a general, computationally efficient, flexible, and robust multivariate statistical framework that provides effect sizes on a common meaningful scale, allows for unified treatment of discrete, continuous, unidimensional and multidimensional variables, and enables direct comparisons of representations from behavioral and brain responses across any recording modality. We validate the use of this estimate as a statistical test within a neuroimaging context, considering both discrete stimulus classes and continuous stimulus features. We also present examples of analyses facilitated by these developments, including application of multivariate analyses to MEG planar magnetic field gradients, and pairwise temporal interactions in evoked EEG responses. We show the benefit of considering the instantaneous temporal derivative together with the raw values of M/EEG signals as a multivariate response, how we can separately quantify modulations of amplitude and direction for vector quantities, and how we can measure the emergence of novel information over time in evoked responses. Open-source Matlab and Python code implementing the new methods accompanies this article. Hum Brain Mapp 38:1541-1573, 2017. © 2016 Wiley Periodicals, Inc. 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

PubMed Central

Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

2018-01-01

Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

PubMed

Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

2018-06-01

The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

Sampling theory and automated simulations for vertical sections, applied to human brain.

PubMed

Cruz-Orive, L M; Gelšvartas, J; Roberts, N

2014-02-01

In recent years, there have been substantial developments in both magnetic resonance imaging techniques and automatic image analysis software. The purpose of this paper is to develop stereological image sampling theory (i.e. unbiased sampling rules) that can be used by image analysts for estimating geometric quantities such as surface area and volume, and to illustrate its implementation. The methods will ideally be applied automatically on segmented, properly sampled 2D images - although convenient manual application is always an option - and they are of wide applicability in many disciplines. In particular, the vertical sections design to estimate surface area is described in detail and applied to estimate the area of the pial surface and of the boundary between cortex and underlying white matter (i.e. subcortical surface area). For completeness, cortical volume and mean cortical thickness are also estimated. The aforementioned surfaces were triangulated in 3D with the aid of FreeSurfer software, which provided accurate surface area measures that served as gold standards. Furthermore, a software was developed to produce digitized trace curves of the triangulated target surfaces automatically from virtual sections. From such traces, a new method (called the 'lambda method') is presented to estimate surface area automatically. In addition, with the new software, intersections could be counted automatically between the relevant surface traces and a cycloid test grid for the classical design. This capability, together with the aforementioned gold standard, enabled us to thoroughly check the performance and the variability of the different estimators by Monte Carlo simulations for studying the human brain. In particular, new methods are offered to split the total error variance into the orientations, sectioning and cycloid components. The latter prediction was hitherto unavailable--one is proposed here and checked by way of simulations on a given set of digitized vertical sections with automatically superimposed cycloid grids of three different sizes. Concrete and detailed recommendations are given to implement the methods. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

The Language–Number Interface in the Brain: A Complex Parametric Study of Quantifiers and Quantities

PubMed Central

Heim, Stefan; Amunts, Katrin; Drai, Dan; Eickhoff, Simon B.; Hautvast, Sarah; Grodzinsky, Yosef

2011-01-01

The neural bases for numerosity and language are of perennial interest. In monkeys, neural separation of numerical Estimation and numerical Comparison has been demonstrated. As linguistic and numerical knowledge can only be compared in humans, we used a new fMRI paradigm in an attempt to dissociate Estimation from Comparison, and at the same time uncover the neural relation between numerosity and language. We used complex stimuli: images depicting a proportion between quantities of blue and yellow circles were coupled with sentences containing quantifiers that described them (e.g., “most/few of the circles are yellow”). Participants verified sentences against images. Both Estimation and Comparison recruited adjacent, partially overlapping bi-hemispheric fronto-parietal regions. Additional semantic analysis of positive vs. negative quantifiers involving the interpretation of quantity and numerosity specifically recruited left area 45. The anatomical proximity between numerosity regions and those involved in semantic analysis points to subtle links between the number system and language. Results fortify the homology of Estimation and Comparison between humans and monkeys. PMID:22470338

The brain-life theory: towards a consistent biological definition of humanness.

PubMed Central

Goldenring, J M

1985-01-01

This paper suggests that medically the term a 'human being' should be defined by the presence of an active human brain. The brain is the only unique and irreplaceable organ in the human body, as the orchestrator of all organ systems and the seat of personality. Thus, the presence or absence of brain life truly defines the presence or absence of human life in the medical sense. When viewed in this way, human life may be seen as a continuous spectrum between the onset of brain life in utero (eight weeks gestation), until the occurrence of brain death. At any point human tissue or organ systems may be present, but without the presence of a functional human brain, these do not constitute a 'human being', at least in a medical sense. The implications of this theory for various ethical concerns such as in vitro fertilisation and abortion are discussed. This theory is the most consistent possible for the definition of a human being with no contradictions inherent. However, having a good theory of definition of a 'human being' does not necessarily solve the ethical problems discussed herein. PMID:4078859

Mechanical properties of porcine brain tissue in vivo and ex vivo estimated by MR elastography.

PubMed

Guertler, Charlotte A; Okamoto, Ruth J; Schmidt, John L; Badachhape, Andrew A; Johnson, Curtis L; Bayly, Philip V

2018-03-01

The mechanical properties of brain tissue in vivo determine the response of the brain to rapid skull acceleration. These properties are thus of great interest to the developers of mathematical models of traumatic brain injury (TBI) or neurosurgical simulations. Animal models provide valuable insight that can improve TBI modeling. In this study we compare estimates of mechanical properties of the Yucatan mini-pig brain in vivo and ex vivo using magnetic resonance elastography (MRE) at multiple frequencies. MRE allows estimations of properties in soft tissue, either in vivo or ex vivo, by imaging harmonic shear wave propagation. Most direct measurements of brain mechanical properties have been performed using samples of brain tissue ex vivo. It has been observed that direct estimates of brain mechanical properties depend on the frequency and amplitude of loading, as well as the time post-mortem and condition of the sample. Using MRE in the same animals at overlapping frequencies, we observe that porcine brain tissue in vivo appears stiffer than porcine brain tissue samples ex vivo at frequencies of 100 Hz and 125 Hz, but measurements show closer agreement at lower frequencies. Copyright © 2018 Elsevier Ltd. All rights reserved.

How Haptic Size Sensations Improve Distance Perception

PubMed Central

Battaglia, Peter W.; Kersten, Daniel; Schrater, Paul R.

2011-01-01

Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual “posterior sampling”. In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information. PMID:21738457

Multisensory decisions provide support for probabilistic number representations.

PubMed

Kanitscheider, Ingmar; Brown, Amanda; Pouget, Alexandre; Churchland, Anne K

2015-06-01

A large body of evidence suggests that an approximate number sense allows humans to estimate numerosity in sensory scenes. This ability is widely observed in humans, including those without formal mathematical training. Despite this, many outstanding questions remain about the nature of the numerosity representation in the brain. Specifically, it is not known whether approximate numbers are represented as scalar estimates of numerosity or, alternatively, as probability distributions over numerosity. In the present study, we used a multisensory decision task to distinguish these possibilities. We trained human subjects to decide whether a test stimulus had a larger or smaller numerosity compared with a fixed reference. Depending on the trial, the numerosity was presented as either a sequence of visual flashes or a sequence of auditory tones, or both. To test for a probabilistic representation, we varied the reliability of the stimulus by adding noise to the visual stimuli. In accordance with a probabilistic representation, we observed a significant improvement in multisensory compared with unisensory trials. Furthermore, a trial-by-trial analysis revealed that although individual subjects showed strategic differences in how they leveraged auditory and visual information, all subjects exploited the reliability of unisensory cues. An alternative, nonprobabilistic model, in which subjects combined cues without regard for reliability, was not able to account for these trial-by-trial choices. These findings provide evidence that the brain relies on a probabilistic representation for numerosity decisions. Copyright © 2015 the American Physiological Society.

Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality, and Emotion.

PubMed

Kong, Ru; Li, Jingwei; Orban, Csaba; Sabuncu, Mert R; Liu, Hesheng; Schaefer, Alexander; Sun, Nanbo; Zuo, Xi-Nian; Holmes, Avram J; Eickhoff, Simon B; Yeo, B T Thomas

2018-06-06

Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to delineate individual-specific brain networks. A major question is whether individual-specific network topography (i.e., location and spatial arrangement) is behaviorally relevant. Here, we propose a multi-session hierarchical Bayesian model (MS-HBM) for estimating individual-specific cortical networks and investigate whether individual-specific network topography can predict human behavior. The multiple layers of the MS-HBM explicitly differentiate intra-subject (within-subject) from inter-subject (between-subject) network variability. By ignoring intra-subject variability, previous network mappings might confuse intra-subject variability for inter-subject differences. Compared with other approaches, MS-HBM parcellations generalized better to new rs-fMRI and task-fMRI data from the same subjects. More specifically, MS-HBM parcellations estimated from a single rs-fMRI session (10 min) showed comparable generalizability as parcellations estimated by 2 state-of-the-art methods using 5 sessions (50 min). We also showed that behavioral phenotypes across cognition, personality, and emotion could be predicted by individual-specific network topography with modest accuracy, comparable to previous reports predicting phenotypes based on connectivity strength. Network topography estimated by MS-HBM was more effective for behavioral prediction than network size, as well as network topography estimated by other parcellation approaches. Thus, similar to connectivity strength, individual-specific network topography might also serve as a fingerprint of human behavior.

Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

PubMed

Whittingstall, Kevin; Bartels, Andreas; Singh, Vanessa; Kwon, Soyoung; Logothetis, Nikos K

2010-10-01

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an estimate of the current density at every time point. We then carried out a correlation between the time series of visual contrast changes in the movie with that of EEG voxels. We found the most significant correlations in visual area V1, just as seen in previous fMRI studies (Bartels A, Zeki, S, Logothetis NK. Natural vision reveals regional specialization to local motion and to contrast-invariant, global flow in the human brain. Cereb Cortex 2008;18(3):705-717), but on the time scale of milliseconds rather than of seconds. To obtain an estimate of how the EEG signal relates to the BOLD signal, we calculated the IRF between the BOLD signal and the estimated current density in area V1. We found that this IRF was very similar to that observed using combined intracortical recordings and fMRI experiments in nonhuman primates. Taken together, these findings open a new approach to noninvasive mapping of the brain. It allows, firstly, the localization of feature-selective brain areas during natural viewing conditions with the temporal resolution of EEG. Secondly, it provides a tool to assess EEG/BOLD transfer functions during processing of more natural stimuli. This is especially useful in combined EEG/fMRI experiments, where one can now potentially study neural-hemodynamic relationships across the whole brain volume in a noninvasive manner. Copyright © 2010 Elsevier Inc. All rights reserved.

Elevated gene expression levels distinguish human from non-human primate brains

PubMed Central

Cáceres, Mario; Lachuer, Joel; Zapala, Matthew A.; Redmond, John C.; Kudo, Lili; Geschwind, Daniel H.; Lockhart, David J.; Preuss, Todd M.; Barlow, Carrolee

2003-01-01

Little is known about how the human brain differs from that of our closest relatives. To investigate the genetic basis of human specializations in brain organization and cognition, we compared gene expression profiles for the cerebral cortex of humans, chimpanzees, and rhesus macaques by using several independent techniques. We identified 169 genes that exhibited expression differences between human and chimpanzee cortex, and 91 were ascribed to the human lineage by using macaques as an outgroup. Surprisingly, most differences between the brains of humans and non-human primates involved up-regulation, with ≈90% of the genes being more highly expressed in humans. By contrast, in the comparison of human and chimpanzee heart and liver, the numbers of up- and down-regulated genes were nearly identical. Our results indicate that the human brain displays a distinctive pattern of gene expression relative to non-human primates, with higher expression levels for many genes belonging to a wide variety of functional classes. The increased expression of these genes could provide the basis for extensive modifications of cerebral physiology and function in humans and suggests that the human brain is characterized by elevated levels of neuronal activity. PMID:14557539

Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited.

PubMed

Thomas, Cibu; Ye, Frank Q; Irfanoglu, M Okan; Modi, Pooja; Saleem, Kadharbatcha S; Leopold, David A; Pierpaoli, Carlo

2014-11-18

Tractography based on diffusion-weighted MRI (DWI) is widely used for mapping the structural connections of the human brain. Its accuracy is known to be limited by technical factors affecting in vivo data acquisition, such as noise, artifacts, and data undersampling resulting from scan time constraints. It generally is assumed that improvements in data quality and implementation of sophisticated tractography methods will lead to increasingly accurate maps of human anatomical connections. However, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of independent knowledge of the true anatomical connections in humans. Here we investigate the future prospects of DWI-based connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the macaque brain. The results of different tractography methods were compared with maps of known axonal projections from previous tracer studies in the macaque. Despite the exceptional quality of the DWI data, none of the methods demonstrated high anatomical accuracy. The methods that showed the highest sensitivity showed the lowest specificity, and vice versa. Additionally, anatomical accuracy was highly dependent upon parameters of the tractography algorithm, with different optimal values for mapping different pathways. These results suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is unlikely to be overcome by improvements in data acquisition and analysis alone.

A New Conditionally Immortalized Human Fetal Brain Pericyte Cell Line: Establishment and Functional Characterization as a Promising Tool for Human Brain Pericyte Studies.

PubMed

Umehara, Kenta; Sun, Yuchen; Hiura, Satoshi; Hamada, Koki; Itoh, Motoyuki; Kitamura, Keita; Oshima, Motohiko; Iwama, Atsushi; Saito, Kosuke; Anzai, Naohiko; Chiba, Kan; Akita, Hidetaka; Furihata, Tomomi

2018-07-01

While pericytes wrap around microvascular endothelial cells throughout the human body, their highest coverage rate is found in the brain. Brain pericytes actively contribute to various brain functions, including the development and stabilization of the blood-brain barrier (BBB), tissue regeneration, and brain inflammation. Accordingly, detailed characterization of the functional nature of brain pericytes is important for understanding the mechanistic basis of brain physiology and pathophysiology. Herein, we report on the development of a new human brain pericyte cell line, hereafter referred to as the human brain pericyte/conditionally immortalized clone 37 (HBPC/ci37). Developed via the cell conditionally immortalization method, these cells exhibited excellent proliferative ability at 33 °C. However, when cultured at 37 °C, HBPC/ci37 cells showed a differentiated phenotype that was marked by morphological alterations and increases in several pericyte-enriched marker mRNA levels, such as platelet-derived growth factor receptor β. It was also found that HBPC/ci37 cells possessed the facilitative ability of in vitro BBB formation and differentiation into a neuronal lineage. Furthermore, HBPC/ci37 cells exhibited the typical "reactive" features of brain pericytes in response to pro-inflammatory cytokines. To summarize, our results clearly demonstrate that HBPC/ci37 cells possess the ability to perform several key brain pericyte functions while also showing the capacity for extensive and continuous proliferation. Based on these findings, it can be expected that, as a unique human brain pericyte model, HBPC/ci37 cells have the potential to contribute to significant advances in the understanding of human brain pericyte physiology and pathophysiology.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images.

PubMed

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S; Lin, Weili; Shen, Dinggang

2015-09-01

Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient's exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [(18)F]FDG PET image by using a low-dose brain [(18)F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. The authors employ a regression forest for predicting the standard-dose brain [(18)F]FDG PET image by low-dose brain [(18)F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [(18)F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [(18)F]FDG PET image and substantially enhanced image quality of low-dose brain [(18)F]FDG PET image. In this paper, the authors propose a framework to generate standard-dose brain [(18)F]FDG PET image using low-dose brain [(18)F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [(18)F]FDG PET can be well-predicted using MRI and low-dose brain [(18)F]FDG PET.

Prediction of standard-dose brain PET image by using MRI and low-dose brain [18F]FDG PET images

PubMed Central

Kang, Jiayin; Gao, Yaozong; Shi, Feng; Lalush, David S.; Lin, Weili; Shen, Dinggang

2015-01-01

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. As yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [18F]FDG PET image by using a low-dose brain [18F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [18F]FDG PET image by low-dose brain [18F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [18F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [18F]FDG PET image and substantially enhanced image quality of low-dose brain [18F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [18F]FDG PET image using low-dose brain [18F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [18F]FDG PET can be well-predicted using MRI and low-dose brain [18F]FDG PET. PMID:26328979

Prediction of standard-dose brain PET image by using MRI and low-dose brain [{sup 18}F]FDG PET images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Jiayin; Gao, Yaozong; Shi, Feng

Purpose: Positron emission tomography (PET) is a nuclear medical imaging technology that produces 3D images reflecting tissue metabolic activity in human body. PET has been widely used in various clinical applications, such as in diagnosis of brain disorders. High-quality PET images play an essential role in diagnosing brain diseases/disorders. In practice, in order to obtain high-quality PET images, a standard-dose radionuclide (tracer) needs to be used and injected into a living body. As a result, it will inevitably increase the patient’s exposure to radiation. One solution to solve this problem is predicting standard-dose PET images using low-dose PET images. Asmore » yet, no previous studies with this approach have been reported. Accordingly, in this paper, the authors propose a regression forest based framework for predicting a standard-dose brain [{sup 18}F]FDG PET image by using a low-dose brain [{sup 18}F]FDG PET image and its corresponding magnetic resonance imaging (MRI) image. Methods: The authors employ a regression forest for predicting the standard-dose brain [{sup 18}F]FDG PET image by low-dose brain [{sup 18}F]FDG PET and MRI images. Specifically, the proposed method consists of two main steps. First, based on the segmented brain tissues (i.e., cerebrospinal fluid, gray matter, and white matter) in the MRI image, the authors extract features for each patch in the brain image from both low-dose PET and MRI images to build tissue-specific models that can be used to initially predict standard-dose brain [{sup 18}F]FDG PET images. Second, an iterative refinement strategy, via estimating the predicted image difference, is used to further improve the prediction accuracy. Results: The authors evaluated their algorithm on a brain dataset, consisting of 11 subjects with MRI, low-dose PET, and standard-dose PET images, using leave-one-out cross-validations. The proposed algorithm gives promising results with well-estimated standard-dose brain [{sup 18}F]FDG PET image and substantially enhanced image quality of low-dose brain [{sup 18}F]FDG PET image. Conclusions: In this paper, the authors propose a framework to generate standard-dose brain [{sup 18}F]FDG PET image using low-dose brain [{sup 18}F]FDG PET and MRI images. Both the visual and quantitative results indicate that the standard-dose brain [{sup 18}F]FDG PET can be well-predicted using MRI and low-dose brain [{sup 18}F]FDG PET.« less

Perivascular Mesenchymal Stem Cells From the Adult Human Brain Harbor No Instrinsic Neuroectodermal but High Mesodermal Differentiation Potential.

PubMed

Lojewski, Xenia; Srimasorn, Sumitra; Rauh, Juliane; Francke, Silvan; Wobus, Manja; Taylor, Verdon; Araúzo-Bravo, Marcos J; Hallmeyer-Elgner, Susanne; Kirsch, Matthias; Schwarz, Sigrid; Schwarz, Johannes; Storch, Alexander; Hermann, Andreas

2015-10-01

Brain perivascular cells have recently been identified as a novel mesodermal cell type in the human brain. These cells reside in the perivascular niche and were shown to have mesodermal and, to a lesser extent, tissue-specific differentiation potential. Mesenchymal stem cells (MSCs) are widely proposed for use in cell therapy in many neurological disorders; therefore, it is of importance to better understand the "intrinsic" MSC population of the human brain. We systematically characterized adult human brain-derived pericytes during in vitro expansion and differentiation and compared these cells with fetal and adult human brain-derived neural stem cells (NSCs) and adult human bone marrow-derived MSCs. We found that adult human brain pericytes, which can be isolated from the hippocampus and from subcortical white matter, are-in contrast to adult human NSCs-easily expandable in monolayer cultures and show many similarities to human bone marrow-derived MSCs both regarding both surface marker expression and after whole transcriptome profile. Human brain pericytes showed a negligible propensity for neuroectodermal differentiation under various differentiation conditions but efficiently generated mesodermal progeny. Consequently, human brain pericytes resemble bone marrow-derived MSCs and might be very interesting for possible autologous and endogenous stem cell-based treatment strategies and cell therapeutic approaches for treating neurological diseases. Perivascular mesenchymal stem cells (MSCs) recently gained significant interest because of their appearance in many tissues including the human brain. MSCs were often reported as being beneficial after transplantation in the central nervous system in different neurological diseases; therefore, adult brain perivascular cells derived from human neural tissue were systematically characterized concerning neural stem cell and MSC marker expression, transcriptomics, and mesodermal and inherent neuroectodermal differentiation potential in vitro and in vivo after in utero transplantation. This study showed the lack of an innate neuronal but high mesodermal differentiation potential. Because of their relationship to mesenchymal stem cells, these adult brain perivascular mesodermal cells are of great interest for possible autologous therapeutic use. ©AlphaMed Press.

Human brain lesion-deficit inference remapped.

PubMed

Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev

2014-09-01

Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury-the commonest aetiology in lesion-deficit studies-where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant. Positively, we show that novel machine learning techniques employing high-dimensional inference can nonetheless accurately converge on the true locus. We conclude that current inferences about human brain function and deficits based on lesion mapping must be re-evaluated with methodology that adequately captures the high-dimensional structure of lesion data. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.

New genes contribute to genetic and phenotypic novelties in human evolution

PubMed Central

Zhang, Yong E.; Long, Manyuan

2014-01-01

New genes in human genomes have been found relevant in evolution and biology of humans. It was conservatively estimated that the human genome encodes more than 300 human-specific genes and 1,000 primate-specific genes. These new arrivals appear to be implicated in brain function and male reproduction. Surprisingly, increasing evidence indicates that they may also bring negative pleiotropic effects, while assuming various possible biological functions as sources of phenotypic novelties, suggesting a non-progressive route for functional evolution. Similar to these fixed new genes, polymorphic new genes were found to contribute to functional evolution within species, e.g. with respect to digestion or disease resistance, revealing that new genes can acquire new or diverged functions in its initial stage as prototypic genes. These progresses have provided new opportunity to explore the genetic basis of human biology and human evolutionary history in a new dimension. PMID:25218862

Atlas-based fuzzy connectedness segmentation and intensity nonuniformity correction applied to brain MRI.

PubMed

Zhou, Yongxin; Bai, Jing

2007-01-01

A framework that combines atlas registration, fuzzy connectedness (FC) segmentation, and parametric bias field correction (PABIC) is proposed for the automatic segmentation of brain magnetic resonance imaging (MRI). First, the atlas is registered onto the MRI to initialize the following FC segmentation. Original techniques are proposed to estimate necessary initial parameters of FC segmentation. Further, the result of the FC segmentation is utilized to initialize a following PABIC algorithm. Finally, we re-apply the FC technique on the PABIC corrected MRI to get the final segmentation. Thus, we avoid expert human intervention and provide a fully automatic method for brain MRI segmentation. Experiments on both simulated and real MRI images demonstrate the validity of the method, as well as the limitation of the method. Being a fully automatic method, it is expected to find wide applications, such as three-dimensional visualization, radiation therapy planning, and medical database construction.

Analysis of a simulation algorithm for direct brain drug delivery

PubMed Central

Rosenbluth, Kathryn Hammond; Eschermann, Jan Felix; Mittermeyer, Gabriele; Thomson, Rowena; Mittermeyer, Stephan; Bankiewicz, Krystof S.

2011-01-01

Convection enhanced delivery (CED) achieves targeted delivery of drugs with a pressure-driven infusion through a cannula placed stereotactically in the brain. This technique bypasses the blood brain barrier and gives precise distributions of drugs, minimizing off-target effects of compounds such as viral vectors for gene therapy or toxic chemotherapy agents. The exact distribution is affected by the cannula positioning, flow rate and underlying tissue structure. This study presents an analysis of a simulation algorithm for predicting the distribution using baseline MRI images acquired prior to inserting the cannula. The MRI images included diffusion tensor imaging (DTI) to estimate the tissue properties. The algorithm was adapted for the devices and protocols identified for upcoming trials and validated with direct MRI visualization of Gadolinium in 20 infusions in non-human primates. We found strong agreement between the size and location of the simulated and gadolinium volumes, demonstrating the clinical utility of this surgical planning algorithm. PMID:21945468

Effects of Cell Phone Radiofrequency Signal Exposure on Brain Glucos Metabolism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volkow, N.D.; Wang, G.; Volkow, N.D.

The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with ({sup 18}F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice,more » once with the right cell phone activated (sound muted) for 50 minutes ('on' condition) and once with both cell phones deactivated ('off' condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm{sup 3}) and P < .05 (corrected for multiple comparisons) were considered significant. Brain glucose metabolism computed as absolute metabolism ({micro}mol/100 g per minute) and as normalized metabolism (region/whole brain). Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 {micro}mol/100 g per minute; mean difference, 2.4 [95% confidence interval, 0.67-4.2]; P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001). In healthy participants and compared with no exposure, 50-minute cell phone exposure was associated with increased brain glucose metabolism in the region closest to the antenna. This finding is of unknown clinical significance.« less

Effects of Cell Phone Radiofrequency Signal Exposure on Brain Glucose Metabolism

PubMed Central

Volkow, Nora D.; Tomasi, Dardo; Wang, Gene-Jack; Vaska, Paul; Fowler, Joanna S.; Telang, Frank; Alexoff, Dave; Logan, Jean; Wong, Christopher

2011-01-01

Context The dramatic increase in use of cellular telephones has generated concern about possible negative effects of radiofrequency signals delivered to the brain. However, whether acute cell phone exposure affects the human brain is unclear. Objective To evaluate if acute cell phone exposure affects brain glucose metabolism, a marker of brain activity. Design, Setting, and Participants Randomized crossover study conducted between January 1 and December 31, 2009, at a single US laboratory among 47 healthy participants recruited from the community. Cell phones were placed on the left and right ears and positron emission tomography with (18F)fluorodeoxyglucose injection was used to measure brain glucose metabolism twice, once with the right cell phone activated (sound muted) for 50 minutes (“on” condition) and once with both cell phones deactivated (“off” condition). Statistical parametric mapping was used to compare metabolism between on and off conditions using paired t tests, and Pearson linear correlations were used to verify the association of metabolism and estimated amplitude of radiofrequency-modulated electromagnetic waves emitted by the cell phone. Clusters with at least 1000 voxels (volume >8 cm3) and P < .05 (corrected for multiple comparisons) were considered significant. Main Outcome Measure Brain glucose metabolism computed as absolute metabolism (µmol/100 g per minute) and as normalized metabolism (region/whole brain). Results Whole-brain metabolism did not differ between on and off conditions. In contrast, metabolism in the region closest to the antenna (orbitofrontal cortex and temporal pole) was significantly higher for on than off conditions (35.7 vs 33.3 µmol/100 g per minute; mean difference, 2.4 [95% confidence interval, 0.67–4.2]; P = .004). The increases were significantly correlated with the estimated electromagnetic field amplitudes both for absolute metabolism (R = 0.95, P < .001) and normalized metabolism (R = 0.89; P < .001). Conclusions In healthy participants and compared with no exposure, 50-minute cell phone exposure was associated with increased brain glucose metabolism in the region closest to the antenna. This finding is of unknown clinical significance. PMID:21343580

Metabolic costs and evolutionary implications of human brain development.

PubMed

Kuzawa, Christopher W; Chugani, Harry T; Grossman, Lawrence I; Lipovich, Leonard; Muzik, Otto; Hof, Patrick R; Wildman, Derek E; Sherwood, Chet C; Leonard, William R; Lange, Nicholas

2014-09-09

The high energetic costs of human brain development have been hypothesized to explain distinctive human traits, including exceptionally slow and protracted preadult growth. Although widely assumed to constrain life-history evolution, the metabolic requirements of the growing human brain are unknown. We combined previously collected PET and MRI data to calculate the human brain's glucose use from birth to adulthood, which we compare with body growth rate. We evaluate the strength of brain-body metabolic trade-offs using the ratios of brain glucose uptake to the body's resting metabolic rate (RMR) and daily energy requirements (DER) expressed in glucose-gram equivalents (glucosermr% and glucoseder%). We find that glucosermr% and glucoseder% do not peak at birth (52.5% and 59.8% of RMR, or 35.4% and 38.7% of DER, for males and females, respectively), when relative brain size is largest, but rather in childhood (66.3% and 65.0% of RMR and 43.3% and 43.8% of DER). Body-weight growth (dw/dt) and both glucosermr% and glucoseder% are strongly, inversely related: soon after birth, increases in brain glucose demand are accompanied by proportionate decreases in dw/dt. Ages of peak brain glucose demand and lowest dw/dt co-occur and subsequent developmental declines in brain metabolism are matched by proportionate increases in dw/dt until puberty. The finding that human brain glucose demands peak during childhood, and evidence that brain metabolism and body growth rate covary inversely across development, support the hypothesis that the high costs of human brain development require compensatory slowing of body growth rate.

Lipidomics of human brain aging and Alzheimer's disease pathology.

PubMed

Naudí, Alba; Cabré, Rosanna; Jové, Mariona; Ayala, Victoria; Gonzalo, Hugo; Portero-Otín, Manuel; Ferrer, Isidre; Pamplona, Reinald

2015-01-01

Lipids stimulated and favored the evolution of the brain. Adult human brain contains a large amount of lipids, and the largest diversity of lipid classes and lipid molecular species. Lipidomics is defined as "the full characterization of lipid molecular species and of their biological roles with respect to expression of proteins involved in lipid metabolism and function, including gene regulation." Therefore, the study of brain lipidomics can help to unravel the diversity and to disclose the specificity of these lipid traits and its alterations in neural (neurons and glial) cells, groups of neural cells, brain, and fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of human brain aging and Alzheimer disease. This review will discuss the lipid composition of the adult human brain. We first consider a brief approach to lipid definition, classification, and tools for analysis from the new point of view that has emerged with lipidomics, and then turn to the lipid profiles in human brain and how lipids affect brain function. Finally, we focus on the current status of lipidomics findings in human brain aging and Alzheimer's disease pathology. Neurolipidomics will increase knowledge about physiological and pathological functions of brain cells and will place the concept of selective neuronal vulnerability in a lipid context. © 2015 Elsevier Inc. All rights reserved.

Estimating the brain pathological age of Alzheimer’s disease patients from MR image data based on the separability distance criterion

NASA Astrophysics Data System (ADS)

Li, Yongming; Li, Fan; Wang, Pin; Zhu, Xueru; Liu, Shujun; Qiu, Mingguo; Zhang, Jingna; Zeng, Xiaoping

2016-10-01

Traditional age estimation methods are based on the same idea that uses the real age as the training label. However, these methods ignore that there is a deviation between the real age and the brain age due to accelerated brain aging. This paper considers this deviation and searches for it by maximizing the separability distance value rather than by minimizing the difference between the estimated brain age and the real age. Firstly, set the search range of the deviation as the deviation candidates according to prior knowledge. Secondly, use the support vector regression (SVR) as the age estimation model to minimize the difference between the estimated age and the real age plus deviation rather than the real age itself. Thirdly, design the fitness function based on the separability distance criterion. Fourthly, conduct age estimation on the validation dataset using the trained age estimation model, put the estimated age into the fitness function, and obtain the fitness value of the deviation candidate. Fifthly, repeat the iteration until all the deviation candidates are involved and get the optimal deviation with maximum fitness values. The real age plus the optimal deviation is taken as the brain pathological age. The experimental results showed that the separability was apparently improved. For normal control-Alzheimer’s disease (NC-AD), normal control-mild cognition impairment (NC-MCI), and MCI-AD, the average improvements were 0.178 (35.11%), 0.033 (14.47%), and 0.017 (39.53%), respectively. For NC-MCI-AD, the average improvement was 0.2287 (64.22%). The estimated brain pathological age could be not only more helpful to the classification of AD but also more precisely reflect accelerated brain aging. In conclusion, this paper offers a new method for brain age estimation that can distinguish different states of AD and can better reflect the extent of accelerated aging.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal flexibility among the three networks. Our proposed methods provide a novel and powerful generative model for investigating dynamic brain connectivity. Copyright © 2017 Elsevier Inc. All rights reserved.

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

PubMed Central

Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Activity flow over resting-state networks shapes cognitive task activations.

PubMed

Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

2016-12-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Activity flow over resting-state networks shapes cognitive task activations

PubMed Central

Cole, Michael W.; Ito, Takuya; Bassett, Danielle S.; Schultz, Douglas H.

2016-01-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations. PMID:27723746

Profiling neuronal ion channelopathies with non-invasive brain imaging and dynamic causal models: Case studies of single gene mutations

PubMed Central

Gilbert, Jessica R.; Symmonds, Mkael; Hanna, Michael G.; Dolan, Raymond J.; Friston, Karl J.; Moran, Rosalyn J.

2016-01-01

Clinical assessments of brain function rely upon visual inspection of electroencephalographic waveform abnormalities in tandem with functional magnetic resonance imaging. However, no current technology proffers in vivo assessments of activity at synapses, receptors and ion-channels, the basis of neuronal communication. Using dynamic causal modeling we compared electrophysiological responses from two patients with distinct monogenic ion channelopathies and a large cohort of healthy controls to demonstrate the feasibility of assaying synaptic-level channel communication non-invasively. Synaptic channel abnormality was identified in both patients (100% sensitivity) with assay specificity above 89%, furnishing estimates of neurotransmitter and voltage-gated ion throughput of sodium, calcium, chloride and potassium. This performance indicates a potential novel application as an adjunct for clinical assessments in neurological and psychiatric settings. More broadly, these findings indicate that biophysical models of synaptic channels can be estimated non-invasively, having important implications for advancing human neuroimaging to the level of non-invasive ion channel assays. PMID:26342528

Energetic and nutritional constraints on infant brain development: implications for brain expansion during human evolution.

PubMed

Cunnane, Stephen C; Crawford, Michael A

2014-12-01

The human brain confronts two major challenges during its development: (i) meeting a very high energy requirement, and (ii) reliably accessing an adequate dietary source of specific brain selective nutrients needed for its structure and function. Implicitly, these energetic and nutritional constraints to normal brain development today would also have been constraints on human brain evolution. The energetic constraint was solved in large measure by the evolution in hominins of a unique and significant layer of body fat on the fetus starting during the third trimester of gestation. By providing fatty acids for ketone production that are needed as brain fuel, this fat layer supports the brain's high energy needs well into childhood. This fat layer also contains an important reserve of the brain selective omega-3 fatty acid, docosahexaenoic acid (DHA), not available in other primates. Foremost amongst the brain selective minerals are iodine and iron, with zinc, copper and selenium also being important. A shore-based diet, i.e., fish, molluscs, crustaceans, frogs, bird's eggs and aquatic plants, provides the richest known dietary sources of brain selective nutrients. Regular access to these foods by the early hominin lineage that evolved into humans would therefore have helped free the nutritional constraint on primate brain development and function. Inadequate dietary supply of brain selective nutrients still has a deleterious impact on human brain development on a global scale today, demonstrating the brain's ongoing vulnerability. The core of the shore-based paradigm of human brain evolution proposes that sustained access by certain groups of early Homo to freshwater and marine food resources would have helped surmount both the nutritional as well as the energetic constraints on mammalian brain development. Copyright © 2014 Elsevier Ltd. All rights reserved.

Organoid technology for brain and therapeutics research.

PubMed

Wang, Zhi; Wang, Shu-Na; Xu, Tian-Ying; Miao, Zhu-Wei; Su, Ding-Feng; Miao, Chao-Yu

2017-10-01

Brain is one of the most complex organs in human. The current brain research is mainly based on the animal models and traditional cell culture. However, the inherent species differences between humans and animals as well as the gap between organ level and cell level make it difficult to study human brain development and associated disorders through traditional technologies. Recently, the brain organoids derived from pluripotent stem cells have been reported to recapitulate many key features of human brain in vivo, for example recapitulating the zone of putative outer radial glia cells. Brain organoids offer a new platform for scientists to study brain development, neurological diseases, drug discovery and personalized medicine, regenerative medicine, and so on. Here, we discuss the progress, applications, advantages, limitations, and prospects of brain organoid technology in neurosciences and related therapeutics. © 2017 John Wiley & Sons Ltd.

Non-invasive Brain Stimulation: Probing Intracortical Circuits and Improving Cognition in the Aging Brain

PubMed Central

Gomes-Osman, Joyce; Indahlastari, Aprinda; Fried, Peter J.; Cabral, Danylo L. F.; Rice, Jordyn; Nissim, Nicole R.; Aksu, Serkan; McLaren, Molly E.; Woods, Adam J.

2018-01-01

The impact of cognitive aging on brain function and structure is complex, and the relationship between aging-related structural changes and cognitive function are not fully understood. Physiological and pathological changes to the aging brain are highly variable, making it difficult to estimate a cognitive trajectory with which to monitor the conversion to cognitive decline. Beyond the information on the structural and functional consequences of cognitive aging gained from brain imaging and neuropsychological studies, non-invasive brain stimulation techniques such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) can enable stimulation of the human brain in vivo, offering useful insights into the functional integrity of intracortical circuits using electrophysiology and neuromodulation. TMS measurements can be used to identify and monitor changes in cortical reactivity, the integrity of inhibitory and excitatory intracortical circuits, the mechanisms of long-term potentiation (LTP)/depression-like plasticity and central cholinergic function. Repetitive TMS and tDCS can be used to modulate neuronal excitability and enhance cortical function, and thus offer a potential means to slow or reverse cognitive decline. This review will summarize and critically appraise relevant literature regarding the use of TMS and tDCS to probe cortical areas affected by the aging brain, and as potential therapeutic tools to improve cognitive function in the aging population. Challenges arising from intra-individual differences, limited reproducibility, and methodological differences will be discussed.

Estimated maximal and current brain volume predict cognitive ability in old age.

PubMed

Royle, Natalie A; Booth, Tom; Valdés Hernández, Maria C; Penke, Lars; Murray, Catherine; Gow, Alan J; Maniega, Susana Muñoz; Starr, John; Bastin, Mark E; Deary, Ian J; Wardlaw, Joanna M

2013-12-01

Brain tissue deterioration is a significant contributor to lower cognitive ability in later life; however, few studies have appropriate data to establish how much influence prior brain volume and prior cognitive performance have on this association. We investigated the associations between structural brain imaging biomarkers, including an estimate of maximal brain volume, and detailed measures of cognitive ability at age 73 years in a large (N = 620), generally healthy, community-dwelling population. Cognitive ability data were available from age 11 years. We found positive associations (r) between general cognitive ability and estimated brain volume in youth (male, 0.28; females, 0.12), and in measured brain volume in later life (males, 0.27; females, 0.26). Our findings show that cognitive ability in youth is a strong predictor of estimated prior and measured current brain volume in old age but that these effects were the same for both white and gray matter. As 1 of the largest studies of associations between brain volume and cognitive ability with normal aging, this work contributes to the wider understanding of how some early-life factors influence cognitive aging. Copyright © 2013 Elsevier Inc. All rights reserved.

Systemic treatment of focal brain injury in the rat by human umbilical cord blood cells being at different level of neural commitment.

PubMed

Gornicka-Pawlak, El Bieta; Janowski, Miroslaw; Habich, Aleksandra; Jablonska, Anna; Drela, Katarzyna; Kozlowska, Hanna; Lukomska, Barbara; Sypecka, Joanna; Domanska-Janik, Krystyna

2011-01-01

The aim of the study was to evaluate therapeutic effectiveness of intra-arterial infusion of human umbilical cord blood (HUCB) derived cells at different stages of their neural conversion. Freshly isolated mononuclear cells (D-0), neurally directed progenitors (D-3) and neural-like stem cells derived from umbilical cord blood (NSC) were compared. Focal brain damage was induced in rats by stereotactic injection of ouabain into dorsolateral striatum Three days later 10(7) of different subsets of HUCB cells were infused into the right internal carotid artery. Following surgery rats were housed in enriched environment for 30 days. Behavioral assessment consisted of tests for sensorimotor deficits (walking beam, rotarod, vibrissae elicited forelimb placing, apomorphine induced rotations), cognitive impairments (habit learning and object recognition) and exploratory behavior (open field). Thirty days after surgery the lesion volume was measured and the presence of donor cells was detected in the brain at mRNA level. At the same time immunohistochemical analysis of brain tissue was performed to estimate the local tissue response of ouabain injured rats and its modulation after HUCB cells systemic treatment. Functional effects of different subsets of cord blood cells shared substantial diversity in various behavioral tests. An additional analysis showed that D-0 HUCB cells were the most effective in functional restoration and reduction of brain lesion volume. None of transplanted cord blood derived cell fractions were detected in rat's brains at 30(th) day after treatment. This may suggest that the mechanism(s) underlying positive effects of HUCB derived cell may concern the other than direct neural cell supplementation. In addition increased immunoreactivity of markers indicating local cells proliferation and migration suggests stimulation of endogenous reparative processes by HUCB D-0 cell interarterial infusion.

Steady-state evoked potentials possibilities for mental-state estimation

NASA Technical Reports Server (NTRS)

Junker, Andrew M.; Schnurer, John H.; Ingle, David F.; Downey, Craig W.

1988-01-01

The use of the human steady-state evoked potential (SSEP) as a possible measure of mental-state estimation is explored. A method for evoking a visual response to a sum-of-ten sine waves is presented. This approach provides simultaneous multiple frequency measurements of the human EEG to the evoking stimulus in terms of describing functions (gain and phase) and remnant spectra. Ways in which these quantities vary with the addition of performance tasks (manual tracking, grammatical reasoning, and decision making) are presented. Models of the describing function measures can be formulated using systems engineering technology. Relationships between model parameters and performance scores during manual tracking are discussed. Problems of unresponsiveness and lack of repeatability of subject responses are addressed in terms of a need for loop closure of the SSEP. A technique to achieve loop closure using a lock-in amplifier approach is presented. Results of a study designed to test the effectiveness of using feedback to consciously connect humans to their evoked response are presented. Findings indicate that conscious control of EEG is possible. Implications of these results in terms of secondary tasks for mental-state estimation and brain actuated control are addressed.

Shared Mechanisms in the Estimation of Self-Generated Actions and the Prediction of Other’s Actions by Humans

PubMed Central

Ganesh, Gowrishankar

2017-01-01

Abstract The question of how humans predict outcomes of observed motor actions by others is a fundamental problem in cognitive and social neuroscience. Previous theoretical studies have suggested that the brain uses parts of the forward model (used to estimate sensory outcomes of self-generated actions) to predict outcomes of observed actions. However, this hypothesis has remained controversial due to the lack of direct experimental evidence. To address this issue, we analyzed the behavior of darts experts in an understanding learning paradigm and utilized computational modeling to examine how outcome prediction of observed actions affected the participants’ ability to estimate their own actions. We recruited darts experts because sports experts are known to have an accurate outcome estimation of their own actions as well as prediction of actions observed in others. We first show that learning to predict the outcomes of observed dart throws deteriorates an expert’s abilities to both produce his own darts actions and estimate the outcome of his own throws (or self-estimation). Next, we introduce a state-space model to explain the trial-by-trial changes in the darts performance and self-estimation through our experiment. The model-based analysis reveals that the change in an expert’s self-estimation is explained only by considering a change in the individual’s forward model, showing that an improvement in an expert’s ability to predict outcomes of observed actions affects the individual’s forward model. These results suggest that parts of the same forward model are utilized in humans to both estimate outcomes of self-generated actions and predict outcomes of observed actions. PMID:29340300

Human sexual behavior related to pathology and activity of the brain.

PubMed

Komisaruk, Barry R; Rodriguez Del Cerro, Maria Cruz

2015-01-01

Reviewed in this chapter are: (1) correlations among human sexual behavior, brain pathology, and brain activity, including caveats regarding the interpretation of "cause and effect" among these factors, and the degree to which "hypersexuality" and reported changes in sexual orientation correlated with brain pathology are uniquely sexual or are attributable to a generalized disinhibition of brain function; (2) the effects, in some cases inhibitory, in others facilitatory, on sexual behavior and motivation, of stroke, epileptic seizures, traumatic brain injury, and brain surgery; and (3) insights into sexual motivation and behavior recently gained from functional brain imaging research and its interpretive limitations. We conclude from the reviewed research that the neural orchestra underlying the symphony of human sexuality comprises, rather than brain "centers," multiple integrated brain systems, and that there are more questions than answers in our understanding of the control of human sexual behavior by the brain - a level of understanding that is still in embryonic form. © 2015 Elsevier B.V. All rights reserved.

The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture.

PubMed

Fan, Lingzhong; Li, Hai; Zhuo, Junjie; Zhang, Yu; Wang, Jiaojian; Chen, Liangfu; Yang, Zhengyi; Chu, Congying; Xie, Sangma; Laird, Angela R; Fox, Peter T; Eickhoff, Simon B; Yu, Chunshui; Jiang, Tianzi

2016-08-01

The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states. © The Author 2016. Published by Oxford University Press.

Brain Evolution and Human Neuropsychology: The Inferential Brain Hypothesis

PubMed Central

Koscik, Timothy R.; Tranel, Daniel

2013-01-01

Collaboration between human neuropsychology and comparative neuroscience has generated invaluable contributions to our understanding of human brain evolution and function. Further cross-talk between these disciplines has the potential to continue to revolutionize these fields. Modern neuroimaging methods could be applied in a comparative context, yielding exciting new data with the potential of providing insight into brain evolution. Conversely, incorporating an evolutionary base into the theoretical perspectives from which we approach human neuropsychology could lead to novel hypotheses and testable predictions. In the spirit of these objectives, we present here a new theoretical proposal, the Inferential Brain Hypothesis, whereby the human brain is thought to be characterized by a shift from perceptual processing to inferential computation, particularly within the social realm. This shift is believed to be a driving force for the evolution of the large human cortex. PMID:22459075

A combination of experimental measurement, constitutive damage model, and diffusion tensor imaging to characterize the mechanical properties of the human brain.

PubMed

Karimi, Alireza; Rahmati, Seyed Mohammadali; Razaghi, Reza

2017-09-01

Understanding the mechanical properties of the human brain is deemed important as it may subject to various types of complex loadings during the Traumatic Brain Injury (TBI). Although many studies so far have been conducted to quantify the mechanical properties of the brain, there is a paucity of knowledge on the mechanical properties of the human brain tissue and the damage of its axon fibers under the various types of complex loadings during the Traumatic Brain Injury (TBI). Although many studies so far have been conducted to quantify the mechanical properties of the brain, there is a paucity of knowledge on the mechanical properties of the human brain tissue and the damage of its axon fibers under the frontal lobe of the human brain. The constrained nonlinear minimization method was employed to identify the brain coefficients according to the axial and transversal compressive data. The pseudo-elastic damage model data was also well compared with that of the experimental data and it not only up to the primary loading but also the discontinuous softening could well address the mechanical behavior of the brain tissue.

Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms.

PubMed

Stewart, Daniel C; Rubiano, Andrés; Dyson, Kyle; Simmons, Chelsey S

2017-01-01

While mechanical properties of the brain have been investigated thoroughly, the mechanical properties of human brain tumors rarely have been directly quantified due to the complexities of acquiring human tissue. Quantifying the mechanical properties of brain tumors is a necessary prerequisite, though, to identify appropriate materials for surgical tool testing and to define target parameters for cell biology and tissue engineering applications. Since characterization methods vary widely for soft biological and synthetic materials, here, we have developed a characterization method compatible with abnormally shaped human brain tumors, mouse tumors, animal tissue and common hydrogels, which enables direct comparison among samples. Samples were tested using a custom-built millimeter-scale indenter, and resulting force-displacement data is analyzed to quantify the steady-state modulus of each sample. We have directly quantified the quasi-static mechanical properties of human brain tumors with effective moduli ranging from 0.17-16.06 kPa for various pathologies. Of the readily available and inexpensive animal tissues tested, chicken liver (steady-state modulus 0.44 ± 0.13 kPa) has similar mechanical properties to normal human brain tissue while chicken crassus gizzard muscle (steady-state modulus 3.00 ± 0.65 kPa) has similar mechanical properties to human brain tumors. Other materials frequently used to mimic brain tissue in mechanical tests, like ballistic gel and chicken breast, were found to be significantly stiffer than both normal and diseased brain tissue. We have directly compared quasi-static properties of brain tissue, brain tumors, and common mechanical surrogates, though additional tests would be required to determine more complex constitutive models.

Body mass estimates of hominin fossils and the evolution of human body size.

PubMed

Grabowski, Mark; Hatala, Kevin G; Jungers, William L; Richmond, Brian G

2015-08-01

Body size directly influences an animal's place in the natural world, including its energy requirements, home range size, relative brain size, locomotion, diet, life history, and behavior. Thus, an understanding of the biology of extinct organisms, including species in our own lineage, requires accurate estimates of body size. Since the last major review of hominin body size based on postcranial morphology over 20 years ago, new fossils have been discovered, species attributions have been clarified, and methods improved. Here, we present the most comprehensive and thoroughly vetted set of individual fossil hominin body mass predictions to date, and estimation equations based on a large (n = 220) sample of modern humans of known body masses. We also present species averages based exclusively on fossils with reliable taxonomic attributions, estimates of species averages by sex, and a metric for levels of sexual dimorphism. Finally, we identify individual traits that appear to be the most reliable for mass estimation for each fossil species, for use when only one measurement is available for a fossil. Our results show that many early hominins were generally smaller-bodied than previously thought, an outcome likely due to larger estimates in previous studies resulting from the use of large-bodied modern human reference samples. Current evidence indicates that modern human-like large size first appeared by at least 3-3.5 Ma in some Australopithecus afarensis individuals. Our results challenge an evolutionary model arguing that body size increased from Australopithecus to early Homo. Instead, we show that there is no reliable evidence that the body size of non-erectus early Homo differed from that of australopiths, and confirm that Homo erectus evolved larger average body size than earlier hominins. Copyright © 2015 Elsevier Ltd. All rights reserved.

Diversity of human copy number variation and multicopy genes.

PubMed

Sudmant, Peter H; Kitzman, Jacob O; Antonacci, Francesca; Alkan, Can; Malig, Maika; Tsalenko, Anya; Sampas, Nick; Bruhn, Laurakay; Shendure, Jay; Eichler, Evan E

2010-10-29

Copy number variants affect both disease and normal phenotypic variation, but those lying within heavily duplicated, highly identical sequence have been difficult to assay. By analyzing short-read mapping depth for 159 human genomes, we demonstrated accurate estimation of absolute copy number for duplications as small as 1.9 kilobase pairs, ranging from 0 to 48 copies. We identified 4.1 million "singly unique nucleotide" positions informative in distinguishing specific copies and used them to genotype the copy and content of specific paralogs within highly duplicated gene families. These data identify human-specific expansions in genes associated with brain development, reveal extensive population genetic diversity, and detect signatures consistent with gene conversion in the human species. Our approach makes ~1000 genes accessible to genetic studies of disease association.

A Unified Estimation Framework for State-Related Changes in Effective Brain Connectivity.

PubMed

Samdin, S Balqis; Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain

2017-04-01

This paper addresses the critical problem of estimating time-evolving effective brain connectivity. Current approaches based on sliding window analysis or time-varying coefficient models do not simultaneously capture both slow and abrupt changes in causal interactions between different brain regions. To overcome these limitations, we develop a unified framework based on a switching vector autoregressive (SVAR) model. Here, the dynamic connectivity regimes are uniquely characterized by distinct vector autoregressive (VAR) processes and allowed to switch between quasi-stationary brain states. The state evolution and the associated directed dependencies are defined by a Markov process and the SVAR parameters. We develop a three-stage estimation algorithm for the SVAR model: 1) feature extraction using time-varying VAR (TV-VAR) coefficients, 2) preliminary regime identification via clustering of the TV-VAR coefficients, 3) refined regime segmentation by Kalman smoothing and parameter estimation via expectation-maximization algorithm under a state-space formulation, using initial estimates from the previous two stages. The proposed framework is adaptive to state-related changes and gives reliable estimates of effective connectivity. Simulation results show that our method provides accurate regime change-point detection and connectivity estimates. In real applications to brain signals, the approach was able to capture directed connectivity state changes in functional magnetic resonance imaging data linked with changes in stimulus conditions, and in epileptic electroencephalograms, differentiating ictal from nonictal periods. The proposed framework accurately identifies state-dependent changes in brain network and provides estimates of connectivity strength and directionality. The proposed approach is useful in neuroscience studies that investigate the dynamics of underlying brain states.

Predilection sites for Toxoplasma gondii in sheep tissues revealed by magnetic capture and real-time PCR detection.

PubMed

Juránková, Jana; Basso, Walter; Neumayerová, Helena; Frencová, Anita; Baláž, Vojtech; Deplazes, Peter; Koudela, Břetislav

2015-12-01

Undercooked lamb and mutton are common sources of Toxoplasma gondii infection for humans. A sequence specific magnetic capture technique in combination with quantitative real-time PCR targeting the 529 bp repeat element of T. gondii was used for estimation of the parasite burdens in various sheep tissues (n = 6) three months after peroral experimental inoculation with 10,000 T. gondii oocysts. Brain was the most frequently affected organ (positive in all 6 sheep) and showed the highest estimated parasite loads (0.5-30,913 parasites/g tissue). Lung samples were positive in three sheep, with load estimates of 36.3 to <1 parasite/g tissue. Heart tissue was positive in three sheep and kidney only in one animal with low parasite loads (<1 parasite/g tissue). Only few skeletal muscle samples in 2 animals showed positive results, with very low parasite burdens, while samples from further internal organs (i.e. liver and spleen) were negative in all animals. This study identified the brain as the most important predilection site and therefore the most appropriate tissue for T. gondii detection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Toxoplasma Modulates Signature Pathways of Human Epilepsy, Neurodegeneration & Cancer.

PubMed

Ngô, Huân M; Zhou, Ying; Lorenzi, Hernan; Wang, Kai; Kim, Taek-Kyun; Zhou, Yong; El Bissati, Kamal; Mui, Ernest; Fraczek, Laura; Rajagopala, Seesandra V; Roberts, Craig W; Henriquez, Fiona L; Montpetit, Alexandre; Blackwell, Jenefer M; Jamieson, Sarra E; Wheeler, Kelsey; Begeman, Ian J; Naranjo-Galvis, Carlos; Alliey-Rodriguez, Ney; Davis, Roderick G; Soroceanu, Liliana; Cobbs, Charles; Steindler, Dennis A; Boyer, Kenneth; Noble, A Gwendolyn; Swisher, Charles N; Heydemann, Peter T; Rabiah, Peter; Withers, Shawn; Soteropoulos, Patricia; Hood, Leroy; McLeod, Rima

2017-09-13

One third of humans are infected lifelong with the brain-dwelling, protozoan parasite, Toxoplasma gondii. Approximately fifteen million of these have congenital toxoplasmosis. Although neurobehavioral disease is associated with seropositivity, causality is unproven. To better understand what this parasite does to human brains, we performed a comprehensive systems analysis of the infected brain: We identified susceptibility genes for congenital toxoplasmosis in our cohort of infected humans and found these genes are expressed in human brain. Transcriptomic and quantitative proteomic analyses of infected human, primary, neuronal stem and monocytic cells revealed effects on neurodevelopment and plasticity in neural, immune, and endocrine networks. These findings were supported by identification of protein and miRNA biomarkers in sera of ill children reflecting brain damage and T. gondii infection. These data were deconvoluted using three systems biology approaches: "Orbital-deconvolution" elucidated upstream, regulatory pathways interconnecting human susceptibility genes, biomarkers, proteomes, and transcriptomes. "Cluster-deconvolution" revealed visual protein-protein interaction clusters involved in processes affecting brain functions and circuitry, including lipid metabolism, leukocyte migration and olfaction. Finally, "disease-deconvolution" identified associations between the parasite-brain interactions and epilepsy, movement disorders, Alzheimer's disease, and cancer. This "reconstruction-deconvolution" logic provides templates of progenitor cells' potentiating effects, and components affecting human brain parasitism and diseases.

Educating the Human Brain. Human Brain Development Series

ERIC Educational Resources Information Center

Posner, Michael I.; Rothbart, Mary K.

2006-01-01

"Educating the Human Brain" is the product of a quarter century of research. This book provides an empirical account of the early development of attention and self regulation in infants and young children. It examines the brain areas involved in regulatory networks, their connectivity, and how their development is influenced by genes and…

Is the social brain theory applicable to human individual differences? Relationship between sociability personality dimension and brain size.

PubMed

Horváth, Klára; Martos, János; Mihalik, Béla; Bódizs, Róbert

2011-06-17

Our study intends to examine whether the social brain theory is applicable to human individual differences. According to the social brain theory primates have larger brains as it could be expected from their body sizes due to the adaptation to a more complex social life. Regarding humans there were few studies about the relationship between theory of mind and frontal and temporal brain lobes. We hypothesized that these brain lobes, as well as the whole cerebrum and neocortex are in connection with the Sociability personality dimension that is associated with individuals' social lives. Our findings support this hypothesis as Sociability correlated positively with the examined brain structures if we control the effects of body size differences and age. These results suggest that the social brain theory can be extended to human interindividual differences and they have some implications to personality psychology too.

Insulin-regulated aminopeptidase immunoreactivity is abundantly present in human hypothalamus and posterior pituitary gland, with reduced expression in paraventricular and suprachiasmatic neurons in chronic schizophrenia.

PubMed

Bernstein, Hans-Gert; Müller, Susan; Dobrowolny, Hendrik; Wolke, Carmen; Lendeckel, Uwe; Bukowska, Alicja; Keilhoff, Gerburg; Becker, Axel; Trübner, Kurt; Steiner, Johann; Bogerts, Bernhard

2017-08-01

The vasopressin- and oxytocin-degrading enzyme insulin-regulated aminopeptidase (IRAP) is expressed in various organs including the brain. However, knowledge about its presence in human hypothalamus is fragmentary. Functionally, for a number of reasons (genetic linkage, hydrolysis of oxytocin and vasopressin, its role as angiotensin IV receptor in learning and memory and others) IRAP might play a role in schizophrenia. We studied the regional and cellular localization of IRAP in normal human brain with special emphasis on the hypothalamus and determined numerical densities of IRAP-expressing cells in the paraventricular, supraoptic and suprachiasmatic nuclei in schizophrenia patients and controls. By using immunohistochemistry and Western blot analysis, IRAP was immunolocalized in postmortem human brains. Cell countings were performed to estimate numbers and numerical densities of IRAP immunoreactive hypothalamic neurons in schizophrenia patients and control cases. Shape, size and regional distribution of IRAP-expressing cells, as well the lack of co-localization with the glia marker glutamine synthetase, show that IRAP is expressed in neurons. IRAP immunoreactive cells were observed in the hippocampal formation, cerebral cortex, thalamus, amygdala and, abundantly, hypothalamus. Double labeling experiments (IRAP and oxytocin/neurophysin 1, IRAP with vasopressin/neurophysin 2) revealed that IRAP is present in oxytocinergic and in vasopressinergic neurons. In schizophrenia patients, the numerical density of IRAP-expressing neurons in the paraventricular and the suprachiasmatic nuclei is significantly reduced, which might be associated with the reduction in neurophysin-containing neurons in these nuclei in schizophrenia. The pathophysiological role of lowered hypothalamic IRAP expression in schizophrenia remains to be established.

Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain to Cockroach Brain

PubMed Central

2016-01-01

An all-chain-wireless brain-to-brain system (BTBS), which enabled motion control of a cyborg cockroach via human brain, was developed in this work. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) was used in this system for recognizing human motion intention and an optimization algorithm was proposed in SSVEP to improve online performance of the BCI. The cyborg cockroach was developed by surgically integrating a portable microstimulator that could generate invasive electrical nerve stimulation. Through Bluetooth communication, specific electrical pulse trains could be triggered from the microstimulator by BCI commands and were sent through the antenna nerve to stimulate the brain of cockroach. Serial experiments were designed and conducted to test overall performance of the BTBS with six human subjects and three cockroaches. The experimental results showed that the online classification accuracy of three-mode BCI increased from 72.86% to 78.56% by 5.70% using the optimization algorithm and the mean response accuracy of the cyborgs using this system reached 89.5%. Moreover, the results also showed that the cyborg could be navigated by the human brain to complete walking along an S-shape track with the success rate of about 20%, suggesting the proposed BTBS established a feasible functional information transfer pathway from the human brain to the cockroach brain. PMID:26982717

Brain-Computer Interface Controlled Cyborg: Establishing a Functional Information Transfer Pathway from Human Brain to Cockroach Brain.

PubMed

Li, Guangye; Zhang, Dingguo

2016-01-01

An all-chain-wireless brain-to-brain system (BTBS), which enabled motion control of a cyborg cockroach via human brain, was developed in this work. Steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) was used in this system for recognizing human motion intention and an optimization algorithm was proposed in SSVEP to improve online performance of the BCI. The cyborg cockroach was developed by surgically integrating a portable microstimulator that could generate invasive electrical nerve stimulation. Through Bluetooth communication, specific electrical pulse trains could be triggered from the microstimulator by BCI commands and were sent through the antenna nerve to stimulate the brain of cockroach. Serial experiments were designed and conducted to test overall performance of the BTBS with six human subjects and three cockroaches. The experimental results showed that the online classification accuracy of three-mode BCI increased from 72.86% to 78.56% by 5.70% using the optimization algorithm and the mean response accuracy of the cyborgs using this system reached 89.5%. Moreover, the results also showed that the cyborg could be navigated by the human brain to complete walking along an S-shape track with the success rate of about 20%, suggesting the proposed BTBS established a feasible functional information transfer pathway from the human brain to the cockroach brain.

Patterns of differences in brain morphology in humans as compared to extant apes.

PubMed

Aldridge, Kristina

2011-01-01

Although human evolution is characterized by a vast increase in brain size, it is not clear whether or not certain regions of the brain are enlarged disproportionately in humans, or how this enlargement relates to differences in overall neural morphology. The aim of this study is to determine whether or not there are specific suites of features that distinguish the morphology of the human brain from that of apes. The study sample consists of whole brain, in vivo magnetic resonance images (MRIs) of anatomically modern humans (Homo sapiens sapiens) and five ape species (gibbons, orangutans, gorillas, chimpanzees, bonobos). Twenty-nine 3D landmarks, including surface and internal features of the brain were located on 3D MRI reconstructions of each individual using MEASURE software. Landmark coordinate data were scaled for differences in size and analyzed using Euclidean Distance Matrix Analysis (EDMA) to statistically compare the brains of each non-human ape species to the human sample. Results of analyses show both a pattern of brain morphology that is consistently different between all apes and humans, as well as patterns that differ among species. Further, both the consistent and species-specific patterns include cortical and subcortical features. The pattern that remains consistent across species indicates a morphological reorganization of 1) relationships between cortical and subcortical frontal structures, 2) expansion of the temporal lobe and location of the amygdala, and 3) expansion of the anterior parietal region. Additionally, results demonstrate that, although there is a pattern of morphology that uniquely defines the human brain, there are also patterns that uniquely differentiate human morphology from the morphology of each non-human ape species, indicating that reorganization of neural morphology occurred at the evolutionary divergence of each of these groups. Copyright © 2010 Elsevier Ltd. All rights reserved.

Patterns of differences in brain morphology in humans as compared to extant apes

PubMed Central

Aldridge, Kristina

2010-01-01

Although human evolution is characterized by a vast increase in brain size, it is not clear whether or not certain regions of the brain are enlarged disproportionately in humans, or how this enlargement relates to differences in overall neural morphology. The aim of this study is to determine whether or not there are specific suites of features that distinguish the morphology of the human brain from that of apes. The study sample consists of whole brain, in vivo magnetic resonance images (MRIs) of anatomically modern humans (Homo sapiens sapiens) and five ape species (gibbons, orangutans, gorillas, chimpanzees, bonobos). Twenty-nine 3D landmarks, including surface and internal features of the brain were located on 3D MRI reconstructions of each individual using MEASURE software. Landmark coordinate data were scaled for differences in size and analyzed using Euclidean Distance Matrix Analysis (EDMA) to statistically compare the brains of each non-human ape species to the human sample. Results of analyses show both a pattern of brain morphology that is consistently different between all apes and humans, as well as patterns that differ among species. Further, both the consistent and species-specific patterns include cortical and subcortical features. The pattern that remains consistent across species indicates a morphological reorganization of 1) relationships between cortical and subcortical frontal structures, 2) expansion of the temporal lobe and location of the amygdala, and 3) expansion of the anterior parietal region. Additionally, results demonstrate that, although there is a pattern of morphology that uniquely defines the human brain, there are also patterns that uniquely differentiate human morphology from the morphology of each non-human ape species, indicating that reorganization of neural morphology occurred at the evolutionary divergence of each of these groups. PMID:21056456

Relationship Between Large-Scale Functional and Structural Covariance Networks in Idiopathic Generalized Epilepsy

PubMed Central

Zhang, Zhiqiang; Mantini, Dante; Xu, Qiang; Wang, Zhengge; Chen, Guanghui; Jiao, Qing; Zang, Yu-Feng

2013-01-01

Abstract The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic–clonic seizures. PMID:23510272

Magnetic Resonance Imaging Profile of Blood–Brain Barrier Injury in Patients With Acute Intracerebral Hemorrhage

PubMed Central

Aksoy, Didem; Bammer, Roland; Mlynash, Michael; Venkatasubramanian, Chitra; Eyngorn, Irina; Snider, Ryan W.; Gupta, Sandeep N.; Narayana, Rashmi; Fischbein, Nancy; Wijman, Christine A. C.

2013-01-01

Background Spontaneous intracerebral hemorrhage (ICH) is associated with blood–brain barrier (BBB) injury, which is a poorly understood factor in ICH pathogenesis, potentially contributing to edema formation and perihematomal tissue injury. We aimed to assess and quantify BBB permeability following human spontaneous ICH using dynamic contrast‐enhanced magnetic resonance imaging (DCE MRI). We also investigated whether hematoma size or location affected the amount of BBB leakage. Methods and Results Twenty‐five prospectively enrolled patients from the Diagnostic Accuracy of MRI in Spontaneous intracerebral Hemorrhage (DASH) study were examined using DCE MRI at 1 week after symptom onset. Contrast agent dynamics in the brain tissue and general tracer kinetic modeling were used to estimate the forward leakage rate (Ktrans) in regions of interest (ROI) in and surrounding the hematoma and in contralateral mirror–image locations (control ROI). In all patients BBB permeability was significantly increased in the brain tissue immediately adjacent to the hematoma, that is, the hematoma rim, compared to the contralateral mirror ROI (P<0.0001). Large hematomas (>30 mL) had higher Ktrans values than small hematomas (P<0.005). Ktrans values of lobar hemorrhages were significantly higher than the Ktrans values of deep hemorrhages (P<0.005), independent of hematoma volume. Higher Ktrans values were associated with larger edema volumes. Conclusions BBB leakage in the brain tissue immediately bordering the hematoma can be measured and quantified by DCE MRI in human ICH. BBB leakage at 1 week is greater in larger hematomas as well as in hematomas in lobar locations and is associated with larger edema volumes. PMID:23709564

Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space

PubMed Central

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F. Xavier; Milham, Michael P.

2013-01-01

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test–retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo’s TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). PMID:23085497

Tissue specific resonance frequencies of water and metabolites within the human brain

NASA Astrophysics Data System (ADS)

Chadzynski, Grzegorz L.; Bender, Benjamin; Groeger, Adriane; Erb, Michael; Klose, Uwe

2011-09-01

Chemical shift imaging (CSI) without water suppression was used to examine tissue-specific resonance frequencies of water and metabolites within the human brain. The aim was to verify if there are any regional differences in those frequencies and to determine the influence of chemical shift displacement in slice-selection direction. Unsuppressed spectra were acquired at 3 T from nine subjects. Resonance frequencies of water and after water signal removal of total choline, total creatine and NAA were estimated. Furthermore, frequency distances between the water and those resonances were calculated. Results were corrected for chemical shift displacement. Frequency distances between water and metabolites were consistent and greater for GM than for WM. The highest value of WM to GM difference (14 ppb) was observed for water to NAA frequency distance. This study demonstrates that there are tissue-specific differences between frequency distances of water and metabolites. Moreover, the influence of chemical shift displacement in slice-selection direction is showed to be negligible.

Tissue specific resonance frequencies of water and metabolites within the human brain.

PubMed

Chadzynski, Grzegorz L; Bender, Benjamin; Groeger, Adriane; Erb, Michael; Klose, Uwe

2011-09-01

Chemical shift imaging (CSI) without water suppression was used to examine tissue-specific resonance frequencies of water and metabolites within the human brain. The aim was to verify if there are any regional differences in those frequencies and to determine the influence of chemical shift displacement in slice-selection direction. Unsuppressed spectra were acquired at 3T from nine subjects. Resonance frequencies of water and after water signal removal of total choline, total creatine and NAA were estimated. Furthermore, frequency distances between the water and those resonances were calculated. Results were corrected for chemical shift displacement. Frequency distances between water and metabolites were consistent and greater for GM than for WM. The highest value of WM to GM difference (14ppb) was observed for water to NAA frequency distance. This study demonstrates that there are tissue-specific differences between frequency distances of water and metabolites. Moreover, the influence of chemical shift displacement in slice-selection direction is showed to be negligible. Copyright © 2011 Elsevier Inc. All rights reserved.

[Effect of new peptide bioregulators livagen and epitalon on enkephalin-degrading enzymes in human serum].

PubMed

Kost, N V; Sokolov, O Iu; Gabaeva, M V; Zolotarev, Iu A; Malinin, V V; Khavinson, V Kh

2003-01-01

The effect of new peptide bioregulators--Livagen (Lys-Glu-Asp-Ala) and Epitalon (Ala-Glu-Asp-Gly)--on endogenous opioid system was studied, particularly, their ability to change the activity of enkephalin-degrading enzymes from serum and interact with opioid receptors of the brain membrane fraction. Enkephalinase activity was assayed in vitro by the rate of 3H-Leu-enkephalin hydrolysis in the presence of the tested peptides. Livagen and Epitalon inhibited enkephalin-degrading enzymes from human serum. Livagen proved to be more efficient also as compared to well-known peptidase inhibitors such as puromycin, leupeptin, and D-PAM. The dose-inhibitory effect curves for Livagen and Epitalon were plotted; their IC50 equaled 20 and 500 microM, respectively. The interaction between the peptides and opioid receptors was estimated using a radioreceptor method with [3H][D-Ala2, D-Leu5]-enkephalin. No interaction was observed between the tested peptides and mu- or delta-opioid receptors of the membrane fraction from the rat brain.

Brain Activity and Human Unilateral Chewing

PubMed Central

Quintero, A.; Ichesco, E.; Myers, C.; Schutt, R.; Gerstner, G.E.

2012-01-01

Brain mechanisms underlying mastication have been studied in non-human mammals but less so in humans. We used functional magnetic resonance imaging (fMRI) to evaluate brain activity in humans during gum chewing. Chewing was associated with activations in the cerebellum, motor cortex and caudate, cingulate, and brainstem. We also divided the 25-second chew-blocks into 5 segments of equal 5-second durations and evaluated activations within and between each of the 5 segments. This analysis revealed activation clusters unique to the initial segment, which may indicate brain regions involved with initiating chewing. Several clusters were uniquely activated during the last segment as well, which may represent brain regions involved with anticipatory or motor events associated with the end of the chew-block. In conclusion, this study provided evidence for specific brain areas associated with chewing in humans and demonstrated that brain activation patterns may dynamically change over the course of chewing sequences. PMID:23103631

Human Brain Modeling with Its Anatomical Structure and Realistic Material Properties for Brain Injury Prediction.

PubMed

Atsumi, Noritoshi; Nakahira, Yuko; Tanaka, Eiichi; Iwamoto, Masami

2018-05-01

Impairments of executive brain function after traumatic brain injury (TBI) due to head impacts in traffic accidents need to be obviated. Finite element (FE) analyses with a human brain model facilitate understanding of the TBI mechanisms. However, conventional brain FE models do not suitably describe the anatomical structure in the deep brain, which is a critical region for executive brain function, and the material properties of brain parenchyma. In this study, for better TBI prediction, a novel brain FE model with anatomical structure in the deep brain was developed. The developed model comprises a constitutive model of brain parenchyma considering anisotropy and strain rate dependency. Validation was performed against postmortem human subject test data associated with brain deformation during head impact. Brain injury analyses were performed using head acceleration curves obtained from reconstruction analysis of rear-end collision with a human whole-body FE model. The difference in structure was found to affect the regions of strain concentration, while the difference in material model contributed to the peak strain value. The injury prediction result by the proposed model was consistent with the characteristics in the neuroimaging data of TBI patients due to traffic accidents.

Brain-mapping projects using the common marmoset.

PubMed

Okano, Hideyuki; Mitra, Partha

2015-04-01

Globally, there is an increasing interest in brain-mapping projects, including the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative project in the USA, the Human Brain Project (HBP) in Europe, and the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project in Japan. These projects aim to map the structure and function of neuronal circuits to ultimately understand the vast complexity of the human brain. Brain/MINDS is focused on structural and functional mapping of the common marmoset (Callithrix jacchus) brain. This non-human primate has numerous advantages for brain mapping, including a well-developed frontal cortex and a compact brain size, as well as the availability of transgenic technologies. In the present review article, we discuss strategies for structural and functional mapping of the marmoset brain and the relation of the common marmoset to other animals models. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Fast estimation of diffusion tensors under Rician noise by the EM algorithm.

PubMed

Liu, Jia; Gasbarra, Dario; Railavo, Juha

2016-01-15

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a fast computational method for maximum likelihood estimation (MLE) of diffusivities under the Rician noise model based on the expectation maximization (EM) algorithm. By using data augmentation, we are able to transform a non-linear regression problem into the generalized linear modeling framework, reducing dramatically the computational cost. The Fisher-scoring method is used for achieving fast convergence of the tensor parameter. The new method is implemented and applied using both synthetic and real data in a wide range of b-amplitudes up to 14,000s/mm(2). Higher accuracy and precision of the Rician estimates are achieved compared with other log-normal based methods. In addition, we extend the maximum likelihood (ML) framework to the maximum a posteriori (MAP) estimation in DTI under the aforementioned scheme by specifying the priors. We will describe how close numerically are the estimators of model parameters obtained through MLE and MAP estimation. Copyright © 2015 Elsevier B.V. All rights reserved.

Fractals in the neurosciences, Part II: clinical applications and future perspectives.

PubMed

Di Ieva, Antonio; Esteban, Francisco J; Grizzi, Fabio; Klonowski, Wlodzimierz; Martín-Landrove, Miguel

2015-02-01

It has been ascertained that the human brain is a complex system studied at multiple scales, from neurons and microcircuits to macronetworks. The brain is characterized by a hierarchical organization that gives rise to its highly topological and functional complexity. Over the last decades, fractal geometry has been shown as a universal tool for the analysis and quantification of the geometric complexity of natural objects, including the brain. The fractal dimension has been identified as a quantitative parameter for the evaluation of the roughness of neural structures, the estimation of time series, and the description of patterns, thus able to discriminate different states of the brain in its entire physiopathological spectrum. Fractal-based computational analyses have been applied to the neurosciences, particularly in the field of clinical neurosciences including neuroimaging and neuroradiology, neurology and neurosurgery, psychiatry and psychology, and neuro-oncology and neuropathology. After a review of the basic concepts of fractal analysis and its main applications to the basic neurosciences in part I of this series, here, we review the main applications of fractals to the clinical neurosciences for a holistic approach towards a fractal geometry model of the brain. © The Author(s) 2013.

Human brain distinctiveness based on EEG spectral coherence connectivity.

PubMed

Rocca, D La; Campisi, P; Vegso, B; Cserti, P; Kozmann, G; Babiloni, F; Fallani, F De Vico

2014-09-01

The use of EEG biometrics, for the purpose of automatic people recognition, has received increasing attention in the recent years. Most of the current analyses rely on the extraction of features characterizing the activity of single brain regions, like power spectrum estimation, thus neglecting possible temporal dependencies between the generated EEG signals. However, important physiological information can be extracted from the way different brain regions are functionally coupled. In this study, we propose a novel approach that fuses spectral coherence-based connectivity between different brain regions as a possibly viable biometric feature. The proposed approach is tested on a large dataset of subjects (N = 108) during eyes-closed (EC) and eyes-open (EO) resting state conditions. The obtained recognition performance shows that using brain connectivity leads to higher distinctiveness with respect to power-spectrum measurements, in both the experimental conditions. Notably, a 100% recognition accuracy is obtained in EC and EO when integrating functional connectivity between regions in the frontal lobe, while a lower 97.5% is obtained in EC (96.26% in EO) when fusing power spectrum information from parieto-occipital (centro-parietal in EO) regions. Taken together, these results suggest that the functional connectivity patterns represent effective features for improving EEG-based biometric systems.

The CONNECT project: Combining macro- and micro-structure.

PubMed

Assaf, Yaniv; Alexander, Daniel C; Jones, Derek K; Bizzi, Albero; Behrens, Tim E J; Clark, Chris A; Cohen, Yoram; Dyrby, Tim B; Huppi, Petra S; Knoesche, Thomas R; Lebihan, Denis; Parker, Geoff J M; Poupon, Cyril; Anaby, Debbie; Anwander, Alfred; Bar, Leah; Barazany, Daniel; Blumenfeld-Katzir, Tamar; De-Santis, Silvia; Duclap, Delphine; Figini, Matteo; Fischi, Elda; Guevara, Pamela; Hubbard, Penny; Hofstetter, Shir; Jbabdi, Saad; Kunz, Nicolas; Lazeyras, Francois; Lebois, Alice; Liptrot, Matthew G; Lundell, Henrik; Mangin, Jean-François; Dominguez, David Moreno; Morozov, Darya; Schreiber, Jan; Seunarine, Kiran; Nava, Simone; Poupon, Cyril; Riffert, Till; Sasson, Efrat; Schmitt, Benoit; Shemesh, Noam; Sotiropoulos, Stam N; Tavor, Ido; Zhang, Hui Gary; Zhou, Feng-Lei

2013-10-15

In recent years, diffusion MRI has become an extremely important tool for studying the morphology of living brain tissue, as it provides unique insights into both its macrostructure and microstructure. Recent applications of diffusion MRI aimed to characterize the structural connectome using tractography to infer connectivity between brain regions. In parallel to the development of tractography, additional diffusion MRI based frameworks (CHARMED, AxCaliber, ActiveAx) were developed enabling the extraction of a multitude of micro-structural parameters (axon diameter distribution, mean axonal diameter and axonal density). This unique insight into both tissue microstructure and connectivity has enormous potential value in understanding the structure and organization of the brain as well as providing unique insights to abnormalities that underpin disease states. The CONNECT (Consortium Of Neuroimagers for the Non-invasive Exploration of brain Connectivity and Tracts) project aimed to combine tractography and micro-structural measures of the living human brain in order to obtain a better estimate of the connectome, while also striving to extend validation of these measurements. This paper summarizes the project and describes the perspective of using micro-structural measures to study the connectome. Copyright © 2013 Elsevier Inc. All rights reserved.

Causal Inference for fMRI Time Series Data with Systematic Errors of Measurement in a Balanced On/Off Study of Social Evaluative Threat.

PubMed

Sobel, Michael E; Lindquist, Martin A

2014-07-01

Functional magnetic resonance imaging (fMRI) has facilitated major advances in understanding human brain function. Neuroscientists are interested in using fMRI to study the effects of external stimuli on brain activity and causal relationships among brain regions, but have not stated what is meant by causation or defined the effects they purport to estimate. Building on Rubin's causal model, we construct a framework for causal inference using blood oxygenation level dependent (BOLD) fMRI time series data. In the usual statistical literature on causal inference, potential outcomes, assumed to be measured without systematic error, are used to define unit and average causal effects. However, in general the potential BOLD responses are measured with stimulus dependent systematic error. Thus we define unit and average causal effects that are free of systematic error. In contrast to the usual case of a randomized experiment where adjustment for intermediate outcomes leads to biased estimates of treatment effects (Rosenbaum, 1984), here the failure to adjust for task dependent systematic error leads to biased estimates. We therefore adjust for systematic error using measured "noise covariates" , using a linear mixed model to estimate the effects and the systematic error. Our results are important for neuroscientists, who typically do not adjust for systematic error. They should also prove useful to researchers in other areas where responses are measured with error and in fields where large amounts of data are collected on relatively few subjects. To illustrate our approach, we re-analyze data from a social evaluative threat task, comparing the findings with results that ignore systematic error.

Estimation of Dynamic Sparse Connectivity Patterns From Resting State fMRI.

PubMed

Cai, Biao; Zille, Pascal; Stephen, Julia M; Wilson, Tony W; Calhoun, Vince D; Wang, Yu Ping

2018-05-01

Functional connectivity (FC) estimated from functional magnetic resonance imaging (fMRI) time series, especially during resting state periods, provides a powerful tool to assess human brain functional architecture in health, disease, and developmental states. Recently, the focus of connectivity analysis has shifted toward the subnetworks of the brain, which reveals co-activating patterns over time. Most prior works produced a dense set of high-dimensional vectors, which are hard to interpret. In addition, their estimations to a large extent were based on an implicit assumption of spatial and temporal stationarity throughout the fMRI scanning session. In this paper, we propose an approach called dynamic sparse connectivity patterns (dSCPs), which takes advantage of both matrix factorization and time-varying fMRI time series to improve the estimation power of FC. The feasibility of analyzing dynamic FC with our model is first validated through simulated experiments. Then, we use our framework to measure the difference between young adults and children with real fMRI data set from the Philadelphia Neurodevelopmental Cohort (PNC). The results from the PNC data set showed significant FC differences between young adults and children in four different states. For instance, young adults had reduced connectivity between the default mode network and other subnetworks, as well as hyperconnectivity within the visual system in states 1 and 3, and hypoconnectivity in state 2. Meanwhile, they exhibited temporal correlation patterns that changed over time within functional subnetworks. In addition, the dSCPs model indicated that older people tend to spend more time within a relatively connected FC pattern. Overall, the proposed method provides a valid means to assess dynamic FC, which could facilitate the study of brain networks.

Dexamethasone-mediated inhibition of Glioblastoma neurosphere dispersal in an ex vivo organotypic neural assay

PubMed Central

Meleis, Ahmed M.; Mahtabfar, Aria; Danish, Shabbar

2017-01-01

Glioblastoma is highly aggressive. Early dispersal of the primary tumor renders localized therapy ineffective. Recurrence always occurs and leads to patient death. Prior studies have shown that dispersal of Glioblastoma can be significantly reduced by Dexamethasone (Dex), a drug currently used to control brain tumor related edema. However, due to high doses and significant side effects, treatment is tapered and discontinued as soon as edema has resolved. Prior analyses of the dispersal inhibitory effects of Dex were performed on tissue culture plastic, or polystyrene filters seeded with normal human astrocytes, conditions which inherently differ from the parenchymal architecture of neuronal tissue. The aim of this study was to utilize an ex-vivo model to examine Dex-mediated inhibition of tumor cell migration from low-passage, human Glioblastoma neurospheres on multiple substrates including mouse retina, and slices of mouse, pig, and human brain. We also determined the lowest possible Dex dose that can inhibit dispersal. Analysis by Two-Factor ANOVA shows that for GBM-2 and GBM-3, Dex treatment significantly reduces dispersal on all tissue types. However, the magnitude of the effect appears to be tissue-type specific. Moreover, there does not appear to be a difference in Dex-mediated inhibition of dispersal between mouse retina, mouse brain and human brain. To estimate the lowest possible dose at which Dex can inhibit dispersal, LogEC50 values were compared by Extra Sum-of-Squares F-test. We show that it is possible to achieve 50% reduction in dispersal with Dex doses ranging from 3.8 x10-8M to 8.0x10-9M for GBM-2, and 4.3x10-8M to 1.8x10-9M for GBM-3, on mouse retina and brain slices, respectively. These doses are 3-30-fold lower than those used to control edema. This study extends our previous in vitro data and identifies the mouse retina as a potential substrate for in vivo studies of GBM dispersal. PMID:29040322

Risk patterns and correlated brain activities. Multidimensional statistical analysis of FMRI data in economic decision making study.

PubMed

van Bömmel, Alena; Song, Song; Majer, Piotr; Mohr, Peter N C; Heekeren, Hauke R; Härdle, Wolfgang K

2014-07-01

Decision making usually involves uncertainty and risk. Understanding which parts of the human brain are activated during decisions under risk and which neural processes underly (risky) investment decisions are important goals in neuroeconomics. Here, we analyze functional magnetic resonance imaging (fMRI) data on 17 subjects who were exposed to an investment decision task from Mohr, Biele, Krugel, Li, and Heekeren (in NeuroImage 49, 2556-2563, 2010b). We obtain a time series of three-dimensional images of the blood-oxygen-level dependent (BOLD) fMRI signals. We apply a panel version of the dynamic semiparametric factor model (DSFM) presented in Park, Mammen, Wolfgang, and Borak (in Journal of the American Statistical Association 104(485), 284-298, 2009) and identify task-related activations in space and dynamics in time. With the panel DSFM (PDSFM) we can capture the dynamic behavior of the specific brain regions common for all subjects and represent the high-dimensional time-series data in easily interpretable low-dimensional dynamic factors without large loss of variability. Further, we classify the risk attitudes of all subjects based on the estimated low-dimensional time series. Our classification analysis successfully confirms the estimated risk attitudes derived directly from subjects' decision behavior.

Cerebral glycogen in humans following acute and recurrent hypoglycemia: Implications on a role in hypoglycemia unawareness.

PubMed

Öz, Gülin; DiNuzzo, Mauro; Kumar, Anjali; Moheet, Amir; Khowaja, Ameer; Kubisiak, Kristine; Eberly, Lynn E; Seaquist, Elizabeth R

2017-08-01

Supercompensated brain glycogen levels may contribute to the development of hypoglycemia-associated autonomic failure (HAAF) following recurrent hypoglycemia (RH) by providing energy for the brain during subsequent periods of hypoglycemia. To assess the role of glycogen supercompensation in the generation of HAAF, we estimated the level of brain glycogen following RH and acute hypoglycemia (AH). After undergoing 3 hyperinsulinemic, euglycemic and 3 hyperinsulinemic, hypoglycemic clamps (RH) on separate occasions at least 1 month apart, five healthy volunteers received [1- 13 C]glucose intravenously over 80+ h while maintaining euglycemia. 13 C-glycogen levels in the occipital lobe were measured by 13 C magnetic resonance spectroscopy at ∼8, 20, 32, 44, 56, 68 and 80 h at 4 T and glycogen levels estimated by fitting the data with a biophysical model that takes into account the tiered glycogen structure. Similarly, prior 13 C-glycogen data obtained following a single hypoglycemic episode (AH) were fitted with the same model. Glycogen levels did not significantly increase after RH relative to after euglycemia, while they increased by ∼16% after AH relative to after euglycemia. These data suggest that glycogen supercompensation may be blunted with repeated hypoglycemic episodes. A causal relationship between glycogen supercompensation and generation of HAAF remains to be established.

Chaos in the brain: imaging via chaoticity of EEG/MEG signals

NASA Astrophysics Data System (ADS)

Kowalik, Zbigniew J.; Elbert, Thomas; Rockstroh, Brigitte; Hoke, Manfried

1995-03-01

Brain electro- (EEG) or magnetoencephalogram (MEG) can be analyzed by using methods of the nonlinear system theory. We show that even for very short and nonstationary time series it is possible to functionally differentiate various brain activities. Usually the analysis assumes that the analyzed signals are both long and stationary, so that the classic spectral methods can be used. Even more convincing results can be obtained under these circumstances when the dimensional analysis or estimation of the Kolmogorov entropy or the Lyapunov exponent are performed. When measuring the spontaneous activity of a human brain the assumption of stationarity is questionable and `static' methods (correlation dimension, entropy, etc.) are then not adequate. In this case `dynamic' methods like pointwise-D2 dimension or chaoticity measures should be applied. Predictability measures in the form of local Lyapunov exponents are capable of revealing directly the chaoticity of a given process, and can practically be applied for functional differentiation of brain activity. We exemplify these in cases of apallic syndrome, tinnitus and schizophrenia. We show that: the average chaoticity in apallic syndrome differentiates brain states both in space and time, chaoticity changes temporally in case of schizophrenia (critical jumps of chaoticity), chaoticity changes locally in space, i.e., in the cortex plane in case of tinnitus.

Advanced lesion symptom mapping analyses and implementation as BCBtoolkit.

PubMed

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika; Volle, Emmanuelle; Thiebaut de Schotten, Michel

2018-03-01

Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1].

Neuroimaging meta-analysis of cannabis use studies reveals convergent functional alterations in brain regions supporting cognitive control and reward processing.

PubMed

Yanes, Julio A; Riedel, Michael C; Ray, Kimberly L; Kirkland, Anna E; Bird, Ryan T; Boeving, Emily R; Reid, Meredith A; Gonzalez, Raul; Robinson, Jennifer L; Laird, Angela R; Sutherland, Matthew T

2018-03-01

Lagging behind rapid changes to state laws, societal views, and medical practice is the scientific investigation of cannabis's impact on the human brain. While several brain imaging studies have contributed important insight into neurobiological alterations linked with cannabis use, our understanding remains limited. Here, we sought to delineate those brain regions that consistently demonstrate functional alterations among cannabis users versus non-users across neuroimaging studies using the activation likelihood estimation meta-analysis framework. In ancillary analyses, we characterized task-related brain networks that co-activate with cannabis-affected regions using data archived in a large neuroimaging repository, and then determined which psychological processes may be disrupted via functional decoding techniques. When considering convergent alterations among users, decreased activation was observed in the anterior cingulate cortex, which co-activated with frontal, parietal, and limbic areas and was linked with cognitive control processes. Similarly, decreased activation was observed in the dorsolateral prefrontal cortex, which co-activated with frontal and occipital areas and linked with attention-related processes. Conversely, increased activation among users was observed in the striatum, which co-activated with frontal, parietal, and other limbic areas and linked with reward processing. These meta-analytic outcomes indicate that cannabis use is linked with differential, region-specific effects across the brain.

Metabolic costs and evolutionary implications of human brain development

PubMed Central

Kuzawa, Christopher W.; Chugani, Harry T.; Grossman, Lawrence I.; Lipovich, Leonard; Muzik, Otto; Hof, Patrick R.; Wildman, Derek E.; Sherwood, Chet C.; Leonard, William R.; Lange, Nicholas

2014-01-01

The high energetic costs of human brain development have been hypothesized to explain distinctive human traits, including exceptionally slow and protracted preadult growth. Although widely assumed to constrain life-history evolution, the metabolic requirements of the growing human brain are unknown. We combined previously collected PET and MRI data to calculate the human brain’s glucose use from birth to adulthood, which we compare with body growth rate. We evaluate the strength of brain–body metabolic trade-offs using the ratios of brain glucose uptake to the body’s resting metabolic rate (RMR) and daily energy requirements (DER) expressed in glucose-gram equivalents (glucosermr% and glucoseder%). We find that glucosermr% and glucoseder% do not peak at birth (52.5% and 59.8% of RMR, or 35.4% and 38.7% of DER, for males and females, respectively), when relative brain size is largest, but rather in childhood (66.3% and 65.0% of RMR and 43.3% and 43.8% of DER). Body-weight growth (dw/dt) and both glucosermr% and glucoseder% are strongly, inversely related: soon after birth, increases in brain glucose demand are accompanied by proportionate decreases in dw/dt. Ages of peak brain glucose demand and lowest dw/dt co-occur and subsequent developmental declines in brain metabolism are matched by proportionate increases in dw/dt until puberty. The finding that human brain glucose demands peak during childhood, and evidence that brain metabolism and body growth rate covary inversely across development, support the hypothesis that the high costs of human brain development require compensatory slowing of body growth rate. PMID:25157149

Neuron-Enriched Gene Expression Patterns are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain

PubMed Central

Tan, Powell Patrick Cheng; French, Leon; Pavlidis, Paul

2013-01-01

An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia to neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain. PMID:23440889

Neuron-Enriched Gene Expression Patterns are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain.

PubMed

Tan, Powell Patrick Cheng; French, Leon; Pavlidis, Paul

2013-01-01

An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia to neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain.

Brain Volume Estimation Enhancement by Morphological Image Processing Tools.

PubMed

Zeinali, R; Keshtkar, A; Zamani, A; Gharehaghaji, N

2017-12-01

Volume estimation of brain is important for many neurological applications. It is necessary in measuring brain growth and changes in brain in normal/abnormal patients. Thus, accurate brain volume measurement is very important. Magnetic resonance imaging (MRI) is the method of choice for volume quantification due to excellent levels of image resolution and between-tissue contrast. Stereology method is a good method for estimating volume but it requires to segment enough MRI slices and have a good resolution. In this study, it is desired to enhance stereology method for volume estimation of brain using less MRI slices with less resolution. In this study, a program for calculating volume using stereology method has been introduced. After morphologic method, dilation was applied and the stereology method enhanced. For the evaluation of this method, we used T1-wighted MR images from digital phantom in BrainWeb which had ground truth. The volume of 20 normal brain extracted from BrainWeb, was calculated. The volumes of white matter, gray matter and cerebrospinal fluid with given dimension were estimated correctly. Volume calculation from Stereology method in different cases was made. In three cases, Root Mean Square Error (RMSE) was measured. Case I with T=5, d=5, Case II with T=10, D=10 and Case III with T=20, d=20 (T=slice thickness, d=resolution as stereology parameters). By comparing these results of two methods, it is obvious that RMSE values for our proposed method are smaller than Stereology method. Using morphological operation, dilation allows to enhance the estimation volume method, Stereology. In the case with less MRI slices and less test points, this method works much better compared to Stereology method.

Tempo Rubato : Animacy Speeds Up Time in the Brain

PubMed Central

Carrozzo, Mauro; Moscatelli, Alessandro; Lacquaniti, Francesco

2010-01-01

Background How do we estimate time when watching an action? The idea that events are timed by a centralized clock has recently been called into question in favour of distributed, specialized mechanisms. Here we provide evidence for a critical specialization: animate and inanimate events are separately timed by humans. Methodology/Principal Findings In different experiments, observers were asked to intercept a moving target or to discriminate the duration of a stationary flash while viewing different scenes. Time estimates were systematically shorter in the sessions involving human characters moving in the scene than in those involving inanimate moving characters. Remarkably, the animate/inanimate context also affected randomly intermingled trials which always depicted the same still character. Conclusions/Significance The existence of distinct time bases for animate and inanimate events might be related to the partial segregation of the neural networks processing these two categories of objects, and could enhance our ability to predict critically timed actions. PMID:21206749

The Molecular Basis of Human Brain Evolution.

PubMed

Enard, Wolfgang

2016-10-24

Humans are a remarkable species, especially because of the remarkable properties of their brain. Since the split from the chimpanzee lineage, the human brain has increased three-fold in size and has acquired abilities for vocal learning, language and intense cooperation. To better understand the molecular basis of these changes is of great biological and biomedical interest. However, all the about 16 million fixed genetic changes that occurred during human evolution are fully correlated with all molecular, cellular, anatomical and behavioral changes that occurred during this time. Hence, as humans and chimpanzees cannot be crossed or genetically manipulated, no direct evidence for linking particular genetic and molecular changes to human brain evolution can be obtained. Here, I sketch a framework how indirect evidence can be obtained and review findings related to the molecular basis of human cognition, vocal learning and brain size. In particular, I discuss how a comprehensive comparative approach, leveraging cellular systems and genomic technologies, could inform the evolution of our brain in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hominin life history: reconstruction and evolution

PubMed Central

Robson, Shannen L; Wood, Bernard

2008-01-01

In this review we attempt to reconstruct the evolutionary history of hominin life history from extant and fossil evidence. We utilize demographic life history theory and distinguish life history variables, traits such as weaning, age at sexual maturity, and life span, from life history-related variables such as body mass, brain growth, and dental development. The latter are either linked with, or can be used to make inferences about, life history, thus providing an opportunity for estimating life history parameters in fossil taxa. We compare the life history variables of modern great apes and identify traits that are likely to be shared by the last common ancestor of Pan-Homo and those likely to be derived in hominins. All great apes exhibit slow life histories and we infer this to be true of the last common ancestor of Pan-Homo and the stem hominin. Modern human life histories are even slower, exhibiting distinctively long post-menopausal life spans and later ages at maturity, pointing to a reduction in adult mortality since the Pan-Homo split. We suggest that lower adult mortality, distinctively short interbirth intervals, and early weaning characteristic of modern humans are derived features resulting from cooperative breeding. We evaluate the fidelity of three life history-related variables, body mass, brain growth and dental development, with the life history parameters of living great apes. We found that body mass is the best predictor of great ape life history events. Brain growth trajectories and dental development and eruption are weakly related proxies and inferences from them should be made with caution. We evaluate the evidence of life history-related variables available for extinct species and find that prior to the transitional hominins there is no evidence of any hominin taxon possessing a body size, brain size or aspects of dental development much different from what we assume to be the primitive life history pattern for the Pan-Homo clade. Data for life history-related variables among the transitional hominin grade are consistent and none agrees with a modern human pattern. Aside from mean body mass, adult brain size, crown and root formation times, and the timing and sequence of dental eruption of Homo erectus are inconsistent with that of modern humans. Homo antecessor fossil material suggests a brain size similar to that of Homo erectus s. s., and crown formation times that are not yet modern, though there is some evidence of modern human-like timing of tooth formation and eruption. The body sizes, brain sizes, and dental development of Homo heidelbergensis and Homo neanderthalensis are consistent with a modern human life history but samples are too small to be certain that they have life histories within the modern human range. As more life history-related variable information for hominin species accumulates we are discovering that they can also have distinctive life histories that do not conform to any living model. At least one extinct hominin subclade, Paranthropus, has a pattern of dental life history-related variables that most likely set it apart from the life histories of both modern humans and chimpanzees. PMID:18380863

Removal of interfering nucleotides from brain extracts containing substance p. Effect of drugs on brain concentrations of substance p

PubMed Central

Laszlo, I.

1963-01-01

Several methods for removing interfering nucleotides, adenosine-5'-monophosphate and adenosine 5'-triphosphate from brain extracts have been studied. An enzymic method, using adenylic acid deaminase, has been found suitable. This deaminates adenosine monophosphate to 5'-inosinic acid, an inactive compound which does not influence the estimations of substance P. Owing to the adenosine triphosphatase content of the enzyme extract, adenosine triphosphate was also inactivated. For the estimation of adenosine monophosphate-deaminase activity, a simple colorimetric method is described which measures the ammonia liberated from adenosine monophosphate. Substance P in mouse brain extracts was estimated after treatment of the animals with various drugs, and after the enzymic removal of interfering nucleotides from the brain extracts. The drugs had no effect on the substance P content of mouse brain. The effect of drugs on the contractions of the guinea-pig ileum induced by substance P was also investigated, and the effect of drugs on the estimations of substance P in brain extracts is discussed. PMID:14066136

Mechanical characterization of human brain tumors from patients and comparison to potential surgical phantoms

PubMed Central

Rubiano, Andrés; Dyson, Kyle; Simmons, Chelsey S.

2017-01-01

While mechanical properties of the brain have been investigated thoroughly, the mechanical properties of human brain tumors rarely have been directly quantified due to the complexities of acquiring human tissue. Quantifying the mechanical properties of brain tumors is a necessary prerequisite, though, to identify appropriate materials for surgical tool testing and to define target parameters for cell biology and tissue engineering applications. Since characterization methods vary widely for soft biological and synthetic materials, here, we have developed a characterization method compatible with abnormally shaped human brain tumors, mouse tumors, animal tissue and common hydrogels, which enables direct comparison among samples. Samples were tested using a custom-built millimeter-scale indenter, and resulting force-displacement data is analyzed to quantify the steady-state modulus of each sample. We have directly quantified the quasi-static mechanical properties of human brain tumors with effective moduli ranging from 0.17–16.06 kPa for various pathologies. Of the readily available and inexpensive animal tissues tested, chicken liver (steady-state modulus 0.44 ± 0.13 kPa) has similar mechanical properties to normal human brain tissue while chicken crassus gizzard muscle (steady-state modulus 3.00 ± 0.65 kPa) has similar mechanical properties to human brain tumors. Other materials frequently used to mimic brain tissue in mechanical tests, like ballistic gel and chicken breast, were found to be significantly stiffer than both normal and diseased brain tissue. We have directly compared quasi-static properties of brain tissue, brain tumors, and common mechanical surrogates, though additional tests would be required to determine more complex constitutive models. PMID:28582392

Transcriptional Landscape of the Prenatal Human Brain

PubMed Central

Miller, Jeremy A.; Ding, Song-Lin; Sunkin, Susan M.; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L.; Aiona, Kaylynn; Arnold, James M.; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A.; Dee, Nick; Dolbeare, Tim A.; Facer, Benjamin A. C.; Feng, David; Fliss, Tim P.; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W.; Gu, Guangyu; Howard, Robert E.; Jochim, Jayson M.; Kuan, Chihchau L.; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A.; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick F.; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D.; Parry, Sheana E.; Player, Allison Stevens; Pletikos, Mihovil; Reding, Melissa; Royall, Joshua J.; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V.; Shen, Elaine H.; Sjoquist, Nathan; Slaughterbeck, Clifford R.; Smith, Michael; Sodt, Andy J.; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B.; Geschwind, Daniel H.; Glass, Ian A.; Hawrylycz, Michael J.; Hevner, Robert F.; Huang, Hao; Jones, Allan R.; Knowles, James A.; Levitt, Pat; Phillips, John W.; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G.; Lein, Ed S.

2014-01-01

Summary The anatomical and functional architecture of the human brain is largely determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and postmitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and human-expanded outer subventricular zones. Both germinal and postmitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in frontal lobe. Finally, many neurodevelopmental disorder and human evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development. PMID:24695229

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain

PubMed Central

Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.

2010-01-01

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408

Prevalence estimates for primary brain tumors in the United States by age, gender, behavior, and histology.

PubMed

Porter, Kimberly R; McCarthy, Bridget J; Freels, Sally; Kim, Yoonsang; Davis, Faith G

2010-06-01

Prevalence is the best indicator of cancer survivorship in the population, but few studies have focused on brain tumor prevalence because of previous data limitations. Hence, the full impact of primary brain tumors on the healthcare system in the United States is not completely described. The present study provides an estimate of the prevalence of disease in the United States, updating an earlier prevalence study. Incidence data for 2004 and survival data for 1985-2005 were obtained by the Central Brain Tumor Registry of the United States from selected regions, modeled under 2 different survival assumptions, to estimate prevalence rates for the year 2004 and projected estimates for 2010. The overall incidence rate for primary brain tumors was 18.1 per 100 000 person-years with 2-, 5-, 10-, and 20-year observed survival rates of 62%, 54%, 45%, and 30%, respectively. On the basis of the sum of nonmalignant and averaged malignant estimates, the overall prevalence rate of individuals with a brain tumor was estimated to be 209.0 per 100 000 in 2004 and 221.8 per 100 000 in 2010. The female prevalence rate (264.8 per 100 000) was higher than that in males (158.7 per 100 000). The averaged prevalence rate for malignant tumors (42.5 per 100 000) was lower than the prevalence for nonmalignant tumors (166.5 per 100 000). This study provides estimates of the 2004 (n = 612 770) and 2010 (n = 688 096) expected number of individuals living with primary brain tumor diagnoses in the United States, providing more current and robust estimates for aiding healthcare planning and patient advocacy for an aging US population.

Communication and the primate brain: insights from neuroimaging studies in humans, chimpanzees and macaques.

PubMed

Wilson, Benjamin; Petkov, Christopher I

2011-04-01

Considerable knowledge is available on the neural substrates for speech and language from brain-imaging studies in humans, but until recently there was a lack of data for comparison from other animal species on the evolutionarily conserved brain regions that process species-specific communication signals. To obtain new insights into the relationship of the substrates for communication in primates, we compared the results from several neuroimaging studies in humans with those that have recently been obtained from macaque monkeys and chimpanzees. The recent work in humans challenges the longstanding notion of highly localized speech areas. As a result, the brain regions that have been identified in humans for speech and nonlinguistic voice processing show a striking general correspondence to how the brains of other primates analyze species-specific vocalizations or information in the voice, such as voice identity. The comparative neuroimaging work has begun to clarify evolutionary relationships in brain function, supporting the notion that the brain regions that process communication signals in the human brain arose from a precursor network of regions that is present in nonhuman primates and is used for processing species-specific vocalizations. We conclude by considering how the stage now seems to be set for comparative neurobiology to characterize the ancestral state of the network that evolved in humans to support language.

Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies

PubMed Central

Liu, Xun; Hairston, Jacqueline; Schrier, Madeleine; Fan, Jin

2011-01-01

To better understand the reward circuitry in human brain, we conducted activation likelihood estimation (ALE) and parametric voxel-based meta-analyses (PVM) on 142 neuroimaging studies that examined brain activation in reward-related tasks in healthy adults. We observed several core brain areas that participated in reward-related decision making, including the nucleus accumbens (NAcc), caudate, putamen, thalamus, orbitofrontal cortex (OFC), bilateral anterior insula, anterior (ACC) and posterior (PCC) cingulate cortex, as well as cognitive control regions in the inferior parietal lobule and prefrontal cortex (PFC). The NAcc was commonly activated by both positive and negative rewards across various stages of reward processing (e.g., anticipation, outcome, and evaluation). In addition, the medial OFC and PCC preferentially responded to positive rewards, whereas the ACC, bilateral anterior insula, and lateral PFC selectively responded to negative rewards. Reward anticipation activated the ACC, bilateral anterior insula, and brain stem, whereas reward outcome more significantly activated the NAcc, medial OFC, and amygdala. Neurobiological theories of reward-related decision making should therefore distributed and interrelated representations of reward valuation and valence assessment into account. PMID:21185861

Prediction of brain maturity based on cortical thickness at different spatial resolutions.

PubMed

Khundrakpam, Budhachandra S; Tohka, Jussi; Evans, Alan C

2015-05-01

Several studies using magnetic resonance imaging (MRI) scans have shown developmental trajectories of cortical thickness. Cognitive milestones happen concurrently with these structural changes, and a delay in such changes has been implicated in developmental disorders such as attention-deficit/hyperactivity disorder (ADHD). Accurate estimation of individuals' brain maturity, therefore, is critical in establishing a baseline for normal brain development against which neurodevelopmental disorders can be assessed. In this study, cortical thickness derived from structural magnetic resonance imaging (MRI) scans of a large longitudinal dataset of normally growing children and adolescents (n=308), were used to build a highly accurate predictive model for estimating chronological age (cross-validated correlation up to R=0.84). Unlike previous studies which used kernelized approach in building prediction models, we used an elastic net penalized linear regression model capable of producing a spatially sparse, yet accurate predictive model of chronological age. Upon investigating different scales of cortical parcellation from 78 to 10,240 brain parcels, we observed that the accuracy in estimated age improved with increased spatial scale of brain parcellation, with the best estimations obtained for spatial resolutions consisting of 2560 and 10,240 brain parcels. The top predictors of brain maturity were found in highly localized sensorimotor and association areas. The results of our study demonstrate that cortical thickness can be used to estimate individuals' brain maturity with high accuracy, and the estimated ages relate to functional and behavioural measures, underscoring the relevance and scope of the study in the understanding of biological maturity. Copyright © 2015 Elsevier Inc. All rights reserved.

Structural and functional correlates of visual field asymmetry in the human brain by diffusion kurtosis MRI and functional MRI.

PubMed

O'Connell, Caitlin; Ho, Leon C; Murphy, Matthew C; Conner, Ian P; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C

2016-11-09

Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.

Multispectral imaging of absorption and scattering properties of in vivo exposed rat brain using a digital red-green-blue camera.

PubMed

Yoshida, Keiichiro; Nishidate, Izumi; Ishizuka, Tomohiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2015-05-01

In order to estimate multispectral images of the absorption and scattering properties in the cerebral cortex of in vivo rat brain, we investigated spectral reflectance images estimated by the Wiener estimation method using a digital RGB camera. A Monte Carlo simulation-based multiple regression analysis for the corresponding spectral absorbance images at nine wavelengths (500, 520, 540, 560, 570, 580, 600, 730, and 760 nm) was then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentrations of oxygenated hemoglobin and that of deoxygenated hemoglobin were estimated as the absorption parameters, whereas the coefficient a and the exponent b of the reduced scattering coefficient spectrum approximated by a power law function were estimated as the scattering parameters. The spectra of absorption and reduced scattering coefficients were reconstructed from the absorption and scattering parameters, and the spectral images of absorption and reduced scattering coefficients were then estimated. In order to confirm the feasibility of this method, we performed in vivo experiments on exposed rat brain. The estimated images of the absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of the reduced scattering coefficients had a broad scattering spectrum, exhibiting a larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. The changes in the estimated absorption and scattering parameters during normoxia, hyperoxia, and anoxia indicate the potential applicability of the method by which to evaluate the pathophysiological conditions of in vivo brain due to the loss of tissue viability.

[Sexual differentiation of the human brain].

PubMed

Kula, K; Słowikowska-Hilczer, J

2000-01-01

Normal human development requires the compatibility between genetic sex (sex chromosomes), sex of gonades (tests or ovaries), genitalia (external and internal sex organs), somatic features (body characteristics) and psychic sex. The psychic sex, called frequently gender, consist of gender identity (self-estimation), gender role (objective estimation) and sexual orientation (hetero- or homosexual). It was believed that the psychic gender depends only on socio-environmental influences such as rearing, learning and individual choice. Although, the process of sexual differentiation of human brain is not completely elucidated, it has became recently evident that endogenous hormones more then socio-environmental factors influence gender differences. Experimental studies on animals revealed that transient action of sex steroids during perinatal period of life is crucial for the dymorphism of sexual behavior (male or female) in adulthood. It seems, that also in the human male neonates testosterone produced by testes perinatally takes the main role in the irreversible masculinization of the brain i.e. creation of the differences vs. female brain. The evaluation of patients with disturbances of sexual differentiation of external genitalia (the lack of the testosterone transformation into 5-alpha dihydrotestosterone in peripheral tissues of men or the inborn excess of androgens in women with the congenital adrenal hyperplasia) has served as a useful clinical model for understanding factors, affecting the formation of gender. In these individuals the formal sex established according to genetic sex and somatic sex may be incompatible with gender identity and role. However, it has been found that the female gender identity is most frequently associated with the presence of ovaries or the lack of gonads (gonadal dysgenesis), while the male gender identity appear most frequently in the presence of testicular tissue irrespective of female or hermaphrodite (intersex) phenotype. In genetic men with the absence of male genitalia formation, caused by the aberrant function of androgen receptor, the gender identity depends on the severity of the disorder: female gender identity in the complete androgen insensitivity syndrome and female or male gender identity in the complete androgen insensitivity syndrome and female or male in the partial androgen insensitivity. These clinical observations confirm the experimental data indicating androgen role in the male gender identity creation. This knowledge is necessary for the decision of the direction of surgical correction of sex organs in children with ambiguous genitalia, which should not depend on the expected efficiency to perform sexual intercourse, but mostly on the expected or already present individual gender identity.

Possibility of Predicting Serotonin Transporter Occupancy From the In Vitro Inhibition Constant for Serotonin Transporter, the Clinically Relevant Plasma Concentration of Unbound Drugs, and Their Profiles for Substrates of Transporters.

PubMed

Yahata, Masahiro; Chiba, Koji; Watanabe, Takao; Sugiyama, Yuichi

2017-09-01

Accurate prediction of target occupancy facilitates central nervous system drug development. In this review, we discuss the predictability of serotonin transporter (SERT) occupancy in human brain estimated from in vitro K i values for human SERT and plasma concentrations of unbound drug (C u,plasma ), as well as the impact of drug transporters in the blood-brain barrier. First, the geometric means of in vitro K i values were compared with the means of in vivo K i values (K i,u,plasma ) which were calculated as C u,plasma values at 50% occupancy of SERT obtained from previous clinical positron emission tomography/single photon emission computed tomography imaging studies for 6 selective serotonin transporter reuptake inhibitors and 3 serotonin norepinephrine reuptake inhibitors. The in vitro K i values for 7 drugs were comparable to their in vivo K i,u,plasma values within 3-fold difference. SERT occupancy was overestimated for 5 drugs (P-glycoprotein substrates) and underestimated for 2 drugs (presumably uptake transporter substrates, although no evidence exists as yet). In conclusion, prediction of human SERT occupancy from in vitro K i values and C u,plasma was successful for drugs that are not transporter substrates and will become possible in future even for transporter substrates, once the transporter activities will be accurately estimated from in vitro experiments. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Monitoring alert and drowsy states by modeling EEG source nonstationarity

NASA Astrophysics Data System (ADS)

Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

2017-10-01

Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to monitoring cognitive or mental states of human operators in attention-critical settings or in passive brain-computer interfaces.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

PubMed

Job, Dominic E; Dickie, David Alexander; Rodriguez, David; Robson, Andrew; Danso, Sammy; Pernet, Cyril; Bastin, Mark E; Boardman, James P; Murray, Alison D; Ahearn, Trevor; Waiter, Gordon D; Staff, Roger T; Deary, Ian J; Shenkin, Susan D; Wardlaw, Joanna M

2017-01-01

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

FIB/SEM technology and Alzheimer's disease: three-dimensional analysis of human cortical synapses.

PubMed

Blazquez-Llorca, Lidia; Merchán-Pérez, Ángel; Rodríguez, José-Rodrigo; Gascón, Jorge; DeFelipe, Javier

2013-01-01

The quantification and measurement of synapses is a major goal in the study of brain organization in both health and disease. Serial section electron microscopy (EM) is the ideal method since it permits the direct quantification of crucial features such as the number of synapses per unit volume or the distribution and size of synapses. However, a major limitation is that obtaining long series of ultrathin sections is extremely time-consuming and difficult. Consequently, quantitative EM studies are scarce and the most common method employed to estimate synaptic density in the human brain is indirect, by counting at the light microscopic level immunoreactive puncta using synaptic markers. The recent development of automatic EM methods in experimental animals, such as the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM), are opening new avenues. Here we explored the utility of FIB/SEM to examine the cerebral cortex of Alzheimer's disease patients. We found that FIB/SEM is an excellent tool to study in detail the ultrastructure and alterations of the synaptic organization of the human brain. Using this technology, it is possible to reconstruct different types of plaques and the surrounding neuropil to find new aspects of the pathological process associated with the disease, namely; to count the exact number and types of synapses in different regions of the plaques, to study the spatial distribution of synapses, and to analyze the morphology and nature of the various types of dystrophic neurites and amyloid deposits.

Modification of existing human motor memories is enabled by primary cortical processing during memory reactivation.

PubMed

Censor, Nitzan; Dimyan, Michael A; Cohen, Leonardo G

2010-09-14

One of the most challenging tasks of the brain is to constantly update the internal neural representations of existing memories. Animal studies have used invasive methods such as direct microfusion of protein inhibitors to designated brain areas, in order to study the neural mechanisms underlying modification of already existing memories after their reactivation during recall [1-4]. Because such interventions are not possible in humans, it is not known how these neural processes operate in the human brain. In a series of experiments we show here that when an existing human motor memory is reactivated during recall, modification of the memory is blocked by virtual lesion [5] of the related primary cortical human brain area. The virtual lesion was induced by noninvasive repetitive transcranial magnetic stimulation guided by a frameless stereotactic brain navigation system and each subject's brain image. The results demonstrate that primary cortical processing in the human brain interacting with pre-existing reactivated memory traces is critical for successful modification of the existing related memory. Modulation of reactivated memories by noninvasive cortical stimulation may have important implications for human memory research and have far-reaching clinical applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain

PubMed Central

Wang, Niting; Li, Zehua; Xiao, Fangyan; Dai, Jiapei

2016-01-01

Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain. PMID:27432962

Beyond sex differences: new approaches for thinking about variation in brain structure and function

PubMed Central

Joel, Daphna; Fausto-Sterling, Anne

2016-01-01

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. PMID:26833844

Evidence of a Conserved Molecular Response to Selection for Increased Brain Size in Primates

PubMed Central

Harrison, Peter W.; Caravas, Jason A.; Raghanti, Mary Ann; Phillips, Kimberley A.; Mundy, Nicholas I.

2017-01-01

The adaptive significance of human brain evolution has been frequently studied through comparisons with other primates. However, the evolution of increased brain size is not restricted to the human lineage but is a general characteristic of primate evolution. Whether or not these independent episodes of increased brain size share a common genetic basis is unclear. We sequenced and de novo assembled the transcriptome from the neocortical tissue of the most highly encephalized nonhuman primate, the tufted capuchin monkey (Cebus apella). Using this novel data set, we conducted a genome-wide analysis of orthologous brain-expressed protein coding genes to identify evidence of conserved gene–phenotype associations and species-specific adaptations during three independent episodes of brain size increase. We identify a greater number of genes associated with either total brain mass or relative brain size across these six species than show species-specific accelerated rates of evolution in individual large-brained lineages. We test the robustness of these associations in an expanded data set of 13 species, through permutation tests and by analyzing how genome-wide patterns of substitution co-vary with brain size. Many of the genes targeted by selection during brain expansion have glutamatergic functions or roles in cell cycle dynamics. We also identify accelerated evolution in a number of individual capuchin genes whose human orthologs are associated with human neuropsychiatric disorders. These findings demonstrate the value of phenotypically informed genome analyses, and suggest at least some aspects of human brain evolution have occurred through conserved gene–phenotype associations. Understanding these commonalities is essential for distinguishing human-specific selection events from general trends in brain evolution. PMID:28391320

Glutamatergic and GABAergic TCA cycle and neurotransmitter cycling fluxes in different regions of mouse brain.

PubMed

Tiwari, Vivek; Ambadipudi, Susmitha; Patel, Anant B

2013-10-01

The (13)C nuclear magnetic resonance (NMR) studies together with the infusion of (13)C-labeled substrates in rats and humans have provided important insight into brain energy metabolism. In the present study, we have extended a three-compartment metabolic model in mouse to investigate glutamatergic and GABAergic tricarboxylic acid (TCA) cycle and neurotransmitter cycle fluxes across different regions of the brain. The (13)C turnover of amino acids from [1,6-(13)C2]glucose was monitored ex vivo using (1)H-[(13)C]-NMR spectroscopy. The astroglial glutamate pool size, one of the important parameters of the model, was estimated by a short infusion of [2-(13)C]acetate. The ratio Vcyc/VTCA was calculated from the steady-state acetate experiment. The (13)C turnover curves of [4-(13)C]/[3-(13)C]glutamate, [4-(13)C]glutamine, [2-(13)C]/[3-(13)C]GABA, and [3-(13)C]aspartate from [1,6-(13)C2]glucose were analyzed using a three-compartment metabolic model to estimate the rates of the TCA cycle and neurotransmitter cycle associated with glutamatergic and GABAergic neurons. The glutamatergic TCA cycle rate was found to be highest in the cerebral cortex (0.91 ± 0.05 μmol/g per minute) and least in the hippocampal region (0.64 ± 0.07 μmol/g per minute) of the mouse brain. In contrast, the GABAergic TCA cycle flux was found to be highest in the thalamus-hypothalamus (0.28 ± 0.01 μmol/g per minute) and least in the cerebral cortex (0.24 ± 0.02 μmol/g per minute). These findings indicate that the energetics of excitatory and inhibitory function is distinct across the mouse brain.

Brain serotonin transporter density and aggression in abstinent methamphetamine abusers.

PubMed

Sekine, Yoshimoto; Ouchi, Yasuomi; Takei, Nori; Yoshikawa, Etsuji; Nakamura, Kazuhiko; Futatsubashi, Masami; Okada, Hiroyuki; Minabe, Yoshio; Suzuki, Katsuaki; Iwata, Yasuhide; Tsuchiya, Kenji J; Tsukada, Hideo; Iyo, Masaomi; Mori, Norio

2006-01-01

In animals, methamphetamine is known to have a neurotoxic effect on serotonin neurons, which have been implicated in the regulation of mood, anxiety, and aggression. It remains unknown whether methamphetamine damages serotonin neurons in humans. To investigate the status of brain serotonin neurons and their possible relationship with clinical characteristics in currently abstinent methamphetamine abusers. Case-control analysis. A hospital research center. Twelve currently abstinent former methamphetamine abusers (5 women and 7 men) and 12 age-, sex-, and education-matched control subjects recruited from the community. The brain regional density of the serotonin transporter, a structural component of serotonin neurons, was estimated using positron emission tomography and trans-1,2,3,5,6,10-beta-hexahydro-6-[4-(methylthio)phenyl]pyrrolo-[2,1-a]isoquinoline ([(11)C](+)McN-5652). Estimates were derived from region-of-interest and statistical parametric mapping methods, followed by within-case analysis using the measures of clinical variables. The duration of methamphetamine use, the magnitude of aggression and depressive symptoms, and changes in serotonin transporter density represented by the [(11)C](+)McN-5652 distribution volume. Methamphetamine abusers showed increased levels of aggression compared with controls. Region-of-interest and statistical parametric mapping analyses revealed that the serotonin transporter density in global brain regions (eg, the midbrain, thalamus, caudate, putamen, cerebral cortex, and cerebellum) was significantly lower in methamphetamine abusers than in control subjects, and this reduction was significantly inversely correlated with the duration of methamphetamine use. Furthermore, statistical parametric mapping analyses indicated that the density in the orbitofrontal, temporal, and anterior cingulate areas was closely associated with the magnitude of aggression in methamphetamine abusers. Protracted abuse of methamphetamine may reduce the density of the serotonin transporter in the brain, leading to elevated aggression, even in currently abstinent abusers.

Loss of Brain Aerobic Glycolysis in Normal Human Aging.

PubMed

Goyal, Manu S; Vlassenko, Andrei G; Blazey, Tyler M; Su, Yi; Couture, Lars E; Durbin, Tony J; Bateman, Randall J; Benzinger, Tammie L-S; Morris, John C; Raichle, Marcus E

2017-08-01

The normal aging human brain experiences global decreases in metabolism, but whether this affects the topography of brain metabolism is unknown. Here we describe PET-based measurements of brain glucose uptake, oxygen utilization, and blood flow in cognitively normal adults from 20 to 82 years of age. Age-related decreases in brain glucose uptake exceed that of oxygen use, resulting in loss of brain aerobic glycolysis (AG). Whereas the topographies of total brain glucose uptake, oxygen utilization, and blood flow remain largely stable with age, brain AG topography changes significantly. Brain regions with high AG in young adults show the greatest change, as do regions with prolonged developmental transcriptional features (i.e., neoteny). The normal aging human brain thus undergoes characteristic metabolic changes, largely driven by global loss and topographic changes in brain AG. Copyright © 2017 Elsevier Inc. All rights reserved.

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Quantitative Imaging of Energy Expenditure in Human Brain

PubMed Central

Zhu, Xiao-Hong; Qiao, Hongyan; Du, Fei; Xiong, Qiang; Liu, Xiao; Zhang, Xiaoliang; Ugurbil, Kamil; Chen, Wei

2012-01-01

Despite the essential role of the brain energy generated from ATP hydrolysis in supporting cortical neuronal activity and brain function, it is challenging to noninvasively image and directly quantify the energy expenditure in the human brain. In this study, we applied an advanced in vivo 31P MRS imaging approach to obtain regional cerebral metabolic rates of high-energy phosphate reactions catalyzed by ATPase (CMRATPase) and creatine kinase (CMRCK), and to determine CMRATPase and CMRCK in pure grey mater (GM) and white mater (WM), respectively. It was found that both ATPase and CK rates are three times higher in GM than WM; and CMRCK is seven times higher than CMRATPase in GM and WM. Among the total brain ATP consumption in the human cortical GM and WM, 77% of them are used by GM in which approximately 96% is by neurons. A single cortical neuron utilizes approximately 4.7 billion ATPs per second in a resting human brain. This study demonstrates the unique utility of in vivo 31P MRS imaging modality for direct imaging of brain energy generated from ATP hydrolysis, and provides new insights into the human brain energetics and its role in supporting neuronal activity and brain function. PMID:22487547

Characteristics of allelic gene expression in human brain cells from single-cell RNA-seq data analysis.

PubMed

Zhao, Dejian; Lin, Mingyan; Pedrosa, Erika; Lachman, Herbert M; Zheng, Deyou

2017-11-10

Monoallelic expression of autosomal genes has been implicated in human psychiatric disorders. However, there is a paucity of allelic expression studies in human brain cells at the single cell and genome wide levels. In this report, we reanalyzed a previously published single-cell RNA-seq dataset from several postmortem human brains and observed pervasive monoallelic expression in individual cells, largely in a random manner. Examining single nucleotide variants with a predicted functional disruption, we found that the "damaged" alleles were overall expressed in fewer brain cells than their counterparts, and at a lower level in cells where their expression was detected. We also identified many brain cell type-specific monoallelically expressed genes. Interestingly, many of these cell type-specific monoallelically expressed genes were enriched for functions important for those brain cell types. In addition, function analysis showed that genes displaying monoallelic expression and correlated expression across neuronal cells from different individual brains were implicated in the regulation of synaptic function. Our findings suggest that monoallelic gene expression is prevalent in human brain cells, which may play a role in generating cellular identity and neuronal diversity and thus increasing the complexity and diversity of brain cell functions.

Detecting Large-Scale Brain Networks Using EEG: Impact of Electrode Density, Head Modeling and Source Localization

PubMed Central

Liu, Quanying; Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2018-01-01

Resting state networks (RSNs) in the human brain were recently detected using high-density electroencephalography (hdEEG). This was done by using an advanced analysis workflow to estimate neural signals in the cortex and to assess functional connectivity (FC) between distant cortical regions. FC analyses were conducted either using temporal (tICA) or spatial independent component analysis (sICA). Notably, EEG-RSNs obtained with sICA were very similar to RSNs retrieved with sICA from functional magnetic resonance imaging data. It still remains to be clarified, however, what technological aspects of hdEEG acquisition and analysis primarily influence this correspondence. Here we examined to what extent the detection of EEG-RSN maps by sICA depends on the electrode density, the accuracy of the head model, and the source localization algorithm employed. Our analyses revealed that the collection of EEG data using a high-density montage is crucial for RSN detection by sICA, but also the use of appropriate methods for head modeling and source localization have a substantial effect on RSN reconstruction. Overall, our results confirm the potential of hdEEG for mapping the functional architecture of the human brain, and highlight at the same time the interplay between acquisition technology and innovative solutions in data analysis. PMID:29551969

The impact of cognitive load on reward evaluation.

PubMed

Krigolson, Olave E; Hassall, Cameron D; Satel, Jason; Klein, Raymond M

2015-11-19

The neural systems that afford our ability to evaluate rewards and punishments are impacted by a variety of external factors. Here, we demonstrate that increased cognitive load reduces the functional efficacy of a reward processing system within the human medial-frontal cortex. In our paradigm, two groups of participants used performance feedback to estimate the exact duration of one second while electroencephalographic (EEG) data was recorded. Prior to performing the time estimation task, both groups were instructed to keep their eyes still and avoid blinking in line with well established EEG protocol. However, during performance of the time-estimation task, one of the two groups was provided with trial-to-trial-feedback about their performance on the time-estimation task and their eye movements to induce a higher level of cognitive load relative to participants in the other group who were solely provided with feedback about the accuracy of their temporal estimates. In line with previous work, we found that the higher level of cognitive load reduced the amplitude of the feedback-related negativity, a component of the human event-related brain potential associated with reward evaluation within the medial-frontal cortex. Importantly, our results provide further support that increased cognitive load reduces the functional efficacy of a neural system associated with reward processing. Copyright © 2015 Elsevier B.V. All rights reserved.

Toward determining the lifetime occurrence of metastatic brain tumors estimated from 2007 United States cancer incidence data

PubMed Central

Davis, Faith G.; Dolecek, Therese A.; McCarthy, Bridget J.; Villano, John L.

2012-01-01

Few population estimates of brain metastasis in the United States are available, prompting this study. Our objective was to estimate the expected number of metastatic brain tumors that would subsequently develop among incident cancer cases for 1 diagnosis year in the United States. Incidence proportions for primary cancer sites known to develop brain metastasis were applied to United States cancer incidence data for 2007 that were retrieved from accessible data sets through Centers for Disease Control and Prevention (CDC Wonder) and Surveillance, Epidemiology, and End Results (SEER) Program Web sites. Incidence proportions were identified for cancer sites, reflecting 80% of all cancers. It was conservatively estimated that almost 70 000 new brain metastases would occur over the remaining lifetime of individuals who received a diagnosis in 2007 of primary invasive cancer in the United States. That is, 6% of newly diagnosed cases of cancer during 2007 would be expected to develop brain metastasis as a progression of their original cancer diagnosis; the most frequent sites for metastases being lung and bronchus and breast cancers. The estimated numbers of brain metastasis will be expected to be higher among white individuals, female individuals, and older age groups. Changing patterns in the occurrence of primary cancers, trends in populations at risk, effectiveness of treatments on survival, and access to those treatments will influence the extent of brain tumor metastasis at the population level. These findings provide insight on the patterns of brain tumor metastasis and the future burden of this condition in the United States. PMID:22898372

Toward determining the lifetime occurrence of metastatic brain tumors estimated from 2007 United States cancer incidence data.

PubMed

Davis, Faith G; Dolecek, Therese A; McCarthy, Bridget J; Villano, John L

2012-09-01

Few population estimates of brain metastasis in the United States are available, prompting this study. Our objective was to estimate the expected number of metastatic brain tumors that would subsequently develop among incident cancer cases for 1 diagnosis year in the United States. Incidence proportions for primary cancer sites known to develop brain metastasis were applied to United States cancer incidence data for 2007 that were retrieved from accessible data sets through Centers for Disease Control and Prevention (CDC Wonder) and Surveillance, Epidemiology, and End Results (SEER) Program Web sites. Incidence proportions were identified for cancer sites, reflecting 80% of all cancers. It was conservatively estimated that almost 70 000 new brain metastases would occur over the remaining lifetime of individuals who received a diagnosis in 2007 of primary invasive cancer in the United States. That is, 6% of newly diagnosed cases of cancer during 2007 would be expected to develop brain metastasis as a progression of their original cancer diagnosis; the most frequent sites for metastases being lung and bronchus and breast cancers. The estimated numbers of brain metastasis will be expected to be higher among white individuals, female individuals, and older age groups. Changing patterns in the occurrence of primary cancers, trends in populations at risk, effectiveness of treatments on survival, and access to those treatments will influence the extent of brain tumor metastasis at the population level. These findings provide insight on the patterns of brain tumor metastasis and the future burden of this condition in the United States.

Total brain death: a reply to Alan Shewmon.

PubMed

Lee, Patrick; GriseZ, Germain

2012-06-01

D. Alan Shewmon has advanced a well-documented challenge to the widely accepted total brain death criterion for death of the human being. We show that Shewmon’s argument against this criterion is unsound, though he does refute the standard argument for that criterion. We advance a distinct argument for the total brain death criterion and answer likely objections. Since human beings are rational animals--sentient organisms of a specific type--the loss of the radical capacity for sentience (the capacity to sense or to develop the capacity to sense) involves a substantial change, the passing away of the human organism. In human beings total brain death involves the complete loss of the radical capacity for sentience, and so in human beings total brain death is death.

Estimation of effective brain connectivity with dual Kalman filter and EEG source localization methods.

PubMed

Rajabioun, Mehdi; Nasrabadi, Ali Motie; Shamsollahi, Mohammad Bagher

2017-09-01

Effective connectivity is one of the most important considerations in brain functional mapping via EEG. It demonstrates the effects of a particular active brain region on others. In this paper, a new method is proposed which is based on dual Kalman filter. In this method, firstly by using a brain active localization method (standardized low resolution brain electromagnetic tomography) and applying it to EEG signal, active regions are extracted, and appropriate time model (multivariate autoregressive model) is fitted to extracted brain active sources for evaluating the activity and time dependence between sources. Then, dual Kalman filter is used to estimate model parameters or effective connectivity between active regions. The advantage of this method is the estimation of different brain parts activity simultaneously with the calculation of effective connectivity between active regions. By combining dual Kalman filter with brain source localization methods, in addition to the connectivity estimation between parts, source activity is updated during the time. The proposed method performance has been evaluated firstly by applying it to simulated EEG signals with interacting connectivity simulation between active parts. Noisy simulated signals with different signal to noise ratios are used for evaluating method sensitivity to noise and comparing proposed method performance with other methods. Then the method is applied to real signals and the estimation error during a sweeping window is calculated. By comparing proposed method results in different simulation (simulated and real signals), proposed method gives acceptable results with least mean square error in noisy or real conditions.

A Direct Brain-to-Brain Interface in Humans

PubMed Central

Rao, Rajesh P. N.; Stocco, Andrea; Bryan, Matthew; Sarma, Devapratim; Youngquist, Tiffany M.; Wu, Joseph; Prat, Chantel S.

2014-01-01

We describe the first direct brain-to-brain interface in humans and present results from experiments involving six different subjects. Our non-invasive interface, demonstrated originally in August 2013, combines electroencephalography (EEG) for recording brain signals with transcranial magnetic stimulation (TMS) for delivering information to the brain. We illustrate our method using a visuomotor task in which two humans must cooperate through direct brain-to-brain communication to achieve a desired goal in a computer game. The brain-to-brain interface detects motor imagery in EEG signals recorded from one subject (the “sender”) and transmits this information over the internet to the motor cortex region of a second subject (the “receiver”). This allows the sender to cause a desired motor response in the receiver (a press on a touchpad) via TMS. We quantify the performance of the brain-to-brain interface in terms of the amount of information transmitted as well as the accuracies attained in (1) decoding the sender’s signals, (2) generating a motor response from the receiver upon stimulation, and (3) achieving the overall goal in the cooperative visuomotor task. Our results provide evidence for a rudimentary form of direct information transmission from one human brain to another using non-invasive means. PMID:25372285

Cloning and sequence analysis of the human brain beta-adrenergic receptor. Evolutionary relationship to rodent and avian beta-receptors and porcine muscarinic receptors.

PubMed

Chung, F Z; Lentes, K U; Gocayne, J; Fitzgerald, M; Robinson, D; Kerlavage, A R; Fraser, C M; Venter, J C

1987-01-26

Two cDNA clones, lambda-CLFV-108 and lambda-CLFV-119, encoding for the beta-adrenergic receptor, have been isolated from a human brain stem cDNA library. One human genomic clone, LCV-517 (20 kb), was characterized by restriction mapping and partial sequencing. The human brain beta-receptor consists of 413 amino acids with a calculated Mr of 46480. The gene contains three potential glucocorticoid receptor-binding sites. The beta-receptor expressed in human brain was homology with rodent (88%) and avian (52%) beta-receptors and with porcine muscarinic cholinergic receptors (31%), supporting our proposal [(1984) Proc. Natl. Acad. Sci. USA 81, 272 276] that adrenergic and muscarinic cholinergic receptors are structurally related. This represents the first cloning of a neurotransmitter receptor gene from human brain.

An Integrated Self-Aware Cognitive Architecture

DTIC Science & Technology

2008-03-01

human-like cognitive growth. Our approach is inspired by studies of the human brain -mind: in particular, by theoretical models of representations of...agency in the higher associative human brain areas. This feature (a theory of mind including representations of one’s self) allows the system to...self-aware cognition that we believe is necessary for human-like cognitive growth. Our approach is inspired by studies of the human brain -mind: in

Brain development in rodents and humans: Identifying benchmarks of maturation and vulnerability to injury across species

PubMed Central

Semple, Bridgette D.; Blomgren, Klas; Gimlin, Kayleen; Ferriero, Donna M.; Noble-Haeusslein, Linda J.

2013-01-01

Hypoxic-ischemic and traumatic brain injuries are leading causes of long-term mortality and disability in infants and children. Although several preclinical models using rodents of different ages have been developed, species differences in the timing of key brain maturation events can render comparisons of vulnerability and regenerative capacities difficult to interpret. Traditional models of developmental brain injury have utilized rodents at postnatal day 7–10 as being roughly equivalent to a term human infant, based historically on the measurement of post-mortem brain weights during the 1970s. Here we will examine fundamental brain development processes that occur in both rodents and humans, to delineate a comparable time course of postnatal brain development across species. We consider the timing of neurogenesis, synaptogenesis, gliogenesis, oligodendrocyte maturation and age-dependent behaviors that coincide with developmentally regulated molecular and biochemical changes. In general, while the time scale is considerably different, the sequence of key events in brain maturation is largely consistent between humans and rodents. Further, there are distinct parallels in regional vulnerability as well as functional consequences in response to brain injuries. With a focus on developmental hypoxicischemic encephalopathy and traumatic brain injury, this review offers guidelines for researchers when considering the most appropriate rodent age for the developmental stage or process of interest to approximate human brain development. PMID:23583307

Bovine brain ribonuclease is the functional homolog of human ribonuclease 1.

PubMed

Eller, Chelcie H; Lomax, Jo E; Raines, Ronald T

2014-09-19

Mounting evidence suggests that human pancreatic ribonuclease (RNase 1) plays important roles in vivo, ranging from regulating blood clotting and inflammation to directly counteracting tumorigenic cells. Understanding these putative roles has been pursued with continual comparisons of human RNase 1 to bovine RNase A, an enzyme that appears to function primarily in the ruminant gut. Our results imply a different physiology for human RNase 1. We demonstrate distinct functional differences between human RNase 1 and bovine RNase A. Moreover, we characterize another RNase 1 homolog, bovine brain ribonuclease, and find pronounced similarities between that enzyme and human RNase 1. We report that human RNase 1 and bovine brain ribonuclease share high catalytic activity against double-stranded RNA substrates, a rare quality among ribonucleases. Both human RNase 1 and bovine brain RNase are readily endocytosed by mammalian cells, aided by tight interactions with cell surface glycans. Finally, we show that both human RNase 1 and bovine brain RNase are secreted from endothelial cells in a regulated manner, implying a potential role in vascular homeostasis. Our results suggest that brain ribonuclease, not RNase A, is the true bovine homolog of human RNase 1, and provide fundamental insight into the ancestral roles and functional adaptations of RNase 1 in mammals. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

A theory of marks and mind: the effect of notational systems on hominid brain evolution and child development with an emphasis on exchanges between mothers and children.

PubMed

Sheridan, Susan Rich

2005-01-01

A model of human language requires a theory of meaningful marks. Humans are the only species who use marks to think. A theory of marks identifies children's scribbles as significant behavior, while hypothesizing the importance of rotational systems to hominid brain evolution. By recognizing the importance of children's scribbles and drawings in developmental terms as well as in evolutionary terms, a marks-based rather than a predominantly speech-based theory of the human brain, language, and consciousness emerges. Combined research in anthropology, primatology, art history, neurology, child development (including research with deaf and blind children), gender studies and literacy suggests the importance of notational systems to human language, revealing the importance of mother/child interactions around marks and sounds to the development of an expressive, communicative, symbolic human brain. An understanding of human language is enriched by identifying marks carved on bone 1.9 million years ago as observational lunar calendar-keeping, pushing proto-literacy back dramatically. Neurologically, children recapitulate the meaningful marks of early hominins when they scribble and draw, reminding us that literacy belongs to humankind's earliest history. Even more than speech, such meaningful marks played - and continue to play - decisive roles in human brain evolution. The hominid brain required a model for integrative, transformative neural transfer. The research strongly suggests that humankind's multiple literacies (art, literature, scientific writing, mathematics and music) depended upon dyadic exchanges between hominid mothers and children, and that this exchange and sharing of visuo-spatial information drove the elaboration of human speech in terms of syntax, grammar and vocabulary. The human brain was spatial before it was linguistic. The child scribbles and draws before it speaks or writes. Children babble and scribble within the first two years of life. Hands and mouths are proximal on the sensory-motor cortex. Gestures accompany speech. Illiterate brains mis-pronounce nonsense sounds. Literate brains do not. Written language (work of the hands) enhances spoken language (work of the mouth). Until brain scans map the neurological links between human gesture, speech and marks in the context of mother/caregiver/child interactions, and research with literate and illiterate brains document even more precisely the long-term differences between these brains, the evolutionary pressure of marks on especially flexible maternal and infant brain tissue that occurred 1.9 million years, radically changing primate brain capabilities, requires an integrated theory of marks and mind.

Transcriptional landscape of the prenatal human brain.

PubMed

Miller, Jeremy A; Ding, Song-Lin; Sunkin, Susan M; Smith, Kimberly A; Ng, Lydia; Szafer, Aaron; Ebbert, Amanda; Riley, Zackery L; Royall, Joshua J; Aiona, Kaylynn; Arnold, James M; Bennet, Crissa; Bertagnolli, Darren; Brouner, Krissy; Butler, Stephanie; Caldejon, Shiella; Carey, Anita; Cuhaciyan, Christine; Dalley, Rachel A; Dee, Nick; Dolbeare, Tim A; Facer, Benjamin A C; Feng, David; Fliss, Tim P; Gee, Garrett; Goldy, Jeff; Gourley, Lindsey; Gregor, Benjamin W; Gu, Guangyu; Howard, Robert E; Jochim, Jayson M; Kuan, Chihchau L; Lau, Christopher; Lee, Chang-Kyu; Lee, Felix; Lemon, Tracy A; Lesnar, Phil; McMurray, Bergen; Mastan, Naveed; Mosqueda, Nerick; Naluai-Cecchini, Theresa; Ngo, Nhan-Kiet; Nyhus, Julie; Oldre, Aaron; Olson, Eric; Parente, Jody; Parker, Patrick D; Parry, Sheana E; Stevens, Allison; Pletikos, Mihovil; Reding, Melissa; Roll, Kate; Sandman, David; Sarreal, Melaine; Shapouri, Sheila; Shapovalova, Nadiya V; Shen, Elaine H; Sjoquist, Nathan; Slaughterbeck, Clifford R; Smith, Michael; Sodt, Andy J; Williams, Derric; Zöllei, Lilla; Fischl, Bruce; Gerstein, Mark B; Geschwind, Daniel H; Glass, Ian A; Hawrylycz, Michael J; Hevner, Robert F; Huang, Hao; Jones, Allan R; Knowles, James A; Levitt, Pat; Phillips, John W; Sestan, Nenad; Wohnoutka, Paul; Dang, Chinh; Bernard, Amy; Hohmann, John G; Lein, Ed S

2014-04-10

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain

PubMed Central

Barrett, Lisa Feldman; Satpute, Ajay

2013-01-01

Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

Structural and Functional Correlates of Visual Field Asymmetry in the Human Brain by Diffusion Kurtosis MRI and Functional MRI

PubMed Central

O’Connell, Caitlin; Ho, Leon C.; Murphy, Matthew C.; Conner, Ian P.; Wollstein, Gadi; Cham, Rakie; Chan, Kevin C.

2016-01-01

Human visual performance has been observed to exhibit superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine if the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI (DKI), respectively in 15 healthy individuals at 3 Tesla. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In DKI, the brain regions mapping to the lower visual field exhibited higher mean kurtosis but not fractional anisotropy or mean diffusivity when compared to the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing. PMID:27631541

Development of a Human Neurovascular Unit Organotypic Systems Model of Early Brain Development

EPA Science Inventory

The inability to model human brain and blood-brain barrier development in vitro poses a major challenge in studies of how chemicals impact early neurogenic periods. During human development, disruption of thyroid hormone (TH) signaling is related to adverse morphological effects ...

Characterization and pathogenesis of aerosolized eastern equine encephalitis in the common marmoset (Callithrix jacchus).

PubMed

Porter, Aimee I; Erwin-Cohen, Rebecca A; Twenhafel, Nancy; Chance, Taylor; Yee, Steven B; Kern, Steven J; Norwood, David; Hartman, Laurie J; Parker, Michael D; Glass, Pamela J; DaSilva, Luis

2017-02-07

Licensed antiviral therapeutics and vaccines to protect against eastern equine encephalitis virus (EEEV) in humans currently do not exist. Animal models that faithfully recapitulate the clinical characteristics of human EEEV encephalitic disease, including fever, drowsiness, anorexia, and neurological signs such as seizures, are needed to satisfy requirements of the Food and Drug Administration (FDA) for clinical product licensing under the Animal Rule. In an effort to meet this requirement, we estimated the median lethal dose and described the pathogenesis of aerosolized EEEV in the common marmoset (Callithrix jacchus). Five marmosets were exposed to aerosolized EEEV FL93-939 in doses ranging from 2.4 × 10 1 PFU to 7.95 × 10 5 PFU. The median lethal dose was estimated to be 2.05 × 10 2 PFU. Lethality was observed as early as day 4 post-exposure in the highest-dosed marmoset but animals at lower inhaled doses had a protracted disease course where humane study endpoint was not met until as late as day 19 post-exposure. Clinical signs were observed as early as 3 to 4 days post-exposure, including fever, ruffled fur, decreased grooming, and leukocytosis. Clinical signs increased in severity as disease progressed to include decreased body weight, subdued behavior, tremors, and lack of balance. Fever was observed as early as day 2-3 post-exposure in the highest dose groups and hypothermia was observed in several cases as animals became moribund. Infectious virus was found in several key tissues, including brain, liver, kidney, and several lymph nodes. Clinical hematology results included early neutrophilia, lymphopenia, and thrombocytopenia. Key pathological changes included meningoencephalitis and retinitis. Immunohistochemical staining for viral antigen was positive in the brain, retina, and lymph nodes. More intense and widespread IHC labeling occurred with increased aerosol dose. We have estimated the medial lethal dose of aerosolized EEEV and described the pathology of clinical disease in the marmoset model. The results demonstrate that the marmoset is an animal model suitable for emulation of human EEEV disease in the development of medical countermeasures.

Relations between Brain Structure and Attentional Function in Spina Bifida: Utilization of Robust Statistical Approaches

PubMed Central

Kulesz, Paulina A.; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M.; Francis, David J.

2015-01-01

Objective Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Method Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product moment correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator Results All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Conclusions Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PMID:25495830

Relations between volumetric measures of brain structure and attentional function in spina bifida: utilization of robust statistical approaches.

PubMed

Kulesz, Paulina A; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M; Francis, David J

2015-03-01

Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product-moment correlation was compared with 4 robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator. All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Automatic estimation of extent of resection and residual tumor volume of patients with glioblastoma.

PubMed

Meier, Raphael; Porz, Nicole; Knecht, Urspeter; Loosli, Tina; Schucht, Philippe; Beck, Jürgen; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio

2017-10-01

OBJECTIVE In the treatment of glioblastoma, residual tumor burden is the only prognostic factor that can be actively influenced by therapy. Therefore, an accurate, reproducible, and objective measurement of residual tumor burden is necessary. This study aimed to evaluate the use of a fully automatic segmentation method-brain tumor image analysis (BraTumIA)-for estimating the extent of resection (EOR) and residual tumor volume (RTV) of contrast-enhancing tumor after surgery. METHODS The imaging data of 19 patients who underwent primary resection of histologically confirmed supratentorial glioblastoma were retrospectively reviewed. Contrast-enhancing tumors apparent on structural preoperative and immediate postoperative MR imaging in this patient cohort were segmented by 4 different raters and the automatic segmentation BraTumIA software. The manual and automatic results were quantitatively compared. RESULTS First, the interrater variabilities in the estimates of EOR and RTV were assessed for all human raters. Interrater agreement in terms of the coefficient of concordance (W) was higher for RTV (W = 0.812; p < 0.001) than for EOR (W = 0.775; p < 0.001). Second, the volumetric estimates of BraTumIA for all 19 patients were compared with the estimates of the human raters, which showed that for both EOR (W = 0.713; p < 0.001) and RTV (W = 0.693; p < 0.001) the estimates of BraTumIA were generally located close to or between the estimates of the human raters. No statistically significant differences were detected between the manual and automatic estimates. BraTumIA showed a tendency to overestimate contrast-enhancing tumors, leading to moderate agreement with expert raters with respect to the literature-based, survival-relevant threshold values for EOR. CONCLUSIONS BraTumIA can generate volumetric estimates of EOR and RTV, in a fully automatic fashion, which are comparable to the estimates of human experts. However, automated analysis showed a tendency to overestimate the volume of a contrast-enhancing tumor, whereas manual analysis is prone to subjectivity, thereby causing considerable interrater variability.

Socioeconomic status moderates age-related differences in the brain's functional network organization and anatomy across the adult lifespan.

PubMed

Chan, Micaela Y; Na, Jinkyung; Agres, Phillip F; Savalia, Neil K; Park, Denise C; Wig, Gagan S

2018-05-14

An individual's environmental surroundings interact with the development and maturation of their brain. An important aspect of an individual's environment is his or her socioeconomic status (SES), which estimates access to material resources and social prestige. Previous characterizations of the relation between SES and the brain have primarily focused on earlier or later epochs of the lifespan (i.e., childhood, older age). We broaden this work to examine the relationship between SES and the brain across a wide range of human adulthood (20-89 years), including individuals from the less studied middle-age range. SES, defined by education attainment and occupational socioeconomic characteristics, moderates previously reported age-related differences in the brain's functional network organization and whole-brain cortical structure. Across middle age (35-64 years), lower SES is associated with reduced resting-state system segregation (a measure of effective functional network organization). A similar but less robust relationship exists between SES and age with respect to brain anatomy: Lower SES is associated with reduced cortical gray matter thickness in middle age. Conversely, younger and older adulthood do not exhibit consistent SES-related difference in the brain measures. The SES-brain relationships persist after controlling for measures of physical and mental health, cognitive ability, and participant demographics. Critically, an individual's childhood SES cannot account for the relationship between their current SES and functional network organization. These findings provide evidence that SES relates to the brain's functional network organization and anatomy across adult middle age, and that higher SES may be a protective factor against age-related brain decline. Copyright © 2018 the Author(s). Published by PNAS.

Enhanced upper respiratory tract airflow and head fanning reduce brain temperature in brain-injured, mechanically ventilated patients: a randomized, crossover, factorial trial.

PubMed

Harris, B A; Andrews, P J D; Murray, G D

2007-01-01

Heat loss from the upper airways and through the skull are physiological mechanisms of brain cooling which have not been fully explored clinically. This randomized, crossover, factorial trial in 12 brain-injured, orally intubated patients investigated the effect of enhanced nasal airflow (high flow unhumidified air with 20 p.p.m. nitric oxide gas) and bilateral head fanning on frontal lobe brain temperature and selective brain cooling. After a 30 min baseline, each patient received the four possible combinations of the interventions--airflow, fanning, both together, no intervention--in randomized order. Each combination was delivered for 30 min and followed by a 30 min washout, the last 5 min of which provided the baseline for the next intervention. The difference in mean brain temperature over the last 5 min of the preceding washout minus the mean over the last 5 min of intervention, was 0.15 degrees C with nasal airflow (P=0.001, 95% CI 0.06-0.23 degrees C) and 0.26 degrees C with head fanning (P<0.001, 95% CI 0.17-0.34 degrees C). The estimate of the combined effect of airflow and fanning on brain temperature was 0.41 degrees C. Selective brain cooling did not occur. Physiologically, this study demonstrates that heat loss through the upper airways and through the skull can reduce parenchymal brain temperature in brain-injured humans and the onset of temperature reduction is rapid. Clinically, in ischaemic stroke, a temperature decrease of 0.27 degrees C may reduce the relative risk of poor outcome by 10-20%. Head fanning may have the potential to achieve a temperature decrease of this order.

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution

PubMed Central

Mendizabal, Isabel; Shi, Lei; Keller, Thomas E.; Konopka, Genevieve; Preuss, Todd M.; Hsieh, Tzung-Fu; Hu, Enzhi; Zhang, Zhe; Su, Bing; Yi, Soojin V.

2016-01-01

How do epigenetic modifications change across species and how do these modifications affect evolution? These are fundamental questions at the forefront of our evolutionary epigenomic understanding. Our previous work investigated human and chimpanzee brain methylomes, but it was limited by the lack of outgroup data which is critical for comparative (epi)genomic studies. Here, we compared whole genome DNA methylation maps from brains of humans, chimpanzees and also rhesus macaques (outgroup) to elucidate DNA methylation changes during human brain evolution. Moreover, we validated that our approach is highly robust by further examining 38 human-specific DMRs using targeted deep genomic and bisulfite sequencing in an independent panel of 37 individuals from five primate species. Our unbiased genome-scan identified human brain differentially methylated regions (DMRs), irrespective of their associations with annotated genes. Remarkably, over half of the newly identified DMRs locate in intergenic regions or gene bodies. Nevertheless, their regulatory potential is on par with those of promoter DMRs. An intriguing observation is that DMRs are enriched in active chromatin loops, suggesting human-specific evolutionary remodeling at a higher-order chromatin structure. These findings indicate that there is substantial reprogramming of epigenomic landscapes during human brain evolution involving noncoding regions. PMID:27563052

Linking brains and brawn: exercise and the evolution of human neurobiology.

PubMed

Raichlen, David A; Polk, John D

2013-01-07

The hunting and gathering lifestyle adopted by human ancestors around 2 Ma required a large increase in aerobic activity. High levels of physical activity altered the shape of the human body, enabling access to new food resources (e.g. animal protein) in a changing environment. Recent experimental work provides strong evidence that both acute bouts of exercise and long-term exercise training increase the size of brain components and improve cognitive performance in humans and other taxa. However, to date, researchers have not explored the possibility that the increases in aerobic capacity and physical activity that occurred during human evolution directly influenced the human brain. Here, we hypothesize that proximate mechanisms linking physical activity and neurobiology in living species may help to explain changes in brain size and cognitive function during human evolution. We review evidence that selection acting on endurance increased baseline neurotrophin and growth factor signalling (compounds responsible for both brain growth and for metabolic regulation during exercise) in some mammals, which in turn led to increased overall brain growth and development. This hypothesis suggests that a significant portion of human neurobiology evolved due to selection acting on features unrelated to cognitive performance.

Midsagittal Brain Variation among Non-Human Primates: Insights into Evolutionary Expansion of the Human Precuneus.

PubMed

Pereira-Pedro, Ana Sofia; Rilling, James K; Chen, Xu; Preuss, Todd M; Bruner, Emiliano

2017-01-01

The precuneus is a major element of the superior parietal lobule, positioned on the medial side of the hemisphere and reaching the dorsal surface of the brain. It is a crucial functional region for visuospatial integration, visual imagery, and body coordination. Previously, we argued that the precuneus expanded in recent human evolution, based on a combination of paleontological, comparative, and intraspecific evidence from fossil and modern human endocasts as well as from human and chimpanzee brains. The longitudinal proportions of this region are a major source of anatomical variation among adult humans and, being much larger in Homo sapiens, is the main characteristic differentiating human midsagittal brain morphology from that of our closest living primate relative, the chimpanzee. In the current shape analysis, we examine precuneus variation in non-human primates through landmark-based models, to evaluate the general pattern of variability in non-human primates, and to test whether precuneus proportions are influenced by allometric effects of brain size. Results show that precuneus proportions do not covary with brain size, and that the main difference between monkeys and apes involves a vertical expansion of the frontal and occipital regions in apes. Such differences might reflect differences in brain proportions or differences in cranial architecture. In this sample, precuneus variation is apparently not influenced by phylogenetic or allometric factors, but does vary consistently within species, at least in chimpanzees and macaques. This result further supports the hypothesis that precuneus expansion in modern humans is not merely a consequence of increasing brain size or of allometric scaling, but rather represents a species-specific morphological change in our lineage. © 2017 S. Karger AG, Basel.

Development of brain injury criteria (BrIC).

PubMed

Takhounts, Erik G; Craig, Matthew J; Moorhouse, Kevin; McFadden, Joe; Hasija, Vikas

2013-11-01

Rotational motion of the head as a mechanism for brain injury was proposed back in the 1940s. Since then a multitude of research studies by various institutions were conducted to confirm/reject this hypothesis. Most of the studies were conducted on animals and concluded that rotational kinematics experienced by the animal's head may cause axonal deformations large enough to induce their functional deficit. Other studies utilized physical and mathematical models of human and animal heads to derive brain injury criteria based on deformation/pressure histories computed from their models. This study differs from the previous research in the following ways: first, it uses two different detailed mathematical models of human head (SIMon and GHBMC), each validated against various human brain response datasets; then establishes physical (strain and stress based) injury criteria for various types of brain injury based on scaled animal injury data; and finally, uses Anthropomorphic Test Devices (ATDs) (Hybrid III 50th Male, Hybrid III 5th Female, THOR 50th Male, ES-2re, SID-IIs, WorldSID 50th Male, and WorldSID 5th Female) test data (NCAP, pendulum, and frontal offset tests) to establish a kinematically based brain injury criterion (BrIC) for all ATDs. Similar procedures were applied to college football data where thousands of head impacts were recorded using a six degrees of freedom (6 DOF) instrumented helmet system. Since animal injury data used in derivation of BrIC were predominantly for diffuse axonal injury (DAI) type, which is currently an AIS 4+ injury, cumulative strain damage measure (CSDM) and maximum principal strain (MPS) were used to derive risk curves for AIS 4+ anatomic brain injuries. The AIS 1+, 2+, 3+, and 5+ risk curves for CSDM and MPS were then computed using the ratios between corresponding risk curves for head injury criterion (HIC) at a 50% risk. The risk curves for BrIC were then obtained from CSDM and MPS risk curves using the linear relationship between CSDM - BrIC and MPS - BrIC respectively. AIS 3+, 4+ and 5+ field risk of anatomic brain injuries was also estimated using the National Automotive Sampling System - Crashworthiness Data System (NASS-CDS) database for crash conditions similar to the frontal NCAP and side impact conditions that the ATDs were tested in. This was done to assess the risk curve ratios derived from HIC risk curves. The results of the study indicated that: (1) the two available human head models - SIMon and GHBMC - were found to be highly correlated when CSDMs and max principal strains were compared; (2) BrIC correlates best to both - CSDM and MPS, and rotational velocity (not rotational acceleration) is the mechanism for brain injuries; and (3) the critical values for angular velocity are directionally dependent, and are independent of the ATD used for measuring them. The newly developed brain injury criterion is a complement to the existing HIC, which is based on translational accelerations. Together, the two criteria may be able to capture most brain injuries and skull fractures occurring in automotive or any other impact environment. One of the main limitations for any brain injury criterion, including BrIC, is the lack of human injury data to validate the criteria against, although some approximation for AIS 2+ injury is given based on the angular velocities calculated at 50% probability of concussion in college football players instrumented with 5 DOF helmet system. Despite the limitations, a new kinematic rotational brain injury criterion - BrIC - may offer a way to capture brain injuries in situations when using translational accelerations based HIC alone may not be sufficient.

Identification of the Transcriptional Targets of FOXP2, a Gene Linked to Speech and Language, in Developing Human Brain

PubMed Central

Spiteri, Elizabeth ; Konopka, Genevieve ; Coppola, Giovanni ; Bomar, Jamee ; Oldham, Michael ; Ou, Jing ; Vernes, Sonja C. ; Fisher, Simon E. ; Ren, Bing ; Geschwind, Daniel H. 

2007-01-01

Mutations in FOXP2, a member of the forkhead family of transcription factor genes, are the only known cause of developmental speech and language disorders in humans. To date, there are no known targets of human FOXP2 in the nervous system. The identification of FOXP2 targets in the developing human brain, therefore, provides a unique tool with which to explore the development of human language and speech. Here, we define FOXP2 targets in human basal ganglia (BG) and inferior frontal cortex (IFC) by use of chromatin immunoprecipitation followed by microarray analysis (ChIP-chip) and validate the functional regulation of targets in vitro. ChIP-chip identified 285 FOXP2 targets in fetal human brain; statistically significant overlap of targets in BG and IFC indicates a core set of 34 transcriptional targets of FOXP2. We identified targets specific to IFC or BG that were not observed in lung, suggesting important regional and tissue differences in FOXP2 activity. Many target genes are known to play critical roles in specific aspects of central nervous system patterning or development, such as neurite outgrowth, as well as plasticity. Subsets of the FOXP2 transcriptional targets are either under positive selection in humans or differentially expressed between human and chimpanzee brain. This is the first ChIP-chip study to use human brain tissue, making the FOXP2-target genes identified in these studies important to understanding the pathways regulating speech and language in the developing human brain. These data provide the first insight into the functional network of genes directly regulated by FOXP2 in human brain and by evolutionary comparisons, highlighting genes likely to be involved in the development of human higher-order cognitive processes. PMID:17999357

Development of a High Angular Resolution Diffusion Imaging Human Brain Template

PubMed Central

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-01-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. PMID:24440528

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Listeriolysin O mediates cytotoxicity against human brain microvascular

USDA-ARS?s Scientific Manuscript database

Penetration of the brain microvascular endothelial layer is one of the routes L. monocytogenes use to breach the blood-brain barrier. Because host factors in the blood severely limit direct invasion of human brain microvascular endothelial cells (HBMECs) by L. monocytogenes, alternative mechanisms m...

A New Antigen Retrieval Technique for Human Brain Tissue

PubMed Central

Byne, William; Haroutunian, Vahram; García-Villanueva, Mercedes; Rábano, Alberto; García-Amado, María; Prensa, Lucía; Giménez-Amaya, José Manuel

2008-01-01

Immunohistochemical staining of tissues is a powerful tool used to delineate the presence or absence of an antigen. During the last 30 years, antigen visualization in human brain tissue has been significantly limited by the masking effect of fixatives. In the present study, we have used a new method for antigen retrieval in formalin-fixed human brain tissue and examined the effectiveness of this protocol to reveal masked antigens in tissues with both short and long formalin fixation times. This new method, which is based on the use of citraconic acid, has not been previously utilized in brain tissue although it has been employed in various other tissues such as tonsil, ovary, skin, lymph node, stomach, breast, colon, lung and thymus. Thus, we reported here a novel method to carry out immunohistochemical studies in free-floating human brain sections. Since fixation of brain tissue specimens in formaldehyde is a commonly method used in brain banks, this new antigen retrieval method could facilitate immunohistochemical studies of brains with prolonged formalin fixation times. PMID:18852880

γ-Secretase binding sites in aged and Alzheimer’s disease human cerebrum: The choroid plexus as a putative origin of CSF Aβ

PubMed Central

Liu, Fei; Xue, Zhi-Qin; Deng, Si-Hao; Kun, Xiong; Luo, Xue-Gang; Patrylo, Peter R.; Rose, Gregory M.; Cai, Huaibin; Struble, Robert G.; Cai, Yan; Yan, Xiao-Xin

2013-01-01

Deposition of β-amyloid (Aβ) peptides, cleavage products of β-amyloid precursor protein (APP) by β-secretase-1 (BACE1) and γ-secretase, is a neuropathological hallmark of Alzheimer’s disease (AD). γ-Secretase inhibition is a therapeutical anti-Aβ approach, although less is clear about the change of the enzyme’s activity in AD brain. Cerebrospinal fluid (CSF) Aβ peptides are considered to derive from brain parenchyma, thus may serve as biomarkers for assessing cerebral amyloidosis and anti-Aβ efficacy. The present study compared active γ-secretase binding sites with Aβ deposition in aged and AD human cerebrum, and explored a possibility of Aβ production and secretion by the choroid plexus (CP). Specific binding density of [3H]-L-685,458, a radiolabeled high affinity γ-secretase inhibitor, in the temporal neocortex and hippocampal formation was similar for AD and control cases with comparable ages and postmortem delays. The CP in postmortem samples exhibited exceptionally high [3H]-L-685,458 binding density, with the estimated maximal binding sites (Bmax) reduced in the AD relative to control groups. Surgically resected human CP exhibited APP, BACE1 and presenilin-1 immunoreactivity, and β-site APP cleavage enzymatic activity. In primary culture, human CP cells also expressed these amyloidogenic proteins but released Aβ40 and Aβ42 into the medium. These results suggest that γ-secretase activity appears not altered in the cerebrum in AD related to aged control, nor correlated with regional amyloid plaque pathology. The choroid plexus appears to represent a novel non-neuronal source in the brain that may contribute Aβ into cerebrospinal fluid, probably at reduced levels in AD. PMID:23432732

Limbic grey matter changes in early Parkinson's disease.

PubMed

Li, Xingfeng; Xing, Yue; Schwarz, Stefan T; Auer, Dorothee P

2017-05-02

The purpose of this study was to investigate local and network-related changes of limbic grey matter in early Parkinson's disease (PD) and their inter-relation with non-motor symptom severity. We applied voxel-based morphometric methods in 538 T1 MRI images retrieved from the Parkinson's Progression Markers Initiative website. Grey matter densities and cross-sectional estimates of age-related grey matter change were compared between subjects with early PD (n = 366) and age-matched healthy controls (n = 172) within a regression model, and associations of grey matter density with symptoms were investigated. Structural brain networks were obtained using covariance analysis seeded in regions showing grey matter abnormalities in PD subject group. Patients displayed focally reduced grey matter density in the right amygdala, which was present from the earliest stages of the disease without further advance in mild-moderate disease stages. Right amygdala grey matter density showed negative correlation with autonomic dysfunction and positive with cognitive performance in patients, but no significant interrelations were found with anxiety scores. Patients with PD also demonstrated right amygdala structural disconnection with less structural connectivity of the right amygdala with the cerebellum and thalamus but increased covariance with bilateral temporal cortices compared with controls. Age-related grey matter change was also increased in PD preferentially in the limbic system. In conclusion, detailed brain morphometry in a large group of early PD highlights predominant limbic grey matter deficits with stronger age associations compared with controls and associated altered structural connectivity pattern. This provides in vivo evidence for early limbic grey matter pathology and structural network changes that may reflect extranigral disease spread in PD. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Toward reliable characterization of functional homogeneity in the human brain: preprocessing, scan duration, imaging resolution and computational space.

PubMed

Zuo, Xi-Nian; Xu, Ting; Jiang, Lili; Yang, Zhi; Cao, Xiao-Yan; He, Yong; Zang, Yu-Feng; Castellanos, F Xavier; Milham, Michael P

2013-01-15

While researchers have extensively characterized functional connectivity between brain regions, the characterization of functional homogeneity within a region of the brain connectome is in early stages of development. Several functional homogeneity measures were proposed previously, among which regional homogeneity (ReHo) was most widely used as a measure to characterize functional homogeneity of resting state fMRI (R-fMRI) signals within a small region (Zang et al., 2004). Despite a burgeoning literature on ReHo in the field of neuroimaging brain disorders, its test-retest (TRT) reliability remains unestablished. Using two sets of public R-fMRI TRT data, we systematically evaluated the ReHo's TRT reliability and further investigated the various factors influencing its reliability and found: 1) nuisance (head motion, white matter, and cerebrospinal fluid) correction of R-fMRI time series can significantly improve the TRT reliability of ReHo while additional removal of global brain signal reduces its reliability, 2) spatial smoothing of R-fMRI time series artificially enhances ReHo intensity and influences its reliability, 3) surface-based R-fMRI computation largely improves the TRT reliability of ReHo, 4) a scan duration of 5 min can achieve reliable estimates of ReHo, and 5) fast sampling rates of R-fMRI dramatically increase the reliability of ReHo. Inspired by these findings and seeking a highly reliable approach to exploratory analysis of the human functional connectome, we established an R-fMRI pipeline to conduct ReHo computations in both 3-dimensions (volume) and 2-dimensions (surface). Copyright © 2012 Elsevier Inc. All rights reserved.

Noninvasive quantification of human brain antioxidant concentrations after an intravenous bolus of vitamin C

USDA-ARS?s Scientific Manuscript database

Background: Until now, antioxidant based initiatives for preventing dementia have lacked a means to detect deficiency or measure pharmacologic effect in the human brain in situ. Objective: Our objective was to apply a novel method to measure key human brain antioxidant concentrations throughout the ...

Relationship between concentrations of lutein and StARD3 among pediatric and geriatric human brain tissue

USDA-ARS?s Scientific Manuscript database

Lutein, a dietary carotenoid, selectively accumulates in human retina and brain. While many epidemiological studies show evidence of a relationship between lutein status and cognitive health, lutein's selective uptake in human brain tissue and its potential function in early neural development and c...

Immunohistochemical Demonstration of Specific Antigens in the Human Brain Fixed in Zinc-ethanol-Formaldehyde

PubMed Central

Korzhevskii, D.E.; Sukhorukova, E.G.; Kirik, O.V.; Grigorev, I.P.

2015-01-01

Tissue fixation is critical for immunohistochemistry. Recently, we developed a zinc-ethanol-formalin fixative (ZEF), and the present study was aimed to assess the applicability of the ZEF for the human brain histology and immunohistochemistry and to evaluate the detectability of different antigens in the human brain fixed with ZEF. In total, 11 antigens were tested, including NeuN, neuron-specific enolase, GFAP, Iba-1, calbindin, calretinin, choline acetyltransferase, glutamic acid decarboxylase (GAD65), tyrosine hydroxylase, synaptophysin, and α-tubulin. The obtained data show that: i) the ZEF has potential for use in general histological practice, where detailed characterization of human brain morphology is needed; ii) the antigens tested are well-preserved in the human brain specimens fixed in the ZEF. PMID:26428887

Convergent transcriptional specializations in the brains of humans and song-learning birds

PubMed Central

Pfenning, Andreas R.; Hara, Erina; Whitney, Osceola; Rivas, Miriam V.; Wang, Rui; Roulhac, Petra L.; Howard, Jason T.; Wirthlin, Morgan; Lovell, Peter V.; Ganapathy, Ganeshkumar; Mouncastle, Jacquelyn; Moseley, M. Arthur; Thompson, J. Will; Soderblom, Erik J.; Iriki, Atsushi; Kato, Masaki; Gilbert, M. Thomas P.; Zhang, Guojie; Bakken, Trygve; Bongaarts, Angie; Bernard, Amy; Lein, Ed; Mello, Claudio V.; Hartemink, Alexander J.; Jarvis, Erich D.

2015-01-01

Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes. PMID:25504733

MR-assisted PET Motion Correction for eurological Studies in an Integrated MR-PET Scanner

PubMed Central

Catana, Ciprian; Benner, Thomas; van der Kouwe, Andre; Byars, Larry; Hamm, Michael; Chonde, Daniel B.; Michel, Christian J.; El Fakhri, Georges; Schmand, Matthias; Sorensen, A. Gregory

2011-01-01

Head motion is difficult to avoid in long PET studies, degrading the image quality and offsetting the benefit of using a high-resolution scanner. As a potential solution in an integrated MR-PET scanner, the simultaneously acquired MR data can be used for motion tracking. In this work, a novel data processing and rigid-body motion correction (MC) algorithm for the MR-compatible BrainPET prototype scanner is described and proof-of-principle phantom and human studies are presented. Methods To account for motion, the PET prompts and randoms coincidences as well as the sensitivity data are processed in the line or response (LOR) space according to the MR-derived motion estimates. After sinogram space rebinning, the corrected data are summed and the motion corrected PET volume is reconstructed from these sinograms and the attenuation and scatter sinograms in the reference position. The accuracy of the MC algorithm was first tested using a Hoffman phantom. Next, human volunteer studies were performed and motion estimates were obtained using two high temporal resolution MR-based motion tracking techniques. Results After accounting for the physical mismatch between the two scanners, perfectly co-registered MR and PET volumes are reproducibly obtained. The MR output gates inserted in to the PET list-mode allow the temporal correlation of the two data sets within 0.2 s. The Hoffman phantom volume reconstructed processing the PET data in the LOR space was similar to the one obtained processing the data using the standard methods and applying the MC in the image space, demonstrating the quantitative accuracy of the novel MC algorithm. In human volunteer studies, motion estimates were obtained from echo planar imaging and cloverleaf navigator sequences every 3 seconds and 20 ms, respectively. Substantially improved PET images with excellent delineation of specific brain structures were obtained after applying the MC using these MR-based estimates. Conclusion A novel MR-based MC algorithm was developed for the integrated MR-PET scanner. High temporal resolution MR-derived motion estimates (obtained while simultaneously acquiring anatomical or functional MR data) can be used for PET MC. An MR-based MC has the potential to improve PET as a quantitative method, increasing its reliability and reproducibility which could benefit a large number of neurological applications. PMID:21189415

A simple physiologically based pharmacokinetic model evaluating the effect of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans

PubMed Central

Saylor, Kyle; Zhang, Chenming

2017-01-01

Physiologically based pharmacokinetic (PBPK) modeling was applied to investigate the effects of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans. Successful construction of both rat and human models was achieved by fitting model outputs to published nicotine concentration time course data in the blood and in the brain. Key parameters presumed to have the most effect on the ability of these antibodies to prevent nicotine from entering the brain were selected for investigation using the human model. These parameters, which included antibody affinity for nicotine, antibody cross-reactivity with cotinine, and antibody concentration, were broken down into different, clinically-derived in silico treatment levels and fed into the human PBPK model. Model predictions suggested that all three parameters, in addition to smoking status, have a sizable impact on anti-nicotine antibodies’ ability to prevent nicotine from entering the brain and that the antibodies elicited by current human vaccines do not have sufficient binding characteristics to reduce brain nicotine concentrations. If the antibody binding characteristics achieved in animal studies can similarly be achieved in human studies, however, nicotine vaccine efficacy in terms of brain nicotine concentration reduction is predicted to meet threshold values for alleviating nicotine dependence. PMID:27473014

Beyond sex differences: new approaches for thinking about variation in brain structure and function.

PubMed

Joel, Daphna; Fausto-Sterling, Anne

2016-02-19

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. © 2016 The Author(s).

Low-resolution mapping of the effective attenuation coefficient of the human head: a multidistance approach applied to high-density optical recordings

PubMed Central

Chiarelli, Antonio M.; Maclin, Edward L.; Low, Kathy A.; Fantini, Sergio; Fabiani, Monica; Gratton, Gabriele

2017-01-01

Abstract. Near infrared (NIR) light has been widely used for measuring changes in hemoglobin concentration in the human brain (functional NIR spectroscopy, fNIRS). fNIRS is based on the differential measurement and estimation of absorption perturbations, which, in turn, are based on correctly estimating the absolute parameters of light propagation. To do so, it is essential to accurately characterize the baseline optical properties of tissue (absorption and reduced scattering coefficients). However, because of the diffusive properties of the medium, separate determination of absorption and scattering across the head is challenging. The effective attenuation coefficient (EAC), which is proportional to the geometric mean of absorption and reduced scattering coefficients, can be estimated in a simpler fashion by multidistance light decay measurements. EAC mapping could be of interest for the scientific community because of its absolute information content, and because light propagation is governed by the EAC for source–detector distances exceeding 1 cm, which sense depths extending beyond the scalp and skull layers. Here, we report an EAC mapping procedure that can be applied to standard fNIRS recordings, yielding topographic maps with 2- to 3-cm resolution. Application to human data indicates the importance of venous sinuses in determining regional EAC variations, a factor often overlooked. PMID:28466026

Low-resolution mapping of the effective attenuation coefficient of the human head: a multidistance approach applied to high-density optical recordings.

PubMed

Chiarelli, Antonio M; Maclin, Edward L; Low, Kathy A; Fantini, Sergio; Fabiani, Monica; Gratton, Gabriele

2017-04-01

Near infrared (NIR) light has been widely used for measuring changes in hemoglobin concentration in the human brain (functional NIR spectroscopy, fNIRS). fNIRS is based on the differential measurement and estimation of absorption perturbations, which, in turn, are based on correctly estimating the absolute parameters of light propagation. To do so, it is essential to accurately characterize the baseline optical properties of tissue (absorption and reduced scattering coefficients). However, because of the diffusive properties of the medium, separate determination of absorption and scattering across the head is challenging. The effective attenuation coefficient (EAC), which is proportional to the geometric mean of absorption and reduced scattering coefficients, can be estimated in a simpler fashion by multidistance light decay measurements. EAC mapping could be of interest for the scientific community because of its absolute information content, and because light propagation is governed by the EAC for source-detector distances exceeding 1 cm, which sense depths extending beyond the scalp and skull layers. Here, we report an EAC mapping procedure that can be applied to standard fNIRS recordings, yielding topographic maps with 2- to 3-cm resolution. Application to human data indicates the importance of venous sinuses in determining regional EAC variations, a factor often overlooked.

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

A super-resolution ultrasound method for brain vascular mapping

PubMed Central

O'Reilly, Meaghan A.; Hynynen, Kullervo

2013-01-01

Purpose: High-resolution vascular imaging has not been achieved in the brain due to limitations of current clinical imaging modalities. The authors present a method for transcranial ultrasound imaging of single micrometer-size bubbles within a tube phantom. Methods: Emissions from single bubbles within a tube phantom were mapped through an ex vivo human skull using a sparse hemispherical receiver array and a passive beamforming algorithm. Noninvasive phase and amplitude correction techniques were applied to compensate for the aberrating effects of the skull bone. The positions of the individual bubbles were estimated beyond the diffraction limit of ultrasound to produce a super-resolution image of the tube phantom, which was compared with microcomputed tomography (micro-CT). Results: The resulting super-resolution ultrasound image is comparable to results obtained via the micro-CT for small tissue specimen imaging. Conclusions: This method provides superior resolution to deep-tissue contrast ultrasound and has the potential to be extended to provide complete vascular network imaging in the brain. PMID:24320408

Studying frequency processing of the brain to enhance long-term memory and develop a human brain protocol.

PubMed

Friedrich, Wernher; Du, Shengzhi; Balt, Karlien

2015-01-01

The temporal lobe in conjunction with the hippocampus is responsible for memory processing. The gamma wave is involved with this process. To develop a human brain protocol, a better understanding of the relationship between gamma and long-term memory is vital. A more comprehensive understanding of the human brain and specific analogue waves it uses will support the development of a human brain protocol. Fifty-eight participants aged between 6 and 60 years participated in long-term memory experiments. It is envisaged that the brain could be stimulated through binaural beats (sound frequency) at 40 Hz (gamma) to enhance long-term memory capacity. EEG recordings have been transformed to sound and then to an information standard, namely ASCII. Statistical analysis showed a proportional relationship between long-term memory and gamma activity. Results from EEG recordings indicate a pattern. The pattern was obtained through the de-codification of an EEG recording to sound and then to ASCII. Stimulation of gamma should enhance long term memory capacity. More research is required to unlock the human brains' protocol key. This key will enable the processing of information directly to and from human memory via gamma, the hippocampus and the temporal lobe.

Human-specific features of spatial gene expression and regulation in eight brain regions.

PubMed

Xu, Chuan; Li, Qian; Efimova, Olga; He, Liu; Tatsumoto, Shoji; Stepanova, Vita; Oishi, Takao; Udono, Toshifumi; Yamaguchi, Katsushi; Shigenobu, Shuji; Kakita, Akiyoshi; Nawa, Hiroyuki; Khaitovich, Philipp; Go, Yasuhiro

2018-06-13

Molecular maps of the human brain alone do not inform us of the features unique to humans. Yet, the identification of these features is important for understanding both the evolution and nature of human cognition. Here, we approached this question by analyzing gene expression and H3K27ac chromatin modification data collected in eight brain regions of humans, chimpanzees, gorillas, a gibbon and macaques. An analysis of spatial transcriptome trajectories across eight brain regions in four primate species revealed 1,851 genes showing human-specific transcriptome differences in one or multiple brain regions, in contrast to 240 chimpanzee-specific ones. More than half of these human-specific differences represented elevated expression of genes enriched in neuronal and astrocytic markers in the human hippocampus, while the rest were enriched in microglial markers and displayed human-specific expression in several frontal cortical regions and the cerebellum. An analysis of the predicted regulatory interactions driving these differences revealed the role of transcription factors in species-specific transcriptome changes, while epigenetic modifications were linked to spatial expression differences conserved across species. Published by Cold Spring Harbor Laboratory Press.

A High-Resolution In Vivo Atlas of the Human Brain's Serotonin System.

PubMed

Beliveau, Vincent; Ganz, Melanie; Feng, Ling; Ozenne, Brice; Højgaard, Liselotte; Fisher, Patrick M; Svarer, Claus; Greve, Douglas N; Knudsen, Gitte M

2017-01-04

The serotonin (5-hydroxytryptamine, 5-HT) system modulates many important brain functions and is critically involved in many neuropsychiatric disorders. Here, we present a high-resolution, multidimensional, in vivo atlas of four of the human brain's 5-HT receptors (5-HT 1A , 5-HT 1B , 5-HT 2A , and 5-HT 4 ) and the 5-HT transporter (5-HTT). The atlas is created from molecular and structural high-resolution neuroimaging data consisting of positron emission tomography (PET) and magnetic resonance imaging (MRI) scans acquired in a total of 210 healthy individuals. Comparison of the regional PET binding measures with postmortem human brain autoradiography outcomes showed a high correlation for the five 5-HT targets and this enabled us to transform the atlas to represent protein densities (in picomoles per milliliter). We also assessed the regional association between protein concentration and mRNA expression in the human brain by comparing the 5-HT density across the atlas with data from the Allen Human Brain atlas and identified receptor- and transporter-specific associations that show the regional relation between the two measures. Together, these data provide unparalleled insight into the serotonin system of the human brain. We present a high-resolution positron emission tomography (PET)- and magnetic resonance imaging-based human brain atlas of important serotonin receptors and the transporter. The regional PET-derived binding measures correlate strongly with the corresponding autoradiography protein levels. The strong correlation enables the transformation of the PET-derived human brain atlas into a protein density map of the serotonin (5-hydroxytryptamine, 5-HT) system. Next, we compared the regional receptor/transporter protein densities with mRNA levels and uncovered unique associations between protein expression and density at high detail. This new in vivo neuroimaging atlas of the 5-HT system not only provides insight in the human brain's regional protein synthesis, transport, and density, but also represents a valuable source of information for the neuroscience community as a comparative instrument to assess brain disorders. Copyright © 2017 the authors 0270-6474/17/370120-09$15.00/0.

A role for human brain pericytes in neuroinflammation

PubMed Central

2014-01-01

Background Brain inflammation plays a key role in neurological disease. Although much research has been conducted investigating inflammatory events in animal models, potential differences in human brain versus rodent models makes it imperative that we also study these phenomena in human cells and tissue. Methods Primary human brain cell cultures were generated from biopsy tissue of patients undergoing surgery for drug-resistant epilepsy. Cells were treated with pro-inflammatory compounds IFNγ, TNFα, IL-1β, and LPS, and chemokines IP-10 and MCP-1 were measured by immunocytochemistry, western blot, and qRT-PCR. Microarray analysis was also performed on late passage cultures treated with vehicle or IFNγ and IL-1β. Results Early passage human brain cell cultures were a mixture of microglia, astrocytes, fibroblasts and pericytes. Later passage cultures contained proliferating fibroblasts and pericytes only. Under basal culture conditions all cell types showed cytoplasmic NFκB indicating that they were in a non-activated state. Expression of IP-10 and MCP-1 were significantly increased in response to pro-inflammatory stimuli. The two chemokines were expressed in mixed cultures as well as cultures of fibroblasts and pericytes only. The expression of IP-10 and MCP-1 were regulated at the mRNA and protein level, and both were secreted into cell culture media. NFκB nuclear translocation was also detected in response to pro-inflammatory cues (except IFNγ) in all cell types. Microarray analysis of brain pericytes also revealed widespread changes in gene expression in response to the combination of IFNγ and IL-1β treatment including interleukins, chemokines, cellular adhesion molecules and much more. Conclusions Adult human brain cells are sensitive to cytokine challenge. As expected ‘classical’ brain immune cells, such as microglia and astrocytes, responded to cytokine challenge but of even more interest, brain pericytes also responded to such challenge with a rich repertoire of gene expression. Immune activation of brain pericytes may play an important role in communicating inflammatory signals to and within the brain interior and may also be involved in blood brain barrier (BBB) disruption . Targeting brain pericytes, as well as microglia and astrocytes, may provide novel opportunities for reducing brain inflammation and maintaining BBB function and brain homeostasis in human brain disease. PMID:24920309

A case for human systems neuroscience.

PubMed

Gardner, J L

2015-06-18

Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. Our approach has been to use a combination of psychophysics in which we can use human behavioral flexibility to make quantitative measurements of behavior and link those through computational models to measurements of cortical activity through magnetic resonance imaging. In particular, we have tested various computational hypotheses about what neural mechanisms could account for behavioral enhancement with spatial attention (Pestilli et al., 2011). Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Treatment and prognosis of breast cancer patients with brain metastases according to intrinsic subtype.

PubMed

Kuba, Sayaka; Ishida, Mayumi; Nakamura, Yoshiaki; Yamanouchi, Kosho; Minami, Shigeki; Taguchi, Kenichi; Eguchi, Susumu; Ohno, Shinji

2014-11-01

How breast cancer subtypes should affect treatment decisions for breast cancer patients with brain metastases is unclear. We analyzed local brain metastases treatments and their outcomes according to subtype in patients with breast cancer and brain metastases. We reviewed records and database information for women treated at the National Kyushu Cancer Center between 2001 and 2010. Patients were divided into three breast cancer subtype groups: Luminal (estrogen receptor positive and/or progesterone receptor positive, but human epidermal growth factor receptor 2 negative); human epidermal growth factor receptor 2 positive and triple negative (estrogen receptor negative, progesterone receptor negative and human epidermal growth factor receptor 2 negative). Of 524 advanced breast cancer patients, we reviewed 65 (12%) with brain metastases and records showing estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status, as well as outcome data; there were 26 (40%) Luminal, 26 (40%) had human epidermal growth factor receptor 2 and 13 (20%) had triple negative subtypes. There was no statistical difference in the number of brain metastases among subtypes; however, rates of stereotactic radiosurgery or surgery for brain metastases differed significantly by subtype (human epidermal growth factor receptor 2: 81%, Luminal: 42% and triple negative: 47%; P = 0.03). Patients having the human epidermal growth factor receptor 2 subtype, a performance status of ≤1 and ≤4 brain metastases, who underwent systemic therapy after brain metastases and underwent stereotactic radiosurgery or surgery, were predicted to have longer overall survival after brain metastases. Multivariate analysis demonstrated that not having systemic therapy and not having the human epidermal growth factor receptor 2 subtype were independent factors associated with an increased risk of death (hazard ratio 2.4, 95% confidence interval 1.01-5.6; P = 0.05 and hazard ratio 2.9, 95% confidence interval 1.5-5.8; P = 0.003, respectively). Our study showed that local brain treatments and prognosis differed by subtype in breast cancer patients with brain metastases. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Carbohydrates as a cerebral metabolic fuel.

PubMed

Evans, M; Amiel, S A

1998-03-01

The human brain is an extremely active metabolic organ with little endogenous stores of energy. It is thus dependent on circulating glucose to fuel metabolism and support cognitive functioning. However there is growing evidence that the human brain is able to utilise other non-glucose fuels during times of glucose lack. We review the evidence for the potential of the human brain to use the alternate fuels lactate and beta-hydroxybutyrate, and some recent studies examining the ability of regions of brain to use non-glucose lipid fuels. The human brain does not seem to have the ability to use the gluconeogenic precursor alanine to any significant degree. Regionality within the brain can be examined in vivo by the use of positron emission tomography, which offers the exciting prospect of studying human brain metabolism in vivo using a simple and non-interventional technique. Increased understanding of the brain's metabolism, the way in which hypoglycaemia is recognised and the manner in which this can be altered in the syndrome of hypoglycaemia unawareness and deficient counterregulation will help develop further strategies to prevent the clinical problems associated with hypoglycaemia in insulin-dependent diabetic adults and children.

ABC transporters and cytochromes P450 in the human central nervous system: influence on brain pharmacokinetics and contribution to neurodegenerative disorders.

PubMed

Dutheil, Fabien; Jacob, Aude; Dauchy, Sandrine; Beaune, Philippe; Scherrmann, Jean-Michel; Declèves, Xavier; Loriot, Marie-Anne

2010-10-01

The identification of xenobiotic metabolizing enzymes (i.e., CYP) and transporters (i.e., ABC transporters) (XMET) in the human brain, including the BBB, raises the question whether these transporters and enzymes have specific functions in brain physiology, neuropharmacology and toxicology. Relevant literature was identified using PubMed search articles published up to March 2010. Search terms included 'ABC transporters and P450 or CYP', 'drug metabolism, effect and toxicity' and 'neurodegenerative disease (Alzheimer and Parkinson diseases)' restricted to the field of 'brain or human brain'. This review aims to provide a better understanding of XMET functions in the human brain and show their pharmacological importance for improving drug delivery and efficacy and also for managing their side effects. Finally, the impact of brain XMET activity during neurodegenerative processes is discussed, giving an opportunity to identify new markers of human brain diseases. During the last 2 decades, much evidence concerning the specific distribution patterns of XMET, their induction by xenobiotics and endobiotics and their genetic variations have made cerebral ABC transporters and CYP enzymes key elements in the way individual patients respond to centrally acting drugs.

[Is abortion murder?].

PubMed

Werning, C

1995-09-01

Discussions about Paragraph 218 of the German federal abortion law have spawned antithetical opinions: on the one hand, the full right of the mother or parents to decide about the incipient human life; and on the other hand, under the dogma of abortion is murder, providing abortion is rejected even when the pregnancy is the result of rape and it is unwanted. Two questions are closely related to this issue: 1) what makes human beings human and 2) when does human life begin. From a medical point of view the function of the brain is fundamentally linked to being human. The brain controls almost all functions of the body and determines its psychological makeup, such as intellect and, in a theological sense, the soul. Without the brain such functioning is not possible, since brain death means the death of human life. Children born with anencephaly and microencephaly can never live a human life. At the end of life various diseases (stroke, Alzheimer disease) can severely damage the brain. In these cases normal living is also no longer possible. Yet ethically it is untenable to actively kill these human beings. But when one considers that life-threatening diseases can require life-support intervention, then often the pragmatic intervention is not far removed from active euthanasia. The other question related to the beginning of human life is even more difficult to answer. It is the fertilization of the egg cells; but a conglomeration of cells in the early phase of pregnancy can hardly be characterized as a human person. The human identity, personality, and worth is associated with the functioning of the brain, so only when the brain is fully developed can there be any talk about an unborn human being.

Estimating and Testing the Sources of Evoked Potentials in the Brain.

ERIC Educational Resources Information Center

Huizenga, Hilde M.; Molenaar, Peter C. M.

1994-01-01

The source of an event-related brain potential (ERP) is estimated from multivariate measures of ERP on the head under several mathematical and physical constraints on the parameters of the source model. Statistical aspects of estimation are discussed, and new tests are proposed. (SLD)

Evidence of native α-synuclein conformers in the human brain.

PubMed

Gould, Neal; Mor, Danielle E; Lightfoot, Richard; Malkus, Kristen; Giasson, Benoit; Ischiropoulos, Harry

2014-03-14

α-Synuclein aggregation is central to the pathogenesis of several brain disorders. However, the native conformations and functions of this protein in the human brain are not precisely known. The native state of α-synuclein was probed by gel filtration coupled with native gradient gel separation, an array of antibodies with non-overlapping epitopes, and mass spectrometry. The existence of metastable conformers and stable monomer was revealed in the human brain.

Magnetic resonance elastography of the brain: A comparison between pigs and humans.

PubMed

Weickenmeier, Johannes; Kurt, Mehmet; Ozkaya, Efe; Wintermark, Max; Pauly, Kim Butts; Kuhl, Ellen

2018-01-01

Magnetic resonance elastography holds promise as a non-invasive, easy-to-use, in vivo biomarker for neurodegenerative diseases. Throughout the past decade, pigs have gained increased popularity as large animal models for human neurodegeneration. However, the volume of a pig brain is an order of magnitude smaller than the human brain, its skull is 40% thicker, and its head is about twice as big. This raises the question to which extent established vibration devices, actuation frequencies, and analysis tools for humans translate to large animal studies in pigs. Here we explored the feasibility of using human brain magnetic resonance elastography to characterize the dynamic properties of the porcine brain. In contrast to humans, where vibration devices induce an anterior-posterior displacement recorded in transverse sections, the porcine anatomy requires a dorsal-ventral displacement recorded in coronal sections. Within these settings, we applied a wide range of actuation frequencies, from 40Hz to 90Hz, and recorded the storage and loss moduli for human and porcine brains. Strikingly, we found that optimal actuation frequencies for humans translate one-to-one to pigs and reliably generate shear waves for elastographic post-processing. In a direct comparison, human and porcine storage and loss moduli followed similar trends and increased with increasing frequency. When translating these frequency-dependent storage and loss moduli into the frequency-independent stiffnesses and viscosities of a standard linear solid model, we found human values of μ 1 =1.3kPa, μ 2 =2.1kPa, and η=0.025kPas and porcine values of μ 1 =2.0kPa, μ 2 =4.9kPa, and η=0.046kPas. These results suggest that living human brain is softer and less viscous than dead porcine brain. Our study compares, for the first time, magnetic resonance elastography in human and porcine brains, and paves the way towards systematic interspecies comparison studies and ex vivo validation of magnetic resonance elastography as a whole. Copyright © 2017 Elsevier Ltd. All rights reserved.

High-Speed and Scalable Whole-Brain Imaging in Rodents and Primates.

PubMed

Seiriki, Kaoru; Kasai, Atsushi; Hashimoto, Takeshi; Schulze, Wiebke; Niu, Misaki; Yamaguchi, Shun; Nakazawa, Takanobu; Inoue, Ken-Ichi; Uezono, Shiori; Takada, Masahiko; Naka, Yuichiro; Igarashi, Hisato; Tanuma, Masato; Waschek, James A; Ago, Yukio; Tanaka, Kenji F; Hayata-Takano, Atsuko; Nagayasu, Kazuki; Shintani, Norihito; Hashimoto, Ryota; Kunii, Yasuto; Hino, Mizuki; Matsumoto, Junya; Yabe, Hirooki; Nagai, Takeharu; Fujita, Katsumasa; Matsuda, Toshio; Takuma, Kazuhiro; Baba, Akemichi; Hashimoto, Hitoshi

2017-06-21

Subcellular resolution imaging of the whole brain and subsequent image analysis are prerequisites for understanding anatomical and functional brain networks. Here, we have developed a very high-speed serial-sectioning imaging system named FAST (block-face serial microscopy tomography), which acquires high-resolution images of a whole mouse brain in a speed range comparable to that of light-sheet fluorescence microscopy. FAST enables complete visualization of the brain at a resolution sufficient to resolve all cells and their subcellular structures. FAST renders unbiased quantitative group comparisons of normal and disease model brain cells for the whole brain at a high spatial resolution. Furthermore, FAST is highly scalable to non-human primate brains and human postmortem brain tissues, and can visualize neuronal projections in a whole adult marmoset brain. Thus, FAST provides new opportunities for global approaches that will allow for a better understanding of brain systems in multiple animal models and in human diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

Responses of brain and non-brain endothelial cells to meningitis-causing Escherichia coli K1.

PubMed

Paul-Satyaseela, Maneesh; Xie, Yi; Di Cello, Francescopaolo; Kim, Kwang Sik

2006-03-31

Bacterial interaction with specific host tissue may contribute to its propensity to cause an infection in a particular site. In this study, we examined whether meningitis-causing Escherichia coli K1 interaction with human brain microvascular endothelial cells, which constitute the blood-brain barrier, differed from its interaction with non-brain endothelial cells derived from skin and umbilical cord. We showed that E. coli K1 association was significantly greater with human brain microvascular endothelial cells than with non-brain endothelial cells. In addition, human brain microvascular endothelial cells maintained their morphology and intercellular junctional resistance in response to E. coli K1. In contrast, non-brain endothelial cells exhibited decreased transendothelial electrical resistance and detachment from the matrix upon exposure to E. coli K1. These different responses of brain and non-brain endothelial cells to E. coli K1 may form the basis of E. coli K1's propensity to cause meningitis.

Dynamic Granger-Geweke causality modeling with application to interictal spike propagation

PubMed Central

Lin, Fa-Hsuan; Hara, Keiko; Solo, Victor; Vangel, Mark; Belliveau, John W.; Stufflebeam, Steven M.; Hamalainen, Matti S.

2010-01-01

A persistent problem in developing plausible neurophysiological models of perception, cognition, and action is the difficulty of characterizing the interactions between different neural systems. Previous studies have approached this problem by estimating causal influences across brain areas activated during cognitive processing using Structural Equation Modeling and, more recently, with Granger-Geweke causality. While SEM is complicated by the need for a priori directional connectivity information, the temporal resolution of dynamic Granger-Geweke estimates is limited because the underlying autoregressive (AR) models assume stationarity over the period of analysis. We have developed a novel optimal method for obtaining data-driven directional causality estimates with high temporal resolution in both time and frequency domains. This is achieved by simultaneously optimizing the length of the analysis window and the chosen AR model order using the SURE criterion. Dynamic Granger-Geweke causality in time and frequency domains is subsequently calculated within a moving analysis window. We tested our algorithm by calculating the Granger-Geweke causality of epileptic spike propagation from the right frontal lobe to the left frontal lobe. The results quantitatively suggested the epileptic activity at the left frontal lobe was propagated from the right frontal lobe, in agreement with the clinical diagnosis. Our novel computational tool can be used to help elucidate complex directional interactions in the human brain. PMID:19378280

At least eighty percent of brain grey matter is modifiable by physical activity: A review study.

PubMed

Batouli, Seyed Amir Hossein; Saba, Valiallah

2017-08-14

The human brain is plastic, i.e. it can show structural changes in response to the altered environment. Physical activity (PA) is a lifestyle factor which has significant associations with the structural and functional aspects of the human brain, as well as with the mind and body health. Many studies have reported regional/global brain volume increments due to exercising; however, a map which shows the overall extent of the influences of PAs on brain structure is not available. In this study, we collected all the reports on brain structural alterations in association with PA in healthy humans, and next, a brain map of the extent of these effects is provided. The results of this study showed that a large network of brain areas, equal to 82% of the total grey matter volume, were associated with PA. This finding has important implications in utilizing PA as a mediator factor for educational purposes in children, rehabilitation applications in patients, improving the cognitive abilities of the human brain such as in learning or memory, and preventing age-related brain deteriorations. Copyright © 2017 Elsevier B.V. All rights reserved.

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Human primary mixed brain cultures: preparation, differentiation, characterization and application to neuroscience research.

PubMed

Ray, Balmiki; Chopra, Nipun; Long, Justin M; Lahiri, Debomoy K

2014-09-16

Culturing primary cortical neurons is an essential neuroscience technique. However, most cultures are derived from rodent brains and standard protocols for human brain cultures are sparse. Herein, we describe preparation, maintenance and major characteristics of a primary human mixed brain culture, including neurons, obtained from legally aborted fetal brain tissue. This approach employs standard materials and techniques used in the preparation of rodent neuron cultures, with critical modifications. This culture has distinct differences from rodent cultures. Specifically, a significant numbers of cells in the human culture are derived from progenitor cells, and the yield and survival of the cells grossly depend on the presence of bFGF. In the presence of bFGF, this culture can be maintained for an extended period. Abundant productions of amyloid-β, tau and proteins make this a powerful model for Alzheimer's research. The culture also produces glia and different sub-types of neurons. We provide a well-characterized methodology for human mixed brain cultures useful to test therapeutic agents under various conditions, and to carry forward mechanistic and translational studies for several brain disorders.

A Hybrid CPU-GPU Accelerated Framework for Fast Mapping of High-Resolution Human Brain Connectome

PubMed Central

Ren, Ling; Xu, Mo; Xie, Teng; Gong, Gaolang; Xu, Ningyi; Yang, Huazhong; He, Yong

2013-01-01

Recently, a combination of non-invasive neuroimaging techniques and graph theoretical approaches has provided a unique opportunity for understanding the patterns of the structural and functional connectivity of the human brain (referred to as the human brain connectome). Currently, there is a very large amount of brain imaging data that have been collected, and there are very high requirements for the computational capabilities that are used in high-resolution connectome research. In this paper, we propose a hybrid CPU-GPU framework to accelerate the computation of the human brain connectome. We applied this framework to a publicly available resting-state functional MRI dataset from 197 participants. For each subject, we first computed Pearson’s Correlation coefficient between any pairs of the time series of gray-matter voxels, and then we constructed unweighted undirected brain networks with 58 k nodes and a sparsity range from 0.02% to 0.17%. Next, graphic properties of the functional brain networks were quantified, analyzed and compared with those of 15 corresponding random networks. With our proposed accelerating framework, the above process for each network cost 80∼150 minutes, depending on the network sparsity. Further analyses revealed that high-resolution functional brain networks have efficient small-world properties, significant modular structure, a power law degree distribution and highly connected nodes in the medial frontal and parietal cortical regions. These results are largely compatible with previous human brain network studies. Taken together, our proposed framework can substantially enhance the applicability and efficacy of high-resolution (voxel-based) brain network analysis, and have the potential to accelerate the mapping of the human brain connectome in normal and disease states. PMID:23675425

An improved Bayesian tensor regularization and sampling algorithm to track neuronal fiber pathways in the language circuit.

PubMed

Mishra, Arabinda; Anderson, Adam W; Wu, Xi; Gore, John C; Ding, Zhaohua

2010-08-01

The purpose of this work is to design a neuronal fiber tracking algorithm, which will be more suitable for reconstruction of fibers associated with functionally important regions in the human brain. The functional activations in the brain normally occur in the gray matter regions. Hence the fibers bordering these regions are weakly myelinated, resulting in poor performance of conventional tractography methods to trace the fiber links between them. A lower fractional anisotropy in this region makes it even difficult to track the fibers in the presence of noise. In this work, the authors focused on a stochastic approach to reconstruct these fiber pathways based on a Bayesian regularization framework. To estimate the true fiber direction (propagation vector), the a priori and conditional probability density functions are calculated in advance and are modeled as multivariate normal. The variance of the estimated tensor element vector is associated with the uncertainty due to noise and partial volume averaging (PVA). An adaptive and multiple sampling of the estimated tensor element vector, which is a function of the pre-estimated variance, overcomes the effect of noise and PVA in this work. The algorithm has been rigorously tested using a variety of synthetic data sets. The quantitative comparison of the results to standard algorithms motivated the authors to implement it for in vivo DTI data analysis. The algorithm has been implemented to delineate fibers in two major language pathways (Broca's to SMA and Broca's to Wernicke's) across 12 healthy subjects. Though the mean of standard deviation was marginally bigger than conventional (Euler's) approach [P. J. Basser et al., "In vivo fiber tractography using DT-MRI data," Magn. Reson. Med. 44(4), 625-632 (2000)], the number of extracted fibers in this approach was significantly higher. The authors also compared the performance of the proposed method to Lu's method [Y. Lu et al., "Improved fiber tractography with Bayesian tensor regularization," Neuroimage 31(3), 1061-1074 (2006)] and Friman's stochastic approach [O. Friman et al., "A Bayesian approach for stochastic white matter tractography," IEEE Trans. Med. Imaging 25(8), 965-978 (2006)]. Overall performance of the approach is found to be superior to above two methods, particularly when the signal-to-noise ratio was low. The authors observed that an adaptive sampling of the tensor element vectors, estimated as a function of the variance in a Bayesian framework, can effectively delineate neuronal fibers to analyze the structure-function relationship in human brain. The simulated and in vivo results are in good agreement with the theoretical aspects of the algorithm.

How structure sculpts function: Unveiling the contribution of anatomical connectivity to the brain's spontaneous correlation structure

NASA Astrophysics Data System (ADS)

Bettinardi, R. G.; Deco, G.; Karlaftis, V. M.; Van Hartevelt, T. J.; Fernandes, H. M.; Kourtzi, Z.; Kringelbach, M. L.; Zamora-López, G.

2017-04-01

Intrinsic brain activity is characterized by highly organized co-activations between different regions, forming clustered spatial patterns referred to as resting-state networks. The observed co-activation patterns are sustained by the intricate fabric of millions of interconnected neurons constituting the brain's wiring diagram. However, as for other real networks, the relationship between the connectional structure and the emergent collective dynamics still evades complete understanding. Here, we show that it is possible to estimate the expected pair-wise correlations that a network tends to generate thanks to the underlying path structure. We start from the assumption that in order for two nodes to exhibit correlated activity, they must be exposed to similar input patterns from the entire network. We then acknowledge that information rarely spreads only along a unique route but rather travels along all possible paths. In real networks, the strength of local perturbations tends to decay as they propagate away from the sources, leading to a progressive attenuation of the original information content and, thus, of their influence. Accordingly, we define a novel graph measure, topological similarity, which quantifies the propensity of two nodes to dynamically correlate as a function of the resemblance of the overall influences they are expected to receive due to the underlying structure of the network. Applied to the human brain, we find that the similarity of whole-network inputs, estimated from the topology of the anatomical connectome, plays an important role in sculpting the backbone pattern of time-average correlations observed at rest.

Hemispheric Specialization and the Growth of Human Understanding.

ERIC Educational Resources Information Center

Kinsbourne, Marcel

1982-01-01

Connectionistic notions of hemispheric specialization and use are incompatible with the network organization of the human brain. Although brain organization has correspondence with phenomena at more complex levels of analysis, the correspondence is not categorical in nature, as has been claimed by the left-brain/right-brain theorists. (Author/GC)

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

Advanced lesion symptom mapping analyses and implementation as BCBtoolkit

PubMed Central

Foulon, Chris; Cerliani, Leonardo; Kinkingnéhun, Serge; Levy, Richard; Rosso, Charlotte; Urbanski, Marika

2018-01-01

Abstract Background Patients with brain lesions provide a unique opportunity to understand the functioning of the human mind. However, even when focal, brain lesions have local and remote effects that impact functionally and structurally connected circuits. Similarly, function emerges from the interaction between brain areas rather than their sole activity. For instance, category fluency requires the associations between executive, semantic, and language production functions. Findings Here, we provide, for the first time, a set of complementary solutions for measuring the impact of a given lesion on the neuronal circuits. Our methods, which were applied to 37 patients with a focal frontal brain lesions, revealed a large set of directly and indirectly disconnected brain regions that had significantly impacted category fluency performance. The directly disconnected regions corresponded to areas that are classically considered as functionally engaged in verbal fluency and categorization tasks. These regions were also organized into larger directly and indirectly disconnected functional networks, including the left ventral fronto-parietal network, whose cortical thickness correlated with performance on category fluency. Conclusions The combination of structural and functional connectivity together with cortical thickness estimates reveal the remote effects of brain lesions, provide for the identification of the affected networks, and strengthen our understanding of their relationship with cognitive and behavioral measures. The methods presented are available and freely accessible in the BCBtoolkit as supplementary software [1]. PMID:29432527

A Mechanistic Model of Human Recall of Social Network Structure and Relationship Affect.

PubMed

Omodei, Elisa; Brashears, Matthew E; Arenas, Alex

2017-12-07

The social brain hypothesis argues that the need to deal with social challenges was key to our evolution of high intelligence. Research with non-human primates as well as experimental and fMRI studies in humans produce results consistent with this claim, leading to an estimate that human primary groups should consist of roughly 150 individuals. Gaps between this prediction and empirical observations can be partially accounted for using "compression heuristics", or schemata that simplify the encoding and recall of social information. However, little is known about the specific algorithmic processes used by humans to store and recall social information. We describe a mechanistic model of human network recall and demonstrate its sufficiency for capturing human recall behavior observed in experimental contexts. We find that human recall is predicated on accurate recall of a small number of high degree network nodes and the application of heuristics for both structural and affective information. This provides new insight into human memory, social network evolution, and demonstrates a novel approach to uncovering human cognitive operations.

Kinetic analysis of the translocator protein positron emission tomography ligand [18F]GE-180 in the human brain.

PubMed

Feeney, Claire; Scott, Gregory; Raffel, Joel; Roberts, S; Coello, Christopher; Jolly, Amy; Searle, Graham; Goldstone, A P; Brooks, David J; Nicholas, Richard S; Trigg, William; Gunn, Roger N; Sharp, David J

2016-11-01

PET can image neuroinflammation by targeting the translocator protein (TSPO), which is upregulated in activated microglia. The high nonspecific binding of the first-generation TSPO radioligand [ 11 C]PK-11195 limits accurate quantification. [ 18 F]GE-180, a novel TSPO ligand, displays superior binding to [ 11 C]PK-11195 in vitro. Our objectives were to: (1) evaluate tracer characteristics of [ 18 F]GE-180 in the brains of healthy human subjects; and (2) investigate whether the TSPO Ala147Thr polymorphism influences outcome measures. Ten volunteers (five high-affinity binders, HABs, and five mixed-affinity binders, MABs) underwent a dynamic PET scan with arterial sampling after injection of [ 18 F]GE-180. Kinetic modelling of time-activity curves with one-tissue and two-tissue compartment models and Logan graphical analysis was applied to the data. The primary outcome measure was the total volume of distribution (V T ) across various regions of interest (ROIs). Secondary outcome measures were the standardized uptake values (SUV), the distribution volume and SUV ratios estimated using a pseudoreference region. The two-tissue compartment model was the best model. The average regional delivery rate constant (K 1 ) was 0.01 mL cm -3  min -1 indicating low extraction across the blood-brain barrier (1 %). The estimated median V T across all ROIs was also low, ranging from 0.16 mL cm -3 in the striatum to 0.38 mL cm -3 in the thalamus. There were no significant differences in V T between HABs and MABs across all ROIs. A reversible two-tissue compartment model fitted the data well and determined that the tracer has a low first-pass extraction (approximately 1 %) and low V T estimates in healthy individuals. There was no observable dependency on the rs6971 polymorphism as compared to other second-generation TSPO PET tracers. Investigation of [ 18 F]GE-180 in populations with neuroinflammatory disease is needed to determine its suitability for quantitative assessment of TSPO expression.

Sex beyond the genitalia: The human brain mosaic

PubMed Central

Joel, Daphna; Berman, Zohar; Tavor, Ido; Wexler, Nadav; Gaber, Olga; Stein, Yaniv; Shefi, Nisan; Pool, Jared; Urchs, Sebastian; Margulies, Daniel S.; Liem, Franziskus; Hänggi, Jürgen; Jäncke, Lutz; Assaf, Yaniv

2015-01-01

Whereas a categorical difference in the genitals has always been acknowledged, the question of how far these categories extend into human biology is still not resolved. Documented sex/gender differences in the brain are often taken as support of a sexually dimorphic view of human brains (“female brain” or “male brain”). However, such a distinction would be possible only if sex/gender differences in brain features were highly dimorphic (i.e., little overlap between the forms of these features in males and females) and internally consistent (i.e., a brain has only “male” or only “female” features). Here, analysis of MRIs of more than 1,400 human brains from four datasets reveals extensive overlap between the distributions of females and males for all gray matter, white matter, and connections assessed. Moreover, analyses of internal consistency reveal that brains with features that are consistently at one end of the “maleness-femaleness” continuum are rare. Rather, most brains are comprised of unique “mosaics” of features, some more common in females compared with males, some more common in males compared with females, and some common in both females and males. Our findings are robust across sample, age, type of MRI, and method of analysis. These findings are corroborated by a similar analysis of personality traits, attitudes, interests, and behaviors of more than 5,500 individuals, which reveals that internal consistency is extremely rare. Our study demonstrates that, although there are sex/gender differences in the brain, human brains do not belong to one of two distinct categories: male brain/female brain. PMID:26621705

Conscious brain-to-brain communication in humans using non-invasive technologies.

PubMed

Grau, Carles; Ginhoux, Romuald; Riera, Alejandro; Nguyen, Thanh Lam; Chauvat, Hubert; Berg, Michel; Amengual, Julià L; Pascual-Leone, Alvaro; Ruffini, Giulio

2014-01-01

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies

PubMed Central

Grau, Carles; Ginhoux, Romuald; Riera, Alejandro; Nguyen, Thanh Lam; Chauvat, Hubert; Berg, Michel; Amengual, Julià L.; Pascual-Leone, Alvaro; Ruffini, Giulio

2014-01-01

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues. PMID:25137064

Human and animal cognition: Continuity and discontinuity

PubMed Central

Premack, David

2007-01-01

Microscopic study of the human brain has revealed neural structures, enhanced wiring, and forms of connectivity among nerve cells not found in any animal, challenging the view that the human brain is simply an enlarged chimpanzee brain. On the other hand, cognitive studies have found animals to have abilities once thought unique to the human. This suggests a disparity between brain and mind. The suggestion is misleading. Cognitive research has not kept pace with neural research. Neural findings are based on microscopic study of the brain and are primarily cellular. Because cognition cannot be studied microscopically, we need to refine the study of cognition by using a different approach. In examining claims of similarity between animals and humans, one must ask: What are the dissimilarities? This approach prevents confusing similarity with equivalence. We follow this approach in examining eight cognitive cases—teaching, short-term memory, causal reasoning, planning, deception, transitive inference, theory of mind, and language—and find, in all cases, that similarities between animal and human abilities are small, dissimilarities large. There is no disparity between brain and mind. PMID:17717081

Functional organization of the transcriptome in human brain

PubMed Central

Oldham, Michael C; Konopka, Genevieve; Iwamoto, Kazuya; Langfelder, Peter; Kato, Tadafumi; Horvath, Steve; Geschwind, Daniel H

2009-01-01

The enormous complexity of the human brain ultimately derives from a finite set of molecular instructions encoded in the human genome. These instructions can be directly studied by exploring the organization of the brain’s transcriptome through systematic analysis of gene coexpression relationships. We analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astrocytes and microglia. These modules provide an initial description of the transcriptional programs that distinguish the major cell classes of the human brain and indicate that cell type–specific information can be obtained from whole brain tissue without isolating homogeneous populations of cells. Other modules corresponded to additional cell types, organelles, synaptic function, gender differences and the subventricular neurogenic niche. We found that subventricular zone astrocytes, which are thought to function as neural stem cells in adults, have a distinct gene expression pattern relative to protoplasmic astrocytes. Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome. PMID:18849986

Small-world human brain networks: Perspectives and challenges.

PubMed

Liao, Xuhong; Vasilakos, Athanasios V; He, Yong

2017-06-01

Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic Multi-Coil Shimming of the Human Brain at 7 Tesla

PubMed Central

Juchem, Christoph; Nixon, Terence W.; McIntyre, Scott; Boer, Vincent O.; Rothman, Douglas L.; de Graaf, Robin A.

2011-01-01

High quality magnetic field homogenization of the human brain (i.e. shimming) for MR imaging and spectroscopy is a demanding task. The susceptibility differences between air and tissue are a longstanding problem as they induce complex field distortions in the prefrontal cortex and the temporal lobes. To date, the theoretical gains of high field MR have only been realized partially in the human brain due to limited magnetic field homogeneity. A novel shimming technique for the human brain is presented that is based on the combination of non-orthogonal basis fields from 48 individual, circular coils. Custom-built amplifier electronics enabled the dynamic application of the multi-coil shim fields in a slice-specific fashion. Dynamic multi-coil (DMC) shimming is shown to eliminate most of the magnetic field inhomogeneity apparent in the human brain at 7 Tesla and provided improved performance compared to state-of-the-art dynamic shim updating with zero through third order spherical harmonic functions. The novel technique paves the way for high field MR applications of the human brain for which excellent magnetic field homogeneity is a prerequisite. PMID:21824794

Control-display mapping in brain-computer interfaces.

PubMed

Thurlings, Marieke E; van Erp, Jan B F; Brouwer, Anne-Marie; Blankertz, Benjamin; Werkhoven, Peter

2012-01-01

Event-related potential (ERP) based brain-computer interfaces (BCIs) employ differences in brain responses to attended and ignored stimuli. When using a tactile ERP-BCI for navigation, mapping is required between navigation directions on a visual display and unambiguously corresponding tactile stimuli (tactors) from a tactile control device: control-display mapping (CDM). We investigated the effect of congruent (both display and control horizontal or both vertical) and incongruent (vertical display, horizontal control) CDMs on task performance, the ERP and potential BCI performance. Ten participants attended to a target (determined via CDM), in a stream of sequentially vibrating tactors. We show that congruent CDM yields best task performance, enhanced the P300 and results in increased estimated BCI performance. This suggests a reduced availability of attentional resources when operating an ERP-BCI with incongruent CDM. Additionally, we found an enhanced N2 for incongruent CDM, which indicates a conflict between visual display and tactile control orientations. Incongruency in control-display mapping reduces task performance. In this study, brain responses, task and system performance are related to (in)congruent mapping of command options and the corresponding stimuli in a brain-computer interface (BCI). Directional congruency reduces task errors, increases available attentional resources, improves BCI performance and thus facilitates human-computer interaction.

Effect of chronic exposure to aspartame on oxidative stress in the brain of albino rats.

PubMed

Iyyaswamy, Ashok; Rathinasamy, Sheeladevi

2012-09-01

This study was aimed at investigating the chronic effect of the artificial sweetener aspartame on oxidative stress in brain regions of Wistar strain albino rats. Many controversial reports are available on the use of aspartame as it releases methanol as one of its metabolite during metabolism. The present study proposed to investigate whether chronic aspartame (75 mg/kg) administration could release methanol and induce oxidative stress in the rat brain. To mimic the human methanol metabolism, methotrexate (MTX)-treated rats were included to study the aspartame effects. Wistar strain male albino rats were administered with aspartame orally and studied along with controls and MTX-treated controls. The blood methanol level was estimated, the animal was sacrificed and the free radical changes were observed in brain discrete regions by assessing the scavenging enzymes, reduced glutathione, lipid peroxidation (LPO) and protein thiol levels. It was observed that there was a significant increase in LPO levels, superoxide dismutase (SOD) activity, GPx levels and CAT activity with a significant decrease in GSH and protein thiol. Moreover, the increases in some of these enzymes were region specific. Chronic exposure of aspartame resulted in detectable methanol in blood. Methanol per se and its metabolites may be responsible for the generation of oxidative stress in brain regions.

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

PubMed

Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Major involvement of Na(+) -dependent multivitamin transporter (SLC5A6/SMVT) in uptake of biotin and pantothenic acid by human brain capillary endothelial cells.

PubMed

Uchida, Yasuo; Ito, Katsuaki; Ohtsuki, Sumio; Kubo, Yoshiyuki; Suzuki, Takashi; Terasaki, Tetsuya

2015-07-01

The purpose of this study was to clarify the expression of Na(+) -dependent multivitamin transporter (SLC5A6/SMVT) and its contribution to the supply of biotin and pantothenic acid to the human brain via the blood-brain barrier. DNA microarray and immunohistochemical analyses confirmed that SLC5A6 is expressed in microvessels of human brain. The absolute expression levels of SLC5A6 protein in isolated human and monkey brain microvessels were 1.19 and 0.597 fmol/μg protein, respectively, as determined by a quantitative targeted absolute proteomics technique. Using an antibody-free method established by Kubo et al. (2015), we found that SLC5A6 was preferentially localized at the luminal membrane of brain capillary endothelium. Knock-down analysis using SLC5A6 siRNA showed that SLC5A6 accounts for 88.7% and 98.6% of total [(3) H]biotin and [(3) H]pantothenic acid uptakes, respectively, by human cerebral microvascular endothelial cell line hCMEC/D3. SLC5A6-mediated transport in hCMEC/D3 was markedly inhibited not only by biotin and pantothenic acid, but also by prostaglandin E2, lipoic acid, docosahexaenoic acid, indomethacin, ketoprofen, diclofenac, ibuprofen, phenylbutazone, and flurbiprofen. This study is the first to confirm expression of SLC5A6 in human brain microvessels and to provide evidence that SLC5A6 is a major contributor to luminal uptake of biotin and pantothenic acid at the human blood-brain barrier. In humans, it was unclear (not concluded) about what transport system at the blood-brain barrier (BBB) is responsible for the brain uptakes of two vitamins, biotin and pantothenic acid, which are necessary for brain proper function. This study clarified for the first time that the solute carrier 5A6/Na(+) -dependent multivitamin transporter SLC5A6/SMVT is responsible for the supplies of biotin and pantothenic acid into brain across the BBB in humans. DHA, docosahexaenoic acid; NSAID, non-steroidal anti-inflammatory drug; PGE2, prostaglandin E2. © 2015 International Society for Neurochemistry.

Nonlocal Intracranial Cavity Extraction

PubMed Central

Manjón, José V.; Eskildsen, Simon F.; Coupé, Pierrick; Romero, José E.; Collins, D. Louis; Robles, Montserrat

2014-01-01

Automatic and accurate methods to estimate normalized regional brain volumes from MRI data are valuable tools which may help to obtain an objective diagnosis and followup of many neurological diseases. To estimate such regional brain volumes, the intracranial cavity volume (ICV) is often used for normalization. However, the high variability of brain shape and size due to normal intersubject variability, normal changes occurring over the lifespan, and abnormal changes due to disease makes the ICV estimation problem challenging. In this paper, we present a new approach to perform ICV extraction based on the use of a library of prelabeled brain images to capture the large variability of brain shapes. To this end, an improved nonlocal label fusion scheme based on BEaST technique is proposed to increase the accuracy of the ICV estimation. The proposed method is compared with recent state-of-the-art methods and the results demonstrate an improved performance both in terms of accuracy and reproducibility while maintaining a reduced computational burden. PMID:25328511

brain-coX: investigating and visualising gene co-expression in seven human brain transcriptomic datasets.

PubMed

Freytag, Saskia; Burgess, Rosemary; Oliver, Karen L; Bahlo, Melanie

2017-06-08

The pathogenesis of neurological and mental health disorders often involves multiple genes, complex interactions, as well as brain- and development-specific biological mechanisms. These characteristics make identification of disease genes for such disorders challenging, as conventional prioritisation tools are not specifically tailored to deal with the complexity of the human brain. Thus, we developed a novel web-application-brain-coX-that offers gene prioritisation with accompanying visualisations based on seven gene expression datasets in the post-mortem human brain, the largest such resource ever assembled. We tested whether our tool can correctly prioritise known genes from 37 brain-specific KEGG pathways and 17 psychiatric conditions. We achieved average sensitivity of nearly 50%, at the same time reaching a specificity of approximately 75%. We also compared brain-coX's performance to that of its main competitors, Endeavour and ToppGene, focusing on the ability to discover novel associations. Using a subset of the curated SFARI autism gene collection we show that brain-coX's prioritisations are most similar to SFARI's own curated gene classifications. brain-coX is the first prioritisation and visualisation web-tool targeted to the human brain and can be freely accessed via http://shiny.bioinf.wehi.edu.au/freytag.s/ .

Brain drain and health workforce distortions in Mozambique.

PubMed

Sherr, Kenneth; Mussa, Antonio; Chilundo, Baltazar; Gimbel, Sarah; Pfeiffer, James; Hagopian, Amy; Gloyd, Stephen

2012-01-01

Trained human resources are fundamental for well-functioning health systems, and the lack of health workers undermines public sector capacity to meet population health needs. While external brain drain from low and middle-income countries is well described, there is little understanding of the degree of internal brain drain, and how increases in health sector funding through global health initiatives may contribute to the outflow of health workers from the public sector to donor agencies, non-governmental organisations (NGOs), and the private sector. An observational study was conducted to estimate the degree of internal and external brain drain among Mozambican nationals qualifying from domestic and foreign medical schools between 1980-2006. Data were collected 26-months apart in 2008 and 2010, and included current employment status, employer, geographic location of employment, and main work duties. Of 723 qualifying physicians between 1980-2006, 95.9% (693) were working full-time, including 71.1% (493) as clinicians, 20.5% (142) as health system managers, and 6.9% (48) as researchers/professors. 25.5% (181) of the sample had left the public sector, of which 62.4% (113) continued working in-country and 37.6% (68) emigrated from Mozambique. Of those cases of internal migration, 66.4% (75) worked for NGOs, 21.2% (24) for donor agencies, and 12.4% (14) in the private sector. Annual incidence of physician migration was estimated to be 3.7%, predominately to work in the growing NGO sector. An estimated 36.3% (41/113) of internal migration cases had previously held senior-level management positions in the public sector. Internal migration is an important contributor to capital flight from the public sector, accounting for more cases of physician loss than external migration in Mozambique. Given the urgent need to strengthen public sector health systems, frank reflection by donors and NGOs is needed to assess how hiring practices may undermine the very systems they seek to strengthen.

Brain Drain and Health Workforce Distortions in Mozambique

PubMed Central

Sherr, Kenneth; Mussa, Antonio; Chilundo, Baltazar; Gimbel, Sarah; Pfeiffer, James; Hagopian, Amy; Gloyd, Stephen

2012-01-01

Introduction Trained human resources are fundamental for well-functioning health systems, and the lack of health workers undermines public sector capacity to meet population health needs. While external brain drain from low and middle-income countries is well described, there is little understanding of the degree of internal brain drain, and how increases in health sector funding through global health initiatives may contribute to the outflow of health workers from the public sector to donor agencies, non-governmental organisations (NGOs), and the private sector. Methods An observational study was conducted to estimate the degree of internal and external brain drain among Mozambican nationals qualifying from domestic and foreign medical schools between 1980–2006. Data were collected 26-months apart in 2008 and 2010, and included current employment status, employer, geographic location of employment, and main work duties. Results Of 723 qualifying physicians between 1980–2006, 95.9% (693) were working full-time, including 71.1% (493) as clinicians, 20.5% (142) as health system managers, and 6.9% (48) as researchers/professors. 25.5% (181) of the sample had left the public sector, of which 62.4% (113) continued working in-country and 37.6% (68) emigrated from Mozambique. Of those cases of internal migration, 66.4% (75) worked for NGOs, 21.2% (24) for donor agencies, and 12.4% (14) in the private sector. Annual incidence of physician migration was estimated to be 3.7%, predominately to work in the growing NGO sector. An estimated 36.3% (41/113) of internal migration cases had previously held senior-level management positions in the public sector. Discussion Internal migration is an important contributor to capital flight from the public sector, accounting for more cases of physician loss than external migration in Mozambique. Given the urgent need to strengthen public sector health systems, frank reflection by donors and NGOs is needed to assess how hiring practices may undermine the very systems they seek to strengthen. PMID:22558237

Accurate determination of brain metabolite concentrations using ERETIC as external reference.

PubMed

Zoelch, Niklaus; Hock, Andreas; Heinzer-Schweizer, Susanne; Avdievitch, Nikolai; Henning, Anke

2017-08-01

Magnetic Resonance Spectroscopy (MRS) can provide in vivo metabolite concentrations in standard concentration units if a reliable reference signal is available. For 1 H MRS in the human brain, typically the signal from the tissue water is used as the (internal) reference signal. However, a concentration determination based on the tissue water signal most often requires a reliable estimate of the water concentration present in the investigated tissue. Especially in clinically interesting cases, this estimation might be difficult. To avoid assumptions about the water in the investigated tissue, the Electric REference To access In vivo Concentrations (ERETIC) method has been proposed. In this approach, the metabolite signal is compared with a reference signal acquired in a phantom and potential coil-loading differences are corrected using a synthetic reference signal. The aim of this study, conducted with a transceiver quadrature head coil, was to increase the accuracy of the ERETIC method by correcting the influence of spatial B 1 inhomogeneities and to simplify the quantification with ERETIC by incorporating an automatic phase correction for the ERETIC signal. Transmit field ( B1+) differences are minimized with a volume-selective power optimization, whereas reception sensitivity changes are corrected using contrast-minimized images of the brain and by adapting the voxel location in the phantom measurement closely to the position measured in vivo. By applying the proposed B 1 correction scheme, the mean metabolite concentrations determined with ERETIC in 21 healthy subjects at three different positions agree with concentrations derived with the tissue water signal as reference. In addition, brain water concentrations determined with ERETIC were in agreement with estimations derived using tissue segmentation and literature values for relative water densities. Based on the results, the ERETIC method presented here is a valid tool to derive in vivo metabolite concentration, with potential advantages compared with internal water referencing in diseased tissue. Copyright © 2017 John Wiley & Sons, Ltd.

Brain Imaging of Human Sexual Response: Recent Developments and Future Directions.

PubMed

Ruesink, Gerben B; Georgiadis, Janniko R

2017-01-01

The purpose of this study is to provide a comprehensive summary of the latest developments in the experimental brain study of human sexuality, focusing on brain connectivity during the sexual response. Stable patterns of brain activation have been established for different phases of the sexual response, especially with regard to the wanting phase, and changes in these patterns can be linked to sexual response variations, including sexual dysfunctions. From this solid basis, connectivity studies of the human sexual response have begun to add a deeper understanding of the brain network function and structure involved. The study of "sexual" brain connectivity is still very young. Yet, by approaching the brain as a connected organ, the essence of brain function is captured much more accurately, increasing the likelihood of finding useful biomarkers and targets for intervention in sexual dysfunction.

Common biology of craving across legal and illegal drugs - a quantitative meta-analysis of cue-reactivity brain response.

PubMed

Kühn, Simone; Gallinat, Jürgen

2011-04-01

The present quantitative meta-analysis set out to test whether cue-reactivity responses in humans differ across drugs of abuse and whether these responses constitute the biological basis of drug craving as a core psychopathology of addiction. By means of activation likelihood estimation, we investigated the concurrence of brain regions activated by cue-induced craving paradigms across studies on nicotine, alcohol and cocaine addicts. Furthermore, we analysed the concurrence of brain regions positively correlated with self-reported craving in nicotine and alcohol studies. We found direct overlap between nicotine, alcohol and cocaine cue reactivity in the ventral striatum. In addition, regions of close proximity were observed in the anterior cingulate cortex (ACC; nicotine and cocaine) and amygdala (alcohol, nicotine and cocaine). Brain regions of concurrence in drug cue-reactivity paradigms that overlapped with brain regions of concurrence in self-reported craving correlations were found in the ACC, ventral striatum and right pallidum (for alcohol). This first quantitative meta-analysis on drug cue reactivity identifies brain regions underlying nicotine, alcohol and cocaine dependency, i.e. the ventral striatum. The ACC, right pallidum and ventral striatum were related to drug cue reactivity as well as self-reported craving, suggesting that this set of brain regions constitutes the core circuit of drug craving in nicotine and alcohol addiction. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

T cells establish and maintain CNS viral infection in HIV-infected humanized mice.

PubMed

Honeycutt, Jenna B; Liao, Baolin; Nixon, Christopher C; Cleary, Rachel A; Thayer, William O; Birath, Shayla L; Swanson, Michael D; Sheridan, Patricia; Zakharova, Oksana; Prince, Francesca; Kuruc, JoAnn; Gay, Cynthia L; Evans, Chris; Eron, Joseph J; Wahl, Angela; Garcia, J Victor

2018-06-04

The human brain is an important site of HIV replication and persistence during antiretroviral therapy (ART). Direct evaluation of HIV infection in the brains of otherwise healthy individuals is not feasible; therefore, we performed a large-scale study of bone marrow/liver/thymus (BLT) humanized mice as an in vivo model to study HIV infection in the brain. Human immune cells, including CD4+ T cells and macrophages, were present throughout the BLT mouse brain. HIV DNA, HIV RNA, and/or p24+ cells were observed in the brains of HIV-infected animals, regardless of the HIV isolate used. HIV infection resulted in decreased numbers of CD4+ T cells, increased numbers of CD8+ T cells, and a decreased CD4+/CD8+ T cell ratio in the brain. Using humanized T cell-only mice (ToM), we demonstrated that T cells establish and maintain HIV infection of the brain in the complete absence of human myeloid cells. HIV infection of ToM resulted in CD4+ T cell depletion and a reduced CD4+/CD8+ T cell ratio. ART significantly reduced HIV levels in the BLT mouse brain, and the immune cell populations present were indistinguishable from those of uninfected controls, which demonstrated the effectiveness of ART in controlling HIV replication in the CNS and returning cellular homeostasis to a pre-HIV state.

Soft brain-machine interfaces for assistive robotics: A novel control approach.

PubMed

Schiatti, Lucia; Tessadori, Jacopo; Barresi, Giacinto; Mattos, Leonardo S; Ajoudani, Arash

2017-07-01

Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients. The interface is composed of an eye-tracking system, for an intuitive and reliable control of a robotic arm system's trajectories, and a Brain-Computer Interface (BCI) unit, for the control of the robot Cartesian stiffness, which determines the interaction forces between the robot and environment. The latter control is achieved by estimating in real-time a unidimensional index from user's electroencephalographic (EEG) signals, which provides the probability of a neutral or active state. This estimated state is then translated into a stiffness value for the robotic arm, allowing a reliable modulation of the robot's impedance. A preliminary evaluation of this hybrid interface concept provided evidence on the effective execution of tasks with dynamic uncertainties, demonstrating the great potential of this control method in BMI applications for self-service and clinical care.

On Evaluating Brain Tissue Classifiers without a Ground Truth

PubMed Central

Martin-Fernandez, Marcos; Ungar, Lida; Nakamura, Motoaki; Koo, Min-Seong; McCarley, Robert W.; Shenton, Martha E.

2009-01-01

In this paper, we present a set of techniques for the evaluation of brain tissue classifiers on a large data set of MR images of the head. Due to the difficulty of establishing a gold standard for this type of data, we focus our attention on methods which do not require a ground truth, but instead rely on a common agreement principle. Three different techniques are presented: the Williams’ index, a measure of common agreement; STAPLE, an Expectation Maximization algorithm which simultaneously estimates performance parameters and constructs an estimated reference standard; and Multidimensional Scaling, a visualization technique to explore similarity data. We apply these different evaluation methodologies to a set eleven different segmentation algorithms on forty MR images. We then validate our evaluation pipeline by building a ground truth based on human expert tracings. The evaluations with and without a ground truth are compared. Our findings show that comparing classifiers without a gold standard can provide a lot of interesting information. In particular, outliers can be easily detected, strongly consistent or highly variable techniques can be readily discriminated, and the overall similarity between different techniques can be assessed. On the other hand, we also find that some information present in the expert segmentations is not captured by the automatic classifiers, suggesting that common agreement alone may not be sufficient for a precise performance evaluation of brain tissue classifiers. PMID:17532646

Comparative Methylome Analyses Identify Epigenetic Regulatory Loci of Human Brain Evolution.

PubMed

Mendizabal, Isabel; Shi, Lei; Keller, Thomas E; Konopka, Genevieve; Preuss, Todd M; Hsieh, Tzung-Fu; Hu, Enzhi; Zhang, Zhe; Su, Bing; Yi, Soojin V

2016-11-01

How do epigenetic modifications change across species and how do these modifications affect evolution? These are fundamental questions at the forefront of our evolutionary epigenomic understanding. Our previous work investigated human and chimpanzee brain methylomes, but it was limited by the lack of outgroup data which is critical for comparative (epi)genomic studies. Here, we compared whole genome DNA methylation maps from brains of humans, chimpanzees and also rhesus macaques (outgroup) to elucidate DNA methylation changes during human brain evolution. Moreover, we validated that our approach is highly robust by further examining 38 human-specific DMRs using targeted deep genomic and bisulfite sequencing in an independent panel of 37 individuals from five primate species. Our unbiased genome-scan identified human brain differentially methylated regions (DMRs), irrespective of their associations with annotated genes. Remarkably, over half of the newly identified DMRs locate in intergenic regions or gene bodies. Nevertheless, their regulatory potential is on par with those of promoter DMRs. An intriguing observation is that DMRs are enriched in active chromatin loops, suggesting human-specific evolutionary remodeling at a higher-order chromatin structure. These findings indicate that there is substantial reprogramming of epigenomic landscapes during human brain evolution involving noncoding regions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Dopaminergic Neurotransmission in the Human Brain: New Lessons from Perturbation and Imaging

PubMed Central

Ko, Ji Hyun; Strafella, Antonio P.

2012-01-01

Dopamine plays an important role in several brain functions and is involved in the pathogenesis of several psychiatric and neurological disorders. Neuroimaging techniques such as positron emission tomography allow us to quantify dopaminergic activity in the living human brain. Combining these with brain stimulation techniques offers us the unique opportunity to tackle questions regarding region-specific neurochemical activity. Such studies may aid clinicians and scientists to disentangle neural circuitries within the human brain and thereby help them to understand the underlying mechanisms of a given function in relation to brain diseases. Furthermore, it may also aid the development of alternative treatment approaches for various neurological and psychiatric conditions. PMID:21536838

Sparse Spectro-Temporal Receptive Fields Based on Multi-Unit and High-Gamma Responses in Human Auditory Cortex

PubMed Central

Jenison, Rick L.; Reale, Richard A.; Armstrong, Amanda L.; Oya, Hiroyuki; Kawasaki, Hiroto; Howard, Matthew A.

2015-01-01

Spectro-Temporal Receptive Fields (STRFs) were estimated from both multi-unit sorted clusters and high-gamma power responses in human auditory cortex. Intracranial electrophysiological recordings were used to measure responses to a random chord sequence of Gammatone stimuli. Traditional methods for estimating STRFs from single-unit recordings, such as spike-triggered-averages, tend to be noisy and are less robust to other response signals such as local field potentials. We present an extension to recently advanced methods for estimating STRFs from generalized linear models (GLM). A new variant of regression using regularization that penalizes non-zero coefficients is described, which results in a sparse solution. The frequency-time structure of the STRF tends toward grouping in different areas of frequency-time and we demonstrate that group sparsity-inducing penalties applied to GLM estimates of STRFs reduces the background noise while preserving the complex internal structure. The contribution of local spiking activity to the high-gamma power signal was factored out of the STRF using the GLM method, and this contribution was significant in 85 percent of the cases. Although the GLM methods have been used to estimate STRFs in animals, this study examines the detailed structure directly from auditory cortex in the awake human brain. We used this approach to identify an abrupt change in the best frequency of estimated STRFs along posteromedial-to-anterolateral recording locations along the long axis of Heschl’s gyrus. This change correlates well with a proposed transition from core to non-core auditory fields previously identified using the temporal response properties of Heschl’s gyrus recordings elicited by click-train stimuli. PMID:26367010

In vivo imaging of scattering and absorption properties of exposed brain using a digital red-green-blue camera

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Yoshida, Keiichiro; Kawauchi, Satoko; Sato, Shunichi; Sato, Manabu

2014-03-01

We investigate a method to estimate the spectral images of reduced scattering coefficients and the absorption coefficients of in vivo exposed brain tissues in the range from visible to near-infrared wavelength (500-760 nm) based on diffuse reflectance spectroscopy using a digital RGB camera. In the proposed method, the multi-spectral reflectance images of in vivo exposed brain are reconstructed from the digital red, green blue images using the Wiener estimation algorithm. The Monte Carlo simulation-based multiple regression analysis for the absorbance spectra is then used to specify the absorption and scattering parameters of brain tissue. In this analysis, the concentration of oxygenated hemoglobin and that of deoxygenated hemoglobin are estimated as the absorption parameters whereas the scattering amplitude a and the scattering power b in the expression of μs'=aλ-b as the scattering parameters, respectively. The spectra of absorption and reduced scattering coefficients are reconstructed from the absorption and scattering parameters, and finally, the spectral images of absorption and reduced scattering coefficients are estimated. The estimated images of absorption coefficients were dominated by the spectral characteristics of hemoglobin. The estimated spectral images of reduced scattering coefficients showed a broad scattering spectrum, exhibiting larger magnitude at shorter wavelengths, corresponding to the typical spectrum of brain tissue published in the literature. In vivo experiments with exposed brain of rats during CSD confirmed the possibility of the method to evaluate both hemodynamics and changes in tissue morphology due to electrical depolarization.

Effect of Magnitude Estimation of Pleasantness and Intensity on fMRI Activation to Taste

PubMed Central

Cerf-Ducastel, B.; Haase, L.; Murphy, C.

2012-01-01

The goal of the present study was to investigate whether the psychophysical evaluation of taste stimuli using magnitude estimation influences the pattern of cortical activation observed with neuroimaging. That is, whether different brain areas are involved in the magnitude estimation of pleasantness relative to the magnitude estimation of intensity. fMRI was utilized to examine the patterns of cortical activation involved in magnitude estimation of pleasantness and intensity during hunger in response to taste stimuli. During scanning, subjects were administered taste stimuli orally and were asked to evaluate the perceived pleasantness or intensity using the general Labeled Magnitude Scale (Green 1996, Bartoshuk et al. 2004). Image analysis was conducted using AFNI. Magnitude estimation of intensity and pleasantness shared common activations in the insula, rolandic operculum, and the medio dorsal nucleus of the thalamus. Globally, magnitude estimation of pleasantness produced significantly more activation than magnitude estimation of intensity. Areas differentially activated during magnitude estimation of pleasantness versus intensity included, e.g., the insula, the anterior cingulate gyrus, and putamen; suggesting that different brain areas were recruited when subjects made magnitude estimates of intensity and pleasantness. These findings demonstrate significant differences in brain activation during magnitude estimation of intensity and pleasantness to taste stimuli. An appreciation for the complexity of brain response to taste stimuli may facilitate a clearer understanding of the neural mechanisms underlying eating behavior and over consumption. PMID:23227271

A multi-pathway hypothesis for human visual fear signaling

PubMed Central

Silverstein, David N.; Ingvar, Martin

2015-01-01

A hypothesis is proposed for five visual fear signaling pathways in humans, based on an analysis of anatomical connectivity from primate studies and human functional connectvity and tractography from brain imaging studies. Earlier work has identified possible subcortical and cortical fear pathways known as the “low road” and “high road,” which arrive at the amygdala independently. In addition to a subcortical pathway, we propose four cortical signaling pathways in humans along the visual ventral stream. All four of these traverse through the LGN to the visual cortex (VC) and branching off at the inferior temporal area, with one projection directly to the amygdala; another traversing the orbitofrontal cortex; and two others passing through the parietal and then prefrontal cortex, one excitatory pathway via the ventral-medial area and one regulatory pathway via the ventral-lateral area. These pathways have progressively longer propagation latencies and may have progressively evolved with brain development to take advantage of higher-level processing. Using the anatomical path lengths and latency estimates for each of these five pathways, predictions are made for the relative processing times at selective ROIs and arrival at the amygdala, based on the presentation of a fear-relevant visual stimulus. Partial verification of the temporal dynamics of this hypothesis might be accomplished using experimental MEG analysis. Possible experimental protocols are suggested. PMID:26379513

Lipid transport and human brain development.

PubMed

Betsholtz, Christer

2015-07-01

How the human brain rapidly builds up its lipid content during brain growth and maintains its lipids in adulthood has remained elusive. Two new studies show that inactivating mutations in MFSD2A, known to be expressed specifically at the blood-brain barrier, lead to microcephaly, thereby offering a simple and surprising solution to an old enigma.

Theoretical Implications of Contemporary Brain Science for Japanese EFL Learning

ERIC Educational Resources Information Center

Clayton, John Lloyd

2015-01-01

Recent advances in brain science show that adult native Japanese speakers utilize a different balance of language processing routes in the brain as compared to native English speakers. Biologically this represents the remarkable flexibility of the human brain to adapt universal human cognitive processes to fit the specific needs of linguistic and…

Aerobic glycolysis in the human brain is associated with development and neotenous gene expression

PubMed Central

Goyal, Manu S.; Hawrylycz, Michael; Miller, Jeremy A.; Snyder, Abraham Z.; Raichle, Marcus E.

2015-01-01

SUMMARY Aerobic glycolysis (AG), i.e., non-oxidative metabolism of glucose despite the presence of abundant oxygen, accounts for 10–12% of glucose used by the adult human brain. AG varies regionally in the resting state. Brain AG may support synaptic growth and remodeling; however, data supporting this hypothesis are sparse. Here, we report on investigations on the role of AG in the human brain. Meta-analysis of prior brain glucose and oxygen metabolism studies demonstrates that AG increases during childhood, precisely when synaptic growth rates are highest. In resting adult humans, AG correlates with persistence of gene expression typical of infancy (transcriptional neoteny). In brain regions with the highest AG, we find increased gene expression related to synapse formation and growth. In contrast, regions high in oxidative glucose metabolism express genes related to mitochondria and synaptic transmission. Our results suggest that brain AG supports developmental processes, particularly those required for synapse formation and growth. PMID:24411938

Cell lineage analysis in human brain using endogenous retroelements

PubMed Central

Evrony, Gilad D.; Lee, Eunjung; Mehta, Bhaven K.; Benjamini, Yuval; Johnson, Robert M.; Cai, Xuyu; Yang, Lixing; Haseley, Psalm; Lehmann, Hillel S.; Park, Peter J.; Walsh, Christopher A.

2015-01-01

Summary Somatic mutations occur during brain development and are increasingly implicated as a cause of neurogenetic disease. However, the patterns in which somatic mutations distribute in the human brain are unknown. We used high-coverage whole-genome sequencing of single neurons from a normal individual to identify spontaneous somatic mutations as clonal marks to track cell lineages in human brain. Somatic mutation analyses in >30 locations throughout the nervous system identified multiple lineages and sub-lineages of cells marked by different LINE-1 (L1) retrotransposition events and subsequent mutation of poly-A microsatellites within L1. One clone contained thousands of cells limited to the left middle frontal gyrus, whereas a second distinct clone contained millions of cells distributed over the entire left hemisphere. These patterns mirror known somatic mutation disorders of brain development, and suggest that focally distributed mutations are also prevalent in normal brains. Single-cell analysis of somatic mutation enables tracing of cell lineage clones in human brain. PMID:25569347

Development of a high angular resolution diffusion imaging human brain template.

PubMed

Varentsova, Anna; Zhang, Shengwei; Arfanakis, Konstantinos

2014-05-01

Brain diffusion templates contain rich information about the microstructure of the brain, and are used as references in spatial normalization or in the development of brain atlases. The accuracy of diffusion templates constructed based on the diffusion tensor (DT) model is limited in regions with complex neuronal micro-architecture. High angular resolution diffusion imaging (HARDI) overcomes limitations of the DT model and is capable of resolving intravoxel heterogeneity. However, when HARDI is combined with multiple-shot sequences to minimize image artifacts, the scan time becomes inappropriate for human brain imaging. In this work, an artifact-free HARDI template of the human brain was developed from low angular resolution multiple-shot diffusion data. The resulting HARDI template was produced in ICBM-152 space based on Turboprop diffusion data, was shown to resolve complex neuronal micro-architecture in regions with intravoxel heterogeneity, and contained fiber orientation information consistent with known human brain anatomy. Copyright © 2014 Elsevier Inc. All rights reserved.

A simple physiologically based pharmacokinetic model evaluating the effect of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saylor, Kyle, E-mail: saylor@vt.edu; Zhang, Chenmi

Physiologically based pharmacokinetic (PBPK) modeling was applied to investigate the effects of anti-nicotine antibodies on nicotine disposition in the brains of rats and humans. Successful construction of both rat and human models was achieved by fitting model outputs to published nicotine concentration time course data in the blood and in the brain. Key parameters presumed to have the most effect on the ability of these antibodies to prevent nicotine from entering the brain were selected for investigation using the human model. These parameters, which included antibody affinity for nicotine, antibody cross-reactivity with cotinine, and antibody concentration, were broken down intomore » different, clinically-derived in silico treatment levels and fed into the human PBPK model. Model predictions suggested that all three parameters, in addition to smoking status, have a sizable impact on anti-nicotine antibodies' ability to prevent nicotine from entering the brain and that the antibodies elicited by current human vaccines do not have sufficient binding characteristics to reduce brain nicotine concentrations. If the antibody binding characteristics achieved in animal studies can similarly be achieved in human studies, however, nicotine vaccine efficacy in terms of brain nicotine concentration reduction is predicted to meet threshold values for alleviating nicotine dependence. - Highlights: • Modelling of nicotine disposition in the presence of anti-nicotine antibodies • Key vaccine efficacy factors are evaluated in silico in rats and in humans. • Model predicts insufficient antibody binding in past human nicotine vaccines. • Improving immunogenicity and antibody specificity may lead to vaccine success.« less

Connectivity profiles reveal the relationship between brain areas for social cognition in human and monkey temporoparietal cortex

PubMed Central

Mars, Rogier B.; Sallet, Jérôme; Neubert, Franz-Xaver; Rushworth, Matthew F. S.

2013-01-01

The human ability to infer the thoughts and beliefs of others, often referred to as “theory of mind,” as well as the predisposition to even consider others, are associated with activity in the temporoparietal junction (TPJ) area. Unlike the case of most human brain areas, we have little sense of whether or how TPJ is related to brain areas in other nonhuman primates. It is not possible to address this question by looking for similar task-related activations in nonhuman primates because there is no evidence that nonhuman primates engage in theory-of-mind tasks in the same manner as humans. Here, instead, we explore the relationship by searching for areas in the macaque brain that interact with other macaque brain regions in the same manner as human TPJ interacts with other human brain regions. In other words, we look for brain regions with similar positions within a distributed neural circuit in the two species. We exploited the fact that human TPJ has a unique functional connectivity profile with cortical areas with known homologs in the macaque. For each voxel in the macaque temporal and parietal cortex we evaluated the similarity of its functional connectivity profile to that of human TPJ. We found that areas in the middle part of the superior temporal cortex, often associated with the processing of faces and other social stimuli, have the most similar connectivity profile. These results suggest that macaque face processing areas and human mentalizing areas might have a similar precursor. PMID:23754406

Neuronal density, size and shape in the human anterior cingulate cortex: a comparison of Nissl and NeuN staining.

PubMed

Gittins, Rebecca; Harrison, Paul J

2004-03-15

There are an increasing number of quantitative morphometric studies of the human cerebral cortex, especially as part of comparative investigations of major psychiatric disorders. In this context, the present study had two aims. First, to provide quantitative data regarding key neuronal morphometric parameters in the anterior cingulate cortex. Second, to compare the results of conventional Nissl staining with those observed after immunostaining with NeuN, an antibody becoming widely used as a selective neuronal marker. We stained adjacent sections of area 24b from 16 adult brains with cresyl violet or NeuN. We measured the density of pyramidal and non-pyramidal neurons, and the size and shape of pyramidal neurons, in laminae II, III, Va, Vb and VI, using two-dimensional counting methods. Strong correlations between the two modes of staining were seen for all variables. However, NeuN gave slightly higher estimates of neuronal density and size, and a more circular perikaryal shape. Brain pH was correlated with neuronal size, measured with both methods, and with neuronal shape. Age and post-mortem interval showed no correlations with any parameter. These data confirm the value of NeuN as a tool for quantitative neuronal morphometric studies in routinely processed human brain tissue. Absolute values are highly correlated between NeuN and cresyl violet stains, but cannot be interchanged. NeuN may be particularly useful when it is important to distinguish small neurons from glia, such as in cytoarchitectural studies of the cerebral cortex in depression and schizophrenia.

EEG functional connectivity is partially predicted by underlying white matter connectivity

PubMed Central

Chu, CJ; Tanaka, N; Diaz, J; Edlow, BL; Wu, O; Hämäläinen, M; Stufflebeam, S; Cash, SS; Kramer, MA.

2015-01-01

Over the past decade, networks have become a leading model to illustrate both the anatomical relationships (structural networks) and the coupling of dynamic physiology (functional networks) linking separate brain regions. The relationship between these two levels of description remains incompletely understood and an area of intense research interest. In particular, it is unclear how cortical currents relate to underlying brain structural architecture. In addition, although theory suggests that brain communication is highly frequency dependent, how structural connections influence overlying functional connectivity in different frequency bands has not been previously explored. Here we relate functional networks inferred from statistical associations between source imaging of EEG activity and underlying cortico-cortical structural brain connectivity determined by probabilistic white matter tractography. We evaluate spontaneous fluctuating cortical brain activity over a long time scale (minutes) and relate inferred functional networks to underlying structural connectivity for broadband signals, as well as in seven distinct frequency bands. We find that cortical networks derived from source EEG estimates partially reflect both direct and indirect underlying white matter connectivity in all frequency bands evaluated. In addition, we find that when structural support is absent, functional connectivity is significantly reduced for high frequency bands compared to low frequency bands. The association between cortical currents and underlying white matter connectivity highlights the obligatory interdependence of functional and structural networks in the human brain. The increased dependence on structural support for the coupling of higher frequency brain rhythms provides new evidence for how underlying anatomy directly shapes emergent brain dynamics at fast time scales. PMID:25534110

Small Worldness in Dense and Weighted Connectomes

NASA Astrophysics Data System (ADS)

Colon-Perez, Luis; Couret, Michelle; Triplett, William; Price, Catherine; Mareci, Thomas

2016-05-01

The human brain is a heterogeneous network of connected functional regions; however, most brain network studies assume that all brain connections can be described in a framework of binary connections. The brain is a complex structure of white matter tracts connected by a wide range of tract sizes, which suggests a broad range of connection strengths. Therefore, the assumption that the connections are binary yields an incomplete picture of the brain. Various thresholding methods have been used to remove spurious connections and reduce the graph density in binary networks. But these thresholds are arbitrary and make problematic the comparison of networks created at different thresholds. The heterogeneity of connection strengths can be represented in graph theory by applying weights to the network edges. Using our recently introduced edge weight parameter, we estimated the topological brain network organization using a complimentary weighted connectivity framework to the traditional framework of a binary network. To examine the reproducibility of brain networks in a controlled condition, we studied the topological network organization of a single healthy individual by acquiring 10 repeated diffusion-weighted magnetic resonance image datasets, over a one-month period on the same scanner, and analyzing these networks with deterministic tractography. We applied a threshold to both the binary and weighted networks and determined that the extra degree of freedom that comes with the framework of weighting network connectivity provides a robust result as any threshold level. The proposed weighted connectivity framework provides a stable result and is able to demonstrate the small world property of brain networks in situations where the binary framework is inadequate and unable to demonstrate this network property.

Contribution of Neuroimaging Studies to Understanding Development of Human Cognitive Brain Functions

PubMed Central

Morita, Tomoyo; Asada, Minoru; Naito, Eiichi

2016-01-01

Humans experience significant physical and mental changes from birth to adulthood, and a variety of perceptual, cognitive and motor functions mature over the course of approximately 20 years following birth. To deeply understand such developmental processes, merely studying behavioral changes is not sufficient; simultaneous investigation of the development of the brain may lead us to a more comprehensive understanding. Recent advances in noninvasive neuroimaging technologies largely contribute to this understanding. Here, it is very important to consider the development of the brain from the perspectives of “structure” and “function” because both structure and function of the human brain mature slowly. In this review, we first discuss the process of structural brain development, i.e., how the structure of the brain, which is crucial when discussing functional brain development, changes with age. Second, we introduce some representative studies and the latest studies related to the functional development of the brain, particularly for visual, facial recognition, and social cognition functions, all of which are important for humans. Finally, we summarize how brain science can contribute to developmental study and discuss the challenges that neuroimaging should address in the future. PMID:27695409

Cell diversity and network dynamics in photosensitive human brain organoids

PubMed Central

Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z.; Sherwood, John L.; Yang, Sung Min; Berger, Daniel; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin; Boyden, Edward S.; Lichtman, Jeff; Williams, Ziv M.; McCarroll, Steven A.; Arlotta, Paola

2017-01-01

In vitro models of the developing brain such as 3D brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, it remains undefined what cells are generated within organoids and to what extent they recapitulate the regional complexity, cellular diversity, and circuit functionality of the brain. Here, we analyzed gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (over 9 months) enabling unprecedented levels of maturity including the formation of dendritic spines and of spontaneously-active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photoreceptor-like cells, which may offer ways to probe the functionality of human neuronal circuits using physiological sensory stimuli. PMID:28445462

Cell diversity and network dynamics in photosensitive human brain organoids.

PubMed

Quadrato, Giorgia; Nguyen, Tuan; Macosko, Evan Z; Sherwood, John L; Min Yang, Sung; Berger, Daniel R; Maria, Natalie; Scholvin, Jorg; Goldman, Melissa; Kinney, Justin P; Boyden, Edward S; Lichtman, Jeff W; Williams, Ziv M; McCarroll, Steven A; Arlotta, Paola

2017-05-04

In vitro models of the developing brain such as three-dimensional brain organoids offer an unprecedented opportunity to study aspects of human brain development and disease. However, the cells generated within organoids and the extent to which they recapitulate the regional complexity, cellular diversity and circuit functionality of the brain remain undefined. Here we analyse gene expression in over 80,000 individual cells isolated from 31 human brain organoids. We find that organoids can generate a broad diversity of cells, which are related to endogenous classes, including cells from the cerebral cortex and the retina. Organoids could be developed over extended periods (more than 9 months), allowing for the establishment of relatively mature features, including the formation of dendritic spines and spontaneously active neuronal networks. Finally, neuronal activity within organoids could be controlled using light stimulation of photosensitive cells, which may offer a way to probe the functionality of human neuronal circuits using physiological sensory stimuli.

Developmental patterns of chimpanzee cerebral tissues provide important clues for understanding the remarkable enlargement of the human brain.

PubMed

Sakai, Tomoko; Matsui, Mie; Mikami, Akichika; Malkova, Ludise; Hamada, Yuzuru; Tomonaga, Masaki; Suzuki, Juri; Tanaka, Masayuki; Miyabe-Nishiwaki, Takako; Makishima, Haruyuki; Nakatsukasa, Masato; Matsuzawa, Tetsuro

2013-02-22

Developmental prolongation is thought to contribute to the remarkable brain enlargement observed in modern humans (Homo sapiens). However, the developmental trajectories of cerebral tissues have not been explored in chimpanzees (Pan troglodytes), even though they are our closest living relatives. To address this lack of information, the development of cerebral tissues was tracked in growing chimpanzees during infancy and the juvenile stage, using three-dimensional magnetic resonance imaging and compared with that of humans and rhesus macaques (Macaca mulatta). Overall, cerebral development in chimpanzees demonstrated less maturity and a more protracted course during prepuberty, as observed in humans but not in macaques. However, the rapid increase in cerebral total volume and proportional dynamic change in the cerebral tissue in humans during early infancy, when white matter volume increases dramatically, did not occur in chimpanzees. A dynamic reorganization of cerebral tissues of the brain during early infancy, driven mainly by enhancement of neuronal connectivity, is likely to have emerged in the human lineage after the split between humans and chimpanzees and to have promoted the increase in brain volume in humans. Our findings may lead to powerful insights into the ontogenetic mechanism underlying human brain enlargement.

Developmental patterns of chimpanzee cerebral tissues provide important clues for understanding the remarkable enlargement of the human brain

PubMed Central

Sakai, Tomoko; Matsui, Mie; Mikami, Akichika; Malkova, Ludise; Hamada, Yuzuru; Tomonaga, Masaki; Suzuki, Juri; Tanaka, Masayuki; Miyabe-Nishiwaki, Takako; Makishima, Haruyuki; Nakatsukasa, Masato; Matsuzawa, Tetsuro

2013-01-01

Developmental prolongation is thought to contribute to the remarkable brain enlargement observed in modern humans (Homo sapiens). However, the developmental trajectories of cerebral tissues have not been explored in chimpanzees (Pan troglodytes), even though they are our closest living relatives. To address this lack of information, the development of cerebral tissues was tracked in growing chimpanzees during infancy and the juvenile stage, using three-dimensional magnetic resonance imaging and compared with that of humans and rhesus macaques (Macaca mulatta). Overall, cerebral development in chimpanzees demonstrated less maturity and a more protracted course during prepuberty, as observed in humans but not in macaques. However, the rapid increase in cerebral total volume and proportional dynamic change in the cerebral tissue in humans during early infancy, when white matter volume increases dramatically, did not occur in chimpanzees. A dynamic reorganization of cerebral tissues of the brain during early infancy, driven mainly by enhancement of neuronal connectivity, is likely to have emerged in the human lineage after the split between humans and chimpanzees and to have promoted the increase in brain volume in humans. Our findings may lead to powerful insights into the ontogenetic mechanism underlying human brain enlargement. PMID:23256194

Metabolic acceleration and the evolution of human brain size and life history.

PubMed

Pontzer, Herman; Brown, Mary H; Raichlen, David A; Dunsworth, Holly; Hare, Brian; Walker, Kara; Luke, Amy; Dugas, Lara R; Durazo-Arvizu, Ramon; Schoeller, Dale; Plange-Rhule, Jacob; Bovet, Pascal; Forrester, Terrence E; Lambert, Estelle V; Thompson, Melissa Emery; Shumaker, Robert W; Ross, Stephen R

2016-05-19

Humans are distinguished from the other living apes in having larger brains and an unusual life history that combines high reproductive output with slow childhood growth and exceptional longevity. This suite of derived traits suggests major changes in energy expenditure and allocation in the human lineage, but direct measures of human and ape metabolism are needed to compare evolved energy strategies among hominoids. Here we used doubly labelled water measurements of total energy expenditure (TEE; kcal day(-1)) in humans, chimpanzees, bonobos, gorillas and orangutans to test the hypothesis that the human lineage has experienced an acceleration in metabolic rate, providing energy for larger brains and faster reproduction without sacrificing maintenance and longevity. In multivariate regressions including body size and physical activity, human TEE exceeded that of chimpanzees and bonobos, gorillas and orangutans by approximately 400, 635 and 820 kcal day(-1), respectively, readily accommodating the cost of humans' greater brain size and reproductive output. Much of the increase in TEE is attributable to humans' greater basal metabolic rate (kcal day(-1)), indicating increased organ metabolic activity. Humans also had the greatest body fat percentage. An increased metabolic rate, along with changes in energy allocation, was crucial in the evolution of human brain size and life history.

Sex differences in brain organization: implications for human communication.

PubMed

Hanske-Petitpierre, V; Chen, A C

1985-12-01

This article reviews current knowledge in two major research domains: sex differences in neuropsychophysiology, and in human communication. An attempt was made to integrate knowledge from several areas of brain research with human communication and to clarify how such a cooperative effort may be beneficial to both fields of study. By combining findings from the area of brain research, a communication paradigm was developed which contends that brain-related sex differences may reside largely in the area of communication of emotion.

Genotype and Ancestry Modulate Brain's DAT Availability in Healthy Humans

PubMed Central

Shumay, Elena; Chen, John; Fowler, Joanna S.; Volkow, Nora D.

2011-01-01

The dopamine transporter (DAT) is a principal regulator of dopaminergic neurotransmission and its gene (the SLC6A3) is a strong biological candidate gene for various behavioral- and neurological disorders. Intense investigation of the link between the SLC6A3 polymorphisms and behavioral phenotypes yielded inconsistent and even contradictory results. Reliance on objective brain phenotype measures, for example, those afforded by brain imaging, might critically improve detection of DAT genotype-phenotype association. Here, we tested the relationship between the DAT brain availability and the SLC6A3 genotypes using an aggregate sample of 95 healthy participants of several imaging studies. These studies employed positron emission tomography (PET) with [11C]cocaine wherein the DAT availability was estimated as Bmax/Kd; while the genotype values were obtained on two repeat polymorphisms - 3-UTR- and intron 8- VNTRs. The main findings are the following: 1) both polymorphisms analyzed as single genetic markers and in combination (haplotype) modulate DAT density in midbrain; 2) ethnic background and age influence the strength of these associations; and 3) age-related changes in DAT availability differ in the 3-UTR and intron8 – genotype groups. PMID:21826203