Adult Human Neurogenesis: From Microscopy to Magnetic Resonance Imaging

PubMed Central

Sierra, Amanda; Encinas, Juan M.; Maletic-Savatic, Mirjana

2011-01-01

Neural stem cells reside in well-defined areas of the adult human brain and are capable of generating new neurons throughout the life span. In rodents, it is well established that the new born neurons are involved in olfaction as well as in certain forms of memory and learning. In humans, the functional relevance of adult human neurogenesis is being investigated, in particular its implication in the etiopathology of a variety of brain disorders. Adult neurogenesis in the human brain was discovered by utilizing methodologies directly imported from the rodent research, such as immunohistological detection of proliferation and cell-type specific biomarkers in postmortem or biopsy tissue. However, in the vast majority of cases, these methods do not support longitudinal studies; thus, the capacity of the putative stem cells to form new neurons under different disease conditions cannot be tested. More recently, new technologies have been specifically developed for the detection and quantification of neural stem cells in the living human brain. These technologies rely on the use of magnetic resonance imaging, available in hospitals worldwide. Although they require further validation in rodents and primates, these new methods hold the potential to test the contribution of adult human neurogenesis to brain function in both health and disease. This review reports on the current knowledge on adult human neurogenesis. We first review the different methods available to assess human neurogenesis, both ex vivo and in vivo and then appraise the changes of adult neurogenesis in human diseases. PMID:21519376

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

Two Dimensional Finite Element Analysis for the Effect of a Pressure Wave in the Human Brain

NASA Astrophysics Data System (ADS)

Ponce L., Ernesto; Ponce S., Daniel

2008-11-01

Brain injuries in people of all ages is a serious, world-wide health problem, with consequences as varied as attention or memory deficits, difficulties in problem-solving, aggressive social behavior, and neuro degenerative diseases such as Alzheimer's and Parkinson's. Brain injuries can be the result of a direct impact, but also pressure waves and direct impulses. The aim of this work is to develop a predictive method to calculate the stress generated in the human brain by pressure waves such as high power sounds. The finite element method is used, combined with elastic wave theory. The predictions of the generated stress levels are compared with the resistance of the arterioles that pervade the brain. The problem was focused to the Chilean mining where there are some accidents happen by detonations and high sound level. There are not formal medical investigation, however these pressure waves could produce human brain damage.

Automating Cell Detection and Classification in Human Brain Fluorescent Microscopy Images Using Dictionary Learning and Sparse Coding

PubMed Central

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A.; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M.

2017-01-01

Background Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. New method Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Results Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. Comparison with existing methods We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. Conclusion The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. PMID:28267565

Skull and cerebrospinal fluid effects on microwave radiation propagation in human brain

NASA Astrophysics Data System (ADS)

Ansari, M. A.; Zarei, M.; Akhlaghipour, N.; Niknam, A. R.

2017-12-01

The determination of microwave absorption distribution in the human brain is necessary for the detection of brain tumors using thermo-acoustic imaging and for removing them using hyperthermia treatment. In contrast to ionizing radiation, hyperthermia treatment can be applied to remove tumors inside the brain without the concern of including secondary malignancies, which typically form from the neuronal cells of the septum pellucidum. The aim of this study is to determine the microwave absorption distribution in an adult human brain and to study the effects of skull and cerebrospinal fluid on the propagation of microwave radiation inside the brain. To this end, we simulate the microwave absorption distribution in a realistic adult brain model (Colin 27) using the mesh-based Monte Carlo (MMC) method. This is because in spite of there being other numerical methods, the MMC does not require a large memory, even for complicated geometries, and its algorithm is simple and easy to implement with low computational cost. The brain model is constructed using high-resolution (1 mm isotropic voxel) and low noise magnetic resonance imaging (MRI) scans and its volume contains 181×217×181 voxels, covering the brain completely. Using the MMC method, the radiative transport equation is solved and the absorbed microwave energy distribution in different brain regions is obtained without any fracture or anomaly. The simulation results show that the skull and cerebrospinal fluid guide the microwave radiation and suppress its penetration through deep brain compartments as a shielding factor. These results reveal that the MMC can be used to predict the amount of required energy to increase the temperature inside the tumour during hyperthermia treatment. Our results also show why a deep tumour inside an adult human brain cannot be efficiently treated using hyperthermia treatment. Finally, the accuracy of the presented numerical method is verified using the signal flow graph technique.

A versatile new technique to clear mouse and human brain

NASA Astrophysics Data System (ADS)

Costantini, Irene; Di Giovanna, Antonino Paolo; Allegra Mascaro, Anna Letizia; Silvestri, Ludovico; Müllenbroich, Marie Caroline; Sacconi, Leonardo; Pavone, Francesco S.

2015-07-01

Large volumes imaging with microscopic resolution is limited by light scattering. In the last few years based on refractive index matching, different clearing approaches have been developed. Organic solvents and water-based optical clearing agents have been used for optical clearing of entire mouse brain. Although these methods guarantee high transparency and preservation of the fluorescence, though present other non-negligible limitations. Tissue transformation by CLARITY allows high transparency, whole brain immunolabelling and structural and molecular preservation. This method however requires a highly expensive refractive index matching solution limiting practical applicability. In this work we investigate the effectiveness of a water-soluble clearing agent, the 2,2'-thiodiethanol (TDE) to clear mouse and human brain. TDE does not quench the fluorescence signal, is compatible with immunostaining and does not introduce any deformation at sub-cellular level. The not viscous nature of the TDE make it a suitable agent to perform brain slicing during serial two-photon (STP) tomography. In fact, by improving penetration depth it reduces tissue slicing, decreasing the acquisition time and cutting artefacts. TDE can also be used as a refractive index medium for CLARITY. The potential of this method has been explored by imaging a whole transgenic mouse brain with the light sheet microscope. Moreover we apply this technique also on blocks of dysplastic human brain tissue transformed with CLARITY and labeled with different antibody. This clearing approach significantly expands the application of single and two-photon imaging, providing a new useful method for quantitative morphological analysis of structure in mouse and human brain.

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

PubMed

Alegro, Maryana; Theofilas, Panagiotis; Nguy, Austin; Castruita, Patricia A; Seeley, William; Heinsen, Helmut; Ushizima, Daniela M; Grinberg, Lea T

2017-04-15

Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks. Copyright © 2017 Elsevier B.V. All rights reserved.

Methodological dimensions of transcranial brain stimulation with the electrical current in human.

PubMed

Rostami, Maryam; Golesorkhi, Mehrshad; Ekhtiari, Hamed

2013-01-01

Transcranial current stimulation (TCS) is a neuromodulation method in which the patient is exposed to a mild electric current (direct or alternating) at 1-2 mA, resulting in an increase or a decrease in the brain excitability. This modification in neural activities can be used as a method for functional human brain mapping with causal inferences. This method might also facilitate the treatments of many neuropsychiatric disorders based on its inexpensive, simple, safe, noninvasive, painless, semi-focal excitatory and inhibitory effects. Given this, a comparison amongst different brain stimulation modalities has been made to determine the potential advantages of the TCS method. In addition, considerable methodological details on using TCS in basic and clinical neuroscience studies in human subjects have been introduced. Technical characteristics of TCS devices and their related accessories with regard to safety concerns have also been well articulated. Finally, some TCS application opportunities have been emphasized, including its potential use in the near future.

An improved high-throughput lipid extraction method for the analysis of human brain lipids.

PubMed

Abbott, Sarah K; Jenner, Andrew M; Mitchell, Todd W; Brown, Simon H J; Halliday, Glenda M; Garner, Brett

2013-03-01

We have developed a protocol suitable for high-throughput lipidomic analysis of human brain samples. The traditional Folch extraction (using chloroform and glass-glass homogenization) was compared to a high-throughput method combining methyl-tert-butyl ether (MTBE) extraction with mechanical homogenization utilizing ceramic beads. This high-throughput method significantly reduced sample handling time and increased efficiency compared to glass-glass homogenizing. Furthermore, replacing chloroform with MTBE is safer (less carcinogenic/toxic), with lipids dissolving in the upper phase, allowing for easier pipetting and the potential for automation (i.e., robotics). Both methods were applied to the analysis of human occipital cortex. Lipid species (including ceramides, sphingomyelins, choline glycerophospholipids, ethanolamine glycerophospholipids and phosphatidylserines) were analyzed via electrospray ionization mass spectrometry and sterol species were analyzed using gas chromatography mass spectrometry. No differences in lipid species composition were evident when the lipid extraction protocols were compared, indicating that MTBE extraction with mechanical bead homogenization provides an improved method for the lipidomic profiling of human brain tissue.

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.

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.

Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD.

PubMed

Atasoy, Selen; Roseman, Leor; Kaelen, Mendel; Kringelbach, Morten L; Deco, Gustavo; Carhart-Harris, Robin L

2017-12-15

Recent studies have started to elucidate the effects of lysergic acid diethylamide (LSD) on the human brain but the underlying dynamics are not yet fully understood. Here we used 'connectome-harmonic decomposition', a novel method to investigate the dynamical changes in brain states. We found that LSD alters the energy and the power of individual harmonic brain states in a frequency-selective manner. Remarkably, this leads to an expansion of the repertoire of active brain states, suggestive of a general re-organization of brain dynamics given the non-random increase in co-activation across frequencies. Interestingly, the frequency distribution of the active repertoire of brain states under LSD closely follows power-laws indicating a re-organization of the dynamics at the edge of criticality. Beyond the present findings, these methods open up for a better understanding of the complex brain dynamics in health and disease.

The impact of poverty on the development of brain networks

PubMed Central

Lipina, Sebastián J.; Posner, Michael I.

2012-01-01

Although the study of brain development in non-human animals is an old one, recent imaging methods have allowed non-invasive studies of the gray and white matter of the human brain over the lifespan. Classic animal studies show clearly that impoverished environments reduce cortical gray matter in relation to complex environments and cognitive and imaging studies in humans suggest which networks may be most influenced by poverty. Studies have been clear in showing the plasticity of many brain systems, but whether sensitivity to learning differs over the lifespan and for which networks is still unclear. A major task for current research is a successful integration of these methods to understand how development and learning shape the neural networks underlying achievements in literacy, numeracy, and attention. This paper seeks to foster further integration by reviewing the current state of knowledge relating brain changes to behavior and indicating possible future directions. PMID:22912613

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.

An automatic method of brain tumor segmentation from MRI volume based on the symmetry of brain and level set method

NASA Astrophysics Data System (ADS)

Li, Xiaobing; Qiu, Tianshuang; Lebonvallet, Stephane; Ruan, Su

2010-02-01

This paper presents a brain tumor segmentation method which automatically segments tumors from human brain MRI image volume. The presented model is based on the symmetry of human brain and level set method. Firstly, the midsagittal plane of an MRI volume is searched, the slices with potential tumor of the volume are checked out according to their symmetries, and an initial boundary of the tumor in the slice, in which the tumor is in the largest size, is determined meanwhile by watershed and morphological algorithms; Secondly, the level set method is applied to the initial boundary to drive the curve evolving and stopping to the appropriate tumor boundary; Lastly, the tumor boundary is projected one by one to its adjacent slices as initial boundaries through the volume for the whole tumor. The experiment results are compared with hand tracking of the expert and show relatively good accordance between both.

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.

Neurophysiology of the esophagus.

PubMed

Brock, Christina; Brokjaer, Anne; Drewes, Asbjørn Mohr; Farmer, Adam D; Frøkjaer, Jens Brøndum; Gregersen, Hans; Lottrup, Christian

2014-09-01

The following, from the 12th OESO World Conference: Cancers of the Esophagus, includes commentaries on the methods and characteristics of esophageal afferents in humans; the pitfalls in characterization of mechanosensitive afferents; the sensitization of esophageal afferents in human studies; the brain source modeling in the understanding of the esophagus-brain axis; the use of evoked brain potentials in the esophagus; and measuring descending inhibition in animal and human studies. © 2014 New York Academy of Sciences.

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

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain.

PubMed

Eide, Per Kristian; Ringstad, Geir

2015-11-01

Recently, the "glymphatic system" of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain.

Time-resolved fluorescence spectroscopy of human brain tumors

NASA Astrophysics Data System (ADS)

Marcu, Laura; Thompson, Reid C.; Garde, Smita; Sedrak, Mark; Black, Keith L.; Yong, William H.

2002-05-01

Fluorescence spectroscopy of the endogenous emission of brain tumors has been researched as a potentially important method for the intraoperative localization of brain tumor margins. In this study, we investigate the use of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) for demarcation of primary brain tumors by studying the time-resolved spectra of gliomas of different histologic grades. Time-resolved fluorescence (3 ns, 337 nm excitation) from excised human brain tumor show differences between the time-resolved emission of malignant glioma and normal brain tissue (gray and white matter). Our findings suggest that brain tumors can be differentiated from normal brain tissue based upon unique time-resolved fluorescence signature.

Analysis of evoked deep brain connectivity.

PubMed

Klimeš, Petr; Janeček, Jiři; Jurák, Pavel; Halámek, Josef; Chládek, Han; Brázdil, Milan

2013-01-01

Establishing dependencies and connectivity among different structures in the human brain is an extremely complex issue. Methods that are often used for connectivity analysis are based on correlation mechanisms. Correlation methods can analyze changes in signal shape or instantaneous power level. Although recent studies imply that observation of results from both groups of methods together can disclose some of the basic functions and behavior of the human brain during mental activity and decision-making, there is no technique covering changes in the shape of signals along with changes in their power levels. We present a method using a time evaluation of the correlation along with a comparison of power levels in every available contact pair from intracranial electrodes placed in deep brain structures. Observing shape changes in signals after stimulation together with their power levels provides us with new information about signal character between different structures in the brain during task-related events - visual stimulation with motor response. The results for a subject with 95 intracerebral contacts used in this paper demonstrate a clear methodology capable of spatially analyzing connectivity among deep brain structures.

SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests

PubMed Central

Serag, Ahmed; Wilkinson, Alastair G.; Telford, Emma J.; Pataky, Rozalia; Sparrow, Sarah A.; Anblagan, Devasuda; Macnaught, Gillian; Semple, Scott I.; Boardman, James P.

2017-01-01

Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38–42 weeks gestational age), children and adolescents (4–17 years) and adults (35–71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course. PMID:28163680

Optical pathology of human brain metastasis of lung cancer using combined resonance Raman and spatial frequency spectroscopies

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Pu, Yang; Cheng, Gangge; Zhou, Lixin; Chen, Jun; Zhu, Ke; Alfano, Robert R.

2016-03-01

Raman spectroscopy has become widely used for diagnostic purpose of breast, lung and brain cancers. This report introduced a new approach based on spatial frequency spectra analysis of the underlying tissue structure at different stages of brain tumor. Combined spatial frequency spectroscopy (SFS), Resonance Raman (RR) spectroscopic method is used to discriminate human brain metastasis of lung cancer from normal tissues for the first time. A total number of thirty-one label-free micrographic images of normal and metastatic brain cancer tissues obtained from a confocal micro- Raman spectroscopic system synchronously with examined RR spectra of the corresponding samples were collected from the identical site of tissue. The difference of the randomness of tissue structures between the micrograph images of metastatic brain tumor tissues and normal tissues can be recognized by analyzing spatial frequency. By fitting the distribution of the spatial frequency spectra of human brain tissues as a Gaussian function, the standard deviation, σ, can be obtained, which was used to generate a criterion to differentiate human brain cancerous tissues from the normal ones using Support Vector Machine (SVM) classifier. This SFS-SVM analysis on micrograph images presents good results with sensitivity (85%), specificity (75%) in comparison with gold standard reports of pathology and immunology. The dual-modal advantages of SFS combined with RR spectroscopy method may open a new way in the neuropathology applications.

Mechanisms of Neurodegeneration and Regeneration in Alcoholism

PubMed Central

Crews, Fulton T.; Nixon, Kim

2009-01-01

Aims: This is a review of preclinical studies covering alcohol-induced brain neuronal death and loss of neurogenesis as well as abstinence-induced brain cell genesis, e.g. brain regeneration. Efforts are made to relate preclinical studies to human studies. Methods: The studies described are preclinical rat experiments using a 4-day binge ethanol treatment known to induce physical dependence to ethanol. Neurodegeneration and cognitive deficits following binge treatment mimic the mild degeneration and cognitive deficits found in humans. Various histological methods are used to follow brain regional degeneration and regeneration. Results: Alcohol-induced degeneration occurs due to neuronal death during alcohol intoxication. Neuronal death is related to increases in oxidative stress in brain that coincide with the induction of proinflammatory cytokines and oxidative enzymes that insult brain. Degeneration is associated with increased NF-κB proinflammatory transcription and decreased CREB transcription. Corticolimbic brain regions are most sensitive to binge-induced degeneration and induce relearning deficits. Drugs that block oxidative stress and NF-κB transcription or increase CREB transcription block binge-induced neurodegeneration, inhibition of neurogenesis and proinflammatory enzyme induction. Regeneration of brain occurs during abstinence following binge ethanol treatment. Bursts of proliferating cells occur across multiple brain regions, with many new microglia across brain after months of abstinence and many new neurons in neurogenic hippocampal dentate gyrus. Brain regeneration may be important to sustain abstinence in humans. Conclusions: Alcohol-induced neurodegeneration occurs primarily during intoxication and is related to increased oxidative stress and proinflammatory proteins that are neurotoxic. Abstinence after binge ethanol intoxication results in brain cell genesis that could contribute to the return of brain function and structure found in abstinent humans. PMID:18940959

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.

Global differential expression of genes located in the Down Syndrome Critical Region in normal human brain

PubMed Central

Montoya, Julio Cesar; Fajardo, Dianora; Peña, Angela; Sánchez, Adalberto; Domínguez, Martha C; Satizábal, José María

2014-01-01

Background: The information of gene expression obtained from databases, have made possible the extraction and analysis of data related with several molecular processes involving not only in brain homeostasis but its disruption in some neuropathologies; principally in Down syndrome and the Alzheimer disease. Objective: To correlate the levels of transcription of 19 genes located in the Down Syndrome Critical Region (DSCR) with their expression in several substructures of normal human brain. Methods: There were obtained expression profiles of 19 DSCR genes in 42 brain substructures, from gene expression values available at the database of the human brain of the Brain Atlas of the Allen Institute for Brain Sciences", (http://human.brain-map.org/). The co-expression patterns of DSCR genes in brain were calculated by using multivariate statistical methods. Results: Highest levels of gene expression were registered at caudate nucleus, nucleus accumbens and putamen among central areas of cerebral cortex. Increased expression levels of RCAN1 that encode by a protein involved in signal transduction process of the CNS were recorded for PCP4 that participates in the binding to calmodulin and TTC3; a protein that is associated with differentiation of neurons. That previously identified brain structures play a crucial role in the learning process, in different class of memory and in motor skills. Conclusion: The precise regulation of DSCR gene expression is crucial to maintain the brain homeostasis, especially in those areas with high levels of gene expression associated with a remarkable process of learning and cognition. PMID:25767303

An automatic rat brain extraction method based on a deformable surface model.

PubMed

Li, Jiehua; Liu, Xiaofeng; Zhuo, Jiachen; Gullapalli, Rao P; Zara, Jason M

2013-08-15

The extraction of the brain from the skull in medical images is a necessary first step before image registration or segmentation. While pre-clinical MR imaging studies on small animals, such as rats, are increasing, fully automatic imaging processing techniques specific to small animal studies remain lacking. In this paper, we present an automatic rat brain extraction method, the Rat Brain Deformable model method (RBD), which adapts the popular human brain extraction tool (BET) through the incorporation of information on the brain geometry and MR image characteristics of the rat brain. The robustness of the method was demonstrated on T2-weighted MR images of 64 rats and compared with other brain extraction methods (BET, PCNN, PCNN-3D). The results demonstrate that RBD reliably extracts the rat brain with high accuracy (>92% volume overlap) and is robust against signal inhomogeneity in the images. Copyright © 2013 Elsevier B.V. All rights reserved.

Lesion studies of human emotion and feeling.

PubMed

Feinstein, Justin S

2013-06-01

The lesion method provides unique insight into how the human brain generates emotion and feeling. Recent work has explored a number of interesting topics including the dissociation of emotional experience from memory in patients with amnesia, the reliability of specific emotional deficits following focal brain damage (including fear and the amygdala), and the investigation of compensatory neural mechanisms in lesion patients. Several detailed case studies have challenged the necessary role of the insular cortex in both awareness and feeling by showing that even in rare instances of complete bilateral insula destruction, the patient remains fully sentient and capable of expressing and feeling emotion. These findings highlight the distributed nature of emotion processing in the human brain and emphasize the importance of utilizing the lesion method for elucidating brain-behavior relationships. Copyright © 2012 Elsevier Ltd. All rights reserved.

MRI with intrathecal MRI gadolinium contrast medium administration: a possible method to assess glymphatic function in human brain

PubMed Central

Ringstad, Geir

2015-01-01

Recently, the “glymphatic system” of the brain has been discovered in rodents, which is a paravascular, transparenchymal route for clearance of excess brain metabolites and distribution of compounds in the cerebrospinal fluid. It has already been demonstrated that intrathecally administered gadolinium (Gd) contrast medium distributes along this route in rats, but so far not in humans. A 27-year-old woman underwent magnetic resonance imaging (MRI) with intrathecal administration of gadobutrol, which distributed throughout her entire brain after 1 and 4.5 h. MRI with intrathecal Gd may become a tool to study glymphatic function in the human brain. PMID:26634147

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

Tomographic brain imaging with nucleolar detail and automatic cell counting

NASA Astrophysics Data System (ADS)

Hieber, Simone E.; Bikis, Christos; Khimchenko, Anna; Schweighauser, Gabriel; Hench, Jürgen; Chicherova, Natalia; Schulz, Georg; Müller, Bert

2016-09-01

Brain tissue evaluation is essential for gaining in-depth insight into its diseases and disorders. Imaging the human brain in three dimensions has always been a challenge on the cell level. In vivo methods lack spatial resolution, and optical microscopy has a limited penetration depth. Herein, we show that hard X-ray phase tomography can visualise a volume of up to 43 mm3 of human post mortem or biopsy brain samples, by demonstrating the method on the cerebellum. We automatically identified 5,000 Purkinje cells with an error of less than 5% at their layer and determined the local surface density to 165 cells per mm2 on average. Moreover, we highlight that three-dimensional data allows for the segmentation of sub-cellular structures, including dendritic tree and Purkinje cell nucleoli, without dedicated staining. The method suggests that automatic cell feature quantification of human tissues is feasible in phase tomograms obtained with isotropic resolution in a label-free manner.

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.

Knowledge-Guided Robust MRI Brain Extraction for Diverse Large-Scale Neuroimaging Studies on Humans and Non-Human Primates

PubMed Central

Wang, Yaping; Nie, Jingxin; Yap, Pew-Thian; Li, Gang; Shi, Feng; Geng, Xiujuan; Guo, Lei; Shen, Dinggang

2014-01-01

Accurate and robust brain extraction is a critical step in most neuroimaging analysis pipelines. In particular, for the large-scale multi-site neuroimaging studies involving a significant number of subjects with diverse age and diagnostic groups, accurate and robust extraction of the brain automatically and consistently is highly desirable. In this paper, we introduce population-specific probability maps to guide the brain extraction of diverse subject groups, including both healthy and diseased adult human populations, both developing and aging human populations, as well as non-human primates. Specifically, the proposed method combines an atlas-based approach, for coarse skull-stripping, with a deformable-surface-based approach that is guided by local intensity information and population-specific prior information learned from a set of real brain images for more localized refinement. Comprehensive quantitative evaluations were performed on the diverse large-scale populations of ADNI dataset with over 800 subjects (55∼90 years of age, multi-site, various diagnosis groups), OASIS dataset with over 400 subjects (18∼96 years of age, wide age range, various diagnosis groups), and NIH pediatrics dataset with 150 subjects (5∼18 years of age, multi-site, wide age range as a complementary age group to the adult dataset). The results demonstrate that our method consistently yields the best overall results across almost the entire human life span, with only a single set of parameters. To demonstrate its capability to work on non-human primates, the proposed method is further evaluated using a rhesus macaque dataset with 20 subjects. Quantitative comparisons with popularly used state-of-the-art methods, including BET, Two-pass BET, BET-B, BSE, HWA, ROBEX and AFNI, demonstrate that the proposed method performs favorably with superior performance on all testing datasets, indicating its robustness and effectiveness. PMID:24489639

Automatic Brain Portion Segmentation From Magnetic Resonance Images of Head Scans Using Gray Scale Transformation and Morphological Operations.

PubMed

Somasundaram, Karuppanagounder; Ezhilarasan, Kamalanathan

2015-01-01

To develop an automatic skull stripping method for magnetic resonance imaging (MRI) of human head scans. The proposed method is based on gray scale transformation and morphological operations. The proposed method has been tested with 20 volumes of normal T1-weighted images taken from Internet Brain Segmentation Repository. Experimental results show that the proposed method gives better results than the popular skull stripping methods Brain Extraction Tool and Brain Surface Extractor. The average value of Jaccard and Dice coefficients are 0.93 and 0.962 respectively. In this article, we have proposed a novel skull stripping method using intensity transformation and morphological operations. This is a low computational complexity method but gives competitive or better results than that of the popular skull stripping methods Brain Surface Extractor and Brain Extraction Tool.

Information flow between interacting human brains: Identification, validation, and relationship to social expertise.

PubMed

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-04-21

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender's and receiver's temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions.

Complexity of EEG-signal in Time Domain - Possible Biomedical Application

NASA Astrophysics Data System (ADS)

Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

2002-07-01

Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

Quantitative measurement of intact alpha-synuclein proteoforms from post-mortem control and Parkinson's disease brain tissue by intact protein mass spectrometry.

PubMed

Kellie, John F; Higgs, Richard E; Ryder, John W; Major, Anthony; Beach, Thomas G; Adler, Charles H; Merchant, Kalpana; Knierman, Michael D

2014-07-23

A robust top down proteomics method is presented for profiling alpha-synuclein species from autopsied human frontal cortex brain tissue from Parkinson's cases and controls. The method was used to test the hypothesis that pathology associated brain tissue will have a different profile of post-translationally modified alpha-synuclein than the control samples. Validation of the sample processing steps, mass spectrometry based measurements, and data processing steps were performed. The intact protein quantitation method features extraction and integration of m/z data from each charge state of a detected alpha-synuclein species and fitting of the data to a simple linear model which accounts for concentration and charge state variability. The quantitation method was validated with serial dilutions of intact protein standards. Using the method on the human brain samples, several previously unreported modifications in alpha-synuclein were identified. Low levels of phosphorylated alpha synuclein were detected in brain tissue fractions enriched for Lewy body pathology and were marginally significant between PD cases and controls (p = 0.03).

Resting-State Functional Connectivity in the Human Connectome Project: Current Status and Relevance to Understanding Psychopathology.

PubMed

Barch, Deanna M

A key tenet of modern psychiatry is that psychiatric disorders arise from abnormalities in brain circuits that support human behavior. Our ability to examine hypotheses around circuit-level abnormalities in psychiatric disorders has been made possible by advances in human neuroimaging technologies. These advances have provided the basis for recent efforts to develop a more complex understanding of the function of brain circuits in health and of their relationship to behavior-providing, in turn, a foundation for our understanding of how disruptions in such circuits contribute to the development of psychiatric disorders. This review focuses on the use of resting-state functional connectivity MRI to assess brain circuits, on the advances generated by the Human Connectome Project, and on how these advances potentially contribute to understanding neural circuit dysfunction in psychopathology. The review gives particular attention to the methods developed by the Human Connectome Project that may be especially relevant to studies of psychopathology; it outlines some of the key findings about what constitutes a brain region; and it highlights new information about the nature and stability of brain circuits. Some of the Human Connectome Project's new findings particularly relevant to psychopathology-about neural circuits and their relationships to behavior-are also presented. The review ends by discussing the extension of Human Connectome Project methods across the lifespan and into manifest illness. Potential treatment implications are also considered.

Finding the "g"-Factor in Brain Structure Using the Method of Correlated Vectors

ERIC Educational Resources Information Center

Colom, Roberto; Jung, Rex E.; Haier, Richard J.

2006-01-01

It is unclear whether brain mechanisms underlying human intelligence are distributed throughout the brain or mainly concentrated in the frontal lobes. Data are inconsistent possibly due, at least in part, to the different ways the construct of intelligence is measured. Here we apply the method of correlated vectors to determine how the general…

Method and apparatus for extraction of low-frequency artifacts from brain waves for alertness detection

DOEpatents

Clapp, Ned E.; Hively, Lee M.

1997-01-01

Methods and apparatus automatically detect alertness in humans by monitoring and analyzing brain wave signals. Steps include: acquiring the brain wave (EEG or MEG) data from the subject, digitizing the data, separating artifact data from raw data, and comparing trends in f-data to alertness indicators, providing notification of inadequate alertness.

Visualization of migration of human cortical neurons generated from induced pluripotent stem cells.

PubMed

Bamba, Yohei; Kanemura, Yonehiro; Okano, Hideyuki; Yamasaki, Mami

2017-09-01

Neuronal migration is considered a key process in human brain development. However, direct observation of migrating human cortical neurons in the fetal brain is accompanied by ethical concerns and is a major obstacle in investigating human cortical neuronal migration. We established a novel system that enables direct visualization of migrating cortical neurons generated from human induced pluripotent stem cells (hiPSCs). We observed the migration of cortical neurons generated from hiPSCs derived from a control and from a patient with lissencephaly. Our system needs no viable brain tissue, which is usually used in slice culture. Migratory behavior of human cortical neuron can be observed more easily and more vividly by its fluorescence and glial scaffold than that by earlier methods. Our in vitro experimental system provides a new platform for investigating development of the human central nervous system and brain malformation. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

PubMed

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Introductory overview of research instruments for recording the electrical activity of neurons in the human brain

NASA Astrophysics Data System (ADS)

Garell, P. C.; Granner, M. A.; Noh, M. D.; Howard, M. A.; Volkov, I. O.; Gillies, G. T.

1998-12-01

Scientific advancement is often spurred by the development of new instruments for investigation. Over the last several decades, many new instruments have been produced to further our understanding of the physiology of the human brain. We present a partial overview of some of these instruments, paying particular attention to those which record the electrical activity of the human brain. We preface the review with a brief primer on neuroanatomy and physiology, followed by a discussion of the latest types of apparatus used to investigate various properties of the central nervous system. A special focus is on microelectrode investigations that employ both intracellular and extracellular methods of recording the electrical activity of single neurons; another is on the modern electroencephalographic, electrocorticographic, and magnetoencephalographic methods used to study the spontaneous and evoked field potentials of the brain. Some examples of clinical applications are included, where appropriate.

Neuronal Correlation Parameter and the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System.

PubMed

Haranas, Ioannis; Gkigkitzis, Ioannis; Kotsireas, Ilias; Austerlitz, Carlos

2017-01-01

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition.

Fiber tracking of brain white matter based on graph theory.

PubMed

Lu, Meng

2015-01-01

Brain white matter tractography is reconstructed via diffusion-weighted magnetic resonance images. Due to the complex structure of brain white matter fiber bundles, fiber crossing and fiber branching are abundant in human brain. And regular methods with diffusion tensor imaging (DTI) can't accurately handle this problem. the biggest problems of the brain tractography. Therefore, this paper presented a novel brain white matter tractography method based on graph theory, so the fiber tracking between two voxels is transformed into locating the shortest path in a graph. Besides, the presented method uses Q-ball imaging (QBI) as the source data instead of DTI, because QBI can provide accurate information about multiple fiber crossing and branching in one voxel using orientation distribution function (ODF). Experiments showed that the presented method can accurately handle the problem of brain white matter fiber crossing and branching, and reconstruct brain tractograhpy both in phantom data and real brain data.

Recent Research into the Hemisphericity of the Human Brain and the Implications of Those Findings in the Teaching of Reading.

ERIC Educational Resources Information Center

McLendon, Gloria H.

Research data in neurosurgery, neuropsychology, and neurolinguistics indicate that the human brain is lateralized toward one of two methods of information processing, and that, in most humans, the language bias appears to be a left hemisphere function, while the visiospatial bias belongs to the right. Furthermore, the left hemisphere seems to…

Glutathione in the human brain: Review of its roles and measurement by magnetic resonance spectroscopy.

PubMed

Rae, Caroline D; Williams, Stephen R

2017-07-15

We review the transport, synthesis and catabolism of glutathione in the brain as well as its compartmentation and biochemistry in different brain cells. The major reactions involving glutathione are reviewed and the factors limiting its availability in brain cells are discussed. We also describe and critique current methods for measuring glutathione in the human brain using magnetic resonance spectroscopy, and review the literature on glutathione measurements in healthy brains and in neurological, psychiatric, neurodegenerative and neurodevelopmental conditions In summary: Healthy human brain glutathione concentration is ∼1-2 mM, but it varies by brain region, with evidence of gender differences and age effects; in neurological disease glutathione appears reduced in multiple sclerosis, motor neurone disease and epilepsy, while being increased in meningiomas; in psychiatric disease the picture is complex and confounded by methodological differences, regional effects, length of disease and drug-treatment. Both increases and decreases in glutathione have been reported in depression and schizophrenia. In Alzheimer's disease and mild cognitive impairment there is evidence for a decrease in glutathione compared to age-matched healthy controls. Improved methods to measure glutathione in vivo will provide better precision in glutathione determination and help resolve the complex biochemistry of this molecule in health and disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Regional Homogeneity

PubMed Central

Jiang, Lili; Zuo, Xi-Nian

2015-01-01

Much effort has been made to understand the organizational principles of human brain function using functional magnetic resonance imaging (fMRI) methods, among which resting-state fMRI (rfMRI) is an increasingly recognized technique for measuring the intrinsic dynamics of the human brain. Functional connectivity (FC) with rfMRI is the most widely used method to describe remote or long-distance relationships in studies of cerebral cortex parcellation, interindividual variability, and brain disorders. In contrast, local or short-distance functional interactions, especially at a scale of millimeters, have rarely been investigated or systematically reviewed like remote FC, although some local FC algorithms have been developed and applied to the discovery of brain-based changes under neuropsychiatric conditions. To fill this gap between remote and local FC studies, this review will (1) briefly survey the history of studies on organizational principles of human brain function; (2) propose local functional homogeneity as a network centrality to characterize multimodal local features of the brain connectome; (3) render a neurobiological perspective on local functional homogeneity by linking its temporal, spatial, and individual variability to information processing, anatomical morphology, and brain development; and (4) discuss its role in performing connectome-wide association studies and identify relevant challenges, and recommend its use in future brain connectomics studies. PMID:26170004

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

13C MRS of Human Brain at 7 Tesla Using [2-13C]Glucose Infusion and Low Power Broadband Stochastic Proton Decoupling

PubMed Central

Li, Shizhe; An, Li; Yu, Shao; Araneta, Maria Ferraris; Johnson, Christopher S.; Wang, Shumin; Shen, Jun

2015-01-01

Purpose 13C magnetic resonance spectroscopy (MRS) of human brain at 7 Tesla (T) may pose patient safety issues due to high RF power deposition for proton decoupling. The purpose of present work is to study the feasibility of in vivo 13C MRS of human brain at 7 T using broadband low RF power proton decoupling. Methods Carboxylic/amide 13C MRS of human brain by broadband stochastic proton decoupling was demonstrated on a 7 T scanner. RF safety was evaluated using the finite-difference time-domain method. 13C signal enhancement by nuclear Overhauser effect (NOE) and proton decoupling was evaluated in both phantoms and in vivo. Results At 7 T, the peak amplitude of carboxylic/amide 13C signals was increased by a factor of greater than 4 due to the combined effects of NOE and proton decoupling. The 7 T 13C MRS technique used decoupling power and average transmit power of less than 35 W and 3.6 W, respectively. Conclusion In vivo 13C MRS studies of human brain can be performed at 7 T well below the RF safety threshold by detecting carboxylic/amide carbons with broadband stochastic proton decoupling. PMID:25917936

Method and apparatus for extraction of low-frequency artifacts from brain waves for alertness detection

DOEpatents

Clapp, N.E.; Hively, L.M.

1997-05-06

Methods and apparatus automatically detect alertness in humans by monitoring and analyzing brain wave signals. Steps include: acquiring the brain wave (EEG or MEG) data from the subject, digitizing the data, separating artifact data from raw data, and comparing trends in f-data to alertness indicators, providing notification of inadequate alertness. 4 figs.

Brain Injury Differences in Frontal Impact Crash Using Different Simulation Strategies

PubMed Central

Ma, Chunsheng; Shen, Ming; Li, Peiyu; Zhang, Jinhuan

2015-01-01

In the real world crashes, brain injury is one of the leading causes of deaths. Using isolated human head finite element (FE) model to study the brain injury patterns and metrics has been a simplified methodology widely adopted, since it costs significantly lower computation resources than a whole human body model does. However, the degree of precision of this simplification remains questionable. This study compared these two kinds of methods: (1) using a whole human body model carried on the sled model and (2) using an isolated head model with prescribed head motions, to study the brain injury. The distribution of the von Mises stress (VMS), maximum principal strain (MPS), and cumulative strain damage measure (CSDM) was used to compare the two methods. The results showed that the VMS of brain mainly concentrated at the lower cerebrum and occipitotemporal region close to the cerebellum. The isolated head modelling strategy predicted higher levels of MPS and CSDM 5%, while the difference is small in CSDM 10% comparison. It suggests that isolated head model may not equivalently reflect the strain levels below the 10% compared to the whole human body model. PMID:26495029

Handedness- and brain size-related efficiency differences in small-world brain networks: a resting-state functional magnetic resonance imaging study.

PubMed

Li, Meiling; Wang, Junping; Liu, Feng; Chen, Heng; Lu, Fengmei; Wu, Guorong; Yu, Chunshui; Chen, Huafu

2015-05-01

The human brain has been described as a complex network, which integrates information with high efficiency. However, the relationships between the efficiency of human brain functional networks and handedness and brain size remain unclear. Twenty-one left-handed and 32 right-handed healthy subjects underwent a resting-state functional magnetic resonance imaging scan. The whole brain functional networks were constructed by thresholding Pearson correlation matrices of 90 cortical and subcortical regions. Graph theory-based methods were employed to further analyze their topological properties. As expected, all participants demonstrated small-world topology, suggesting a highly efficient topological structure. Furthermore, we found that smaller brains showed higher local efficiency, whereas larger brains showed higher global efficiency, reflecting a suitable efficiency balance between local specialization and global integration of brain functional activity. Compared with right-handers, significant alterations in nodal efficiency were revealed in left-handers, involving the anterior and median cingulate gyrus, middle temporal gyrus, angular gyrus, and amygdala. Our findings indicated that the functional network organization in the human brain was associated with handedness and brain size.

Study on the application of MRF and the D-S theory to image segmentation of the human brain and quantitative analysis of the brain tissue

NASA Astrophysics Data System (ADS)

Guan, Yihong; Luo, Yatao; Yang, Tao; Qiu, Lei; Li, Junchang

2012-01-01

The features of the spatial information of Markov random field image was used in image segmentation. It can effectively remove the noise, and get a more accurate segmentation results. Based on the fuzziness and clustering of pixel grayscale information, we find clustering center of the medical image different organizations and background through Fuzzy cmeans clustering method. Then we find each threshold point of multi-threshold segmentation through two dimensional histogram method, and segment it. The features of fusing multivariate information based on the Dempster-Shafer evidence theory, getting image fusion and segmentation. This paper will adopt the above three theories to propose a new human brain image segmentation method. Experimental result shows that the segmentation result is more in line with human vision, and is of vital significance to accurate analysis and application of tissues.

[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.

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

Task-Related Edge Density (TED)—A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain

PubMed Central

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach “Task-related Edge Density” (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function. PMID:27341204

Task-Related Edge Density (TED)-A New Method for Revealing Dynamic Network Formation in fMRI Data of the Human Brain.

PubMed

Lohmann, Gabriele; Stelzer, Johannes; Zuber, Verena; Buschmann, Tilo; Margulies, Daniel; Bartels, Andreas; Scheffler, Klaus

2016-01-01

The formation of transient networks in response to external stimuli or as a reflection of internal cognitive processes is a hallmark of human brain function. However, its identification in fMRI data of the human brain is notoriously difficult. Here we propose a new method of fMRI data analysis that tackles this problem by considering large-scale, task-related synchronisation networks. Networks consist of nodes and edges connecting them, where nodes correspond to voxels in fMRI data, and the weight of an edge is determined via task-related changes in dynamic synchronisation between their respective times series. Based on these definitions, we developed a new data analysis algorithm that identifies edges that show differing levels of synchrony between two distinct task conditions and that occur in dense packs with similar characteristics. Hence, we call this approach "Task-related Edge Density" (TED). TED proved to be a very strong marker for dynamic network formation that easily lends itself to statistical analysis using large scale statistical inference. A major advantage of TED compared to other methods is that it does not depend on any specific hemodynamic response model, and it also does not require a presegmentation of the data for dimensionality reduction as it can handle large networks consisting of tens of thousands of voxels. We applied TED to fMRI data of a fingertapping and an emotion processing task provided by the Human Connectome Project. TED revealed network-based involvement of a large number of brain areas that evaded detection using traditional GLM-based analysis. We show that our proposed method provides an entirely new window into the immense complexity of human brain function.

Stepwise Connectivity of the Modal Cortex Reveals the Multimodal Organization of the Human Brain

PubMed Central

Sepulcre, Jorge; Sabuncu, Mert R.; Yeo, Thomas B.; Liu, Hesheng; Johnson, Keith A.

2012-01-01

How human beings integrate information from external sources and internal cognition to produce a coherent experience is still not well understood. During the past decades, anatomical, neurophysiological and neuroimaging research in multimodal integration have stood out in the effort to understand the perceptual binding properties of the brain. Areas in the human lateral occipito-temporal, prefrontal and posterior parietal cortices have been associated with sensory multimodal processing. Even though this, rather patchy, organization of brain regions gives us a glimpse of the perceptual convergence, the articulation of the flow of information from modality-related to the more parallel cognitive processing systems remains elusive. Using a method called Stepwise Functional Connectivity analysis, the present study analyzes the functional connectome and transitions from primary sensory cortices to higher-order brain systems. We identify the large-scale multimodal integration network and essential connectivity axes for perceptual integration in the human brain. PMID:22855814

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.

Human brain mapping: A systematic comparison of parcellation methods for the human cerebral cortex.

PubMed

Arslan, Salim; Ktena, Sofia Ira; Makropoulos, Antonios; Robinson, Emma C; Rueckert, Daniel; Parisot, Sarah

2018-04-15

The macro-connectome elucidates the pathways through which brain regions are structurally connected or functionally coupled to perform a specific cognitive task. It embodies the notion of representing and understanding all connections within the brain as a network, while the subdivision of the brain into interacting functional units is inherent in its architecture. As a result, the definition of network nodes is one of the most critical steps in connectivity network analysis. Although brain atlases obtained from cytoarchitecture or anatomy have long been used for this task, connectivity-driven methods have arisen only recently, aiming to delineate more homogeneous and functionally coherent regions. This study provides a systematic comparison between anatomical, connectivity-driven and random parcellation methods proposed in the thriving field of brain parcellation. Using resting-state functional MRI data from the Human Connectome Project and a plethora of quantitative evaluation techniques investigated in the literature, we evaluate 10 subject-level and 24 groupwise parcellation methods at different resolutions. We assess the accuracy of parcellations from four different aspects: (1) reproducibility across different acquisitions and groups, (2) fidelity to the underlying connectivity data, (3) agreement with fMRI task activation, myelin maps, and cytoarchitectural areas, and (4) network analysis. This extensive evaluation of different parcellations generated at the subject and group level highlights the strengths and shortcomings of the various methods and aims to provide a guideline for the choice of parcellation technique and resolution according to the task at hand. The results obtained in this study suggest that there is no optimal method able to address all the challenges faced in this endeavour simultaneously. Copyright © 2017 Elsevier Inc. All rights reserved.

In vivo Magnetic Resonance Spectroscopy of cerebral glycogen metabolism in animals and humans.

PubMed

Khowaja, Ameer; Choi, In-Young; Seaquist, Elizabeth R; Öz, Gülin

2015-02-01

Glycogen serves as an important energy reservoir in the human body. Despite the abundance of glycogen in the liver and skeletal muscles, its concentration in the brain is relatively low, hence its significance has been questioned. A major challenge in studying brain glycogen metabolism has been the lack of availability of non-invasive techniques for quantification of brain glycogen in vivo. Invasive methods for brain glycogen quantification such as post mortem extraction following high energy microwave irradiation are not applicable in the human brain. With the advent of (13)C Magnetic Resonance Spectroscopy (MRS), it has been possible to measure brain glycogen concentrations and turnover in physiological conditions, as well as under the influence of stressors such as hypoglycemia and visual stimulation. This review presents an overview of the principles of the (13)C MRS methodology and its applications in both animals and humans to further our understanding of glycogen metabolism under normal physiological and pathophysiological conditions such as hypoglycemia unawareness.

In vivo Magnetic Resonance Spectroscopy of cerebral glycogen metabolism in animals and humans

PubMed Central

Khowaja, Ameer; Choi, In-Young; Seaquist, Elizabeth R.; Öz, Gülin

2015-01-01

Glycogen serves as an important energy reservoir in the human body. Despite the abundance of glycogen in the liver and skeletal muscles, its concentration in the brain is relatively low, hence its significance has been questioned. A major challenge in studying brain glycogen metabolism has been the lack of availability of non-invasive techniques for quantification of brain glycogen in vivo. Invasive methods for brain glycogen quantification such as post mortem extraction following high energy microwave irradiation are not applicable in the human brain. With the advent of 13C Magnetic Resonance Spectroscopy (MRS), it has been possible to measure brain glycogen concentrations and turnover in physiological conditions, as well as under the influence of stressors such as hypoglycemia and visual stimulation. This review presents an overview of the principles of the 13C MRS methodology and its applications in both animals and humans to further our understanding of glycogen metabolism under normal physiological and pathophysiological conditions such as hypoglycemia unawareness. PMID:24676563

Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities. To propose a method that effectively segments brain tumor from MR images and to evaluate the performance of unsupervised optimal fuzzy clustering (UOFC) algorithm for segmentation of brain tumor from MR images. Segmentation is done by preprocessing the MR image to standardize intensity inhomogeneities followed by feature extraction, feature fusion and clustering. Different validation measures are used to evaluate the performance of the proposed method using different clustering algorithms. The proposed method using UOFC algorithm produces high sensitivity (96%) and low specificity (4%) compared to other clustering methods. Validation results clearly show that the proposed method with UOFC algorithm effectively segments brain tumor from MR images.

Expansion of Multipotent Stem Cells from the Adult Human Brain

PubMed Central

Murrell, Wayne; Palmero, Emily; Bianco, John; Stangeland, Biljana; Joel, Mrinal; Paulson, Linda; Thiede, Bernd; Grieg, Zanina; Ramsnes, Ingunn; Skjellegrind, Håvard K.; Nygård, Ståle; Brandal, Petter; Sandberg, Cecilie; Vik-Mo, Einar; Palmero, Sheryl; Langmoen, Iver A.

2013-01-01

The discovery of stem cells in the adult human brain has revealed new possible scenarios for treatment of the sick or injured brain. Both clinical use of and preclinical research on human adult neural stem cells have, however, been seriously hampered by the fact that it has been impossible to passage these cells more than a very few times and with little expansion of cell numbers. Having explored a number of alternative culturing conditions we here present an efficient method for the establishment and propagation of human brain stem cells from whatever brain tissue samples we have tried. We describe virtually unlimited expansion of an authentic stem cell phenotype. Pluripotency proteins Sox2 and Oct4 are expressed without artificial induction. For the first time multipotency of adult human brain-derived stem cells is demonstrated beyond tissue boundaries. We characterize these cells in detail in vitro including microarray and proteomic approaches. Whilst clarification of these cells’ behavior is ongoing, results so far portend well for the future repair of tissues by transplantation of an adult patient’s own-derived stem cells. PMID:23967194

The effects of gut microbiota on CNS function in humans

PubMed Central

Tillisch, Kirsten

2014-01-01

The role of the gastrointestinal microbiota in human brain development and function is an area of increasing interest and research. Preclinical models suggest a role for the microbiota in broad aspects of human health, including mood, cognition, and chronic pain. Early human studies suggest that altering the microbiota with beneficial bacteria, or probiotics, can lead to changes in brain function, as well as subjective reports of mood. As the mechanisms of bidirectional communication between the brain and microbiota are better understood, it is expected that these pathways will be harnessed to provide novel methods to enhance health and treat disease. PMID:24838095

Colorization and Automated Segmentation of Human T2 MR Brain Images for Characterization of Soft Tissues

PubMed Central

Attique, Muhammad; Gilanie, Ghulam; Hafeez-Ullah; Mehmood, Malik S.; Naweed, Muhammad S.; Ikram, Masroor; Kamran, Javed A.; Vitkin, Alex

2012-01-01

Characterization of tissues like brain by using magnetic resonance (MR) images and colorization of the gray scale image has been reported in the literature, along with the advantages and drawbacks. Here, we present two independent methods; (i) a novel colorization method to underscore the variability in brain MR images, indicative of the underlying physical density of bio tissue, (ii) a segmentation method (both hard and soft segmentation) to characterize gray brain MR images. The segmented images are then transformed into color using the above-mentioned colorization method, yielding promising results for manual tracing. Our color transformation incorporates the voxel classification by matching the luminance of voxels of the source MR image and provided color image by measuring the distance between them. The segmentation method is based on single-phase clustering for 2D and 3D image segmentation with a new auto centroid selection method, which divides the image into three distinct regions (gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using prior anatomical knowledge). Results have been successfully validated on human T2-weighted (T2) brain MR images. The proposed method can be potentially applied to gray-scale images from other imaging modalities, in bringing out additional diagnostic tissue information contained in the colorized image processing approach as described. PMID:22479421

Swift Acetate Glial Assay (SAGA): an accelerated human ¹³C MRS brain exam for clinical diagnostic use.

PubMed

Sailasuta, Napapon; Tran, Thao T; Harris, Kent C; Ross, B D

2010-12-01

We demonstrate a robust procedure for the quantitative characterization of glial metabolism in human brain. In the past, the slope of the uptake and production of enriched label at steady state were used to determine metabolic rates, requiring the patient to be in the magnet for 120-160 min. In the present method, (13)C cerebral metabolite profiles were acquired at steady state alone on a routine clinical MR scanner in 25.6 min. Results obtained from the new short method (SAGA) were comparable to those achieved in a conventional, long method and effective for determination of glial metabolic rate in posterior-parietal and frontal brain regions. Copyright © 2010 Elsevier Inc. All rights reserved.

Information flow between interacting human brains: Identification, validation, and relationship to social expertise

PubMed Central

Bilek, Edda; Ruf, Matthias; Schäfer, Axel; Akdeniz, Ceren; Calhoun, Vince D.; Schmahl, Christian; Demanuele, Charmaine; Tost, Heike; Kirsch, Peter; Meyer-Lindenberg, Andreas

2015-01-01

Social interactions are fundamental for human behavior, but the quantification of their neural underpinnings remains challenging. Here, we used hyperscanning functional MRI (fMRI) to study information flow between brains of human dyads during real-time social interaction in a joint attention paradigm. In a hardware setup enabling immersive audiovisual interaction of subjects in linked fMRI scanners, we characterize cross-brain connectivity components that are unique to interacting individuals, identifying information flow between the sender’s and receiver’s temporoparietal junction. We replicate these findings in an independent sample and validate our methods by demonstrating that cross-brain connectivity relates to a key real-world measure of social behavior. Together, our findings support a central role of human-specific cortical areas in the brain dynamics of dyadic interactions and provide an approach for the noninvasive examination of the neural basis of healthy and disturbed human social behavior with minimal a priori assumptions. PMID:25848050

Human connectome module pattern detection using a new multi-graph MinMax cut model.

PubMed

De, Wang; Wang, Yang; Nie, Feiping; Yan, Jingwen; Cai, Weidong; Saykin, Andrew J; Shen, Li; Huang, Heng

2014-01-01

Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding the large-scale brain networks that underlie higher-level cognition in human. However, suitable computational network analysis tools are still lacking in human connectome research. To address this problem, we propose a novel multi-graph min-max cut model to detect the consistent network modules from the brain connectivity networks of all studied subjects. A new multi-graph MinMax cut model is introduced to solve this challenging computational neuroscience problem and the efficient optimization algorithm is derived. In the identified connectome module patterns, each network module shows similar connectivity patterns in all subjects, which potentially associate to specific brain functions shared by all subjects. We validate our method by analyzing the weighted fiber connectivity networks. The promising empirical results demonstrate the effectiveness of our method.

Linking brain, mind and behavior.

PubMed

Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

A Novel Method for Quantifying Human In Situ Whole Brain Deformation under Rotational Loading Using Sonomicrometry.

PubMed

Alshareef, Ahmed; Giudice, J Sebastian; Forman, Jason; Salzar, Robert S; Panzer, Matthew B

2018-03-01

Traumatic brain injuries (TBI) are one of the least understood injuries to the body. Finite element (FE) models of the brain have been crucial for understanding concussion and for developing injury mitigation systems; however, the experimental brain deformation data currently used to validate these models are limited. The objective of this study was to develop a methodology for the investigation of in situ three-dimensional brain deformation during pure rotational loading of the head, using sonomicrometry. Sonomicrometry uses ultrasonic pulses to measure the dynamic distances between piezoelectric crystals implanted in any sound-transmitting media. A human cadaveric head-neck specimen was acquired 14 h postmortem and was instrumented with an array of 32 small sonomicrometry crystals embedded in the head: 24 crystals were implanted in the brain, and 8 were fixed to the inner skull. A dynamic rotation was then applied to the head using a closed-loop controlled test device. Four pulses with different severity levels were applied around three orthogonal anatomical axes of rotation. A repeated test of the highest severity rotation was conducted in each axis to assess repeatability. All tests were completed within 56 h postmortem. Overall, the combined experimental and sonomicrometry methods were demonstrated to reliably and repeatedly capture three-dimensional dynamic deformation of an intact human brain. These methods provide a framework for using sonomicrometry to acquire multidimensional experimental data required for FE model development and validation, and will lend insight into the deformations sustained by the brain during impact.

IMAGING BRAIN SIGNAL TRANSDUCTION AND METABOLISM VIA ARACHIDONIC AND DOCOSAHEXAENOIC ACID IN ANIMALS AND HUMANS

PubMed Central

Basselin, Mireille; Ramadan, Epolia; Rapoport, Stanley I.

2012-01-01

The polyunsaturated fatty acids (PUFAs), arachidonic acid (AA, 20:4n-6) and docosahexaenoic acid (DHA, 22:6n-3), important second messengers in brain, are released from membrane phospholipid following receptor-mediated activation of specific phospholipase A2 (PLA2) enzymes. We developed an in vivo method in rodents using quantitative autoradiography to image PUFA incorporation into brain from plasma, and showed that their incorporation rates equal their rates of metabolic consumption by brain. Thus, quantitative imaging of unesterified plasma AA or DHA incorporation into brain can be used as a biomarker of brain PUFA metabolism and neurotransmission. We have employed our method to image and quantify effects of mood stabilizers on brain AA/DHA incorporation during neurotransmission by muscarinic M1,3,5, serotonergic 5-HT2A/2C, dopaminergic D2-like (D2, D3, D4) or glutamatergic N-methyl-D-aspartic acid (NMDA) receptors, and effects of inhibition of acetylcholinesterase, of selective serotonin and dopamine reuptake transporter inhibitors, of neuroinflammation (HIV-1 and lipopolysaccharide) and excitotoxicity, and in genetically modified rodents. The method has been extended for the use with positron emission tomography (PET), and can be employed to determine how human brain AA/DHA signaling and consumption are influenced by diet, aging, disease and genetics. PMID:22178644

Intergenerational Neuroimaging of Human Brain Circuitry

PubMed Central

Ho, Tiffany C.; Sanders, Stephan J.; Gotlib, Ian H.; Hoeft, Fumiko

2016-01-01

Neuroscientists are increasingly using advanced neuroimaging methods to elucidate the intergenerational transmission of human brain circuitry. This new line of work promises to shed insight into the ontogeny of complex behavioral traits, including psychiatric disorders, and possible mechanisms of transmission. Here, we highlight recent intergenerational neuroimaging studies and provide recommendations for future work. PMID:27623194

Graph Theory at the Service of Electroencephalograms.

PubMed

Iakovidou, Nantia D

2017-04-01

The brain is one of the largest and most complex organs in the human body and EEG is a noninvasive electrophysiological monitoring method that is used to record the electrical activity of the brain. Lately, the functional connectivity in human brain has been regarded and studied as a complex network using EEG signals. This means that the brain is studied as a connected system where nodes, or units, represent different specialized brain regions and links, or connections, represent communication pathways between the nodes. Graph theory and theory of complex networks provide a variety of measures, methods, and tools that can be useful to efficiently model, analyze, and study EEG networks. This article is addressed to computer scientists who wish to be acquainted and deal with the study of EEG data and also to neuroscientists who would like to become familiar with graph theoretic approaches and tools to analyze EEG data.

A stable and reproducible human blood-brain barrier model derived from hematopoietic stem cells.

PubMed

Cecchelli, Romeo; Aday, Sezin; Sevin, Emmanuel; Almeida, Catarina; Culot, Maxime; Dehouck, Lucie; Coisne, Caroline; Engelhardt, Britta; Dehouck, Marie-Pierre; Ferreira, Lino

2014-01-01

The human blood brain barrier (BBB) is a selective barrier formed by human brain endothelial cells (hBECs), which is important to ensure adequate neuronal function and protect the central nervous system (CNS) from disease. The development of human in vitro BBB models is thus of utmost importance for drug discovery programs related to CNS diseases. Here, we describe a method to generate a human BBB model using cord blood-derived hematopoietic stem cells. The cells were initially differentiated into ECs followed by the induction of BBB properties by co-culture with pericytes. The brain-like endothelial cells (BLECs) express tight junctions and transporters typically observed in brain endothelium and maintain expression of most in vivo BBB properties for at least 20 days. The model is very reproducible since it can be generated from stem cells isolated from different donors and in different laboratories, and could be used to predict CNS distribution of compounds in human. Finally, we provide evidence that Wnt/β-catenin signaling pathway mediates in part the BBB inductive properties of pericytes.

Imaging Human Brain Perfusion with Inhaled Hyperpolarized 129Xe MR Imaging.

PubMed

Rao, Madhwesha R; Stewart, Neil J; Griffiths, Paul D; Norquay, Graham; Wild, Jim M

2018-02-01

Purpose To evaluate the feasibility of directly imaging perfusion of human brain tissue by using magnetic resonance (MR) imaging with inhaled hyperpolarized xenon 129 ( 129 Xe). Materials and Methods In vivo imaging with 129 Xe was performed in three healthy participants. The combination of a high-yield spin-exchange optical pumping 129 Xe polarizer, custom-built radiofrequency coils, and an optimized gradient-echo MR imaging protocol was used to achieve signal sensitivity sufficient to directly image hyperpolarized 129 Xe dissolved in the human brain. Conventional T1-weighted proton (hydrogen 1 [ 1 H]) images and perfusion images by using arterial spin labeling were obtained for comparison. Results Images of 129 Xe uptake were obtained with a signal-to-noise ratio of 31 ± 9 and demonstrated structural similarities to the gray matter distribution on conventional T1-weighted 1 H images and to perfusion images from arterial spin labeling. Conclusion Hyperpolarized 129 Xe MR imaging is an injection-free means of imaging the perfusion of cerebral tissue. The proposed method images the uptake of inhaled xenon gas to the extravascular brain tissue compartment across the intact blood-brain barrier. This level of sensitivity is not readily available with contemporary MR imaging methods. © RSNA, 2017.

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.

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

Quantitative Susceptibility Mapping of Human Brain Reflects Spatial Variation in Tissue Composition

PubMed Central

Li, Wei; Wu, Bing; Liu, Chunlei

2011-01-01

Image phase from gradient echo MRI provides a unique contrast that reflects brain tissue composition variations, such as iron and myelin distribution. Phase imaging is emerging as a powerful tool for the investigation of functional brain anatomy and disease diagnosis. However, the quantitative value of phase is compromised by its nonlocal and orientation dependent properties. There is an increasing need for reliable quantification of magnetic susceptibility, the intrinsic property of tissue. In this study, we developed a novel and accurate susceptibility mapping method that is also phase-wrap insensitive. The proposed susceptibility mapping method utilized two complementary equations: (1) the Fourier relationship of phase and magnetic susceptibility; and (2) the first-order partial derivative of the first equation in the spatial frequency domain. In numerical simulation, this method reconstructed the susceptibility map almost free of streaking artifact. Further, the iterative implementation of this method allowed for high quality reconstruction of susceptibility maps of human brain in vivo. The reconstructed susceptibility map provided excellent contrast of iron-rich deep nuclei and white matter bundles from surrounding tissues. Further, it also revealed anisotropic magnetic susceptibility in brain white matter. Hence, the proposed susceptibility mapping method may provide a powerful tool for the study of brain physiology and pathophysiology. Further elucidation of anisotropic magnetic susceptibility in vivo may allow us to gain more insight into the white matter microarchitectures. PMID:21224002

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

Rat model of blood-brain barrier disruption to allow targeted neurovascular therapeutics.

PubMed

Martin, Jacob A; Maris, Alexander S; Ehtesham, Moneeb; Singer, Robert J

2012-11-30

Endothelial cells with tight junctions along with the basement membrane and astrocyte end feet surround cerebral blood vessels to form the blood-brain barrier(1). The barrier selectively excludes molecules from crossing between the blood and the brain based upon their size and charge. This function can impede the delivery of therapeutics for neurological disorders. A number of chemotherapeutic drugs, for example, will not effectively cross the blood-brain barrier to reach tumor cells(2). Thus, improving the delivery of drugs across the blood-brain barrier is an area of interest. The most prevalent methods for enhancing the delivery of drugs to the brain are direct cerebral infusion and blood-brain barrier disruption(3). Direct intracerebral infusion guarantees that therapies reach the brain; however, this method has a limited ability to disperse the drug(4). Blood-brain barrier disruption (BBBD) allows drugs to flow directly from the circulatory system into the brain and thus more effectively reach dispersed tumor cells. Three methods of barrier disruption include osmotic barrier disruption, pharmacological barrier disruption, and focused ultrasound with microbubbles. Osmotic disruption, pioneered by Neuwelt, uses a hypertonic solution of 25% mannitol that dehydrates the cells of the blood-brain barrier causing them to shrink and disrupt their tight junctions. Barrier disruption can also be accomplished pharmacologically with vasoactive compounds such as histamine(5) and bradykinin(6). This method, however, is selective primarily for the brain-tumor barrier(7). Additionally, RMP-7, an analog of the peptide bradykinin, was found to be inferior when compared head-to-head with osmotic BBBD with 25% mannitol(8). Another method, focused ultrasound (FUS) in conjunction with microbubble ultrasound contrast agents, has also been shown to reversibly open the blood-brain barrier(9). In comparison to FUS, though, 25% mannitol has a longer history of safety in human patients that makes it a proven tool for translational research(10-12). In order to accomplish BBBD, mannitol must be delivered at a high rate directly into the brain's arterial circulation. In humans, an endovascular catheter is guided to the brain where rapid, direct flow can be accomplished. This protocol models human BBBD as closely as possible. Following a cut-down to the bifurcation of the common carotid artery, a catheter is inserted retrograde into the ECA and used to deliver mannitol directly into the internal carotid artery (ICA) circulation. Propofol and N2O anesthesia are used for their ability to maximize the effectiveness of barrier disruption(13). If executed properly, this procedure has the ability to safely, effectively, and reversibly open the blood-brain barrier and improve the delivery of drugs that do not ordinarily reach the brain (8,13,14).

BrainNet Viewer: a network visualization tool for human brain connectomics.

PubMed

Xia, Mingrui; Wang, Jinhui; He, Yong

2013-01-01

The human brain is a complex system whose topological organization can be represented using connectomics. Recent studies have shown that human connectomes can be constructed using various neuroimaging technologies and further characterized using sophisticated analytic strategies, such as graph theory. These methods reveal the intriguing topological architectures of human brain networks in healthy populations and explore the changes throughout normal development and aging and under various pathological conditions. However, given the huge complexity of this methodology, toolboxes for graph-based network visualization are still lacking. Here, using MATLAB with a graphical user interface (GUI), we developed a graph-theoretical network visualization toolbox, called BrainNet Viewer, to illustrate human connectomes as ball-and-stick models. Within this toolbox, several combinations of defined files with connectome information can be loaded to display different combinations of brain surface, nodes and edges. In addition, display properties, such as the color and size of network elements or the layout of the figure, can be adjusted within a comprehensive but easy-to-use settings panel. Moreover, BrainNet Viewer draws the brain surface, nodes and edges in sequence and displays brain networks in multiple views, as required by the user. The figure can be manipulated with certain interaction functions to display more detailed information. Furthermore, the figures can be exported as commonly used image file formats or demonstration video for further use. BrainNet Viewer helps researchers to visualize brain networks in an easy, flexible and quick manner, and this software is freely available on the NITRC website (www.nitrc.org/projects/bnv/).

Localization of migraine susceptibility genes in human brain by single-cell RNA sequencing.

PubMed

Renthal, William

2018-01-01

Background Migraine is a debilitating disorder characterized by severe headaches and associated neurological symptoms. A key challenge to understanding migraine has been the cellular complexity of the human brain and the multiple cell types implicated in its pathophysiology. The present study leverages recent advances in single-cell transcriptomics to localize the specific human brain cell types in which putative migraine susceptibility genes are expressed. Methods The cell-type specific expression of both familial and common migraine-associated genes was determined bioinformatically using data from 2,039 individual human brain cells across two published single-cell RNA sequencing datasets. Enrichment of migraine-associated genes was determined for each brain cell type. Results Analysis of single-brain cell RNA sequencing data from five major subtypes of cells in the human cortex (neurons, oligodendrocytes, astrocytes, microglia, and endothelial cells) indicates that over 40% of known migraine-associated genes are enriched in the expression profiles of a specific brain cell type. Further analysis of neuronal migraine-associated genes demonstrated that approximately 70% were significantly enriched in inhibitory neurons and 30% in excitatory neurons. Conclusions This study takes the next step in understanding the human brain cell types in which putative migraine susceptibility genes are expressed. Both familial and common migraine may arise from dysfunction of discrete cell types within the neurovascular unit, and localization of the affected cell type(s) in an individual patient may provide insight into to their susceptibility to migraine.

Hypothesis-driven methods to augment human cognition by optimizing cortical oscillations

PubMed Central

Horschig, Jörn M.; Zumer, Johanna M.; Bahramisharif, Ali

2014-01-01

Cortical oscillations have been shown to represent fundamental functions of a working brain, e.g., communication, stimulus binding, error monitoring, and inhibition, and are directly linked to behavior. Recent studies intervening with these oscillations have demonstrated effective modulation of both the oscillations and behavior. In this review, we collect evidence in favor of how hypothesis-driven methods can be used to augment cognition by optimizing cortical oscillations. We elaborate their potential usefulness for three target groups: healthy elderly, patients with attention deficit/hyperactivity disorder, and healthy young adults. We discuss the relevance of neuronal oscillations in each group and show how each of them can benefit from the manipulation of functionally-related oscillations. Further, we describe methods for manipulation of neuronal oscillations including direct brain stimulation as well as indirect task alterations. We also discuss practical considerations about the proposed techniques. In conclusion, we propose that insights from neuroscience should guide techniques to augment human cognition, which in turn can provide a better understanding of how the human brain works. PMID:25018706

Functional neuroimaging: technical, logical, and social perspectives.

PubMed

Aguirre, Geoffrey K

2014-01-01

Neuroscientists have long sought to study the dynamic activity of the human brain-what's happening in the brain, that is, while people are thinking, feeling, and acting. Ideally, an inside look at brain function would simultaneously and continuously measure the biochemical state of every cell in the central nervous system. While such a miraculous method is science fiction, a century of progress in neuroimaging technologies has made such simultaneous and continuous measurement a plausible fiction. Despite this progress, practitioners of modern neuroimaging struggle with two kinds of limitations: those that attend the particular neuroimaging methods we have today and those that would limit any method of imaging neural activity, no matter how powerful. In this essay, I consider the liabilities and potential of techniques that measure human brain activity. I am concerned here only with methods that measure relevant physiologic states of the central nervous system and relate those measures to particular mental states. I will consider in particular the preeminent method of functional neuroimaging: BOLD fMRI. While there are several practical limits on the biological information that current technologies can measure, these limits-as important as they are-are minor in comparison to the fundamental logical restraints on the conclusions that can be drawn from brain imaging studies. © 2014 by The Hastings Center.

Enhanced cortical thickness measurements for rodent brains via Lagrangian-based RK4 streamline computation

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Kim, Sun Hyung; Oguz, Ipek; Styner, Martin

2016-03-01

The cortical thickness of the mammalian brain is an important morphological characteristic that can be used to investigate and observe the brain's developmental changes that might be caused by biologically toxic substances such as ethanol or cocaine. Although various cortical thickness analysis methods have been proposed that are applicable for human brain and have developed into well-validated open-source software packages, cortical thickness analysis methods for rodent brains have not yet become as robust and accurate as those designed for human brains. Based on a previously proposed cortical thickness measurement pipeline for rodent brain analysis,1 we present an enhanced cortical thickness pipeline in terms of accuracy and anatomical consistency. First, we propose a Lagrangian-based computational approach in the thickness measurement step in order to minimize local truncation error using the fourth-order Runge-Kutta method. Second, by constructing a line object for each streamline of the thickness measurement, we can visualize the way the thickness is measured and achieve sub-voxel accuracy by performing geometric post-processing. Last, with emphasis on the importance of an anatomically consistent partial differential equation (PDE) boundary map, we propose an automatic PDE boundary map generation algorithm that is specific to rodent brain anatomy, which does not require manual labeling. The results show that the proposed cortical thickness pipeline can produce statistically significant regions that are not observed in the previous cortical thickness analysis pipeline.

Detection of glucose in the human brain with 1 H MRS at 7 Tesla.

PubMed

Kaiser, Lana G; Hirokazu, Kawaguchi; Fukunaga, Masaki; B Matson, Gerald

2016-12-01

A new method is proposed for noninvasive detection of glucose in vivo using proton MR spectroscopy at 7 Tesla. The proposed method utilizes J-difference editing to uncover the resonance of beta-glucose (β-glc) at 3.23 ppm, which is strongly overlapped with choline. Calculations using the density matrix formalism are used to maximize the signal-to-noise ratio of the β-glc resonance at 3.23 ppm. The calculations are verified using phantom and in vivo data collected at 7 Tesla. The proposed method allows observation of the glucose signal at 3.23 ppm in the human brain spectrum. Additional co-edited resonances of N-acetylaspartylglutamatate and glutathione are also detected in the same experiment. The proposed method does not require carbon ( 13 C)- labeled glucose injections and 13 C hardware; as such, it has a potential to provide valuable information on intrinsic glucose concentration in the human brain in vivo. Magn Reson Med 76:1653-1660, 2016. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Spatial Mapping of Structural and Connectional Imaging Data for the Developing Human Brain with Diffusion Tensor Imaging

PubMed Central

Ouyang, Austin; Jeon, Tina; Sunkin, Susan M.; Pletikos, Mihovil; Sedmak, Goran; Sestan, Nenad; Lein, Ed S.; Huang, Hao

2014-01-01

During human brain development from fetal stage to adulthood, the white matter (WM) tracts undergo dramatic changes. Diffusion tensor imaging (DTI), a widely used magnetic resonance imaging (MRI) modality, offers insight into the dynamic changes of WM fibers as these fibers can be noninvasively traced and three-dimensionally (3D) reconstructed with DTI tractography. The DTI and conventional T1 weighted MRI images also provide sufficient cortical anatomical details for mapping the cortical regions of interests (ROIs). In this paper, we described basic concepts and methods of DTI techniques that can be used to trace major WM tracts noninvasively from fetal brain of 14 postconceptional weeks (pcw) to adult brain. We applied these techniques to acquire DTI data and trace, reconstruct and visualize major WM tracts during development. After categorizing major WM fiber bundles into five unique functional tract groups, namely limbic, brain stem, projection, commissural and association tracts, we revealed formation and maturation of these 3D reconstructed WM tracts of the developing human brain. The structural and connectional imaging data offered by DTI provides the anatomical backbone of transcriptional atlas of the developing human brain. PMID:25448302

The Zagreb Collection of human brains: a unique, versatile, but underexploited resource for the neuroscience community.

PubMed

Judaš, Miloš; Šimić, Goran; Petanjek, Zdravko; Jovanov-Milošević, Nataša; Pletikos, Mihovil; Vasung, Lana; Vukšić, Mario; Kostović, Ivica

2011-05-01

The Zagreb Collection of developing and adult human brains was founded in 1974 by Ivica Kostović and consists of 1,278 developing and adult human brains, including 610 fetal, 317 children, and 359 adult brains. It is one of the largest collections of developing human brains. The collection serves as a key resource for many focused research projects and has led to several seminal contributions on mammalian cortical development, such as the discovery of the transient fetal subplate zone and of early bilaminar synaptogenesis in the embryonic and fetal human cerebral cortex, and the first description of growing afferent pathways in the human fetal telencephalon. The Zagreb Collection also serves as a core resource for ever-growing networks of international collaboration and represents the starting point for many young investigators who now pursue independent research careers at leading international institutions. The Zagreb Collection, however, remains underexploited owing to a lack of adequate funding in Croatia. Funding could establish an online catalog of the collection and modern virtual microscopy scanning methods to make the collection internationally more accessible. © 2011 New York Academy of Sciences.

Pushing spatial and temporal resolution for functional and diffusion MRI in the Human Connectome Project

PubMed Central

Uğurbil, Kamil; Xu, Junqian; Auerbach, Edward J.; Moeller, Steen; Vu, An; Duarte-Carvajalino, Julio M.; Lenglet, Christophe; Wu, Xiaoping; Schmitter, Sebastian; Van de Moortele, Pierre Francois; Strupp, John; Sapiro, Guillermo; De Martino, Federico; Wang, Dingxin; Harel, Noam; Garwood, Michael; Chen, Liyong; Feinberg, David A.; Smith, Stephen M.; Miller, Karla L.; Sotiropoulos, Stamatios N; Jbabdi, Saad; Andersson, Jesper L; Behrens, Timothy EJ; Glasser, Matthew F.; Van Essen, David; Yacoub, Essa

2013-01-01

The human connectome project (HCP) relies primarily on three complementary magnetic resonance (MR) methods. These are: 1) resting state functional MR imaging (rfMRI) which uses correlations in the temporal fluctuations in an fMRI time series to deduce ‘functional connectivity’; 2) diffusion imaging (dMRI), which provides the input for tractography algorithms used for the reconstruction of the complex axonal fiber architecture; and 3) task based fMRI (tfMRI), which is employed to identify functional parcellation in the human brain in order to assist analyses of data obtained with the first two methods. We describe technical improvements and optimization of these methods as well as instrumental choices that impact speed of acquisition of fMRI and dMRI images at 3 Tesla, leading to whole brain coverage with 2 mm isotropic resolution in 0.7 second for fMRI, and 1.25 mm isotropic resolution dMRI data for tractography analysis with three-fold reduction in total data acquisition time. Ongoing technical developments and optimization for acquisition of similar data at 7 Tesla magnetic field are also presented, targeting higher resolution, specificity of functional imaging signals, mitigation of the inhomogeneous radio frequency (RF) fields and power deposition. Results demonstrate that overall, these approaches represent a significant advance in MR imaging of the human brain to investigate brain function and structure. PMID:23702417

Brain cancer probed by native fluorescence and stokes shift spectroscopy

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; He, Yong; Pu, Yang; Li, Qingbo; Wang, Wei; Alfano, Robert R.

2012-12-01

Optical biopsy spectroscopy was applied to diagnosis human brain cancer in vitro. The spectra of native fluorescence, Stokes shift and excitation spectra were obtained from malignant meningioma, benign, normal meningeal tissues and acoustic neuroma benign tissues. The wide excitation wavelength ranges were used to establish the criterion for distinguishing brain diseases. The alteration of fluorescence spectra between normal and abnormal brain tissues were identified by the characteristic fluorophores under the excitation with UV to visible wavelength range. It was found that the ratios of the peak intensities and peak position in both spectra of fluorescence and Stokes shift may be used to diagnose human brain meninges diseases. The preliminary analysis of fluorescence spectral data from cancer and normal meningeal tissues by basic biochemical component analysis model (BBCA) and Bayes classification model based on statistical methods revealed the changes of components, and classified the difference between cancer and normal human brain meningeal tissues in a predictions accuracy rate is 0.93 in comparison with histopathology and immunohistochemistry reports (gold standard).

The glia doctrine: addressing the role of glial cells in healthy brain ageing.

PubMed

Nagelhus, Erlend A; Amiry-Moghaddam, Mahmood; Bergersen, Linda H; Bjaalie, Jan G; Eriksson, Jens; Gundersen, Vidar; Leergaard, Trygve B; Morth, J Preben; Storm-Mathisen, Jon; Torp, Reidun; Walhovd, Kristine B; Tønjum, Tone

2013-10-01

Glial cells in their plurality pervade the human brain and impact on brain structure and function. A principal component of the emerging glial doctrine is the hypothesis that astrocytes, the most abundant type of glial cells, trigger major molecular processes leading to brain ageing. Astrocyte biology has been examined using molecular, biochemical and structural methods, as well as 3D brain imaging in live animals and humans. Exosomes are extracelluar membrane vesicles that facilitate communication between glia, and have significant potential for biomarker discovery and drug delivery. Polymorphisms in DNA repair genes may indirectly influence the structure and function of membrane proteins expressed in glial cells and predispose specific cell subgroups to degeneration. Physical exercise may reduce or retard age-related brain deterioration by a mechanism involving neuro-glial processes. It is most likely that additional information about the distribution, structure and function of glial cells will yield novel insight into human brain ageing. Systematic studies of glia and their functions are expected to eventually lead to earlier detection of ageing-related brain dysfunction and to interventions that could delay, reduce or prevent brain dysfunction. Copyright © 2013 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Non-invasive detection and quantification of brain microvascular deficits by near-infrared spectroscopy in a rat model of Vascular Cognitive Impairment

NASA Astrophysics Data System (ADS)

Hallacoglu, Bertan; Sassaroli, Angelo M.; Rosenberg, Irwin H.; Troen, Aron; Fantini, Sergio

2011-02-01

Structural abnormalities in brain microvasculature are commonly associated with Alzheimer's Disease and other dementias. However, the extent to which structural microvascular abnormalities cause functional impairments in brain circulation and thereby to cognitive impairment is unclear. Non-invasive, near-infrared spectroscopy (NIRS) methods can be used to determine the absolute hemoglobin concentration and saturation in brain tissue, from which additional parameters such as cerebral blood volume (a theoretical correlate of brain microvascular density) can be derived. Validating such NIRS parameters in animal models, and understanding their relationship to cognitive function is an important step in the ultimate application of these methods to humans. To this end we applied a non-invasive multidistance NIRS method to determine the absolute concentration and saturation of cerebral hemoglobin in rat, by separately measuring absorption and reduced scattering coefficients without relying on pre- or post-correction factors. We applied this method to study brain circulation in folate deficient rats, which express brain microvascular pathology1 and which we have shown to develop cognitive impairment.2 We found absolute brain hemoglobin concentration ([HbT]) and oxygen saturation (StO2) to be significantly lower in folate deficient rats (n=6) with respect to control rats (n=5) (for [HbT]: 73+/-10 μM vs. 95+/-14 μM for StO2: 55%+/-7% vs. 66% +/-4%), implicating microvascular pathology and diminished oxygen delivery as a mechanism of cognitive impairment. More generally, our study highlights how noninvasive, absolute NIRS measurements can provide unique insight into the pathophysiology of Vascular Cognitive Impairment. Applying this method to this and other rat models of cognitive impairment will help to validate physiologically meaningful NIRS parameters for the ultimate goal of studying cerebral microvascular disease and cognitive decline in humans.

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

Rajagopal, Gautham; Joshi, Anand A.; Leahy, Richard M.

2017-02-01

Brain Extraction (classification of brain and non-brain tissue) of MRI brain images is a crucial pre-processing step necessary for imaging-based anatomical studies of the human brain. Several automated methods and software tools are available for performing this task, but differences in MR image parameters (pulse sequence, resolution) and instrumentand subject-dependent noise and artefacts affect the performance of these automated methods. We describe and evaluate a method that automatically adapts the default parameters of the Brain Surface Extraction (BSE) algorithm to optimize a cost function chosen to reflect accurate brain extraction. BSE uses a combination of anisotropic filtering, Marr-Hildreth edge detection, and binary morphology for brain extraction. Our algorithm automatically adapts four parameters associated with these steps to maximize the brain surface area to volume ratio. We evaluate the method on a total of 109 brain volumes with ground truth brain masks generated by an expert user. A quantitative evaluation of the performance of the proposed algorithm showed an improvement in the mean (s.d.) Dice coefficient from 0.8969 (0.0376) for default parameters to 0.9509 (0.0504) for the optimized case. These results indicate that automatic parameter optimization can result in significant improvements in definition of the brain mask.

Reconstruction of human brain spontaneous activity based on frequency-pattern analysis of magnetoencephalography data

PubMed Central

Llinás, Rodolfo R.; Ustinin, Mikhail N.; Rykunov, Stanislav D.; Boyko, Anna I.; Sychev, Vyacheslav V.; Walton, Kerry D.; Rabello, Guilherme M.; Garcia, John

2015-01-01

A new method for the analysis and localization of brain activity has been developed, based on multichannel magnetic field recordings, over minutes, superimposed on the MRI of the individual. Here, a high resolution Fourier Transform is obtained over the entire recording period, leading to a detailed multi-frequency spectrum. Further analysis implements a total decomposition of the frequency components into functionally invariant entities, each having an invariant field pattern localizable in recording space. The method, addressed as functional tomography, makes it possible to find the distribution of magnetic field sources in space. Here, the method is applied to the analysis of simulated data, to oscillating signals activating a physical current dipoles phantom, and to recordings of spontaneous brain activity in 10 healthy adults. In the analysis of simulated data, 61 dipoles are localized with 0.7 mm precision. Concerning the physical phantom the method is able to localize three simultaneously activated current dipoles with 1 mm precision. Spatial resolution 3 mm was attained when localizing spontaneous alpha rhythm activity in 10 healthy adults, where the alpha peak was specified for each subject individually. Co-registration of the functional tomograms with each subject's head MRI localized alpha range activity to the occipital and/or posterior parietal brain region. This is the first application of this new functional tomography to human brain activity. The method successfully provides an overall view of brain electrical activity, a detailed spectral description and, combined with MRI, the localization of sources in anatomical brain space. PMID:26528119

From The Cover: Microtransplantation of functional receptors and channels from the Alzheimer's brain to frog oocytes

NASA Astrophysics Data System (ADS)

Miledi, R.; Dueñas, Z.; Martinez-Torres, A.; Kawas, C. H.; Eusebi, F.

2004-02-01

About a decade ago, cell membranes from the electric organ of Torpedo and from the rat brain were transplanted to frog oocytes, which thus acquired functional Torpedo and rat neurotransmitter receptors. Nevertheless, the great potential that this method has for studying human diseases has remained virtually untapped. Here, we show that cell membranes from the postmortem brains of humans that suffered Alzheimer's disease can be microtransplanted to the plasma membrane of Xenopus oocytes. We show also that these postmortem membranes carry neurotransmitter receptors and voltage-operated channels that are still functional, even after they have been kept frozen for many years. This method provides a new and powerful approach to study directly the functional characteristics and structure of receptors, channels, and other membrane proteins of the Alzheimer's brain. This knowledge may help in understanding the basis of Alzheimer's disease and also help in developing new treatments. -aminobutyric acid receptors | sodium channels | calcium channels | postmortem brain

A Single-Cell Roadmap of Lineage Bifurcation in Human ESC Models of Embryonic Brain Development.

PubMed

Yao, Zizhen; Mich, John K; Ku, Sherman; Menon, Vilas; Krostag, Anne-Rachel; Martinez, Refugio A; Furchtgott, Leon; Mulholland, Heather; Bort, Susan; Fuqua, Margaret A; Gregor, Ben W; Hodge, Rebecca D; Jayabalu, Anu; May, Ryan C; Melton, Samuel; Nelson, Angelique M; Ngo, N Kiet; Shapovalova, Nadiya V; Shehata, Soraya I; Smith, Michael W; Tait, Leah J; Thompson, Carol L; Thomsen, Elliot R; Ye, Chaoyang; Glass, Ian A; Kaykas, Ajamete; Yao, Shuyuan; Phillips, John W; Grimley, Joshua S; Levi, Boaz P; Wang, Yanling; Ramanathan, Sharad

2017-01-05

During human brain development, multiple signaling pathways generate diverse cell types with varied regional identities. Here, we integrate single-cell RNA sequencing and clonal analyses to reveal lineage trees and molecular signals underlying early forebrain and mid/hindbrain cell differentiation from human embryonic stem cells (hESCs). Clustering single-cell transcriptomic data identified 41 distinct populations of progenitor, neuronal, and non-neural cells across our differentiation time course. Comparisons with primary mouse and human gene expression data demonstrated rostral and caudal progenitor and neuronal identities from early brain development. Bayesian analyses inferred a unified cell-type lineage tree that bifurcates between cortical and mid/hindbrain cell types. Two methods of clonal analyses confirmed these findings and further revealed the importance of Wnt/β-catenin signaling in controlling this lineage decision. Together, these findings provide a rich transcriptome-based lineage map for studying human brain development and modeling developmental disorders. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimization of the first dimension for separation by two-dimensional gel electrophoresis of basic proteins from human brain tissue.

PubMed

Pennington, Kyla; McGregor, Emma; Beasley, Clare L; Everall, Ian; Cotter, David; Dunn, Michael J

2004-01-01

A major cause of poor resolution in the alkaline pH range of two-dimensional electrophoresis (2-DE) gels is unsatisfactory separation of basic proteins in the first dimension. We have compared methods for the separation of basic proteins in the isoelectric focusing dimension of human brain proteins. The combined use of anodic cup-loading and the hydroxyethyldisulphide containing solution (DeStreak) produced better resolution in both analytical and micropreparative protein loaded 2-DE gels than the other methods investigated.

Preprocessing film-copied MRI for studying morphological brain changes.

PubMed

Pham, Tuan D; Eisenblätter, Uwe; Baune, Bernhard T; Berger, Klaus

2009-06-15

The magnetic resonance imaging (MRI) of the brain is one of the important data items for studying memory and morbidity in elderly as these images can provide useful information through the quantitative measures of various regions of interest of the brain. As an effort to fully automate the biomedical analysis of the brain that can be combined with the genetic data of the same human population and where the records of the original MRI data are missing, this paper presents two effective methods for addressing this imaging problem. The first method handles the restoration of the film-copied MRI. The second method involves the segmentation of the image data. Experimental results and comparisons with other methods suggest the usefulness of the proposed image analysis methodology.

Analysis of Brain Recurrence

NASA Astrophysics Data System (ADS)

Frilot, Clifton; Kim, Paul Y.; Carrubba, Simona; McCarty, David E.; Chesson, Andrew L.; Marino, Andrew A.

Analysis of Brain Recurrence (ABR) is a method for extracting physiologically significant information from the electroencephalogram (EEG), a non-stationary electrical output of the brain, the ultimate complex dynamical system. ABR permits quantification of temporal patterns in the EEG produced by the non-autonomous differential laws that govern brain metabolism. In the context of appropriate experimental and statistical designs, ABR is ideally suited to the task of interpreting the EEG. Present applications of ABR include discovery of a human magnetic sense, increased mechanistic understanding of neuronal membrane processes, diagnosis of degenerative neurological disease, detection of changes in brain metabolism caused by weak environmental electromagnetic fields, objective characterization of the quality of human sleep, and evaluation of sleep disorders. ABR has important beneficial implications for the development of clinical and experimental neuroscience.

Nanoparticle-mediated transcriptional modification enhances neuronal differentiation of human neural stem cells following transplantation in rat brain.

PubMed

Li, Xiaowei; Tzeng, Stephany Y; Liu, Xiaoyan; Tammia, Markus; Cheng, Yu-Hao; Rolfe, Andrew; Sun, Dong; Zhang, Ning; Green, Jordan J; Wen, Xuejun; Mao, Hai-Quan

2016-04-01

Strategies to enhance survival and direct the differentiation of stem cells in vivo following transplantation in tissue repair site are critical to realizing the potential of stem cell-based therapies. Here we demonstrated an effective approach to promote neuronal differentiation and maturation of human fetal tissue-derived neural stem cells (hNSCs) in a brain lesion site of a rat traumatic brain injury model using biodegradable nanoparticle-mediated transfection method to deliver key transcriptional factor neurogenin-2 to hNSCs when transplanted with a tailored hyaluronic acid (HA) hydrogel, generating larger number of more mature neurons engrafted to the host brain tissue than non-transfected cells. The nanoparticle-mediated transcription activation method together with an HA hydrogel delivery matrix provides a translatable approach for stem cell-based regenerative therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Network Analysis: Applications for the Developing Brain

PubMed Central

Chu-Shore, Catherine J.; Kramer, Mark A.; Bianchi, Matt T.; Caviness, Verne S.; Cash, Sydney S.

2011-01-01

Development of the human brain follows a complex trajectory of age-specific anatomical and physiological changes. The application of network analysis provides an illuminating perspective on the dynamic interregional and global properties of this intricate and complex system. Here, we provide a critical synopsis of methods of network analysis with a focus on developing brain networks. After discussing basic concepts and approaches to network analysis, we explore the primary events of anatomical cortical development from gestation through adolescence. Upon this framework, we describe early work revealing the evolution of age-specific functional brain networks in normal neurodevelopment. Finally, we review how these relationships can be altered in disease and perhaps even rectified with treatment. While this method of description and inquiry remains in early form, there is already substantial evidence that the application of network models and analysis to understanding normal and abnormal human neural development holds tremendous promise for future discovery. PMID:21303762

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

A biochemical landscape of A-to-I RNA editing in the human brain transcriptome

PubMed Central

Sakurai, Masayuki; Ueda, Hiroki; Yano, Takanori; Okada, Shunpei; Terajima, Hideki; Mitsuyama, Toutai; Toyoda, Atsushi; Fujiyama, Asao; Kawabata, Hitomi; Suzuki, Tsutomu

2014-01-01

Inosine is an abundant RNA modification in the human transcriptome and is essential for many biological processes in modulating gene expression at the post-transcriptional level. Adenosine deaminases acting on RNA (ADARs) catalyze the hydrolytic deamination of adenosines to inosines (A-to-I editing) in double-stranded regions. We previously established a biochemical method called “inosine chemical erasing” (ICE) to directly identify inosines on RNA strands with high reliability. Here, we have applied the ICE method combined with deep sequencing (ICE-seq) to conduct an unbiased genome-wide screening of A-to-I editing sites in the transcriptome of human adult brain. Taken together with the sites identified by the conventional ICE method, we mapped 19,791 novel sites and newly found 1258 edited mRNAs, including 66 novel sites in coding regions, 41 of which cause altered amino acid assignment. ICE-seq detected novel editing sites in various repeat elements as well as in short hairpins. Gene ontology analysis revealed that these edited mRNAs are associated with transcription, energy metabolism, and neurological disorders, providing new insights into various aspects of human brain functions. PMID:24407955

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

Systems biology of human epilepsy applied to patients with brain tumors.

PubMed

Mittal, Sandeep; Shah, Aashit K; Barkmeier, Daniel T; Loeb, Jeffrey A

2013-12-01

Epilepsy is a disease of recurrent seizures that can be associated with a wide variety of acquired and developmental brain lesions. Current medications for patients with epilepsy can suppress seizures; they do not cure or modify the underlying disease process. On the other hand, surgical removal of focal brain regions that produce seizures can be curative. This surgical procedure can be more precise with the placement of intracranial recording electrodes to identify brain regions that generate seizure activity as well as those that are critical for normal brain function. The detail that goes into these surgeries includes extensive neuroimaging, electrophysiology, and clinical data. Combined with precisely localized tissues removed, these data provide an unparalleled opportunity to learn about the interrelationships of many "systems" in the human brain not possible in just about any other human brain disorder. Herein, we describe a systems biology approach developed to study patients who undergo brain surgery for epilepsy and how we have begun to apply these methods to patients whose seizures are associated with brain tumors. A central goal of this clinical and translational research program is to improve our understanding of epilepsy and brain tumors and to improve diagnosis and treatment outcomes of both. Wiley Periodicals, Inc. © 2013 International League Against Epilepsy.

Twenty-first century brain banking. Processing brains for research: the Columbia University methods

PubMed Central

del Amaya, Maria Pilar; Keller, Christian E.

2007-01-01

Carefully categorized postmortem human brains are crucial for research. The lack of generally accepted methods for processing human postmortem brains for research persists. Thus, brain banking is essential; however, it cannot be achieved at the cost of the teaching mission of the academic institution by routing brains away from residency programs, particularly when the autopsy rate is steadily decreasing. A consensus must be reached whereby a brain can be utilizable for diagnosis, research, and teaching. The best diagnostic categorization possible must be secured and the yield of samples for basic investigation maximized. This report focuses on integrated, novel methods currently applied at the New York Brain Bank, Columbia University, New York, which are designed to reach accurate neuropathological diagnosis, optimize the yield of samples, and process fresh-frozen samples suitable for a wide range of modern investigations. The brains donated for research are processed as soon as possible after death. The prosector must have a good command of the neuroanatomy, neuropathology, and the protocol. One half of each brain is immersed in formalin for performing the thorough neuropathologic evaluation, which is combined with the teaching task. The contralateral half is extensively dissected at the fresh state. The anatomical origin of each sample is recorded using the map of Brodmann for the cortical samples. The samples are frozen at −160°C, barcode labeled, and ready for immediate disbursement once categorized diagnostically. A rigorous organization of freezer space, coupled to an electronic tracking system with its attached software, fosters efficient access for retrieval within minutes of any specific frozen samples in storage. This report describes how this achievement is feasible with emphasis on the actual processing of brains donated for research. PMID:17985145

Midbrain-like Organoids from Human Pluripotent Stem Cells Contain Functional Dopaminergic and Neuromelanin-Producing Neurons.

PubMed

Jo, Junghyun; Xiao, Yixin; Sun, Alfred Xuyang; Cukuroglu, Engin; Tran, Hoang-Dai; Göke, Jonathan; Tan, Zi Ying; Saw, Tzuen Yih; Tan, Cheng-Peow; Lokman, Hidayat; Lee, Younghwan; Kim, Donghoon; Ko, Han Seok; Kim, Seong-Oh; Park, Jae Hyeon; Cho, Nam-Joon; Hyde, Thomas M; Kleinman, Joel E; Shin, Joo Heon; Weinberger, Daniel R; Tan, Eng King; Je, Hyunsoo Shawn; Ng, Huck-Hui

2016-08-04

Recent advances in 3D culture systems have led to the generation of brain organoids that resemble different human brain regions; however, a 3D organoid model of the midbrain containing functional midbrain dopaminergic (mDA) neurons has not been reported. We developed a method to differentiate human pluripotent stem cells into a large multicellular organoid-like structure that contains distinct layers of neuronal cells expressing characteristic markers of human midbrain. Importantly, we detected electrically active and functionally mature mDA neurons and dopamine production in our 3D midbrain-like organoids (MLOs). In contrast to human mDA neurons generated using 2D methods or MLOs generated from mouse embryonic stem cells, our human MLOs produced neuromelanin-like granules that were structurally similar to those isolated from human substantia nigra tissues. Thus our MLOs bearing features of the human midbrain may provide a tractable in vitro system to study the human midbrain and its related diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

MRI Segmentation of the Human Brain: Challenges, Methods, and Applications

PubMed Central

Despotović, Ivana

2015-01-01

Image segmentation is one of the most important tasks in medical image analysis and is often the first and the most critical step in many clinical applications. In brain MRI analysis, image segmentation is commonly used for measuring and visualizing the brain's anatomical structures, for analyzing brain changes, for delineating pathological regions, and for surgical planning and image-guided interventions. In the last few decades, various segmentation techniques of different accuracy and degree of complexity have been developed and reported in the literature. In this paper we review the most popular methods commonly used for brain MRI segmentation. We highlight differences between them and discuss their capabilities, advantages, and limitations. To address the complexity and challenges of the brain MRI segmentation problem, we first introduce the basic concepts of image segmentation. Then, we explain different MRI preprocessing steps including image registration, bias field correction, and removal of nonbrain tissue. Finally, after reviewing different brain MRI segmentation methods, we discuss the validation problem in brain MRI segmentation. PMID:25945121

High resolution mass spectrometric brain proteomics by MALDI-FTICR-MS combined with determination of P, S, Cu, Zn and Fe by LA-ICP-MS

NASA Astrophysics Data System (ADS)

Becker, J. Susanne; Zoriy, Miroslav; Przybylski, Michael; Becker, J. Sabine

2007-03-01

The combination of atomic and molecular mass spectrometric methods was applied for characterization and identification of several human proteins from Alzheimer's diseased brain. A brain protein mixture was separated by two-dimensional (2D) gel electrophoresis and the protein spots were fast screened by microlocal analysis using LA-ICP-MS (laser ablation inductively coupled plasma mass spectrometry) in respect to phosphorus, sulfur, copper, zinc and iron content. Five selected protein spots in 2D gel containing these elements were investigated after tryptic digestion by matrix assisted laser desorption ionization Fourier transform ion cyclotron resonance mass spectrometry (MALDI-FTICR-MS). Than element concentrations (P, Cu, Zn and Fe) were determined in three identified human brain proteins by LA-ICP-MS in the 2D gel. Results of structure analysis of human brain proteins by MALDI-FTICR-MS were combined with those of the direct determination of phosphorus, copper, zinc and iron concentrations in protein spots with LA-ICP-MS. From the results of atomic and molecular mass spectrometric techniques the human brain proteins were characterized in respect to their structure, sequence, phosphorylation state and metal content as well.

Growth and development of the brain and impact on cognitive outcomes.

PubMed

Hüppi, Petra S

2010-01-01

Understanding human brain development from the fetal life to adulthood is of great clinical importance as many neurological and neurobehavioral disorders have their origin in early structural and functional cerebral maturation. The developing brain is particularly prone to being affected by endogenous and exogenous events through the fetal and early postnatal life. The concept of 'developmental plasticity or disruption of the developmental program' summarizes these events. Increases in white matter, which speed up communication between brain cells, growing complexity of neuronal networks suggested by gray and white matter changes, and environmentally sensitive plasticity are all essential aspects in a child's ability to mentalize and maintain the adaptive flexibility necessary for achieving high sociocognitive functioning. Advancement in neuroimaging has opened up new ways for examining the developing human brain in vivo, the study of the effects of early antenatal, perinatal and neonatal events on later structural and functional brain development resulting in developmental disabilities or developmental resilience. In this review, methods of quantitative assessment of human brain development, such as 3D-MRI with image segmentation, diffusion tensor imaging to assess connectivity and functional MRI to visualize brain function will be presented. Copyright (c) 2010 S. Karger AG, Basel.

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.

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.

Brain Stimulation in Addiction

PubMed Central

Salling, Michael C; Martinez, Diana

2016-01-01

Localized stimulation of the human brain to treat neuropsychiatric disorders has been in place for over 20 years. Although these methods have been used to a greater extent for mood and movement disorders, recent work has explored brain stimulation methods as potential treatments for addiction. The rationale behind stimulation therapy in addiction involves reestablishing normal brain function in target regions in an effort to dampen addictive behaviors. In this review, we present the rationale and studies investigating brain stimulation in addiction, including transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Overall, these studies indicate that brain stimulation has an acute effect on craving for drugs and alcohol, but few studies have investigated the effect of brain stimulation on actual drug and alcohol use or relapse. Stimulation therapies may achieve their effect through direct or indirect modulation of brain regions involved in addiction, either acutely or through plastic changes in neuronal transmission. Although these mechanisms are not well understood, further identification of the underlying neurobiology of addiction and rigorous evaluation of brain stimulation methods has the potential for unlocking an effective, long-term treatment of addiction. PMID:27240657

Connectome imaging for mapping human brain pathways

PubMed Central

Shi, Y; Toga, A W

2017-01-01

With the fast advance of connectome imaging techniques, we have the opportunity of mapping the human brain pathways in vivo at unprecedented resolution. In this article we review the current developments of diffusion magnetic resonance imaging (MRI) for the reconstruction of anatomical pathways in connectome studies. We first introduce the background of diffusion MRI with an emphasis on the technical advances and challenges in state-of-the-art multi-shell acquisition schemes used in the Human Connectome Project. Characterization of the microstructural environment in the human brain is discussed from the tensor model to the general fiber orientation distribution (FOD) models that can resolve crossing fibers in each voxel of the image. Using FOD-based tractography, we describe novel methods for fiber bundle reconstruction and graph-based connectivity analysis. Building upon these novel developments, there have already been successful applications of connectome imaging techniques in reconstructing challenging brain pathways. Examples including retinofugal and brainstem pathways will be reviewed. Finally, we discuss future directions in connectome imaging and its interaction with other aspects of brain imaging research. PMID:28461700

Discovery of new candidate genes related to brain development using protein interaction information.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

Decoding the time-course of object recognition in the human brain: From visual features to categorical decisions.

PubMed

Contini, Erika W; Wardle, Susan G; Carlson, Thomas A

2017-10-01

Visual object recognition is a complex, dynamic process. Multivariate pattern analysis methods, such as decoding, have begun to reveal how the brain processes complex visual information. Recently, temporal decoding methods for EEG and MEG have offered the potential to evaluate the temporal dynamics of object recognition. Here we review the contribution of M/EEG time-series decoding methods to understanding visual object recognition in the human brain. Consistent with the current understanding of the visual processing hierarchy, low-level visual features dominate decodable object representations early in the time-course, with more abstract representations related to object category emerging later. A key finding is that the time-course of object processing is highly dynamic and rapidly evolving, with limited temporal generalisation of decodable information. Several studies have examined the emergence of object category structure, and we consider to what degree category decoding can be explained by sensitivity to low-level visual features. Finally, we evaluate recent work attempting to link human behaviour to the neural time-course of object processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection method utilizing the diagnostic information from neurologists and a corner matching method based on the uncertainty and structure of brain medical images. Additionally, we present a similarity calculation method for brain image classification. Experimental results on two brain image sets show the proposed corner-based brain medical image classifier outperforms the state-of-the-art studies.

Population based MRI and DTI templates of the adult ferret brain and tools for voxelwise analysis.

PubMed

Hutchinson, E B; Schwerin, S C; Radomski, K L; Sadeghi, N; Jenkins, J; Komlosh, M E; Irfanoglu, M O; Juliano, S L; Pierpaoli, C

2017-05-15

Non-invasive imaging has the potential to play a crucial role in the characterization and translation of experimental animal models to investigate human brain development and disorders, especially when employed to study animal models that more accurately represent features of human neuroanatomy. The purpose of this study was to build and make available MRI and DTI templates and analysis tools for the ferret brain as the ferret is a well-suited species for pre-clinical MRI studies with folded cortical surface, relatively high white matter volume and body dimensions that allow imaging with pre-clinical MRI scanners. Four ferret brain templates were built in this study - in-vivo MRI and DTI and ex-vivo MRI and DTI - using brain images across many ferrets and region of interest (ROI) masks corresponding to established ferret neuroanatomy were generated by semi-automatic and manual segmentation. The templates and ROI masks were used to create a web-based ferret brain viewing software for browsing the MRI and DTI volumes with annotations based on the ROI masks. A second objective of this study was to provide a careful description of the imaging methods used for acquisition, processing, registration and template building and to demonstrate several voxelwise analysis methods including Jacobian analysis of morphometry differences between the female and male brain and bias-free identification of DTI abnormalities in an injured ferret brain. The templates, tools and methodological optimization presented in this study are intended to advance non-invasive imaging approaches for human-similar animal species that will enable the use of pre-clinical MRI studies for understanding and treating brain disorders. Published by Elsevier Inc.

Natural image classification driven by human brain activity

NASA Astrophysics Data System (ADS)

Zhang, Dai; Peng, Hanyang; Wang, Jinqiao; Tang, Ming; Xue, Rong; Zuo, Zhentao

2016-03-01

Natural image classification has been a hot topic in computer vision and pattern recognition research field. Since the performance of an image classification system can be improved by feature selection, many image feature selection methods have been developed. However, the existing supervised feature selection methods are typically driven by the class label information that are identical for different samples from the same class, ignoring with-in class image variability and therefore degrading the feature selection performance. In this study, we propose a novel feature selection method, driven by human brain activity signals collected using fMRI technique when human subjects were viewing natural images of different categories. The fMRI signals associated with subjects viewing different images encode the human perception of natural images, and therefore may capture image variability within- and cross- categories. We then select image features with the guidance of fMRI signals from brain regions with active response to image viewing. Particularly, bag of words features based on GIST descriptor are extracted from natural images for classification, and a sparse regression base feature selection method is adapted to select image features that can best predict fMRI signals. Finally, a classification model is built on the select image features to classify images without fMRI signals. The validation experiments for classifying images from 4 categories of two subjects have demonstrated that our method could achieve much better classification performance than the classifiers built on image feature selected by traditional feature selection methods.

Neuronal nuclei isolation from human postmortem brain tissue.

PubMed

Matevossian, Anouch; Akbarian, Schahram

2008-10-01

Neurons in the human brain become postmitotic largely during prenatal development, and thus maintain their nuclei throughout the full lifespan. However, little is known about changes in neuronal chromatin and nuclear organization during the course of development and aging, or in chronic neuropsychiatric disease. However, to date most chromatin and DNA based assays (other than FISH) lack single cell resolution. To this end, the considerable cellular heterogeneity of brain tissue poses a significant limitation, because typically various subpopulations of neurons are intermingled with different types of glia and other non-neuronal cells. One possible solution would be to grow cell-type specific cultures, but most CNS cells, including neurons, are ex vivo sustainable, at best, for only a few weeks and thus would provide an incomplete model for epigenetic mechanisms potentially operating across the full lifespan. Here, we provide a protocol to extract and purify nuclei from frozen (never fixed) human postmortem brain. The method involves extraction of nuclei in hypotonic lysis buffer, followed by ultracentrifugation and immunotagging with anti-NeuN antibody. Labeled neuronal nuclei are then collected separately using fluorescence-activated sorting. This method should be applicable to any brain region in a wide range of species and suitable for chromatin immunoprecipitation studies with site- and modification-specific anti-histone antibodies, and for DNA methylation and other assays.

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.

Motif-Synchronization: A new method for analysis of dynamic brain networks with EEG

NASA Astrophysics Data System (ADS)

Rosário, R. S.; Cardoso, P. T.; Muñoz, M. A.; Montoya, P.; Miranda, J. G. V.

2015-12-01

The major aim of this work was to propose a new association method known as Motif-Synchronization. This method was developed to provide information about the synchronization degree and direction between two nodes of a network by counting the number of occurrences of some patterns between any two time series. The second objective of this work was to present a new methodology for the analysis of dynamic brain networks, by combining the Time-Varying Graph (TVG) method with a directional association method. We further applied the new algorithms to a set of human electroencephalogram (EEG) signals to perform a dynamic analysis of the brain functional networks (BFN).

Neuropsychology and cognitive neuroscience in the fMRI era: A recapitulation of localizationist and connectionist views.

PubMed

Sutterer, Matthew J; Tranel, Daniel

2017-11-01

We highlight the past 25 years of cognitive neuroscience and neuropsychology, focusing on the impact to the field of the introduction in 1992 of functional MRI (fMRI). We reviewed the past 25 years of literature in cognitive neuroscience and neuropsychology, focusing on the relation and interplay of fMRI studies and studies utilizing the "lesion method" in human participants with focal brain damage. Our review highlights the state of localist/connectionist research debates in cognitive neuroscience and neuropsychology circa 1992, and details how the introduction of fMRI into the field at that time catalyzed a new wave of efforts to map complex human behavior to specific brain regions. This, in turn, eventually evolved into many studies that focused on networks and connections between brain areas, culminating in recent years with large-scale investigations such as the Human Connectome Project. We argue that throughout the past 25 years, neuropsychology-and more precisely, the "lesion method" in humans-has continued to play a critical role in arbitrating conclusions and theories derived from inferred patterns of local brain activity or wide-spread connectivity from functional imaging approaches. We conclude by highlighting the future for neuropsychology in the context of an increasingly complex methodological armamentarium. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Localization of MEG human brain responses to retinotopic visual stimuli with contrasting source reconstruction approaches

PubMed Central

Cicmil, Nela; Bridge, Holly; Parker, Andrew J.; Woolrich, Mark W.; Krug, Kristine

2014-01-01

Magnetoencephalography (MEG) allows the physiological recording of human brain activity at high temporal resolution. However, spatial localization of the source of the MEG signal is an ill-posed problem as the signal alone cannot constrain a unique solution and additional prior assumptions must be enforced. An adequate source reconstruction method for investigating the human visual system should place the sources of early visual activity in known locations in the occipital cortex. We localized sources of retinotopic MEG signals from the human brain with contrasting reconstruction approaches (minimum norm, multiple sparse priors, and beamformer) and compared these to the visual retinotopic map obtained with fMRI in the same individuals. When reconstructing brain responses to visual stimuli that differed by angular position, we found reliable localization to the appropriate retinotopic visual field quadrant by a minimum norm approach and by beamforming. Retinotopic map eccentricity in accordance with the fMRI map could not consistently be localized using an annular stimulus with any reconstruction method, but confining eccentricity stimuli to one visual field quadrant resulted in significant improvement with the minimum norm. These results inform the application of source analysis approaches for future MEG studies of the visual system, and indicate some current limits on localization accuracy of MEG signals. PMID:24904268

The “curved lead pathway” method to enable a single lead to reach any two intracranial targets

NASA Astrophysics Data System (ADS)

Ding, Chen-Yu; Yu, Liang-Hong; Lin, Yuan-Xiang; Chen, Fan; Lin, Zhang-Ya; Kang, De-Zhi

2017-01-01

Deep brain stimulation is an effective way to treat movement disorders, and a powerful research tool for exploring brain functions. This report proposes a “curved lead pathway” method for lead implantation, such that a single lead can reach in sequence to any two intracranial targets. A new type of stereotaxic system for implanting a curved lead to the brain of human/primates was designed, the auxiliary device needed for this method to be used in rat/mouse was fabricated and verified in rat, and the Excel algorithm used for automatically calculating the necessary parameters was implemented. This “curved lead pathway” method of lead implantation may complement the current method, make lead implantation for multiple targets more convenient, and expand the experimental techniques of brain function research.

A volumetric conformal mapping approach for clustering white matter fibers in the brain

PubMed Central

Gupta, Vikash; Prasad, Gautam; Thompson, Paul

2017-01-01

The human brain may be considered as a genus-0 shape, topologically equivalent to a sphere. Various methods have been used in the past to transform the brain surface to that of a sphere using harmonic energy minimization methods used for cortical surface matching. However, very few methods have studied volumetric parameterization of the brain using a spherical embedding. Volumetric parameterization is typically used for complicated geometric problems like shape matching, morphing and isogeometric analysis. Using conformal mapping techniques, we can establish a bijective mapping between the brain and the topologically equivalent sphere. Our hypothesis is that shape analysis problems are simplified when the shape is defined in an intrinsic coordinate system. Our goal is to establish such a coordinate system for the brain. The efficacy of the method is demonstrated with a white matter clustering problem. Initial results show promise for future investigation in these parameterization technique and its application to other problems related to computational anatomy like registration and segmentation. PMID:29177252

Establishing Mouse Models for Zika Virus-induced Neurological Disorders Using Intracerebral Injection Strategies: Embryonic, Neonatal, and Adult.

PubMed

Herrlinger, Stephanie A; Shao, Qiang; Ma, Li; Brindley, Melinda; Chen, Jian-Fu

2018-04-26

The Zika virus (ZIKV) is a flavivirus currently endemic in North, Central, and South America. It is now established that the ZIKV can cause microcephaly and additional brain abnormalities. However, the mechanism underlying the pathogenesis of ZIKV in the developing brain remains unclear. Intracerebral surgical methods are frequently used in neuroscience research to address questions about both normal and abnormal brain development and brain function. This protocol utilizes classical surgical techniques and describes methods that allow one to model ZIKV-associated human neurological disease in the mouse nervous system. While direct brain inoculation does not model the normal mode of virus transmission, the method allows investigators to ask targeted questions concerning the consequence after ZIKV infection of the developing brain. This protocol describes embryonic, neonatal, and adult stages of intraventricular inoculation of ZIKV. Once mastered, this method can become a straightforward and reproducible technique that only takes a few hours to perform.

The brain in time: insights from neuromagnetic recordings.

PubMed

Hari, Riitta; Parkkonen, Lauri; Nangini, Cathy

2010-03-01

The millisecond time resolution of magnetoencephalography (MEG) is instrumental for investigating the brain basis of sensory processing, motor planning, cognition, and social interaction. We review the basic principles, recent progress, and future potential of MEG in noninvasive tracking of human brain activity. Cortical activation sequences from tens to hundreds of milliseconds can be followed during, e.g., perception, motor action, imitation, and language processing by recording both spontaneous and evoked brain signals. Moreover, tagging of sensory input can be used to reveal neuronal mechanisms of binaural interaction and perception of ambiguous images. The results support the emerging ideas of multiple, hierarchically organized temporal scales in human brain function. Instrumentation and data analysis methods are rapidly progressing, enabling attempts to decode the four-dimensional spatiotemporal signal patterns to reveal correlates of behavior and mental contents.

Plasticity following early-life brain injury: Insights from quantitative MRI.

PubMed

Fiori, Simona; Guzzetta, Andrea

2015-03-01

Over the last decade, the application of novel advanced neuroimaging techniques to study congenital brain damage has provided invaluable insights into the mechanisms underlying early neuroplasticity. The concept that is clearly emerging, both from human and nun-human studies, is that functional reorganization in the immature brain is substantially different from that of the more mature, developed brain. This applies to the reorganization of language, the sensorimotor system, and the visual system. The rapid implementation and development of higher order imaging methods will offer increased, currently unavailable knowledge about the specific mechanisms of cerebral plasticity in infancy, which is essential to support the development of early therapeutic interventions aimed at supporting and enhancing functional reorganization during a time of greatest potential brain plasticity. Copyright © 2015. Published by Elsevier Inc.

A three-dimensional histological atlas of the human basal ganglia. II. Atlas deformation strategy and evaluation in deep brain stimulation for Parkinson disease.

PubMed

Bardinet, Eric; Bhattacharjee, Manik; Dormont, Didier; Pidoux, Bernard; Malandain, Grégoire; Schüpbach, Michael; Ayache, Nicholas; Cornu, Philippe; Agid, Yves; Yelnik, Jérôme

2009-02-01

The localization of any given target in the brain has become a challenging issue because of the increased use of deep brain stimulation to treat Parkinson disease, dystonia, and nonmotor diseases (for example, Tourette syndrome, obsessive compulsive disorders, and depression). The aim of this study was to develop an automated method of adapting an atlas of the human basal ganglia to the brains of individual patients. Magnetic resonance images of the brain specimen were obtained before extraction from the skull and histological processing. Adaptation of the atlas to individual patient anatomy was performed by reshaping the atlas MR images to the images obtained in the individual patient using a hierarchical registration applied to a region of interest centered on the basal ganglia, and then applying the reshaping matrix to the atlas surfaces. Results were evaluated by direct visual inspection of the structures visible on MR images and atlas anatomy, by comparison with electrophysiological intraoperative data, and with previous atlas studies in patients with Parkinson disease. The method was both robust and accurate, never failing to provide an anatomically reliable atlas to patient registration. The registration obtained did not exceed a 1-mm mismatch with the electrophysiological signatures in the region of the subthalamic nucleus. This registration method applied to the basal ganglia atlas forms a powerful and reliable method for determining deep brain stimulation targets within the basal ganglia of individual patients.

Development of induced glioblastoma by implantation of a human xenograft in Yucatan minipig as a large animal model.

PubMed

Khoshnevis, Mehrdad; Carozzo, Claude; Bonnefont-Rebeix, Catherine; Belluco, Sara; Leveneur, Olivia; Chuzel, Thomas; Pillet-Michelland, Elodie; Dreyfus, Matthieu; Roger, Thierry; Berger, François; Ponce, Frédérique

2017-04-15

Glioblastoma is the most common and deadliest primary brain tumor for humans. Despite many efforts toward the improvement of therapeutic methods, prognosis is poor and the disease remains incurable with a median survival of 12-14.5 months after an optimal treatment. To develop novel treatment modalities for this fatal disease, new devices must be tested on an ideal animal model before performing clinical trials in humans. A new model of induced glioblastoma in Yucatan minipigs was developed. Nine immunosuppressed minipigs were implanted with the U87 human glioblastoma cell line in both the left and right hemispheres. Computed tomography (CT) acquisitions were performed once a week to monitor tumor growth. Among the 9 implanted animals, 8 minipigs showed significant macroscopic tumors on CT acquisitions. Histological examination of the brain after euthanasia confirmed the CT imaging findings with the presence of an undifferentiated glioma. Yucatan minipig, given its brain size and anatomy (gyrencephalic structure) which are comparable to humans, provides a reliable brain tumor model for preclinical studies of different therapeutic METHODS: in realistic conditions. Moreover, the short development time, the lower cyclosporine and caring cost and the compatibility with the size of commercialized stereotactic frames make it an affordable and practical animal model, especially in comparison with large breed pigs. This reproducible glioma model could simulate human anatomical conditions in preclinical studies and facilitate the improvement of novel therapeutic devices, designed at the human scale from the outset. Copyright © 2017 Elsevier B.V. All rights reserved.

Doubly Selective Multiple Quantum Chemical Shift Imaging and T1 Relaxation Time Measurement of Glutathione (GSH) in the Human Brain In Vivo

PubMed Central

Choi, In-Young; Lee, Phil

2012-01-01

Mapping of a major antioxidant, glutathione (GSH), was achieved in the human brain in vivo using a doubly selective multiple quantum filtering based chemical shift imaging (CSI) of GSH at 3 T. Both in vivo and phantom tests in CSI and single voxel measurements were consistent with excellent suppression of overlapping signals from creatine, γ-Amino butyric acid (GABA) and macromolecules. The GSH concentration in the fronto-parietal region was 1.20 ± 0.16 µmol/g (mean ± SD, n = 7). The longitudinal relaxation time (T1) of GSH in the human brain was 397 ± 44 ms (mean ± SD, n = 5), which was substantially shorter than those of other metabolites. This GSH CSI method permits us to address regional differences of GSH in the human brain with conditions where oxidative stress has been implicated, including multiple sclerosis, aging and neurodegenerative diseases. PMID:22730142

Differentiation and characterization of human pluripotent stem cell-derived brain microvascular endothelial cells.

PubMed

Stebbins, Matthew J; Wilson, Hannah K; Canfield, Scott G; Qian, Tongcheng; Palecek, Sean P; Shusta, Eric V

2016-05-15

The blood-brain barrier (BBB) is a critical component of the central nervous system (CNS) that regulates the flux of material between the blood and the brain. Because of its barrier properties, the BBB creates a bottleneck to CNS drug delivery. Human in vitro BBB models offer a potential tool to screen pharmaceutical libraries for CNS penetration as well as for BBB modulators in development and disease, yet primary and immortalized models respectively lack scalability and robust phenotypes. Recently, in vitro BBB models derived from human pluripotent stem cells (hPSCs) have helped overcome these challenges by providing a scalable and renewable source of human brain microvascular endothelial cells (BMECs). We have demonstrated that hPSC-derived BMECs exhibit robust structural and functional characteristics reminiscent of the in vivo BBB. Here, we provide a detailed description of the methods required to differentiate and functionally characterize hPSC-derived BMECs to facilitate their widespread use in downstream applications. Copyright © 2015 Elsevier Inc. All rights reserved.

Putting the brain to work: neuroergonomics past, present, and future.

PubMed

Parasuraman, Raja; Wilson, Glenn F

2008-06-01

The authors describe research and applications in prominent areas of neuroergonomics. Because human factors/ergonomics examines behavior and mind at work, it should include the study of brain mechanisms underlying human performance. Neuroergonomic studies are reviewed in four areas: workload and vigilance, adaptive automation, neuroengineering, and molecular genetics and individual differences. Neuroimaging studies have helped identify the components of mental workload, workload assessment in complex tasks, and resource depletion in vigilance. Furthermore, real-time neurocognitive assessment of workload can trigger adaptive automation. Neural measures can also drive brain-computer interfaces to provide disabled users new communication channels. Finally, variants of particular genes can be associated with individual differences in specific cognitive functions. Neuroergonomics shows that considering what makes work possible - the human brain - can enrich understanding of the use of technology by humans and can inform technological design. Applications of neuroergonomics include the assessment of operator workload and vigilance, implementation of real-time adaptive automation, neuroengineering for people with disabilities, and design of selection and training methods.

Free-floating adult human brain-derived slice cultures as a model to study the neuronal impact of Alzheimer's disease-associated Aβ oligomers.

PubMed

Mendes, Niele D; Fernandes, Artur; Almeida, Glaucia M; Santos, Luis E; Selles, Maria Clara; Lyra-Silva, Natalia; Machado, Carla M; Horta-Júnior, José A C; Louzada, Paulo R; De Felice, Fernanda G; Alvez-Leon, Soniza; Marcondes, Jorge; Assirati, João Alberto; Matias, Caio M; Klein, William L; Garcia-Cairasco, Norberto; Ferreira, Sergio T; Neder, Luciano; Sebollela, Adriano

2018-05-31

Slice cultures have been prepared from several organs. With respect to the brain, advantages of slice cultures over dissociated cell cultures include maintenance of the cytoarchitecture and neuronal connectivity. Slice cultures from adult human brain have been reported and constitute a promising method to study neurological diseases. Despite this potential, few studies have characterized in detail cell survival and function along time in short-term, free-floating cultures. We used tissue from adult human brain cortex from patients undergoing temporal lobectomy to prepare 200 μm-thick slices. Along the period in culture, we evaluated neuronal survival, histological modifications, and neurotransmitter release. The toxicity of Alzheimer's-associated Aβ oligomers (AβOs) to cultured slices was also analyzed. Neurons in human brain slices remain viable and neurochemically active for at least four days in vitro, which allowed detection of binding of AβOs. We further found that slices exposed to AβOs presented elevated levels of hyperphosphorylated Tau, a hallmark of Alzheimer's disease. Although slice cultures from adult human brain have been previously prepared, this is the first report to analyze cell viability and neuronal activity in short-term free-floating cultures as a function of days in vitro. Once surgical tissue is available, the current protocol is easy to perform and produces functional slices from adult human brain. These slice cultures may represent a preferred model for translational studies of neurodegenerative disorders when long term culturing in not required, as in investigations on AβO neurotoxicity. Copyright © 2018 Elsevier B.V. All rights reserved.

Multiclassifier fusion in human brain MR segmentation: modelling convergence.

PubMed

Heckemann, Rolf A; Hajnal, Joseph V; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2006-01-01

Segmentations of MR images of the human brain can be generated by propagating an existing atlas label volume to the target image. By fusing multiple propagated label volumes, the segmentation can be improved. We developed a model that predicts the improvement of labelling accuracy and precision based on the number of segmentations used as input. Using a cross-validation study on brain image data as well as numerical simulations, we verified the model. Fit parameters of this model are potential indicators of the quality of a given label propagation method or the consistency of the input segmentations used.

Maternal Support and Brain Development: Neuroscience Validation for the Importance of Early Caregiving Relationships

ERIC Educational Resources Information Center

Luby, Joan; Rogers, Cynthia

2013-01-01

Advances in brain imaging methods and technology over the last 2 decades have opened an unprecedented window into the understanding of the structure and function of the human brain. In this article, the authors describe their investigation of the relationship between maternal support, observed during the preschool period, and the size of key brain…

Decoding Lifespan Changes of the Human Brain Using Resting-State Functional Connectivity MRI

PubMed Central

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8–79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' “brain ages” from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI. PMID:22952990

Decoding lifespan changes of the human brain using resting-state functional connectivity MRI.

PubMed

Wang, Lubin; Su, Longfei; Shen, Hui; Hu, Dewen

2012-01-01

The development of large-scale functional brain networks is a complex, lifelong process that can be investigated using resting-state functional connectivity MRI (rs-fcMRI). In this study, we aimed to decode the developmental dynamics of the whole-brain functional network in seven decades (8-79 years) of the human lifespan. We first used parametric curve fitting to examine linear and nonlinear age effect on the resting human brain, and then combined manifold learning and support vector machine methods to predict individuals' "brain ages" from rs-fcMRI data. We found that age-related changes in interregional functional connectivity exhibited spatially and temporally specific patterns. During brain development from childhood to senescence, functional connections tended to linearly increase in the emotion system and decrease in the sensorimotor system; while quadratic trajectories were observed in functional connections related to higher-order cognitive functions. The complex patterns of age effect on the whole-brain functional network could be effectively represented by a low-dimensional, nonlinear manifold embedded in the functional connectivity space, which uncovered the inherent structure of brain maturation and aging. Regression of manifold coordinates with age further showed that the manifold representation extracted sufficient information from rs-fcMRI data to make prediction about individual brains' functional development levels. Our study not only gives insights into the neural substrates that underlie behavioral and cognitive changes over age, but also provides a possible way to quantitatively describe the typical and atypical developmental progression of human brain function using rs-fcMRI.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

The maternal brain and its plasticity in humans

PubMed Central

Kim, Pilyoung; Strathearn, Lane; Swain, James E.

2015-01-01

Early mother-infant relationships play important roles in infants’ optimal development. New mothers undergo neurobiological changes that support developing mother-infant relationships regardless of great individual differences in those relationships. In this article, we review the neural plasticity in human mothers’ brains based on functional magnetic resonance imaging (fMRI) studies. First, we review the neural circuits that are involved in establishing and maintaining mother-infant relationships. Second, we discuss early postpartum factors (e.g., birth and feeding methods, hormones, and parental sensitivity) that are associated with individual differences in maternal brain neuroplasticity. Third, we discuss abnormal changes in the maternal brain related to psychopathology (i.e., postpartum depression, posttraumatic stress disorder, substance abuse) and potential brain remodeling associated with interventions. Last, we highlight potentially important future research directions to better understand normative changes in the maternal brain and risks for abnormal changes that may disrupt early mother-infant relationships. PMID:26268151

Chemical Probes for Visualizing Intact Animal and Human Brain Tissue.

PubMed

Lai, Hei Ming; Ng, Wai-Lung; Gentleman, Steve M; Wu, Wutian

2017-06-22

Newly developed tissue clearing techniques can be used to render intact tissues transparent. When combined with fluorescent labeling technologies and optical sectioning microscopy, this allows visualization of fine structure in three dimensions. Gene-transfection techniques have proved very useful in visualizing cellular structures in animal models, but they are not applicable to human brain tissue. Here, we discuss the characteristics of an ideal chemical fluorescent probe for use in brain and other cleared tissues, and offer a comprehensive overview of currently available chemical probes. We describe their working principles and compare their performance with the goal of simplifying probe selection for neuropathologists and stimulating probe development by chemists. We propose several approaches for the development of innovative chemical labeling methods which, when combined with tissue clearing, have the potential to revolutionize how we study the structure and function of the human brain. Copyright © 2017 Elsevier Ltd. All rights reserved.

Big data challenges in decoding cortical activity in a human with quadriplegia to inform a brain computer interface.

PubMed

Friedenberg, David A; Bouton, Chad E; Annetta, Nicholas V; Skomrock, Nicholas; Mingming Zhang; Schwemmer, Michael; Bockbrader, Marcia A; Mysiw, W Jerry; Rezai, Ali R; Bresler, Herbert S; Sharma, Gaurav

2016-08-01

Recent advances in Brain Computer Interfaces (BCIs) have created hope that one day paralyzed patients will be able to regain control of their paralyzed limbs. As part of an ongoing clinical study, we have implanted a 96-electrode Utah array in the motor cortex of a paralyzed human. The array generates almost 3 million data points from the brain every second. This presents several big data challenges towards developing algorithms that should not only process the data in real-time (for the BCI to be responsive) but are also robust to temporal variations and non-stationarities in the sensor data. We demonstrate an algorithmic approach to analyze such data and present a novel method to evaluate such algorithms. We present our methodology with examples of decoding human brain data in real-time to inform a BCI.

Brains, genes, and primates.

PubMed

Izpisua Belmonte, Juan Carlos; Callaway, Edward M; Caddick, Sarah J; Churchland, Patricia; Feng, Guoping; Homanics, Gregg E; Lee, Kuo-Fen; Leopold, David A; Miller, Cory T; Mitchell, Jude F; Mitalipov, Shoukhrat; Moutri, Alysson R; Movshon, J Anthony; Okano, Hideyuki; Reynolds, John H; Ringach, Dario; Sejnowski, Terrence J; Silva, Afonso C; Strick, Peter L; Wu, Jun; Zhang, Feng

2015-05-06

One of the great strengths of the mouse model is the wide array of genetic tools that have been developed. Striking examples include methods for directed modification of the genome, and for regulated expression or inactivation of genes. Within neuroscience, it is now routine to express reporter genes, neuronal activity indicators, and opsins in specific neuronal types in the mouse. However, there are considerable anatomical, physiological, cognitive, and behavioral differences between the mouse and the human that, in some areas of inquiry, limit the degree to which insights derived from the mouse can be applied to understanding human neurobiology. Several recent advances have now brought into reach the goal of applying these tools to understanding the primate brain. Here we describe these advances, consider their potential to advance our understanding of the human brain and brain disorders, discuss bioethical considerations, and describe what will be needed to move forward. Copyright © 2015 Elsevier Inc. All rights reserved.

Brains, Genes and Primates

PubMed Central

Belmonte, Juan Carlos Izpisua; Callaway, Edward M.; Churchland, Patricia; Caddick, Sarah J.; Feng, Guoping; Homanics, Gregg E.; Lee, Kuo-Fen; Leopold, David A.; Miller, Cory T.; Mitchell, Jude F.; Mitalipov, Shoukhrat; Moutri, Alysson R.; Movshon, J. Anthony; Okano, Hideyuki; Reynolds, John H.; Ringach, Dario; Sejnowski, Terrence J.; Silva, Afonso C.; Strick, Peter L.; Wu, Jun; Zhang, Feng

2015-01-01

One of the great strengths of the mouse model is the wide array of genetic tools that have been developed. Striking examples include methods for directed modification of the genome, and for regulated expression or inactivation of genes. Within neuroscience, it is now routine to express reporter genes, neuronal activity indicators and opsins in specific neuronal types in the mouse. However, there are considerable anatomical, physiological, cognitive and behavioral differences between the mouse and the human that, in some areas of inquiry, limit the degree to which insights derived from the mouse can be applied to understanding human neurobiology. Several recent advances have now brought into reach the goal of applying these tools to understanding the primate brain. Here we describe these advances, consider their potential to advance our understanding of the human brain and brain disorders, discuss bioethical considerations, and describe what will be needed to move forward. PMID:25950631

In Silico Prediction for Intestinal Absorption and Brain Penetration of Chemical Pesticides in Humans.

PubMed

Chedik, Lisa; Mias-Lucquin, Dominique; Bruyere, Arnaud; Fardel, Olivier

2017-06-30

Intestinal absorption and brain permeation constitute key parameters of toxicokinetics for pesticides, conditioning their toxicity, including neurotoxicity. However, they remain poorly characterized in humans. The present study was therefore designed to evaluate human intestine and brain permeation for a large set of pesticides ( n = 338) belonging to various chemical classes, using an in silico graphical BOILED-Egg/SwissADME online method based on lipophilicity and polarity that was initially developed for drugs. A high percentage of the pesticides (81.4%) was predicted to exhibit high intestinal absorption, with a high accuracy (96%), whereas a lower, but substantial, percentage (38.5%) displayed brain permeation. Among the pesticide classes, organochlorines ( n = 30) constitute the class with the lowest percentage of intestine-permeant members (40%), whereas that of the organophosphorus compounds ( n = 99) has the lowest percentage of brain-permeant chemicals (9%). The predictions of the permeations for the pesticides were additionally shown to be significantly associated with various molecular descriptors well-known to discriminate between permeant and non-permeant drugs. Overall, our in silico data suggest that human exposure to pesticides through the oral way is likely to result in an intake of these dietary contaminants for most of them and brain permeation for some of them, thus supporting the idea that they have toxic effects on human health, including neurotoxic effects.

In Silico Prediction for Intestinal Absorption and Brain Penetration of Chemical Pesticides in Humans

PubMed Central

Chedik, Lisa; Mias-Lucquin, Dominique; Bruyere, Arnaud; Fardel, Olivier

2017-01-01

Intestinal absorption and brain permeation constitute key parameters of toxicokinetics for pesticides, conditioning their toxicity, including neurotoxicity. However, they remain poorly characterized in humans. The present study was therefore designed to evaluate human intestine and brain permeation for a large set of pesticides (n = 338) belonging to various chemical classes, using an in silico graphical BOILED-Egg/SwissADME online method based on lipophilicity and polarity that was initially developed for drugs. A high percentage of the pesticides (81.4%) was predicted to exhibit high intestinal absorption, with a high accuracy (96%), whereas a lower, but substantial, percentage (38.5%) displayed brain permeation. Among the pesticide classes, organochlorines (n = 30) constitute the class with the lowest percentage of intestine-permeant members (40%), whereas that of the organophosphorus compounds (n = 99) has the lowest percentage of brain-permeant chemicals (9%). The predictions of the permeations for the pesticides were additionally shown to be significantly associated with various molecular descriptors well-known to discriminate between permeant and non-permeant drugs. Overall, our in silico data suggest that human exposure to pesticides through the oral way is likely to result in an intake of these dietary contaminants for most of them and brain permeation for some of them, thus supporting the idea that they have toxic effects on human health, including neurotoxic effects. PMID:28665355

Methods to uncover an antibody epitope in the KPI domain of Alzheimer's amyloid precursor protein for immunohistochemistry in human brain.

PubMed

Campbell, E; Pearson, R C; Parkinson, D

1999-11-15

A novel polyclonal antibody (Ab993), specific for a KPI domain epitope of APP, was characterised for use in immunoprecipitation, Western blotting and immunohistochemistry. Conditioned medium from NTera2/D1 cells was used for immunoprecipitation and Western blots. Paraffin-embedded human brain sections were used for immunohistochemistry. The antibody recognised KPI-containing APP on Western blots after standard solubilisation but immunoprecipitation of soluble APP required reduction with 2-mercaptoethanol followed by alkylation of reduced sulphydryl bonds with sodium iodoacetate. Immunohistochemical staining of human brain sections was significantly enhanced by this pre-treatment. Microwaving of sections also increased immunolabelling, by a mechanism that was additive to reduction and alkylation. Incubation in 80% formic acid did not confer any enhancement of immunoreactivity. Ab993, applied with the methods reported here, is expected to be valuable in investigations of the pathogenesis of Alzheimer's disease to determine the source of the beta-amyloid peptide.

Soluble Amyloid-beta Aggregates from Human Alzheimer’s Disease Brains

PubMed Central

Esparza, Thomas J.; Wildburger, Norelle C.; Jiang, Hao; Gangolli, Mihika; Cairns, Nigel J.; Bateman, Randall J.; Brody, David L.

2016-01-01

Soluble amyloid-beta (Aβ) aggregates likely contribute substantially to the dementia that characterizes Alzheimer’s disease. However, despite intensive study of in vitro preparations and animal models, little is known about the characteristics of soluble Aβ aggregates in the human Alzheimer’s disease brain. Here we present a new method for extracting soluble Aβ aggregates from human brains, separating them from insoluble aggregates and Aβ monomers using differential ultracentrifugation, and purifying them >6000 fold by dual antibody immunoprecipitation. The method resulted in <40% loss of starting material, no detectible ex vivo aggregation of monomeric Aβ, and no apparent ex vivo alterations in soluble aggregate sizes. By immunoelectron microscopy, soluble Aβ aggregates typically appear as clusters of 10–20 nanometer diameter ovoid structures with 2-3 amino-terminal Aβ antibody binding sites, distinct from previously characterized structures. This approach may facilitate investigation into the characteristics of native soluble Aβ aggregates, and deepen our understanding of Alzheimer’s dementia. PMID:27917876

Resolving anatomical and functional structure in human brain organization: identifying mesoscale organization in weighted network representations.

PubMed

Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M

2014-10-01

Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.

Medical diagnosis imaging systems: image and signal processing applications aided by fuzzy logic

NASA Astrophysics Data System (ADS)

Hata, Yutaka

2010-04-01

First, we describe an automated procedure for segmenting an MR image of a human brain based on fuzzy logic for diagnosing Alzheimer's disease. The intensity thresholds for segmenting the whole brain of a subject are automatically determined by finding the peaks of the intensity histogram. After these thresholds are evaluated in a region growing, the whole brain can be identified. Next, we describe a procedure for decomposing the obtained whole brain into the left and right cerebral hemispheres, the cerebellum and the brain stem. Our method then identified the whole brain, the left cerebral hemisphere, the right cerebral hemisphere, the cerebellum and the brain stem. Secondly, we describe a transskull sonography system that can visualize the shape of the skull and brain surface from any point to examine skull fracture and some brain diseases. We employ fuzzy signal processing to determine the skull and brain surface. The phantom model, the animal model with soft tissue, the animal model with brain tissue, and a human subjects' forehead is applied in our system. The all shapes of the skin surface, skull surface, skull bottom, and brain tissue surface are successfully determined.

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.

Defining functional SMA and pre-SMA subregions in human MFC using resting state fMRI: functional connectivity-based parcellation method.

PubMed

Kim, Jae-Hun; Lee, Jong-Min; Jo, Hang Joon; Kim, Sook Hui; Lee, Jung Hee; Kim, Sung Tae; Seo, Sang Won; Cox, Robert W; Na, Duk L; Kim, Sun I; Saad, Ziad S

2010-02-01

Noninvasive parcellation of the human cerebral cortex is an important goal for understanding and examining brain functions. Recently, the patterns of anatomical connections using diffusion tensor imaging (DTI) have been used to parcellate brain regions. Here, we present a noninvasive parcellation approach that uses "functional fingerprints" obtained by correlation measures on resting state functional magnetic resonance imaging (fMRI) data to parcellate brain regions. In other terms, brain regions are parcellated based on the similarity of their connection--as reflected by correlation during resting state--to the whole brain. The proposed method was used to parcellate the medial frontal cortex (MFC) into supplementary motor areas (SMA) and pre-SMA subregions. In agreement with anatomical landmark-based parcellation, we find that functional fingerprint clustering of the MFC results in anterior and posterior clusters. The probabilistic maps from 12 subjects showed that the anterior cluster is mainly located rostral to the vertical commissure anterior (VCA) line, whereas the posterior cluster is mainly located caudal to VCA line, suggesting the homologues of pre-SMA and SMA. The functional connections from the putative pre-SMA cluster were connected to brain regions which are responsible for complex/cognitive motor control, whereas those from the putative SMA cluster were connected to brain regions which are related to the simple motor control. These findings demonstrate the feasibility of the functional connectivity-based parcellation of the human cerebral cortex using resting state fMRI. Copyright (c) 2009 Elsevier Inc. All rights reserved.

EEG slow waves in traumatic brain injury: Convergent findings in mouse and man

PubMed Central

Modarres, Mo; Kuzma, Nicholas N.; Kretzmer, Tracy; Pack, Allan I.; Lim, Miranda M.

2016-01-01

Objective Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). Methods We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. Results Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). Conclusion and implications Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms. PMID:28018987

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

Hemispherical map for the human brain cortex

NASA Astrophysics Data System (ADS)

Tosun, Duygu; Prince, Jerry L.

2001-07-01

Understanding the function of the human brain cortex is a primary goal in human brain mapping. Methods to unfold and flatten the cortical surface for visualization and measurement have been described in previous literature; but comparison across multiple subjects is still difficult because of the lack of a standard mapping technique. We describe a new approach that maps each hemisphere of the cortex to a portion of a sphere in a standard way, making comparison of anatomy and function across different subjects possible. Starting with a three-dimensional magnetic resonance image of the brain, the cortex is segmented and represented as a triangle mesh. Defining a cut around the corpus collosum identifies the left and right hemispheres. Together, the two hemispheres are mapped to the complex plane using a conformal mapping technique. A Mobius transformation, which is conformal, is used to transform the points on the complex plane so that a projective transformation maps each brain hemisphere onto a spherical segment comprising a sphere with a cap removed. We determined the best size of the spherical cap by minimizing the relative area distortion between hemispherical maps and original cortical surfaces. The relative area distortion between the hemispherical maps and the original cortical surfaces for fifteen human brains is analyzed.

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

Allen Brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system

PubMed Central

Sunkin, Susan M.; Ng, Lydia; Lau, Chris; Dolbeare, Tim; Gilbert, Terri L.; Thompson, Carol L.; Hawrylycz, Michael; Dang, Chinh

2013-01-01

The Allen Brain Atlas (http://www.brain-map.org) provides a unique online public resource integrating extensive gene expression data, connectivity data and neuroanatomical information with powerful search and viewing tools for the adult and developing brain in mouse, human and non-human primate. Here, we review the resources available at the Allen Brain Atlas, describing each product and data type [such as in situ hybridization (ISH) and supporting histology, microarray, RNA sequencing, reference atlases, projection mapping and magnetic resonance imaging]. In addition, standardized and unique features in the web applications are described that enable users to search and mine the various data sets. Features include both simple and sophisticated methods for gene searches, colorimetric and fluorescent ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, Brain Explorer software for 3D navigation of anatomy and gene expression, and an interactive reference atlas viewer. In addition, cross data set searches enable users to query multiple Allen Brain Atlas data sets simultaneously. All of the Allen Brain Atlas resources can be accessed through the Allen Brain Atlas data portal. PMID:23193282

(13)C MRS of human brain at 7 Tesla using [2-(13)C]glucose infusion and low power broadband stochastic proton decoupling.

PubMed

Li, Shizhe; An, Li; Yu, Shao; Ferraris Araneta, Maria; Johnson, Christopher S; Wang, Shumin; Shen, Jun

2016-03-01

Carbon-13 ((13)C) MR spectroscopy (MRS) of the human brain at 7 Tesla (T) may pose patient safety issues due to high radiofrequency (RF) power deposition for proton decoupling. The purpose of present work is to study the feasibility of in vivo (13)C MRS of human brain at 7 T using broadband low RF power proton decoupling. Carboxylic/amide (13)C MRS of human brain by broadband stochastic proton decoupling was demonstrated on a 7 T scanner. RF safety was evaluated using the finite-difference time-domain method. (13)C signal enhancement by nuclear Overhauser effect (NOE) and proton decoupling was evaluated in both phantoms and in vivo. At 7 T, the peak amplitude of carboxylic/amide (13)C signals was increased by a factor of greater than 4 due to the combined effects of NOE and proton decoupling. The 7 T (13)C MRS technique used decoupling power and average transmit power of less than 35 watts (W) and 3.6 W, respectively. In vivo (13)C MRS studies of human brain can be performed at 7 T, well below the RF safety threshold, by detecting carboxylic/amide carbons with broadband stochastic proton decoupling. © 2015 Wiley Periodicals, Inc.

Cryo-image Analysis of Tumor Cell Migration, Invasion, and Dispersal in a Mouse Xenograft Model of Human Glioblastoma Multiforme

PubMed Central

Qutaish, Mohammed Q.; Sullivant, Kristin E.; Burden-Gulley, Susan M.; Lu, Hong; Roy, Debashish; Wang, Jing; Basilion, James P.; Brady-Kalnay, Susann M.; Wilson, David L.

2012-01-01

Purpose The goals of this study were to create cryo-imaging methods to quantify characteristics (size, dispersal, and blood vessel density) of mouse orthotopic models of glioblastoma multiforme (GBM) and to enable studies of tumor biology, targeted imaging agents, and theranostic nanoparticles. Procedures Green fluorescent protein-labeled, human glioma LN-229 cells were implanted into mouse brain. At 20–38 days, cryo-imaging gave whole brain, 4-GB, 3D microscopic images of bright field anatomy, including vasculature, and fluorescent tumor. Image analysis/visualization methods were developed. Results Vessel visualization and segmentation methods successfully enabled analyses. The main tumor mass volume, the number of dispersed clusters, the number of cells/cluster, and the percent dispersed volume all increase with age of the tumor. Histograms of dispersal distance give a mean and median of 63 and 56 μm, respectively, averaged over all brains. Dispersal distance tends to increase with age of the tumors. Dispersal tends to occur along blood vessels. Blood vessel density did not appear to increase in and around the tumor with this cell line. Conclusion Cryo-imaging and software allow, for the first time, 3D, whole brain, microscopic characterization of a tumor from a particular cell line. LN-229 exhibits considerable dispersal along blood vessels, a characteristic of human tumors that limits treatment success. PMID:22125093

Purification of α-Synuclein from Human Brain Reveals an Instability of Endogenous Multimers as the Protein Approaches Purity

PubMed Central

2015-01-01

Despite two decades of research, the structure–function relationships of endogenous, physiological forms of α-synuclein (αSyn) are not well understood. Most in vitro studies of this Parkinson’s disease-related protein have focused on recombinant αSyn that is unfolded and monomeric, assuming that this represents its state in the normal human brain. Recently, we have provided evidence that αSyn exists in considerable part in neurons, erythrocytes, and other cells as a metastable multimer that principally sizes as a tetramer. In contrast to recombinant αSyn, physiological tetramers purified from human erythrocytes have substantial α-helical content and resist pathological aggregation into β-sheet rich fibers. Here, we report the first method to fully purify soluble αSyn from the most relevant source, human brain. We describe protocols that purify αSyn to homogeneity from nondiseased human cortex using ammonium sulfate precipitation, gel filtration, and ion exchange, hydrophobic interaction, and affinity chromatographies. Cross-linking of the starting material and the partially purified chromatographic fractions revealed abundant αSyn multimers, including apparent tetramers, but these were destabilized in large part to monomers during the final purification step. The method also fully purified the homologue β-synuclein, with a similar outcome. Circular dichroism spectroscopy showed that purified, brain-derived αSyn can display more helical content than the recombinant protein, but this result varied. Collectively, our data suggest that purifying αSyn to homogeneity destabilizes native, α-helix-rich multimers that exist in intact and partially purified brain samples. This finding suggests existence of a stabilizing cofactor (e.g., a small lipid) present inside neurons that is lost during final purification. PMID:25490121

Assessing Environmental Exposure to β-N-Methylamino-L-Alanine (BMAA) in Complex Sample Matrices: a Comparison of the Three Most Popular LC-MS/MS Methods.

PubMed

Baker, Teesha C; Tymm, Fiona J M; Murch, Susan J

2018-01-01

β-N-Methylamino-L-alanine (BMAA) is a naturally occurring non-protein amino acid produced by cyanobacteria, accumulated through natural food webs, found in mammalian brain tissues. Recent evidence indicates an association between BMAA and neurological disease. The accurate detection and quantification of BMAA in food and environmental samples are critical to understanding BMAA metabolism and limiting human exposure. To date, there have been more than 78 reports on BMAA in cyanobacteria and human samples, but different methods give conflicting data and divergent interpretations in the literature. The current work was designed to determine whether orthogonal chromatography and mass spectrometry methods give consistent data interpretation from a single sample matrix using the three most common analytical methods. The methods were recreated as precisely as possible from the literature with optimization of the mass spectrometry parameters specific to the instrument. Four sample matrices, cyanobacteria, human brain, blue crab, and Spirulina, were analyzed as 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) derivatives, propyl chloroformate (PCF) derivatives separated by reverse phase chromatography, or underivatized extracts separated by HILIC chromatography. The three methods agreed on positive detection of BMAA in cyanobacteria and no detected BMAA in the sample of human brain matrix. Interpretation was less clear for a sample of blue crab which was strongly positive for BMAA by AQC and PCF but negative by HILIC and for four spirulina raw materials that were negative by PCF but positive by AQC and HILIC. Together, these data demonstrate that the methods gave different results and that the choices in interpretation of the methods determined whether BMAA was detected. Failure to detect BMAA cannot be considered proof of absence.

Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution.

PubMed

Smaers, J B; Soligo, C

2013-05-22

Comparative analyses of primate brain evolution have highlighted changes in size and internal organization as key factors underlying species diversity. It remains, however, unclear (i) how much variation in mosaic brain reorganization versus variation in relative brain size contributes to explaining the structural neural diversity observed across species, (ii) which mosaic changes contribute most to explaining diversity, and (iii) what the temporal origin, rates and processes are that underlie evolutionary shifts in mosaic reorganization for individual branches of the primate tree of life. We address these questions by combining novel comparative methods that allow assessing the temporal origin, rate and process of evolutionary changes on individual branches of the tree of life, with newly available data on volumes of key brain structures (prefrontal cortex, frontal motor areas and cerebrocerebellum) for a sample of 17 species (including humans). We identify patterns of mosaic change in brain evolution that mirror brain systems previously identified by electrophysiological and anatomical tract-tracing studies in non-human primates and functional connectivity MRI studies in humans. Across more than 40 Myr of anthropoid primate evolution, mosaic changes contribute more to explaining neural diversity than changes in relative brain size, and different mosaic patterns are differentially selected for when brains increase or decrease in size. We identify lineage-specific evolutionary specializations for all branches of the tree of life covered by our sample and demonstrate deep evolutionary roots for mosaic patterns associated with motor control and learning.

Brain reorganization, not relative brain size, primarily characterizes anthropoid brain evolution

PubMed Central

Smaers, J. B.; Soligo, C.

2013-01-01

Comparative analyses of primate brain evolution have highlighted changes in size and internal organization as key factors underlying species diversity. It remains, however, unclear (i) how much variation in mosaic brain reorganization versus variation in relative brain size contributes to explaining the structural neural diversity observed across species, (ii) which mosaic changes contribute most to explaining diversity, and (iii) what the temporal origin, rates and processes are that underlie evolutionary shifts in mosaic reorganization for individual branches of the primate tree of life. We address these questions by combining novel comparative methods that allow assessing the temporal origin, rate and process of evolutionary changes on individual branches of the tree of life, with newly available data on volumes of key brain structures (prefrontal cortex, frontal motor areas and cerebrocerebellum) for a sample of 17 species (including humans). We identify patterns of mosaic change in brain evolution that mirror brain systems previously identified by electrophysiological and anatomical tract-tracing studies in non-human primates and functional connectivity MRI studies in humans. Across more than 40 Myr of anthropoid primate evolution, mosaic changes contribute more to explaining neural diversity than changes in relative brain size, and different mosaic patterns are differentially selected for when brains increase or decrease in size. We identify lineage-specific evolutionary specializations for all branches of the tree of life covered by our sample and demonstrate deep evolutionary roots for mosaic patterns associated with motor control and learning. PMID:23536600

A Four-Dimensional Probabilistic Atlas of the Human Brain

PubMed Central

Mazziotta, John; Toga, Arthur; Evans, Alan; Fox, Peter; Lancaster, Jack; Zilles, Karl; Woods, Roger; Paus, Tomas; Simpson, Gregory; Pike, Bruce; Holmes, Colin; Collins, Louis; Thompson, Paul; MacDonald, David; Iacoboni, Marco; Schormann, Thorsten; Amunts, Katrin; Palomero-Gallagher, Nicola; Geyer, Stefan; Parsons, Larry; Narr, Katherine; Kabani, Noor; Le Goualher, Georges; Feidler, Jordan; Smith, Kenneth; Boomsma, Dorret; Pol, Hilleke Hulshoff; Cannon, Tyrone; Kawashima, Ryuta; Mazoyer, Bernard

2001-01-01

The authors describe the development of a four-dimensional atlas and reference system that includes both macroscopic and microscopic information on structure and function of the human brain in persons between the ages of 18 and 90 years. Given the presumed large but previously unquantified degree of structural and functional variance among normal persons in the human population, the basis for this atlas and reference system is probabilistic. Through the efforts of the International Consortium for Brain Mapping (ICBM), 7,000 subjects will be included in the initial phase of database and atlas development. For each subject, detailed demographic, clinical, behavioral, and imaging information is being collected. In addition, 5,800 subjects will contribute DNA for the purpose of determining genotype– phenotype–behavioral correlations. The process of developing the strategies, algorithms, data collection methods, validation approaches, database structures, and distribution of results is described in this report. Examples of applications of the approach are described for the normal brain in both adults and children as well as in patients with schizophrenia. This project should provide new insights into the relationship between microscopic and macroscopic structure and function in the human brain and should have important implications in basic neuroscience, clinical diagnostics, and cerebral disorders. PMID:11522763

Biological bases of human musicality.

PubMed

Perrone-Capano, Carla; Volpicelli, Floriana; di Porzio, Umberto

2017-04-01

Music is a universal language, present in all human societies. It pervades the lives of most human beings and can recall memories and feelings of the past, can exert positive effects on our mood, can be strongly evocative and ignite intense emotions, and can establish or strengthen social bonds. In this review, we summarize the research and recent progress on the origins and neural substrates of human musicality as well as the changes in brain plasticity elicited by listening or performing music. Indeed, music improves performance in a number of cognitive tasks and may have beneficial effects on diseased brains. The emerging picture begins to unravel how and why particular brain circuits are affected by music. Numerous studies show that music affects emotions and mood, as it is strongly associated with the brain's reward system. We can therefore assume that an in-depth study of the relationship between music and the brain may help to shed light on how the mind works and how the emotions arise and may improve the methods of music-based rehabilitation for people with neurological disorders. However, many facets of the mind-music connection still remain to be explored and enlightened.

Chemical exchange saturation transfer MRI contrast in the human brain at 9.4 T.

PubMed

Zaiss, Moritz; Schuppert, Mark; Deshmane, Anagha; Herz, Kai; Ehses, Philipp; Füllbier, Lars; Lindig, Tobias; Bender, Benjamin; Ernemann, Ulrike; Scheffler, Klaus

2018-06-15

The high chemical shift separation at 9.4 T allows for selective saturation of proton pools in exchange with water protons. For the first time, highly selective and comprehensive chemical exchange saturation transfer (CEST) experiments were performed in the human brain at 9.4 T. This work provides insight into CEST signals in the human brain in comparison with existing animal studies, as well as with CEST effects in vivo at lower field strengths. A novel snapshot-CEST method for human brain scans at 9.4 T was optimized and employed for highly-spectrally-resolved (95 offsets) CEST measurements in healthy subjects and one brain tumor patient. Reproducibility and stability between scans was verified in grey and white matter after B 0 , B 1 , and motion correction of the acquired 3D CEST volumes. Two-step Lorentzian fitting was used to further improve separation of spectrally discernible signals to create known and novel CEST contrast maps at 9.4 T. At a saturation power of B 1  = 0.5 μT most selective CEST effects could be obtained in the human brain with high inter-scan reproducibility. While contrast behavior of previously measured signals at lower field, namely amide-, guanidyl- and NOE-CEST effects, could be reproduced, novel signals at 2.7 ppm, and -1.6 ppm could be verified in healthy subjects and in a brain tumor patient for the first time. High spectral resolution chemical exchange saturation transfer at 9.4 T allows deeper insights into the Z-spectrum structure of the human brain, and provides many different contrasts showing different correlations in healthy tissue and in tumor-affected areas of the brain, generating hypotheses for future investigations of in-vivo-CEST at UHF. Copyright © 2018 Elsevier Inc. All rights reserved.

Evidence for hubs in human functional brain networks

PubMed Central

Power, Jonathan D; Schlaggar, Bradley L; Lessov-Schlaggar, Christina N; Petersen, Steven E

2013-01-01

Summary Hubs integrate and distribute information in powerful ways due to the number and positioning of their contacts in a network. Several resting state functional connectivity MRI reports have implicated regions of the default mode system as brain hubs; we demonstrate that previous degree-based approaches to hub identification may have identified portions of large brain systems rather than critical nodes of brain networks. We utilize two methods to identify hub-like brain regions: 1) finding network nodes that participate in multiple sub-networks of the brain, and 2) finding spatial locations where several systems are represented within a small volume. These methods converge on a distributed set of regions that differ from previous reports on hubs. This work identifies regions that support multiple systems, leading to spatially constrained predictions about brain function that may be tested in terms of lesions, evoked responses, and dynamic patterns of activity. PMID:23972601

Correcting for strong eddy current induced B0 modulation enables two-spoke RF pulse design with parallel transmission: demonstration at 9.4T in the human brain.

PubMed

Wu, Xiaoping; Adriany, Gregor; Ugurbil, Kamil; Van de Moortele, Pierre-Francois

2013-01-01

Successful implementation of homogeneous slice-selective RF excitation in the human brain at 9.4T using 16-channel parallel transmission (pTX) is demonstrated. A novel three-step pulse design method incorporating fast real-time measurement of eddy current induced B0 variations as well as correction of resulting phase errors during excitation is described. To demonstrate the utility of the proposed method, phantom and in-vivo experiments targeting a uniform excitation in an axial slice were conducted using two-spoke pTX pulses. Even with the pre-emphasis activated, eddy current induced B0 variations with peak-to-peak values greater than 4 kHz were observed on our system during the rapid switches of slice selective gradients. This large B0 variation, when not corrected, resulted in drastically degraded excitation fidelity with the coefficient of variation (CV) of the flip angle calculated for the region of interest being large (~ 12% in the phantom and ~ 35% in the brain). By comparison, excitation fidelity was effectively restored, and satisfactory flip angle uniformity was achieved when using the proposed method, with the CV value reduced to ~ 3% in the phantom and ~ 8% in the brain. Additionally, experimental results were in good agreement with the numerical predictions obtained from Bloch simulations. Slice-selective flip angle homogenization in the human brain at 9.4T using 16-channel 3D spoke pTX pulses is achievable despite of large eddy current induced excitation phase errors; correcting for the latter was critical in this success.

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

A new use for long-term frozen brain tissue: Golgi impregnation

PubMed Central

Melendez-Ferro, Miguel; Perez-Costas, Emma; Roberts, Rosalinda C.

2009-01-01

The study of dendritic spine shape and number has become a standard in the analysis of synaptic transmission anomalies since a considerable number of neuropsychiatric and neurological diseases have their foundation in alterations in these structures. One of the best ways to study possible alterations of dendritic spines is the use of Golgi impregnation. Although usually the Golgi method implies the use of fresh or fixed tissue, here we report the use of Golgi-Cox for the staining of human and animal brain tissue kept frozen for long periods of time. We successfully applied the Golgi-Cox method to human brain tissue stored for up to 15 years in a freezer. The technique produced reliable and reproducible impregnation of dendrites and dendritic spines in different cortical areas. We also applied the same technique to rat brain frozen for up to one year, obtaining the same satisfactory results. The fact that Golgi-Cox can be successfully applied to this type of tissue adds a new value for hundreds of frozen human or animal brains kept in the freezers of the laboratories, that otherwise would not be useful for anything else. Researchers other than neuroanatomists, i.e. in fields such as biochemistry and molecular biology can also benefit from a simple and reliable technique that can be applied to tissue left from their primary experiments. PMID:18789970

Corallocins A-C, Nerve Growth and Brain-Derived Neurotrophic Factor Inducing Metabolites from the Mushroom Hericium coralloides.

PubMed

Wittstein, Kathrin; Rascher, Monique; Rupcic, Zeljka; Löwen, Eduard; Winter, Barbara; Köster, Reinhard W; Stadler, Marc

2016-09-23

Three new natural products, corallocins A-C (1-3), along with two known compounds were isolated from the mushroom Hericium coralloides. Their benzofuranone and isoindolinone structures were elucidated by spectral methods. All corallocins induced nerve growth factor and/or brain-derived neurotrophic factor expression in human 1321N1 astrocytes. Furthermore, corallocin B showed antiproliferative activity against HUVEC and human cancer cell lines MCF-7 and KB-3-1.

In vitro 3D regeneration-like growth of human patient brain tissue.

PubMed

Tang-Schomer, M D; Wu, W B; Kaplan, D L; Bookland, M J

2018-05-01

In vitro culture of primary neurons is widely adapted with embryonic but not mature brain tissue. Here, we extended a previously developed bioengineered three-dimensional (3D) embryonic brain tissue model to resected normal patient brain tissue in an attempt to regenerate human neurons in vitro. Single cells and small sized (diameter < 100 μm) spheroids from dissociated brain tissue were seeded into 3D silk fibroin-based scaffolds, with or without collagen or Matrigel, and compared with two-dimensional cultures and scaffold-free suspension cultures. Changes of cell phenotypes (neuronal, astroglial, neural progenitor, and neuroepithelial) were quantified with flow cytometry and analyzed with a new method of statistical analysis specifically designed for percentage comparison. Compared with a complete lack of viable cells in conventional neuronal cell culture condition, supplements of vascular endothelial growth factor-containing pro-endothelial cell condition led to regenerative growth of neurons and astroglial cells from "normal" human brain tissue of epilepsy surgical patients. This process involved delayed expansion of Nestin+ neural progenitor cells, emergence of TUJ1+ immature neurons, and Vimentin+ neuroepithelium-like cell sheet formation in prolonged cultures (14 weeks). Micro-tissue spheroids, but not single cells, supported the brain tissue growth, suggesting importance of preserving native cell-cell interactions. The presence of 3D scaffold, but not hydrogel, allowed for Vimentin+ cell expansion, indicating a different growth mechanism than pluripotent cell-based brain organoid formation. The slow and delayed process implied an origin of quiescent neural precursors in the neocortex tissue. Further optimization of the 3D tissue model with primary human brain cells could provide personalized brain disease models. Copyright © 2018 John Wiley & Sons, Ltd.

Skulls and Human Evolution: The Use of Casts of Anthropoid Skulls in Teaching Concepts of Human Evolution.

ERIC Educational Resources Information Center

Gipps, John

1991-01-01

Proposes the use of a series of 11 casts of fossil skulls as a method of teaching about the theory of human evolution. Students explore the questions of which skulls are "human" and which came first in Homo Sapien development, large brain or upright stance. (MDH)

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.

A novel method for fast imaging of brain function, non-invasively, with light

NASA Astrophysics Data System (ADS)

Chance, Britton; Anday, Endla; Nioka, Shoko; Zhou, Shuoming; Hong, Long; Worden, Katherine; Li, C.; Murray, T.; Ovetsky, Y.; Pidikiti, D.; Thomas, R.

1998-05-01

Imaging of the human body by any non-invasive technique has been an appropriate goal of physics and medicine, and great success has been obtained with both Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) in brain imaging. Non-imaging responses to functional activation using near infrared spectroscopy of brain (fNIR) obtained in 1993 (Chance, et al. [1]) and in 1994 (Tamura, et al. [2]) are now complemented with images of pre-frontal and parietal stimulation in adults and pre-term neonates in this communication (see also [3]). Prior studies used continuous [4], pulsed [3] or modulated [5] light. The amplitude and phase cancellation of optical patterns as demonstrated for single source detector pairs affords remarkable sensitivity of small object detection in model systems [6]. The methods have now been elaborated with multiple source detector combinations (nine sources, four detectors). Using simple back projection algorithms it is now possible to image sensorimotor and cognitive activation of adult and pre- and full-term neonate human brain function in times < 30 sec and with two dimensional resolutions of < 1 cm in two dimensional displays. The method can be used in evaluation of adult and neonatal cerebral dysfunction in a simple, portable and affordable method that does not require immobilization, as contrasted to MRI and PET.

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.

Simultaneous quantification of nicotine, opioids, cocaine, and metabolites in human fetal postmortem brain by liquid chromatography tandem mass spectrometry

PubMed Central

Shakleya, Diaa M.

2011-01-01

A validated method for simultaneous LCMSMS quantification of nicotine, cocaine, 6-acetylmorphine (6AM), codeine, and metabolites in 100 mg fetal human brain was developed and validated. After homogenization and solid-phase extraction, analytes were resolved on a Hydro-RP analytical column with gradient elution. Empirically determined linearity was from 5–5,000 pg/mg for cocaine and benzoylecgonine (BE), 25–5,000 pg/mg for cotinine, ecgonine methyl ester (EME) and 6AM, 50–5000 pg/mg for trans-3-hydroxycotinine (OH-cotinine) and codeine, and 250–5,000 pg/mg for nicotine. Potential endogenous and exogenous interferences were resolved. Intra- and inter-assay analytical recoveries were ≥92%, intra- and inter-day and total assay imprecision were ≤14% RSD and extraction efficiencies were ≥67.2% with ≤83% matrix effect. Method applicability was demonstrated with a postmortem fetal brain containing 40 pg/mg cotinine, 65 pg/mg OH-cotinine, 13 pg/mg cocaine, 34 pg/mg EME, and 525 pg/mg BE. This validated method is useful for determination of nicotine, opioid, and cocaine biomarkers in brain. PMID:19229524

LOGISMOS-B for primates: primate cortical surface reconstruction and thickness measurement

NASA Astrophysics Data System (ADS)

Oguz, Ipek; Styner, Martin; Sanchez, Mar; Shi, Yundi; Sonka, Milan

2015-03-01

Cortical thickness and surface area are important morphological measures with implications for many psychiatric and neurological conditions. Automated segmentation and reconstruction of the cortical surface from 3D MRI scans is challenging due to the variable anatomy of the cortex and its highly complex geometry. While many methods exist for this task in the context of the human brain, these methods are typically not readily applicable to the primate brain. We propose an innovative approach based on our recently proposed human cortical reconstruction algorithm, LOGISMOS-B, and the Laplace-based thickness measurement method. Quantitative evaluation of our approach was performed based on a dataset of T1- and T2-weighted MRI scans from 12-month-old macaques where labeling by our anatomical experts was used as independent standard. In this dataset, LOGISMOS-B has an average signed surface error of 0.01 +/- 0.03mm and an unsigned surface error of 0.42 +/- 0.03mm over the whole brain. Excluding the rather problematic temporal pole region further improves unsigned surface distance to 0.34 +/- 0.03mm. This high level of accuracy reached by our algorithm even in this challenging developmental dataset illustrates its robustness and its potential for primate brain studies.

A Method for Whole Brain Ex Vivo Magnetic Resonance Imaging with Minimal Susceptibility Artifacts

PubMed Central

Shatil, Anwar S.; Matsuda, Kant M.; Figley, Chase R.

2016-01-01

Magnetic resonance imaging (MRI) is a non-destructive technique that is capable of localizing pathologies and assessing other anatomical features (e.g., tissue volume, microstructure, and white matter connectivity) in postmortem, ex vivo human brains. However, when brains are removed from the skull and cerebrospinal fluid (i.e., their normal in vivo magnetic environment), air bubbles and air–tissue interfaces typically cause magnetic susceptibility artifacts that severely degrade the quality of ex vivo MRI data. In this report, we describe a relatively simple and cost-effective experimental setup for acquiring artifact-free ex vivo brain images using a clinical MRI system with standard hardware. In particular, we outline the necessary steps, from collecting an ex vivo human brain to the MRI scanner setup, and have also described changing the formalin (as might be necessary in longitudinal postmortem studies). Finally, we share some representative ex vivo MRI images that have been acquired using the proposed setup in order to demonstrate the efficacy of this approach. We hope that this protocol will provide both clinicians and researchers with a straight-forward and cost-effective solution for acquiring ex vivo MRI data from whole postmortem human brains. PMID:27965620

Non-invasive measurement of brain glycogen by NMR spectroscopy and its application to the study of brain metabolism

PubMed Central

Tesfaye, Nolawit; Seaquist, Elizabeth R.; Öz, Gülin

2011-01-01

Glycogen is the reservoir for glucose in the brain. Beyond the general agreement that glycogen serves as an energy source in the central nervous system, its exact role in brain energy metabolism has yet to be elucidated. Experiments performed in cell and tissue culture and animals have shown that glycogen content is affected by several factors including glucose, insulin, neurotransmitters, and neuronal activation. The study of in vivo glycogen metabolism has been hindered by the inability to measure glycogen non-invasively, but in the past several years, the development of a non-invasive localized 13C nuclear magnetic resonance (NMR) spectroscopy method has enabled the study of glycogen metabolism in the conscious human. With this technique, 13C-glucose is administered intravenously and its incorporation into and wash-out from brain glycogen is tracked. One application of this method has been to the study of brain glycogen metabolism in humans during hypoglycemia: data have shown that mobilization of brain glycogen is augmented during hypoglycemia and, after a single episode of hypoglycemia, glycogen synthesis rate is increased, suggesting that glycogen stores rebound to levels greater than baseline. Such studies suggest glycogen may serve as a potential energy reservoir in hypoglycemia and may participate in the brain's adaptation to recurrent hypoglycemia and eventual development of hypoglycemia unawareness. Beyond this focused area of study, 13C NMR spectroscopy has a broad potential for application in the study of brain glycogen metabolism and carries the promise of a better understanding of the role of brain glycogen in diabetes and other conditions. PMID:21732401

Neuroimaging Research: from Null-Hypothesis Falsification to Out-Of-Sample Generalization

ERIC Educational Resources Information Center

Bzdok, Danilo; Varoquaux, Gaël; Thirion, Bertrand

2017-01-01

Brain-imaging technology has boosted the quantification of neurobiological phenomena underlying human mental operations and their disturbances. Since its inception, drawing inference on neurophysiological effects hinged on classical statistical methods, especially, the general linear model. The tens of thousands of variables per brain scan were…

Variability in Cortical Representations of Speech Sound Perception

ERIC Educational Resources Information Center

Boatman, Dana F.

2007-01-01

Recent brain mapping studies have provided new insights into the cortical systems that mediate human speech perception. Electrocortical stimulation mapping (ESM) is a brain mapping method that is used clinically to localize cortical functions in neurosurgical patients. Recent ESM studies have yielded new insights into the cortical systems that…

Preparation of Acute Brain Slices Using an Optimized N-Methyl-D-glucamine Protective Recovery Method.

PubMed

Ting, Jonathan T; Lee, Brian R; Chong, Peter; Soler-Llavina, Gilberto; Cobbs, Charles; Koch, Christof; Zeng, Hongkui; Lein, Ed

2018-02-26

This protocol is a practical guide to the N-methyl-D-glucamine (NMDG) protective recovery method of brain slice preparation. Numerous recent studies have validated the utility of this method for enhancing neuronal preservation and overall brain slice viability. The implementation of this technique by early adopters has facilitated detailed investigations into brain function using diverse experimental applications and spanning a wide range of animal ages, brain regions, and cell types. Steps are outlined for carrying out the protective recovery brain slice technique using an optimized NMDG artificial cerebrospinal fluid (aCSF) media formulation and enhanced procedure to reliably obtain healthy brain slices for patch clamp electrophysiology. With this updated approach, a substantial improvement is observed in the speed and reliability of gigaohm seal formation during targeted patch clamp recording experiments while maintaining excellent neuronal preservation, thereby facilitating challenging experimental applications. Representative results are provided from multi-neuron patch clamp recording experiments to assay synaptic connectivity in neocortical brain slices prepared from young adult transgenic mice and mature adult human neurosurgical specimens. Furthermore, the optimized NMDG protective recovery method of brain slicing is compatible with both juvenile and adult animals, thus resolving a limitation of the original methodology. In summary, a single media formulation and brain slicing procedure can be implemented across various species and ages to achieve excellent viability and tissue preservation.

Preparation of Acute Brain Slices Using an Optimized N-Methyl-D-glucamine Protective Recovery Method

PubMed Central

Chong, Peter; Soler-Llavina, Gilberto; Cobbs, Charles; Koch, Christof; Zeng, Hongkui; Lein, Ed

2018-01-01

This protocol is a practical guide to the N-methyl-D-glucamine (NMDG) protective recovery method of brain slice preparation. Numerous recent studies have validated the utility of this method for enhancing neuronal preservation and overall brain slice viability. The implementation of this technique by early adopters has facilitated detailed investigations into brain function using diverse experimental applications and spanning a wide range of animal ages, brain regions, and cell types. Steps are outlined for carrying out the protective recovery brain slice technique using an optimized NMDG artificial cerebrospinal fluid (aCSF) media formulation and enhanced procedure to reliably obtain healthy brain slices for patch clamp electrophysiology. With this updated approach, a substantial improvement is observed in the speed and reliability of gigaohm seal formation during targeted patch clamp recording experiments while maintaining excellent neuronal preservation, thereby facilitating challenging experimental applications. Representative results are provided from multi-neuron patch clamp recording experiments to assay synaptic connectivity in neocortical brain slices prepared from young adult transgenic mice and mature adult human neurosurgical specimens. Furthermore, the optimized NMDG protective recovery method of brain slicing is compatible with both juvenile and adult animals, thus resolving a limitation of the original methodology. In summary, a single media formulation and brain slicing procedure can be implemented across various species and ages to achieve excellent viability and tissue preservation. PMID:29553547

DCS-SVM: a novel semi-automated method for human brain MR image segmentation.

PubMed

Ahmadvand, Ali; Daliri, Mohammad Reza; Hajiali, Mohammadtaghi

2017-11-27

In this paper, a novel method is proposed which appropriately segments magnetic resonance (MR) brain images into three main tissues. This paper proposes an extension of our previous work in which we suggested a combination of multiple classifiers (CMC)-based methods named dynamic classifier selection-dynamic local training local Tanimoto index (DCS-DLTLTI) for MR brain image segmentation into three main cerebral tissues. This idea is used here and a novel method is developed that tries to use more complex and accurate classifiers like support vector machine (SVM) in the ensemble. This work is challenging because the CMC-based methods are time consuming, especially on huge datasets like three-dimensional (3D) brain MR images. Moreover, SVM is a powerful method that is used for modeling datasets with complex feature space, but it also has huge computational cost for big datasets, especially those with strong interclass variability problems and with more than two classes such as 3D brain images; therefore, we cannot use SVM in DCS-DLTLTI. Therefore, we propose a novel approach named "DCS-SVM" to use SVM in DCS-DLTLTI to improve the accuracy of segmentation results. The proposed method is applied on well-known datasets of the Internet Brain Segmentation Repository (IBSR) and promising results are obtained.

Principal component analysis of the cytokine and chemokine response to human traumatic brain injury.

PubMed

Helmy, Adel; Antoniades, Chrystalina A; Guilfoyle, Mathew R; Carpenter, Keri L H; Hutchinson, Peter J

2012-01-01

There is a growing realisation that neuro-inflammation plays a fundamental role in the pathology of Traumatic Brain Injury (TBI). This has led to the search for biomarkers that reflect these underlying inflammatory processes using techniques such as cerebral microdialysis. The interpretation of such biomarker data has been limited by the statistical methods used. When analysing data of this sort the multiple putative interactions between mediators need to be considered as well as the timing of production and high degree of statistical co-variance in levels of these mediators. Here we present a cytokine and chemokine dataset from human brain following human traumatic brain injury and use principal component analysis and partial least squares discriminant analysis to demonstrate the pattern of production following TBI, distinct phases of the humoral inflammatory response and the differing patterns of response in brain and in peripheral blood. This technique has the added advantage of making no assumptions about the Relative Recovery (RR) of microdialysis derived parameters. Taken together these techniques can be used in complex microdialysis datasets to summarise the data succinctly and generate hypotheses for future study.

Prediction of brain tissue temperature using near-infrared spectroscopy.

PubMed

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-04-01

Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of [Formula: see text] (animal dataset) and [Formula: see text] (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications.

Early brain development toward shaping of human mind: an integrative psychoneurodevelopmental model in prenatal and perinatal medicine.

PubMed

Hruby, Radovan; Maas, Lili M; Fedor-Freybergh, P G

2013-01-01

The article introduces an integrative psychoneurodevelopmental model of complex human brain and mind development based on the latest findings in prenatal and perinatal medicine in terms of integrative neuroscience. The human brain development is extraordinarily complex set of events and could be influenced by a lot of factors. It is supported by new insights into the early neuro-ontogenic processes with the help of structural 3D magnetic resonance imaging or diffusion tensor imaging of fetal human brain. Various factors and targets for neural development including birth weight variability, fetal and early-life programming, fetal neurobehavioral states and fetal behavioral responses to various stimuli and others are discussed. Molecular biology reveals increasing sets of genes families as well as transcription and neurotropic factors together with critical epigenetic mechanisms to be deeply employed in the crucial neurodevelopmental events. Another field of critical importance is psychoimmuno-neuroendocrinology. Various effects of glucocorticoids as well as other hormones, prenatal stress and fetal HPA axis modulation are thought to be of special importance for brain development. The early postnatal period is characterized by the next intense shaping of complex competences, induced mainly by the very unique mother - newborn´s interactions and bonding. All these mechanisms serve to shape individual human mind with complex abilities and neurobehavioral strategies. Continuous research elucidating these special competences of human fetus and newborn/child supports integrative neuroscientific approach to involve various scientific disciplines for the next progress in human brain and mind research, and opens new scientific challenges and philosophic attitudes. New findings and approaches in this field could establish new methods in science, in primary prevention and treatment strategies, and markedly contribute to the development of modern integrative and personalized medicine.

Towards Ultra-High Resolution Fibre Tract Mapping of the Human Brain – Registration of Polarised Light Images and Reorientation of Fibre Vectors

PubMed Central

Palm, Christoph; Axer, Markus; Gräßel, David; Dammers, Jürgen; Lindemeyer, Johannes; Zilles, Karl; Pietrzyk, Uwe; Amunts, Katrin

2009-01-01

Polarised light imaging (PLI) utilises the birefringence of the myelin sheaths in order to visualise the orientation of nerve fibres in microtome sections of adult human post-mortem brains at ultra-high spatial resolution. The preparation of post-mortem brains for PLI involves fixation, freezing and cutting into 100-μm-thick sections. Hence, geometrical distortions of histological sections are inevitable and have to be removed for 3D reconstruction and subsequent fibre tracking. We here present a processing pipeline for 3D reconstruction of these sections using PLI derived multimodal images of post-mortem brains. Blockface images of the brains were obtained during cutting; they serve as reference data for alignment and elimination of distortion artefacts. In addition to the spatial image transformation, fibre orientation vectors were reoriented using the transformation fields, which consider both affine and subsequent non-linear registration. The application of this registration and reorientation approach results in a smooth fibre vector field, which reflects brain morphology. PLI combined with 3D reconstruction and fibre tracking is a powerful tool for human brain mapping. It can also serve as an independent method for evaluating in vivo fibre tractography. PMID:20461231

Impact of correction factors in human brain lesion-behavior inference.

PubMed

Sperber, Christoph; Karnath, Hans-Otto

2017-03-01

Statistical voxel-based lesion-behavior mapping (VLBM) in neurological patients with brain lesions is frequently used to examine the relationship between structure and function of the healthy human brain. Only recently, two simulation studies noted reduced anatomical validity of this method, observing the results of VLBM to be systematically misplaced by about 16 mm. However, both simulation studies differed from VLBM analyses of real data in that they lacked the proper use of two correction factors: lesion size and "sufficient lesion affection." In simulation experiments on a sample of 274 real stroke patients, we found that the use of these two correction factors reduced misplacement markedly compared to uncorrected VLBM. Apparently, the misplacement is due to physiological effects of brain lesion anatomy. Voxel-wise topographies of collateral damage in the real data were generated and used to compute a metric for the inter-voxel relation of brain damage. "Anatomical bias" vectors that were solely calculated from these inter-voxel relations in the patients' real anatomical data, successfully predicted the VLBM misplacement. The latter has the potential to help in the development of new VLBM methods that provide even higher anatomical validity than currently available by the proper use of correction factors. Hum Brain Mapp 38:1692-1701, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

Brain Dynamics: Methodological Issues and Applications in Psychiatric and Neurologic Diseases

NASA Astrophysics Data System (ADS)

Pezard, Laurent

The human brain is a complex dynamical system generating the EEG signal. Numerical methods developed to study complex physical dynamics have been used to characterize EEG since the mid-eighties. This endeavor raised several issues related to the specificity of EEG. Firstly, theoretical and methodological studies should address the major differences between the dynamics of the human brain and physical systems. Secondly, this approach of EEG signal should prove to be relevant for dealing with physiological or clinical problems. A set of studies performed in our group is presented here within the context of these two problematic aspects. After the discussion of methodological drawbacks, we review numerical simulations related to the high dimension and spatial extension of brain dynamics. Experimental studies in neurologic and psychiatric disease are then presented. We conclude that if it is now clear that brain dynamics changes in relation with clinical situations, methodological problems remain largely unsolved.

High-throughput 3D whole-brain quantitative histopathology in rodents

PubMed Central

Vandenberghe, Michel E.; Hérard, Anne-Sophie; Souedet, Nicolas; Sadouni, Elmahdi; Santin, Mathieu D.; Briet, Dominique; Carré, Denis; Schulz, Jocelyne; Hantraye, Philippe; Chabrier, Pierre-Etienne; Rooney, Thomas; Debeir, Thomas; Blanchard, Véronique; Pradier, Laurent; Dhenain, Marc; Delzescaux, Thierry

2016-01-01

Histology is the gold standard to unveil microscopic brain structures and pathological alterations in humans and animal models of disease. However, due to tedious manual interventions, quantification of histopathological markers is classically performed on a few tissue sections, thus restricting measurements to limited portions of the brain. Recently developed 3D microscopic imaging techniques have allowed in-depth study of neuroanatomy. However, quantitative methods are still lacking for whole-brain analysis of cellular and pathological markers. Here, we propose a ready-to-use, automated, and scalable method to thoroughly quantify histopathological markers in 3D in rodent whole brains. It relies on block-face photography, serial histology and 3D-HAPi (Three Dimensional Histology Analysis Pipeline), an open source image analysis software. We illustrate our method in studies involving mouse models of Alzheimer’s disease and show that it can be broadly applied to characterize animal models of brain diseases, to evaluate therapeutic interventions, to anatomically correlate cellular and pathological markers throughout the entire brain and to validate in vivo imaging techniques. PMID:26876372

Assessing Brain–Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

PubMed Central

Gennaro, Federico; de Bruin, Eling D.

2018-01-01

Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG) is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains’ role while moving and was tagged mobile brain/body imaging (MoBI). This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g., muscle activity and kinematics), through wireless recording wearable devices/sensors. Notably, several MoBI studies using EEG–EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, MoBI and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint toward promising opportunities; however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability, and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the MoBI framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g., age-related sarcopenia) remains to be determined. PMID:29535995

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.

A robust, efficient and flexible method for staining myelinated axons in blocks of brain tissue.

PubMed

Wahlsten, Douglas; Colbourne, Frederick; Pleus, Richard

2003-03-15

Previous studies have demonstrated the utility of the gold chloride method for en bloc staining of a bisected brain in mice and rats. The present study explores several variations in the method, assesses its reliability, and extends the limits of its application. We conclude that the method is very efficient, highly robust, sufficiently accurate for most purposes, and adaptable to many morphometric measures. We obtained acceptable staining of commissures in every brain, despite a wide variety of fixation methods. One-half could be stained 24 h after the brain was extracted and the other half could be stained months later. When staining failed because of an exhausted solution, the brain could be stained successfully in fresh solution. Relatively small changes were found in the sizes of commissures several weeks after initial fixation or staining. A half brain stained to reveal the mid-sagittal section could then be sectioned coronally and stained again in either gold chloride for myelin or cresyl violet for Nissl substance. Uncertainty, arising from pixelation of digitized images was far less than errors arising from human judgments about the histological limits of major commissures. Useful data for morphometric analysis were obtained by scanning the surface of a gold chloride stained block of brain with an inexpensive flatbed scanner.

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.

Structure Shapes Dynamics and Directionality in Diverse Brain Networks: Mathematical Principles and Empirical Confirmation in Three Species

NASA Astrophysics Data System (ADS)

Moon, Joon-Young; Kim, Junhyeok; Ko, Tae-Wook; Kim, Minkyung; Iturria-Medina, Yasser; Choi, Jee-Hyun; Lee, Joseph; Mashour, George A.; Lee, Uncheol

2017-04-01

Identifying how spatially distributed information becomes integrated in the brain is essential to understanding higher cognitive functions. Previous computational and empirical studies suggest a significant influence of brain network structure on brain network function. However, there have been few analytical approaches to explain the role of network structure in shaping regional activities and directionality patterns. In this study, analytical methods are applied to a coupled oscillator model implemented in inhomogeneous networks. We first derive a mathematical principle that explains the emergence of directionality from the underlying brain network structure. We then apply the analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully predicting simulation and empirical electroencephalographic data. The results demonstrate that the global directionality patterns in resting state brain networks can be predicted solely by their unique network structures. This study forms a foundation for a more comprehensive understanding of how neural information is directed and integrated in complex brain networks.

Meta-analysis of associations between human brain volume and intelligence differences: How strong are they and what do they mean?

PubMed

Pietschnig, Jakob; Penke, Lars; Wicherts, Jelte M; Zeiler, Michael; Voracek, Martin

2015-10-01

Positive associations between human intelligence and brain size have been suspected for more than 150 years. Nowadays, modern non-invasive measures of in vivo brain volume (Magnetic Resonance Imaging) make it possible to reliably assess associations with IQ. By means of a systematic review of published studies and unpublished results obtained by personal communications with researchers, we identified 88 studies examining effect sizes of 148 healthy and clinical mixed-sex samples (>8000 individuals). Our results showed significant positive associations of brain volume and IQ (r=.24, R(2)=.06) that generalize over age (children vs. adults), IQ domain (full-scale, performance, and verbal IQ), and sex. Application of a number of methods for detection of publication bias indicates that strong and positive correlation coefficients have been reported frequently in the literature whilst small and non-significant associations appear to have been often omitted from reports. We show that the strength of the positive association of brain volume and IQ has been overestimated in the literature, but remains robust even when accounting for different types of dissemination bias, although reported effects have been declining over time. While it is tempting to interpret this association in the context of human cognitive evolution and species differences in brain size and cognitive ability, we show that it is not warranted to interpret brain size as an isomorphic proxy of human intelligence differences. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spread spectrum time-resolved diffuse optical measurement system for enhanced sensitivity in detecting human brain activity

NASA Astrophysics Data System (ADS)

Mehta, Kalpesh; Hasnain, Ali; Zhou, Xiaowei; Luo, Jianwen; Penney, Trevor B.; Chen, Nanguang

2017-04-01

Diffuse optical spectroscopy (DOS) and imaging methods have been widely applied to noninvasive detection of brain activity. We have designed and implemented a low cost, portable, real-time one-channel time-resolved DOS system for neuroscience studies. Phantom experiments were carried out to test the performance of the system. We further conducted preliminary human experiments and demonstrated that enhanced sensitivity in detecting neural activity in the cortex could be achieved by the use of late arriving photons.

Region-specific protein misfolding cyclic amplification reproduces brain tropism of prion strains.

PubMed

Privat, Nicolas; Levavasseur, Etienne; Yildirim, Serfildan; Hannaoui, Samia; Brandel, Jean-Philippe; Laplanche, Jean-Louis; Béringue, Vincent; Seilhean, Danielle; Haïk, Stéphane

2017-10-06

Human prion diseases such as Creutzfeldt-Jakob disease are transmissible brain proteinopathies, characterized by the accumulation of a misfolded isoform of the host cellular prion protein (PrP) in the brain. According to the prion model, prions are defined as proteinaceous infectious particles composed solely of this abnormal isoform of PrP (PrP Sc ). Even in the absence of genetic material, various prion strains can be propagated in experimental models. They can be distinguished by the pattern of disease they produce and especially by the localization of PrP Sc deposits within the brain and the spongiform lesions they induce. The mechanisms involved in this strain-specific targeting of distinct brain regions still are a fundamental, unresolved question in prion research. To address this question, we exploited a prion conversion in vitro assay, protein misfolding cyclic amplification (PMCA), by using experimental scrapie and human prion strains as seeds and specific brain regions from mice and humans as substrates. We show here that region-specific PMCA in part reproduces the specific brain targeting observed in experimental, acquired, and sporadic Creutzfeldt-Jakob diseases. Furthermore, we provide evidence that, in addition to cellular prion protein, other region- and species-specific molecular factors influence the strain-dependent prion conversion process. This important step toward understanding prion strain propagation in the human brain may impact research on the molecular factors involved in protein misfolding and the development of ultrasensitive methods for diagnosing prion disease. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Proton magnetic resonance spectroscopy imaging in the study of human brain cancer.

PubMed

Martínez-Bisbal, M C; Celda, B

2009-12-01

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging technique that provides metabolic information on brain tumor. This biochemical information can be processed and presented as density maps of several metabolites, among them N-acetylaspartate (marker of neuronal viability), choline (marker of membrane turnover), creatine (related to the energy state of the cells), myo-Inositol (exclusively found in astrocytes), lipids and lactate (observed in necrosis and other pathological processes) which mean relevant information in the context of brain tumors. Thus, this technique is a multiparametrical molecular imaging method that can complete the magnetic resonance imaging (MRI) study enabling the detection of biochemical patterns of different features and aspects of brain tumors. In this article, the role of MRSI as a molecular imaging technique to provide biochemical information on human brain tumors is reviewed. The most frequent questions and situations in the study of human brain tumors in clinical settings will be considered, as well as the distinction of neoplastic lesions from non neoplastic, the tumor type identification, the study of heterogeneity and infiltration of normal appearing white matter and the therapy following with detection of side effects. The great amount of data in MRSI acquisition compared to the single voxel techniques requires the use of automated methods of quantification, but the possibility to obtain self-reference in the non-affected areas allows different strategies for data handling and interpretation, as presented in the literature. The combination of MRSI with other physiological MRI techniques and positron emission tomography is also included in this review.

Gender Differences of Brain Glucose Metabolic Networks Revealed by FDG-PET: Evidence from a Large Cohort of 400 Young Adults

PubMed Central

Li, Kai; Zhu, Hong; Qi, Rongfeng; Zhang, Zhiqiang; Lu, Guangming

2013-01-01

Background Gender differences of the human brain are an important issue in neuroscience research. In recent years, an increasing amount of evidence has been gathered from noninvasive neuroimaging studies supporting a sexual dimorphism of the human brain. However, there is a lack of imaging studies on gender differences of brain metabolic networks based on a large population sample. Materials and Methods FDG PET data of 400 right-handed, healthy subjects, including 200 females (age: 25∼45 years, mean age±SD: 40.9±3.9 years) and 200 age-matched males were obtained and analyzed in the present study. We first investigated the regional differences of brain glucose metabolism between genders using a voxel-based two-sample t-test analysis. Subsequently, we investigated the gender differences of the metabolic networks. Sixteen metabolic covariance networks using seed-based correlation were analyzed. Seven regions showing significant regional metabolic differences between genders, and nine regions conventionally used in the resting-state network studies were selected as regions-of-interest. Permutation tests were used for comparing within- and between-network connectivity between genders. Results Compared with the males, females showed higher metabolism in the posterior part and lower metabolism in the anterior part of the brain. Moreover, there were widely distributed patterns of the metabolic networks in the human brain. In addition, significant gender differences within and between brain glucose metabolic networks were revealed in the present study. Conclusion This study provides solid data that reveal gender differences in regional brain glucose metabolism and brain glucose metabolic networks. These observations might contribute to the better understanding of the gender differences in human brain functions, and suggest that gender should be included as a covariate when designing experiments and explaining results of brain glucose metabolic networks in the control and experimental individuals or patients. PMID:24358312

3D spatially encoded and accelerated TE-averaged echo planar spectroscopic imaging in healthy human brain.

PubMed

Iqbal, Zohaib; Wilson, Neil E; Thomas, M Albert

2016-03-01

Several different pathologies, including many neurodegenerative disorders, affect the energy metabolism of the brain. Glutamate, a neurotransmitter in the brain, can be used as a biomarker to monitor these metabolic processes. One method that is capable of quantifying glutamate concentration reliably in several regions of the brain is TE-averaged (1) H spectroscopic imaging. However, this type of method requires the acquisition of multiple TE lines, resulting in long scan durations. The goal of this experiment was to use non-uniform sampling, compressed sensing reconstruction and an echo planar readout gradient to reduce the scan time by a factor of eight to acquire TE-averaged spectra in three spatial dimensions. Simulation of glutamate and glutamine showed that the 2.2-2.4 ppm spectral region contained 95% glutamate signal using the TE-averaged method. Peak integration of this spectral range and home-developed, prior-knowledge-based fitting were used for quantitation. Gray matter brain phantom measurements were acquired on a Siemens 3 T Trio scanner. Non-uniform sampling was applied retrospectively to these phantom measurements and quantitative results of glutamate with respect to creatine 3.0 (Glu/Cr) ratios showed a coefficient of variance of 16% for peak integration and 9% for peak fitting using eight-fold acceleration. In vivo scans of the human brain were acquired as well and five different brain regions were quantified using the prior-knowledge-based algorithm. Glu/Cr ratios from these regions agreed with previously reported results in the literature. The method described here, called accelerated TE-averaged echo planar spectroscopic imaging (TEA-EPSI), is a significant methodological advancement and may be a useful tool for categorizing glutamate changes in pathologies where affected brain regions are not known a priori. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Frozen tissue preparation for high-resolution multiplex histological analyses of human brain specimens.

PubMed

Shao, Fangjie; Jiang, Wenhong; Gao, Qingqing; Li, Baizhou; Sun, Chongran; Wang, Qiyuan; Chen, Qin; Sun, Bing; Shen, Hong; Zhu, Keqing; Zhang, Jianmin; Liu, Chong

2017-10-01

The availability of a comprehensive tissue library is essential for elucidating the function and pathology of human brains. Considering the irreplaceable status of the formalin-fixation-paraffin-embedding (FFPE) preparation in routine pathology and the advantage of ultra-low temperature to preserve nucleic acids and proteins for multi-omics studies, these methods have become major modalities for the construction of brain tissue libraries. Nevertheless, the use of FFPE and snap-frozen samples is limited in high-resolution histological analyses because the preparation destroys tissue integrity and/or many important cellular markers. To overcome these limitations, we detailed a protocol to prepare and analyze frozen human brain samples that is particularly suitable for high-resolution multiplex immunohistological studies. As an alternative, we offered an optimized procedure to rescue snap-frozen tissues for the same purpose. Importantly, we provided a guideline to construct libraries of frozen tissue with minimal effort, cost and space. Taking advantage of this new tissue preparation modality to nicely preserve the cellular information that was otherwise damaged using conventional methods and to effectively remove tissue autofluorescence, we described the high-resolution landscape of the cellular composition in both lower-grade gliomas and glioblastoma multiforme samples. Our work showcases the great value of fixed frozen tissue in understanding the cellular mechanisms of CNS functions and abnormalities.

Non-invasive Brain Stimulation: A Paradigm Shift in Understanding Brain Oscillations.

PubMed

Vosskuhl, Johannes; Strüber, Daniel; Herrmann, Christoph S

2018-01-01

Cognitive neuroscience set out to understand the neural mechanisms underlying cognition. One central question is how oscillatory brain activity relates to cognitive processes. Up to now, most of the evidence supporting this relationship was correlative in nature. This situation changed dramatically with the recent development of non-invasive brain stimulation (NIBS) techniques, which open up new vistas for neuroscience by allowing researchers for the first time to validate their correlational theories by manipulating brain functioning directly. In this review, we focus on transcranial alternating current stimulation (tACS), an electrical brain stimulation method that applies sinusoidal currents to the intact scalp of human individuals to directly interfere with ongoing brain oscillations. We outline how tACS can impact human brain oscillations by employing different levels of observation from non-invasive tACS application in healthy volunteers and intracranial recordings in patients to animal studies demonstrating the effectiveness of alternating electric fields on neurons in vitro and in vivo . These findings likely translate to humans as comparable effects can be observed in human and animal studies. Neural entrainment and plasticity are suggested to mediate the behavioral effects of tACS. Furthermore, we focus on mechanistic theories about the relationship between certain cognitive functions and specific parameters of brain oscillaitons such as its amplitude, frequency, phase and phase coherence. For each of these parameters we present the current state of testing its functional relevance by means of tACS. Recent developments in the field of tACS are outlined which include the stimulation with physiologically inspired non-sinusoidal waveforms, stimulation protocols which allow for the observation of online-effects, and closed loop applications of tACS.

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.

The temporal change in the cortical activations due to salty and sweet tastes in humans: fMRI and time-intensity sensory evaluation.

PubMed

Nakamura, Yuko; Goto, Tazuko K; Tokumori, Kenji; Yoshiura, Takashi; Kobayashi, Koji; Nakamura, Yasuhiko; Honda, Hiroshi; Ninomiya, Yuzo; Yoshiura, Kazunori

2012-04-18

It remains unclear how the cerebral cortex of humans perceives taste temporally, and whether or not such objective data about the brain show a correlation with the current widely used conventional methods of taste-intensity sensory evaluation. The aim of this study was to investigate the difference in the time-intensity profile between salty and sweet tastes in the human brain. The time-intensity profiles of functional MRI (fMRI) data of the human taste cortex were analyzed using finite impulse response analysis for a direct interpretation in terms of the peristimulus time signal. Also, time-intensity sensory evaluations for tastes were performed under the same condition as fMRI to confirm the reliability of the temporal profile in the fMRI data. The time-intensity profile for the brain activations due to a salty taste changed more rapidly than those due to a sweet taste in the human brain cortex and was also similar to the time-intensity sensory evaluation, confirming the reliability of the temporal profile of the fMRI data. In conclusion, the time-intensity profile using finite impulse response analysis for fMRI data showed that there was a temporal difference in the neural responses between salty and sweet tastes over a given period of time. This indicates that there might be taste-specific temporal profiles of activations in the human brain.

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).

Correcting for Strong Eddy Current Induced B0 Modulation Enables Two-Spoke RF Pulse Design with Parallel Transmission: Demonstration at 9.4T in the Human Brain

PubMed Central

Wu, Xiaoping; Adriany, Gregor; Ugurbil, Kamil; Van de Moortele, Pierre-Francois

2013-01-01

Successful implementation of homogeneous slice-selective RF excitation in the human brain at 9.4T using 16-channel parallel transmission (pTX) is demonstrated. A novel three-step pulse design method incorporating fast real-time measurement of eddy current induced B0 variations as well as correction of resulting phase errors during excitation is described. To demonstrate the utility of the proposed method, phantom and in-vivo experiments targeting a uniform excitation in an axial slice were conducted using two-spoke pTX pulses. Even with the pre-emphasis activated, eddy current induced B0 variations with peak-to-peak values greater than 4 kHz were observed on our system during the rapid switches of slice selective gradients. This large B0 variation, when not corrected, resulted in drastically degraded excitation fidelity with the coefficient of variation (CV) of the flip angle calculated for the region of interest being large (∼12% in the phantom and ∼35% in the brain). By comparison, excitation fidelity was effectively restored, and satisfactory flip angle uniformity was achieved when using the proposed method, with the CV value reduced to ∼3% in the phantom and ∼8% in the brain. Additionally, experimental results were in good agreement with the numerical predictions obtained from Bloch simulations. Slice-selective flip angle homogenization in the human brain at 9.4T using 16-channel 3D spoke pTX pulses is achievable despite of large eddy current induced excitation phase errors; correcting for the latter was critical in this success. PMID:24205098

Clinical Phase IIB Trial of Oxycyte Perflurocarbon in Severe Human Traumatic Brain Injury

DTIC Science & Technology

2013-10-01

TERMS Penetrating ballistic brain injury, ischemia, hypoxia, perfluorocarbon , cell death, perfusion. 16. SECURITY CLASSIFICATION OF: 17. LIMITATION...SUBTITLE The Role of Perfluorocarbons in Mitigating Traumatic Brain Injury 5a. CONTRACT NUMBER W81XWH-08-1-0419 5b. GRANT NUMBER 5c. PROGRAM...damage seems to be mediated by mechanisms that follow the initial injury (secondary mechanisms). Perfluorocarbons (PFCs) are one of the methods by which

Automated data processing of { 1H-decoupled} 13C MR spectra acquired from human brain in vivo

NASA Astrophysics Data System (ADS)

Shic, Frederick; Ross, Brian

2003-06-01

In clinical 13C infusion studies, broadband excitation of 200 ppm of the human brain yields 13C MR spectra with a time resolution of 2-5 min and generates up to 2000 metabolite peaks over 2 h. We describe a fast, automated, observer-independent technique for processing { 1H-decoupled} 13C spectra. Quantified 13C spectroscopic signals, before and after the administration of [1- 13C]glucose and/or [1- 13C]acetate in human subjects are determined. Stepwise improvements of data processing are illustrated by examples of normal and pathological results. Variation in analysis of individual 13C resonances ranged between 2 and 14%. Using this method it is possible to reliably identify subtle metabolic effects of brain disease including Alzheimer's disease and epilepsy.

The role of sleep in human declarative memory consolidation.

PubMed

Alger, Sara E; Chambers, Alexis M; Cunningham, Tony; Payne, Jessica D

2015-01-01

Through a variety of methods, researchers have begun unraveling the mystery of why humans spend one-third of their lives asleep. Though sleep likely serves multiple functions, it has become clear that the sleeping brain offers an ideal environment for solidifying newly learned information in the brain. Sleep , which comprises a complex collection of brain states, supports the consolidation of many different types of information. It not only promotes learning and memory stabilization, but also memory reorganization that can lead to various forms of insightful behavior. As this chapter will describe, research provides ample support for these crucial cognitive functions of sleep . Focusing on the declarative memory system in humans, we review the literature regarding the benefits of sleep for both neutral and emotionally salient declarative memory. Finally, we discuss the literature regarding the impact of sleep on emotion regulation.

[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.

EEG slow waves in traumatic brain injury: Convergent findings in mouse and man.

PubMed

Modarres, Mo; Kuzma, Nicholas N; Kretzmer, Tracy; Pack, Allan I; Lim, Miranda M

2016-07-01

Evidence from previous studies suggests that greater sleep pressure, in the form of EEG-based slow waves, accumulates in specific brain regions that are more active during prior waking experience. We sought to quantify the number and coherence of EEG slow waves in subjects with mild traumatic brain injury (mTBI). We developed a method to automatically detect individual slow waves in each EEG channel, and validated this method using simulated EEG data. We then used this method to quantify EEG-based slow waves during sleep and wake states in both mouse and human subjects with mTBI. A modified coherence index that accounts for information from multiple channels was calculated as a measure of slow wave synchrony. Brain-injured mice showed significantly higher theta:alpha amplitude ratios and significantly more slow waves during spontaneous wakefulness and during prolonged sleep deprivation, compared to sham-injured control mice. Human subjects with mTBI showed significantly higher theta:beta amplitude ratios and significantly more EEG slow waves while awake compared to age-matched control subjects. We then quantified the global coherence index of slow waves across several EEG channels in human subjects. Individuals with mTBI showed significantly less EEG global coherence compared to control subjects while awake, but not during sleep. EEG global coherence was significantly correlated with severity of post-concussive symptoms (as assessed by the Neurobehavioral Symptom Inventory scale). Taken together, our data from both mouse and human studies suggest that EEG slow wave quantity and the global coherence index of slow waves may represent a sensitive marker for the diagnosis and prognosis of mTBI and post-concussive symptoms.

iELVis: An open source MATLAB toolbox for localizing and visualizing human intracranial electrode data.

PubMed

Groppe, David M; Bickel, Stephan; Dykstra, Andrew R; Wang, Xiuyuan; Mégevand, Pierre; Mercier, Manuel R; Lado, Fred A; Mehta, Ashesh D; Honey, Christopher J

2017-04-01

Intracranial electrical recordings (iEEG) and brain stimulation (iEBS) are invaluable human neuroscience methodologies. However, the value of such data is often unrealized as many laboratories lack tools for localizing electrodes relative to anatomy. To remedy this, we have developed a MATLAB toolbox for intracranial electrode localization and visualization, iELVis. NEW METHOD: iELVis uses existing tools (BioImage Suite, FSL, and FreeSurfer) for preimplant magnetic resonance imaging (MRI) segmentation, neuroimaging coregistration, and manual identification of electrodes in postimplant neuroimaging. Subsequently, iELVis implements methods for correcting electrode locations for postimplant brain shift with millimeter-scale accuracy and provides interactive visualization on 3D surfaces or in 2D slices with optional functional neuroimaging overlays. iELVis also localizes electrodes relative to FreeSurfer-based atlases and can combine data across subjects via the FreeSurfer average brain. It takes 30-60min of user time and 12-24h of computer time to localize and visualize electrodes from one brain. We demonstrate iELVis's functionality by showing that three methods for mapping primary hand somatosensory cortex (iEEG, iEBS, and functional MRI) provide highly concordant results. COMPARISON WITH EXISTING METHODS: iELVis is the first public software for electrode localization that corrects for brain shift, maps electrodes to an average brain, and supports neuroimaging overlays. Moreover, its interactive visualizations are powerful and its tutorial material is extensive. iELVis promises to speed the progress and enhance the robustness of intracranial electrode research. The software and extensive tutorial materials are freely available as part of the EpiSurg software project: https://github.com/episurg/episurg. Copyright © 2017 Elsevier B.V. All rights reserved.

Methods of measuring metabolism during surgery in humans: focus on the liver-brain relationship.

PubMed

Battezzati, Alberto; Bertoli, Simona

2004-09-01

The purpose of this work is to review recent advances in setting methods and models for measuring metabolism during surgery in humans. Surgery, especially solid organ transplantation, may offer unique experimental models in which it is ethically acceptable to gain information on difficult problems of amino acid and protein metabolism. Two areas are reviewed: the metabolic study of the anhepatic phase during liver transplantation and brain microdialysis during cerebral surgery. The first model offers an innovative approach to understand the relative role of liver and extrahepatic organs in gluconeogenesis, and to evaluate whether other organs can perform functions believed to be exclusively or almost exclusively performed by the liver. The second model offers an insight to intracerebral metabolism that is closely bound to that of the liver. The recent advances in metabolic research during surgery provide knowledge immediately useful for perioperative patient management and for a better control of surgical stress. The studies during the anhepatic phase of liver transplantation have showed that gluconeogenesis and glutamine metabolism are very active processes outside the liver. One of the critical organs for extrahepatic glutamine metabolism is the brain. Microdialysis studies helped to prove that in humans there is an intense trafficking of glutamine, glutamate and alanine among neurons and astrocytes. This delicate network is influenced by systemic amino acid metabolism. The metabolic dialogue between the liver and the brain is beginning to be understood in this light in order to explain the metabolic events of brain damage during liver failure.

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.

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.

Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

PubMed

Cai, Congbo; Wang, Chao; Zeng, Yiqing; Cai, Shuhui; Liang, Dong; Wu, Yawen; Chen, Zhong; Ding, Xinghao; Zhong, Jianhui

2018-04-24

An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T 2 mapping from single-shot overlapping-echo detachment (OLED) planar imaging. The training dataset was obtained from simulations that were carried out on SPROM (Simulation with PRoduct Operator Matrix) software developed by our group. The relationship between the original OLED image containing two echo signals and the corresponding T 2 mapping was learned by ResNet training. After the ResNet was trained, it was applied to reconstruct the T 2 mapping from simulation and in vivo human brain data. Although the ResNet was trained entirely on simulated data, the trained network was generalized well to real human brain data. The results from simulation and in vivo human brain experiments show that the proposed method significantly outperforms the echo-detachment-based method. Reliable T 2 mapping with higher accuracy is achieved within 30 ms after the network has been trained, while the echo-detachment-based OLED reconstruction method took approximately 2 min. The proposed method will facilitate real-time dynamic and quantitative MR imaging via OLED sequence, and deep convolutional neural network has the potential to reconstruct maps from complex MRI sequences efficiently. © 2018 International Society for Magnetic Resonance in Medicine.

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

Postmortem changes in the neuroanatomical characteristics of the primate brain: the hippocampal formation

PubMed Central

Lavenex, Pierre; Lavenex, Pamela Banta; Bennett, Jeffrey L.; Amaral, David G.

2009-01-01

Comparative studies of the structural organization of the brain are fundamental to our understanding of human brain function. However, whereas brains of experimental animals are fixed by perfusion of a fixative through the vasculature, human or ape brains are fixed by immersion after varying postmortem intervals. Although differential treatments might affect the fundamental characteristics of the tissue, this question has not been evaluated empirically in primate brains. Monkey brains were either perfused, or acquired after varying postmortem intervals before immersion-fixation in 4% paraformaldehyde. We found that the fixation method affected the neuroanatomical characteristics of the monkey hippocampal formation. Soma size was smaller in Nissl-stained, immersion-fixed tissue, although overall brain volume was larger, as compared to perfusion-fixed tissue. Non-phosphorylated high-molecular-weight neurofilament immunoreactivity was lower in CA3 pyramidal neurons, dentate mossy cells and the entorhinal cortex, whereas it was higher in the mossy fiber pathway in immersion-fixed tissue. Serotonin-immunoreactive fibers were well-stained in perfused tissue but were undetectable in immersion-fixed tissue. Although regional immunoreactivity patterns for calcium-binding proteins were not affected, intracellular staining degraded with increasing postmortem intervals. Somatostatin-immunoreactive clusters of large axonal varicosities, previously reported only in humans, were observed in immersion-fixed monkey tissue. In addition, calretinin-immunoreactive multipolar neurons, previously observed only in rodents, were found in the rostral dentate gyrus in both perfused and immersion-fixed brains. In conclusion, comparative studies of the brain must evaluate the effects of fixation on the staining pattern of each marker in every structure of interest before drawing conclusions about species differences. PMID:18972553

Postmortem changes in the neuroanatomical characteristics of the primate brain: hippocampal formation.

PubMed

Lavenex, Pierre; Lavenex, Pamela Banta; Bennett, Jeffrey L; Amaral, David G

2009-01-01

Comparative studies of the structural organization of the brain are fundamental to our understanding of human brain function. However, whereas brains of experimental animals are fixed by perfusion of a fixative through the vasculature, human or ape brains are fixed by immersion after varying postmortem intervals. Although differential treatments might affect the fundamental characteristics of the tissue, this question has not been evaluated empirically in primate brains. Monkey brains were either perfused or acquired after varying postmortem intervals before immersion-fixation in 4% paraformaldehyde. We found that the fixation method affected the neuroanatomical characteristics of the monkey hippocampal formation. Soma size was smaller in Nissl-stained, immersion-fixed tissue, although overall brain volume was larger as compared to perfusion-fixed tissue. Nonphosphorylated high-molecular-weight neurofilament immunoreactivity was lower in CA3 pyramidal neurons, dentate mossy cells, and the entorhinal cortex, whereas it was higher in the mossy fiber pathway in immersion-fixed tissue. Serotonin-immunoreactive fibers were well stained in perfused tissue but were undetectable in immersion-fixed tissue. Although regional immunoreactivity patterns for calcium-binding proteins were not affected, intracellular staining degraded with increasing postmortem intervals. Somatostatin-immunoreactive clusters of large axonal varicosities, previously reported only in humans, were observed in immersion-fixed monkey tissue. In addition, calretinin-immunoreactive multipolar neurons, previously observed only in rodents, were found in the rostral dentate gyrus in both perfused and immersion-fixed brains. In conclusion, comparative studies of the brain must evaluate the effects of fixation on the staining pattern of each marker in every structure of interest before drawing conclusions about species differences.

Cumulative Brain Injury from Motor Vehicle-Induced Whole-Body Vibration and Prevention by Human Apolipoprotein A-I Molecule Mimetic (4F) Peptide (an Apo A-I Mimetic)

PubMed Central

Yan, Ji-Geng; Zhang, Lin-ling; Agresti, Michael; Yan, Yuhui; LoGiudice, John; Sanger, James R.; Matloub, Hani S.; Pritchard, Kirkwood A.; Jaradeh, Safwan S.; Havlik, Robert

2017-01-01

Background Insidious cumulative brain injury from motor vehicle-induced whole-body vibration (MV-WBV) has not yet been studied. The objective of the present study is to validate whether whole-body vibration for long periods causes cumulative brain injury and impairment of the cerebral function. We also explored a preventive method for MV-WBV injury. Methods A study simulating whole-body vibration was conducted in 72 male Sprague-Dawley rats divided into 9 groups (N = 8): (1) 2-week normal control; (2) 2-week sham control (in the tube without vibration); (3) 2-week vibration (exposed to whole-body vibration at 30 Hz and .5 G acceleration for 4 hours/day, 5 days/week for 2 weeks; vibration parameters in the present study are similar to the most common driving conditions); (4) 4-week sham control; (5) 4-week vibration; (6) 4-week vibration with human apolipoprotein A-I molecule mimetic (4F)-preconditioning; (7) 8-week sham control; (8) 8-week vibration; and (9) 8-week 4F-preconditioning group. All the rats were evaluated by behavioral, physiological, and histological studies of the brain. Results Brain injury from vibration is a cumulative process starting with cerebral vasoconstriction, squeezing of the endothelial cells, increased free radicals, decreased nitric oxide, insufficient blood supply to the brain, and repeated reperfusion injury to brain neurons. In the 8-week vibration group, which indicated chronic brain edema, shrunken neuron numbers increased and whole neurons atrophied, which strongly correlated with neural functional impairment. There was no prominent brain neuronal injury in the 4F groups. Conclusions The present study demonstrated cumulative brain injury from MV-WBV and validated the preventive effects of 4F preconditioning. PMID:26433438

Thioesters for the in vitro evaluation of agents to image brain cholinesterases.

PubMed

Macdonald, Ian R; Jollymore, Courtney T; Reid, G Andrew; Pottie, Ian R; Martin, Earl; Darvesh, Sultan

2013-06-01

Cholinesterases are associated with pathology characteristic of conditions such as Alzheimer's disease and are therefore, considered targets for neuroimaging. Ester derivatives of N-methylpiperidinol are promising potential imaging agents; however, methodology is lacking for evaluating these compounds in vitro. Here, we report the synthesis and evaluation of a series of N-methylpiperidinyl thioesters, possessing comparable properties to their corresponding esters, which can be directly evaluated for cholinesterase kinetics and histochemical distribution in human brain tissue. N-methylpiperidinyl esters and thioesters were synthesized and they demonstrated comparable cholinesterase kinetics. Furthermore, thioesters were capable, using histochemical method, to visualize cholinesterase activity in human brain tissue. N-methylpiperidinyl thioesters can be rapidly evaluated for cholinesterase kinetics and visualization of enzyme distribution in brain tissue which may facilitate development of cholinesterase imaging agents for application to conditions such as Alzheimer's disease.

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

A Simple Noise Correction Scheme for Diffusional Kurtosis Imaging

PubMed Central

Glenn, G. Russell; Tabesh, Ali; Jensen, Jens H.

2014-01-01

Purpose Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis. Methods Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates. Results As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR. Conclusion The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms. PMID:25172990

Mapping fetal brain development in utero using magnetic resonance imaging: the Big Bang of brain mapping.

PubMed

Studholme, Colin

2011-08-15

The development of tools to construct and investigate probabilistic maps of the adult human brain from magnetic resonance imaging (MRI) has led to advances in both basic neuroscience and clinical diagnosis. These tools are increasingly being applied to brain development in adolescence and childhood, and even to neonatal and premature neonatal imaging. Even earlier in development, parallel advances in clinical fetal MRI have led to its growing use as a tool in challenging medical conditions. This has motivated new engineering developments encompassing optimal fast MRI scans and techniques derived from computer vision, the combination of which allows full 3D imaging of the moving fetal brain in utero without sedation. These promise to provide a new and unprecedented window into early human brain growth. This article reviews the developments that have led us to this point, examines the current state of the art in the fields of fast fetal imaging and motion correction, and describes the tools to analyze dynamically changing fetal brain structure. New methods to deal with developmental tissue segmentation and the construction of spatiotemporal atlases are examined, together with techniques to map fetal brain growth patterns.

Improved volumetric measurement of brain structure with a distortion correction procedure using an ADNI phantom.

PubMed

Maikusa, Norihide; Yamashita, Fumio; Tanaka, Kenichiro; Abe, Osamu; Kawaguchi, Atsushi; Kabasawa, Hiroyuki; Chiba, Shoma; Kasahara, Akihiro; Kobayashi, Nobuhisa; Yuasa, Tetsuya; Sato, Noriko; Matsuda, Hiroshi; Iwatsubo, Takeshi

2013-06-01

Serial magnetic resonance imaging (MRI) images acquired from multisite and multivendor MRI scanners are widely used in measuring longitudinal structural changes in the brain. Precise and accurate measurements are important in understanding the natural progression of neurodegenerative disorders such as Alzheimer's disease. However, geometric distortions in MRI images decrease the accuracy and precision of volumetric or morphometric measurements. To solve this problem, the authors suggest a commercially available phantom-based distortion correction method that accommodates the variation in geometric distortion within MRI images obtained with multivendor MRI scanners. The authors' method is based on image warping using a polynomial function. The method detects fiducial points within a phantom image using phantom analysis software developed by the Mayo Clinic and calculates warping functions for distortion correction. To quantify the effectiveness of the authors' method, the authors corrected phantom images obtained from multivendor MRI scanners and calculated the root-mean-square (RMS) of fiducial errors and the circularity ratio as evaluation values. The authors also compared the performance of the authors' method with that of a distortion correction method based on a spherical harmonics description of the generic gradient design parameters. Moreover, the authors evaluated whether this correction improves the test-retest reproducibility of voxel-based morphometry in human studies. A Wilcoxon signed-rank test with uncorrected and corrected images was performed. The root-mean-square errors and circularity ratios for all slices significantly improved (p < 0.0001) after the authors' distortion correction. Additionally, the authors' method was significantly better than a distortion correction method based on a description of spherical harmonics in improving the distortion of root-mean-square errors (p < 0.001 and 0.0337, respectively). Moreover, the authors' method reduced the RMS error arising from gradient nonlinearity more than gradwarp methods. In human studies, the coefficient of variation of voxel-based morphometry analysis of the whole brain improved significantly from 3.46% to 2.70% after distortion correction of the whole gray matter using the authors' method (Wilcoxon signed-rank test, p < 0.05). The authors proposed a phantom-based distortion correction method to improve reproducibility in longitudinal structural brain analysis using multivendor MRI. The authors evaluated the authors' method for phantom images in terms of two geometrical values and for human images in terms of test-retest reproducibility. The results showed that distortion was corrected significantly using the authors' method. In human studies, the reproducibility of voxel-based morphometry analysis for the whole gray matter significantly improved after distortion correction using the authors' method.

Ex-vivo MR Volumetry of Human Brain Hemispheres

PubMed Central

Kotrotsou, Aikaterini; Bennett, David A.; Schneider, Julie A.; Dawe, Robert J.; Golak, Tom; Leurgans, Sue E.; Yu, Lei; Arfanakis, Konstantinos

2013-01-01

Purpose The aims of this work were to: a) develop an approach for ex-vivo MR volumetry of human brain hemispheres that does not contaminate the results of histopathological examination, b) longitudinally assess regional brain volumes postmortem, and c) investigate the relationship between MR volumetric measurements performed in-vivo and ex-vivo. Methods An approach for ex-vivo MR volumetry of human brain hemispheres was developed. Five hemispheres from elderly subjects were imaged ex-vivo longitudinally. All datasets were segmented. The longitudinal behavior of volumes measured ex-vivo was assessed. The relationship between in-vivo and ex-vivo volumetric measurements was investigated in seven elderly subjects imaged both ante-mortem and postmortem. Results The presented approach for ex-vivo MR volumetry did not contaminate the results of histopathological examination. For a period of 6 months postmortem, within-subject volume variation across time points was substantially smaller than inter-subject volume variation. A close linear correspondence was detected between in-vivo and ex-vivo volumetric measurements. Conclusion Regional brain volumes measured with the presented approach for ex-vivo MR volumetry remain relatively unchanged for a period of 6 months postmortem. Furthermore, the linear relationship between in-vivo and ex-vivo MR volumetric measurements suggests that the presented approach captures information linked to ante-mortem macrostructural brain characteristics. PMID:23440751

Synaptic inputs from stroke-injured brain to grafted human stem cell-derived neurons activated by sensory stimuli.

PubMed

Tornero, Daniel; Tsupykov, Oleg; Granmo, Marcus; Rodriguez, Cristina; Grønning-Hansen, Marita; Thelin, Jonas; Smozhanik, Ekaterina; Laterza, Cecilia; Wattananit, Somsak; Ge, Ruimin; Tatarishvili, Jemal; Grealish, Shane; Brüstle, Oliver; Skibo, Galina; Parmar, Malin; Schouenborg, Jens; Lindvall, Olle; Kokaia, Zaal

2017-03-01

Transplanted neurons derived from stem cells have been proposed to improve function in animal models of human disease by various mechanisms such as neuronal replacement. However, whether the grafted neurons receive functional synaptic inputs from the recipient's brain and integrate into host neural circuitry is unknown. Here we studied the synaptic inputs from the host brain to grafted cortical neurons derived from human induced pluripotent stem cells after transplantation into stroke-injured rat cerebral cortex. Using the rabies virus-based trans-synaptic tracing method and immunoelectron microscopy, we demonstrate that the grafted neurons receive direct synaptic inputs from neurons in different host brain areas located in a pattern similar to that of neurons projecting to the corresponding endogenous cortical neurons in the intact brain. Electrophysiological in vivo recordings from the cortical implants show that physiological sensory stimuli, i.e. cutaneous stimulation of nose and paw, can activate or inhibit spontaneous activity in grafted neurons, indicating that at least some of the afferent inputs are functional. In agreement, we find using patch-clamp recordings that a portion of grafted neurons respond to photostimulation of virally transfected, channelrhodopsin-2-expressing thalamo-cortical axons in acute brain slices. The present study demonstrates, for the first time, that the host brain regulates the activity of grafted neurons, providing strong evidence that transplanted human induced pluripotent stem cell-derived cortical neurons can become incorporated into injured cortical circuitry. Our findings support the idea that these neurons could contribute to functional recovery in stroke and other conditions causing neuronal loss in cerebral cortex. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Effect of filtration of signals of brain activity on quality of recognition of brain activity patterns using artificial intelligence methods

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Musatov, Vyachaslav Yu.

2018-02-01

In present work we studied features of the human brain states classification, corresponding to the real movements of hands and legs. For this purpose we used supervised learning algorithm based on feed-forward artificial neural networks (ANNs) with error back-propagation along with the support vector machine (SVM) method. We compared the quality of operator movements classification by means of EEG signals obtained experimentally in the absence of preliminary processing and after filtration in different ranges up to 25 Hz. It was shown that low-frequency filtering of multichannel EEG data significantly improved accuracy of operator movements classification.

Cerebral localization, then and now.

PubMed

Marshall, John C; Fink, Gereon R

2003-11-01

We review some of the progress made in understanding the nature of functional specialization in the human brain, beginning with the anatomical claim that all mental faculties have their own distinct material substrate in different regions of the brain and the psychological claim that each mental faculty is characterized by the content domain with which it deals. This conceptual framework led behavioral neurologists to show how discrete brain lesions provoked different types of language, praxic, gnostic, spatial, and memory disorders. The simplest way of interpreting these anatomoclinical associations was to conjecture that the normal function (now impaired by brain damage) was localized within that lesioned region. It was also realized that cognitive impairments could arise from lesions that spared the functional centers themselves but disconnected them from other centers. Nonetheless, many neuroscientists remained skeptical of the entire paradigm. Accordingly, in the late 19th century functional localization began to be studied in the intact human brain by such techniques as measuring the temperature of different brain regions when different cognitive tasks were performed. During the 20th century these crude techniques gave way to positron emission tomography, functional magnetic resonance imaging, and magnetoencephalography. The relatively precise spatial and temporal resolution of modern methods now raises a crucial question: Do the functional localizations obtained by the anatomoclinical method converge with those implied by the functional neuroimaging of cognition in healthy volunteers? We then conclude with some recent suggestions that functional specialization is not such a fixed property of brain regions as previously supposed.

Phase-difference and spectroscopic imaging for monitoring of human brain temperature during cooling.

PubMed

Weis, Jan; Covaciu, Lucian; Rubertsson, Sten; Allers, Mats; Lunderquist, Anders; Ortiz-Nieto, Francisco; Ahlström, Håkan

2012-12-01

Decrease of the human brain temperature was induced by intranasal cooling. The main purpose of this study was to compare the two magnetic resonance methods for monitoring brain temperature changes during cooling: phase-difference and magnetic resonance spectroscopic imaging (MRSI) with high spatial resolution. Ten healthy volunteers were measured. Selective brain cooling was performed through nasal cavities using saline-cooled balloon catheters. MRSI was based on a radiofrequency spoiled gradient echo sequence. The spectral information was encoded by incrementing the echo time of the subsequent eight image records. Reconstructed voxel size was 1×1×5 mm(3). Relative brain temperature was computed from the positions of water spectral lines. Phase maps were obtained from the first image record of the MRSI sequence. Mild hypothermia was achieved in 15-20 min. Mean brain temperature reduction varied in the interval <-3.0; -0.6>°C and <-2.7; -0.7>°C as measured by the MRSI and phase-difference methods, respectively. Very good correlation was found in all locations between the temperatures measured by both techniques except in the frontal lobe. Measurements in the transversal slices were more robust to the movement artifacts than those in the sagittal planes. Good agreement was found between the MRSI and phase-difference techniques. Copyright © 2012 Elsevier Inc. All rights reserved.

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

Ultrasound-mediated blood-brain barrier disruption for targeted drug delivery in the central nervous system

PubMed Central

Aryal, Muna; Arvanitis, Costas D.; Alexander, Phillip M.; McDannold, Nathan

2014-01-01

The physiology of the vasculature in the central nervous system (CNS), which includes the blood-brain barrier (BBB) and other factors, complicates the delivery of most drugs to the brain. Different methods have been used to bypass the BBB, but they have limitations such as being invasive, non-targeted or requiring the formulation of new drugs. Focused ultrasound (FUS), when combined with circulating microbubbles, is a noninvasive method to locally and transiently disrupt the BBB at discrete targets. This review provides insight on the current status of this unique drug delivery technique, experience in preclinical models, and potential for clinical translation. If translated to humans, this method would offer a flexible means to target therapeutics to desired points or volumes in the brain, and enable the whole arsenal of drugs in the CNS that are currently prevented by the BBB. PMID:24462453

Identification of Insulin Receptor Splice Variant B in Neurons by in situ Detection in Human Brain Samples.

PubMed

Spencer, Brian; Rank, Logan; Metcalf, Jeff; Desplats, Paula

2018-03-06

Insulin and its receptor are widely expressed in a variety of tissues throughout the body including liver, adipose tissue, liver and brain. The insulin receptor is expressed as two functionally distinct isoforms, differentiated by a single 12 amino acid exon. The two receptor isoforms, designated IR/A and IR/B, are expressed in a highly tissue and cell specific manner and relative proportions of the different isoforms vary during development, aging and disease states. The high degree of similarity between the two isoforms has prevented detailed studies as differentiation of the two isoforms by traditional immunological methods cannot be achieved. We describe here a new in situ RT-PCR/ FISH assay that allows for the visualization of IR/A and IR/B in tissue along with tissue specific markers. We used this new method to show for the first time that IR/A and IR/B are both expressed in neurons in the adult human brain. Thus, we present a method that enables the investigation of IR/A and IR/B insulin receptor isoform expression in situ in various tissues.

A comparative quantitative analysis of cytoarchitecture and minicolumnar organization in Broca's area in humans and great apes.

PubMed

Schenker, Natalie M; Buxhoeveden, Daniel P; Blackmon, William L; Amunts, Katrin; Zilles, Karl; Semendeferi, Katerina

2008-09-01

Broca's area was identified in the inferior frontal gyrus of chimpanzee, bonobo, gorilla, and orangutan brains through direct cytoarchitectonic comparison with human brains. Across species, Broca's area comprises Brodmann's areas 44 and 45. We found that these areas exhibited similar cytoarchitectonic characteristics in all species examined. We analyzed the minicolumnar organization of cells in layer III of Broca's area in 11 human and 9 great ape specimens. A semiautomated method was used to analyze digitized images of histological sections stained for Nissl substance. Horizontal spacing distance and gray level index (GLI; or the area fraction occupied by cells) were quantified in all images. In contrast to area Tpt, the only cortical area for which comparative minicolumnar data have been published previously for humans and one of the great apes, we found no population-level asymmetry, for either horizontal spacing distance or GLI. Only human females exhibited a leftward asymmetry in GLI. GLI was lower in humans than in great apes (P < 0.001), allowing more space for connectivity in layer III. In humans, horizontal spacing distance was greater than in great apes but smaller relative to brain size. (c) 2008 Wiley-Liss, Inc.

Is orbital volume associated with eyeball and visual cortex volume in humans?

PubMed Central

Pearce, Eiluned; Bridge, Holly

2013-01-01

Background In humans orbital volume increases linearly with absolute latitude. Scaling across mammals between visual system components suggests that these larger orbits should translate into larger eyes and visual cortices in high latitude humans. Larger eyes at high latitudes may be required to maintain adequate visual acuity and enhance visual sensitivity under lower light levels. Aim To test the assumption that orbital volume can accurately index eyeball and visual cortex volumes specifically in humans. Subjects & Methods Structural Magnetic Resonance Imaging (MRI) techniques are employed to measure eye and orbit (N=88), and brain and visual cortex (N=99) volumes in living humans. Facial dimensions and foramen magnum area (a proxy for body mass) were also measured. Results A significant positive linear relationship was found between (i) orbital and eyeball volumes, (ii) eyeball and visual cortex grey matter volumes, (iii) different visual cortical areas, independently of overall brain volume. Conclusion In humans the components of the visual system scale from orbit to eye to visual cortex volume independently of overall brain size. These findings indicate that orbit volume can index eye and visual cortex volume in humans, suggesting that larger high latitude orbits do translate into larger visual cortices. PMID:23879766

Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

PubMed

Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

2013-11-01

Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

Driving working memory with frequency-tuned noninvasive brain stimulation.

PubMed

Albouy, Philippe; Baillet, Sylvain; Zatorre, Robert J

2018-04-29

Frequency-tuned noninvasive brain stimulation is a recent approach in cognitive neuroscience that involves matching the frequency of transcranially applied electromagnetic fields to that of specific oscillatory components of the underlying neurophysiology. The objective of this method is to modulate ongoing/intrinsic brain oscillations, which correspond to rhythmic fluctuations of neural excitability, to causally change behavior. We review the impact of frequency-tuned noninvasive brain stimulation on the research field of human working memory. We argue that this is a powerful method to probe and understand the mechanisms of memory functions, targeting specifically task-related oscillatory dynamics, neuronal representations, and brain networks. We report the main behavioral and neurophysiological outcomes published to date, in particular, how functionally relevant oscillatory signatures in signal power and interregional connectivity yield causal changes of working memory abilities. We also present recent developments of the technique that aim to modulate cross-frequency coupling in polyrhythmic neural activity. Overall, the method has led to significant advances in our understanding of the mechanisms of systems neuroscience, and the role of brain oscillations in cognition and behavior. We also emphasize the translational impact of noninvasive brain stimulation techniques in the development of therapeutic approaches. © 2018 New York Academy of Sciences.

Prediction of brain tissue temperature using near-infrared spectroscopy

PubMed Central

Holper, Lisa; Mitra, Subhabrata; Bale, Gemma; Robertson, Nicola; Tachtsidis, Ilias

2017-01-01

Abstract. Broadband near-infrared spectroscopy (NIRS) can provide an endogenous indicator of tissue temperature based on the temperature dependence of the water absorption spectrum. We describe a first evaluation of the calibration and prediction of brain tissue temperature obtained during hypothermia in newborn piglets (animal dataset) and rewarming in newborn infants (human dataset) based on measured body (rectal) temperature. The calibration using partial least squares regression proved to be a reliable method to predict brain tissue temperature with respect to core body temperature in the wavelength interval of 720 to 880 nm with a strong mean predictive power of R2=0.713±0.157 (animal dataset) and R2=0.798±0.087 (human dataset). In addition, we applied regression receiver operating characteristic curves for the first time to evaluate the temperature prediction, which provided an overall mean error bias between NIRS predicted brain temperature and body temperature of 0.436±0.283°C (animal dataset) and 0.162±0.149°C (human dataset). We discuss main methodological aspects, particularly the well-known aspect of over- versus underestimation between brain and body temperature, which is relevant for potential clinical applications. PMID:28630878

Lifting the veil on the dynamics of neuronal activities evoked by transcranial magnetic stimulation

PubMed Central

Li, Bingshuo; Virtanen, Juha P; Oeltermann, Axel; Schwarz, Cornelius; Giese, Martin A; Ziemann, Ulf

2017-01-01

Transcranial magnetic stimulation (TMS) is a widely used non-invasive tool to study and modulate human brain functions. However, TMS-evoked activity of individual neurons has remained largely inaccessible due to the large TMS-induced electromagnetic fields. Here, we present a general method providing direct in vivo electrophysiological access to TMS-evoked neuronal activity 0.8–1 ms after TMS onset. We translated human single-pulse TMS to rodents and unveiled time-grained evoked activities of motor cortex layer V neurons that show high-frequency spiking within the first 6 ms depending on TMS-induced current orientation and a multiphasic spike-rhythm alternating between excitation and inhibition in the 6–300 ms epoch, all of which can be linked to various human TMS responses recorded at the level of spinal cord and muscles. The advance here facilitates a new level of insight into the TMS-brain interaction that is vital for developing this non-invasive tool to purposefully explore and effectively treat the human brain. PMID:29165241

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

Detecting activity-evoked pH changes in human brain

PubMed Central

Magnotta, Vincent A.; Heo, Hye-Young; Dlouhy, Brian J.; Dahdaleh, Nader S.; Follmer, Robin L.; Thedens, Daniel R.; Welsh, Michael J.; Wemmie, John A.

2012-01-01

Localized pH changes have been suggested to occur in the brain during normal function. However, the existence of such pH changes has also been questioned. Lack of methods for noninvasively measuring pH with high spatial and temporal resolution has limited insight into this issue. Here we report that a magnetic resonance imaging (MRI) strategy, T1 relaxation in the rotating frame (T1ρ), is sufficiently sensitive to detect widespread pH changes in the mouse and human brain evoked by systemically manipulating carbon dioxide or bicarbonate. Moreover, T1ρ detected a localized acidosis in the human visual cortex induced by a flashing checkerboard. Lactate measurements and pH-sensitive 31P spectroscopy at the same site also identified a localized acidosis. Consistent with the established role for pH in blood flow recruitment, T1ρ correlated with blood oxygenation level-dependent contrast commonly used in functional MRI. However, T1ρ was not directly sensitive to blood oxygen content. These observations indicate that localized pH fluctuations occur in the human brain during normal function. Furthermore, they suggest a unique functional imaging strategy based on pH that is independent of traditional functional MRI contrast mechanisms. PMID:22566645

The rebirth of neuroscience in psychosomatic medicine, Part I: historical context, methods, and relevant basic science.

PubMed

Lane, Richard D; Waldstein, Shari R; Chesney, Margaret A; Jennings, J Richard; Lovallo, William R; Kozel, Peter J; Rose, Robert M; Drossman, Douglas A; Schneiderman, Neil; Thayer, Julian F; Cameron, Oliver G

2009-02-01

Neuroscience was an integral part of psychosomatic medicine at its inception in the early 20th century. Since the mid-20th century, however, psychosomatic research has largely ignored the brain. The field of neuroscience has burgeoned in recent years largely because a variety of powerful new methods have become available. Many of these methods allow for the noninvasive study of the living human brain and thus are potentially available for integration into psychosomatic medicine research at this time. In this first paper we examine various methods available for human neuroscientific investigation and discuss their relative strengths and weaknesses. We next review some basic functional neuroanatomy involving structures that are increasingly being identified as relevant for psychosomatic processes. We then discuss, and provide examples of, how the brain influences end organs through "information transfer systems," including the autonomic, neuroendocrine, and immune systems. The evidence currently available suggests that neuroscience holds great promise for advancing the goal of understanding the mechanisms by which psychosocial variables influence physical disease outcomes. An increased focus on such mechanistic research in psychosomatic medicine is needed to further its acceptance into the field of medicine.

Using the Optical Fractionator to Estimate Total Cell Numbers in the Normal and Abnormal Developing Human Forebrain.

PubMed

Larsen, Karen B

2017-01-01

Human fetal brain development is a complex process which is vulnerable to disruption at many stages. Although histogenesis is well-documented, only a few studies have quantified cell numbers across normal human fetal brain growth. Due to the present lack of normative data it is difficult to gauge abnormal development. Furthermore, many studies of brain cell numbers have employed biased counting methods, whereas innovations in stereology during the past 20-30 years enable reliable and efficient estimates of cell numbers. However, estimates of cell volumes and densities in fetal brain samples are unreliable due to unpredictable shrinking artifacts, and the fragility of the fetal brain requires particular care in handling and processing. The optical fractionator design offers a direct and robust estimate of total cell numbers in the fetal brain with a minimum of handling of the tissue. Bearing this in mind, we have used the optical fractionator to quantify the growth of total cell numbers as a function of fetal age. We discovered a two-phased development in total cell numbers in the human fetal forebrain consisting of an initial steep rise in total cell numbers between 13 and 20 weeks of gestation, followed by a slower linear phase extending from mid-gestation to 40 weeks of gestation. Furthermore, we have demonstrated a reduced total cell number in the forebrain in fetuses with Down syndome at midgestation and in intrauterine growth-restricted fetuses during the third trimester.

Kisspeptin modulates sexual and emotional brain processing in humans

PubMed Central

Comninos, Alexander N.; Wall, Matthew B.; Demetriou, Lysia; Shah, Amar J.; Clarke, Sophie A.; Narayanaswamy, Shakunthala; Nesbitt, Alexander; Izzi-Engbeaya, Chioma; Prague, Julia K.; Abbara, Ali; Ratnasabapathy, Risheka; Salem, Victoria; Nijher, Gurjinder M.; Jayasena, Channa N.; Tanner, Mark; Bassett, Paul; Mehta, Amrish; Rabiner, Eugenii A.; Hönigsperger, Christoph; Silva, Meire Ribeiro; Brandtzaeg, Ole Kristian; Wilson, Steven Ray; Brown, Rachel C.; Thomas, Sarah A.; Bloom, Stephen R.; Dhillo, Waljit S.

2017-01-01

BACKGROUND. Sex, emotion, and reproduction are fundamental and tightly entwined aspects of human behavior. At a population level in humans, both the desire for sexual stimulation and the desire to bond with a partner are important precursors to reproduction. However, the relationships between these processes are incompletely understood. The limbic brain system has key roles in sexual and emotional behaviors, and is a likely candidate system for the integration of behavior with the hormonal reproductive axis. We investigated the effects of kisspeptin, a recently identified key reproductive hormone, on limbic brain activity and behavior. METHODS. Using a combination of functional neuroimaging and hormonal and psychometric analyses, we compared the effects of kisspeptin versus vehicle administration in 29 healthy heterosexual young men. RESULTS. We demonstrated that kisspeptin administration enhanced limbic brain activity specifically in response to sexual and couple-bonding stimuli. Furthermore, kisspeptin’s enhancement of limbic brain structures correlated with psychometric measures of reward, drive, mood, and sexual aversion, providing functional significance. In addition, kisspeptin administration attenuated negative mood. CONCLUSIONS. Collectively, our data provide evidence of an undescribed role for kisspeptin in integrating sexual and emotional brain processing with reproduction in humans. These results have important implications for our understanding of reproductive biology and are highly relevant to the current pharmacological development of kisspeptin as a potential therapeutic agent for patients with common disorders of reproductive function. FUNDING. National Institute for Health Research (NIHR), Wellcome Trust (Ref 080268), and the Medical Research Council (MRC). PMID:28112678

In vivo NAD assay reveals the intracellular NAD contents and redox state in healthy human brain and their age dependences

PubMed Central

Zhu, Xiao-Hong; Lu, Ming; Lee, Byeong-Yeul; Ugurbil, Kamil; Chen, Wei

2015-01-01

NAD is an essential metabolite that exists in NAD+ or NADH form in all living cells. Despite its critical roles in regulating mitochondrial energy production through the NAD+/NADH redox state and modulating cellular signaling processes through the activity of the NAD+-dependent enzymes, the method for quantifying intracellular NAD contents and redox state is limited to a few in vitro or ex vivo assays, which are not suitable for studying a living brain or organ. Here, we present a magnetic resonance (MR) -based in vivo NAD assay that uses the high-field MR scanner and is capable of noninvasively assessing NAD+ and NADH contents and the NAD+/NADH redox state in intact human brain. The results of this study provide the first insight, to our knowledge, into the cellular NAD concentrations and redox state in the brains of healthy volunteers. Furthermore, an age-dependent increase of intracellular NADH and age-dependent reductions in NAD+, total NAD contents, and NAD+/NADH redox potential of the healthy human brain were revealed in this study. The overall findings not only provide direct evidence of declined mitochondrial functions and altered NAD homeostasis that accompany the normal aging process but also, elucidate the merits and potentials of this new NAD assay for noninvasively studying the intracellular NAD metabolism and redox state in normal and diseased human brain or other organs in situ. PMID:25730862

Advanced Microscopic Imaging Methods to Investigate Cortical Development and the Etiology of Mental Retardation

ERIC Educational Resources Information Center

Haydar, Tarik F.

2005-01-01

Studies on human patients and animal models of disease have shown that disruptions in prenatal and early postnatal brain development are a root cause of mental retardation. Since proper brain development is achieved by a strict spatiotemporal control of neurogenesis, cell migration, and patterning of synapses, abnormalities in one or more of these…

Understanding in an Instant: Neurophysiological Evidence for Mechanistic Language Circuits in the Brain

ERIC Educational Resources Information Center

Pulvermuller, Friedemann; Shtyrov, Yury; Hauk, Olaf

2009-01-01

How long does it take the human mind to grasp the idea when hearing or reading a sentence? Neurophysiological methods looking directly at the time course of brain activity indexes of comprehension are critical for finding the answer to this question. As the dominant cognitive approaches, models of serial/cascaded and parallel processing, make…

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

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.

Post-focus expansion of ion beams for low fluence and large area MeV ion irradiation: Application to human brain tissue and electronics devices

NASA Astrophysics Data System (ADS)

Whitlow, Harry J.; Guibert, Edouard; Jeanneret, Patrick; Homsy, Alexandra; Roth, Joy; Krause, Sven; Roux, Adrien; Eggermann, Emmanuel; Stoppini, Luc

2017-08-01

Irradiation with ∼3 MeV proton fluences of 106-109 protons cm-2 have been applied to study the effects on human brain tissue corresponding to single-cell irradiation doses and doses received by electronic components in low-Earth orbit. The low fluence irradiations were carried out using a proton microbeam with the post-focus expansion of the beam; a method developed by the group of Breese [1]. It was found from electrophysiological measurements that the mean neuronal frequency of human brain tissue decreased to zero as the dose increased to 0-1050 Gy. Enhancement-mode MOSFET transistors exhibited a 10% reduction in threshold voltage for 2.7 MeV proton doses of 10 Gy while a NPN bipolar transistor required ∼800 Gy to reduce the hfe by 10%, which is consistent the expected values.

Inter-species activity correlations reveal functional correspondences between monkey and human brain areas

PubMed Central

Mantini, Dante; Hasson, Uri; Betti, Viviana; Perrucci, Mauro G.; Romani, Gian Luca; Corbetta, Maurizio; Orban, Guy A.; Vanduffel, Wim

2012-01-01

Evolution-driven functional changes in the primate brain are typically assessed by aligning monkey and human activation maps using cortical surface expansion models. These models use putative homologous areas as registration landmarks, assuming they are functionally correspondent. In cases where functional changes have occurred in an area, this assumption prohibits to reveal whether other areas may have assumed lost functions. Here we describe a method to examine functional correspondences across species. Without making spatial assumptions, we assess similarities in sensory-driven functional magnetic resonance imaging responses between monkey (Macaca mulatta) and human brain areas by means of temporal correlation. Using natural vision data, we reveal regions for which functional processing has shifted to topologically divergent locations during evolution. We conclude that substantial evolution-driven functional reorganizations have occurred, not always consistent with cortical expansion processes. This novel framework for evaluating changes in functional architecture is crucial to building more accurate evolutionary models. PMID:22306809

High-field fMRI unveils orientation columns in humans.

PubMed

Yacoub, Essa; Harel, Noam; Ugurbil, Kâmil

2008-07-29

Functional (f)MRI has revolutionized the field of human brain research. fMRI can noninvasively map the spatial architecture of brain function via localized increases in blood flow after sensory or cognitive stimulation. Recent advances in fMRI have led to enhanced sensitivity and spatial accuracy of the measured signals, indicating the possibility of detecting small neuronal ensembles that constitute fundamental computational units in the brain, such as cortical columns. Orientation columns in visual cortex are perhaps the best known example of such a functional organization in the brain. They cannot be discerned via anatomical characteristics, as with ocular dominance columns. Instead, the elucidation of their organization requires functional imaging methods. However, because of insufficient sensitivity, spatial accuracy, and image resolution of the available mapping techniques, thus far, they have not been detected in humans. Here, we demonstrate, by using high-field (7-T) fMRI, the existence and spatial features of orientation- selective columns in humans. Striking similarities were found with the known spatial features of these columns in monkeys. In addition, we found that a larger number of orientation columns are devoted to processing orientations around 90 degrees (vertical stimuli with horizontal motion), whereas relatively similar fMRI signal changes were observed across any given active column. With the current proliferation of high-field MRI systems and constant evolution of fMRI techniques, this study heralds the exciting prospect of exploring unmapped and/or unknown columnar level functional organizations in the human brain.

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

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.

Technical advances power neuroscience

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

Barinaga, M.

New techniques are helping researchers study the development of nerve cells in cell cultures and in vivo. These new methods are offering insights into the brain that were not available even a couple of years ago. Among the new advances discussed are imaging technology for evaluating the thinking human brain. One area in which researchers have made recent progress is the quest for ways to create immortal cell lines from specific types of nerve cells. Other projects using genetically engineered retroviruses and tumor-inducing genes, as well as gene regulation are discussed. Recent advances in neuroscience techniques apply not only tomore » neurons, but also to whole brains as well. One example is a high-resulution electroencephalogram (EEG). Although the EEG cannot pin down the actual sites of activity as precisely as static brain imaging methods, it complements them with real-time recording that can keep up with the very rapid pace of brain activity.« less

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.

Dynamic multi-coil technique (DYNAMITE) shimming for echo-planar imaging of the human brain at 7 Tesla.

PubMed

Juchem, Christoph; Umesh Rudrapatna, S; Nixon, Terence W; de Graaf, Robin A

2015-01-15

Gradient-echo echo-planar imaging (EPI) is the primary method of choice in functional MRI and other methods relying on fast MRI to image brain activation and connectivity. However, the high susceptibility of EPI towards B0 magnetic field inhomogeneity poses serious challenges. Conventional magnetic field shimming with low-order spherical harmonic (SH) functions is capable of compensating shallow field distortions, but performs poorly for global brain shimming or on specific areas with strong susceptibility-induced B0 distortions such as the prefrontal cortex (PFC). Excellent B0 homogeneity has been demonstrated recently in the human brain at 7 Tesla with the DYNAmic Multi-coIl TEchnique (DYNAMITE) for magnetic field shimming (J Magn Reson (2011) 212:280-288). Here, we report the benefits of DYNAMITE shimming for multi-slice EPI and T2* mapping. A standard deviation of 13Hz was achieved for the residual B0 distribution in the human brain at 7 Tesla with DYNAMITE shimming and was 60% lower compared to conventional shimming that employs static zero through third order SH shapes. The residual field inhomogeneity with SH shimming led to an average 8mm shift at acquisition parameters commonly used for fMRI and was reduced to 1.5-3mm with DYNAMITE shimming. T2* values obtained from the prefrontal and temporal cortices with DYNAMITE shimming were 10-50% longer than those measured with SH shimming. The reduction of the confounding macroscopic B0 field gradients with DYNAMITE shimming thereby promises improved access to the relevant microscopic T2* effects. The combination of high spatial resolution and DYNAMITE shimming allows largely artifact-free EPI and T2* mapping throughout the brain, including prefrontal and temporal lobe areas. DYNAMITE shimming is expected to critically benefit a wide range of MRI applications that rely on excellent B0 magnetic field conditions including EPI-based fMRI to study various cognitive processes and assessing large-scale brain connectivity in vivo. As such, DYNAMITE shimming has the potential to replace conventional SH shim systems in human MR scanners. Copyright © 2014 Elsevier Inc. All rights reserved.

Dynamic Multi-Coil Technique (DYNAMITE) Shimming for Echo-Planar Imaging of the Human Brain at 7 Tesla

PubMed Central

Juchem, Christoph; Rudrapatna, S. Umesh; Nixon, Terence W.; de Graaf, Robin A.

2014-01-01

Gradient-echo echo-planar imaging (EPI) is the primary method of choice in functional MRI and other methods relying on fast MRI to image brain activation and connectivity. However, the high susceptibility of EPI towards B0 magnetic field inhomogeneity poses serious challenges. Conventional magnetic field shimming with low-order spherical harmonic (SH) functions is capable of compensating shallow field distortions, but performs poorly for global brain shimming or on specific areas with strong susceptibility-induced B0 distortions such as the prefrontal cortex (PFC). Excellent B0 homogeneity has been demonstrated recently in the human brain at 7 Tesla with the DYNAmic Multi-coIl TEchnique (DYNAMITE) for magnetic field shimming (Juchem et al., J Magn Reson (2011) 212:280-288). Here, we report the benefits of DYNAMITE shimming for multi-slice EPI and T2* mapping. A standard deviation of 13 Hz was achieved for the residual B0 distribution in the human brain at 7 Tesla with DYNAMITE shimming and was 60% lower compared to conventional shimming that employs static zero through third order SH shapes. The residual field inhomogeneity with SH shimming led to an average 8 mm shift at acquisition parameters commonly used for fMRI and was reduced to 1.5-3 mm with DYNAMITE shimming. T2* values obtained from the prefrontal and temporal cortices with DYNAMITE shimming were 10-50% longer than those measured with SH shimming. The reduction of the confounding macroscopic B0 field gradients with DYNAMITE shimming thereby promises improved access to the relevant microscopic T2* effects. The combination of high spatial resolution and DYNAMITE shimming allows largely artifact-free EPI and T2* mapping throughout the brain, including prefrontal and temporal lobe areas. DYNAMITE shimming is expected to critically benefit a wide range of MRI applications that rely on excellent B0 magnetic field conditions including EPI-based fMRI to study various cognitive processes and assessing large-scale brain connectivity in vivo. As such, DYNAMITE shimming has the potential to replace conventional SH shim systems in human MR scanners. PMID:25462795

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.

The self-regulating brain and neurofeedback: Experimental science and clinical promise.

PubMed

Thibault, Robert T; Lifshitz, Michael; Raz, Amir

2016-01-01

Neurofeedback, one of the primary examples of self-regulation, designates a collection of techniques that train the brain and help to improve its function. Since coming on the scene in the 1960s, electroencephalography-neurofeedback has become a treatment vehicle for a host of mental disorders; however, its clinical effectiveness remains controversial. Modern imaging technologies of the living human brain (e.g., real-time functional magnetic resonance imaging) and increasingly rigorous research protocols that utilize such methodologies begin to shed light on the underlying mechanisms that may facilitate more effective clinical applications. In this paper we focus on recent technological advances in the field of human brain imaging and discuss how these modern methods may influence the field of neurofeedback. Toward this end, we outline the state of the evidence and sketch out future directions to further explore the potential merits of this contentious therapeutic prospect. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

PubMed

Pascual-Marqui, R D; Esslen, M; Kochi, K; Lehmann, D

2002-01-01

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.

Body Maps in the Infant Brain

PubMed Central

Marshall, Peter J.; Meltzoff, Andrew N.

2015-01-01

Researchers have examined representations of the body in the adult brain, but relatively little attention has been paid to ontogenetic aspects of neural body maps in human infants. Novel applications of methods for recording brain activity in infants are delineating cortical body maps in the first months of life. Body maps may facilitate infants’ registration of similarities between self and other—an ability that is foundational to developing social cognition. Alterations in interpersonal aspects of body representations might also contribute to social deficits in certain neurodevelopmental disorders. PMID:26231760

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.

Ad cerebrum per scientia: Ira Hirsh, psychoacoustics, and new approaches to understanding the human brain

NASA Astrophysics Data System (ADS)

Lauter, Judith

2002-05-01

As Research Director of CID, Ira emphasized the importance of combining information from biology with rigorous studies of behavior, such as psychophysics, to better understand how the brain and body accomplish the goals of everyday life. In line with this philosophy, my doctoral dissertation sought to explain brain functional asymmetries (studied with dichotic listening) in terms of the physical dimensions of a library of test sounds designed to represent a speech-music continuum. Results highlighted individual differences plus similarities in terms of patterns of relative ear advantages, suggesting an organizational basis for brain asymmetries depending on physical dimensions of stimulus and gesture with analogs in auditory, visual, somatosensory, and motor systems. My subsequent work has employed a number of noninvasive methods (OAEs, EPs, qEEG, PET, MRI) to explore the neurobiological bases of individual differences in general and functional asymmetries in particular. This research has led to (1) the AXS test battery for assessing the neurobiology of human sensory-motor function; (2) the handshaking model of brain function, describing dynamic relations along all three body/brain axes; (3) the four-domain EPIC model of functional asymmetries; and (4) the trimodal brain, a new model of individual differences based on psychoimmunoneuroendocrinology.

Supervised dictionary learning for inferring concurrent brain networks.

PubMed

Zhao, Shijie; Han, Junwei; Lv, Jinglei; Jiang, Xi; Hu, Xintao; Zhao, Yu; Ge, Bao; Guo, Lei; Liu, Tianming

2015-10-01

Task-based fMRI (tfMRI) has been widely used to explore functional brain networks via predefined stimulus paradigm in the fMRI scan. Traditionally, the general linear model (GLM) has been a dominant approach to detect task-evoked networks. However, GLM focuses on task-evoked or event-evoked brain responses and possibly ignores the intrinsic brain functions. In comparison, dictionary learning and sparse coding methods have attracted much attention recently, and these methods have shown the promise of automatically and systematically decomposing fMRI signals into meaningful task-evoked and intrinsic concurrent networks. Nevertheless, two notable limitations of current data-driven dictionary learning method are that the prior knowledge of task paradigm is not sufficiently utilized and that the establishment of correspondences among dictionary atoms in different brains have been challenging. In this paper, we propose a novel supervised dictionary learning and sparse coding method for inferring functional networks from tfMRI data, which takes both of the advantages of model-driven method and data-driven method. The basic idea is to fix the task stimulus curves as predefined model-driven dictionary atoms and only optimize the other portion of data-driven dictionary atoms. Application of this novel methodology on the publicly available human connectome project (HCP) tfMRI datasets has achieved promising results.

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.

DNA Double-Strand Break Repair Genes and Oxidative Damage in Brain Metastasis of Breast Cancer

PubMed Central

Evans, Lynda; Duchnowska, Renata; Reed, L. Tiffany; Palmieri, Diane; Qian, Yongzhen; Badve, Sunil; Sledge, George; Gril, Brunilde; Aladjem, Mirit I.; Fu, Haiqing; Flores, Natasha M.; Gökmen-Polar, Yesim; Biernat, Wojciech; Szutowicz-Zielińska, Ewa; Mandat, Tomasz; Trojanowski, Tomasz; Och, Waldemar; Czartoryska-Arlukowicz, Bogumiła; Jassem, Jacek; Mitchell, James B.

2014-01-01

Background Breast cancer frequently metastasizes to the brain, colonizing a neuro-inflammatory microenvironment. The molecular pathways facilitating this colonization remain poorly understood. Methods Expression profiling of 23 matched sets of human resected brain metastases and primary breast tumors by two-sided paired t test was performed to identify brain metastasis–specific genes. The implicated DNA repair genes BARD1 and RAD51 were modulated in human (MDA-MB-231-BR) and murine (4T1-BR) brain-tropic breast cancer cell lines by lentiviral transduction of cDNA or short hairpin RNA (shRNA) coding sequences. Their functional contribution to brain metastasis development was evaluated in mouse xenograft models (n = 10 mice per group). Results Human brain metastases overexpressed BARD1 and RAD51 compared with either matched primary tumors (1.74-fold, P < .001; 1.46-fold, P < .001, respectively) or unlinked systemic metastases (1.49-fold, P = .01; 1.44-fold, P = .008, respectively). Overexpression of either gene in MDA-MB-231-BR cells increased brain metastases by threefold to fourfold after intracardiac injections, but not lung metastases upon tail-vein injections. In 4T1-BR cells, shRNA-mediated RAD51 knockdown reduced brain metastases by 2.5-fold without affecting lung metastasis development. In vitro, BARD1- and RAD51-overexpressing cells showed reduced genomic instability but only exhibited growth and colonization phenotypes upon DNA damage induction. Reactive oxygen species were present in tumor cells and elevated in the metastatic neuro-inflammatory microenvironment and could provide an endogenous source of genotoxic stress. Tempol, a brain-permeable oxygen radical scavenger suppressed brain metastasis promotion induced by BARD1 and RAD51 overexpression. Conclusions BARD1 and RAD51 are frequently overexpressed in brain metastases from breast cancer and may constitute a mechanism to overcome reactive oxygen species–mediated genotoxic stress in the metastatic brain. PMID:24948741

Neonatal brain resting-state functional connectivity imaging modalities.

PubMed

Mohammadi-Nejad, Ali-Reza; Mahmoudzadeh, Mahdi; Hassanpour, Mahlegha S; Wallois, Fabrice; Muzik, Otto; Papadelis, Christos; Hansen, Anne; Soltanian-Zadeh, Hamid; Gelovani, Juri; Nasiriavanaki, Mohammadreza

2018-06-01

Infancy is the most critical period in human brain development. Studies demonstrate that subtle brain abnormalities during this state of life may greatly affect the developmental processes of the newborn infants. One of the rapidly developing methods for early characterization of abnormal brain development is functional connectivity of the brain at rest. While the majority of resting-state studies have been conducted using magnetic resonance imaging (MRI), there is clear evidence that resting-state functional connectivity (rs-FC) can also be evaluated using other imaging modalities. The aim of this review is to compare the advantages and limitations of different modalities used for the mapping of infants' brain functional connectivity at rest. In addition, we introduce photoacoustic tomography, a novel functional neuroimaging modality, as a complementary modality for functional mapping of infants' brain.

Syntactic Processing in the Human Brain: What We Know, What We Don't Know, and a Suggestion for How to Proceed

ERIC Educational Resources Information Center

Fedorenko, Evelina; Nieto-Castanon, Alfonso; Kanwisher, Nancy

2012-01-01

For every claim in the neuroimaging literature about a particular brain region supporting syntactic processing, there exist other claims implicating the target region in different linguistic processes, and, in many cases, in non-linguistic cognitive processes (e.g., Blumstein, 2009). We argue that traditional group analysis methods in neuroimaging…

Protein analysis through Western blot of cells excised individually from human brain and muscle tissue

PubMed Central

Koob, A.O.; Bruns, L.; Prassler, C.; Masliah, E.; Klopstock, T.; Bender, A.

2016-01-01

Comparing protein levels from single cells in tissue has not been achieved through Western blot. Laser capture microdissection allows for the ability to excise single cells from sectioned tissue and compile an aggregate of cells in lysis buffer. In this study we analyzed proteins from cells excised individually from brain and muscle tissue through Western blot. After we excised individual neurons from the substantia nigra of the brain, the accumulated surface area of the individual cells was 120,000, 24,000, 360,000, 480,000, 600,000 μm2. We used an optimized Western blot protocol to probe for tyrosine hydroxylase in this cell pool. We also took 360,000 μm2 of astrocytes (1700 cells) and analyzed the specificity of the method. In muscle we were able to analyze the proteins of the five complexes of the electron transport chain through Western blot from 200 human cells. With this method, we demonstrate the ability to compare cell-specific protein levels in the brain and muscle and describe for the first time how to visualize proteins through Western blot from cells captured individually. PMID:22402104

Protein analysis through Western blot of cells excised individually from human brain and muscle tissue.

PubMed

Koob, A O; Bruns, L; Prassler, C; Masliah, E; Klopstock, T; Bender, A

2012-06-15

Comparing protein levels from single cells in tissue has not been achieved through Western blot. Laser capture microdissection allows for the ability to excise single cells from sectioned tissue and compile an aggregate of cells in lysis buffer. In this study we analyzed proteins from cells excised individually from brain and muscle tissue through Western blot. After we excised individual neurons from the substantia nigra of the brain, the accumulated surface area of the individual cells was 120,000, 24,000, 360,000, 480,000, 600,000 μm2. We used an optimized Western blot protocol to probe for tyrosine hydroxylase in this cell pool. We also took 360,000 μm2 of astrocytes (1700 cells) and analyzed the specificity of the method. In muscle we were able to analyze the proteins of the five complexes of the electron transport chain through Western blot from 200 human cells. With this method, we demonstrate the ability to compare cell-specific protein levels in the brain and muscle and describe for the first time how to visualize proteins through Western blot from cells captured individually. Copyright © 2012 Elsevier Inc. All rights reserved.

Methodological aspects of EEG and body dynamics measurements during motion

PubMed Central

Reis, Pedro M. R.; Hebenstreit, Felix; Gabsteiger, Florian; von Tscharner, Vinzenz; Lochmann, Matthias

2014-01-01

EEG involves the recording, analysis, and interpretation of voltages recorded on the human scalp which originate from brain gray matter. EEG is one of the most popular methods of studying and understanding the processes that underlie behavior. This is so, because EEG is relatively cheap, easy to wear, light weight and has high temporal resolution. In terms of behavior, this encompasses actions, such as movements that are performed in response to the environment. However, there are methodological difficulties which can occur when recording EEG during movement such as movement artifacts. Thus, most studies about the human brain have examined activations during static conditions. This article attempts to compile and describe relevant methodological solutions that emerged in order to measure body and brain dynamics during motion. These descriptions cover suggestions on how to avoid and reduce motion artifacts, hardware, software and techniques for synchronously recording EEG, EMG, kinematics, kinetics, and eye movements during motion. Additionally, we present various recording systems, EEG electrodes, caps and methods for determinating real/custom electrode positions. In the end we will conclude that it is possible to record and analyze synchronized brain and body dynamics related to movement or exercise tasks. PMID:24715858

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.

Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging.

PubMed

Liu, Tian; Liu, Jing; de Rochefort, Ludovic; Spincemaille, Pascal; Khalidov, Ildar; Ledoux, James Robert; Wang, Yi

2011-09-01

Magnetic susceptibility varies among brain structures and provides insights into the chemical and molecular composition of brain tissues. However, the determination of an arbitrary susceptibility distribution from the measured MR signal phase is a challenging, ill-conditioned inverse problem. Although a previous method named calculation of susceptibility through multiple orientation sampling (COSMOS) has solved this inverse problem both theoretically and experimentally using multiple angle acquisitions, it is often impractical to carry out on human subjects. Recently, the feasibility of calculating the brain susceptibility distribution from a single-angle acquisition was demonstrated using morphology enabled dipole inversion (MEDI). In this study, we further improved the original MEDI method by sparsifying the edges in the quantitative susceptibility map that do not have a corresponding edge in the magnitude image. Quantitative susceptibility maps generated by the improved MEDI were compared qualitatively and quantitatively with those generated by calculation of susceptibility through multiple orientation sampling. The results show a high degree of agreement between MEDI and calculation of susceptibility through multiple orientation sampling, and the practicality of MEDI allows many potential clinical applications. Copyright © 2011 Wiley-Liss, Inc.

Optimal Measurement Conditions for Spatiotemporal EEG/MEG Source Analysis.

ERIC Educational Resources Information Center

Huizenga, Hilde M.; Heslenfeld, Dirk J.; Molenaar, Peter C. M.

2002-01-01

Developed a method to determine the required number and position of sensors for human brain electromagnetic source analysis. Studied the method through a simulation study and an empirical study on visual evoked potentials in one adult male. Results indicate the method is fast and reliable and improves source precision. (SLD)

Immunocytochemical detection of astrocytes in brain slices in combination with Nissl staining.

PubMed

Korzhevskii, D E; Otellin, V A

2005-07-01

The present study was performed to develop a simple and reliable method for the combined staining of specimens to allow the advantages of immunocytochemical detection of astrocytes and assessment of the functional state of neurons by the Nissl method to be assessed simultaneously. The protocol suggested for processing paraffin sections allows preservation of tissue structure at high quality and allows the selective identification of astrocytes with counterstaining of neurons by the Nissl method. The protocol can be used without modification for processing brain specimens from humans and various mammals--except mice and rabbits.

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.

Metabolic Brain Network Analysis of Hypothyroidism Symptom Based on [18F]FDG-PET of Rats.

PubMed

Wan, Hongkai; Tan, Ziyu; Zheng, Qiang; Yu, Jing

2018-03-12

Recent researches have demonstrated the value of using 2-deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET) imaging to reveal the hypothyroidism-related damages in local brain regions. However, the influence of hypothyroidism on the entire brain network is barely studied. This study focuses on the application of graph theory on analyzing functional brain networks of the hypothyroidism symptom. For both the hypothyroidism and the control groups of Wistar rats, the functional brain networks were constructed by thresholding the glucose metabolism correlation matrices of 58 brain regions. The network topological properties (including the small-world properties and the nodal centralities) were calculated and compared between the two groups. We found that the rat brains, like human brains, have typical properties of the small-world network in both the hypothyroidism and the control groups. However, the hypothyroidism group demonstrated lower global efficiency and decreased local cliquishness of the brain network, indicating hypothyroidism-related impairment to the brain network. The hypothyroidism group also has decreased nodal centrality in the left posterior hippocampus, the right hypothalamus, pituitary, pons, and medulla. This observation accorded with the hypothyroidism-related functional disorder of hypothalamus-pituitary-thyroid (HPT) feedback regulation mechanism. Our research quantitatively confirms that hypothyroidism hampers brain cognitive function by causing impairment to the brain network of glucose metabolism. This study reveals the feasibility and validity of applying graph theory method to preclinical [ 18 F]FDG-PET images and facilitates future study on human subjects.

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.

Cerebroventricular Microinjection (CVMI) into Adult Zebrafish Brain Is an Efficient Misexpression Method for Forebrain Ventricular Cells

PubMed Central

Kizil, Caghan; Brand, Michael

2011-01-01

The teleost fish Danio rerio (zebrafish) has a remarkable ability to generate newborn neurons in its brain at adult stages of its lifespan-a process called adult neurogenesis. This ability relies on proliferating ventricular progenitors and is in striking contrast to mammalian brains that have rather restricted capacity for adult neurogenesis. Therefore, investigating the zebrafish brain can help not only to elucidate the molecular mechanisms of widespread adult neurogenesis in a vertebrate species, but also to design therapies in humans with what we learn from this teleost. Yet, understanding the cellular behavior and molecular programs underlying different biological processes in the adult zebrafish brain requires techniques that allow manipulation of gene function. As a complementary method to the currently used misexpression techniques in zebrafish, such as transgenic approaches or electroporation-based delivery of DNA, we devised a cerebroventricular microinjection (CVMI)-assisted knockdown protocol that relies on vivo morpholino oligonucleotides, which do not require electroporation for cellular uptake. This rapid method allows uniform and efficient knockdown of genes in the ventricular cells of the zebrafish brain, which contain the neurogenic progenitors. We also provide data on the use of CVMI for growth factor administration to the brain – in our case FGF8, which modulates the proliferation rate of the ventricular cells. In this paper, we describe the CVMI method and discuss its potential uses in zebrafish. PMID:22076157

High-resolution detection of 13C multiplets from the conscious mouse brain by ex vivo NMR spectroscopy

PubMed Central

Marin-Valencia, Isaac; Good, Levi B.; Ma, Qian; Jeffrey, F. Mark; Malloy, Craig R.; Pascual, Juan M.

2011-01-01

Glucose readily supplies the brain with the majority of carbon needed to sustain neurotransmitter production and utilization., The rate of brain glucose metabolism can be computed using 13C nuclear magnetic resonance (NMR) spectroscopy by detecting changes in 13C contents of products generated by cerebral metabolism. As previously observed, scalar coupling between adjacent 13C carbons (multiplets) can provide additional information to 13C contents for the computation of metabolic rates. Most NMR studies have been conducted in large animals (often under anesthesia) because the mass of the target organ is a limiting factor for NMR. Yet, despite the challengingly small size of the mouse brain, NMR studies are highly desirable because the mouse constitutes a common animal model for human neurological disorders. We have developed a method for the ex vivo resolution of NMR multiplets arising from the brain of an awake mouse after the infusion of [1,6-13C2]glucose. NMR spectra obtained by this method display favorable signal-to-noise ratios. With this protocol, the 13C multiplets of glutamate, glutamine, GABA and aspartate achieved steady state after 150 min. The method enables the accurate resolution of multiplets over time in the awake mouse brain. We anticipate that this method can be broadly applicable to compute brain fluxes in normal and transgenic mouse models of neurological disorders. PMID:21946227

Microwave reflection, transmission, and absorption by human brain tissue

NASA Astrophysics Data System (ADS)

Ansari, M. A.; Akhlaghipour, N.; Zarei, M.; Niknam, A. R.

2018-04-01

These days, the biological effects of electromagnetic (EM) radiations on the brain, especially in the frequency range of mobile communications, have caught the attention of many scientists. Therefore, in this paper, the propagation of mobile phone electromagnetic waves in the brain tissues is investigated analytically and numerically. The brain is modeled by three layers consisting of skull, grey and white matter. First, we have analytically calculated the microwave reflection, transmission, and absorption coefficients using signal flow graph technique. The effect of microwave frequency and variations in the thickness of layers on the propagation of microwave through brain are studied. Then, the penetration of microwave in the layers is numerically investigated by Monte Carlo method. It is shown that the analytical results are in good agreement with those obtained by Monte Carlo method. Our results indicate the absorbed microwave energy depends on microwave frequency and thickness of brain layers, and the absorption coefficient is optimized at a number of frequencies. These findings can be used for comparing the microwave absorbed energy in a child's and adult's brain.

Evaluation of five diffeomorphic image registration algorithms for mouse brain magnetic resonance microscopy.

PubMed

Fu, Zhenrong; Lin, Lan; Tian, Miao; Wang, Jingxuan; Zhang, Baiwen; Chu, Pingping; Li, Shaowu; Pathan, Muhammad Mohsin; Deng, Yulin; Wu, Shuicai

2017-11-01

The development of genetically engineered mouse models for neuronal diseases and behavioural disorders have generated a growing need for small animal imaging. High-resolution magnetic resonance microscopy (MRM) provides powerful capabilities for noninvasive studies of mouse brains, while avoiding some limits associated with the histological procedures. Quantitative comparison of structural images is a critical step in brain imaging analysis, which highly relies on the performance of image registration techniques. Nowadays, there is a mushrooming growth of human brain registration algorithms, while fine-tuning of those algorithms for mouse brain MRMs is rarely addressed. Because of their topology preservation property and outstanding performance in human studies, diffeomorphic transformations have become popular in computational anatomy. In this study, we specially tuned five diffeomorphic image registration algorithms [DARTEL, geodesic shooting, diffeo-demons, SyN (Greedy-SyN and geodesic-SyN)] for mouse brain MRMs and evaluated their performance using three measures [volume overlap percentage (VOP), residual intensity error (RIE) and surface concordance ratio (SCR)]. Geodesic-SyN performed significantly better than the other methods according to all three different measures. These findings are important for the studies on structural brain changes that may occur in wild-type and transgenic mouse brains. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

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.

1H Spectroscopic Imaging of Human Brain at 3T: Comparison of Fast 3D-MRSI Techniques

PubMed Central

Zierhut, Matthew L.; Ozturk-Isik, Esin; Chen, Albert P.; Park, Ilwoo; Vigneron, Daniel B.; Nelson, Sarah J.

2011-01-01

Purpose To investigate the signal-to-noise-ratio (SNR) and data quality of time-reduced 1H 3D-MRSI techniques in the human brain at 3T. Materials and Methods Techniques that were investigated included ellipsoidal k-space sampling, parallel imaging, and EPSI. The SNR values for NAA, Cho, Cre, and lactate or lipid peaks were compared after correcting for effective spatial resolution and acquisition time in a phantom and in the brains of human volunteers. Other factors considered were linewidths, metabolite ratios, partial volume effects, and subcutaneous lipid contamination. Results In volunteers, the median normalized SNR for parallel imaging data decreased by 34–42%, but could be significantly improved using regularization. The normalized signal to noise loss in flyback EPSI data was 11–18%. The effective spatial resolutions of the traditional, ellipsoidal, SENSE, and EPSI data were 1.02, 2.43, 1.03, and 1.01cm3, respectively. As expected, lipid contamination was variable between subjects but was highest for the SENSE data. Patient data obtained using the flyback EPSI method were of excellent quality. Conclusions Data from all 1H 3D-MRSI techniques were qualitatively acceptable, based upon SNR, linewidths, and metabolite ratios. The larger FOV obtained with the EPSI methods showed negligible lipid aliasing with acceptable SNR values in less than 9.5 minutes without compromising the PSF. PMID:19711396

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

PubMed

Doborjeh, Maryam Gholami; Wang, Grace Y; Kasabov, Nikola K; Kydd, Robert; Russell, Bruce

2016-09-01

This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a GO/NOGO cognitive task performed by untreated opiate addicts, those undergoing methadone maintenance treatment (MMT) for opiate dependence and a healthy control group. the method is based on an SNN architecture called NeuCube, trained on spatiotemporal EEG data. NeuCube was used to classify EEG data across subject groups and across GO versus NOGO trials, but also facilitated a deeper comparative analysis of the dynamic brain processes. This analysis results in a better understanding of human brain functioning across subject groups when performing a cognitive task. In terms of the EEG data classification, a NeuCube model obtained better results (the maximum obtained accuracy: 90.91%) when compared with traditional statistical and artificial intelligence methods (the maximum obtained accuracy: 50.55%). more importantly, new information about the effects of MMT on cognitive brain functions is revealed through the analysis of the SNN model connectivity and its dynamics. this paper presented a new method for EEG data modeling and revealed new knowledge on brain functions associated with mental activity which is different from the brain activity observed in a resting state of the same subjects.

Towards Tunable Consensus Clustering for Studying Functional Brain Connectivity During Affective Processing.

PubMed

Liu, Chao; Abu-Jamous, Basel; Brattico, Elvira; Nandi, Asoke K

2017-03-01

In the past decades, neuroimaging of humans has gained a position of status within neuroscience, and data-driven approaches and functional connectivity analyses of functional magnetic resonance imaging (fMRI) data are increasingly favored to depict the complex architecture of human brains. However, the reliability of these findings is jeopardized by too many analysis methods and sometimes too few samples used, which leads to discord among researchers. We propose a tunable consensus clustering paradigm that aims at overcoming the clustering methods selection problem as well as reliability issues in neuroimaging by means of first applying several analysis methods (three in this study) on multiple datasets and then integrating the clustering results. To validate the method, we applied it to a complex fMRI experiment involving affective processing of hundreds of music clips. We found that brain structures related to visual, reward, and auditory processing have intrinsic spatial patterns of coherent neuroactivity during affective processing. The comparisons between the results obtained from our method and those from each individual clustering algorithm demonstrate that our paradigm has notable advantages over traditional single clustering algorithms in being able to evidence robust connectivity patterns even with complex neuroimaging data involving a variety of stimuli and affective evaluations of them. The consensus clustering method is implemented in the R package "UNCLES" available on http://cran.r-project.org/web/packages/UNCLES/index.html .

Measurement of creatine kinase reaction rate in human brain using magnetization transfer image-selected in vivo spectroscopy (MT-ISIS) and a volume ³¹P/¹H radiofrequency coil in a clinical 3-T MRI system.

PubMed

Jeong, Eun-Kee; Sung, Young-Hoon; Kim, Seong-Eun; Zuo, Chun; Shi, Xianfeng; Mellon, Eric A; Renshaw, Perry F

2011-08-01

High-energy phosphate metabolism, which allows the synthesis and regeneration of adenosine triphosphate (ATP), is a vital process for neuronal survival and activity. In particular, creatine kinase (CK) serves as an energy reservoir for the rapid buffering of ATP levels. Altered CK enzyme activity, reflecting compromised high-energy phosphate metabolism or mitochondrial dysfunction in the brain, can be assessed using magnetization transfer (MT) MRS. MT (31)P MRS has been used to measure the forward CK reaction rate in animal and human brain, employing a surface radiofrequency coil. However, long acquisition times and excessive radiofrequency irradiation prevent these methods from being used routinely for clinical evaluations. In this article, a new MT (31)P MRS method is presented, which can be practically used to measure the CK forward reaction rate constant in a clinical MRI system employing a volume head (31)P coil for spatial localization, without contamination from the scalp muscle, and an acquisition time of 30 min. Other advantages associated with the method include radiofrequency homogeneity within the regions of interest of the brain using a volume coil with image-selected in vivo spectroscopy localization, and reduction of the specific absorption rate using nonadiabatic radiofrequency pulses for MT saturation. The mean value of k(f) was measured as 0.320 ± 0.075 s(-1) from 10 healthy volunteers with an age range of 18-40 years. These values are consistent with those obtained using earlier methods, and the technique may be used routinely to evaluate energetic processes in the brain on a clinical MRI system. Copyright © 2010 John Wiley & Sons, Ltd.

Validated UPLC-MS/MS method for determination of moclobemide in human brain cell supernatant and its application to bidirectional transport study.

PubMed

Li-Bo, Dai; Miao, Yan; Huan-De, Li; Ping-Fei, Fang; Feng, Wang; Yang, Deng

2013-09-01

A simple and sensitive analytical method based on ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) has been developed for determination of moclobemide in human brain cell monolayer as an in vitro model of blood-brain barrier. Brucine was employed as the internal standard. Moclobemide and internal standard were extracted from cell supernatant by ethyl acetate after alkalinizing with sodium hydroxide. The UPLC separation was performed on an Acquity UPLC(TM) BEH C18 column (50 × 2.1 mm, 1.7 µm, Waters, USA) with a mobile phase consisting of methanol-water (29.5:70.5, v/v); the water in the mobile phase contained 0.05% ammonium acetate and 0.1% formic acid. Detection of the analytes was achieved using positive ion electrospray via multiple reaction monitoring mode. The mass transitions were m/z 269.16 → 182.01 for moclobemide and m/z 395.24 → 324.15 for brucine. The extraction recovery was 83.0-83.4% and the lower limit of quantitation (LLOQ) was 1.0 ng/mL for moclobemide. The method was validated from LLOQ to 1980 ng/mL with a coefficient of determination greater than 0.999. Intra- and inter-day accuracies of the method at three concentrations ranged from 89.1 to 100.9% for moclobemide with precision of 1.1-9.6%. This validated method was successfully applied to bidirectional transport study of moclobemide blood-brain barrier permeability. Copyright © 2013 John Wiley & Sons, Ltd.

The Brain Response to Peripheral Insulin Declines with Age: A Contribution of the Blood-Brain Barrier?

PubMed Central

Heni, Martin; Maetzler, Walter; Fritsche, Andreas; Häring, Hans-Ulrich; Hennige, Anita M.

2015-01-01

Objectives It is a matter of debate whether impaired insulin action originates from a defect at the neural level or impaired transport of the hormone into the brain. In this study, we aimed to investigate the effect of aging on insulin concentrations in the periphery and the central nervous system as well as its impact on insulin-dependent brain activity. Methods Insulin, glucose and albumin concentrations were determined in 160 paired human serum and cerebrospinal fluid (CSF) samples. Additionally, insulin was applied in young and aged mice by subcutaneous injection or intracerebroventricularly to circumvent the blood-brain barrier. Insulin action and cortical activity were assessed by Western blotting and electrocorticography radiotelemetric measurements. Results In humans, CSF glucose and insulin concentrations were tightly correlated with the respective serum/plasma concentrations. The CSF/serum ratio for insulin was reduced in older subjects while the CSF/serum ratio for albumin increased with age like for most other proteins. Western blot analysis in murine whole brain lysates revealed impaired phosphorylation of AKT (P-AKT) in aged mice following peripheral insulin stimulation whereas P-AKT was comparable to levels in young mice after intracerebroventricular insulin application. As readout for insulin action in the brain, insulin-mediated cortical brain activity instantly increased in young mice subcutaneously injected with insulin but was significantly reduced and delayed in aged mice during the treatment period. When insulin was applied intracerebroventricularly into aged animals, brain activity was readily improved. Conclusions This study discloses age-dependent changes in insulin CSF/serum ratios in humans. In the elderly, cerebral insulin resistance might be partially attributed to an impaired transport of insulin into the central nervous system. PMID:25965336

Neurons of human nucleus accumbens.

PubMed

Sazdanović, Maja; Sazdanović, Predrag; Zivanović-Macuzić, Ivana; Jakovljević, Vladimir; Jeremić, Dejan; Peljto, Amir; Tosevski, Jovo

2011-08-01

Nucleus accumbens is a part of the ventral striatum also known as a drug active brain region, especially related with drug addiction. The aim of the study was to investigate the Golgi morphology of the nucleus accumbens neurons. The study was performed on the frontal and sagittal sections of 15 human brains by the Golgi Kopsch method. We classified neurons in the human nucleus accumbens according to their morphology and size into four types: type I--fusiform neurons; type II--fusiform neurons with lateral dendrite, arising from a part of the cell body; type III--pyramidal-like neuron; type IV--multipolar neuron. The medium spiny neurons, which are mostly noted regarding to the drug addictive conditions of the brain, correspond to the type IV--multipolar neurons. Two regions of human nucleus accumbens could be clearly recognized on Nissl and Golgi preparations each containing different predominant neuronal types. Central part of nucleus accumbens, core region, has a low density of impregnated neurons with predominant type III, pyramidal-like neurons, with spines on secondary branches and rare type IV, multipolar neurons. Contrary to the core, peripheral region, shell of nucleus, has a high density of impregnated neurons predominantly contained of type I and type IV--multipolar neurons, which all are rich in spines on secondary and tertiary dendritic branches. Our results indicate great morphological variability of human nucleus accumbens neurons. This requires further investigations and clarifying clinical significance of this important brain region.

Registration of in vivo MR to histology of rodent brains using blockface imaging

NASA Astrophysics Data System (ADS)

Uberti, Mariano; Liu, Yutong; Dou, Huanyu; Mosley, R. Lee; Gendelman, Howard E.; Boska, Michael

2009-02-01

Registration of MRI to histopathological sections can enhance bioimaging validation for use in pathobiologic, diagnostic, and therapeutic evaluations. However, commonly used registration methods fall short of this goal due to tissue shrinkage and tearing after brain extraction and preparation. In attempts to overcome these limitations we developed a software toolbox using 3D blockface imaging as the common space of reference. This toolbox includes a semi-automatic brain extraction technique using constraint level sets (CLS), 3D reconstruction methods for the blockface and MR volume, and a 2D warping technique using thin-plate splines with landmark optimization. Using this toolbox, the rodent brain volume is first extracted from the whole head MRI using CLS. The blockface volume is reconstructed followed by 3D brain MRI registration to the blockface volume to correct the global deformations due to brain extraction and fixation. Finally, registered MRI and histological slices are warped to corresponding blockface images to correct slice specific deformations. The CLS brain extraction technique was validated by comparing manual results showing 94% overlap. The image warping technique was validated by calculating target registration error (TRE). Results showed a registration accuracy of a TRE < 1 pixel. Lastly, the registration method and the software tools developed were used to validate cell migration in murine human immunodeficiency virus type one encephalitis.

Ethical issues when modelling brain disorders innon-human primates.

PubMed

Neuhaus, Carolyn P

2018-05-01

Non-human animal models of human diseases advance our knowledge of the genetic underpinnings of disease and lead to the development of novel therapies for humans. While mice are the most common model organisms, their usefulness is limited. Larger animals may provide more accurate and valuable disease models, but it has, until recently, been challenging to create large animal disease models. Genome editors, such as Clustered Randomised Interspersed Palindromic Repeat (CRISPR), meet some of these challenges and bring routine genome engineering of larger animals and non-human primates (NHPs) well within reach. There is growing interest in creating NHP models of brain disorders such as autism, depression and Alzheimer's, which are very difficult to model or study in other organisms, including humans. New treatments are desperately needed for this set of disorders. This paper is novel in asking: Insofar as NHPs are being considered for use as model organisms for brain disorders, can this be done ethically? The paper concludes that it cannot. Notwithstanding ongoing debate about NHPs' moral status, (1) animal welfare concerns, (2) the availability of alternative methods of studying brain disorders and (3) unmet expectations of benefit justify a stop on the creation of NHP model organisms to study brain disorders. The lure of using new genetic technologies combined with the promise of novel therapeutics presents a formidable challenge to those who call for slow, careful, and only necessary research involving NHPs. But researchers should not create macaques with social deficits or capuchin monkeys with memory deficits just because they can. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

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

Retest imaging of [11C]NOP-1A binding to nociceptin/orphanin FQ peptide (NOP) receptors in the brain of healthy humans.

PubMed

Lohith, Talakad G; Zoghbi, Sami S; Morse, Cheryl L; Araneta, Maria D Ferraris; Barth, Vanessa N; Goebl, Nancy A; Tauscher, Johannes T; Pike, Victor W; Innis, Robert B; Fujita, Masahiro

2014-02-15

[(11)C]NOP-1A is a novel high-affinity PET ligand for imaging nociceptin/orphanin FQ peptide (NOP) receptors. Here, we report reproducibility and reliability measures of binding parameter estimates for [(11)C]NOP-1A binding in the brain of healthy humans. After intravenous injection of [(11)C]NOP-1A, PET scans were conducted twice on eleven healthy volunteers on the same (10/11 subjects) or different (1/11 subjects) days. Subjects underwent serial sampling of radial arterial blood to measure parent radioligand concentrations. Distribution volume (VT; a measure of receptor density) was determined by compartmental (one- and two-tissue) modeling in large regions and by simpler regression methods (graphical Logan and bilinear MA1) in both large regions and voxel data. Retest variability and intraclass correlation coefficient (ICC) of VT were determined as measures of reproducibility and reliability respectively. Regional [(11)C]NOP-1A uptake in the brain was high, with a peak radioactivity concentration of 4-7 SUV (standardized uptake value) and a rank order of putamen>cingulate cortex>cerebellum. Brain time-activity curves fitted well in 10 of 11 subjects by unconstrained two-tissue compartmental model. The retest variability of VT was moderately good across brain regions except cerebellum, and was similar across different modeling methods, averaging 12% for large regions and 14% for voxel-based methods. The retest reliability of VT was also moderately good in most brain regions, except thalamus and cerebellum, and was similar across different modeling methods averaging 0.46 for large regions and 0.48 for voxels having gray matter probability >20%. The lowest retest variability and highest retest reliability of VT were achieved by compartmental modeling for large regions, and by the parametric Logan method for voxel-based methods. Moderately good reproducibility and reliability measures of VT for [(11)C]NOP-1A make it a useful PET ligand for comparing NOP receptor binding between different subject groups or under different conditions in the same subject. Copyright © 2013. Published by Elsevier Inc.

Optimal staining methods for delineation of cortical areas and neuron counts in human brains.

PubMed

Uylings, H B; Zilles, K; Rajkowska, G

1999-04-01

For cytoarchitectonic delineation of cortical areas in human brain, the Gallyas staining for somata with its sharp contrast between cell bodies and neuropil is preferable to the classical Nissl staining, the more so when an image analysis system is used. This Gallyas staining, however, does not appear to be appropriate for counting neuron numbers in pertinent brain areas, due to the lack of distinct cytological features between small neurons and glial cells. For cell counting Nissl is preferable. In an optimal design for cell counting at least both the Gallyas and the Nissl staining must be applied, the former staining for cytoarchitectural delineaton of cortical areas and the latter for counting the number of neurons in the pertinent cortical areas. Copyright 1999 Academic Press.

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.

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.

The potential application of a transcriptionally regulated oncolytic herpes simplex virus for human cancer therapy

PubMed Central

Miao, L; Fraefel, C; Sia, K C; Newman, J P; Mohamed-Bashir, S A; Ng, W H; Lam, P Y P

2014-01-01

Background: Emerging studies have shown the potential benefit of arming oncolytic viruses with therapeutic genes. However, most of these therapeutic genes are placed under the regulation of ubiquitous viral promoters. Our goal is to generate a safer yet potent oncolytic herpes simplex virus type-1 (HSV-1) for cancer therapy. Methods: Using bacterial artificial chromosome (BAC) recombineering, a cell cycle-regulatable luciferase transgene cassette was replaced with the infected cell protein 6 (ICP6) coding region (encoded for UL39 or large subunit of ribonucleotide reductase) of the HSV-1 genome. These recombinant viruses, YE-PC8, were further tested for its proliferation-dependent luciferase gene expression. Results: The ability of YE-PC8 to confer proliferation-dependent transgene expression was demonstrated by injecting similar amount of viruses into the tumour-bearing region of the brain and the contralateral normal brain parenchyma of the same mouse. The results showed enhanced levels of luciferase activities in the tumour region but not in the normal brain parenchyma. Similar findings were observed in YE-PC8-infected short-term human brain patient-derived glioma cells compared with normal human astrocytes. intratumoural injection of YE-PC8 viruses resulted in 77% and 80% of tumour regression in human glioma and human hepatocellular carcinoma xenografts, respectively. Conclusion: YE-PC8 viruses confer tumour selectivity in proliferating cells and may be developed further as a feasible approach to treat human cancers. PMID:24196790

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data.

PubMed

Cha, Kihoon; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

2015-01-01

It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.

Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

PubMed Central

2015-01-01

Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation. PMID:26043779

In vivo bioluminescence imaging validation of a human biopsy-derived orthotopic mouse model of glioblastoma multiforme.

PubMed

Jarzabek, Monika A; Huszthy, Peter C; Skaftnesmo, Kai O; McCormack, Emmet; Dicker, Patrick; Prehn, Jochen H M; Bjerkvig, Rolf; Byrne, Annette T

2013-05-01

Glioblastoma multiforme (GBM), the most aggressive brain malignancy, is characterized by extensive cellular proliferation, angiogenesis, and single-cell infiltration into the brain. We have previously shown that a xenograft model based on serial xenotransplantation of human biopsy spheroids in immunodeficient rodents maintains the genotype and phenotype of the original patient tumor. The present work further extends this model for optical assessment of tumor engraftment and growth using bioluminescence imaging (BLI). A method for successful lentiviral transduction of the firefly luciferase gene into multicellular spheroids was developed and implemented to generate optically active patient tumor cells. Luciferase-expressing spheroids were injected into the brains of immunodeficient mice. BLI photon counts and tumor volumes from magnetic resonance imaging (MRI) were correlated. Luciferase-expressing tumors recapitulated the histopathologic hallmarks of human GBMs and showed proliferation rates and microvessel density counts similar to those of wild-type xenografts. Moreover, we detected widespread invasion of luciferase-positive tumor cells in the mouse brains. Herein we describe a novel optically active model of GBM that closely mimics human pathology with respect to invasion, angiogenesis, and proliferation indices. The model may thus be routinely used for the assessment of novel anti-GBM therapeutic approaches implementing well-established and cost-effective optical imaging strategies.

Dynamic Glucose Enhanced (DGE) MRI for Combined Imaging of Blood Brain Barrier Break Down and Increased Blood Volume in Brain Cancer

PubMed Central

Xu, Xiang; Chan, Kannie WY; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T.; van Zijl, Peter C.M.

2015-01-01

Purpose Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Methods Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. Results DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared to contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (p<0.005). Both CEST and relaxation effects contribute to the signal change. Conclusion DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. PMID:26404120

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

The biochemical, nanomechanical and chemometric signatures of brain cancer

NASA Astrophysics Data System (ADS)

Abramczyk, Halina; Imiela, Anna

2018-01-01

Raman spectroscopy and imaging combined with AFM topography and mechanical indentation by AFM have been shown to be an effective tool for analysis and discrimination of human brain tumors from normal structures. Raman methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n = 5) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma (IV grade), and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational spectra and Raman images we provide a real-time feedback that is label-free method to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, and proteins. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have shown that the ratio of Raman intensities I2930/I2845 at 2930 and 2845 cm- 1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the lipid and protein contents of tumorous brain tissue compared to the non-tumor tissue. Almost all brain tumors have the Raman intensity ratios significantly higher (1.99 ± 0.026) than that found in non-tumor brain tissue, which is 1.456 ± 0.02, and indicates that the relative amount of lipids compared to proteins is significantly higher in the normal brain tissue. Mechanical indentation using AFM on sliced human brain tissues (medulloblastoma, grade IV) revealed that the mechanical properties of this tissue are strongly heterogeneous, between 1.8 and 75.7 kPa, and the mean of 27.16 kPa. The sensitivity and specificity obtained directly from PLSDA and cross validation gives a sensitivity and specificity of 98.5% and 96% and 96.3% and 92% for cross-validation, respectively. The high sensitivity and specificity demonstrates usefulness for a proper decision for a Raman diagnostic test on biochemical alterations monitored by Raman spectroscopy related to brain cancer development.

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

Multichannel optical mapping: investigation of depth information

NASA Astrophysics Data System (ADS)

Sase, Ichiro; Eda, Hideo; Seiyama, Akitoshi; Tanabe, Hiroki C.; Takatsuki, Akira; Yanagida, Toshio

2001-06-01

Near infrared (NIR) light has become a powerful tool for non-invasive imaging of human brain activity. Many systems have been developed to capture the changes in regional brain blood flow and hemoglobin oxygenation, which occur in the human cortex in response to neural activity. We have developed a multi-channel reflectance imaging system, which can be used as a `mapping device' and also as a `multi-channel spectrophotometer'. In the present study, we visualized changes in the hemodynamics of the human occipital region in multiple ways. (1) Stimulating left and right primary visual cortex independently by showing sector shaped checkerboards sequentially over the contralateral visual field, resulted in corresponding changes in the hemodynamics observed by `mapping' measurement. (2) Simultaneous measurement of functional-MRI and NIR (changes in total hemoglobin) during visual stimulation showed good spatial and temporal correlation with each other. (3) Placing multiple channels densely over the occipital region demonstrated spatial patterns more precisely, and depth information was also acquired by placing each pair of illumination and detection fibers at various distances. These results indicate that optical method can provide data for 3D analysis of human brain functions.

Bayesian convolutional neural network based MRI brain extraction on nonhuman primates.

PubMed

Zhao, Gengyan; Liu, Fang; Oler, Jonathan A; Meyerand, Mary E; Kalin, Ned H; Birn, Rasmus M

2018-07-15

Brain extraction or skull stripping of magnetic resonance images (MRI) is an essential step in neuroimaging studies, the accuracy of which can severely affect subsequent image processing procedures. Current automatic brain extraction methods demonstrate good results on human brains, but are often far from satisfactory on nonhuman primates, which are a necessary part of neuroscience research. To overcome the challenges of brain extraction in nonhuman primates, we propose a fully-automated brain extraction pipeline combining deep Bayesian convolutional neural network (CNN) and fully connected three-dimensional (3D) conditional random field (CRF). The deep Bayesian CNN, Bayesian SegNet, is used as the core segmentation engine. As a probabilistic network, it is not only able to perform accurate high-resolution pixel-wise brain segmentation, but also capable of measuring the model uncertainty by Monte Carlo sampling with dropout in the testing stage. Then, fully connected 3D CRF is used to refine the probability result from Bayesian SegNet in the whole 3D context of the brain volume. The proposed method was evaluated with a manually brain-extracted dataset comprising T1w images of 100 nonhuman primates. Our method outperforms six popular publicly available brain extraction packages and three well-established deep learning based methods with a mean Dice coefficient of 0.985 and a mean average symmetric surface distance of 0.220 mm. A better performance against all the compared methods was verified by statistical tests (all p-values < 10 -4 , two-sided, Bonferroni corrected). The maximum uncertainty of the model on nonhuman primate brain extraction has a mean value of 0.116 across all the 100 subjects. The behavior of the uncertainty was also studied, which shows the uncertainty increases as the training set size decreases, the number of inconsistent labels in the training set increases, or the inconsistency between the training set and the testing set increases. Copyright © 2018 Elsevier Inc. All rights reserved.

Brain Connectivity as a DNA Sequencing Problem

NASA Astrophysics Data System (ADS)

Zador, Anthony

The mammalian cortex consists of millions or billions of neurons, each connected to thousands of other neurons. Traditional methods for determining the brain connectivity rely on microscopy to visualize neuronal connections, but such methods are slow, labor-intensive and often lack single neuron resolution. We have recently developed a new method, MAPseq, to recast the determination of brain wiring into a form that can exploit the tremendous recent advances in high-throughput DNA sequencing. DNA sequencing technology has outpaced even Moore's law, so that the cost of sequencing the human genome has dropped from a billion dollars in 2001 to below a thousand dollars today. MAPseq works by introducing random sequences of DNA-``barcodes''-to tag neurons uniquely. With MAPseq, we can determine the connectivity of over 50K single neurons in a single mouse cortex in about a week, an unprecedented throughput, ushering in the era of ``big data'' for brain wiring. We are now developing analytical tools and algorithms to make sense of these novel data sets.

Precise and accurate assay of pregnenolone and five other neurosteroids in monkey brain tissue by LC-MS/MS.

PubMed

Dury, Alain Y; Ke, Yuyong; Labrie, Fernand

2016-09-01

A series of steroids present in the brain have been named "neurosteroids" following the possibility of their role in the central nervous system impairments such as anxiety disorders, depression, premenstrual dysphoric disorder (PMDD), addiction, or even neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Study of their potential role requires a sensitive and accurate assay of their concentration in the monkey brain, the closest model to the human. We have thus developed a robust, precise and accurate liquid chromatography-tandem mass spectrometry method for the assay of pregnenolone, pregnanolone, epipregnanolone, allopregnanolone, epiallopregnanolone, and androsterone in the cynomolgus monkey brain. The extraction method includes a thorough sample cleanup using protein precipitation and phospholipid removal, followed by hexane liquid-liquid extraction and a Girard T ketone-specific derivatization. This method opens the possibility of investigating the potential implication of these six steroids in the most suitable animal model for neurosteroid-related research. Copyright © 2016 Elsevier Inc. All rights reserved.

Brain metastasis detection by resonant Raman optical biopsy method

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-hui; Cheng, Gangge; Zhou, Lixin; Zhang, Chunyuan; Pu, Yang; Li, Zhongwu; Liu, Yulong; Li, Qingbo; Wang, Wei; Alfano, Robert R.

2014-03-01

Resonant Raman (RR) spectroscopy provides an effective way to enhance Raman signal from particular bonds associated with key molecules due to changes on a molecular level. In this study, RR is used for detection of human brain metastases of five kinds of primary organs of lung, breast, kidney, rectal and orbital in ex-vivo. The RR spectra of brain metastases cancerous tissues were measured and compared with those of normal brain tissues and the corresponding primary cancer tissues. The differences of five types of brain metastases tissues in key bio-components of carotene, tryptophan, lactate, alanine and methyl/methylene group were investigated. The SVM-KNN classifier was used to categorize a set of RR spectra data of brain metastasis of lung cancerous tissues from normal brain tissue, yielding diagnostic sensitivity and specificity at 100% and 75%, respectively. The RR spectroscopy may provide new moleculebased optical probe tools for diagnosis and classification of brain metastatic of cancers.

Functional coupling between adenosine A1 receptors and G-proteins in rat and postmortem human brain membranes determined with conventional guanosine-5'-O-(3-[35S]thio)triphosphate ([35S]GTPγS) binding or [35S]GTPγS/immunoprecipitation assay.

PubMed

Odagaki, Yuji; Kinoshita, Masakazu; Ota, Toshio; Meana, J Javier; Callado, Luis F; Matsuoka, Isao; García-Sevilla, Jesús A

2018-06-01

Adenosine signaling plays a complex role in multiple physiological processes in the brain, and its dysfunction has been implicated in pathophysiology of neuropsychiatric diseases such as schizophrenia and affective disorders. In the present study, the coupling between adenosine A 1 receptor and G-protein was assessed by means of two [ 35 S]GTPγS binding assays, i.e., conventional filtration method and [ 35 S]GTPγS binding/immunoprecipitation in rat and human brain membranes. The latter method provides information about adenosine A 1 receptor-mediated Gα i-3 activation in rat as well as human brain membranes. On the other hand, adenosine-stimulated [ 35 S]GTPγS binding determined with conventional assay derives from functional activation of Gα i/o proteins (not restricted only to Gα i-3 ) coupled to adenosine A 1 receptors. The determination of adenosine concentrations in the samples used in the present study indicates the possibility that the assay mixture under our experimental conditions contains residual endogenous adenosine at nanomolar concentrations, which was also suggested by the results on the effects of adenosine receptor antagonists on basal [ 35 S]GTPγS binding level. The effects of adenosine deaminase (ADA) on basal binding also support the presence of adenosine. Nevertheless, the varied patterns of ADA discouraged us from adding ADA into assay medium routinely. The concentration-dependent increases elicited by adenosine were determined in 40 subjects without any neuropsychiatric disorders. The increases in %E max values determined by conventional assay according to aging and postmortem delay should be taken into account in future studies focusing on the effects of psychiatric disorders on adenosine A 1 receptor/G-protein interaction in postmortem human brain tissue.

Plasticity of the aging brain: new directions in cognitive neuroscience.

PubMed

Gutchess, Angela

2014-10-31

Cognitive neuroscience has revealed aging of the human brain to be rich in reorganization and change. Neuroimaging results have recast our framework around cognitive aging from one of decline to one emphasizing plasticity. Current methods use neurostimulation approaches to manipulate brain function, providing a direct test of the ways that the brain differently contributes to task performance for younger and older adults. Emerging research into emotional, social, and motivational domains provides some evidence for preservation with age, suggesting potential avenues of plasticity, alongside additional evidence for reorganization. Thus, we begin to see that aging of the brain, amidst interrelated behavioral and biological changes, is as complex and idiosyncratic as the brain itself, qualitatively changing over the life span. Copyright © 2014, American Association for the Advancement of Science.

Whole Brain Size and General Mental Ability: A Review

PubMed Central

Rushton, J. Philippe; Ankney, C. Davison

2009-01-01

We review the literature on the relation between whole brain size and general mental ability (GMA) both within and between species. Among humans, in 28 samples using brain imaging techniques, the mean brain size/GMA correlation is 0.40 (N = 1,389; p < 10−10); in 59 samples using external head size measures it is 0.20 (N = 63,405; p < 10−10). In 6 samples using the method of correlated vectors to distill g, the general factor of mental ability, the mean r is 0.63. We also describe the brain size/GMA correlations with age, socioeconomic position, sex, and ancestral population groups, which also provide information about brain–behavior relationships. Finally, we examine brain size and mental ability from an evolutionary and behavior genetic perspective. PMID:19283594

Infant fMRI: A Model System for Cognitive Neuroscience.

PubMed

Ellis, Cameron T; Turk-Browne, Nicholas B

2018-05-01

Our understanding of the typical human brain has benefitted greatly from studying different kinds of brains and their associated behavioral repertoires, including animal models and neuropsychological patients. This same comparative perspective can be applied to early development - the environment, behavior, and brains of infants provide a model system for understanding how the mature brain works. This approach requires noninvasive methods for measuring brain function in awake, behaving infants. fMRI is becoming increasingly viable for this purpose, with the unique ability to precisely measure the entire brain, including both cortical and subcortical structures. Here we discuss potential lessons from infant fMRI for several domains of adult cognition and consider the challenges of conducting such research and how they might be mitigated. Copyright © 2018 Elsevier Ltd. All rights reserved.

PET Quantification of the Norepinephrine Transporter in Human Brain with (S,S)-18F-FMeNER-D2.

PubMed

Moriguchi, Sho; Kimura, Yasuyuki; Ichise, Masanori; Arakawa, Ryosuke; Takano, Harumasa; Seki, Chie; Ikoma, Yoko; Takahata, Keisuke; Nagashima, Tomohisa; Yamada, Makiko; Mimura, Masaru; Suhara, Tetsuya

2017-07-01

Norepinephrine transporter (NET) in the brain plays important roles in human cognition and the pathophysiology of psychiatric disorders. Two radioligands, ( S , S )- 11 C-MRB and ( S , S )- 18 F-FMeNER-D 2 , have been used for imaging NETs in the thalamus and midbrain (including locus coeruleus) using PET in humans. However, NET density in the equally important cerebral cortex has not been well quantified because of unfavorable kinetics with ( S , S )- 11 C-MRB and defluorination with ( S , S )- 18 F-FMeNER-D 2 , which can complicate NET quantification in the cerebral cortex adjacent to the skull containing defluorinated 18 F radioactivity. In this study, we have established analysis methods of quantification of NET density in the brain including the cerebral cortex using ( S , S )- 18 F-FMeNER-D 2 PET. Methods: We analyzed our previous ( S , S )- 18 F-FMeNER-D 2 PET data of 10 healthy volunteers dynamically acquired for 240 min with arterial blood sampling. The effects of defluorination on the NET quantification in the superficial cerebral cortex was evaluated by establishing a time stability of NET density estimations with an arterial input 2-tissue-compartment model, which guided the less-invasive reference tissue model and area under the time-activity curve methods to accurately quantify NET density in all brain regions including the cerebral cortex. Results: Defluorination of ( S , S )- 18 F-FMeNER-D 2 became prominent toward the latter half of the 240-min scan. Total distribution volumes in the superficial cerebral cortex increased with the scan duration beyond 120 min. We verified that 90-min dynamic scans provided a sufficient amount of data for quantification of NET density unaffected by defluorination. Reference tissue model binding potential values from the 90-min scan data and area under the time-activity curve ratios of 70- to 90-min data allowed for the accurate quantification of NET density in the cerebral cortex. Conclusion: We have established methods of quantification of NET densities in the brain including the cerebral cortex unaffected by defluorination using ( S , S )- 18 F-FMeNER-D 2 These results suggest that we can accurately quantify NET density with a 90-min ( S , S )- 18 F-FMeNER-D 2 scan in broad brain areas. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.

Orthotopic Patient-Derived Glioblastoma Xenografts in Mice.

PubMed

Xu, Zhongye; Kader, Michael; Sen, Rajeev; Placantonakis, Dimitris G

2018-01-01

Patient-derived xenografts (PDX) provide in vivo glioblastoma (GBM) models that recapitulate actual tumors. Orthotopic tumor xenografts within the mouse brain are obtained by injection of GBM stem-like cells derived from fresh surgical specimens. These xenografts reproduce GBM's histologic complexity and hallmark biological behaviors, such as brain invasion, angiogenesis, and resistance to therapy. This method has become essential for analyzing mechanisms of tumorigenesis and testing the therapeutic effect of candidate agents in the preclinical setting. Here, we describe a protocol for establishing orthotopic tumor xenografts in the mouse brain with human GBM cells.

Development of a Finite Element Model for Blast Brain Injury and the Effects of CSF Cavitation

DTIC Science & Technology

2012-02-02

FIGURE 1. Brain geometry from photo ( left ; Visible Human Project) and plane-strain model ( right ). Development of a Finite Element Model method in LS-Dyna...between the non-cavitating ( left ) and cavitating ( right ) models for the 500 kPa/4 ms blast condition. FIGURE 6. (a) Comparing the time-history and (b...between the non-cavitating ( left ) and cavitating ( right ) models for the 500 kPa/4 ms blast condition. PANZER et al. Brain Response to Blast Over the wide

Coordinated Gene Expression of Neuroinflammatory and Cell Signaling Markers in Dorsolateral Prefrontal Cortex during Human Brain Development and Aging

PubMed Central

Primiani, Christopher T.; Ryan, Veronica H.; Rao, Jagadeesh S.; Cam, Margaret C.; Ahn, Kwangmi; Modi, Hiren R.; Rapoport, Stanley I.

2014-01-01

Background Age changes in expression of inflammatory, synaptic, and neurotrophic genes are not well characterized during human brain development and senescence. Knowing these changes may elucidate structural, metabolic, and functional brain processes over the lifespan, as well vulnerability to neurodevelopmental or neurodegenerative diseases. Hypothesis Expression levels of inflammatory, synaptic, and neurotrophic genes in the human brain are coordinated over the lifespan and underlie changes in phenotypic networks or cascades. Methods We used a large-scale microarray dataset from human prefrontal cortex, BrainCloud, to quantify age changes over the lifespan, divided into Development (0 to 21 years, 87 brains) and Aging (22 to 78 years, 144 brains) intervals, in transcription levels of 39 genes. Results Gene expression levels followed different trajectories over the lifespan. Many changes were intercorrelated within three similar groups or clusters of genes during both Development and Aging, despite different roles of the gene products in the two intervals. During Development, changes were related to reported neuronal loss, dendritic growth and pruning, and microglial events; TLR4, IL1R1, NFKB1, MOBP, PLA2G4A, and PTGS2 expression increased in the first years of life, while expression of synaptic genes GAP43 and DBN1 decreased, before reaching plateaus. During Aging, expression was upregulated for potentially pro-inflammatory genes such as NFKB1, TRAF6, TLR4, IL1R1, TSPO, and GFAP, but downregulated for neurotrophic and synaptic integrity genes such as BDNF, NGF, PDGFA, SYN, and DBN1. Conclusions Coordinated changes in gene transcription cascades underlie changes in synaptic, neurotrophic, and inflammatory phenotypic networks during brain Development and Aging. Early postnatal expression changes relate to neuronal, glial, and myelin growth and synaptic pruning events, while late Aging is associated with pro-inflammatory and synaptic loss changes. Thus, comparable transcriptional regulatory networks that operate throughout the lifespan underlie different phenotypic processes during Aging compared to Development. PMID:25329999

Dynamics of the human brain network revealed by time-frequency effective connectivity in fNIRS

PubMed Central

Vergotte, Grégoire; Torre, Kjerstin; Chirumamilla, Venkata Chaitanya; Anwar, Abdul Rauf; Groppa, Sergiu; Perrey, Stéphane; Muthuraman, Muthuraman

2017-01-01

Functional near infrared spectroscopy (fNIRS) is a promising neuroimaging method for investigating networks of cortical regions over time. We propose a directed effective connectivity method (TPDC) allowing the capture of both time and frequency evolution of the brain’s networks using fNIRS data acquired from healthy subjects performing a continuous finger-tapping task. Using this method we show the directed connectivity patterns among cortical motor regions involved in the task and their significant variations in the strength of information flow exchanges. Intra and inter-hemispheric connections during the motor task with their temporal evolution are also provided. Characterisation of the fluctuations in brain connectivity opens up a new way to assess the organisation of the brain to adapt to changing task constraints, or under pathological conditions. PMID:29188123

Periodontal disease associates with higher brain amyloid load in normal elderly

PubMed Central

Kamer, Angela R.; Pirraglia, Elizabeth; Tsui, Wai; Rusinek, Henry; Vallabhajosula, Shankar; Mosconi, Lisa; Yi, Li; McHugh, Pauline; Craig, Ronald G.; Svetcov, Spencer; Linker, Ross; Shi, Chen; Glodzik, Lidia; Williams, Schantel; Corby, Patricia; Saxena, Deepak; de Leon, Mony J.

2015-01-01

Background The accumulation of amyloid β plaques (Aβ) is a central feature of Alzheimer’s disease (AD). First reported in animal models, it remains uncertain if peripheral inflammatory/infectious conditions in humans can promote Aβ brain accumulation. Periodontal disease, a common chronic infection, has been previously reported to be associated with AD. Methods Thirty-eight cognitively normal, healthy, community residing elderly (mean age 61; 68% female) were examined in an Alzheimer’s Disease research center and a University-based Dental School. Linear regression models (adjusted for age, ApoE and smoking) were used to test the hypothesis that periodontal disease assessed by clinical attachment loss was associated with brain Aβ load using 11C-PIB PET imaging. Results After adjusting for confounders, clinical attachment loss (≥ 3mm), representing a history of periodontal inflammatory/infectious burden, was associated with increased 11C-PIB uptake in Aβ vulnerable brain regions (p=0.002). Conclusion We show for the first time in humans an association between periodontal disease and brain Aβ load. These data are consistent with prior animal studies showing that peripheral inflammation/infections are sufficient to produce brain Aβ accumulations. PMID:25491073

T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm.

PubMed

Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik; Yakupov, Renat; Speck, Oliver

2017-03-14

We present an ultrahigh resolution in vivo human brain magnetic resonance imaging (MRI) dataset. It consists of T 1 -weighted whole brain anatomical data acquired at 7 Tesla with a nominal isotropic resolution of 250 μm of a single young healthy Caucasian subject and was recorded using prospective motion correction. The raw data amounts to approximately 1.2 TB and was acquired in eight hours total scan time. The resolution of this dataset is far beyond any previously published in vivo structural whole brain dataset. Its potential use is to build an in vivo MR brain atlas. Methods for image reconstruction and image restoration can be improved as the raw data is made available. Pre-processing and segmentation procedures can possibly be enhanced for high magnetic field strength and ultrahigh resolution data. Furthermore, potential resolution induced changes in quantitative data analysis can be assessed, e.g., cortical thickness or volumetric measures, as high quality images with an isotropic resolution of 1 and 0.5 mm of the same subject are included in the repository as well.

A new microcontroller-based human brain hypothermia system.

PubMed

Kapidere, Metin; Ahiska, Raşit; Güler, Inan

2005-10-01

Many studies show that artificial hypothermia of brain in conditions of anesthesia with the rectal temperature lowered down to 33 degrees C produces pronounced prophylactic effect protecting the brain from anoxia. Out of the methods employed now in clinical practice for reducing the oxygen consumption by the cerebral tissue, the most efficacious is craniocerebral hypothermia (CCH). It is finding even more extensive application in cardiovascular surgery, neurosurgery, neurorenimatology and many other fields of medical practice. In this study, a microcontroller-based designed human brain hypothermia system (HBHS) is designed and constructed. The system is intended for cooling and heating the brain. HBHS consists of a thermoelectric hypothermic helmet, a control and a power unit. Helmet temperature is controlled by 8-bit PIC16F877 microcontroller which is programmed using MPLAB editor. Temperature is converted to 10-bit digital and is controlled automatically by the preset values which have been already entered in the microcontroller. Calibration is controlled and the working range is tested. Temperature of helmet is controlled between -5 and +46 degrees C by microcontroller, with the accuracy of +/-0.5 degrees C.

T1-weighted in vivo human whole brain MRI dataset with an ultrahigh isotropic resolution of 250 μm

NASA Astrophysics Data System (ADS)

Lüsebrink, Falk; Sciarra, Alessandro; Mattern, Hendrik; Yakupov, Renat; Speck, Oliver

2017-03-01

We present an ultrahigh resolution in vivo human brain magnetic resonance imaging (MRI) dataset. It consists of T1-weighted whole brain anatomical data acquired at 7 Tesla with a nominal isotropic resolution of 250 μm of a single young healthy Caucasian subject and was recorded using prospective motion correction. The raw data amounts to approximately 1.2 TB and was acquired in eight hours total scan time. The resolution of this dataset is far beyond any previously published in vivo structural whole brain dataset. Its potential use is to build an in vivo MR brain atlas. Methods for image reconstruction and image restoration can be improved as the raw data is made available. Pre-processing and segmentation procedures can possibly be enhanced for high magnetic field strength and ultrahigh resolution data. Furthermore, potential resolution induced changes in quantitative data analysis can be assessed, e.g., cortical thickness or volumetric measures, as high quality images with an isotropic resolution of 1 and 0.5 mm of the same subject are included in the repository as well.

Cerebral cartography and connectomics

PubMed Central

Sporns, Olaf

2015-01-01

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. PMID:25823870

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

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

Ma, Guangkai; Gao, Yaozong; Wu, Guorong

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features canmore » be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI-LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature.« less

Nonlocal atlas-guided multi-channel forest learning for human brain labeling

PubMed Central

Ma, Guangkai; Gao, Yaozong; Wu, Guorong; Wu, Ligang; Shen, Dinggang

2016-01-01

Purpose: It is important for many quantitative brain studies to label meaningful anatomical regions in MR brain images. However, due to high complexity of brain structures and ambiguous boundaries between different anatomical regions, the anatomical labeling of MR brain images is still quite a challenging task. In many existing label fusion methods, appearance information is widely used. However, since local anatomy in the human brain is often complex, the appearance information alone is limited in characterizing each image point, especially for identifying the same anatomical structure across different subjects. Recent progress in computer vision suggests that the context features can be very useful in identifying an object from a complex scene. In light of this, the authors propose a novel learning-based label fusion method by using both low-level appearance features (computed from the target image) and high-level context features (computed from warped atlases or tentative labeling maps of the target image). Methods: In particular, the authors employ a multi-channel random forest to learn the nonlinear relationship between these hybrid features and target labels (i.e., corresponding to certain anatomical structures). Specifically, at each of the iterations, the random forest will output tentative labeling maps of the target image, from which the authors compute spatial label context features and then use in combination with original appearance features of the target image to refine the labeling. Moreover, to accommodate the high inter-subject variations, the authors further extend their learning-based label fusion to a multi-atlas scenario, i.e., they train a random forest for each atlas and then obtain the final labeling result according to the consensus of results from all atlases. Results: The authors have comprehensively evaluated their method on both public LONI_LBPA40 and IXI datasets. To quantitatively evaluate the labeling accuracy, the authors use the dice similarity coefficient to measure the overlap degree. Their method achieves average overlaps of 82.56% on 54 regions of interest (ROIs) and 79.78% on 80 ROIs, respectively, which significantly outperform the baseline method (random forests), with the average overlaps of 72.48% on 54 ROIs and 72.09% on 80 ROIs, respectively. Conclusions: The proposed methods have achieved the highest labeling accuracy, compared to several state-of-the-art methods in the literature. PMID:26843260

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

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.

Effect of Different Movement Speed Modes on Human Action Observation: An EEG Study.

PubMed

Luo, Tian-Jian; Lv, Jitu; Chao, Fei; Zhou, Changle

2018-01-01

Action observation (AO) generates event-related desynchronization (ERD) suppressions in the human brain by activating partial regions of the human mirror neuron system (hMNS). The activation of the hMNS response to AO remains controversial for several reasons. Therefore, this study investigated the activation of the hMNS response to a speed factor of AO by controlling the movement speed modes of a humanoid robot's arm movements. Since hMNS activation is reflected by ERD suppressions, electroencephalography (EEG) with BCI analysis methods for ERD suppressions were used as the recording and analysis modalities. Six healthy individuals were asked to participate in experiments comprising five different conditions. Four incremental-speed AO tasks and a motor imagery (MI) task involving imaging of the same movement were presented to the individuals. Occipital and sensorimotor regions were selected for BCI analyses. The experimental results showed that hMNS activation was higher in the occipital region but more robust in the sensorimotor region. Since the attended information impacts the activations of the hMNS during AO, the pattern of hMNS activations first rises and subsequently falls to a stable level during incremental-speed modes of AO. The discipline curves suggested that a moderate speed within a decent inter-stimulus interval (ISI) range produced the highest hMNS activations. Since a brain computer/machine interface (BCI) builds a path-way between human and computer/mahcine, the discipline curves will help to construct BCIs made by patterns of action observation (AO-BCI). Furthermore, a new method for constructing non-invasive brain machine brain interfaces (BMBIs) with moderate AO-BCI and motor imagery BCI (MI-BCI) was inspired by this paper.

Simultaneous observation of glutamate, gamma-aminobutyric acid, and glutamine in human brain at 4.7 T using localized two-dimensional constant-time correlation spectroscopy.

PubMed

Watanabe, H; Takaya, N; Mitsumori, F

2008-06-01

Localized two-dimensional constant-time correlation spectroscopy (CT-COSY) was used to resolve glutamate (Glu), gamma-aminobutyric acid (GABA), and glutamine (Gln) in the human brain at 4.7 T. In this method, three-dimensional localization was achieved using three radio frequency pulses of the CT-COSY module for slice selection. As this sequence could decouple JHH along the F1 direction, peak resolution of metabolites was improved even on a magnitude-mode display. In experiments on a phantom containing N-acetylaspartate, creatine, Glu, Gln, and GABA with a constant time delay (Tct) of 110 ms, cross peaks of Glu, Gln, and GABA were obtained on a spectrum processed with standard sine-bell windows, which emphasize sine-dependent signals along the t2 direction. In contrast, diagonal peaks of Glu C4H at 2.35 ppm, GABA C2H at 2.28 ppm, and Gln C4H at 2.44 ppm were resolved on a spectrum processed with Gaussian windows, which emphasize cosine-dependent signals along t2. Human brain spectra were obtained from a 27 mL voxel within the parieto-occipital region using a volume transverse electromagnetic (TEM) coil for both transmission and reception. Tct was 110 ms; the total scan time was 30 min. Diagonal peaks of Glu C4H, GABA C2H, and Gln C4H were also resolved on the spectrum processed with Gaussian windows. These results show that the localized two-dimensional CT-COSY method featuring 1H decoupling along the F1 direction could resolve Glu, GABA, and Gln signals in the human brain. Copyright (c) 2008 John Wiley & Sons, Ltd.

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.

Mapping Neurodegenerative Disease Onset and Progression.

PubMed

Seeley, William W

2017-08-01

Brain networks have been of long-standing interest to neurodegeneration researchers, including but not limited to investigators focusing on conventional prion diseases, which are known to propagate along neural pathways. Tools for human network mapping, however, remained inadequate, limiting our understanding of human brain network architecture and preventing clinical research applications. Until recently, neuropathological studies were the only viable approach to mapping disease onset and progression in humans but required large autopsy cohorts and laborious methods for whole-brain sectioning and staining. Despite important advantages, postmortem studies cannot address in vivo, physiological, or longitudinal questions and have limited potential to explore early-stage disease except for the most common disorders. Emerging in vivo network-based neuroimaging strategies have begun to address these issues, providing data that complement the neuropathological tradition. Overall, findings to date highlight several fundamental principles of neurodegenerative disease anatomy and pathogenesis, as well as some enduring mysteries. These principles and mysteries provide a road map for future research. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei

PubMed Central

Pauli, Wolfgang M.; Nili, Amanda N.; Tyszka, J. Michael

2018-01-01

Recent advances in magnetic resonance imaging methods, including data acquisition, pre-processing and analysis, have benefited research on the contributions of subcortical brain nuclei to human cognition and behavior. At the same time, these developments have led to an increasing need for a high-resolution probabilistic in vivo anatomical atlas of subcortical nuclei. In order to address this need, we constructed high spatial resolution, three-dimensional templates, using high-accuracy diffeomorphic registration of T1- and T2- weighted structural images from 168 typical adults between 22 and 35 years old. In these templates, many tissue boundaries are clearly visible, which would otherwise be impossible to delineate in data from individual studies. The resulting delineations of subcortical nuclei complement current histology-based atlases. We further created a companion library of software tools for atlas development, to offer an open and evolving resource for the creation of a crowd-sourced in vivo probabilistic anatomical atlas of the human brain. PMID:29664465

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.

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.

Structure and function of complex brain networks

PubMed Central

Sporns, Olaf

2013-01-01

An increasing number of theoretical and empirical studies approach the function of the human brain from a network perspective. The analysis of brain networks is made feasible by the development of new imaging acquisition methods as well as new tools from graph theory and dynamical systems. This review surveys some of these methodological advances and summarizes recent findings on the architecture of structural and functional brain networks. Studies of the structural connectome reveal several modules or network communities that are interlinked by hub regions mediating communication processes between modules. Recent network analyses have shown that network hubs form a densely linked collective called a “rich club,” centrally positioned for attracting and dispersing signal traffic. In parallel, recordings of resting and task-evoked neural activity have revealed distinct resting-state networks that contribute to functions in distinct cognitive domains. Network methods are increasingly applied in a clinical context, and their promise for elucidating neural substrates of brain and mental disorders is discussed. PMID:24174898

[Stem Cells in the Brain of Mammals and Human: Fundamental and Applied Aspects].

PubMed

Aleksandrova, M A; Marey, M V

2015-01-01

Brain stem cells represent an extremely intriguing phenomenon. The aim of our review is to present an integrity vision of their role in the brain of mammals and humans, and their clinical perspectives. Over last two decades, investigations of biology of the neural stem cells produced significant changes in general knowledge about the processes of development and functioning of the brain. Researches on the cellular and molecular mechanisms of NSC differentiation and behavior led to new understanding of their involvement in learning and memory. In the regenerative medicine, original therapeutic approaches to neurodegenerative brain diseases have been elaborated due to fundamental achievements in this field. They are based on specific regenerative potential of neural stem cells and progenitor cells, which possess the ability to replace dead cells and express crucially significant biologically active factors that are missing in the pathological brain. For the needs of cell substitution therapy in the neural diseases, adequate methods of maintaining stem cells in culture and their differentiation into different types of neurons and glial cells, have been developed currently. The success of modern cellular technologies has significantly expanded the range of cells used for cell therapy. The near future may bring new perspective and distinct progress in brain cell therapy due to optimizing the cells types most promising for medical needs.

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

Mind Reading and Writing: The Future of Neurotechnology.

PubMed

Roelfsema, Pieter R; Denys, Damiaan; Klink, P Christiaan

2018-05-02

Recent advances in neuroscience and technology have made it possible to record from large assemblies of neurons and to decode their activity to extract information. At the same time, available methods to stimulate the brain and influence ongoing processing are also rapidly expanding. These developments pave the way for advanced neurotechnological applications that directly read from, and write to, the human brain. While such technologies are still primarily used in restricted therapeutic contexts, this may change in the future once their performance has improved and they become more widely applicable. Here, we provide an overview of methods to interface with the brain, speculate about potential applications, and discuss important issues associated with a neurotechnologically assisted future. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Robots As Intentional Agents: Using Neuroscientific Methods to Make Robots Appear More Social.

PubMed

Wiese, Eva; Metta, Giorgio; Wykowska, Agnieszka

2017-01-01

Robots are increasingly envisaged as our future cohabitants. However, while considerable progress has been made in recent years in terms of their technological realization, the ability of robots to interact with humans in an intuitive and social way is still quite limited. An important challenge for social robotics is to determine how to design robots that can perceive the user's needs, feelings, and intentions, and adapt to users over a broad range of cognitive abilities. It is conceivable that if robots were able to adequately demonstrate these skills, humans would eventually accept them as social companions. We argue that the best way to achieve this is using a systematic experimental approach based on behavioral and physiological neuroscience methods such as motion/eye-tracking, electroencephalography, or functional near-infrared spectroscopy embedded in interactive human-robot paradigms. This approach requires understanding how humans interact with each other, how they perform tasks together and how they develop feelings of social connection over time, and using these insights to formulate design principles that make social robots attuned to the workings of the human brain. In this review, we put forward the argument that the likelihood of artificial agents being perceived as social companions can be increased by designing them in a way that they are perceived as intentional agents that activate areas in the human brain involved in social-cognitive processing. We first review literature related to social-cognitive processes and mechanisms involved in human-human interactions, and highlight the importance of perceiving others as intentional agents to activate these social brain areas. We then discuss how attribution of intentionality can positively affect human-robot interaction by (a) fostering feelings of social connection, empathy and prosociality, and by (b) enhancing performance on joint human-robot tasks. Lastly, we describe circumstances under which attribution of intentionality to robot agents might be disadvantageous, and discuss challenges associated with designing social robots that are inspired by neuroscientific principles.

Method of euthanasia affects amygdala plasticity in horizontal brain slices from mice.

PubMed

Kulisch, C; Eckers, N; Albrecht, D

2011-10-15

An important consideration in any terminal experiment is the method used for euthanizing animals. Although the prime consideration is that the method is humane, some methods can have a dramatic impact on experimental outcomes. The standard inhalant anesthetic for experiments in brain slices is isoflurane, which replaced the flammable ethers used in the pioneer days of surgery. To our knowledge, there are no data available evaluating the effects of the method of euthanasia on plasticity changes in brain slices. Here, we compare the magnitude of long-term potentiation (LTP) and long-term depression (LTD) in the lateral nucleus of the amygdala (LA) after euthanasia following either ether or isoflurane anesthesia, as well as in mice decapitated without anesthesia. We found no differences in input-output curves using different methods of euthanasia. The LTP magnitude did not differ between ether and normal isoflurane anesthesia. After deep isoflurane anesthesia LTP induced by high frequency stimulation of cortical or intranuclear afferents was significantly reduced compared to ether anesthesia. In contrast to ether anesthesia and decapitation without anesthesia, the low frequency stimulation of cortical afferents induced a reliable LA-LTD after deep isoflurane anesthesia. Low frequency stimulation of intranuclear afferents only caused LTD after pretreatment with ether anesthesia. The results demonstrate that the method of euthanasia can influence brain plasticity for hours at least in the interface chamber. Therefore, the method of euthanasia is an important consideration when brain plasticity will be evaluated. Copyright © 2011 Elsevier B.V. All rights reserved.

Weight Perturbation Alters Leptin Signal Transduction in a Region-Specific Manner throughout the Brain

PubMed Central

Morabito, Michael V.; Ravussin, Yann; Mueller, Bridget R.; Skowronski, Alicja A.; Watanabe, Kazuhisa; Foo, Kylie S.; Lee, Samuel X.; Lehmann, Anders; Hjorth, Stephan; Zeltser, Lori M.; LeDuc, Charles A.; Leibel, Rudolph L.

2017-01-01

Diet-induced obesity (DIO) resulting from consumption of a high fat diet (HFD) attenuates normal neuronal responses to leptin and may contribute to the metabolic defense of an acquired higher body weight in humans; the molecular bases for the persistence of this defense are unknown. We measured the responses of 23 brain regions to exogenous leptin in 4 different groups of weight- and/or diet-perturbed mice. Responses to leptin were assessed by quantifying pSTAT3 levels in brain nuclei 30 minutes following 3 mg/kg intraperitoneal leptin. HFD attenuated leptin sensing throughout the brain, but weight loss did not restore central leptin signaling to control levels in several brain regions important in energy homeostasis, including the arcuate and dorsomedial hypothalamic nuclei. Effects of diet on leptin signaling varied by brain region, with results dependent on the method of weight loss (restriction of calories of HFD, ad lib intake of standard mouse chow). High fat diet attenuates leptin signaling throughout the brain, but some brain regions maintain their ability to sense leptin. Weight loss restores leptin sensing to some degree in most (but not all) brain regions, while other brain regions display hypersensitivity to leptin following weight loss. Normal leptin sensing was restored in several brain regions, with the pattern of restoration dependent on the method of weight loss. PMID:28107353

Individualized Functional Parcellation of the Human Amygdala Using a Semi-supervised Clustering Method: A 7T Resting State fMRI Study.

PubMed

Zhang, Xianchang; Cheng, Hewei; Zuo, Zhentao; Zhou, Ke; Cong, Fei; Wang, Bo; Zhuo, Yan; Chen, Lin; Xue, Rong; Fan, Yong

2018-01-01

The amygdala plays an important role in emotional functions and its dysfunction is considered to be associated with multiple psychiatric disorders in humans. Cytoarchitectonic mapping has demonstrated that the human amygdala complex comprises several subregions. However, it's difficult to delineate boundaries of these subregions in vivo even if using state of the art high resolution structural MRI. Previous attempts to parcellate this small structure using unsupervised clustering methods based on resting state fMRI data suffered from the low spatial resolution of typical fMRI data, and it remains challenging for the unsupervised methods to define subregions of the amygdala in vivo . In this study, we developed a novel brain parcellation method to segment the human amygdala into spatially contiguous subregions based on 7T high resolution fMRI data. The parcellation was implemented using a semi-supervised spectral clustering (SSC) algorithm at an individual subject level. Under guidance of prior information derived from the Julich cytoarchitectonic atlas, our method clustered voxels of the amygdala into subregions according to similarity measures of their functional signals. As a result, three distinct amygdala subregions can be obtained in each hemisphere for every individual subject. Compared with the cytoarchitectonic atlas, our method achieved better performance in terms of subregional functional homogeneity. Validation experiments have also demonstrated that the amygdala subregions obtained by our method have distinctive, lateralized functional connectivity (FC) patterns. Our study has demonstrated that the semi-supervised brain parcellation method is a powerful tool for exploring amygdala subregional functions.

Anti-correlated cortical networks of intrinsic connectivity in the rat brain.

PubMed

Schwarz, Adam J; Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline "DMN-like" network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans.

Anti-Correlated Cortical Networks of Intrinsic Connectivity in the Rat Brain

PubMed Central

Gass, Natalia; Sartorius, Alexander; Risterucci, Celine; Spedding, Michael; Schenker, Esther; Meyer-Lindenberg, Andreas; Weber-Fahr, Wolfgang

2013-01-01

Abstract In humans, resting-state blood oxygen level-dependent (BOLD) signals in the default mode network (DMN) are temporally anti-correlated with those from a lateral cortical network involving the frontal eye fields, secondary somatosensory and posterior insular cortices. Here, we demonstrate the existence of an analogous lateral cortical network in the rat brain, extending laterally from anterior secondary sensorimotor regions to the insular cortex and exhibiting low-frequency BOLD fluctuations that are temporally anti-correlated with a midline “DMN-like” network comprising posterior/anterior cingulate and prefrontal cortices. The primary nexus for this anti-correlation relationship was the anterior secondary motor cortex, close to regions that have been identified with frontal eye fields in the rat brain. The anti-correlation relationship was corroborated after global signal removal, underscoring this finding as a robust property of the functional connectivity signature in the rat brain. These anti-correlated networks demonstrate strong anatomical homology to networks identified in human and monkey connectivity studies, extend the known preserved functional connectivity relationships between rodent and primates, and support the use of resting-state functional magnetic resonance imaging as a translational imaging method between rat models and humans. PMID:23919836

Predicting novel histopathological microlesions in human epileptic brain through transcriptional clustering.

PubMed

Dachet, Fabien; Bagla, Shruti; Keren-Aviram, Gal; Morton, Andrew; Balan, Karina; Saadat, Laleh; Valyi-Nagy, Tibor; Kupsky, William; Song, Fei; Dratz, Edward; Loeb, Jeffrey A

2015-02-01

Although epilepsy is associated with a variety of abnormalities, exactly why some brain regions produce seizures and others do not is not known. We developed a method to identify cellular changes in human epileptic neocortex using transcriptional clustering. A paired analysis of high and low spiking tissues recorded in vivo from 15 patients predicted 11 cell-specific changes together with their 'cellular interactome'. These predictions were validated histologically revealing millimetre-sized 'microlesions' together with a global increase in vascularity and microglia. Microlesions were easily identified in deeper cortical layers using the neuronal marker NeuN, showed a marked reduction in neuronal processes, and were associated with nearby activation of MAPK/CREB signalling, a marker of epileptic activity, in superficial layers. Microlesions constitute a common, undiscovered layer-specific abnormality of neuronal connectivity in human neocortex that may be responsible for many 'non-lesional' forms of epilepsy. The transcriptional clustering approach used here could be applied more broadly to predict cellular differences in other brain and complex tissue disorders. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The macro-structural variability of the human neocortex.

PubMed

Kruggel, Frithjof

2018-05-15

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure. Copyright © 2018 Elsevier Inc. All rights reserved.

Optical coherence tomography visualizes neurons in human entorhinal cortex

PubMed Central

Magnain, Caroline; Augustinack, Jean C.; Konukoglu, Ender; Frosch, Matthew P.; Sakadžić, Sava; Varjabedian, Ani; Garcia, Nathalie; Wedeen, Van J.; Boas, David A.; Fischl, Bruce

2015-01-01

Abstract. The cytoarchitecture of the human brain is of great interest in diverse fields: neuroanatomy, neurology, neuroscience, and neuropathology. Traditional histology is a method that has been historically used to assess cell and fiber content in the ex vivo human brain. However, this technique suffers from significant distortions. We used a previously demonstrated optical coherence microscopy technique to image individual neurons in several square millimeters of en-face tissue blocks from layer II of the human entorhinal cortex, over 50  μm in depth. The same slices were then sectioned and stained for Nissl substance. We registered the optical coherence tomography (OCT) images with the corresponding Nissl stained slices using a nonlinear transformation. The neurons were then segmented in both images and we quantified the overlap. We show that OCT images contain information about neurons that is comparable to what can be obtained from Nissl staining, and thus can be used to assess the cytoarchitecture of the ex vivo human brain with minimal distortion. With the future integration of a vibratome into the OCT imaging rig, this technique can be scaled up to obtain undistorted volumetric data of centimeter cube tissue blocks in the near term, and entire human hemispheres in the future. PMID:25741528

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Automatic cortical thickness analysis on rodent brain

NASA Astrophysics Data System (ADS)

Lee, Joohwi; Ehlers, Cindy; Crews, Fulton; Niethammer, Marc; Budin, Francois; Paniagua, Beatriz; Sulik, Kathy; Johns, Josephine; Styner, Martin; Oguz, Ipek

2011-03-01

Localized difference in the cortex is one of the most useful morphometric traits in human and animal brain studies. There are many tools and methods already developed to automatically measure and analyze cortical thickness for the human brain. However, these tools cannot be directly applied to rodent brains due to the different scales; even adult rodent brains are 50 to 100 times smaller than humans. This paper describes an algorithm for automatically measuring the cortical thickness of mouse and rat brains. The algorithm consists of three steps: segmentation, thickness measurement, and statistical analysis among experimental groups. The segmentation step provides the neocortex separation from other brain structures and thus is a preprocessing step for the thickness measurement. In the thickness measurement step, the thickness is computed by solving a Laplacian PDE and a transport equation. The Laplacian PDE first creates streamlines as an analogy of cortical columns; the transport equation computes the length of the streamlines. The result is stored as a thickness map over the neocortex surface. For the statistical analysis, it is important to sample thickness at corresponding points. This is achieved by the particle correspondence algorithm which minimizes entropy between dynamically moving sample points called particles. Since the computational cost of the correspondence algorithm may limit the number of corresponding points, we use thin-plate spline based interpolation to increase the number of corresponding sample points. As a driving application, we measured the thickness difference to assess the effects of adolescent intermittent ethanol exposure that persist into adulthood and performed t-test between the control and exposed rat groups. We found significantly differing regions in both hemispheres.

Comprehensive comparative analysis of 5'-end RNA-sequencing methods.

PubMed

Adiconis, Xian; Haber, Adam L; Simmons, Sean K; Levy Moonshine, Ami; Ji, Zhe; Busby, Michele A; Shi, Xi; Jacques, Justin; Lancaster, Madeline A; Pan, Jen Q; Regev, Aviv; Levin, Joshua Z

2018-06-04

Specialized RNA-seq methods are required to identify the 5' ends of transcripts, which are critical for studies of gene regulation, but these methods have not been systematically benchmarked. We directly compared six such methods, including the performance of five methods on a single human cellular RNA sample and a new spike-in RNA assay that helps circumvent challenges resulting from uncertainties in annotation and RNA processing. We found that the 'cap analysis of gene expression' (CAGE) method performed best for mRNA and that most of its unannotated peaks were supported by evidence from other genomic methods. We applied CAGE to eight brain-related samples and determined sample-specific transcription start site (TSS) usage, as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

A mouse model of human repetitive mild traumatic brain injury

PubMed Central

Kane, Michael J.; Pérez, Mariana Angoa; Briggs, Denise I.; Viano, David C.; Kreipke, Christian W.; Kuhn, Donald M.

2011-01-01

A novel method for the study of repetitive mild traumatic brain injury (rmTBI) that models the most common form of head injury in humans is presented. Existing animal models of TBI impart focal, severe damage unlike that seen in repeated and mild concussive injuries, and few are configured for repetitive application. Our model is a modification of the Marmarou weight drop method and allows repeated head impacts to lightly anesthetized mice. A key facet of this method is the delivery of an impact to the cranium of an unrestrained subject allowing rapid acceleration of the free-moving head and torso, an essential characteristic known to be important for concussive injury in humans, and a factor that is missing from existing animal models of TBI. Our method does not require scalp incision, emplacement of protective skull helmets or surgery and the procedure can be completed in 1-2 minutes. Mice spontaneously recover the righting reflex and show no evidence of seizures, paralysis or impaired behavior. Skull fractures and intracranial bleeding are very rare. Minor deficits in motor coordination and locomotor hyperactivity recover over time. Histological analyses reveal mild astrocytic reactivity (increased expression of GFAP) and increased phospho-tau but a lack of blood-brain-barrier disruption, edema and microglial activation. This new animal model is simple and cost-effective and will facilitate characterization of the neurobiological and behavioral consequences of rmTBI. It is also ideal for high throughput screening of potential new therapies for mild concussive injuries as experienced by athletes and military personnel. PMID:21930157

Quantitative validation of a nonlinear histology-MRI coregistration method using Generalized Q-sampling Imaging in complex human cortical white matter

PubMed Central

Gangolli, Mihika; Holleran, Laurena; Kim, Joong Hee; Stein, Thor D.; Alvarez, Victor; McKee, Ann C.; Brody, David L.

2017-01-01

Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250 × 250 × 500 micron spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r = 0.94 for the primary fiber direction and r = 0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing between architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter. PMID:28365421

From "Where" to "What": Distributed Representations of Brand Associations in the Human Brain.

PubMed

Chen, Yu-Ping; Nelson, Leif D; Hsu, Ming

2015-08-01

Considerable attention has been given to the notion that there exists a set of human-like characteristics associated with brands, referred to as brand personality. Here we combine newly available machine learning techniques with functional neuroimaging data to characterize the set of processes that give rise to these associations. We show that brand personality traits can be captured by the weighted activity across a widely distributed set of brain regions previously implicated in reasoning, imagery, and affective processing. That is, as opposed to being constructed via reflective processes, brand personality traits appear to exist a priori inside the minds of consumers, such that we were able to predict what brand a person is thinking about based solely on the relationship between brand personality associations and brain activity. These findings represent an important advance in the application of neuroscientific methods to consumer research, moving from work focused on cataloguing brain regions associated with marketing stimuli to testing and refining mental constructs central to theories of consumer behavior.

Integration of fMRI, NIROT and ERP for studies of human brain function.

PubMed

Gore, John C; Horovitz, Silvina G; Cannistraci, Christopher J; Skudlarski, Pavel

2006-05-01

Different methods of assessing human brain function possess specific advantages and disadvantages compared to others, but it is believed that combining different approaches will provide greater information than can be obtained from each alone. For example, functional magnetic resonance imaging (fMRI) has good spatial resolution but poor temporal resolution, whereas the converse is true for electrophysiological recordings (event-related potentials or ERPs). In this review of recent work, we highlight a novel approach to combining these modalities in a manner designed to increase information on the origins and locations of the generators of specific ERPs and the relationship between fMRI and ERP signals. Near infrared imaging techniques have also been studied as alternatives to fMRI and can be readily integrated with simultaneous electrophysiological recordings. Each of these modalities may in principle be also used in so-called steady-state acquisitions in which the correlational structure of signals from the brain may be analyzed to provide new insights into brain function.

From “Where” to “What”: Distributed Representations of Brand Associations in the Human Brain

PubMed Central

Chen, Yu-Ping; Nelson, Leif D.; Hsu, Ming

2015-01-01

Considerable attention has been given to the notion that there exists a set of human-like characteristics associated with brands, referred to as brand personality. Here we combine newly available machine learning techniques with functional neuroimaging data to characterize the set of processes that give rise to these associations. We show that brand personality traits can be captured by the weighted activity across a widely distributed set of brain regions previously implicated in reasoning, imagery, and affective processing. That is, as opposed to being constructed via reflective processes, brand personality traits appear to exist a priori inside the minds of consumers, such that we were able to predict what brand a person is thinking about based solely on the relationship between brand personality associations and brain activity. These findings represent an important advance in the application of neuroscientific methods to consumer research, moving from work focused on cataloguing brain regions associated with marketing stimuli to testing and refining mental constructs central to theories of consumer behavior. PMID:27065490

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

Microglial dystrophy in the aged and Alzheimer's disease brain is associated with ferritin immunoreactivity.

PubMed

Lopes, Kryslaine O; Sparks, D Larry; Streit, Wolfgang J

2008-08-01

Degeneration of microglial cells may be important for understanding the pathogenesis of aging-related neurodegeneration and neurodegenerative diseases. In this study, we analyzed the morphological characteristics of microglial cells in the nondemented and Alzheimer's disease (AD) human brain using ferritin immunohistochemistry. The central hypothesis was that expression of the iron storage protein ferritin increases the susceptibility of microglia to degeneration, particularly in the aged brain since senescent microglia might become less efficient in maintaining iron homeostasis and free iron can promote oxidative damage. In a primary set of 24 subjects (age range 34-97 years) examined, microglial cells immunoreactive for ferritin were found to constitute a subpopulation of the larger microglial pool labeled with an antibody for HLA-DR antigens. The majority of these ferritin-positive microglia exhibited aberrant morphological (dystrophic) changes in the aged and particularly in the AD brain. No spatial correlation was found between ferritin-positive dystrophic microglia and senile plaques in AD tissues. Analysis of a secondary set of human postmortem brain tissues with a wide range of postmortem intervals (PMI, average 10.94 +/- 5.69 h) showed that the occurrence of microglial dystrophy was independent of PMI and consequently not a product of tissue autolysis. Collectively, these results suggest that microglial involvement in iron storage and metabolism contributes to their degeneration, possibly through increased exposure of the cells to oxidative stress. We conclude that ferritin immunohistochemistry may be a useful method for detecting degenerating microglia in the human brain. (c) 2008 Wiley-Liss, Inc.

Atlas-guided volumetric diffuse optical tomography enhanced by generalized linear model analysis to image risk decision-making responses in young adults.

PubMed

Lin, Zi-Jing; Li, Lin; Cazzell, Mary; Liu, Hanli

2014-08-01

Diffuse optical tomography (DOT) is a variant of functional near infrared spectroscopy and has the capability of mapping or reconstructing three dimensional (3D) hemodynamic changes due to brain activity. Common methods used in DOT image analysis to define brain activation have limitations because the selection of activation period is relatively subjective. General linear model (GLM)-based analysis can overcome this limitation. In this study, we combine the atlas-guided 3D DOT image reconstruction with GLM-based analysis (i.e., voxel-wise GLM analysis) to investigate the brain activity that is associated with risk decision-making processes. Risk decision-making is an important cognitive process and thus is an essential topic in the field of neuroscience. The Balloon Analog Risk Task (BART) is a valid experimental model and has been commonly used to assess human risk-taking actions and tendencies while facing risks. We have used the BART paradigm with a blocked design to investigate brain activations in the prefrontal and frontal cortical areas during decision-making from 37 human participants (22 males and 15 females). Voxel-wise GLM analysis was performed after a human brain atlas template and a depth compensation algorithm were combined to form atlas-guided DOT images. In this work, we wish to demonstrate the excellence of using voxel-wise GLM analysis with DOT to image and study cognitive functions in response to risk decision-making. Results have shown significant hemodynamic changes in the dorsal lateral prefrontal cortex (DLPFC) during the active-choice mode and a different activation pattern between genders; these findings correlate well with published literature in functional magnetic resonance imaging (fMRI) and fNIRS studies. Copyright © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Kinetic Modeling of PET Data Without Blood Sampling

NASA Astrophysics Data System (ADS)

Bentourkia, M.

2005-06-01

In positron emission tomography (PET) imaging, application of kinetic modeling always requires an input curve (IC) together with the PET data. The IC can be obtained by means of external blood sampling or, in the case of cardiac studies, by means of a region-of-interest (ROI) drawn on the blood pool. It is, however, very unsuitable to withdraw and to analyze blood samples, and in small animals, these operations become difficult, while ICs determined from ROIs are generally contaminated by emissions from neighboring sites, or they are underestimated because of partial volume effect. In this paper, we report a new method to extract kinetic parameters from dynamic PET studies without a priori knowledge of the IC. The method is applied in human brain data measured with fluorodeoxyglucose (FDG) human-brain and in cardiac-rat perfusion studies with /sup 13/N-ammonia and /sup 11/C-acetate. The tissue blood volume (TBV), usually fitted together with the rate constants, is extracted simultaneously with the tissue time activity curves for cardiac studies, while for brain gray matter, TBV is known to be about 4% to 7%. The shape of IC is obtained by means of factor analysis from an ROI drawn around a cardiac tissue or a brain artery. The results show a good correlation (p<0.05) between the cerebral metabolic rate of glucose, myocardial blood flow, and oxygen consumption obtained with the new method in comparison to the usual method. In conclusion, it is possible to apply kinetic modeling without any blood sampling, which significantly simplifies PET acquisition and data analysis.

Unfolding dimension and the search for functional markers in the human electroencephalogram

NASA Astrophysics Data System (ADS)

Dünki, Rudolf M.; Schmid, Gary Bruno

1998-02-01

A biparametric approach to dimensional analysis in terms of a so-called ``unfolding dimension'' is introduced to explore the extent to which the human EEG can be described by stable features characteristic of an individual despite the well-known problems of intraindividual variability. Our analysis comprises an EEG data set recorded from healthy individuals over a time span of 5 years. The outcome is shown to be comparable to advanced linear methods of spectral analysis with regard to intraindividual specificity and stability over time. Such linear methods have not yet proven to be specific to the EEG of different brain states. Thus we have also investigated the specificity of our biparametric approach by comparing the mental states schizophrenic psychosis and remission, i.e., illness versus full recovery. A difference between EEG in psychosis and remission became apparent within recordings taken at rest with eyes closed and no stimulated or requested mental activity. Hence our approach distinguishes these functional brain states even in the absence of an active or intentional stimulus. This sheds a different light upon theories of schizophrenia as an information-processing disturbance of the brain.

Knowledge about the Brain for Parents, Students, and Teachers: The Keys to Removing the Invisible Roadblocks to Learning and High Self-Esteem for All Students.

ERIC Educational Resources Information Center

Beamish, Claude R.

This paper presents basic information about the brain and how learning takes place, considers causes of differing human temperaments as explained by principles of Jungian psychology, reports on research on the causes of low achievement, and suggests a method to correct many educational problems. Principles of developmental neurology and right/left…

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.

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

Establishment of a new conditionally immortalized cell line from human brain microvascular endothelial cells: a promising tool for human blood-brain barrier studies.

PubMed

Kamiichi, Atsuko; Furihata, Tomomi; Kishida, Satoshi; Ohta, Yuki; Saito, Kosuke; Kawamatsu, Shinya; Chiba, Kan

2012-12-07

The blood-brain barrier (BBB) is formed by brain microvascular endothelial cells (BMEC) working together with astrocytes and pericytes, in which tight junctions and various transporters strictly regulate the penetration of diverse compounds into the brain. Clarification of the molecular machinery that provides such regulation using in vitro BBB models has provided important insights into the roles of the BBB in central nervous system (CNS) disorders and CNS drug development. In this study, we succeeded in establishing a new cell line, hereinafter referred to as human BMEC/conditionally immortalized, clone β (HBMEC/ciβ), as part of our ongoing efforts to develop an in vitro human BBB model. Our results showed that HBMEC/ciβ proliferated well. Furthermore, we found that HBMEC/ciβ exhibited the barrier property of restricting small molecule intercellular penetration and possessed effective efflux transporter functions, both of which are essential to a functioning BBB. Because higher temperatures are known to terminate immortalization signals, we specifically examined the effects of higher temperatures on the HBMEC/ciβ differentiation status. The results showed that higher temperatures stimulated HBMEC/ciβ differentiation, marked by morphological alteration and increases in several mRNA levels. To summarize, our data indicates that the newly established HBMEC/ciβ offers a promising tool for use in the development of a practical in vitro human BBB model that could make significant contributions toward understanding the molecular biology of CNS disorders, as well as to CNS drug development. It is also believed that the development of a specific culture method for HBMEC/ciβ will add significant value to the HBMEC/ciβ-based BBB model. Copyright © 2012 Elsevier B.V. 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.

Functional brain imaging and bioacoustics in the Bottlenose dolphins, Tursiops truncatus

NASA Astrophysics Data System (ADS)

Ridgway, Sam; Finneran, James; Carder, Donald; van Bonn, William; Smith, Cynthia; Houser, Dorian; Mattrey, Robert; Hoh, Carl

2003-10-01

The dolphin brain is the central processing computer for a complex and effective underwater echolocation and communication system. Until now, it has not been possible to study or diagnose disorders of the dolphin brain employing modern functional imaging methods like those used in human medicine. Our most recent studies employ established methods such as behavioral tasks, physiological observations, and computed tomography (CT) and, for the first time, single photon emission computed tomography (SPECT), and positron emission tomography (PET). Trained dolphins slide out of their enclosure on to a mat and are transported by trainers and veterinarians to the laboratory for injection of a ligand. Following ligand injection, brief experiments include trained vocal responses to acoustic, visual, or tactile stimuli. We have used the ligand technetium (Tc-99m) biscisate (Neurolite) to image circulatory flow by SPECT. Fluro-deoxy-d-glucose (18-F-FDG) has been employed to image brain metabolism with PET. Veterinarians carefully monitored dolphins during and after the procedure. Through these methods, we have demonstrated that functional imaging can be employed safely and productively with dolphins to obtain valuable information on brain structure and function for medical and research purposes. Hemispheric differences and variations in flow and metabolism in different brain areas will be shown.

Method of treating depression

DOEpatents

Henn, Fritz [East Patchogue, NY

2012-01-24

Methods for treatment of depression-related mood disorders in mammals, particularly humans are disclosed. The methods of the invention include administration of compounds capable of enhancing glutamate transporter activity in the brain of mammals suffering from depression. ATP-sensitive K.sup.+ channel openers and .beta.-lactam antibiotics are used to enhance glutamate transport and to treat depression-related mood disorders and depressive symptoms.

Method of treating depression

DOEpatents

Henn, Fritz

2013-04-09

Methods for treatment of depression-related mood disorders in mammals, particularly humans are disclosed. The methods of the invention include administration of compounds capable of enhancing glutamate transporter activity in the brain of mammals suffering from depression. ATP-sensitive K.sup.+ channel openers and .beta.-lactam antibiotics are used to enhance glutamate transport and to treat depression-related mood disorders and depressive symptoms.

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.

Effect of x-radiation to brain on cerebral glucose utilization in the rat.

PubMed

D'Aquino, S; Cicciarello, R; D'Avella, D; Mesiti, M; Albiero, F; Princi, P; Gagliardi, M E; Russi, E; D'Aquino, A

1990-01-01

We assessed, by means of the [14C]-2-deoxy-D-glucose autoradiography method, the effect of whole-brain x-radiation on local cerebral glucose utilization in the rat brain. Animals were exposed to conventional fractionation (200 +/- cGy/day given 5 days a week) to a total dose of 4000 cGy. Metabolic experiments were made 2 weeks after completion of the radiation exposure. In comparison with control and sham-irradiated animals, cerebral metabolic activity was diffusely decreased following irradiation. Statistically significant decreases in metabolic activity were observed in 13 of 27 brain regions studied. In general, brain areas with the highest basal metabolic rates showed the greatest percentage drop of glucose utilization. Post-irradiation metabolic alterations possibly provide an explanation for the syndrome of early delayed deterioration observed in humans after whole-brain radiotherapy.

Electrophysiological and hemodynamic mismatch responses in rats listening to human speech syllables.

PubMed

Mahmoudzadeh, Mahdi; Dehaene-Lambertz, Ghislaine; Wallois, Fabrice

2017-01-01

Speech is a complex auditory stimulus which is processed according to several time-scales. Whereas consonant discrimination is required to resolve rapid acoustic events, voice perception relies on slower cues. Humans, right from preterm ages, are particularly efficient to encode temporal cues. To compare the capacities of preterms to those observed in other mammals, we tested anesthetized adult rats by using exactly the same paradigm as that used in preterm neonates. We simultaneously recorded neural (using ECoG) and hemodynamic responses (using fNIRS) to series of human speech syllables and investigated the brain response to a change of consonant (ba vs. ga) and to a change of voice (male vs. female). Both methods revealed concordant results, although ECoG measures were more sensitive than fNIRS. Responses to syllables were bilateral, but with marked right-hemispheric lateralization. Responses to voice changes were observed with both methods, while only ECoG was sensitive to consonant changes. These results suggest that rats more effectively processed the speech envelope than fine temporal cues in contrast with human preterm neonates, in whom the opposite effects were observed. Cross-species comparisons constitute a very valuable tool to define the singularities of the human brain and species-specific bias that may help human infants to learn their native language.

Glycoblotting method allows for rapid and efficient glycome profiling of human Alzheimer's disease brain, serum and cerebrospinal fluid towards potential biomarker discovery.

PubMed

Gizaw, Solomon T; Ohashi, Tetsu; Tanaka, Masakazu; Hinou, Hiroshi; Nishimura, Shin-Ichiro

2016-08-01

Understanding of the significance of posttranslational glycosylation in Alzheimer's disease (AD) is of growing importance for the investigation of the pathogenesis of AD as well as discovery research of the disease-specific serum biomarkers. We designed a standard protocol for the glycoblotting combined with MALDI-TOFMS to perform rapid and quantitative profiling of the glycan parts of glycoproteins (N-glycans) and glycosphingolipids (GSLs) using human AD's post-mortem samples such as brain tissues (dissected cerebral cortices such as frontal, parietal, occipital, and temporal domains), serum and cerebrospinal fluid (CSF). The structural profiles of the major N-glycans released from glycoproteins and the total expression levels of the glycans were found to be mostly similar between the brain tissues of the AD patients and those of the normal control group. In contrast, the expression levels of the serum and CSF protein N-glycans such as bisect-type and multiply branched glycoforms were increased significantly in AD patient group. In addition, the levels of some gangliosides such as GM1, GM2 and GM3 appeared to alter in the AD patient brain and serum samples when compared with the normal control groups. Alteration of the expression levels of major N- and GSL-glycans in human brain tissues, serum and CSF of AD patients can be monitored quantitatively by means of the glycoblotting-based standard protocols. The changes in the expression levels of the glycans derived from the human post-mortem samples uncovered by the standardized glycoblotting method provides potential serum biomarkers in central nervous system disorders and can contribute to the insight into the molecular mechanisms in the pathogenesis of neurodegenerative diseases and future drug discovery. Most importantly, the present preliminary trials using human post-mortem samples of AD patients suggest that large-scale serum glycomics cohort by means of various-types of human AD patients as well as the normal control sera can facilitate the discovery research of highly sensitive and reliable serum biomarkers for an early diagnosis of AD. This article is part of a Special Issue entitled "Glycans in personalised medicine" Guest Editor: Professor Gordan Lauc. Copyright © 2016 Elsevier B.V. All rights reserved.

Convergence of Cortical, Thalamocortical, and Callosal Pathways during Human Fetal Development Revealed by Diffusion MRI Tractography.

PubMed

Wang, Rongpin; Wilkinson, Molly; Kane, Tara; Takahashi, Emi

2017-01-01

There has been evidence that during brain development, emerging thalamocortical (TC) and corticothalamic (CT) pathways converge in some brain regions and follow each other's trajectories to their final destinations. Corpus callosal (CC) pathways also emerge at a similar developmental stage, and are known to converge with TC pathways in specific cortical regions in mature brains. Given the functional relationships between TC and CC pathways, anatomical convergence of the two pathways are likely important for their functional integration. However, it is unknown (1) where TC and CT subcortically converge in the human brain, and (2) where TC and CC converge in the cortex of the human brain, due to the limitations of non-invasive methods. The goals of this study were to describe the spatio-temporal relationships in the development of the TC/CT and CC pathways in the human brain, using high-angular resolution diffusion MR imaging (HARDI) tractography. Emerging cortical, TC and CC pathways were identified in postmortem fetal brains ranging from 17 gestational weeks (GW) to 30 GW, as well as in vivo 34-40 GW newborns. Some pathways from the thalami were found to be converged with pathways from the cerebral cortex as early as 17 GW. Such convergence was observed mainly in anterior and middle regions of the brain until 21 GW. At 22 GW and onwards, posterior pathways from the thalami also converged with cortical pathways. Many CC pathways reached the full length up to the cortical surface as early as 17 GW, while pathways linked to thalami (not only TC axons but also including pathways linked to thalamic neuronal migration) reached the cortical surface at and after 20 GW. These results suggest that CC pathways developed earlier than the TC pathways. The two pathways were widespread at early stages, but by 40 GW they condensed and formed groups of pathways that projected to specific regions of the cortex and overlapped in some brain regions. These results suggest that HARDI tractography has the potential to identify developing TC/CT and CC pathways with the timing and location of their convergence in fetal stages persisting in postnatal development.

Convergence of Cortical, Thalamocortical, and Callosal Pathways during Human Fetal Development Revealed by Diffusion MRI Tractography

PubMed Central

Wang, Rongpin; Wilkinson, Molly; Kane, Tara; Takahashi, Emi

2017-01-01

There has been evidence that during brain development, emerging thalamocortical (TC) and corticothalamic (CT) pathways converge in some brain regions and follow each other's trajectories to their final destinations. Corpus callosal (CC) pathways also emerge at a similar developmental stage, and are known to converge with TC pathways in specific cortical regions in mature brains. Given the functional relationships between TC and CC pathways, anatomical convergence of the two pathways are likely important for their functional integration. However, it is unknown (1) where TC and CT subcortically converge in the human brain, and (2) where TC and CC converge in the cortex of the human brain, due to the limitations of non-invasive methods. The goals of this study were to describe the spatio-temporal relationships in the development of the TC/CT and CC pathways in the human brain, using high-angular resolution diffusion MR imaging (HARDI) tractography. Emerging cortical, TC and CC pathways were identified in postmortem fetal brains ranging from 17 gestational weeks (GW) to 30 GW, as well as in vivo 34–40 GW newborns. Some pathways from the thalami were found to be converged with pathways from the cerebral cortex as early as 17 GW. Such convergence was observed mainly in anterior and middle regions of the brain until 21 GW. At 22 GW and onwards, posterior pathways from the thalami also converged with cortical pathways. Many CC pathways reached the full length up to the cortical surface as early as 17 GW, while pathways linked to thalami (not only TC axons but also including pathways linked to thalamic neuronal migration) reached the cortical surface at and after 20 GW. These results suggest that CC pathways developed earlier than the TC pathways. The two pathways were widespread at early stages, but by 40 GW they condensed and formed groups of pathways that projected to specific regions of the cortex and overlapped in some brain regions. These results suggest that HARDI tractography has the potential to identify developing TC/CT and CC pathways with the timing and location of their convergence in fetal stages persisting in postnatal development. PMID:29163000

Robust and fast characterization of OCT-based optical attenuation using a novel frequency-domain algorithm for brain cancer detection

NASA Astrophysics Data System (ADS)

Yuan, Wu; Kut, Carmen; Liang, Wenxuan; Li, Xingde

2017-03-01

Cancer is known to alter the local optical properties of tissues. The detection of OCT-based optical attenuation provides a quantitative method to efficiently differentiate cancer from non-cancer tissues. In particular, the intraoperative use of quantitative OCT is able to provide a direct visual guidance in real time for accurate identification of cancer tissues, especially these without any obvious structural layers, such as brain cancer. However, current methods are suboptimal in providing high-speed and accurate OCT attenuation mapping for intraoperative brain cancer detection. In this paper, we report a novel frequency-domain (FD) algorithm to enable robust and fast characterization of optical attenuation as derived from OCT intensity images. The performance of this FD algorithm was compared with traditional fitting methods by analyzing datasets containing images from freshly resected human brain cancer and from a silica phantom acquired by a 1310 nm swept-source OCT (SS-OCT) system. With graphics processing unit (GPU)-based CUDA C/C++ implementation, this new attenuation mapping algorithm can offer robust and accurate quantitative interpretation of OCT images in real time during brain surgery.

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.

On the electrophysiology of aesthetic processing.

PubMed

Jacobsen, Thomas

2013-01-01

One important method that can be applied for gaining an understanding of the underpinning of aesthetics in the brain is that of electrophysiology. Cognitive electrophysiology, in particular, allows the identification of components in a mental processing architecture. The present chapter reviews findings in the neurocognitive psychology of aesthetics, or neuroaesthetics, that have been obtained with the method of event-related brain potentials, as derived from the human electroencephalogram. The cognitive-perceptual bases as well as affective substages of aesthetic processing have been investigated and those are described here. The event-related potential method allows for the identification of mental processing modes in cognitive and aesthetic processing. It also provides an assessment of the mental chronometry of cognitive and affective stages in aesthetic appreciation. As the work described here shows, distinct processes in the brain are engaged in aesthetic judgments. © 2013 Elsevier B.V. All rights reserved.

Foetal Testosterone, Social Relationships, and Restricted Interests in Children

ERIC Educational Resources Information Center

Knickmeyer, Rebecca; Baron-Cohen, Simon; Raggatt, Peter; Taylor, Kevin

2005-01-01

Background: Sex-differences exist in some areas of human social behaviour. In animals, foetal testosterone (fT) plays a central role in organising the brain and in later social behaviour. fT has also been implicated in language development, eye-contact, and spatial ability in humans. Methods: Fifty-eight children (35 male and 23 female), whose fT…

Exploring Deep Space - Uncovering the Anatomy of Periventricular Structures to Reveal the Lateral Ventricles of the Human Brain.

PubMed

Colibaba, Alexandru S; Calma, Aicee Dawn B; Webb, Alexandra L; Valter, Krisztina

2017-10-22

Anatomy students are typically provided with two-dimensional (2D) sections and images when studying cerebral ventricular anatomy and students find this challenging. Because the ventricles are negative spaces located deep within the brain, the only way to understand their anatomy is by appreciating their boundaries formed by related structures. Looking at a 2D representation of these spaces, in any of the cardinal planes, will not enable visualisation of all of the structures that form the boundaries of the ventricles. Thus, using 2D sections alone requires students to compute their own mental image of the 3D ventricular spaces. The aim of this study was to develop a reproducible method for dissecting the human brain to create an educational resource to enhance student understanding of the intricate relationships between the ventricles and periventricular structures. To achieve this, we created a video resource that features a step-by-step guide using a fiber dissection method to reveal the lateral and third ventricles together with the closely related limbic system and basal ganglia structures. One of the advantages of this method is that it enables delineation of the white matter tracts that are difficult to distinguish using other dissection techniques. This video is accompanied by a written protocol that provides a systematic description of the process to aid in the reproduction of the brain dissection. This package offers a valuable anatomy teaching resource for educators and students alike. By following these instructions educators can create teaching resources and students can be guided to produce their own brain dissection as a hands-on practical activity. We recommend that this video guide be incorporated into neuroanatomy teaching to enhance student understanding of the morphology and clinical relevance of the ventricles.

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.

Training the Brain: Practical Applications of Neural Plasticity From the Intersection of Cognitive Neuroscience, Developmental Psychology, and Prevention Science

PubMed Central

Bryck, Richard L.; Fisher, Philip A.

2012-01-01

Prior researchers have shown that the brain has a remarkable ability for adapting to environmental changes. The positive effects of such neural plasticity include enhanced functioning in specific cognitive domains and shifts in cortical representation following naturally occurring cases of sensory deprivation; however, maladaptive changes in brain function and development owing to early developmental adversity and stress have also been well documented. Researchers examining enriched rearing environments in animals have revealed the potential for inducing positive brain plasticity effects and have helped to popularize methods for training the brain to reverse early brain deficits or to boost normal cognitive functioning. In this paper, two classes of empirically based methods of brain training in children are reviewed and critiqued: laboratory-based, mental process training paradigms and ecological interventions based upon neurocognitive conceptual models. Given the susceptibility of executive function disruption, special attention is paid to training programs that emphasize executive function enhancement. In addition, a third approach to brain training, aimed at tapping into compensatory processes, is postulated. Study results showing the effectiveness of this strategy in the field of neurorehabilitation and in terms of naturally occurring compensatory processing in human aging lend credence to the potential of this approach. PMID:21787037

Training the brain: practical applications of neural plasticity from the intersection of cognitive neuroscience, developmental psychology, and prevention science.

PubMed

Bryck, Richard L; Fisher, Philip A

2012-01-01

Prior researchers have shown that the brain has a remarkable ability for adapting to environmental changes. The positive effects of such neural plasticity include enhanced functioning in specific cognitive domains and shifts in cortical representation following naturally occurring cases of sensory deprivation; however, maladaptive changes in brain function and development owing to early developmental adversity and stress have also been well documented. Researchers examining enriched rearing environments in animals have revealed the potential for inducing positive brain plasticity effects and have helped to popularize methods for training the brain to reverse early brain deficits or to boost normal cognitive functioning. In this article, two classes of empirically based methods of brain training in children are reviewed and critiqued: laboratory-based, mental process training paradigms and ecological interventions based upon neurocognitive conceptual models. Given the susceptibility of executive function disruption, special attention is paid to training programs that emphasize executive function enhancement. In addition, a third approach to brain training, aimed at tapping into compensatory processes, is postulated. Study results showing the effectiveness of this strategy in the field of neurorehabilitation and in terms of naturally occurring compensatory processing in human aging lend credence to the potential of this approach. (PsycINFO Database Record (c) 2012 APA, 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.

Inference of ecological and social drivers of human brain-size evolution.

PubMed

González-Forero, Mauricio; Gardner, Andy

2018-05-01

The human brain is unusually large. It has tripled in size from Australopithecines to modern humans 1 and has become almost six times larger than expected for a placental mammal of human size 2 . Brains incur high metabolic costs 3 and accordingly a long-standing question is why the large human brain has evolved 4 . The leading hypotheses propose benefits of improved cognition for overcoming ecological 5-7 , social 8-10 or cultural 11-14 challenges. However, these hypotheses are typically assessed using correlative analyses, and establishing causes for brain-size evolution remains difficult 15,16 . Here we introduce a metabolic approach that enables causal assessment of social hypotheses for brain-size evolution. Our approach yields quantitative predictions for brain and body size from formalized social hypotheses given empirical estimates of the metabolic costs of the brain. Our model predicts the evolution of adult Homo sapiens-sized brains and bodies when individuals face a combination of 60% ecological, 30% cooperative and 10% between-group competitive challenges, and suggests that between-individual competition has been unimportant for driving human brain-size evolution. Moreover, our model indicates that brain expansion in Homo was driven by ecological rather than social challenges, and was perhaps strongly promoted by culture. Our metabolic approach thus enables causal assessments that refine, refute and unify hypotheses of brain-size evolution.

Resonance Raman Spectroscopy of human brain metastasis of lung cancer analyzed by blind source separation

NASA Astrophysics Data System (ADS)

Zhou, Yan; Liu, Cheng-Hui; Pu, Yang; Cheng, Gangge; Yu, Xinguang; Zhou, Lixin; Lin, Dongmei; Zhu, Ke; Alfano, Robert R.

2017-02-01

Resonance Raman (RR) spectroscopy offers a novel Optical Biopsy method in cancer discrimination by a means of enhancement in Raman scattering. It is widely acknowledged that the RR spectrum of tissue is a superposition of spectra of various key building block molecules. In this study, the Resonance Raman (RR) spectra of human metastasis of lung cancerous and normal brain tissues excited by a visible selected wavelength at 532 nm are used to explore spectral changes caused by the tumor evolution. The potential application of RR spectra human brain metastasis of lung cancer was investigated by Blind Source Separation such as Principal Component Analysis (PCA). PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components (PCs). The results show significant RR spectra difference between human metastasis of lung cancerous and normal brain tissues analyzed by PCA. To evaluate the efficacy of for cancer detection, a linear discriminant analysis (LDA) classifier is utilized to calculate the sensitivity, and specificity and the receiver operating characteristic (ROC) curves are used to evaluate the performance of this criterion. Excellent sensitivity of 0.97, specificity (close to 1.00) and the Area Under ROC Curve (AUC) of 0.99 values are achieved under best optimal circumstance. This research demonstrates that RR spectroscopy is effective for detecting changes of tissues due to the development of brain metastasis of lung cancer. RR spectroscopy analyzed by blind source separation may have potential to be a new armamentarium.

Brain Entropy Mapping Using fMRI

PubMed Central

Wang, Ze; Li, Yin; Childress, Anna Rose; Detre, John A.

2014-01-01

Entropy is an important trait for life as well as the human brain. Characterizing brain entropy (BEN) may provide an informative tool to assess brain states and brain functions. Yet little is known about the distribution and regional organization of BEN in normal brain. The purpose of this study was to examine the whole brain entropy patterns using a large cohort of normal subjects. A series of experiments were first performed to validate an approximate entropy measure regarding its sensitivity, specificity, and reliability using synthetic data and fMRI data. Resting state fMRI data from a large cohort of normal subjects (n = 1049) from multi-sites were then used to derive a 3-dimensional BEN map, showing a sharp low-high entropy contrast between the neocortex and the rest of brain. The spatial heterogeneity of resting BEN was further studied using a data-driven clustering method, and the entire brain was found to be organized into 7 hierarchical regional BEN networks that are consistent with known structural and functional brain parcellations. These findings suggest BEN mapping as a physiologically and functionally meaningful measure for studying brain functions. PMID:24657999

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

PubMed

Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

2016-01-15

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Language systems in normal and aphasic human subjects: functional imaging studies and inferences from animal studies.

PubMed

Wise, Richard J S

2003-01-01

The old neurological model of language, based on the writings of Broca, Wernicke and Lichtheim in the 19th century, is now undergoing major modifications. Observations on the anatomy and physiology of auditory processing in non-human primates are giving strong indicators as to how speech perception is organised in the human brain. In the light of this knowledge, functional activation studies with positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are achieving a new level of precision in the investigation of language organisation in the human brain, in a manner not possible with observations on patients with aphasic stroke. Although the use of functional imaging to inform methods of improving aphasia rehabilitation remains underdeveloped, there are strong indicators that this methodology will provide the means to research a very imperfectly developed area of therapy.

Implantable brain computer interface: challenges to neurotechnology translation.

PubMed

Konrad, Peter; Shanks, Todd

2010-06-01

This article reviews three concepts related to implantable brain computer interface (BCI) devices being designed for human use: neural signal extraction primarily for motor commands, signal insertion to restore sensation, and technological challenges that remain. A significant body of literature has occurred over the past four decades regarding motor cortex signal extraction for upper extremity movement or computer interface. However, little is discussed regarding postural or ambulation command signaling. Auditory prosthesis research continues to represent the majority of literature on BCI signal insertion. Significant hurdles continue in the technological translation of BCI implants. These include developing a stable neural interface, significantly increasing signal processing capabilities, and methods of data transfer throughout the human body. The past few years, however, have provided extraordinary human examples of BCI implant potential. Despite technological hurdles, proof-of-concept animal and human studies provide significant encouragement that BCI implants may well find their way into mainstream medical practice in the foreseeable future.

The Chemical Nature of Mercury in Human Brain Following Poisoning or Environmental Exposure

PubMed Central

2010-01-01

Methylmercury is among the most potentially toxic species to which human populations are exposed, both at high levels through poisonings and at lower levels through consumption of fish and other seafood. However, the molecular mechanisms of methylmercury toxicity in humans remain poorly understood. We used synchrotron X-ray absorption spectroscopy (XAS) to study mercury chemical forms in human brain tissue. Individuals poisoned with high levels of methylmercury species showed elevated cortical selenium with significant proportions of nanoparticulate mercuric selenide plus some inorganic mercury and methylmercury bound to organic sulfur. Individuals with a lifetime of high fish consumption showed much lower levels of mercuric selenide and methylmercury cysteineate. Mercury exposure did not perturb organic selenium levels. These results elucidate a key detoxification pathway in the central nervous system and provide new insights into the appropriate methods for biological monitoring. PMID:22826746

Auditory evoked field measurement using magneto-impedance sensors

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

Wang, K., E-mail: o-kabou@echo.nuee.nagoya-u.ac.jp; Tajima, S.; Song, D.

The magnetic field of the human brain is extremely weak, and it is mostly measured and monitored in the magnetoencephalography method using superconducting quantum interference devices. In this study, in order to measure the weak magnetic field of the brain, we constructed a Magneto-Impedance sensor (MI sensor) system that can cancel out the background noise without any magnetic shield. Based on our previous studies of brain wave measurements, we used two MI sensors in this system for monitoring both cerebral hemispheres. In this study, we recorded and compared the auditory evoked field signals of the subject, including the N100 (ormore » N1) and the P300 (or P3) brain waves. The results suggest that the MI sensor can be applied to brain activity measurement.« less

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.

Cellular GABAergic neuroactive steroid (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP) immunostaining levels are increased in the ventral tegmental area of the human Alcohol Use Disorder patients: A postmortem study

PubMed Central

Hasirci, A. Sait; Maldonado-Devincci, Antoniette M.; Beattie, Matthew C.; O'Buckley, Todd K.; Morrow, A. Leslie

2016-01-01

Background The GABAergic neuroactive steroid (3α,5α)-3-hydroxy-pregnan-20-one (3α,5α-THP, allopregnanolone) enhances GABAergic activity and produces subjective effects similar to ethanol. The effect of chronic alcohol exposure on 3α,5α-THP concentrations has been studied in mouse, rat, and monkey limbic brain areas. Chronic ethanol exposure produced divergent brain region and cell specific changes in 3α,5α-THP concentrations in animal studies. However, 3α,5α-THP levels in similar human brain regions have never been examined in individuals diagnosed with alcohol use disorder (AUD). Therefore, we used immunohistochemistry to examine 3α,5α-THP levels in the ventral tegmental area (VTA), substantia nigra pars medialis (SNM), and amygdala of human postmortem brains of patients diagnosed with AUD compared to social drinkers. The effects of sex and liver disease on 3α,5α-THP concentrations were examined in the aforementioned brain regions. Methods Human postmortem brains of AUD patients and age-matched controls were obtained from the New South Wales Brain Tissue Resource Center. Immunohistochemistry was performed using anti-3α,5α-THP antibody on formalin fixed and paraffin embedded brain sections to detect cellular 3α,5α-THP levels. Immunoreactivity was analyzed by pixel density/mm2 for the comparison between AUD patients and controls. Results 3α,5α-THP immunoreactivity was increased by 23.2±9% in the VTA of AUD patients compared to age matched controls (p= 0.014). Moreover, a 29.6±10% increase in 3α,5α-THP immunoreactivity was observed in the SNM of male AUD patients compared to male controls (p<0.01), but not in female subjects. 3α,5α-THP immunoreactivity in the VTA and SNM regions did not differ between non-cirrhotic and cirrhotic AUD patients. A sex difference in 3α,5α-THP immunoreactivity (female 51±18% greater than male) was observed among control subjects in the SNM, but no other brain region. 3α,5α-THP immunoreactivity in the basolateral and lateral amygdala were negatively correlated with the length of the tissue fixation time as well as the age of the subjects, precluding assessment of the effect of AUD. Conclusions Cellular 3α,5α-THP levels in VTA are increased in human AUD patients, an effect that is likely independent of sex and liver disease. The differences between animal models and human studies should be factored into the interpretation of the physiological significance of elevated 3α,5α-THP levels in humans. PMID:28068457

Brain donation in psychiatry: results of a Dutch prospective donor program among psychiatric cohort participants.

PubMed

de Lange, Geertje M; Rademaker, Marleen; Boks, Marco P; Palmen, Saskia J M C

2017-10-20

Human brain tissue is crucial to study the molecular and cellular basis of psychiatric disorders. However, the current availability of human brain tissue is inadequate. Therefore, the Netherlands Brain Bank initiated a program in which almost 4.000 participants of 15 large Dutch psychiatric research cohorts were asked to register as prospective brain donors. We approached patients with schizophrenia, bipolar disorder, major depressive disorder, obsessive-compulsive disorder, post-traumatic stress disorder, families with a child with autism or Attention Deficit Hyperactivity Disorder, healthy relatives and healthy unrelated controls, either face-to-face or by post. We investigated whether diagnosis, method of approach, age, and gender were related to the likelihood of brain-donor registration. We found a striking difference in registration efficiency between the diagnosis groups. Patients with bipolar disorder and healthy relatives registered most often (25% respectively 17%), followed by unrelated controls (8%) and patients with major depressive disorder, post-traumatic stress disorder, and obsessive-compulsive disorder (9%, 6% resp. 5%). A face-to-face approach was 1.3 times more effective than a postal approach and the likelihood of registering as brain donor significantly increased with age. Gender did not make a difference. Between 2013 and 2016, our prospective brain-donor program for psychiatry resulted in an almost eightfold increase (from 149 to 1149) in the number of registered psychiatric patients at the Netherlands Brain Bank. Based on our results we recommend, when starting a prospective brain donor program in psychiatric patients, to focus on face to face recruitment of people in their sixties or older.

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

Magnetic resonance spectroscopy of the human brain.

PubMed

Ross, B; Bluml, S

2001-04-01

Magnetic resonance (MR; synonymous with NMR = nuclear magnetic resonance) is a universal physical technique best known for non-invasive detection and anatomical mapping of water protons (H). MR-spectroscopy (MRS) records protons from tissue chemicals other than water, intrinsic phosphorus containing metabolites, sodium, potassium, carbon, nitrogen, and fluorine. MRS is therefore an imaging technique with the potential to record human and animal biochemistry in vivo. As a result of wide availability of MRI equipment in research laboratories and hospitals, MRS is a serious competitor with PET to define normal body composition and its perturbation by pharmacological and pathological events. This article describes practical aspects of in vivo MRS with particular emphasis on the brain, where novel metabolites have been described. A survey of these new aspects of neurochemistry emphasize their practical utility as neuronal and axonal markers, measures of energy status, membrane constituents, and osmolytes, as well as some xenobiotics, such as alcohol. The concept of multinuclear in vivo MRS is illustrated by diagnosis and therapeutic monitoring of several human brain disorders. Although these methods are currently most frequently encountered in human studies, as well as with transgenic and knockout mouse models, MRS adds a new dimension to anatomic and histopathologic descriptions. Copyright 2001 Wiley-Liss, Inc.

Immunohistochemical and in situ mRNA hybridisation techniques to determine the distribution of ion channels in human brain: a study of neuronal voltage-dependent calcium channels.

PubMed

McCormack, A L; Day, N C; Craig, P J; Smith, W; Beattie, R E; Volsen, S G

1997-08-01

The molecular, structural and functional characterisation of ion channels in the CNS forms an area of intense investigation in current brain research. For strategic and logistical reasons, rodents have historically been the species of choice for these studies. The examination of human CNS tissues generally presents the investigator with specific challenges that are often less problematic in animal studies, e.g. post-mortem delay/agonal status, and thus both the experimental design and techniques must be manipulated accordingly. Since much pharmaceutical interest is currently focused on neuronal ion channels, the examination of their expression in human brain material is of particular importance. We describe here the details of methods that we have developed and used successfully in the study of the expression of voltage-dependent calcium channels (VDCCs) in human CNS tissues. Presynaptic neuronal VDCCs control neurotransmitter release and are important new drug targets. They are composed of three subunits, alpha 1, beta and alpha 2/delta and multiple gene classes of each protein have been identified. Little is known, however, about the distribution of neuronal VDCCs in the human central nervous system, although initial studies have been performed in rat and rabbit.

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…

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

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

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

HDAC6 Brain Mapping with [ 18 F]Bavarostat Enabled by a Ru-Mediated Deoxyfluorination

DOE PAGES

Strebl, Martin G.; Campbell, Arthur J.; Zhao, Wen -Ning; ...

2017-09-06

Histone deacetylase 6 (HDAC6) function and dysregulation have been implicated in the etiology of certain cancers and more recently in central nervous system (CNS) disorders including Rett syndrome, Alzheimer’s and Parkinson’s diseases, and major depressive disorder. HDAC6-selective inhibitors have therapeutic potential, but in the CNS drug space the development of highly brain penetrant HDAC inhibitors has been a persistent challenge. Moreover, no tool exists to directly characterize HDAC6 and its related biology in the living human brain. Here, we report a highly brain penetrant HDAC6 inhibitor, Bavarostat, that exhibits excellent HDAC6 selectivity (>80-fold over all other Zn-containing HDAC paralogues), modulatesmore » tubulin acetylation selectively over histone acetylation, and has excellent brain penetrance. We further demonstrate that Bavarostat can be radiolabeled with 18F by deoxyfluorination through in situ formation of a ruthenium π-complex of the corresponding phenol precursor: the only method currently suitable for synthesis of [ 18F]Bavarostat. In conclusion, by using [ 18F]Bavarostat in a series of rodent and nonhuman primate imaging experiments, we demonstrate its utility for mapping HDAC6 in the living brain, which sets the stage for first-in-human neurochemical imaging of this important target.« less

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.

High-contrast differentiation resolution 3D imaging of rodent brain by X-ray computed microtomography

NASA Astrophysics Data System (ADS)

Zikmund, T.; Novotná, M.; Kavková, M.; Tesařová, M.; Kaucká, M.; Szarowská, B.; Adameyko, I.; Hrubá, E.; Buchtová, M.; Dražanová, E.; Starčuk, Z.; Kaiser, J.

2018-02-01

The biomedically focused brain research is largely performed on laboratory mice considering a high homology between the human and mouse genomes. A brain has an intricate and highly complex geometrical structure that is hard to display and analyse using only 2D methods. Applying some fast and efficient methods of brain visualization in 3D will be crucial for the neurobiology in the future. A post-mortem analysis of experimental animals' brains usually involves techniques such as magnetic resonance and computed tomography. These techniques are employed to visualize abnormalities in the brains' morphology or reparation processes. The X-ray computed microtomography (micro CT) plays an important role in the 3D imaging of internal structures of a large variety of soft and hard tissues. This non-destructive technique is applied in biological studies because the lab-based CT devices enable to obtain a several-micrometer resolution. However, this technique is always used along with some visualization methods, which are based on the tissue staining and thus differentiate soft tissues in biological samples. Here, a modified chemical contrasting protocol of tissues for a micro CT usage is introduced as the best tool for ex vivo 3D imaging of a post-mortem mouse brain. This way, the micro CT provides a high spatial resolution of the brain microscopic anatomy together with a high tissue differentiation contrast enabling to identify more anatomical details in the brain. As the micro CT allows a consequent reconstruction of the brain structures into a coherent 3D model, some small morphological changes can be given into context of their mutual spatial relationships.

Comparison of (/sup 14/C)glucose and (/sup 14/C)deoxyglucose as tracers of brain glucose use

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

Hawkins, R.A.; Mans, A.M.; Davis, D.W.

1988-03-01

Because glucose metabolism and functional activity in brain regions are normally coupled, knowledge of regional brain glucose use can yield insights into regional functional activity. The deoxyglucose (DG) method is widely used for this purpose in experimental animals and humans but questions have arisen regarding its limits and accuracy. Therefore an experiment was designed to compare the DG method on a structure-by-structure basis with another tracer of glucose use, (6-/sup 14/C)glucose, in normal rats. The cerebral metabolic rates obtained using the two tracers were similar in the telencephalon, but the results using DG were substantially lower in the midbrain andmore » hindbrain (diencephalon, 18%; mesencephalon, 20%; metencephalon, 29%; and myelencephalon, 35%). The primary DG metabolite, DG 6-phosphate (DG-6-P) was found to disappear in a non-uniform manner from the major brain structures: telencephalon less than diencephalon less than mesencephalon = metencephalon less than myelencephalon. Thus a correlation was found between the rate of DG-6-P loss and the extent to which the DG method gave lower values of glucose use. Thus this may explain, at least in part, the discrepancies between the two methods.« less

Consequences of Traumatic Brain Injury for Human Vergence Dynamics

PubMed Central

Tyler, Christopher W.; Likova, Lora T.; Mineff, Kristyo N.; Elsaid, Anas M.; Nicholas, Spero C.

2015-01-01

Purpose: Traumatic brain injury involving loss of consciousness has focal effects in the human brainstem, suggesting that it may have particular consequences for eye movement control. This hypothesis was investigated by measurements of vergence eye movement parameters. Methods: Disparity vergence eye movements were measured for a population of 123 normally sighted individuals, 26 of whom had suffered diffuse traumatic brain injury (dTBI) in the past, while the remainder served as controls. Vergence tracking responses were measured to sinusoidal disparity modulation of a random-dot field. Disparity vergence step responses were characterized in terms of their dynamic parameters separately for the convergence and divergence directions. Results: The control group showed notable differences between convergence and divergence dynamics. The dTBI group showed significantly abnormal vergence behavior on many of the dynamic parameters. Conclusion: The results support the hypothesis that occult injury to the oculomotor control system is a common residual outcome of dTBI. PMID:25691880

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

Effects of Physical Exercise Combined with Nutritional Supplements on Aging Brain Related Structures and Functions: A Systematic Review

PubMed Central

Schättin, Alexandra; Baur, Kilian; Stutz, Jan; Wolf, Peter; de Bruin, Eling D.

2016-01-01

Age-related decline in gray and white brain matter goes together with cognitive depletion. To influence cognitive functioning in elderly, several types of physical exercise and nutritional intervention have been performed. This paper systematically reviews the potential additive and complementary effects of nutrition/nutritional supplements and physical exercise on cognition. The search strategy was developed for EMBASE, Medline, PubMed, Cochrane, CINAHL, and PsycInfo databases and focused on the research question: “Is the combination of physical exercise with nutrition/nutritional supplementation more effective than nutrition/nutritional supplementation or physical exercise alone in effecting on brain structure, metabolism, and/or function?” Both mammalian and human studies were included. In humans, randomized controlled trials that evaluated the effects of nutrition/nutritional supplements and physical exercise on cognitive functioning and associated parameters in healthy elderly (>65 years) were included. The systematic search included English and German language literature without any limitation of publication date. The search strategy yielded a total of 3129 references of which 67 studies met the inclusion criteria; 43 human and 24 mammalian, mainly rodent, studies. Three out of 43 human studies investigated a nutrition/physical exercise combination and reported no additive effects. In rodent studies, additive effects were found for docosahexaenoic acid supplementation when combined with physical exercise. Although feasible combinations of physical exercise/nutritional supplements are available for influencing the brain, only a few studies evaluated which possible combinations of nutrition/nutritional supplementation and physical exercise might have an effect on brain structure, metabolism and/or function. The reason for no clear effects of combinatory approaches in humans might be explained by the misfit between the combinations of nutritional methods with the physical interventions in the sense that they were not selected on sharing of similar neuronal mechanisms. Based on the results from this systematic review, future human studies should focus on the combined effect of docosahexaenoic acid supplementation and physical exercise that contains elements of (motor) learning. PMID:27458371

Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development

PubMed Central

Ayaz, Hasan; Onaral, Banu; Izzetoglu, Kurtulus; Shewokis, Patricia A.; McKendrick, Ryan; Parasuraman, Raja

2013-01-01

Functional near infrared spectroscopy (fNIRS) is a non-invasive, safe, and portable optical neuroimaging method that can be used to assess brain dynamics during skill acquisition and performance of complex work and everyday tasks. In this paper we describe neuroergonomic studies that illustrate the use of fNIRS in the examination of training-related brain dynamics and human performance assessment. We describe results of studies investigating cognitive workload in air traffic controllers, acquisition of dual verbal-spatial working memory skill, and development of expertise in piloting unmanned vehicles. These studies used conventional fNIRS devices in which the participants were tethered to the device while seated at a workstation. Consistent with the aims of mobile brain imaging (MoBI), we also describe a compact and battery-operated wireless fNIRS system that performs with similar accuracy as other established fNIRS devices. Our results indicate that both wired and wireless fNIRS systems allow for the examination of brain function in naturalistic settings, and thus are suitable for reliable human performance monitoring and training assessment. PMID:24385959

Causal mapping of emotion networks in the human brain: Framework and initial findings.

PubMed

Dubois, Julien; Oya, Hiroyuki; Tyszka, J Michael; Howard, Matthew; Eberhardt, Frederick; Adolphs, Ralph

2017-11-13

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cerebral cartography and connectomics.

PubMed

Sporns, Olaf

2015-05-19

Cerebral cartography and connectomics pursue similar goals in attempting to create maps that can inform our understanding of the structural and functional organization of the cortex. Connectome maps explicitly aim at representing the brain as a complex network, a collection of nodes and their interconnecting edges. This article reflects on some of the challenges that currently arise in the intersection of cerebral cartography and connectomics. Principal challenges concern the temporal dynamics of functional brain connectivity, the definition of areal parcellations and their hierarchical organization into large-scale networks, the extension of whole-brain connectivity to cellular-scale networks, and the mapping of structure/function relations in empirical recordings and computational models. Successfully addressing these challenges will require extensions of methods and tools from network science to the mapping and analysis of human brain connectivity data. The emerging view that the brain is more than a collection of areas, but is fundamentally operating as a complex networked system, will continue to drive the creation of ever more detailed and multi-modal network maps as tools for on-going exploration and discovery in human connectomics. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A Geographic Cline of Skull and Brain Morphology among Individuals of European Ancestry

PubMed Central

Bakken, Trygve E.; Dale, Anders M.; Schork, Nicholas J.

2011-01-01

Background Human skull and brain morphology are strongly influenced by genetic factors, and skull size and shape vary worldwide. However, the relationship between specific brain morphology and genetically-determined ancestry is largely unknown. Methods We used two independent data sets to characterize variation in skull and brain morphology among individuals of European ancestry. The first data set is a historical sample of 1,170 male skulls with 37 shape measurements drawn from 27 European populations. The second data set includes 626 North American individuals of European ancestry participating in the Alzheimer's Disease Neuroimaging Initiative (ADNI) with magnetic resonance imaging, height and weight, neurological diagnosis, and genome-wide single nucleotide polymorphism (SNP) data. Results We found that both skull and brain morphological variation exhibit a population-genetic fingerprint among individuals of European ancestry. This fingerprint shows a Northwest to Southeast gradient, is independent of body size, and involves frontotemporal cortical regions. Conclusion Our findings are consistent with prior evidence for gene flow in Europe due to historical population movements and indicate that genetic background should be considered in studies seeking to identify genes involved in human cortical development and neuropsychiatric disease. PMID:21849792

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.

Functional brain segmentation using inter-subject correlation in fMRI.

PubMed

Kauppi, Jukka-Pekka; Pajula, Juha; Niemi, Jari; Hari, Riitta; Tohka, Jussi

2017-05-01

The human brain continuously processes massive amounts of rich sensory information. To better understand such highly complex brain processes, modern neuroimaging studies are increasingly utilizing experimental setups that better mimic daily-life situations. A new exploratory data-analysis approach, functional segmentation inter-subject correlation analysis (FuSeISC), was proposed to facilitate the analysis of functional magnetic resonance (fMRI) data sets collected in these experiments. The method provides a new type of functional segmentation of brain areas, not only characterizing areas that display similar processing across subjects but also areas in which processing across subjects is highly variable. FuSeISC was tested using fMRI data sets collected during traditional block-design stimuli (37 subjects) as well as naturalistic auditory narratives (19 subjects). The method identified spatially local and/or bilaterally symmetric clusters in several cortical areas, many of which are known to be processing the types of stimuli used in the experiments. The method is not only useful for spatial exploration of large fMRI data sets obtained using naturalistic stimuli, but also has other potential applications, such as generation of a functional brain atlases including both lower- and higher-order processing areas. Finally, as a part of FuSeISC, a criterion-based sparsification of the shared nearest-neighbor graph was proposed for detecting clusters in noisy data. In the tests with synthetic data, this technique was superior to well-known clustering methods, such as Ward's method, affinity propagation, and K-means ++. Hum Brain Mapp 38:2643-2665, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

PubMed

Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

MEG Source Imaging Method using Fast L1 Minimum-norm and its Applications to Signals with Brain Noise and Human Resting-state Source Amplitude Images

PubMed Central

Huang, Ming-Xiong; Huang, Charles W.; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L.; Baker, Dewleen G.; Song, Tao; Harrington, Deborah L.; Theilmann, Rebecca J.; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M.; Edgar, J. Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T.; Drake, Angela; Lee, Roland R.

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL’s performance of was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL’s performance was then examined in the analysis of human mediannerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer’s problems of signal leaking and distorted source time-courses. PMID:24055704

The biochemical, nanomechanical and chemometric signatures of brain cancer.

PubMed

Abramczyk, Halina; Imiela, Anna

2018-01-05

Raman spectroscopy and imaging combined with AFM topography and mechanical indentation by AFM have been shown to be an effective tool for analysis and discrimination of human brain tumors from normal structures. Raman methods have potential to be applied in clinical practice as they allow for identification of tumor margins during surgery. In this study, we investigate medulloblastoma (grade IV WHO) (n=5) and the tissue from the negative margins used as normal controls. We compare a high grade medulloblastoma (IV grade), and non-tumor samples from human central nervous system (CNS) tissue. Based on the properties of the Raman vibrational spectra and Raman images we provide a real-time feedback that is label-free method to monitor tumor metabolism that reveals reprogramming of biosynthesis of lipids, and proteins. We have found that the high-grade tumors of central nervous system (medulloblastoma) exhibit enhanced level of β-sheet conformation and down-regulated level of α-helix conformation when comparing against normal tissue. We have shown that the ratio of Raman intensities I2930/I2845 at 2930 and 2845cm -1 is a good source of information on the ratio of lipid and protein contents. We have found that the ratio reflects the lipid and protein contents of tumorous brain tissue compared to the non-tumor tissue. Almost all brain tumors have the Raman intensity ratios significantly higher (1.99±0.026) than that found in non-tumor brain tissue, which is 1.456±0.02, and indicates that the relative amount of lipids compared to proteins is significantly higher in the normal brain tissue. Mechanical indentation using AFM on sliced human brain tissues (medulloblastoma, grade IV) revealed that the mechanical properties of this tissue are strongly heterogeneous, between 1.8 and 75.7kPa, and the mean of 27.16kPa. The sensitivity and specificity obtained directly from PLSDA and cross validation gives a sensitivity and specificity of 98.5% and 96% and 96.3% and 92% for cross-validation, respectively. The high sensitivity and specificity demonstrates usefulness for a proper decision for a Raman diagnostic test on biochemical alterations monitored by Raman spectroscopy related to brain cancer development. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The role of free radicals in traumatic brain injury.

PubMed

O'Connell, Karen M; Littleton-Kearney, Marguerite T

2013-07-01

Traumatic brain injury (TBI) is a significant cause of death and disability in both the civilian and the military populations. The primary impact causes initial tissue damage, which initiates biochemical cascades, known as secondary injury, that expand the damage. Free radicals are implicated as major contributors to the secondary injury. Our review of recent rodent and human research reveals the prominent role of the free radicals superoxide anion, nitric oxide, and peroxynitrite in secondary brain injury. Much of our current knowledge is based on rodent studies, and the authors identified a gap in the translation of findings from rodent to human TBI. Rodent models are an effective method for elucidating specific mechanisms of free radical-induced injury at the cellular level in a well-controlled environment. However, human TBI does not occur in a vacuum, and variables controlled in the laboratory may affect the injury progression. Additionally, multiple experimental TBI models are accepted in rodent research, and no one model fully reproduces the heterogeneous injury seen in humans. Free radical levels are measured indirectly in human studies based on assumptions from the findings from rodent studies that use direct free radical measurements. Further study in humans should be directed toward large samples to validate the findings in rodent studies. Data obtained from these studies may lead to more targeted treatment to interrupt the secondary injury cascades.

Serotonergic Psychedelics Temporarily Modify Information Transfer in Humans

PubMed Central

Alonso, Joan Francesc; Romero, Sergio; Mañanas, Miquel Àngel

2015-01-01

Background: Psychedelics induce intense modifications in the sensorium, the sense of “self,” and the experience of reality. Despite advances in our understanding of the molecular and cellular level mechanisms of these drugs, knowledge of their actions on global brain dynamics is still incomplete. Recent imaging studies have found changes in functional coupling between frontal and parietal brain structures, suggesting a modification in information flow between brain regions during acute effects. Methods: Here we assessed the psychedelic-induced changes in directionality of information flow during the acute effects of a psychedelic in humans. We measured modifications in connectivity of brain oscillations using transfer entropy, a nonlinear measure of directed functional connectivity based on information theory. Ten healthy male volunteers with prior experience with psychedelics participated in 2 experimental sessions. They received a placebo or a dose of ayahuasca, a psychedelic preparation containing the serotonergic 5-HT2A agonist N,N-dimethyltryptamine. Results: The analysis showed significant changes in the coupling of brain oscillations between anterior and posterior recording sites. Transfer entropy analysis showed that frontal sources decreased their influence over central, parietal, and occipital sites. Conversely, sources in posterior locations increased their influence over signals measured at anterior locations. Exploratory correlations found that anterior-to-posterior transfer entropy decreases were correlated with the intensity of subjective effects, while the imbalance between anterior-to-posterior and posterior-to-anterior transfer entropy correlated with the degree of incapacitation experienced. Conclusions: These results suggest that psychedelics induce a temporary disruption of neural hierarchies by reducing top-down control and increasing bottom-up information transfer in the human brain. PMID:25820842

In vivo single-shot three-dimensionally localized multiple quantum spectroscopy of GABA in the human brain with improved spectral selectivity

NASA Astrophysics Data System (ADS)

Choi, In-Young; Lee, Sang-Pil; Shen, Jun

2005-01-01

A single-shot multiple quantum filtering method is developed that uses two double-band frequency selective pulses for enhanced spectral selectivity in combination with a slice-selective 90°, a slice-selective universal rotator 90°, and a spectral-spatial pulse composed of two slice-selective universal rotator 45° pulses for single-shot three-dimensional localization. The use of this selective multiple quantum filtering method for C3 and C4 methylene protons of GABA resulted in improved spectral selectivity for GABA and effective suppression of overlapping signals such as creatine and glutathione in each single scan, providing reliable measurements of the GABA doublet in all subjects. The concentration of GABA was measured to be 0.7 ± 0.2 μmol/g (means ± SD, n = 15) in the fronto-parietal region of the human brain in vivo.

Further refinement of the Escherichia coli brain abscess model in rat.

PubMed

Nazzaro, J M; Pagel, M A; Neuwelt, E A

1992-09-01

The rat brain abscess model provides a substrate for the modeling of delivery of therapeutic agents to intracerebral mass lesions. We now report refinement of the Escherichia coli brain abscess model in rat. A K1 surface antigen-negative E. coli isolated from human blood culture was stereotaxically inoculated into deep brain sites. Histopathologic analyses and quantitative cultures demonstrated the consistent production of lesions. No animal in this consecutive series developed meningitis, ventriculitis or sepsis. By contrast, prior experience with E. coli abscess production resulted in 25% failure rate of abscess production or death from sepsis. This improvement in the model may be attributable to specific characteristics of the bacteria used, modification of the inoculation method or the intracerebral placement technique. The present work suggests a reliable and consistent brain abscess model, which may be further used to study brain suppuration.

3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set.

PubMed

Popuri, Karteek; Cobzas, Dana; Murtha, Albert; Jägersand, Martin

2012-07-01

Brain tumor segmentation is a required step before any radiation treatment or surgery. When performed manually, segmentation is time consuming and prone to human errors. Therefore, there have been significant efforts to automate the process. But, automatic tumor segmentation from MRI data is a particularly challenging task. Tumors have a large diversity in shape and appearance with intensities overlapping the normal brain tissues. In addition, an expanding tumor can also deflect and deform nearby tissue. In our work, we propose an automatic brain tumor segmentation method that addresses these last two difficult problems. We use the available MRI modalities (T1, T1c, T2) and their texture characteristics to construct a multidimensional feature set. Then, we extract clusters which provide a compact representation of the essential information in these features. The main idea in this work is to incorporate these clustered features into the 3D variational segmentation framework. In contrast to previous variational approaches, we propose a segmentation method that evolves the contour in a supervised fashion. The segmentation boundary is driven by the learned region statistics in the cluster space. We incorporate prior knowledge about the normal brain tissue appearance during the estimation of these region statistics. In particular, we use a Dirichlet prior that discourages the clusters from the normal brain region to be in the tumor region. This leads to a better disambiguation of the tumor from brain tissue. We evaluated the performance of our automatic segmentation method on 15 real MRI scans of brain tumor patients, with tumors that are inhomogeneous in appearance, small in size and in proximity to the major structures in the brain. Validation with the expert segmentation labels yielded encouraging results: Jaccard (58%), Precision (81%), Recall (67%), Hausdorff distance (24 mm). Using priors on the brain/tumor appearance, our proposed automatic 3D variational segmentation method was able to better disambiguate the tumor from the surrounding tissue.

Non-invasive measurements of tissue hemodynamics with hybrid diffuse optical methods

NASA Astrophysics Data System (ADS)

Durduran, Turgut

Diffuse optical techniques were used to measure hemodynamics of tissues non-invasively. Spectroscopy and tomography of the brain, muscle and implanted tumors were carried out in animal models and humans. Two qualitatively different methods, diffuse optical tomography and diffuse correlation tomography, were hybridized permitting simultaneous measurement of total hemoglobin concentration, blood oxygen saturation and blood flow. This combination of information was processed further to derive estimates of oxygen metabolism (e.g. CMRO 2) in tissue. The diffuse correlation measurements of blood flow were demonstrated in human tissues, for the first time, demonstrating continous, non-invasive imaging of oxygen metabolism in large tissue volumes several centimeters below the tissue surface. The bulk of these investigations focussed on cerebral hemodynamics. Extensive validation of this methodology was carried out in in vivo rat brain models. Three dimensional images of deep tissue hemodynamics in middle cerebral artery occlusion and cortical spreading depression (CSD) were obtained. CSD hemodynamics were found to depend strongly on partial pressure of carbon dioxide. The technique was then adapted for measurement of human brain. All optical spectroscopic measurements of CMRO2 during functional activation were obtained through intact human skull non-invasively. Finally, a high spatio-temporal resolution measurement of cerebral blood flow due to somatosensory cortex activation following electrical forepaw stimulation in rats was carried out with laser speckle flowmetry. New analysis methods were introduced for laser speckle flowmetry. In other organs, deep tissue hemodynamics were measured on human calf muscle during exercise and cuff-ischemia and were shown to have some clinical utility for peripheral vascular disease. In mice tumor models, the measured hemodynamics were shown to be predictive of photodynamic therapy efficacy, again suggesting promise of clinical utility. In total, the research has pioneered the development of diffuse optical measurements of blood flow, oxygenation and oxygen metabolism in a large range of research and clinical applications.

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.

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks

PubMed Central

Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-01-01

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes. PMID:29642483

Drawing Inspiration from Human Brain Networks: Construction of Interconnected Virtual Networks.

PubMed

Murakami, Masaya; Kominami, Daichi; Leibnitz, Kenji; Murata, Masayuki

2018-04-08

Virtualization of wireless sensor networks (WSN) is widely considered as a foundational block of edge/fog computing, which is a key technology that can help realize next-generation Internet of things (IoT) networks. In such scenarios, multiple IoT devices and service modules will be virtually deployed and interconnected over the Internet. Moreover, application services are expected to be more sophisticated and complex, thereby increasing the number of modifications required for the construction of network topologies. Therefore, it is imperative to establish a method for constructing a virtualized WSN (VWSN) topology that achieves low latency on information transmission and high resilience against network failures, while keeping the topological construction cost low. In this study, we draw inspiration from inter-modular connectivity in human brain networks, which achieves high performance when dealing with large-scale networks composed of a large number of modules (i.e., regions) and nodes (i.e., neurons). We propose a method for assigning inter-modular links based on a connectivity model observed in the cerebral cortex of the brain, known as the exponential distance rule (EDR) model. We then choose endpoint nodes of these links by controlling inter-modular assortativity, which characterizes the topological connectivity of brain networks. We test our proposed methods using simulation experiments. The results show that the proposed method based on the EDR model can construct a VWSN topology with an optimal combination of communication efficiency, robustness, and construction cost. Regarding the selection of endpoint nodes for the inter-modular links, the results also show that high assortativity enhances the robustness and communication efficiency because of the existence of inter-modular links of two high-degree nodes.

In vitro model of cerebral ischemia by using brain microvascular endothelial cells derived from human induced pluripotent stem cells.

PubMed

Kokubu, Yasuhiro; Yamaguchi, Tomoko; Kawabata, Kenji

2017-04-29

Brain-derived microvascular endothelial cells (BMECs), which play a central role in blood brain barrier (BBB), can be used for the evaluation of drug transport into the brain. Although human BMEC cell lines have already been reported, they lack original properties such as barrier integrity. Pluripotent stem cells (PSCs) can be used for various applications such as regenerative therapy, drug screening, and pathological study. In the recent study, an induction method of BMECs from PSCs has been established, making it possible to more precisely study the in vitro human BBB function. Here, using induced pluripotent stem (iPS) cell-derived BMECs, we examined the effects of oxygen-glucose deprivation (OGD) and OGD/reoxygenation (OGD/R) on BBB permeability. OGD disrupted the barrier function, and the dysfunction was rapidly restored by re-supply of the oxygen and glucose. Interestingly, TNF-α, which is known to be secreted from astrocytes and microglia in the cerebral ischemia, prevented the restoration of OGD-induced barrier dysfunction in an apoptosis-independent manner. Thus, we could establish the in vitro BBB disease model that mimics the cerebral ischemia by using iPS cell-derived BMECs. Copyright © 2017 Elsevier Inc. All rights reserved.

Brain tumour classification and abnormality detection using neuro-fuzzy technique and Otsu thresholding.

PubMed

Renjith, Arokia; Manjula, P; Mohan Kumar, P

2015-01-01

Brain tumour is one of the main causes for an increase in transience among children and adults. This paper proposes an improved method based on Magnetic Resonance Imaging (MRI) brain image classification and image segmentation approach. Automated classification is encouraged by the need of high accuracy when dealing with a human life. The detection of the brain tumour is a challenging problem, due to high diversity in tumour appearance and ambiguous tumour boundaries. MRI images are chosen for detection of brain tumours, as they are used in soft tissue determinations. First of all, image pre-processing is used to enhance the image quality. Second, dual-tree complex wavelet transform multi-scale decomposition is used to analyse texture of an image. Feature extraction extracts features from an image using gray-level co-occurrence matrix (GLCM). Then, the Neuro-Fuzzy technique is used to classify the stages of brain tumour as benign, malignant or normal based on texture features. Finally, tumour location is detected using Otsu thresholding. The classifier performance is evaluated based on classification accuracies. The simulated results show that the proposed classifier provides better accuracy than previous method.

Considerations for optimal use of postmortem human brains for molecular psychiatry: lessons from schizophrenia.

PubMed

Weickert, Cynthia Shannon; Rothmond, Debora A; Purves-Tyson, Tertia D

2018-01-01

Schizophrenia is a disabling disease impacting millions of people around the world, for which there is no known cure. Current antipsychotic treatments for schizophrenia mainly target psychotic symptoms, do little to ameliorate social or cognitive deficits, have side-effects that cause weight gain, and diabetes and 30% of people do not respond. Thus, better therapeutics for schizophrenia aimed at the route biologic changes are needed and discovering the underlying neurobiology is key to this quest. Postmortem brain studies provide the most direct and detailed way to determine the pathophysiology of schizophrenia. This chapter outlines steps that can be taken to ensure the best-quality molecular data from postmortem brain tissue are obtained. In this chapter, we also discuss targeted and high-throughput methods for examining gene and protein expression and some of the strengths and limitations of each method. We briefly consider why gene and protein expression changes may not always concur within brain tissue. We conclude that postmortem brain research that investigates gene and protein expression in well-characterized and matched brain cohorts provides an important foundation to be considered when interpreting data obtained from studies of living schizophrenia patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Event-related functional MRI: Past, present, and future

PubMed Central

Rosen, Bruce R.; Buckner, Randy L.; Dale, Anders M.

1998-01-01

The past two decades have seen an enormous growth in the field of human brain mapping. Investigators have extensively exploited techniques such as positron emission tomography and MRI to map patterns of brain activity based on changes in cerebral hemodynamics. However, until recently, most studies have investigated equilibrium changes in blood flow measured over time periods upward of 1 min. The advent of high-speed MRI methods, capable of imaging the entire brain with a temporal resolution of a few seconds, allows for brain mapping based on more transient aspects of the hemodynamic response. Today it is now possible to map changes in cerebrovascular parameters essentially in real time, conferring the ability to observe changes in brain state that occur over time periods of seconds. Furthermore, because robust hemodynamic alterations are detectable after neuronal stimuli lasting only a few tens of milliseconds, a new class of task paradigms designed to measure regional responses to single sensory or cognitive events can now be studied. Such “event related” functional MRI should provide for fundamentally new ways to interrogate brain function, and allow for the direct comparison and ultimately integration of data acquired by using more traditional behavioral and electrophysiological methods. PMID:9448240

Cold Blooded: Evaluating Brain Temperature by MRI During Surface Cooling of Human Subjects.

PubMed

Curran, Eric J; Wolfson, Daniel L; Watts, Richard; Freeman, Kalev

2017-10-01

Targeted temperature management (TTM) confers neurological and survival benefits for post-cardiac arrest patients with return of spontaneous circulation (ROSC) who remain comatose. Specialized equipment for induction of hypothermia is not available in the prehospital setting, and there are no reliable methods for emergency medical services personnel to initiate TTM. We hypothesized that the application of surface cooling elements to the neck will decrease brain temperature and act as initiators of TTM. Magnetic resonance (MR) spectroscopy was used to evaluate the effect of a carotid surface cooling element on brain temperature in healthy adults. Six individuals completed this study. We measured a temperature drop of 0.69 ± 0.38 °C (95% CI) in the cortex of the brain following the application of the cooling element. Application of a room temperature element also caused a measurable decrease in brain temperature of 0.66 ± 0.41 °C (95% CI) which may be attributable to baroreceptor activation. The application of surface cooling elements to the neck decreased brain temperature and may serve as a method to initiate TTM in the prehospital setting.

Event-Related Oscillations in Alcoholism Research: A Review

PubMed Central

Pandey, Ashwini K; Kamarajan, Chella; Rangaswamy, Madhavi; Porjesz, Bernice

2013-01-01

Alcohol dependence is characterized as a multi-factorial disorder caused by a complex interaction between genetic and environmental liabilities across development. A variety of neurocognitive deficits/dysfunctions involving impairments in different brain regions and/or neural circuitries have been associated with chronic alcoholism, as well as with a predisposition to develop alcoholism. Several neurobiological and neurobehavioral approaches and methods of analyses have been used to understand the nature of these neurocognitive impairments/deficits in alcoholism. In the present review, we have examined relatively novel methods of analyses of the brain signals that are collectively referred to as event-related oscillations (EROs) and show promise to further our understanding of human brain dynamics while performing various tasks. These new measures of dynamic brain processes have exquisite temporal resolution and allow the study of neural networks underlying responses to sensory and cognitive events, thus providing a closer link to the physiology underlying them. Here, we have reviewed EROs in the study of alcoholism, their usefulness in understanding dynamical brain functions/dysfunctions associated with alcoholism as well as their utility as effective endophenotypes to identify and understand genes associated with both brain oscillations and alcoholism. PMID:24273686

Far-red to near infrared emission and scattering spectroscopy for biomedical applications

NASA Astrophysics Data System (ADS)

Zhang, Gang

2001-06-01

The thesis investigates the far-red and near infrared (NIR) spectral region from biomedical tissue samples for monitoring the state of tissues. The NIR emission wing intensity is weak in comparison to the emission in the visible spectral region. The wing emission from biomedical samples has revealed meaningful information about the state of the tissues. A model is presented to explain the shape of the spectral wing based on a continuum of energy levels. The wing can be used to classify different kinds of tissues; especially it can be used to differentiate cancer part from normal human breast tissues. The research work of the far-red emission from thermal damaged tissue samples shows that the emission intensity in this spectral region is proportional to the extent of the thermal damage of the tissue. Near infrared spectral absorption method is used to investigate blood hemodynamics (perfusion and oxygenation) in brain during sleep-wake transition. The result of the research demonstrates that the continuous wave (CW) type near infrared spectroscopy (NIRS) device can be used to investigate brain blood perfusion and oxygenation with a similar precision with frequency domain (FD) type device. The human subject sleep and wake transition, has been monitored by CW type NIRS instrument with traditional electroencephalograph (EEG) method. Parallel change in oxy-Hb and deoxy-Hb is a discrete event that occurs in the transition from both sleep to wakefulness and wakefulness to sleep. These hemodynamic switches are generally about few seconds delayed from the human decided transition point between sleep and wake on the polygraph EEG recording paper. The combination of NIRS and EEG methods monitor the brain activity, gives more information about the brain activity. The sleep apnea investigation was associated with recurrent apneas, insufficient nasal continuous positive airway pressure (CPAP) and the different response of the peripheral and central compartments to breathing events. The different results with finger pulse oximetry and NIRS suggest that optical monitoring of the brain may have advantages that may help clarify the morbidity of obstructive sleep apnea (OSA) Syndrome.

Revealing pathologies in the liquid crystalline structures of the brain by polarimetric studies (Presentation Recording)

NASA Astrophysics Data System (ADS)

Bakhshetyan, Karen; Melkonyan, Gurgen G.; Galstian, Tigran V.; Saghatelyan, Armen

2015-10-01

Natural or "self" alignment of molecular complexes in living tissue represents many similarities with liquid crystals (LC), which are anisotropic liquids. The orientational characteristics of those complexes may be related to many important functional parameters and their study may reveal important pathologies. The know-how, accumulated thanks to the study of LC materials, may thus be used to this end. One of the traditionally used methods, to characterize those materials, is the polarized light imaging (PLI) that allows for label-free analysis of anisotropic structures in the brain tissue and can be used, for example, for the analysis of myelinated fiber bundles. In the current work, we first attempted to apply the PLI on the mouse histological brain sections to create a map of anisotropic structures using cross-polarizer transmission light. Then we implemented the PLI for comparative study of histological sections of human postmortem brain samples under normal and pathological conditions, such as Parkinson's disease (PD). Imaging the coronal, sagittal and horizontal sections of mouse brain allowed us to create a false color-coded fiber orientation map under polarized light. In human brain datasets for both control and PD groups we measured the pixel intensities in myelin-rich subregions of internal capsule and normalized these to non-myelinated background signal from putamen and caudate nucleus. Quantification of intensities revealed a statistically significant reduction of fiber intensity of PD compared to control subjects (2.801 +/- 0.303 and 3.724 +/- 0.07 respectively; *p < 0.05). Our study confirms the validity of PLI method for visualizing myelinated axonal fibers. This relatively simple technique can become a promising tool for study of neurodegenerative diseases where labeling-free imaging is an important benefit.

In situ enzymatic activity of transglutaminase isoforms on brain tissue sections of rodents: A new approach to monitor differences in post-translational protein modifications during neurodegeneration.

PubMed

Schulze-Krebs, Anja; Canneva, Fabio; Schnepf, Rebecca; Dobner, Julia; Dieterich, Walburga; von Hörsten, Stephan

2016-01-15

Mammalian transglutaminases (TGs) catalyze the irreversible post-translational modifications of proteins, the most prominent of which is the calcium-dependent formation of covalent acyl transfers between the γ-carboxamide group of glutamine and the ε-amino-group of lysine (GGEL-linkage). In the central nervous system, at least four TG isoforms are present and some of them are differentially expressed under pathological conditions in human patients. However, the precise TG-isoform-dependent enzymatic activities in the brain as well as their anatomical distribution are unknown. Specificity of the used biotinylated peptides was analyzed using an in vitro assay. Isoform-specific TG activity was evaluated in in vitro and in situ studies, using brain extracts and native brain tissue obtained from rodents. Our method allowed us to reveal in vitro and in situ TG-isoform-dependent enzymatic activity in brain extracts and tissue of rats and mice, with a specific focus on TG6. In situ activity of this isoform varied between BACHD mice in comparison to their wt controls. TG isozyme-specific activity can be detected by isoform-specific biotinylated peptides in brain tissue sections of rodents to reveal differences in the anatomical and/or subcellular distribution of TG activity. Our findings yield the basis for a broader application of this method for the screening of pathological expression and activity of TGs in a variety of animal models of human diseases, as in the case of neurodegenerative conditions such as Huntington׳s, Parkinson׳s and Alzheimer׳s, where protein modification is involved as a key mechanism of disease progression. Copyright © 2015 Elsevier B.V. All rights reserved.

Radiotracer properties determined by high performance liquid chromatography: a potential tool for brain radiotracer discovery.

PubMed

Tavares, Adriana Alexandre S; Lewsey, James; Dewar, Deborah; Pimlott, Sally L

2012-01-01

Previously, development of novel brain radiotracers has largely relied on simple screening tools. Improved selection methods at the early stages of radiotracer discovery and an increased understanding of the relationships between in vitro physicochemical and in vivo radiotracer properties are needed. We investigated if high performance liquid chromatography (HPLC) methodologies could provide criteria for lead candidate selection by comparing HPLC measurements with radiotracer properties in humans. Ten molecules, previously used as radiotracers in humans, were analysed to obtain the following measures: partition coefficient (Log P); permeability (P(m)); percentage of plasma protein binding (%PPB); and membrane partition coefficient (K(m)). Relationships between brain entry measurements (Log P, P(m) and %PPB) and in vivo brain percentage injected dose (%ID); and K(m) and specific binding in vivo (BP(ND)) were investigated. Log P values obtained using in silico packages and flask methods were compared with Log P values obtained using HPLC. The modelled associations with %ID were stronger for %PPB (r(2)=0.65) and P(m) (r(2)=0.77) than for Log P (r(2)=0.47) while 86% of BP(ND) variance was explained by K(m). Log P values were variable dependant on the methodology used. Log P should not be relied upon as a predictor of blood-brain barrier penetration during brain radiotracer discovery. HPLC measurements of permeability, %PPB and membrane interactions may be potentially useful in predicting in vivo performance and hence allow evaluation and ranking of compound libraries for the selection of lead radiotracer candidates at early stages of radiotracer discovery. Copyright © 2012 Elsevier Inc. All rights reserved.

A novel behavioral paradigm for assessing concept of nests in mice

PubMed Central

Kuang, Hui; Mei, Bing; Cui, Zhenzhong; Lin, Longnian; Tsien, Joe Z.

2013-01-01

Abstract concepts in the brain enable humans to efficiently and correctly recognize and categorize a seemingly infinite amount of objects and daily events. Such abstract generalization abilities are traditionally considered to be unique to humans and perhaps non-human primates. However, emerging neurophysiological recordings indicate the existence of neural correlates for the abstract concept of nests in the mouse brain. To facilitate the molecular and genetic analyses of concepts in the mouse model, we have developed a nest generalization test based on mice’s natural behavior. We show that inducible and forebrain-specific NMDA receptor knockout results in pronounced impairment in this test. Interestingly, this generalization deficit could be gradually compensated for over time by repeated experiences even in face of the continued deficit in object recognition memory. On the contrast, the forebrain-specific presenilin-1 knockout mice, which have subtle phenotypes, were normal in performing this test. Therefore, our study not only establishes a quantitative method for assessing the nest concept in mice, but also demonstrates its great potential in combining powerful mouse genetics for dissecting the molecular basis of concept formation in the brain. PMID:20350568

Using human extra-cortical local field potentials to control a switch

NASA Astrophysics Data System (ADS)

Kennedy, Philip; Andreasen, Dinal; Ehirim, Princewill; King, Brandon; Kirby, Todd; Mao, Hui; Moore, Melody

2004-06-01

Individuals with profound paralysis and mutism require a communication channel. Traditional assistive technology devices eventually fail, especially in the case of amyotrophic lateral sclerosis (ALS) subjects who gradually become totally locked-in. A direct brain-to-computer interface that provides switch functions can provide a direct communication channel to the external world. Electroencephalographic (EEG) signals recorded from scalp electrodes are significantly degraded due to skull and scalp attenuation and ambient noise. The present system using conductive skull screws allows more reliable access to cortical local field potentials (LFPs) without entering the brain itself. We describe an almost locked-in human subject with ALS who activated a switch using online time domain detection techniques. Frequency domain analysis of his LFP activity demonstrates this to be an alternative method of detecting switch activation intentions. With this brain communicator system it is reasonable to expect that locked-in, but cognitively intact, humans will always be able to communicate. Financial disclosure. Authors PK and DA may derive some financial gain from the sale of this device. A patent has been applied under US and international law: 10/675,703.

The integration processing of the visual and auditory information in videos of real-world events: an ERP study.

PubMed

Liu, Baolin; Wang, Zhongning; Jin, Zhixing

2009-09-11

In real life, the human brain usually receives information through visual and auditory channels and processes the multisensory information, but studies on the integration processing of the dynamic visual and auditory information are relatively few. In this paper, we have designed an experiment, where through the presentation of common scenario, real-world videos, with matched and mismatched actions (images) and sounds as stimuli, we aimed to study the integration processing of synchronized visual and auditory information in videos of real-world events in the human brain, through the use event-related potentials (ERPs) methods. Experimental results showed that videos of mismatched actions (images) and sounds would elicit a larger P400 as compared to videos of matched actions (images) and sounds. We believe that the P400 waveform might be related to the cognitive integration processing of mismatched multisensory information in the human brain. The results also indicated that synchronized multisensory information would interfere with each other, which would influence the results of the cognitive integration processing.

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

Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI.

PubMed

Moeskops, Pim; de Bresser, Jeroen; Kuijf, Hugo J; Mendrik, Adriënne M; Biessels, Geert Jan; Pluim, Josien P W; Išgum, Ivana

2018-01-01

Automatic segmentation of brain tissues and white matter hyperintensities of presumed vascular origin (WMH) in MRI of older patients is widely described in the literature. Although brain abnormalities and motion artefacts are common in this age group, most segmentation methods are not evaluated in a setting that includes these items. In the present study, our tissue segmentation method for brain MRI was extended and evaluated for additional WMH segmentation. Furthermore, our method was evaluated in two large cohorts with a realistic variation in brain abnormalities and motion artefacts. The method uses a multi-scale convolutional neural network with a T 1 -weighted image, a T 2 -weighted fluid attenuated inversion recovery (FLAIR) image and a T 1 -weighted inversion recovery (IR) image as input. The method automatically segments white matter (WM), cortical grey matter (cGM), basal ganglia and thalami (BGT), cerebellum (CB), brain stem (BS), lateral ventricular cerebrospinal fluid (lvCSF), peripheral cerebrospinal fluid (pCSF), and WMH. Our method was evaluated quantitatively with images publicly available from the MRBrainS13 challenge ( n  = 20), quantitatively and qualitatively in relatively healthy older subjects ( n  = 96), and qualitatively in patients from a memory clinic ( n  = 110). The method can accurately segment WMH (Overall Dice coefficient in the MRBrainS13 data of 0.67) without compromising performance for tissue segmentations (Overall Dice coefficients in the MRBrainS13 data of 0.87 for WM, 0.85 for cGM, 0.82 for BGT, 0.93 for CB, 0.92 for BS, 0.93 for lvCSF, 0.76 for pCSF). Furthermore, the automatic WMH volumes showed a high correlation with manual WMH volumes (Spearman's ρ  = 0.83 for relatively healthy older subjects). In both cohorts, our method produced reliable segmentations (as determined by a human observer) in most images (relatively healthy/memory clinic: tissues 88%/77% reliable, WMH 85%/84% reliable) despite various degrees of brain abnormalities and motion artefacts. In conclusion, this study shows that a convolutional neural network-based segmentation method can accurately segment brain tissues and WMH in MR images of older patients with varying degrees of brain abnormalities and motion artefacts.

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.

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.

Determining the degree of synchronism for intermittent phase synchronization in human electroencephalography data

NASA Astrophysics Data System (ADS)

Koloskova, A. D.; Moskalenko, O. I.

2017-05-01

The phenomenon of intermittent phase synchronization during development of epileptic activity in human beings has been discovered based on EEG data. The presence of synchronous behavior phases has been detected both during spike-wave discharges and in the regions of background activity of the brain. The degree of synchronism in the intermittent phase-synchronization regime in both cases has been determined, and it has been established that spike-wave discharges are characterized by a higher degree of synchronism than exists in the regions of background activity of the brain. To determine the degree of synchronism, a modified method of evaluating zero conditional Lyapunov exponents from time series is proposed.

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

On the applicability of brain reading for predictive human-machine interfaces in robotics.

PubMed

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors.

On the Applicability of Brain Reading for Predictive Human-Machine Interfaces in Robotics

PubMed Central

Kirchner, Elsa Andrea; Kim, Su Kyoung; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Krell, Mario Michael; Tabie, Marc; Fahle, Manfred

2013-01-01

The ability of today's robots to autonomously support humans in their daily activities is still limited. To improve this, predictive human-machine interfaces (HMIs) can be applied to better support future interaction between human and machine. To infer upcoming context-based behavior relevant brain states of the human have to be detected. This is achieved by brain reading (BR), a passive approach for single trial EEG analysis that makes use of supervised machine learning (ML) methods. In this work we propose that BR is able to detect concrete states of the interacting human. To support this, we show that BR detects patterns in the electroencephalogram (EEG) that can be related to event-related activity in the EEG like the P300, which are indicators of concrete states or brain processes like target recognition processes. Further, we improve the robustness and applicability of BR in application-oriented scenarios by identifying and combining most relevant training data for single trial classification and by applying classifier transfer. We show that training and testing, i.e., application of the classifier, can be carried out on different classes, if the samples of both classes miss a relevant pattern. Classifier transfer is important for the usage of BR in application scenarios, where only small amounts of training examples are available. Finally, we demonstrate a dual BR application in an experimental setup that requires similar behavior as performed during the teleoperation of a robotic arm. Here, target recognition processes and movement preparation processes are detected simultaneously. In summary, our findings contribute to the development of robust and stable predictive HMIs that enable the simultaneous support of different interaction behaviors. PMID:24358125

Spectral properties of the temporal evolution of brain network structure.

PubMed

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Spectral properties of the temporal evolution of brain network structure

NASA Astrophysics Data System (ADS)

Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

2015-12-01

The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

Reconsidering the evolution of brain, cognition, and behavior in birds and mammals

PubMed Central

Willemet, Romain

2013-01-01

Despite decades of research, some of the most basic issues concerning the extraordinarily complex brains and behavior of birds and mammals, such as the factors responsible for the diversity of brain size and composition, are still unclear. This is partly due to a number of conceptual and methodological issues. Determining species and group differences in brain composition requires accounting for the presence of taxon-cerebrotypes and the use of precise statistical methods. The role of allometry in determining brain variables should be revised. In particular, bird and mammalian brains appear to have evolved in response to a variety of selective pressures influencing both brain size and composition. “Brain” and “cognition” are indeed meta-variables, made up of the variables that are ecologically relevant and evolutionarily selected. External indicators of species differences in cognition and behavior are limited by the complexity of these differences. Indeed, behavioral differences between species and individuals are caused by cognitive and affective components. Although intra-species variability forms the basis of species evolution, some of the mechanisms underlying individual differences in brain and behavior appear to differ from those between species. While many issues have persisted over the years because of a lack of appropriate data or methods to test them; several fallacies, particularly those related to the human brain, reflect scientists' preconceptions. The theoretical framework on the evolution of brain, cognition, and behavior in birds and mammals should be reconsidered with these biases in mind. PMID:23847570