Promising approaches to circumvent the blood-brain barrier: progress, pitfalls and clinical prospects in brain cancer.

Science.gov (United States)

Papademetriou, Iason T; Porter, Tyrone

2015-01-01

Brain drug delivery is a major challenge for therapy of central nervous system (CNS) diseases. Biochemical modifications of drugs or drug nanocarriers, methods of local delivery, and blood-brain barrier (BBB) disruption with focused ultrasound and microbubbles are promising approaches which enhance transport or bypass the BBB. These approaches are discussed in the context of brain cancer as an example in CNS drug development. Targeting to receptors enabling transport across the BBB offers noninvasive delivery of small molecule and biological cancer therapeutics. Local delivery methods enable high dose delivery while avoiding systemic exposure. BBB disruption with focused ultrasound and microbubbles offers local and noninvasive treatment. Clinical trials show the prospects of these technologies and point to challenges for the future.

A Demonstration of Approach and Avoidance Conflicts

Science.gov (United States)

Terry, W. Scott

2010-01-01

Choosing between 2 unpleasant alternatives (Would you rather be less intelligent or less attractive?) is more difficult than choosing between two desirable options (Would you rather be more intelligent or more attractive?). Here I describe a classroom demonstration of avoidance-avoidance conflicts. Students make a series of approach-approach and…

Approach of Complex Networks for the Determination of Brain Death

International Nuclear Information System (INIS)

Sun Wei-Gang; Cao Jian-Ting; Wang Ru-Bin

2011-01-01

In clinical practice, brain death is the irreversible end of all brain activity. Compared to current statistical methods for the determination of brain death, we focus on the approach of complex networks for real-world electroencephalography in its determination. Brain functional networks constructed by correlation analysis are derived, and statistical network quantities used for distinguishing the patients in coma or brain death state, such as average strength, clustering coefficient and average path length, are calculated. Numerical results show that the values of network quantities of patients in coma state are larger than those of patients in brain death state. Our findings might provide valuable insights on the determination of brain death. (cross-disciplinary physics and related areas of science and technology)

[Immunocytochemical demonstration of astrocytes in brain sections combined with Nissl staining].

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Korzhevskiĭ, D E; Otellin, V A

2004-01-01

The aim of the present study was to develop an easy and reliable protocol of combined preparation staining, which would unite the advantages of immunocytochemical demonstration of astrocytes with the availability to evaluate functional state of neurons provided by Nissl technique. The presented protocol of paraffin sections processing allows to retain high quality of tissue structure and provides for selective demonstration of astrocytes using the monoclonal antibodies against glial fibrillary acidic protein and contrast Nissl staining of cells. The protocol can be used without any changes for processing of brain sections obtained from the humans and other mammals with the exception of mice and rabbits.

A new methodical approach in neuroscience: assessing inter-personal brain coupling using functional near-infrared imaging (fNIRI hyperscanning

Directory of Open Access Journals (Sweden)

Felix eScholkmann

2013-11-01

Full Text Available Since the first demonstration of how to simultaneously measure brain activity using functional magnetic resonance imaging (fMRI on two subjects about 10 years ago, a new paradigm in neuroscience is emerging: the assessment of the inter-brain coupling between two or more subjects, termed hyperscanning. The hyperscanning approach has the potential to enable a new view on how the brain works and will reveal as yet undiscovered brain functions based on brain-to-brain coupling, since the single-subject setting cannot capture them. In particular, functional near-infrared imaging (fNIRI hyperscanning is a promising new method, offering a cost-effective, easy to apply and reliable technology to measure inter-personal interactions in a natural context. In this short review we report on fNIRI hyperscanning studies published so far and summarize opportunities and challenges for future studies.

Normal and abnormal fetal brain development during the third trimester as demonstrated by neurosonography

International Nuclear Information System (INIS)

Malinger, G.; Lev, D.; Lerman-Sagie, T.

2006-01-01

The multiplanar neurosonographic examination of the fetus enables superb visualization of brain anatomy during pregnancy. The examination may be performed using a transvaginal or a transfundal approach and it is indicated in patients at high risk for CNS anomalies or in those with a suspicious finding during a routine examination. The purpose of this paper is to present a description of the normal brain and of abnormal findings usually diagnosed late in pregnancy, including malformations of cortical development, infratentorial anomalies, and prenatal insults

An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States

Science.gov (United States)

2015-12-22

AFRL-AFOSR-VA-TR-2016-0037 An Integrated Neuroscience and Engineering Approach to Classifying Human Brain-States Adrian Lee UNIVERSITY OF WASHINGTON...to 14-09-2015 4. TITLE AND SUBTITLE An Integrated Neuroscience and Engineering Approach to Classifying Human Brain- States 5a.  CONTRACT NUMBER 5b...specific cognitive states remains elusive, owing perhaps to limited crosstalk between the fields of neuroscience and engineering. Here, we report a

Incidence and prognostic significance of postoperative complications demonstrated on CT after brain tumor removal

Energy Technology Data Exchange (ETDEWEB)

Fukamachi, Akira; Koizumi, Hidehito; Kimura, Ryoichi; Nukui, Hideaki; Kunimine, Hideo

1987-06-01

We surveyed the computed tomographic (CT) findings in 273 patients who had undergone 301 craniotomies for brain tumors to determine the incidence and clinical outcome of the postoperative complications demonstrated on CT. The frequencies of medium-sized or large postoperative lesions were as follows: intracerebral hemorrhage, 11% of 301 operations; subdural fluid collection, 8%; brain edema, 6%; extradural hemorrhage, 4%; cerebral infarction, 3%; ventricular enlargement, 3%; intraventricular hemorrhage, 2%; chronic subdural hematoma, 1%; porencephalic cyst, 0.7%; tension pneumocephalus, 0.7%. In association with these complications, poor outcomes (deaths) developed with the following frequencies: intracerebral hemorrhage including an association with other types of hemorrhage, 4% (deaths, 2%) of 301 operations; cerebral infarction, 1% (deaths, 0.7%); brain edema, 0.7% (deaths, 0.7%); simple intraventricular hemorrhage, 0.3% (no deaths); tension pneumocephalus, 0.3% (no deaths). From these results, we conclude that medium-sized or large intracerebral hemorrhage, massive cerebral infarction and edema have a grave clinical significance in the postoperative course of patients with brain tumors.

Magnetic Resonance and Brain Function. Approaches from Physics

International Nuclear Information System (INIS)

Maraviglia, B.

1999-01-01

In the last decade of this millennium, while, on the one hand, the international scientific community has focused with increasing endeavour on the research about the great unknown of the mechanism and the pathologies of the human brain, on the other hand, the NMR community has achieved some important results, which should widely affect, in the future, the possibility of understanding the function and disfunction of the human brain. In the early 1980's, the beginning of the application of Magnetic Resonance Imaging (MRI) to the morphological study of the brain in vivo, has played an extraordinary role, which, since then, placed MRI in a leading position among the methodologies used for investigation and diagnostics of the Central Nervous System. In the 1990s, the objective of finding new means, based on MRI, capable of giving functional and metabolic information, with the highest possible space resolution, drove the scientists towards different approaches. Among these, the first one to generate a breakthrough in the localization of specific cerebral functions was the Blood Oxygen Level Development (BOLD) MRI. A very wide range of applications followed the discovery of BOLD imaging. Still, this method gives an indirect information of the localization of functions, via the variation of oxygen release and deoxyhemoglobin formation. Of course, a high-resolution spatial distribution of the metabolites, crucial to brain function, would give a deeper insight into the occurring processes. This finality is aimed at by the Double Magnetic Resonance methods, which are developing new procedures able to detect some metabolites with increasing sensitivity and resolution. A third new promising approach to functional MRI should derive from the use of hyperpolarized, opens a series of potential applications to the study of brain function

Brain tissues volume measurements from 2D MRI using parametric approach

Science.gov (United States)

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.

Incidence and prognostic significance of postoperative complications demonstrated on CT after brain tumor removal

International Nuclear Information System (INIS)

Fukamachi, Akira; Koizumi, Hidehito; Kimura, Ryoichi; Nukui, Hideaki; Kunimine, Hideo.

1987-01-01

We surveyed the computed tomographic (CT) findings in 273 patients who had undergone 301 craniotomies for brain tumors to determine the incidence and clinical outcome of the postoperative complications demonstrated on CT. The frequencies of medium-sized or large postoperative lesions were as follows: intracerebral hemorrhage, 11 % of 301 operations; subdural fluid collection, 8 %; brain edema, 6 %; extradural hemorrhage, 4 %; cerebral infarction, 3 %; ventricular enlargement, 3 %; intraventricular hemorrhage, 2 %; chronic subdural hematoma, 1 %; porencephalic cyst, 0.7 %; tension pneumocephalus, 0.7 %. In association with these complications, poor outcomes (deaths) developed with the following frequencies: intracerebral hemorrhage including an association with other types of hemorrhage, 4 % (deaths, 2 %) of 301 operations; cerebral infarction, 1 % (deaths, 0.7 %); brain edema, 0.7 % (deaths, 0.7 %); simple intraventricular hemorrhage, 0.3 % (no deaths); tension pneumocephalus, 0.3 % (no deaths). From these results, we conclude that medium-sized or large intracerebral hemorrhage, massive cerebral infarction and edema have a grave clinical significance in the postoperative course of patients with brain tumors. (author)

Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.

Science.gov (United States)

Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

2016-08-18

This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

An evolutionary computation approach to examine functional brain plasticity

Directory of Open Access Journals (Sweden)

Arnab eRoy

2016-04-01

Full Text Available One common research goal in systems neurosciences is to understand how the functional relationship between a pair of regions of interest (ROIs evolves over time. Examining neural connectivity in this way is well-suited for the study of developmental processes, learning, and even in recovery or treatment designs in response to injury. For most fMRI based studies, the strength of the functional relationship between two ROIs is defined as the correlation between the average signal representing each region. The drawback to this approach is that much information is lost due to averaging heterogeneous voxels, and therefore, the functional relationship between a ROI-pair that evolve at a spatial scale much finer than the ROIs remain undetected. To address this shortcoming, we introduce a novel evolutionary computation (EC based voxel-level procedure to examine functional plasticity between an investigator defined ROI-pair by simultaneously using subject-specific BOLD-fMRI data collected from two sessions seperated by finite duration of time. This data-driven procedure detects a sub-region composed of spatially connected voxels from each ROI (a so-called sub-regional-pair such that the pair shows a significant gain/loss of functional relationship strength across the two time points. The procedure is recursive and iteratively finds all statistically significant sub-regional-pairs within the ROIs. Using this approach, we examine functional plasticity between the default mode network (DMN and the executive control network (ECN during recovery from traumatic brain injury (TBI; the study includes 14 TBI and 12 healthy control subjects. We demonstrate that the EC based procedure is able to detect functional plasticity where a traditional averaging based approach fails. The subject-specific plasticity estimates obtained using the EC-procedure are highly consistent across multiple runs. Group-level analyses using these plasticity estimates showed an increase in

Current approaches to enhance CNS delivery of drugs across the brain barriers

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Lu CT

2014-05-01

Full Text Available Cui-Tao Lu,1 Ying-Zheng Zhao,2,3 Ho Lun Wong,4 Jun Cai,5 Lei Peng,2 Xin-Qiao Tian1 1The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou City, Zhejiang Province, People’s Republic of China; 2Hainan Medical College, Haikou City, Hainan Province, People’s Republic of China; 3College of Pharmaceutical Sciences, Wenzhou Medical University, Zhejiang Province, People’s Republic of China; 4School of Pharmacy, Temple University, Philadelphia, PA, USA; 5Departments of Pediatrics and Anatomical Sciences and Neurobiology, University of Louisville School of Medicine Louisville, KY, USA Abstract: Although many agents have therapeutic potentials for central nervous system (CNS diseases, few of these agents have been clinically used because of the brain barriers. As the protective barrier of the CNS, the blood–brain barrier and the blood–cerebrospinal fluid barrier maintain the brain microenvironment, neuronal activity, and proper functioning of the CNS. Different strategies for efficient CNS delivery have been studied. This article reviews the current approaches to open or facilitate penetration across these barriers for enhanced drug delivery to the CNS. These approaches are summarized into three broad categories: noninvasive, invasive, and miscellaneous techniques. The progresses made using these approaches are reviewed, and the associated mechanisms and problems are discussed. Keywords: drug delivery system, blood–brain barrier (BBB, central nervous system, brain-targeted therapy, cerebrospinal fluid (CSF

A study of brain networks associated with swallowing using graph-theoretical approaches.

Directory of Open Access Journals (Sweden)

Bo Luan

Full Text Available Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, [Formula: see text] years of age. To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.

Biophysical modeling of high field diffusion MRI demonstrates micro-structural aberration in chronic mild stress rat brain

DEFF Research Database (Denmark)

Khan, Ahmad Raza; Chuhutin, Andrey; Wiborg, Ove

2016-01-01

anhedonia is considered to be a realistic model of depression in studies of animal subjects. Stereological and neuronal tracing techniques have demonstrated persistent remodeling of microstructure in hippocampus, prefrontal cortex and amygdala of CMS brains. Recent developments in diffusion MRI (d...... microstructure in the hippocampus, prefrontal cortex, caudate putamen and amygdala regions of CMS rat brains by comparison to brains from normal controls. To validate findings of CMS induced microstructural alteration, histology was performed to determine neurite, nuclear and astrocyte density. d-MRI based...... neurite density and tensor-based mean kurtosis (MKT) were significantly higher, while mean diffusivity (MD), extracellular diffusivity (Deff) and intra-neurite diffusivity(DL) were significantly lower in the amygdala of CMS rat brains. Deff was also significantly lower in the hippocampus and caudate...

ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation.

Science.gov (United States)

Adeshina, A M; Hashim, R

2016-03-01

Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the

On one approach to health protection: Music of the brain.

Science.gov (United States)

Fedotchev, Alexander; Radchenko, Grigoriy; Zemlianaia, Anna

2017-10-18

This review presents the current status of a method for prevention and timely correction of human functional disturbances that was first proposed by Russian neurologist Ya.I. Levin in 1998 and further developed by the authors. The approach is named "Music of the Brain" and is based on musical or music-like stimulation organized in strict accordance with the biopotentials of a patient's brain. Initial studies on the music of the brain approach were analyzed, and its limitations were noted. To enhance the efficiency and usability of the approach, several combinations of music therapy with neurofeedback technique - musical neurofeedback - were developed. Enhanced efficiency of the approach has been shown for correction of functional disturbances during pregnancy and for elimination of stress-induced states in high technology specialists. The use and advantages of musical neurofeedback technology for increasing human cognitive activity, correcting sleep disturbances and treatment of disorders of attention were verified. After further development and testing the approach may be suited for a wide range of therapeutic and rehabilitation procedures in the protection of public health.

Demonstration of endogenous imipramine like material in rat brain

International Nuclear Information System (INIS)

Rehavi, M.; Ventura, I.; Sarne, Y.

1985-01-01

The extraction and partial purification of an endogenous imipramine-like material from rat brain is described. The endogenous factor obtained after gel filtration and silica chromatography inhibits [ 3 H] imipramine specific binding and mimics the inhibitory effect of imipramine on [ 3 H] serotonin uptake in both brain and platelet preparations. The effects of the endogenous material are dose-dependent and it inhibits [ 3 H] imipramine binding in a competitive fashion. The factor is unevenly distributed in the brain with high concentration in the hypothalamus and low concentration in the cerebellum

Brain networks, structural realism, and local approaches to the scientific realism debate.

Science.gov (United States)

Yan, Karen; Hricko, Jonathon

2017-08-01

We examine recent work in cognitive neuroscience that investigates brain networks. Brain networks are characterized by the ways in which brain regions are functionally and anatomically connected to one another. Cognitive neuroscientists use various noninvasive techniques (e.g., fMRI) to investigate these networks. They represent them formally as graphs. And they use various graph theoretic techniques to analyze them further. We distinguish between knowledge of the graph theoretic structure of such networks (structural knowledge) and knowledge of what instantiates that structure (nonstructural knowledge). And we argue that this work provides structural knowledge of brain networks. We explore the significance of this conclusion for the scientific realism debate. We argue that our conclusion should not be understood as an instance of a global structural realist claim regarding the structure of the unobservable part of the world, but instead, as a local structural realist attitude towards brain networks in particular. And we argue that various local approaches to the realism debate, i.e., approaches that restrict realist commitments to particular theories and/or entities, are problematic insofar as they don't allow for the possibility of such a local structural realist attitude. Copyright © 2017 Elsevier Ltd. All rights reserved.

Systems approach to the study of brain damage in the very preterm newborn

Science.gov (United States)

Leviton, Alan; Gressens, Pierre; Wolkenhauer, Olaf; Dammann, Olaf

2015-01-01

Background: A systems approach to the study of brain damage in very preterm newborns has been lacking. Methods: In this perspective piece, we offer encephalopathy of prematurity as an example of the complexity and interrelatedness of brain-damaging molecular processes that can be initiated inflammatory phenomena. Results: Using three transcription factors, nuclear factor-kappa B (NF-κB), Notch-1, and nuclear factor erythroid 2 related factor 2 (NRF2), we show the inter-connectedness of signaling pathways activated by some antecedents of encephalopathy of prematurity. Conclusions: We hope that as biomarkers of exposures and processes leading to brain damage in the most immature newborns become more readily available, those who apply a systems approach to the study of neuroscience can be persuaded to study the pathogenesis of brain disorders in the very preterm newborn. PMID:25926780

Electrophysiological evidences demonstrating differences in brain functions between nonmusicians and musicians.

Science.gov (United States)

Zhang, Li; Peng, Weiwei; Chen, Jie; Hu, Li

2015-09-04

Long-term music training can improve sensorimotor skills, as playing a musical instrument requires the functional integration of information related to multimodal sensory perception and motor execution. This functional integration often leads to functional reorganization of cerebral cortices, including auditory, visual, and motor areas. Moreover, music appreciation can modulate emotions (e.g., stress relief), and long-term music training can enhance a musician's self-control and self-evaluation ability. Therefore, the neural processing of music can also be related to certain higher brain cognitive functions. However, evidence demonstrating that long-term music training modulates higher brain functions is surprisingly rare. Here, we aimed to comprehensively explore the neural changes induced by long-term music training by assessing the differences of transient and quasi-steady-state auditory-evoked potentials between nonmusicians and musicians. We observed that compared to nonmusicians, musicians have (1) larger high-frequency steady-state responses, which reflect the auditory information processing within the sensory system, and (2) smaller low-frequency vertex potentials, which reflect higher cognitive information processing within the novelty/saliency detection system. Therefore, we speculate that long-term music training facilitates "bottom-up" auditory information processing in the sensory system and enhances "top-down" cognitive inhibition of the novelty/saliency detection system.

Characterization of a sequential pipeline approach to automatic tissue segmentation from brain MR Images

International Nuclear Information System (INIS)

Hou, Zujun; Huang, Su

2008-01-01

Quantitative analysis of gray matter and white matter in brain magnetic resonance imaging (MRI) is valuable for neuroradiology and clinical practice. Submission of large collections of MRI scans to pipeline processing is increasingly important. We characterized this process and suggest several improvements. To investigate tissue segmentation from brain MR images through a sequential approach, a pipeline that consecutively executes denoising, skull/scalp removal, intensity inhomogeneity correction and intensity-based classification was developed. The denoising phase employs a 3D-extension of the Bayes-Shrink method. The inhomogeneity is corrected by an improvement of the Dawant et al.'s method with automatic generation of reference points. The N3 method has also been evaluated. Subsequently the brain tissue is segmented into cerebrospinal fluid, gray matter and white matter by a generalized Otsu thresholding technique. Intensive comparisons with other sequential or iterative methods have been carried out using simulated and real images. The sequential approach with judicious selection on the algorithm selection in each stage is not only advantageous in speed, but also can attain at least as accurate segmentation as iterative methods under a variety of noise or inhomogeneity levels. A sequential approach to tissue segmentation, which consecutively executes the wavelet shrinkage denoising, scalp/skull removal, inhomogeneity correction and intensity-based classification was developed to automatically segment the brain tissue into CSF, GM and WM from brain MR images. This approach is advantageous in several common applications, compared with other pipeline methods. (orig.)

Confirming the diversity of the brain after normalization: an approach based on identity authentication.

Directory of Open Access Journals (Sweden)

Fanglin Chen

Full Text Available During the development of neuroimaging, numerous analyses were performed to identify population differences, such as studies on age, gender, and diseases. Researchers first normalized the brain image and then identified features that represent key differences between groups. In these studies, the question of whether normalization (a pre-processing step widely used in neuroimaging studies reduces the diversity of brains was largely ignored. There are a few studies that identify the differences between individuals after normalization. In the current study, we analyzed brain diversity on an individual level, both qualitatively and quantitatively. The main idea was to utilize brain images for identity authentication. First, the brain images were normalized and registered. Then, a pixel-level matching method was developed to compute the identity difference between different images for matching. Finally, by analyzing the performance of the proposed brain recognition strategy, the individual differences in brain images were evaluated. Experimental results on a 150-subject database showed that the proposed approach could achieve a 100% identification ratio, which indicated distinct differences between individuals after normalization. Thus, the results proved that after the normalization stage, brain images retain their main distinguishing information and features. Based on this result, we suggest that diversity (individual differences should be considered when conducting group analysis, and that this approach may facilitate group pattern classification.

Educational games for brain health: revealing their unexplored potential through a neurocognitive approach

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Patrick eFissler

2015-07-01

Full Text Available Educational games link the motivational nature of games with learning of knowledge and skills. Here, we go beyond effects on these learning outcomes. We review two lines of evidence which indicate the currently unexplored potential of educational games to promote brain health: First, gaming with specific neurocognitive demands (e.g., executive control, and second, educational learning experiences (e.g., studying foreign languages improve brain health markers. These markers include cognitive ability, brain function, and brain structure. As educational games allow the combination of specific neurocognitive demands with educational learning experiences, they seem to be optimally suited for promoting brain health. We propose a neurocognitive approach to reveal this unexplored potential of educational games in future research.

Inflammation, caffeine and adenosine in neonatal hypoxic ischemic brain injury

OpenAIRE

Winerdal, Max

2014-01-01

Background: Brain injury during the neonatal period has potentially lifelong consequences for a child. Perinatal infections and inflammation can induce preterm birth and unfavorable cognitive development, Thus inflammation has received enthusiastic interest for potential therapeutic approaches seeking to protect the newborn brain. Experimental evidence demonstrates that inflammation induces brain injury succeeding the initial insult. A key cytokine in brain injury is the tumor necrosis factor...

A network of genes, genetic disorders, and brain areas.

Directory of Open Access Journals (Sweden)

Satoru Hayasaka

Full Text Available The network-based approach has been used to describe the relationship among genes and various phenotypes, producing a network describing complex biological relationships. Such networks can be constructed by aggregating previously reported associations in the literature from various databases. In this work, we applied the network-based approach to investigate how different brain areas are associated to genetic disorders and genes. In particular, a tripartite network with genes, genetic diseases, and brain areas was constructed based on the associations among them reported in the literature through text mining. In the resulting network, a disproportionately large number of gene-disease and disease-brain associations were attributed to a small subset of genes, diseases, and brain areas. Furthermore, a small number of brain areas were found to be associated with a large number of the same genes and diseases. These core brain regions encompassed the areas identified by the previous genome-wide association studies, and suggest potential areas of focus in the future imaging genetics research. The approach outlined in this work demonstrates the utility of the network-based approach in studying genetic effects on the brain.

Potential new approaches for the development of brain imaging agents for single-photon applications

International Nuclear Information System (INIS)

Knapp, F.F. Jr.; Srivastava, P.C.

1984-01-01

This paper describes new strategies for the brain-specific delivery of radionuclides that can be used to evaluate regional cerebral perfusion by single photon imaging techniques. A description of several examples of interesting new strategies that have recently been reported is presented. A new approach at this institution for the brain-specific delivery of radioiodinated iodophenylalkyl-substituted dihyronicotinamide systems is described which shows good brain uptake and retention in preliminary studies in rats. Following transport into the brain these agents appear to undergo facile intracerebral oxidation to the quaternized analogues which do not recross the intact blood-brain barrier and so are effectively trapped in the brain. 49 refs., 9 figs., 1 tab

Cerebral abnormalities in cocaine abusers: Demonstration by SPECT perfusion brain scintigraphy. Work in progress

International Nuclear Information System (INIS)

Tumeh, S.S.; Nagel, J.S.; English, R.J.; Moore, M.; Holman, B.L.

1990-01-01

Single photon emission computed tomography (SPECT) perfusion brain scans with iodine-123 isopropyl iodoamphetamine (IMP) were obtained in 12 subjects who acknowledged using cocaine on a sporadic to a daily basis. The route of cocaine administration varied from nasal to intravenous. Concurrent abuse of other drugs was also reported. None of the patients were positive for human immunodeficiency virus. Brain scans demonstrated focal defects in 11 subjects, including seven who were asymptomatic, and no abnormality in one. Among the findings were scattered focal cortical deficits, which were seen in several patients and which ranged in severity from small and few to multiple and large, with a special predilection for the frontal and temporal lobes. No perfusion deficits were seen on I-123 SPECT images in five healthy volunteers. Focal alterations in cerebral perfusion are seen commonly in asymptomatic drug users, and these focal deficits are readily depicted by I-123 IMP SPECT

Brain based learning with contextual approach to mathematics achievement

Directory of Open Access Journals (Sweden)

V Kartikaningtyas

2017-12-01

Full Text Available The aim of this study was to know the effect of Brain Based Learning (BBL with a contextual approach to mathematics achievement. BBL-contextual is the learning model that designed to develop and optimize the brain ability for getting a new concept and solving the real life problem. This study method was a quasi-experiment. The population was the junior high school students. The sample chosen by using stratified cluster random sampling. The sample was 109 students. The data collected through a mathematics achievement test that was given after the treatment. The data analyzed by using one way ANOVA. The results of the study showed that BBL-contextual is better than direct learning on mathematics achievement. It means BBL-contextual could be an effective and innovative model.

Demonstration of an efficient cooling approach for SBIRS-Low

Science.gov (United States)

Nieczkoski, S. J.; Myers, E. A.

2002-05-01

The Space Based Infrared System-Low (SBIRS-Low) segment is a near-term Air Force program for developing and deploying a constellation of low-earth orbiting observation satellites with gimbaled optics cooled to cryogenic temperatures. The optical system design and requirements present unique challenges that make conventional cooling approaches both complicated and risky. The Cryocooler Interface System (CIS) provides a remote, efficient, and interference-free means of cooling the SBIRS-Low optics. Technology Applications Inc. (TAI), through a two-phase Small Business Innovative Research (SBIR) program with Air Force Research Laboratory (AFRL), has taken the CIS from initial concept feasibility through the design, build, and test of a prototype system. This paper presents the development and demonstration testing of the prototype CIS. Prototype system testing has demonstrated the high efficiency of this cooling approach, making it an attractive option for SBIRS-Low and other sensitive optical and detector systems that require low-impact cryogenic cooling.

Combinatorial Approaches for the Identification of Brain Drug Delivery Targets

Science.gov (United States)

Stutz, Charles C.; Zhang, Xiaobin; Shusta, Eric V.

2018-01-01

The blood-brain barrier (BBB) represents a large obstacle for the treatment of central nervous system diseases. Targeting endogenous nutrient transporters that transcytose the BBB is one promising approach to selectively and noninvasively deliver a drug payload to the brain. The main limitations of the currently employed transcytosing receptors are their ubiquitous expression in the peripheral vasculature and the inherent low levels of transcytosis mediated by such systems. In this review, approaches designed to increase the repertoire of transcytosing receptors which can be targeted for the purpose of drug delivery are discussed. In particular, combinatorial protein libraries can be screened on BBB cells in vitro or in vivo to isolate targeting peptides or antibodies that can trigger transcytosis. Once these targeting reagents are discovered, the cognate BBB transcytosis system can be identified using techniques such as expression cloning or immunoprecipitation coupled with mass spectrometry. Continued technological advances in BBB genomics and proteomics, membrane protein manipulation, and in vitro BBB technology promise to further advance the capability to identify and optimize peptides and antibodies capable of mediating drug transport across the BBB. PMID:23789958

Beamspace fast fully adaptive brain source localization for limited data sequences

International Nuclear Information System (INIS)

Ravan, Maryam

2017-01-01

In the electroencephalogram (EEG) or magnetoencephalogram (MEG) context, brain source localization methods that rely on estimating second order statistics often fail when the observations are taken over a short time interval, especially when the number of electrodes is large. To address this issue, in previous study, we developed a multistage adaptive processing called fast fully adaptive (FFA) approach that can significantly reduce the required sample support while still processing all available degrees of freedom (DOFs). This approach processes the observed data in stages through a decimation procedure. In this study, we introduce a new form of FFA approach called beamspace FFA. We first divide the brain into smaller regions and transform the measured data from the source space to the beamspace in each region. The FFA approach is then applied to the beamspaced data of each region. The goal of this modification is to benefit the correlation sensitivity reduction between sources in different brain regions. To demonstrate the performance of the beamspace FFA approach in the limited data scenario, simulation results with multiple deep and cortical sources as well as experimental results are compared with regular FFA and widely used FINE approaches. Both simulation and experimental results demonstrate that the beamspace FFA method can localize different types of multiple correlated brain sources in low signal to noise ratios more accurately with limited data. (paper)

A Hybrid Hierarchical Approach for Brain Tissue Segmentation by Combining Brain Atlas and Least Square Support Vector Machine

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Kasiri, Keyvan; Kazemi, Kamran; Dehghani, Mohammad Javad; Helfroush, Mohammad Sadegh

2013-01-01

In this paper, we present a new semi-automatic brain tissue segmentation method based on a hybrid hierarchical approach that combines a brain atlas as a priori information and a least-square support vector machine (LS-SVM). The method consists of three steps. In the first two steps, the skull is removed and the cerebrospinal fluid (CSF) is extracted. These two steps are performed using the toolbox FMRIB's automated segmentation tool integrated in the FSL software (FSL-FAST) developed in Oxford Centre for functional MRI of the brain (FMRIB). Then, in the third step, the LS-SVM is used to segment grey matter (GM) and white matter (WM). The training samples for LS-SVM are selected from the registered brain atlas. The voxel intensities and spatial positions are selected as the two feature groups for training and test. SVM as a powerful discriminator is able to handle nonlinear classification problems; however, it cannot provide posterior probability. Thus, we use a sigmoid function to map the SVM output into probabilities. The proposed method is used to segment CSF, GM and WM from the simulated magnetic resonance imaging (MRI) using Brainweb MRI simulator and real data provided by Internet Brain Segmentation Repository. The semi-automatically segmented brain tissues were evaluated by comparing to the corresponding ground truth. The Dice and Jaccard similarity coefficients, sensitivity and specificity were calculated for the quantitative validation of the results. The quantitative results show that the proposed method segments brain tissues accurately with respect to corresponding ground truth. PMID:24696800

The Effects of Brain Based Learning Approach on Motivation and Students Achievement in Mathematics Learning

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Mekarina, M.; Ningsih, Y. P.

2017-09-01

This classroom action research is based by the facts that the students motivation and achievement mathematics learning is less. One of the factors causing is learning that does not provide flexibility to students to empower the potential of the brain optimally. The aim of this research was to improve the student motivation and achievement in mathematics learning by implementing brain based learning approach. The subject of this research was student of grade XI in senior high school. The research consisted of two cycles. Data of student achievement from test, and the student motivation through questionnaire. Furthermore, the finding of this research showed the result of the analysis was the implementation of brain based learning approach can improve student’s achievement and motivation in mathematics learning.

Effects of an explicit problem-solving skills training program using a metacomponential approach for outpatients with acquired brain injury.

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Fong, Kenneth N K; Howie, Dorothy R

2009-01-01

We investigated the effects of an explicit problem-solving skills training program using a metacomponential approach with 33 outpatients with moderate acquired brain injury, in the Hong Kong context. We compared an experimental training intervention with this explicit problem-solving approach, which taught metacomponential strategies, with a conventional cognitive training approach that did not have this explicit metacognitive training. We found significant advantages for the experimental group on the Metacomponential Interview measure in association with the explicit metacomponential training, but transfer to the real-life problem-solving measures was not evidenced in statistically significant findings. Small sample size, limited time of intervention, and some limitations with these tools may have been contributing factors to these results. The training program was demonstrated to have a significantly greater effect than the conventional training approach on metacomponential functioning and the component of problem representation. However, these benefits were not transferable to real-life situations.

The capability of high field MRI in demonstrating post-mortem fetal brains at different gestational age

International Nuclear Information System (INIS)

Zhang Zhonghe; Liu Shuwei; Lin Xiangtao; Gen Hequn; Teng Gaojun; Fang Fang; Zang Fengchao; Yu Taifei; Zhao Bin

2009-01-01

Objective: To study the capability of high field MRI in demonstrating the post-mortem fetal brains at different gestational age (GA). Methods: One hundred and eight post-mortem fetal brains of 14-40 weeks GA were evaluated by 3.0 T MRI. Eleven brains of 14 to 27 weeks GA with good 3.0 T MRI images were chosen and scanned by 7.0 T MRI. The developing sulci, layered structures of fetal cerebral cortex and basal nuclei were evaluated on MRI of different Tesla (3.0 T and 7.0 T) and their results analyzed. Results: On T 1 WI of 3.0 T MRI, the layered structures of fetal cerebral cortex were present at 14 weeks GA, the sulci were more accurately identified after 16 weeks GA. The basal nuclei were clearly distinguishable after 20 weeks CA, and these structures were better visualized as the GA increased. On T 2 WI of 7.0 T MRI, the sulci, layered structures of fetal cerebral cortex and basal nuclei were shown more clearly at the same GA when compared to 3.0 T, especially the sulci at the early developmental stages. Conclusions: T 1 WI of 3.0 T MRI could show the developing structures of post-mortem fetal brain well, but the T 2 WI of 7.0 T MRI were comparatively better. (authors)

Beyond sex differences: new approaches for thinking about variation in brain structure and function.

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Joel, Daphna; Fausto-Sterling, Anne

2016-02-19

In the study of variation in brain structure and function that might relate to sex and gender, language matters because it frames our research questions and methods. In this article, we offer an approach to thinking about variation in brain structure and function that pulls us outside the sex differences formulation. We argue that the existence of differences between the brains of males and females does not unravel the relations between sex and the brain nor is it sufficient to characterize a population of brains. Such characterization is necessary for studying sex effects on the brain as well as for studying brain structure and function in general. Animal studies show that sex interacts with environmental, developmental and genetic factors to affect the brain. Studies of humans further suggest that human brains are better described as belonging to a single heterogeneous population rather than two distinct populations. We discuss the implications of these observations for studies of brain and behaviour in humans and in laboratory animals. We believe that studying sex effects in context and developing or adopting analytical methods that take into account the heterogeneity of the brain are crucial for the advancement of human health and well-being. © 2016 The Author(s).

Structural Graphical Lasso for Learning Mouse Brain Connectivity

KAUST Repository

Yang, Sen

2015-08-07

Investigations into brain connectivity aim to recover networks of brain regions connected by anatomical tracts or by functional associations. The inference of brain networks has recently attracted much interest due to the increasing availability of high-resolution brain imaging data. Sparse inverse covariance estimation with lasso and group lasso penalty has been demonstrated to be a powerful approach to discover brain networks. Motivated by the hierarchical structure of the brain networks, we consider the problem of estimating a graphical model with tree-structural regularization in this paper. The regularization encourages the graphical model to exhibit a brain-like structure. Specifically, in this hierarchical structure, hundreds of thousands of voxels serve as the leaf nodes of the tree. A node in the intermediate layer represents a region formed by voxels in the subtree rooted at that node. The whole brain is considered as the root of the tree. We propose to apply the tree-structural regularized graphical model to estimate the mouse brain network. However, the dimensionality of whole-brain data, usually on the order of hundreds of thousands, poses significant computational challenges. Efficient algorithms that are capable of estimating networks from high-dimensional data are highly desired. To address the computational challenge, we develop a screening rule which can quickly identify many zero blocks in the estimated graphical model, thereby dramatically reducing the computational cost of solving the proposed model. It is based on a novel insight on the relationship between screening and the so-called proximal operator that we first establish in this paper. We perform experiments on both synthetic data and real data from the Allen Developing Mouse Brain Atlas; results demonstrate the effectiveness and efficiency of the proposed approach.

History and current state of immunotherapy in glioma and brain metastasis.

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McGranahan, Tresa; Li, Gordon; Nagpal, Seema

2017-05-01

Malignant brain tumors such as glioblastoma (GBM) and brain metastasis have poor prognosis despite conventional therapies. Successful use of vaccines and checkpoint inhibitors in systemic malignancy has increased the hope that immune therapies could improve survival in patients with brain tumors. Manipulating the immune system to fight malignancy has a long history of both modest breakthroughs and pitfalls that should be considered when applying the current immunotherapy approaches to patients with brain tumors. Therapeutic vaccine trials for GBM date back to the mid 1900s and have taken many forms; from irradiated tumor lysate to cell transfer therapies and peptide vaccines. These therapies were generally well tolerated without significant autoimmune toxicity, however also did not demonstrate significant clinical benefit. In contrast, the newer checkpoint inhibitors have demonstrated durable benefit in some metastatic malignancies, accompanied by significant autoimmune toxicity. While this toxicity was not unexpected, it exceeded what was predicted from pre-clinical studies and in many ways was similar to the prior trials of immunostimulants. This review will discuss the history of these studies and demonstrate that the future use of immune therapy for brain tumors will likely need a personalized approach that balances autoimmune toxicity with the opportunity for significant survival benefit.

Approaches to brain stress testing: BOLD magnetic resonance imaging with computer-controlled delivery of carbon dioxide.

Directory of Open Access Journals (Sweden)

W Alan C Mutch

Full Text Available BACKGROUND: An impaired vascular response in the brain regionally may indicate reduced vascular reserve and vulnerability to ischemic injury. Changing the carbon dioxide (CO(2 tension in arterial blood is commonly used as a cerebral vasoactive stimulus to assess the cerebral vascular response, changing cerebral blood flow (CBF by up to 5-11 percent/mmHg in normal adults. Here we describe two approaches to generating the CO(2 challenge using a computer-controlled gas blender to administer: i a square wave change in CO(2 and, ii a ramp stimulus, consisting of a continuously graded change in CO(2 over a range. Responses were assessed regionally by blood oxygen level dependent (BOLD magnetic resonance imaging (MRI. METHODOLOGY/PRINCIPAL FINDINGS: We studied 8 patients with known cerebrovascular disease (carotid stenosis or occlusion and 2 healthy subjects. The square wave stimulus was used to study the dynamics of the vascular response, while the ramp stimulus assessed the steady-state response to CO(2. Cerebrovascular reactivity (CVR maps were registered by color coding and overlaid on the anatomical scans generated with 3 Tesla MRI to assess the corresponding BOLD signal change/mmHg change in CO(2, voxel-by-voxel. Using a fractal temporal approach, detrended fluctuation analysis (DFA maps of the processed raw BOLD signal per voxel over the same CO(2 range were generated. Regions of BOLD signal decrease with increased CO(2 (coded blue were seen in all of these high-risk patients, indicating regions of impaired CVR. All patients also demonstrated regions of altered signal structure on DFA maps (Hurst exponents less than 0.5; coded blue indicative of anti-persistent noise. While 'blue' CVR maps remained essentially stable over the time of analysis, 'blue' DFA maps improved. CONCLUSIONS/SIGNIFICANCE: This combined dual stimulus and dual analysis approach may be complementary in identifying vulnerable brain regions and thus constitute a regional as

A neurogenetics approach to understanding individual differences in brain, behavior, and risk for psychopathology.

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Bogdan, R; Hyde, L W; Hariri, A R

2013-03-01

Neurogenetics research has begun to advance our understanding of how genetic variation gives rise to individual differences in brain function, which, in turn, shapes behavior and risk for psychopathology. Despite these advancements, neurogenetics research is currently confronted by three major challenges: (1) conducting research on individual variables with small effects, (2) absence of detailed mechanisms, and (3) a need to translate findings toward greater clinical relevance. In this review, we showcase techniques and developments that address these challenges and highlight the benefits of a neurogenetics approach to understanding brain, behavior and psychopathology. To address the challenge of small effects, we explore approaches including incorporating the environment, modeling epistatic relationships and using multilocus profiles. To address the challenge of mechanism, we explore how non-human animal research, epigenetics research and genome-wide association studies can inform our mechanistic understanding of behaviorally relevant brain function. Finally, to address the challenge of clinical relevance, we examine how neurogenetics research can identify novel therapeutic targets and for whom treatments work best. By addressing these challenges, neurogenetics research is poised to exponentially increase our understanding of how genetic variation interacts with the environment to shape the brain, behavior and risk for psychopathology.

Whole-brain activity mapping onto a zebrafish brain atlas.

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Randlett, Owen; Wee, Caroline L; Naumann, Eva A; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E; Portugues, Ruben; Lacoste, Alix M B; Riegler, Clemens; Engert, Florian; Schier, Alexander F

2015-11-01

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open-source atlas containing molecular labels and definitions of anatomical regions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated extracellular signal–regulated kinase (ERK) as a readout of neural activity, we have developed a system to create and contextualize whole-brain maps of stimulus- and behavior-dependent neural activity. This mitogen-activated protein kinase (MAP)-mapping assay is technically simple, and data analysis is completely automated. Because MAP-mapping is performed on freely swimming fish, it is applicable to studies of nearly any stimulus or behavior. Here we demonstrate our high-throughput approach using pharmacological, visual and noxious stimuli, as well as hunting and feeding. The resultant maps outline hundreds of areas associated with behaviors.

Whole-brain activity mapping onto a zebrafish brain atlas

Science.gov (United States)

Randlett, Owen; Wee, Caroline L.; Naumann, Eva A.; Nnaemeka, Onyeka; Schoppik, David; Fitzgerald, James E.; Portugues, Ruben; Lacoste, Alix M.B.; Riegler, Clemens; Engert, Florian; Schier, Alexander F.

2015-01-01

In order to localize the neural circuits involved in generating behaviors, it is necessary to assign activity onto anatomical maps of the nervous system. Using brain registration across hundreds of larval zebrafish, we have built an expandable open source atlas containing molecular labels and anatomical region definitions, the Z-Brain. Using this platform and immunohistochemical detection of phosphorylated-Extracellular signal-regulated kinase (ERK/MAPK) as a readout of neural activity, we have developed a system to create and contextualize whole brain maps of stimulus- and behavior-dependent neural activity. This MAP-Mapping (Mitogen Activated Protein kinase – Mapping) assay is technically simple, fast, inexpensive, and data analysis is completely automated. Since MAP-Mapping is performed on fish that are freely swimming, it is applicable to nearly any stimulus or behavior. We demonstrate the utility of our high-throughput approach using hunting/feeding, pharmacological, visual and noxious stimuli. The resultant maps outline hundreds of areas associated with behaviors. PMID:26778924

A perturbational approach for evaluating the brain's capacity for consciousness.

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Massimini, Marcello; Boly, Melanie; Casali, Adenauer; Rosanova, Mario; Tononi, Giulio

2009-01-01

How do we evaluate a brain's capacity to sustain conscious experience if the subject does not manifest purposeful behaviour and does not respond to questions and commands? What should we measure in this case? An emerging idea in theoretical neuroscience is that what really matters for consciousness in the brain is not activity levels, access to sensory inputs or neural synchronization per se, but rather the ability of different areas of the thalamocortical system to interact causally with each other to form an integrated whole. In particular, the information integration theory of consciousness (IITC) argues that consciousness is integrated information and that the brain should be able to generate consciousness to the extent that it has a large repertoire of available states (information), yet it cannot be decomposed into a collection of causally independent subsystems (integration). To evaluate the ability to integrate information among distributed cortical regions, it may not be sufficient to observe the brain in action. Instead, it is useful to employ a perturbational approach and examine to what extent different regions of the thalamocortical system can interact causally (integration) and produce specific responses (information). Thanks to a recently developed technique, transcranial magnetic stimulation and high-density electroencephalography (TMS/hd-EEG), one can record the immediate reaction of the entire thalamocortical system to controlled perturbations of different cortical areas. In this chapter, using sleep as a model of unconsciousness, we show that TMS/hd-EEG can detect clear-cut changes in the ability of the thalamocortical system to integrate information when the level of consciousness fluctuates across the sleep-wake cycle. Based on these results, we discuss the potential applications of this novel technique to evaluate objectively the brain's capacity for consciousness at the bedside of brain-injured patients.

Brain response pattern identification of fMRI data using a particle swarm optimization-based approach.

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Ma, Xinpei; Chou, Chun-An; Sayama, Hiroki; Chaovalitwongse, Wanpracha Art

2016-09-01

Many neuroscience studies have been devoted to understand brain neural responses correlating to cognition using functional magnetic resonance imaging (fMRI). In contrast to univariate analysis to identify response patterns, it is shown that multi-voxel pattern analysis (MVPA) of fMRI data becomes a relatively effective approach using machine learning techniques in the recent literature. MVPA can be considered as a multi-objective pattern classification problem with the aim to optimize response patterns, in which informative voxels interacting with each other are selected, achieving high classification accuracy associated with cognitive stimulus conditions. To solve the problem, we propose a feature interaction detection framework, integrating hierarchical heterogeneous particle swarm optimization and support vector machines, for voxel selection in MVPA. In the proposed approach, we first select the most informative voxels and then identify a response pattern based on the connectivity of the selected voxels. The effectiveness of the proposed approach was examined for the Haxby's dataset of object-level representations. The computational results demonstrated higher classification accuracy by the extracted response patterns, compared to state-of-the-art feature selection algorithms, such as forward selection and backward selection.

Correlation of Students' Brain Types to Their Conceptions of Learning Science and Approaches to Learning Science

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Park, Jiyeon; Jeon, Dongryul

2015-01-01

The systemizing and empathizing brain type represent two contrasted students' characteristics. The present study investigated differences in the conceptions and approaches to learning science between the systemizing and empathizing brain type students. The instruments are questionnaires on the systematizing and empathizing, questionnaires on the…

The value of brain scanning in cerebro-vascular disease by CT

International Nuclear Information System (INIS)

Huber, G.; Emde, H.

1980-01-01

Brain scanning by scintigraphy and CT studies of the brain are complementary methods. The precise demonstration of the anatomy and the pathology of the brain by CT is supplemented by brain scintigraphy due to the latter's value to assess the hemodynamic properties of a lesion and thus provide important clues to its site and sometimes even its histology. This is especially true in vascular brain disease thus either dispensing the need for an invasive procedure such as angiography or providing information for a specific approach. (orig.) 891 MG/orig. 892 MKO [de

Brain parenchymal damage in neuromyelitis optica spectrum disorder - A multimodal MRI study

Energy Technology Data Exchange (ETDEWEB)

Pache, F.; Paul, F. [Max Delbrueck Center for Molecular Medicine and Charite Universitaetsmedizin Berlin, NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Berlin (Germany); Charite Universitaetsmedizin Berlin, Department of Neurology, Berlin (Germany); Zimmermann, H.; Lacheta, A.; Papazoglou, S.; Kuchling, J.; Wuerfel, J.; Brandt, A.U. [Max Delbrueck Center for Molecular Medicine and Charite Universitaetsmedizin Berlin, NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Berlin (Germany); Finke, C. [Charite Universitaetsmedizin Berlin, Department of Neurology, Berlin (Germany); Humboldt-Universitaet zu Berlin, Berlin School of Mind and Brain, Berlin (Germany); Hamm, B. [Charite Universitaetsmedizin Berlin, Department of Radiology, Berlin (Germany); Ruprecht, K. [Charite Universitaetsmedizin Berlin, Department of Neurology, Berlin (Germany); Scheel, M. [Max Delbrueck Center for Molecular Medicine and Charite Universitaetsmedizin Berlin, NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Berlin (Germany); Charite Universitaetsmedizin Berlin, Department of Radiology, Berlin (Germany)

2016-12-15

To investigate different brain regions for grey (GM) and white matter (WM) damage in a well-defined cohort of neuromyelitis optica spectrum disorder (NMOSD) patients and compare advanced MRI techniques (VBM, Subcortical and cortical analyses (Freesurfer), and DTI) for their ability to detect damage in NMOSD. We analyzed 21 NMOSD patients and 21 age and gender matched control subjects. VBM (GW/WM) and DTI whole brain (TBSS) analyses were performed at different statistical thresholds to reflect different statistical approaches in previous studies. In an automated atlas-based approach, Freesurfer and DTI results were compared between NMOSD and controls. DTI TBSS and DTI atlas based analysis demonstrated microstructural impairment only within the optic radiation or in regions associated with the optic radiation (posterior thalamic radiation p < 0.001, 6.9 % reduction of fractional anisotropy). VBM demonstrated widespread brain GM and WM reduction, but only at exploratory statistical thresholds, with no differences remaining after correction for multiple comparisons. Freesurfer analysis demonstrated no group differences. NMOSD specific parenchymal brain damage is predominantly located in the optic radiation, likely due to a secondary degeneration caused by ON. In comparison, DTI appears to be the most reliable and sensitive technique for brain damage detection in NMOSD. (orig.)

Brain parenchymal damage in neuromyelitis optica spectrum disorder - A multimodal MRI study

International Nuclear Information System (INIS)

Pache, F.; Paul, F.; Zimmermann, H.; Lacheta, A.; Papazoglou, S.; Kuchling, J.; Wuerfel, J.; Brandt, A.U.; Finke, C.; Hamm, B.; Ruprecht, K.; Scheel, M.

2016-01-01

To investigate different brain regions for grey (GM) and white matter (WM) damage in a well-defined cohort of neuromyelitis optica spectrum disorder (NMOSD) patients and compare advanced MRI techniques (VBM, Subcortical and cortical analyses (Freesurfer), and DTI) for their ability to detect damage in NMOSD. We analyzed 21 NMOSD patients and 21 age and gender matched control subjects. VBM (GW/WM) and DTI whole brain (TBSS) analyses were performed at different statistical thresholds to reflect different statistical approaches in previous studies. In an automated atlas-based approach, Freesurfer and DTI results were compared between NMOSD and controls. DTI TBSS and DTI atlas based analysis demonstrated microstructural impairment only within the optic radiation or in regions associated with the optic radiation (posterior thalamic radiation p < 0.001, 6.9 % reduction of fractional anisotropy). VBM demonstrated widespread brain GM and WM reduction, but only at exploratory statistical thresholds, with no differences remaining after correction for multiple comparisons. Freesurfer analysis demonstrated no group differences. NMOSD specific parenchymal brain damage is predominantly located in the optic radiation, likely due to a secondary degeneration caused by ON. In comparison, DTI appears to be the most reliable and sensitive technique for brain damage detection in NMOSD. (orig.)

The blood-brain barrier: structure, function and therapeutic approaches to cross it.

Science.gov (United States)

Tajes, Marta; Ramos-Fernández, Eva; Weng-Jiang, Xian; Bosch-Morató, Mònica; Guivernau, Biuse; Eraso-Pichot, Abel; Salvador, Bertrán; Fernàndez-Busquets, Xavier; Roquer, Jaume; Muñoz, Francisco J

2014-08-01

The blood-brain barrier (BBB) is constituted by a specialized vascular endothelium that interacts directly with astrocytes, neurons and pericytes. It protects the brain from the molecules of the systemic circulation but it has to be overcome for the proper treatment of brain cancer, psychiatric disorders or neurodegenerative diseases, which are dramatically increasing as the population ages. In the present work we have revised the current knowledge on the cellular structure of the BBB and the different procedures utilized currently and those proposed to cross it. Chemical modifications of the drugs, such as increasing their lipophilicity, turn them more prone to be internalized in the brain. Other mechanisms are the use of molecular tools to bind the drugs such as small immunoglobulins, liposomes or nanoparticles that will act as Trojan Horses favoring the drug delivery in brain. This fusion of the classical pharmacology with nanotechnology has opened a wide field to many different approaches with promising results to hypothesize that BBB will not be a major problem for the new generation of neuroactive drugs. The present review provides an overview of all state-of-the-art of the BBB structure and function, as well as of the classic strategies and these appeared in recent years to deliver drugs into the brain for the treatment of Central Nervous System (CNS) diseases.

A MARKOV RANDOM FIELD-BASED APPROACH TO CHARACTERIZING HUMAN BRAIN DEVELOPMENT USING SPATIAL-TEMPORAL TRANSCRIPTOME DATA.

Science.gov (United States)

Lin, Zhixiang; Sanders, Stephan J; Li, Mingfeng; Sestan, Nenad; State, Matthew W; Zhao, Hongyu

2015-03-01

Human neurodevelopment is a highly regulated biological process. In this article, we study the dynamic changes of neurodevelopment through the analysis of human brain microarray data, sampled from 16 brain regions in 15 time periods of neurodevelopment. We develop a two-step inferential procedure to identify expressed and unexpressed genes and to detect differentially expressed genes between adjacent time periods. Markov Random Field (MRF) models are used to efficiently utilize the information embedded in brain region similarity and temporal dependency in our approach. We develop and implement a Monte Carlo expectation-maximization (MCEM) algorithm to estimate the model parameters. Simulation studies suggest that our approach achieves lower misclassification error and potential gain in power compared with models not incorporating spatial similarity and temporal dependency.

Getting to know the brain

International Nuclear Information System (INIS)

Creagh, C.

1992-01-01

While electrical systems, such as electroencephalography, measure events in milliseconds in 'real time', or the time frame in which brain function actually occurs, radio-isotope techniques such as PET and SPECT (which measure chemical activity) need several minutes in which to build up a portrait of events within the brain. In 1989, researchers from the CSIRO Division of Radiophysics, Mathematics and Statistics and Information Technology, and from the Australian Telescope National Facility and the Cognitive Neuroscience Unit at Westmead Hospital in western Sydney, began a demonstration project designed to address those limitations and to extend our knowledge of the brain. This project builds on a decade of work by the Westmead Neuroscience Unit in measuring and imaging complementary aspects of human brain function and structure. It brings together structural and functional measurements of the brain in a multi-modal display combining data from a variety of sources in a computer workstation. The major aims and potential applications of this 'information fusion' approach are summarized. 8 refs., ills

From Brain Maps to Cognitive Ontologies: Informatics and the Search for Mental Structure.

Science.gov (United States)

Poldrack, Russell A; Yarkoni, Tal

2016-01-01

A major goal of cognitive neuroscience is to delineate how brain systems give rise to mental function. Here we review the increasingly large role informatics-driven approaches are playing in such efforts. We begin by reviewing a number of challenges conventional neuroimaging approaches face in trying to delineate brain-cognition mappings--for example, the difficulty in establishing the specificity of postulated associations. Next, we demonstrate how these limitations can potentially be overcome using complementary approaches that emphasize large-scale analysis--including meta-analytic methods that synthesize hundreds or thousands of studies at a time; latent-variable approaches that seek to extract structure from data in a bottom-up manner; and predictive modeling approaches capable of quantitatively inferring mental states from patterns of brain activity. We highlight the underappreciated but critical role for formal cognitive ontologies in helping to clarify, refine, and test theories of brain and cognitive function. Finally, we conclude with a speculative discussion of what future informatics developments may hold for cognitive neuroscience.

Abnormalities of functional brain networks in pathological gambling: a graph-theoretical approach

Science.gov (United States)

Tschernegg, Melanie; Crone, Julia S.; Eigenberger, Tina; Schwartenbeck, Philipp; Fauth-Bühler, Mira; Lemènager, Tagrid; Mann, Karl; Thon, Natasha; Wurst, Friedrich M.; Kronbichler, Martin

2013-01-01

Functional neuroimaging studies of pathological gambling (PG) demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in PG. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional magnetic resonance imaging data in PG. We compared 19 patients with PG to 19 healthy controls (HCs) using the Graph Analysis Toolbox (GAT). None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (supplementary motor area, SMA), reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients. These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that PG is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in PG cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders. PMID:24098282

Abnormalities of Functional Brain Networks in Pathological Gambling: A Graph-Theoretical Approach

Directory of Open Access Journals (Sweden)

Melanie eTschernegg

2013-09-01

Full Text Available Functional neuroimaging studies of pathological gambling demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in pathological gambling. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional MRI data in pathological gambling. We compared 19 patients with pathological gambling to 19 healthy controls using the Graph Analysis Toolbox (GAT. None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (SMA, reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients.These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that pathological gambling is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in pathological gambling cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders.

The outcome after head injury in patients with radiologically demonstrated brain contusion

International Nuclear Information System (INIS)

Eide, P.K.; Tysnes, O.B.

1993-01-01

The early and late outcome was evaluated in head injury patients who presented brain contusion(s) on the cranial CT scan and in patients hospitalized for concussion. There was a high degree of concurrence between mortality and CT findings. Late complaints were common among cases of concussion of the brain. However, the frequency of impaired memory and concentration, speech problems, paresis and epileptic seizures was increased in cases where the CT scan showed brain contusion. Adaptive and social functioning was most impaired in cases with multifocal contusions in both hemispheres. 16 refs., 5 tabs

Potent and Selective BACE-1 Peptide Inhibitors Lower Brain Aβ Levels Mediated by Brain Shuttle Transport

Directory of Open Access Journals (Sweden)

Nadine Ruderisch

2017-10-01

Full Text Available Therapeutic approaches to fight Alzheimer's disease include anti-Amyloidβ (Aβ antibodies and secretase inhibitors. However, the blood-brain barrier (BBB limits the brain exposure of biologics and the chemical space for small molecules to be BBB permeable. The Brain Shuttle (BS technology is capable of shuttling large molecules into the brain. This allows for new types of therapeutic modalities engineered for optimal efficacy on the molecular target in the brain independent of brain penetrating properties. To this end, we designed BACE1 peptide inhibitors with varying lipid modifications with single-digit picomolar cellular potency. Secondly, we generated active-exosite peptides with structurally confirmed dual binding mode and improved potency. When fused to the BS via sortase coupling, these BACE1 inhibitors significantly reduced brain Aβ levels in mice after intravenous administration. In plasma, both BS and non-BS BACE1 inhibitor peptides induced a significant time- and dose-dependent decrease of Aβ. Our results demonstrate that the BS is essential for BACE1 peptide inhibitors to be efficacious in the brain and active-exosite design of BACE1 peptide inhibitors together with lipid modification may be of therapeutic relevance.

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Institute of Scientific and Technical Information of China (English)

ZHANG Yong; QIU Jing; LIU Guanjun; YANG Peng

2012-01-01

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.

Brain perfusion imaging using a Reconstruction-of-Difference (RoD) approach for cone-beam computed tomography

Science.gov (United States)

Mow, M.; Zbijewski, W.; Sisniega, A.; Xu, J.; Dang, H.; Stayman, J. W.; Wang, X.; Foos, D. H.; Koliatsos, V.; Aygun, N.; Siewerdsen, J. H.

2017-03-01

Purpose: To improve the timely detection and treatment of intracranial hemorrhage or ischemic stroke, recent efforts include the development of cone-beam CT (CBCT) systems for perfusion imaging and new approaches to estimate perfusion parameters despite slow rotation speeds compared to multi-detector CT (MDCT) systems. This work describes development of a brain perfusion CBCT method using a reconstruction of difference (RoD) approach to enable perfusion imaging on a newly developed CBCT head scanner prototype. Methods: A new reconstruction approach using RoD with a penalized-likelihood framework was developed to image the temporal dynamics of vascular enhancement. A digital perfusion simulation was developed to give a realistic representation of brain anatomy, artifacts, noise, scanner characteristics, and hemo-dynamic properties. This simulation includes a digital brain phantom, time-attenuation curves and noise parameters, a novel forward projection method for improved computational efficiency, and perfusion parameter calculation. Results: Our results show the feasibility of estimating perfusion parameters from a set of images reconstructed from slow scans, sparse data sets, and arc length scans as short as 60 degrees. The RoD framework significantly reduces noise and time-varying artifacts from inconsistent projections. Proper regularization and the use of overlapping reconstructed arcs can potentially further decrease bias and increase temporal resolution, respectively. Conclusions: A digital brain perfusion simulation with RoD imaging approach has been developed and supports the feasibility of using a CBCT head scanner for perfusion imaging. Future work will include testing with data acquired using a 3D-printed perfusion phantom currently and translation to preclinical and clinical studies.

An assessment of advance relatives approach for brain death organ donation.

Science.gov (United States)

Michaut, Carine; Baumann, Antoine; Gregoire, Hélène; Laviale, Corinne; Audibert, Gérard; Ducrocq, Xavier

2017-01-01

Advance announcement of forthcoming brain death has developed to enable intensivists and organ procurement organisation coordinators to more appropriately, and separately from each other, explain to relatives brain death and the subsequent post-mortem organ donation opportunity. Research aim: The aim was to assess how potentially involved healthcare professionals perceived ethical issues surrounding the strategy of advance approach. A multi-centre opinion survey using an anonymous self-administered questionnaire was conducted in the six-member hospitals of the publicly funded East of France regional organ and tissue procurement network called 'Prélor'. The study population comprised 460 physicians and nurses in the Neurosurgical, Surgical and Medical Intensive Care Units, the Stroke Units and the Emergency Departments. Ethical considerations: The project was approved by the board of the Lorraine University Diploma in Medical Ethics and the Prélor Network administrators. A slight majority of 53.5% of respondents had previously participated in an advance relatives approach: 83% of the physicians and 42% of the nurses. A majority of healthcare professionals (68%) think that the main justification for advance relatives approach is the comprehensive care of the dying patient and the research of his or her most likely opinion (74%). The misunderstanding of the related issues by relatives is an obstacle for 47% of healthcare professionals and 51% think that the answer given by the relatives regarding the most likely opinion of the person regarding post-mortem organ donation really corresponds to the person opinion in only 50% of the cases or less. Time given by advance approach should be employed to help and enable relatives to authentically bear the values and interests of the potential donor in the post-mortem organ donation discussion. Nurses' attendance of advance relatives approach seems necessary to enable them to optimally support the families facing death and

The Effectiveness of the Brain Based Teaching Approach in Enhancing Scientific Understanding of Newtonian Physics among Form Four Students

Science.gov (United States)

Saleh, Salmiza

2012-01-01

The aim of this study was to assess the effectiveness of Brain Based Teaching Approach in enhancing students' scientific understanding of Newtonian Physics in the context of Form Four Physics instruction. The technique was implemented based on the Brain Based Learning Principles developed by Caine & Caine (1991, 2003). This brain compatible…

Brain network activation as a novel biomarker for the return-to-play pathway following sport-related brain injury: A prospective case study

Directory of Open Access Journals (Sweden)

Adam W Kiefer

2015-11-01

Full Text Available Children and adolescent athletes are at a higher risk for concussion than adults, and also experience longer recovery times and increased associated symptoms. It has also recently been demonstrated that multiple, seemingly mild concussions may result in exacerbated and prolonged neurologic deficits. Objective assessments and return to play criteria are needed to reduce risk and morbidity associated with concussive events in these populations. Recent research has pushed to study the use of electroencephalography as an objective measure of brain injury. In the present case study, we present a novel approach that examines event related potentials via a brain network activation (BNA analysis as a biomarker of concussion and recovery. Specifically, changes in BNA scores as indexed through this approach, offer a potential indicator of neurological health as the BNA assessment qualitatively and quantitatively indexes the network dynamics associated with brain injury. Objective tools such as these support accurate and efficient assessment of brain injury and may offer a useful step in categorizing the temporal and spatial changes in brain activity following concussive blows, as well as the functional connectivity of brain networks, associated with concussion.

A Stepwise Approach: Decreasing Infection in Deep Brain Stimulation for Childhood Dystonic Cerebral Palsy.

Science.gov (United States)

Johans, Stephen J; Swong, Kevin N; Hofler, Ryan C; Anderson, Douglas E

2017-09-01

Dystonia is a movement disorder characterized by involuntary muscle contractions, which cause twisting movements or abnormal postures. Deep brain stimulation has been used to improve the quality of life for secondary dystonia caused by cerebral palsy. Despite being a viable treatment option for childhood dystonic cerebral palsy, deep brain stimulation is associated with a high rate of infection in children. The authors present a small series of patients with dystonic cerebral palsy who underwent a stepwise approach for bilateral globus pallidus interna deep brain stimulation placement in order to decrease the rate of infection. Four children with dystonic cerebral palsy who underwent a total of 13 surgical procedures (electrode and battery placement) were identified via a retrospective review. There were zero postoperative infections. Using a multistaged surgical plan for pediatric patients with dystonic cerebral palsy undergoing deep brain stimulation may help to reduce the risk of infection.

MEDICAL BRAIN DRAIN - A THEORETICAL APPROACH

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Boncea Irina

2013-07-01

Full Text Available Medical brain drain is defined as the migration of health personnel from developing countries to developed countries and between industrialized nations in search for better opportunities. This phenomenon became a global growing concern due to its impact on both the donor and the destination countries. This article aims to present the main theoretical contributions starting from 1950 until today and the historical evolution, in the attempt of correlating the particular case of medical brain drain with the theory and evolution of the brain drain in general. This article raises questions and offers answers, identifies the main issues and looks for possible solutions in order to reduce the emigration of medical doctors. Factors of influence include push (low level of income, poor working conditions, the absence of job openings and social recognition, oppressive political climate and pull (better remuneration and working conditions, prospects for career development, job satisfaction, security factors. Developing countries are confronting with the loss of their most valuable intellectuals and the investment in their education, at the benefit of developed nations. An ethical debate arises as the disparities between countries increases, industrialized nations filling in the gaps in health systems with professionals from countries already facing shortages. However, recent literature emphasizes the possibility of a “beneficial brain drain” through education incentives offered by the emigration prospects. Other sources of “brain gain” for donor country are the remittances, the scientific networks and return migration. Measures to stem the medical brain drain involve the common effort and collaboration between developing and developed countries and international organizations. Measures adopted by donor countries include higher salaries, better working conditions, security, career opportunities, incentives to stimulate return migration. Destination

ORIGINAL ARTICLE ORIG ORIG Ct brain demonstration of basal ...

African Journals Online (AJOL)

ganglia in encephalopathic HIV/AIDS children has been relatively well documented. Only two ... presented for CT scan of the brain for neurological symptoms, were reported to have BGC. .... with new onset seizures or a change in mental state. Postmortem ... tion is thought to be a major contributing factor in the development.

Basic emotion processing and the adolescent brain: Task demands, analytic approaches, and trajectories of changes

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Larissa B. Del Piero

2016-06-01

Full Text Available Early neuroimaging studies suggested that adolescents show initial development in brain regions linked with emotional reactivity, but slower development in brain structures linked with emotion regulation. However, the increased sophistication of adolescent brain research has made this picture more complex. This review examines functional neuroimaging studies that test for differences in basic emotion processing (reactivity and regulation between adolescents and either children or adults. We delineated different emotional processing demands across the experimental paradigms in the reviewed studies to synthesize the diverse results. The methods for assessing change (i.e., analytical approach and cohort characteristics (e.g., age range were also explored as potential factors influencing study results. Few unifying dimensions were found to successfully distill the results of the reviewed studies. However, this review highlights the potential impact of subtle methodological and analytic differences between studies, need for standardized and theory-driven experimental paradigms, and necessity of analytic approaches that are can adequately test the trajectories of developmental change that have recently been proposed. Recommendations for future research highlight connectivity analyses and non-linear developmental trajectories, which appear to be promising approaches for measuring change across adolescence. Recommendations are made for evaluating gender and biological markers of development beyond chronological age.

Considering PTSD from the perspective of brain processes: a psychological construction approach.

Science.gov (United States)

Suvak, Michael K; Barrett, Lisa Feldman

2011-02-01

Posttraumatic stress disorder (PTSD) is a complex psychiatric disorder that involves symptoms from various domains that appear to be produced by the combination of several mechanisms. The authors contend that existing neural accounts fail to provide a viable model that explains the emergence and maintenance of PTSD and the associated heterogeneity in the expression of this disorder (cf. Garfinkel & Liberzon, 2009). They introduce a psychological construction approach as a novel framework to probe the brain basis of PTSD, where distributed networks within the human brain are thought to correspond to the basic psychological ingredients of the mind. The authors posit that it is the combination of these ingredients that produces the heterogeneous symptom clusters in PTSD. Their goal is show that a constructionist approach has significant heuristic value in understanding the emergence and maintenance of PTSD symptoms, and leads to different and perhaps more useful conjectures about the origins and maintenance of the syndrome than the traditional hyperreactive fear account. Copyright © 2011 International Society for Traumatic Stress Studies.

A Heuristic Approach to Intra-Brain Communications Using Chaos in a Recurrent Neural Network Model

Science.gov (United States)

Soma, Ken-ichiro; Mori, Ryota; Sato, Ryuichi; Nara, Shigetoshi

2011-09-01

To approach functional roles of chaos in brain, a heuristic model to consider mechanisms of intra-brain communications is proposed. The key idea is to use chaos in firing pattern dynamics of a recurrent neural network consisting of birary state neurons, as propagation medium of pulse signals. Computer experiments and numerical methods are introduced to evaluate signal transport characteristics by calculating correlation functions between sending neurons and receiving neurons of pulse signals.

Insulin and the brain.

Science.gov (United States)

Derakhshan, Fatemeh; Toth, Cory

2013-03-01

Mainly known for its role in peripheral glucose homeostasis, insulin has also significant impact within the brain, functioning as a key neuromodulator in behavioral, cellular, biochemical and molecular studies. The brain is now regarded as an insulin-sensitive organ with widespread, yet selective, expression of the insulin receptor in the olfactory bulb, hypothalamus, hippocampus, cerebellum, amygdala and cerebral cortex. Insulin receptor signaling in the brain is important for neuronal development, glucoregulation, feeding behavior, body weight, and cognitive processes such as with attention, executive functioning, learning and memory. Emerging evidence has demonstrated insulin receptor signaling to be impaired in several neurological disorders. Moreover, insulin receptor signaling is recognized as important for dendritic outgrowth, neuronal survival, circuit development, synaptic plasticity and postsynaptic neurotransmitter receptor trafficking. We review the multiple roles of insulin in the brain, as well as its endogenous trafficking to the brain or its exogenous intervention. Although insulin can be directly targeted to the brain via intracerebroventricular (ICV) or intraparenchymal delivery, these invasive techniques are with significant risk, necessitating repeated surgical intervention and providing potential for systemic hypoglycemia. Another method, intranasal delivery, is a non-invasive, safe, and alternative approach which rapidly targets delivery of molecules to the brain while minimizing systemic exposure. Over the last decades, the delivery of intranasal insulin in animal models and human patients has evolved and expanded, permitting new hope for associated neurodegenerative and neurovascular disorders.

Demonstration of risk-based approaches to nuclear plant regulation

International Nuclear Information System (INIS)

Rahn, F.J.; Sursock, J.P.; Darling, S.S.; Oddo, J.M.

1993-01-01

This paper describes generic technical support EPRI is providing to the nuclear power industry relative to its recent initiatives in the area of risk-based regulations (RBR). A risk-based regulatory approach uses probabilistic risk assessment (PRA), or similar techniques, to allocate safety resources commensurate with the risk posed by nuclear plant operations. This approach will reduce O ampersand M costs, and also improve nuclear plant safety. In order to enhance industry, Nuclear Regulatory Commission (NRC) and public confidence in RBR, three things need to be shown: (1) manpower/resource savings are significant for both NRC and industry; (2) the process is doable in a reasonable amount of time; and (3) the process, if uniformly applied, results in demonstrably cheaper power and safer plants. In 1992, EPRI performed a qualitative study of the key RBR issues contributing to high O ampersand M costs. The results are given on Table 1. This study is being followed up by an in-depth quantitative cost/benefit study to focus technical work on producing guidelines/procedures for licensing submittals to NRC. The guidelines/procedures necessarily will be developed from successful demonstration projects such as the Fitzpatrick pilot plant study proposed by the New York Power Authority and other generic applications. This paper presents three examples: two motor operated valve projects performed by QUADREX Energy Services Corporation working with utilities in responding to NRC Generic Letter 89-10, and a third project working with Yankee Atomic Electric Company on service water systems at a plant in its service system. These demonstration projects aim to show the following: (1) the relative ease of putting together a technical case based on RBR concepts; (2) clarity in differentiating the various risk trade-offs, and in communicating overall reductions in risk with NRC; and (3) improved prioritization of NRC directives

Neural substrate expansion for the restoration of brain function

Directory of Open Access Journals (Sweden)

Han-Chiao Isaac Chen

2016-01-01

Full Text Available Restoring neurological and cognitive function in individuals who have suffered brain damage is one of the principal objectives of modern translational neuroscience. Electrical stimulation approaches, such as deep-brain stimulation, have achieved the most clinical success, but they ultimately may be limited by the computational capacity of the residual cerebral circuitry. An alternative strategy is brain substrate expansion, in which the computational capacity of the brain is augmented through the addition of new processing units and the reconstitution of network connectivity. This latter approach has been explored to some degree using both biological and electronic means but thus far has not demonstrated the ability to reestablish the function of large-scale neuronal networks. In this review, we contend that fulfilling the potential of brain substrate expansion will require a significant shift from current methods that emphasize direct manipulations of the brain (e.g., injections of cellular suspensions and the implantation of multi-electrode arrays to the generation of more sophisticated neural tissues and neural-electric hybrids in vitro that are subsequently transplanted into the brain. Drawing from neural tissue engineering, stem cell biology, and neural interface technologies, this strategy makes greater use of the manifold techniques available in the laboratory to create biocompatible constructs that recapitulate brain architecture and thus are more easily recognized and utilized by brain networks.

Towards a new analytical approach to the challenges of communication difficulties and aquired brain damage in everyday practices

DEFF Research Database (Denmark)

Klemmensen, Charlotte Marie Bisgaard

part of where the participants mainly are persons with acquired brain damage and occupational therapists. I will discuss how a new approach to sense-making practice may be designed in order to study more closely a participants’ perspective in unique situations as they arise. I am interested......The approach of language psychology is grounded in the persons communicating; where as the approach of discursive psychology is grounded in social interaction. There is a lack of scientific knowledge on the social/communicative/interactional challenges of communication difficulties and brain injury...... in everyday life. A sense-making-in-practice approach may help form a new discourse. How may a new analytical approach be designed? May ‘communication’ be described as ‘participation abilities’, using the framework from language psychology combined with discursive psychology and the conventions...

Linking Genes and Brain Development of Honeybee Workers: A Whole-Transcriptome Approach.

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Christina Vleurinck

Full Text Available Honeybees live in complex societies whose capabilities far exceed those of the sum of their single members. This social synergism is achieved mainly by the worker bees, which form a female caste. The worker bees display diverse collaborative behaviors and engage in different behavioral tasks, which are controlled by the central nervous system (CNS. The development of the worker brain is determined by the female sex and the worker caste determination signal. Here, we report on genes that are controlled by sex or by caste during differentiation of the worker's pupal brain. We sequenced and compared transcriptomes from the pupal brains of honeybee workers, queens and drones. We detected 333 genes that are differently expressed and 519 genes that are differentially spliced between the sexes, and 1760 genes that are differentially expressed and 692 genes that are differentially spliced between castes. We further found that 403 genes are differentially regulated by both the sex and caste signals, providing evidence of the integration of both signals through differential gene regulation. In this gene set, we found that the molecular processes of restructuring the cell shape and cell-to-cell signaling are overrepresented. Our approach identified candidate genes that may be involved in brain differentiation that ensures the various social worker behaviors.

A topological approach unveils system invariances and broken symmetries in the brain.

Science.gov (United States)

Tozzi, Arturo; Peters, James F

2016-05-01

Symmetries are widespread invariances underscoring countless systems, including the brain. A symmetry break occurs when the symmetry is present at one level of observation but is hidden at another level. In such a general framework, a concept from algebraic topology, namely, the Borsuk-Ulam theorem (BUT), comes into play and sheds new light on the general mechanisms of nervous symmetries. The BUT tells us that we can find, on an n-dimensional sphere, a pair of opposite points that have the same encoding on an n - 1 sphere. This mapping makes it possible to describe both antipodal points with a single real-valued vector on a lower dimensional sphere. Here we argue that this topological approach is useful for the evaluation of hidden nervous symmetries. This means that symmetries can be found when evaluating the brain in a proper dimension, although they disappear (are hidden or broken) when we evaluate the same brain only one dimension lower. In conclusion, we provide a topological methodology for the evaluation of the most general features of brain activity, i.e., the symmetries, cast in a physical/biological fashion that has the potential to be operationalized. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Experimental Study Comparing a Traditional Approach to Performance Appraisal Training to a Whole-Brain Training Method at C.B. Fleet Laboratories

Science.gov (United States)

Selden, Sally; Sherrier, Tom; Wooters, Robert

2012-01-01

The purpose of this study is to examine the effects of a new approach to performance appraisal training. Motivated by split-brain theory and existing studies of cognitive information processing and performance appraisals, this exploratory study examined the effects of a whole-brain approach to training managers for implementing performance…

Hierarchical brain networks active in approach and avoidance goal pursuit

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Jeffrey Martin Spielberg

2013-06-01

Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

Hierarchical brain networks active in approach and avoidance goal pursuit.

Science.gov (United States)

Spielberg, Jeffrey M; Heller, Wendy; Miller, Gregory A

2013-01-01

Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal-pursuit processes (e.g., motivation) has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity) vital to goal-pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging) with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

Analysis of a human brain transcriptome map

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Greene Jonathan R

2002-04-01

Full Text Available Abstract Background Genome wide transcriptome maps can provide tools to identify candidate genes that are over-expressed or silenced in certain disease tissue and increase our understanding of the structure and organization of the genome. Expressed Sequence Tags (ESTs from the public dbEST and proprietary Incyte LifeSeq databases were used to derive a transcript map in conjunction with the working draft assembly of the human genome sequence. Results Examination of ESTs derived from brain tissues (excluding brain tumor tissues suggests that these genes are distributed on chromosomes in a non-random fashion. Some regions on the genome are dense with brain-enriched genes while some regions lack brain-enriched genes, suggesting a significant correlation between distribution of genes along the chromosome and tissue type. ESTs from brain tumor tissues have also been mapped to the human genome working draft. We reveal that some regions enriched in brain genes show a significant decrease in gene expression in brain tumors, and, conversely that some regions lacking in brain genes show an increased level of gene expression in brain tumors. Conclusions This report demonstrates a novel approach for tissue specific transcriptome mapping using EST-based quantitative assessment.

Structured and Sparse Canonical Correlation Analysis as a Brain-Wide Multi-Modal Data Fusion Approach.

Science.gov (United States)

Mohammadi-Nejad, Ali-Reza; Hossein-Zadeh, Gholam-Ali; Soltanian-Zadeh, Hamid

2017-07-01

Multi-modal data fusion has recently emerged as a comprehensive neuroimaging analysis approach, which usually uses canonical correlation analysis (CCA). However, the current CCA-based fusion approaches face problems like high-dimensionality, multi-collinearity, unimodal feature selection, asymmetry, and loss of spatial information in reshaping the imaging data into vectors. This paper proposes a structured and sparse CCA (ssCCA) technique as a novel CCA method to overcome the above problems. To investigate the performance of the proposed algorithm, we have compared three data fusion techniques: standard CCA, regularized CCA, and ssCCA, and evaluated their ability to detect multi-modal data associations. We have used simulations to compare the performance of these approaches and probe the effects of non-negativity constraint, the dimensionality of features, sample size, and noise power. The results demonstrate that ssCCA outperforms the existing standard and regularized CCA-based fusion approaches. We have also applied the methods to real functional magnetic resonance imaging (fMRI) and structural MRI data of Alzheimer's disease (AD) patients (n = 34) and healthy control (HC) subjects (n = 42) from the ADNI database. The results illustrate that the proposed unsupervised technique differentiates the transition pattern between the subject-course of AD patients and HC subjects with a p-value of less than 1×10 -6 . Furthermore, we have depicted the brain mapping of functional areas that are most correlated with the anatomical changes in AD patients relative to HC subjects.

Insulin resistance in brain and possible therapeutic approaches.

Science.gov (United States)

Cetinkalp, Sevki; Simsir, Ilgin Y; Ertek, Sibel

2014-01-01

Although the brain has long been considered an insulin-independent organ, recent research has shown that insulin has significant effects on the brain, where it plays a role in maintaining glucose and energy homeostasis. To avoid peripheral insulin resistance, the brain may act via hypoinsulinemic responses, maintaining glucose metabolism and insulin sensitivity within its own confines; however, brain insulin resistance may develop due to environmental factors. Insulin has two important functions in the brain: controlling food intake and regulating cognitive functions, particularly memory. Notably, defects in insulin signaling in the brain may contribute to neurodegenerative disorders. Insulin resistance may damage the cognitive system and lead to dementia states. Furthermore, inflammatory processes in the hypothalamus, where insulin receptors are expressed at high density, impair local signaling systems and cause glucose and energy metabolism disorders. Excessive caloric intake and high-fat diets initiate insulin and leptin resistance by inducing mitochondrial dysfunction and endoplasmic reticulum stress in the hypothalamus. This may lead to obesity and diabetes mellitus (DM). Exercise can enhance brain and hypothalamic insulin sensitivity, but it is the option least preferred and/or continuously practiced by the general population. Pharmacological treatments that increase brain and hypothalamic insulin sensitivity may provide new insights into the prevention of dementia disorders, obesity, and type 2 DM in the future.

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

Science.gov (United States)

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-03-03

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

CT brain demonstration of basal ganglion calcification in adult HIV ...

African Journals Online (AJOL)

brain barrier has been postulated. Calcification of the basal ganglia in encephalopathic HIV/AIDS children has been relatively well documented. Only two adult HIV cases with basal ganglion calcification (BGC) have been reported in the literature.

Every Newton Hertz: a macro to micro approach to investigating brain injury.

Science.gov (United States)

Duma, Stefan M; Rowson, Steven

2009-01-01

The high incidence of concussion in contact sports provides a unique opportunity to collect data to characterize mild traumatic brain injury. This paper outlines a macro to micro approach in which the organ level response of the head is analyzed through head acceleration data from human volunteers and the tissue level response is analyzed through finite element analysis of these data. The helmets of Virginia Tech football players are instrumented with multi-accelerometer measurement devices to record linear and rotational head accelerations for every impact during a game or practice. These impacts are then modeled using the Simulated Injury Monitor (SIMon) finite element head model. Cumulative strain damage measure was investigated for the impacts resulting in the high linear and rotational accelerations. The effect of head impacts on functional performance in football players is also investigated to identify any cognitive effects from repetitive sub-concussive impacts. A better understanding of the effects of head impacts and the mechanisms of brain injury will likely result in insight to future head injury prevention methods and cellular research on brain injury.

Electrical Guidance of Human Stem Cells in the Rat Brain

Directory of Open Access Journals (Sweden)

Jun-Feng Feng

2017-07-01

Full Text Available Limited migration of neural stem cells in adult brain is a roadblock for the use of stem cell therapies to treat brain diseases and injuries. Here, we report a strategy that mobilizes and guides migration of stem cells in the brain in vivo. We developed a safe stimulation paradigm to deliver directional currents in the brain. Tracking cells expressing GFP demonstrated electrical mobilization and guidance of migration of human neural stem cells, even against co-existing intrinsic cues in the rostral migration stream. Transplanted cells were observed at 3 weeks and 4 months after stimulation in areas guided by the stimulation currents, and with indications of differentiation. Electrical stimulation thus may provide a potential approach to facilitate brain stem cell therapies.

Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

Science.gov (United States)

Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

2017-08-01

Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

Navigating a 2D Virtual World using Direct Brain Stimulation

Directory of Open Access Journals (Sweden)

Darby M. Losey

2016-11-01

Full Text Available Can the human brain learn to interpret inputs from a virtual world delivered directly through brain stimulation? We answer this question by describing the first demonstration of humans playing a computer game utilizing only direct brain stimulation and no other sensory inputs. The demonstration also provides the first instance of artificial sensory information, in this case depth, being delivered directly to the human brain through noninvasive methods. Our approach utilizes transcranial magnetic stimulation (TMS of the human visual cortex to convey binary information about obstacles in a virtual maze. At certain intensities, TMS elicits visual percepts known as phosphenes, which transmits information to the subject about their current location within the maze. Using this computer-brain interface (CBI, five subjects successfully navigated an average of 92% of all the steps in a variety of virtual maze worlds. They also became more accurate in solving the task over time. These results suggest that humans can learn to utilize information delivered directly and noninvasively to their brains to solve tasks that cannot be solved using their natural senses, opening the door to human sensory augmentation and novel modes of human-computer interaction.

Sexually intrusive behaviour following brain injury: approaches to assessment and rehabilitation.

Science.gov (United States)

Bezeau, Scott C; Bogod, Nicholas M; Mateer, Catherine A

2004-03-01

Sexually intrusive behaviour, which may range from inappropriate commentary to rape, is often observed following a traumatic brain injury. It may represent novel behaviour patterns or an exacerbation of pre-injury personality traits, attitudes, and tendencies. Sexually intrusive behaviour poses a risk to staff and residents of residential facilities and to the community at large, and the development of a sound assessment and treatment plan for sexually intrusive behaviour is therefore very important. A comprehensive evaluation is best served by drawing on the fields of neuropsychology, forensic psychology, and cognitive rehabilitation. The paper discusses the types of brain damage that commonly lead to sexually intrusive behaviour, provides guidance for its assessment, and presents a three-stage treatment model. The importance of a multidisciplinary approach to both assessment and treatment is emphasized. Finally, a case example is provided to illustrate the problem and the possibilities for successful management.

Persistent post-traumatic headache vs. migraine: an MRI study demonstrating differences in brain structure.

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Schwedt, Todd J; Chong, Catherine D; Peplinski, Jacob; Ross, Katherine; Berisha, Visar

2017-08-22

The majority of individuals with post-traumatic headache have symptoms that are indistinguishable from migraine. The overlap in symptoms amongst these individuals raises the question as to whether post-traumatic headache has a unique pathophysiology or if head trauma triggers migraine. The objective of this study was to compare brain structure in individuals with persistent post-traumatic headache (i.e. headache lasting at least 3 months following a traumatic brain injury) attributed to mild traumatic brain injury to that of individuals with migraine. Twenty-eight individuals with persistent post-traumatic headache attributed to mild traumatic brain injury and 28 individuals with migraine underwent brain magnetic resonance imaging on a 3 T scanner. Regional volumes, cortical thickness, surface area and curvature measurements were calculated from T1-weighted sequences and compared between subject groups using ANCOVA. MRI data from 28 healthy control subjects were used to interpret the differences in brain structure between migraine and persistent post-traumatic headache. Differences in regional volumes, cortical thickness, surface area and brain curvature were identified when comparing the group of individuals with persistent post-traumatic headache to the group with migraine. Structure was different between groups for regions within the right lateral orbitofrontal lobe, left caudal middle frontal lobe, left superior frontal lobe, left precuneus and right supramarginal gyrus (p right lateral orbitofrontal lobe, right supramarginal gyrus, and left superior frontal lobe and no differences when comparing the migraine cohort to healthy controls. In conclusion, persistent post-traumatic headache and migraine are associated with differences in brain structure, perhaps suggesting differences in their underlying pathophysiology. Additional studies are needed to further delineate similarities and differences in brain structure and function that are associated with post

An improved approach to reduce partial volume errors in brain SPET

International Nuclear Information System (INIS)

Hatton, R.L.; Hatton, B.F.; Michael, G.; Barnden, L.; QUT, Brisbane, QLD; The Queen Elizabeth Hospital, Adelaide, SA

1999-01-01

Full text: Limitations in SPET resolution give rise to significant partial volume error (PVE) in small brain structures We have investigated a previously published method (Muller-Gartner et al., J Cereb Blood Flow Metab 1992;16: 650-658) to correct PVE in grey matter using MRI. An MRI is registered and segmented to obtain a grey matter tissue volume which is then smoothed to obtain resolution matched to the corresponding SPET. By dividing the original SPET with this correction map, structures can be corrected for PVE on a pixel-by-pixel basis. Since this approach is limited by space-invariant filtering, modification was made by estimating projections for the segmented MRI and reconstructing these using identical parameters to SPET. The methods were tested on simulated brain scans, reconstructed with the ordered subsets EM algorithm (8,16, 32, 64 equivalent EM iterations) The new method provided better recovery visually. For 32 EM iterations, recovery coefficients were calculated for grey matter regions. The effects of potential errors in the method were examined. Mean recovery was unchanged with one pixel registration error, the maximum error found in most registration programs. Errors in segmentation > 2 pixels results in loss of accuracy for small structures. The method promises to be useful for reducing PVE in brain SPET

Registration-based approach for reconstruction of high-resolution in utero fetal MR brain images.

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Rousseau, Francois; Glenn, Orit A; Iordanova, Bistra; Rodriguez-Carranza, Claudia; Vigneron, Daniel B; Barkovich, James A; Studholme, Colin

2006-09-01

This paper describes a novel approach to forming high-resolution MR images of the human fetal brain. It addresses the key problem of fetal motion by proposing a registration-refined compounding of multiple sets of orthogonal fast two-dimensional MRI slices, which are currently acquired for clinical studies, into a single high-resolution MRI volume. A robust multiresolution slice alignment is applied iteratively to the data to correct motion of the fetus that occurs between two-dimensional acquisitions. This is combined with an intensity correction step and a super-resolution reconstruction step, to form a single high isotropic resolution volume of the fetal brain. Experimental validation on synthetic image data with known motion types and underlying anatomy, together with retrospective application to sets of clinical acquisitions, are included. Results indicate that this method promises a unique route to acquiring high-resolution MRI of the fetal brain in vivo allowing comparable quality to that of neonatal MRI. Such data provide a highly valuable window into the process of normal and abnormal brain development, which is directly applicable in a clinical setting.

Intensity-Curvature Measurement Approaches for the Diagnosis of Magnetic Resonance Imaging Brain Tumors

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Carlo Ciulla

2015-11-01

Full Text Available This research presents signal-image post-processing techniques called Intensity-Curvature Measurement Approaches with application to the diagnosis of human brain tumors detected through Magnetic Resonance Imaging (MRI. Post-processing of the MRI of the human brain encompasses the following model functions: (i bivariate cubic polynomial, (ii bivariate cubic Lagrange polynomial, (iii monovariate sinc, and (iv bivariate linear. The following Intensity-Curvature Measurement Approaches were used: (i classic-curvature, (ii signal resilient to interpolation, (iii intensity-curvature measure and (iv intensity-curvature functional. The results revealed that the classic-curvature, the signal resilient to interpolation and the intensity-curvature functional are able to add additional information useful to the diagnosis carried out with MRI. The contribution to the MRI diagnosis of our study are: (i the enhanced gray level scale of the tumor mass and the well-behaved representation of the tumor provided through the signal resilient to interpolation, and (ii the visually perceptible third dimension perpendicular to the image plane provided through the classic-curvature and the intensity-curvature functional.

Left Brain/Right Brain Learning for Adult Education.

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Garvin, Barbara

1986-01-01

Contrasts and compares the theory and practice of adult education as it relates to the issue of right brain/left brain learning. The author stresses the need for a whole-brain approach to teaching and suggests that adult educators, given their philosophical directions, are the perfect potential users of this integrated system. (Editor/CT)

Digital subtraction angiography - a new approach to brain death determination in the newborn

International Nuclear Information System (INIS)

Albertini, A.; Schonfeld, S.; Hiatt, M.; Hegyi, T.

1993-01-01

The diagnosis of brain death in the newborn infants is elusive and often difficult. The lack of cerebral blood flow has become an identified criterion for loss of cerebral function. The diagnosis can be obtained by the technique of digital subtraction angiography, which is presented in two case reports demonstrating the utility of this technique. (orig.)

Deep convolutional neural networks for annotating gene expression patterns in the mouse brain.

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Zeng, Tao; Li, Rongjian; Mukkamala, Ravi; Ye, Jieping; Ji, Shuiwang

2015-05-07

Profiling gene expression in brain structures at various spatial and temporal scales is essential to understanding how genes regulate the development of brain structures. The Allen Developing Mouse Brain Atlas provides high-resolution 3-D in situ hybridization (ISH) gene expression patterns in multiple developing stages of the mouse brain. Currently, the ISH images are annotated with anatomical terms manually. In this paper, we propose a computational approach to annotate gene expression pattern images in the mouse brain at various structural levels over the course of development. We applied deep convolutional neural network that was trained on a large set of natural images to extract features from the ISH images of developing mouse brain. As a baseline representation, we applied invariant image feature descriptors to capture local statistics from ISH images and used the bag-of-words approach to build image-level representations. Both types of features from multiple ISH image sections of the entire brain were then combined to build 3-D, brain-wide gene expression representations. We employed regularized learning methods for discriminating gene expression patterns in different brain structures. Results show that our approach of using convolutional model as feature extractors achieved superior performance in annotating gene expression patterns at multiple levels of brain structures throughout four developing ages. Overall, we achieved average AUC of 0.894 ± 0.014, as compared with 0.820 ± 0.046 yielded by the bag-of-words approach. Deep convolutional neural network model trained on natural image sets and applied to gene expression pattern annotation tasks yielded superior performance, demonstrating its transfer learning property is applicable to such biological image sets.

Intraoperative functional MRI as a new approach to monitor deep brain stimulation in Parkinson's disease

International Nuclear Information System (INIS)

Hesselmann, Volker; Sorger, Bettina; Girnus, Ralf; Lasek, Kathrin; Schulte, Oliver; Krug, Barbara; Lackner, Klaus; Maarouf, Mohammad; Sturm, Volker; Wedekind, Christoph; Bunke, Juergen

2004-01-01

This article deals with technical aspects of intraoperative functional magnetic resonance imaging (fMRI) for monitoring the effect of deep brain stimulation (DBS) in a patient with Parkinson's disease. Under motor activation, therapeutic high-frequency stimulation of the subthalamic nucleus was accompanied by an activation decrease in the contralateral primary sensorimotor cortex and the ipsilateral cerebellum. Furthermore, an activation increase in the contralateral basal ganglia and insula region were detected. These findings demonstrate that fMRI constitutes a promising clinical application for investigating brain activity changes induced by DBS. (orig.)

Extendable supervised dictionary learning for exploring diverse and concurrent brain activities in task-based fMRI.

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Zhao, Shijie; Han, Junwei; Hu, Xintao; Jiang, Xi; Lv, Jinglei; Zhang, Tuo; Zhang, Shu; Guo, Lei; Liu, Tianming

2018-06-01

Recently, a growing body of studies have demonstrated the simultaneous existence of diverse brain activities, e.g., task-evoked dominant response activities, delayed response activities and intrinsic brain activities, under specific task conditions. However, current dominant task-based functional magnetic resonance imaging (tfMRI) analysis approach, i.e., the general linear model (GLM), might have difficulty in discovering those diverse and concurrent brain responses sufficiently. This subtraction-based model-driven approach focuses on the brain activities evoked directly from the task paradigm, thus likely overlooks other possible concurrent brain activities evoked during the information processing. To deal with this problem, in this paper, we propose a novel hybrid framework, called extendable supervised dictionary learning (E-SDL), to explore diverse and concurrent brain activities under task conditions. A critical difference between E-SDL framework and previous methods is that we systematically extend the basic task paradigm regressor into meaningful regressor groups to account for possible regressor variation during the information processing procedure in the brain. Applications of the proposed framework on five independent and publicly available tfMRI datasets from human connectome project (HCP) simultaneously revealed more meaningful group-wise consistent task-evoked networks and common intrinsic connectivity networks (ICNs). These results demonstrate the advantage of the proposed framework in identifying the diversity of concurrent brain activities in tfMRI datasets.

Network Theory and Effects of Transcranial Brain Stimulation Methods on the Brain Networks

Directory of Open Access Journals (Sweden)

Sema Demirci

2014-12-01

Full Text Available In recent years, there has been a shift from classic localizational approaches to new approaches where the brain is considered as a complex system. Therefore, there has been an increase in the number of studies involving collaborations with other areas of neurology in order to develop methods to understand the complex systems. One of the new approaches is graphic theory that has principles based on mathematics and physics. According to this theory, the functional-anatomical connections of the brain are defined as a network. Moreover, transcranial brain stimulation techniques are amongst the recent research and treatment methods that have been commonly used in recent years. Changes that occur as a result of applying brain stimulation techniques on physiological and pathological networks help better understand the normal and abnormal functions of the brain, especially when combined with techniques such as neuroimaging and electroencephalography. This review aims to provide an overview of the applications of graphic theory and related parameters, studies conducted on brain functions in neurology and neuroscience, and applications of brain stimulation systems in the changing treatment of brain network models and treatment of pathological networks defined on the basis of this theory.

Brain enhancement through cognitive training: a new insight from brain connectome

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Fumihiko eTaya

2015-04-01

Full Text Available Owing to the recent advances in neurotechnology and the progress in understanding of brain cognitive functions, improvements of cognitive performance or acceleration of learning process with brain enhancement systems is not out of our reach anymore, on the contrary, it is a tangible target of contemporary research. Although a variety of approaches have been proposed, we will mainly focus on cognitive training interventions, in which learners repeatedly perform cognitive tasks to improve their cognitive abilities. In this review article, we propose that the learning process during the cognitive training can be facilitated by an assistive system monitoring cognitive workloads using EEG biomarkers, and the brain connectome approach can provide additional valuable biomarkers for facilitating leaners' learning processes. For the purpose, we will introduce studies on the cognitive training interventions, EEG biomarkers for cognitive workload, and human brain connectome. As cognitive overload and mental fatigue would reduce or even eliminate gains of cognitive training interventions, a real-time monitoring of cognitive workload can facilitate the learning process by flexibly adjusting difficulty levels of the training task. Moreover, cognitive training interventions should have effects on brain sub-networks, not on a single brain region, and graph theoretical network metrics quantifying topological architecture of the brain network can differentiate with respect to individual cognitive states as well as to different individuals' cognitive abilities, suggesting that the connectome is a valuable approach for tracking the learning progress. Although only a few studies have exploited the connectome approach for studying alterations of the brain network induced by cognitive training interventions so far, we believe that it would be a useful technique for capturing improvements of cognitive functions.

Brain enhancement through cognitive training: a new insight from brain connectome.

Science.gov (United States)

Taya, Fumihiko; Sun, Yu; Babiloni, Fabio; Thakor, Nitish; Bezerianos, Anastasios

2015-01-01

Owing to the recent advances in neurotechnology and the progress in understanding of brain cognitive functions, improvements of cognitive performance or acceleration of learning process with brain enhancement systems is not out of our reach anymore, on the contrary, it is a tangible target of contemporary research. Although a variety of approaches have been proposed, we will mainly focus on cognitive training interventions, in which learners repeatedly perform cognitive tasks to improve their cognitive abilities. In this review article, we propose that the learning process during the cognitive training can be facilitated by an assistive system monitoring cognitive workloads using electroencephalography (EEG) biomarkers, and the brain connectome approach can provide additional valuable biomarkers for facilitating leaners' learning processes. For the purpose, we will introduce studies on the cognitive training interventions, EEG biomarkers for cognitive workload, and human brain connectome. As cognitive overload and mental fatigue would reduce or even eliminate gains of cognitive training interventions, a real-time monitoring of cognitive workload can facilitate the learning process by flexibly adjusting difficulty levels of the training task. Moreover, cognitive training interventions should have effects on brain sub-networks, not on a single brain region, and graph theoretical network metrics quantifying topological architecture of the brain network can differentiate with respect to individual cognitive states as well as to different individuals' cognitive abilities, suggesting that the connectome is a valuable approach for tracking the learning progress. Although only a few studies have exploited the connectome approach for studying alterations of the brain network induced by cognitive training interventions so far, we believe that it would be a useful technique for capturing improvements of cognitive functions.

Brain Network Analysis from High-Resolution EEG Signals

Science.gov (United States)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular

Demonstrated brain insulin resistance in Alzheimer’s disease patients is associated with IGF-1 resistance, IRS-1 dysregulation, and cognitive decline

Science.gov (United States)

Talbot, Konrad; Wang, Hoau-Yan; Kazi, Hala; Han, Li-Ying; Bakshi, Kalindi P.; Stucky, Andres; Fuino, Robert L.; Kawaguchi, Krista R.; Samoyedny, Andrew J.; Wilson, Robert S.; Arvanitakis, Zoe; Schneider, Julie A.; Wolf, Bryan A.; Bennett, David A.; Trojanowski, John Q.; Arnold, Steven E.

2012-01-01

While a potential causal factor in Alzheimer’s disease (AD), brain insulin resistance has not been demonstrated directly in that disorder. We provide such a demonstration here by showing that the hippocampal formation (HF) and, to a lesser degree, the cerebellar cortex in AD cases without diabetes exhibit markedly reduced responses to insulin signaling in the IR→IRS-1→PI3K signaling pathway with greatly reduced responses to IGF-1 in the IGF-1R→IRS-2→PI3K signaling pathway. Reduced insulin responses were maximal at the level of IRS-1 and were consistently associated with basal elevations in IRS-1 phosphorylated at serine 616 (IRS-1 pS616) and IRS-1 pS636/639. In the HF, these candidate biomarkers of brain insulin resistance increased commonly and progressively from normal cases to mild cognitively impaired cases to AD cases regardless of diabetes or APOE ε4 status. Levels of IRS-1 pS616 and IRS-1 pS636/639 and their activated kinases correlated positively with those of oligomeric Aβ plaques and were negatively associated with episodic and working memory, even after adjusting for Aβ plaques, neurofibrillary tangles, and APOE ε4. Brain insulin resistance thus appears to be an early and common feature of AD, a phenomenon accompanied by IGF-1 resistance and closely associated with IRS-1 dysfunction potentially triggered by Aβ oligomers and yet promoting cognitive decline independent of classic AD pathology. PMID:22476197

Reprogramming Cells for Brain Repair

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Randall D. McKinnon

2013-08-01

Full Text Available At present there are no clinical therapies that can repair traumatic brain injury, spinal cord injury or degenerative brain disease. While redundancy and rewiring of surviving circuits can recover some lost function, the brain and spinal column lack sufficient endogenous stem cells to replace lost neurons or their supporting glia. In contrast, pre-clinical studies have demonstrated that exogenous transplants can have remarkable efficacy for brain repair in animal models. Mesenchymal stromal cells (MSCs can provide paracrine factors that repair damage caused by ischemic injury, and oligodendrocyte progenitor cell (OPC grafts give dramatic functional recovery from spinal cord injury. These studies have progressed to clinical trials, including human embryonic stem cell (hESC-derived OPCs for spinal cord repair. However, ESC-derived allografts are less than optimal, and we need to identify a more appropriate donor graft population. The cell reprogramming field has developed the ability to trans-differentiate somatic cells into distinct cell types, a technology that has the potential to generate autologous neurons and glia which address the histocompatibility concerns of allografts and the tumorigenicity concerns of ESC-derived grafts. Further clarifying how cell reprogramming works may lead to more efficient direct reprogram approaches, and possibly in vivo reprogramming, in order to promote brain and spinal cord repair.

The Selfish Brain: Stress and Eating Behavior

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Achim ePeters

2011-05-01

Full Text Available The brain occupies a special hierarchical position in human energy metabolism. If cerebral homeostasis is threatened, the brain behaves in a "selfish" manner by competing for energy resources with the body. Here we present a logistic approach, which is based on the principles of supply and demand known from economics. In this "cerebral supply chain" model, the brain constitutes the final consumer. In order to illustrate the operating mode of the cerebral supply chain, we take experimental data which allow to assess the supply, demand and need of the brain under conditions of psychosocial stress. The experimental results show that the brain under conditions of psychosocial stress actively demands energy from the body, in order to cover its increased energy needs. The data demonstrate that the stressed brain uses a mechanism referred to as "cerebral insulin suppression" to limit glucose fluxes into peripheral tissue (muscle, fat and to enhance cerebral glucose supply. Furthermore psychosocial stress elicits a marked increase in eating behavior in the post-stress phase. Subjects ingested more carbohydrates without any preference for sweet ingredients. These experimentally observed changes of cerebral demand, supply and need are integrated into a logistic framework describing the supply chain of the selfish brain.

Analysis of the cerebral transcriptome in mice subjected to traumatic brain injury: importance of IL-6

DEFF Research Database (Denmark)

Quintana, Albert; Giralt, Mercedes; Molinero, Amalia

2007-01-01

Traumatic brain injury is one of the leading causes of incapacity and death among young people. Injury to the brain elicits a potent inflammatory response, comprising recruitment of inflammatory cells, reactive astrogliosis and activation of brain macrophages. Under the influence of presumably...... such as microarrays. The combination of these modern techniques with the comparison of normal and genetically modified mice boosts the significance of the results obtained. With this approach, we have demonstrated that a cytokine such as interleukin-6 is one of the key players in the response of the brain to injury....

Using human brain activity to guide machine learning.

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Fong, Ruth C; Scheirer, Walter J; Cox, David D

2018-03-29

Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

Combining non-invasive transcranial brain stimulation with neuroimaging and electrophysiology: Current approaches and future perspectives.

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Bergmann, Til Ole; Karabanov, Anke; Hartwigsen, Gesa; Thielscher, Axel; Siebner, Hartwig Roman

2016-10-15

Non-invasive transcranial brain stimulation (NTBS) techniques such as transcranial magnetic stimulation (TMS) and transcranial current stimulation (TCS) are important tools in human systems and cognitive neuroscience because they are able to reveal the relevance of certain brain structures or neuronal activity patterns for a given brain function. It is nowadays feasible to combine NTBS, either consecutively or concurrently, with a variety of neuroimaging and electrophysiological techniques. Here we discuss what kind of information can be gained from combined approaches, which often are technically demanding. We argue that the benefit from this combination is twofold. Firstly, neuroimaging and electrophysiology can inform subsequent NTBS, providing the required information to optimize where, when, and how to stimulate the brain. Information can be achieved both before and during the NTBS experiment, requiring consecutive and concurrent applications, respectively. Secondly, neuroimaging and electrophysiology can provide the readout for neural changes induced by NTBS. Again, using either concurrent or consecutive applications, both "online" NTBS effects immediately following the stimulation and "offline" NTBS effects outlasting plasticity-inducing NTBS protocols can be assessed. Finally, both strategies can be combined to close the loop between measuring and modulating brain activity by means of closed-loop brain state-dependent NTBS. In this paper, we will provide a conceptual framework, emphasizing principal strategies and highlighting promising future directions to exploit the benefits of combining NTBS with neuroimaging or electrophysiology. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation.

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Wang, J; Hao, Z; Wang, H

2018-01-01

The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI) data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC). The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

Risk of brain injury during diagnostic coronary angiography: comparison between right and left radial approach.

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Pacchioni, Andrea; Versaci, Francesco; Mugnolo, Antonio; Penzo, Carlo; Nikas, Dimitrios; Saccà, Salvatore; Favero, Luca; Agostoni, Pier Francesco; Garami, Zsolt; Prati, Francesco; Reimers, Bernhard

2013-09-10

To assess the incidence of silent cerebral embolization when using the transradial approach for diagnostic coronary angiography (DCA). Compared to other vascular access sites, the right transradial approach (RTA) could reduce the amount of brain emboli by avoiding mechanical trauma to the aortic wall caused by catheters and wire, whereas it increases manipulation of catheters in the ascending aorta and has a higher risk of direct embolization into the right common carotid artery. A recent study showed an increased incidence of microembolic signals (MES) in RTA compared to femoral. However, left transradial approach (LTA) has never been assessed. 40 patients with suspected coronary artery disease were randomized to DCA via RTA (n=20) or LTA (n=20) with contemporaneous bilateral transcranial Doppler monitoring. MES were detected in all patients, with a significantly higher rate in the RTA group (median 61, interquartile range (IQR) 47-105, vs 48, IQR 31-60, p=0.035). MES generated during procedures needing >2 catheters (n=8), are higher than those detected during procedures performed with 2 catheters (n=32, 102, IQR 70-108, vs 48, IQR 33-60, p=0.001). At multivariate analysis increasing number of catheters was the only independent predictor of high incidence of MES (OR 16.4, 95% CI 1.23-219.9, p=0.034, -2LL=26.7). LTA has a lower risk of brain embolization because of the lower number of catheter exchange maneuvers. Since the degree of brain embolism depends on the magnitude of mechanical manipulation, catheter changes should be minimized to reduce the risk of cerebral embolization. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Macrophages with cellular backpacks for targeted drug delivery to the brain.

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Klyachko, Natalia L; Polak, Roberta; Haney, Matthew J; Zhao, Yuling; Gomes Neto, Reginaldo J; Hill, Michael C; Kabanov, Alexander V; Cohen, Robert E; Rubner, Michael F; Batrakova, Elena V

2017-09-01

Most potent therapeutics are unable to cross the blood-brain barrier following systemic administration, which necessitates the development of unconventional, clinically applicable drug delivery systems. With the given challenges, biologically active vehicles are crucial to accomplishing this task. We now report a new method for drug delivery that utilizes living cells as vehicles for drug carriage across the blood brain barrier. Cellular backpacks, 7-10 μm diameter polymer patches of a few hundred nanometers in thickness, are a potentially interesting approach, because they can act as drug depots that travel with the cell-carrier, without being phagocytized. Backpacks loaded with a potent antioxidant, catalase, were attached to autologous macrophages and systemically administered into mice with brain inflammation. Using inflammatory response cells enabled targeted drug transport to the inflamed brain. Furthermore, catalase-loaded backpacks demonstrated potent therapeutic effects deactivating free radicals released by activated microglia in vitro. This approach for drug carriage and release can accelerate the development of new drug formulations for all the neurodegenerative disorders. Copyright © 2017. Published by Elsevier Ltd.

Making waves in the brain: What are oscillations, and why modulating them makes sense for brain injury

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Aleksandr ePevzner

2016-04-01

Full Text Available Traumatic brain injury (TBI can result in persistent cognitive, behavioral and emotional deficits. However, the vast majority of patients are not chronically hospitalized; rather they have to manage their disabilities once they are discharged to home. Promoting recovery to pre-injury level is important from a patient care as well as a societal perspective. Electrical neuromodulation is one approach that has shown promise in alleviating symptoms associated with neurological disorders such as in Parkinson’s disease and epilepsy. Consistent with this perspective, both animal and clinical studies have revealed that TBI alters physiological oscillatory rhythms. More recently several studies demonstrated that low frequency stimulation improves cognitive outcome in models of TBI. Specifically, stimulation of the septohippocampal circuit in the theta frequency entrained oscillations and improved spatial learning following traumatic brain injury. In order to evaluate the potential of electrical deep brain stimulation for clinical translation we review the basic neurophysiology of oscillations, their role in cognition and how they are changed post-TBI. Furthermore, we highlight several factors for future pre-clinical and clinical studies to consider, with the hope that it will promote a hypothesis driven approach to subsequent experimental designs and ultimately successful translation to improve outcome in patients with TBI.

Functional community analysis of brain: a new approach for EEG-based investigation of the brain pathology.

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Ahmadlou, Mehran; Adeli, Hojjat

2011-09-15

Analysis of structure of the brain functional connectivity (SBFC) is a fundamental issue for understanding of the brain cognition as well as the pathology of brain disorders. Analysis of communities among sub-parts of a system is increasingly used for social, ecological, and other networks. This paper presents a new methodology for investigation of the SBFC and understanding of the brain based on graph theory and community pattern analysis of functional connectivity graph of the brain obtained from encephalograms (EEGs). The methodology consists of three main parts: fuzzy synchronization likelihood (FSL), community partitioning, and decisions based on partitions. As an example application, the methodology is applied to analysis of brain of patients with attention deficit/hyperactivity disorder (ADHD) and the problem of discrimination of ADHD EEGs from healthy (non-ADHD) EEGs. Copyright © 2011. Published by Elsevier Inc.

A qualitative study adopting a user-centered approach to design and validate a brain computer interface for cognitive rehabilitation for people with brain injury.

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Martin, Suzanne; Armstrong, Elaine; Thomson, Eileen; Vargiu, Eloisa; Solà, Marc; Dauwalder, Stefan; Miralles, Felip; Daly Lynn, Jean

2017-07-14

Cognitive rehabilitation is established as a core intervention within rehabilitation programs following a traumatic brain injury (TBI). Digitally enabled assistive technologies offer opportunities for clinicians to increase remote access to rehabilitation supporting transition into home. Brain Computer Interface (BCI) systems can harness the residual abilities of individuals with limited function to gain control over computers through their brain waves. This paper presents an online cognitive rehabilitation application developed with therapists, to work remotely with people who have TBI, who will use BCI at home to engage in the therapy. A qualitative research study was completed with people who are community dwellers post brain injury (end users), and a cohort of therapists involved in cognitive rehabilitation. A user-centered approach over three phases in the development, design and feasibility testing of this cognitive rehabilitation application included two tasks (Find-a-Category and a Memory Card task). The therapist could remotely prescribe activity with different levels of difficulty. The service user had a home interface which would present the therapy activities. This novel work was achieved by an international consortium of academics, business partners and service users.

Methodological Demonstration of a Text Analytics Approach to Country Logistics System Assessments

DEFF Research Database (Denmark)

Kinra, Aseem; Mukkamala, Raghava Rao; Vatrapu, Ravi

2017-01-01

The purpose of this study is to develop and demonstrate a semi-automated text analytics approach for the identification and categorization of information that can be used for country logistics assessments. In this paper, we develop the methodology on a set of documents for 21 countries using...... and the text analyst. Implications are discussed and future work is outlined....

The modulatory effect of adaptive deep brain stimulation on beta bursts in Parkinson's disease.

Science.gov (United States)

Tinkhauser, Gerd; Pogosyan, Alek; Little, Simon; Beudel, Martijn; Herz, Damian M; Tan, Huiling; Brown, Peter

2017-04-01

Adaptive deep brain stimulation uses feedback about the state of neural circuits to control stimulation rather than delivering fixed stimulation all the time, as currently performed. In patients with Parkinson's disease, elevations in beta activity (13-35 Hz) in the subthalamic nucleus have been demonstrated to correlate with clinical impairment and have provided the basis for feedback control in trials of adaptive deep brain stimulation. These pilot studies have suggested that adaptive deep brain stimulation may potentially be more effective, efficient and selective than conventional deep brain stimulation, implying mechanistic differences between the two approaches. Here we test the hypothesis that such differences arise through differential effects on the temporal dynamics of beta activity. The latter is not constantly increased in Parkinson's disease, but comes in bursts of different durations and amplitudes. We demonstrate that the amplitude of beta activity in the subthalamic nucleus increases in proportion to burst duration, consistent with progressively increasing synchronization. Effective adaptive deep brain stimulation truncated long beta bursts shifting the distribution of burst duration away from long duration with large amplitude towards short duration, lower amplitude bursts. Critically, bursts with shorter duration are negatively and bursts with longer duration positively correlated with the motor impairment off stimulation. Conventional deep brain stimulation did not change the distribution of burst durations. Although both adaptive and conventional deep brain stimulation suppressed mean beta activity amplitude compared to the unstimulated state, this was achieved by a selective effect on burst duration during adaptive deep brain stimulation, whereas conventional deep brain stimulation globally suppressed beta activity. We posit that the relatively selective effect of adaptive deep brain stimulation provides a rationale for why this approach could

Brain-Computer Interfaces in Medicine

Science.gov (United States)

Shih, Jerry J.; Krusienski, Dean J.; Wolpaw, Jonathan R.

2012-01-01

Brain-computer interfaces (BCIs) acquire brain signals, analyze them, and translate them into commands that are relayed to output devices that carry out desired actions. BCIs do not use normal neuromuscular output pathways. The main goal of BCI is to replace or restore useful function to people disabled by neuromuscular disorders such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. From initial demonstrations of electroencephalography-based spelling and single-neuron-based device control, researchers have gone on to use electroencephalographic, intracortical, electrocorticographic, and other brain signals for increasingly complex control of cursors, robotic arms, prostheses, wheelchairs, and other devices. Brain-computer interfaces may also prove useful for rehabilitation after stroke and for other disorders. In the future, they might augment the performance of surgeons or other medical professionals. Brain-computer interface technology is the focus of a rapidly growing research and development enterprise that is greatly exciting scientists, engineers, clinicians, and the public in general. Its future achievements will depend on advances in 3 crucial areas. Brain-computer interfaces need signal-acquisition hardware that is convenient, portable, safe, and able to function in all environments. Brain-computer interface systems need to be validated in long-term studies of real-world use by people with severe disabilities, and effective and viable models for their widespread dissemination must be implemented. Finally, the day-to-day and moment-to-moment reliability of BCI performance must be improved so that it approaches the reliability of natural muscle-based function. PMID:22325364

A simplified ALARA approach to demonstration of compliance with surface contaminated object regulatory requirements

International Nuclear Information System (INIS)

Pope, R.B.; Shappert, L.B.; Michelhaugh, R.D.; Boyle, R.W.; Cook, J.C.

1998-02-01

The US Department of Transportation (DOT) and the US Nuclear Regulatory Commission (NRC) have jointly prepared a comprehensive set of draft guidance for consignors and inspectors to use when applying the newly imposed regulatory requirements for low specific activity (LSA) material and surface contaminated objects (SCOs). The guidance is being developed to facilitate compliance with the new LSA material and SCO requirements, not to impose additional requirements. These new requirements represent, in some areas, significant departures from the manner in which packaging and transportation of these materials and objects were previously controlled. On occasion, it may be appropriate to use conservative approaches to demonstrate compliance with some of the requirements, ensuring that personnel are not exposed to radiation at unnecessary levels, so that exposures are kept as low as reasonably achievable (ALARA). In the draft guidance, one such approach would assist consignors preparing a shipment of a large number of SCOs in demonstrating compliance without unnecessarily exposing personnel. In applying this approach, users need to demonstrate that four conditions are met. These four conditions are used to categorize non-activated, contaminated objects as SCO-2. It is expected that, by applying this approach, it will be possible to categorize a large number of small contaminated objects as SCO-2 without the need for detailed, quantitative measurements of fixed, accessible contamination, or of total (fixed and non-fixed) contamination on inaccessible surfaces. The method, which is based upon reasoned argument coupled with limited measurements and the application of a sum of fractions rule, is described and examples of its use are provided

Rubbertown Next Generation Emission Measurement Demonstration Project Provides Innovative Approaches to Protecting Air Quality

Science.gov (United States)

EPA and the Louisville Metro Air Pollution Control District (LMAPCD) are working together on a research project to demonstrate NGEM approaches near facilities in the Rubbertown industrial area of Louisville, KY.

The impact of initiation: Early onset marijuana smokers demonstrate altered Stroop performance and brain activation

Directory of Open Access Journals (Sweden)

K.A. Sagar

2015-12-01

Full Text Available Marijuana (MJ use is on the rise, particularly among teens and emerging adults. This poses serious public health concern, given the potential deleterious effects of MJ on the developing brain. We examined 50 chronic MJ smokers divided into early onset (regular MJ use prior to age 16; n = 24 and late onset (age 16 or later; n = 26, and 34 healthy control participants (HCs. All completed a modified Stroop Color Word Test during fMRI. Results demonstrated that MJ smokers exhibited significantly poorer performance on the Interference subtest of the Stroop, as well as altered patterns of activation in the cingulate cortex relative to HCs. Further, early onset MJ smokers exhibited significantly poorer performance relative to both HCs and late onset smokers. Additionally, earlier age of MJ onset as well as increased frequency and magnitude (grams/week of MJ use were predictive of poorer Stroop performance. fMRI results revealed that while late onset smokers demonstrated a more similar pattern of activation to the control group, a different pattern was evident in the early onset group. These findings underscore the importance of assessing age of onset and patterns of MJ use and support the need for widespread education and intervention efforts among youth.

Language and the Brain. Cambridge Approaches to Linguistics.

Science.gov (United States)

Obler, Loraine K.; Gjerlow, Kris

This book examines how the brain enables people to speak creatively and build up an understanding of language. The discussion looks at the linguistic and neuro-anatomical underpinnings of language and considers how language skills can systematically break down in individuals with different types of brain damage. By studying children with language…

Insulin-Resistant Brain State: the culprit in sporadic Alzheimer’s Disease?

Science.gov (United States)

Correia, Sónia C.; Santos, Renato X.; Perry, George; Zhu, Xiongwei; Moreira, Paula I.; Smith, Mark A.

2011-01-01

Severe abnormalities in brain glucose/energy metabolism and insulin signaling have been documented to take a pivotal role in early sporadic Alzheimer’s disease (sAD) pathology. Indeed, the “insulin-resistant brain state” has been hypothesized to form the core of the neurodegenerative events that occur in sAD. In this vein, intracerebroventricular administration of subdiabetogenic doses of streptozotocin (STZ) in rats can induce an insulin-resistant brain state, which is proposed as a suitable experimental model of sAD. This review highlights the involvement of disturbed brain insulin metabolism in sAD etiopathogenesis. Furthermore, current knowledge demonstrates that central STZ administration produces brain pathology and behavioral changes that resemble changes found in sAD patients. The STZ-intracerebroventricularly treated rat represents a promising experimental tool in this field by providing new insights concerning early brain alterations in sAD, which can be translated in novel etiopathogenic and therapeutic approaches in this disease. PMID:21262392

An approach for brain-controlled prostheses based on Scene Graph Steady-State Visual Evoked Potentials.

Science.gov (United States)

Li, Rui; Zhang, Xiaodong; Li, Hanzhe; Zhang, Liming; Lu, Zhufeng; Chen, Jiangcheng

2018-08-01

Brain control technology can restore communication between the brain and a prosthesis, and choosing a Brain-Computer Interface (BCI) paradigm to evoke electroencephalogram (EEG) signals is an essential step for developing this technology. In this paper, the Scene Graph paradigm used for controlling prostheses was proposed; this paradigm is based on Steady-State Visual Evoked Potentials (SSVEPs) regarding the Scene Graph of a subject's intention. A mathematic model was built to predict SSVEPs evoked by the proposed paradigm and a sinusoidal stimulation method was used to present the Scene Graph stimulus to elicit SSVEPs from subjects. Then, a 2-degree of freedom (2-DOF) brain-controlled prosthesis system was constructed to validate the performance of the Scene Graph-SSVEP (SG-SSVEP)-based BCI. The classification of SG-SSVEPs was detected via the Canonical Correlation Analysis (CCA) approach. To assess the efficiency of proposed BCI system, the performances of traditional SSVEP-BCI system were compared. Experimental results from six subjects suggested that the proposed system effectively enhanced the SSVEP responses, decreased the degradation of SSVEP strength and reduced the visual fatigue in comparison with the traditional SSVEP-BCI system. The average signal to noise ratio (SNR) of SG-SSVEP was 6.31 ± 2.64 dB, versus 3.38 ± 0.78 dB of traditional-SSVEP. In addition, the proposed system achieved good performances in prosthesis control. The average accuracy was 94.58% ± 7.05%, and the corresponding high information transfer rate (IRT) was 19.55 ± 3.07 bit/min. The experimental results revealed that the SG-SSVEP based BCI system achieves the good performance and improved the stability relative to the conventional approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Brain anatomical networks in early human brain development.

Science.gov (United States)

Fan, Yong; Shi, Feng; Smith, Jeffrey Keith; Lin, Weili; Gilmore, John H; Shen, Dinggang

2011-02-01

Recent neuroimaging studies have demonstrated that human brain networks have economic small-world topology and modular organization, enabling efficient information transfer among brain regions. However, it remains largely unknown how the small-world topology and modular organization of human brain networks emerge and develop. Using longitudinal MRI data of 28 healthy pediatric subjects, collected at their ages of 1 month, 1 year, and 2 years, we analyzed development patterns of brain anatomical networks derived from morphological correlations of brain regional volumes. The results show that the brain network of 1-month-olds has the characteristically economic small-world topology and nonrandom modular organization. The network's cost efficiency increases with the brain development to 1 year and 2 years, so does the modularity, providing supportive evidence for the hypothesis that the small-world topology and the modular organization of brain networks are established during early brain development to support rapid synchronization and information transfer with minimal rewiring cost, as well as to balance between local processing and global integration of information. Copyright © 2010. Published by Elsevier Inc.

Nanoparticle functionalization for brain targeting drug delivery and diagnostic

DEFF Research Database (Denmark)

Gomes, Maria João; Mendes, Bárbara; Martins, Susana

2016-01-01

carriers to cross the BBB and achieve brain, and their functionalization strategies are described; and finally the delivery of nanoparticles to the target moiety, as diagnostics or therapeutics. Therefore, this chapter is focused on how the nanoparticle surface may be functionalized for drug delivery......Nanobiotechnology has been demonstrated to be an efficient tool for targeted therapy as well as diagnosis, with particular emphasis on brain tumor and neurodegenerative diseases. On this regard, the aim of this chapter is focused on engineered nanoparticles targeted to the brain, so that they have...... and diagnostics. Furthermore, it is also mentioned that some BBB targets were already used as transport mediators to central nervous system by functionalization on nanoparticles. It summarizes the nanoparticles potential in therapeutics and molecular targeting to BBB, and also an approach of the nanoparticle...

Generation of Individual Whole-Brain Atlases With Resting-State fMRI Data Using Simultaneous Graph Computation and Parcellation

Directory of Open Access Journals (Sweden)

J. Wang

2018-05-01

Full Text Available The human brain can be characterized as functional networks. Therefore, it is important to subdivide the brain appropriately in order to construct reliable networks. Resting-state functional connectivity-based parcellation is a commonly used technique to fulfill this goal. Here we propose a novel individual subject-level parcellation approach based on whole-brain resting-state functional magnetic resonance imaging (fMRI data. We first used a supervoxel method known as simple linear iterative clustering directly on resting-state fMRI time series to generate supervoxels, and then combined similar supervoxels to generate clusters using a clustering method known as graph-without-cut (GWC. The GWC approach incorporates spatial information and multiple features of the supervoxels by energy minimization, simultaneously yielding an optimal graph and brain parcellation. Meanwhile, it theoretically guarantees that the actual cluster number is exactly equal to the initialized cluster number. By comparing the results of the GWC approach and those of the random GWC approach, we demonstrated that GWC does not rely heavily on spatial structures, thus avoiding the challenges encountered in some previous whole-brain parcellation approaches. In addition, by comparing the GWC approach to two competing approaches, we showed that GWC achieved better parcellation performances in terms of different evaluation metrics. The proposed approach can be used to generate individualized brain atlases for applications related to cognition, development, aging, disease, personalized medicine, etc. The major source codes of this study have been made publicly available at https://github.com/yuzhounh/GWC.

The relational neurobehavioral approach: can a non-aversive program manage adults with brain injury-related aggression without seclusion/restraint?

Science.gov (United States)

Kalapatapu, Raj K; Giles, Gordon M

2017-11-01

The Relational Neurobehavioral Approach (RNA) is a set of non-aversive intervention methods to manage individuals with brain injury-related aggression. New data on interventions used in the RNA and on how the RNA interventions can be used with patients with acquired brain injury (ABI) who have differing levels of functional impairment are provided in this paper. The study was conducted over a 6-week period in a secure 65-bed program for individuals with ABI that is housed in two units of a skilled nursing facility (SNF). Implementation of the RNA was compared between two units that housed patients with differing levels of functional impairment (n = 65 adults). Since this was a hierarchical clustered dataset, Generalized Estimating Equations regression was used in the analyses. RNA interventions used to manage the 495 aggressive incidents included the following: Aggression ignored, Closer observation, Talking to patient, Reassurance, Physical distraction, Isolation without seclusion, Immediate medication by mouth, Holding patient. Different interventions were implemented differentially by staff based on level of functional impairment and without use of seclusion or mechanical restraint. The RNA can be used to non-aversively manage aggression in patients with brain injury and with differing levels of functional impairment. Programs adopting the RNA can potentially manage brain injury-related aggression without seclusion or mechanical restraint. Implications for Rehabilitation The Relational Neurobehavioral Approach (RNA) is a set of non-aversive intervention methods to manage individuals with brain injury-related aggression. RNA methods can be used to manage aggression in patients with brain injury who have differing levels of functional impairment. Successful implementation of the RNA may allow for the management of brain injury-related aggression without seclusion or mechanical restraint.

Transcranial brain stimulation: closing the loop between brain and stimulation

DEFF Research Database (Denmark)

Karabanov, Anke; Thielscher, Axel; Siebner, Hartwig Roman

2016-01-01

-related and state-related variability. Fluctuations in brain-states can be traced online with functional brain imaging and inform the timing or other settings of transcranial brain stimulation. State-informed open-loop stimulation is aligned to the expression of a predefined brain state, according to prespecified......PURPOSE OF REVIEW: To discuss recent strategies for boosting the efficacy of noninvasive transcranial brain stimulation to improve human brain function. RECENT FINDINGS: Recent research exposed substantial intra- and inter-individual variability in response to plasticity-inducing transcranial brain...... stimulation. Trait-related and state-related determinants contribute to this variability, challenging the standard approach to apply stimulation in a rigid, one-size-fits-all fashion. Several strategies have been identified to reduce variability and maximize the plasticity-inducing effects of noninvasive...

Use of subvoxel registration and subtraction to improve demonstration of contrast enhancement in MRI of the brain

International Nuclear Information System (INIS)

Curati, W.L.; Williams, E.J.; Oatridge, A.; Hajnal, J.V.; Saeed, N.; Bydder, G.M.

1996-01-01

To assess the potential of registration of images before and after contrast medium for improving the demonstration of contrast enhancement, we compared conventional 2 D T 1-weighted spin-echo images with precisely registered 3 D volume images and subtraction images derived from them in 2 normal subjects and 30 patients with a variety of brain disease. The volume images were registered to subvoxel accuracy using a rigid body translation and rotation, sinc interpolation and a least-squares fit; subtraction images were obtained from these. Normal contrast enhancement was demonstrated better with positionally registered volume and subtraction images than with conventional images in the meninges, ependyma, diploic veins, scalp, skin, orbit and sinuses. Abnormal enhancement was seen better in meningeal disease, multiple sclerosis and tumours as well as on follow-up studies. Subvoxel registration of images before and after contrast medium may be of considerable value in the recognition of contrast enhancement where there are small changes, or where the changes affect tissues with high or low baseline signal values. The technique also appears likely to be of value in demonstrating contrast enhancement in tissues at inferfaces and at other areas of complex anatomy, and in follow-up studies. (orig.). With 4 figs., 4 tabs

Optogenetic Approaches for Mesoscopic Brain Mapping.

Science.gov (United States)

Kyweriga, Michael; Mohajerani, Majid H

2016-01-01

Recent advances in identifying genetically unique neuronal proteins has revolutionized the study of brain circuitry. Researchers are now able to insert specific light-sensitive proteins (opsins) into a wide range of specific cell types via viral injections or by breeding transgenic mice. These opsins enable the activation, inhibition, or modulation of neuronal activity with millisecond control within distinct brain regions defined by genetic markers. Here we present a useful guide to implement this technique into any lab. We first review the materials needed and practical considerations and provide in-depth instructions for acute surgeries in mice. We conclude with all-optical mapping techniques for simultaneous recording and manipulation of population activity of many neurons in vivo by combining arbitrary point optogenetic stimulation and regional voltage-sensitive dye imaging. It is our intent to make these methods available to anyone wishing to use them.

In Vivo MRI Mapping of Brain Iron Deposition across the Adult Lifespan.

Science.gov (United States)

Acosta-Cabronero, Julio; Betts, Matthew J; Cardenas-Blanco, Arturo; Yang, Shan; Nestor, Peter J

2016-01-13

Disruption of iron homeostasis as a consequence of aging is thought to cause iron levels to increase, potentially promoting oxidative cellular damage. Therefore, understanding how this process evolves through the lifespan could offer insights into both the aging process and the development of aging-related neurodegenerative brain diseases. This work aimed to map, in vivo for the first time with an unbiased whole-brain approach, age-related iron changes using quantitative susceptibility mapping (QSM)--a new postprocessed MRI contrast mechanism. To this end, a full QSM standardization routine was devised and a cohort of N = 116 healthy adults (20-79 years of age) was studied. The whole-brain and ROI analyses confirmed that the propensity of brain cells to accumulate excessive iron as a function of aging largely depends on their exact anatomical location. Whereas only patchy signs of iron scavenging were observed in white matter, strong, bilateral, and confluent QSM-age associations were identified in several deep-brain nuclei--chiefly the striatum and midbrain-and across motor, premotor, posterior insular, superior prefrontal, and cerebellar cortices. The validity of QSM as a suitable in vivo imaging technique with which to monitor iron dysregulation in the human brain was demonstrated by confirming age-related increases in several subcortical nuclei that are known to accumulate iron with age. The study indicated that, in addition to these structures, there is a predilection for iron accumulation in the frontal lobes, which when combined with the subcortical findings, suggests that iron accumulation with age predominantly affects brain regions concerned with motor/output functions. This study used a whole--brain imaging approach known as quantitative susceptibility mapping (QSM) to provide a novel insight into iron accumulation in the brain across the adult lifespan. Validity of the method was demonstrated by showing concordance with ROI analysis and prior knowledge

Effects of Brain-Based Learning Approach on Students' Motivation and Attitudes Levels in Science Class

Science.gov (United States)

Akyurek, Erkan; Afacan, Ozlem

2013-01-01

The purpose of the study was to examine the effect of brain-based learning approach on attitudes and motivation levels in 8th grade students' science classes. The main reason for examining attitudes and motivation levels, the effect of the short-term motivation, attitude shows the long-term effect. The pre/post-test control group research model…

Brain metastases from thyroid carcinoma : studies of cases

International Nuclear Information System (INIS)

Perumal, N.S.; Kotze, T.; Vangu, M.D.T.H.W.

2004-01-01

Full text: Introduction: Because brain metastasis from well differentiated thyroid carcinoma is rare, management of patients presenting with this condition lacks consensus. A recent review of the literature found 17 reports of 75 cases from 1966-2001 in which 28 metastasis were from the brain, 5 from the spinal cord, 2 to both brain and spinal cord, We report our 5 cases with a focus on the last patient. Clinical presentation: A 66-year-old female treated by us for the past 10 years for papillary carcinoma of the thyroid with metastasis to bone. She presented in July 2003 with sudden onset of seizure. A non contrast CT scan demonstrated a solitary lesion in the right anterior high parietal region with a possible second lesion. Intervention: She underwent right frontal craniotomy to expose superior sagittal sinus. An inter-hemispheric approach demonstrated a tumor in the supra-meningeal gyrus that was attached to the calloso-meningeal artery. The histopathology of the surgical specimen confirmed a follicular variant of papillary carcinoma of the thyroid. She then received 11100 MBq 1-131 irradiation, Conclusion: the best therapeutic option for brain metastasis seems to be surgical resection with or without post operative Irradiation with 1-131. Central nervous system metastasis should always be investigated and treated aggressively to improve patients' long term outcome. (author)

Brain-to-Brain Synchrony Tracks Real-World Dynamic Group Interactions in the Classroom.

Science.gov (United States)

Dikker, Suzanne; Wan, Lu; Davidesco, Ido; Kaggen, Lisa; Oostrik, Matthias; McClintock, James; Rowland, Jess; Michalareas, Georgios; Van Bavel, Jay J; Ding, Mingzhou; Poeppel, David

2017-05-08

The human brain has evolved for group living [1]. Yet we know so little about how it supports dynamic group interactions that the study of real-world social exchanges has been dubbed the "dark matter of social neuroscience" [2]. Recently, various studies have begun to approach this question by comparing brain responses of multiple individuals during a variety of (semi-naturalistic) tasks [3-15]. These experiments reveal how stimulus properties [13], individual differences [14], and contextual factors [15] may underpin similarities and differences in neural activity across people. However, most studies to date suffer from various limitations: they often lack direct face-to-face interaction between participants, are typically limited to dyads, do not investigate social dynamics across time, and, crucially, they rarely study social behavior under naturalistic circumstances. Here we extend such experimentation drastically, beyond dyads and beyond laboratory walls, to identify neural markers of group engagement during dynamic real-world group interactions. We used portable electroencephalogram (EEG) to simultaneously record brain activity from a class of 12 high school students over the course of a semester (11 classes) during regular classroom activities (Figures 1A-1C; Supplemental Experimental Procedures, section S1). A novel analysis technique to assess group-based neural coherence demonstrates that the extent to which brain activity is synchronized across students predicts both student class engagement and social dynamics. This suggests that brain-to-brain synchrony is a possible neural marker for dynamic social interactions, likely driven by shared attention mechanisms. This study validates a promising new method to investigate the neuroscience of group interactions in ecologically natural settings. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

Energy Technology Data Exchange (ETDEWEB)

Li, Minghui [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Wang, Junsong, E-mail: wang.junsong@gmail.com [Center for Molecular Metabolism, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 200 Xiao Ling Wei Street, Nanjing 210094 (China); Lu, Zhaoguang; Wei, Dandan; Yang, Minghua [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Kong, Lingyi, E-mail: cpu_lykong@126.com [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China)

2014-01-15

Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a {sup 1}H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment.

NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

International Nuclear Information System (INIS)

Li, Minghui; Wang, Junsong; Lu, Zhaoguang; Wei, Dandan; Yang, Minghua; Kong, Lingyi

2014-01-01

Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a 1 H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment

Neuroimaging in nuclear medicine: drug addicted brain

Energy Technology Data Exchange (ETDEWEB)

Chung, Yong-An; Kim, Dae-Jin [The Catholic University of Korea, Seoul (Korea, Republic of)

2006-02-15

Addiction to illicit drugs in one of today's most important social issues. Most addictive drugs lead to irreversible parenchymal changes in the human brain. Neuroimaging data bring to light the pharmacodynamics and pharmacokinetics of the abused drugs, and demonstrate that addiction is a disease of the brain. Continuous researches better illustrate the neurochemical alterations in brain function, and attempt to discover the links to consequent behavioral changes. Newer hypotheses and theories follow the numerous results, and more rational methods of approaching therapy are being developed. Substance abuse is on the rise in Korea, and social interest in the matter as well. On the other hand, diagnosis and treatment of drug addiction is still very difficult, because how the abused substance acts in the brain, or how it leads to behavioral problems in not widely known. Therefore, understanding the mechanism of drug addiction can improve the process of diagnosing addict patients, planning therapy, and predicting the prognosis . Neuroimaging approaches by nuclear medicine methods are expected to objectively judge behavioral and neurochemical changes, and response to treatment. In addition, as genes associated with addictive behavior are discovered, functional nuclear medicine images will aid in the assessment of individuals. Reviewing published literature on neuroimaging regarding nuclear medicine is expected to be of assistance to the management of drug addict patients. What's more, means of applying nuclear medicine to the care of drug addict patients should be investigated further.

Neuroimaging in nuclear medicine: drug addicted brain

International Nuclear Information System (INIS)

Chung, Yong-An; Kim, Dae-Jin

2006-01-01

Addiction to illicit drugs in one of today's most important social issues. Most addictive drugs lead to irreversible parenchymal changes in the human brain. Neuroimaging data bring to light the pharmacodynamics and pharmacokinetics of the abused drugs, and demonstrate that addiction is a disease of the brain. Continuous researches better illustrate the neurochemical alterations in brain function, and attempt to discover the links to consequent behavioral changes. Newer hypotheses and theories follow the numerous results, and more rational methods of approaching therapy are being developed. Substance abuse is on the rise in Korea, and social interest in the matter as well. On the other hand, diagnosis and treatment of drug addiction is still very difficult, because how the abused substance acts in the brain, or how it leads to behavioral problems in not widely known. Therefore, understanding the mechanism of drug addiction can improve the process of diagnosing addict patients, planning therapy, and predicting the prognosis . Neuroimaging approaches by nuclear medicine methods are expected to objectively judge behavioral and neurochemical changes, and response to treatment. In addition, as genes associated with addictive behavior are discovered, functional nuclear medicine images will aid in the assessment of individuals. Reviewing published literature on neuroimaging regarding nuclear medicine is expected to be of assistance to the management of drug addict patients. What's more, means of applying nuclear medicine to the care of drug addict patients should be investigated further

Are microglia minding us? Digging up the unconscious mind-brain relationship from a neuropsychoanalytic approach.

Directory of Open Access Journals (Sweden)

Takahiro A. Kato

2013-02-01

Full Text Available The unconscious mind-brain relationship remains unresolved. From the perspective of neuroscience, neuronal networks including synapses have been dominantly believed to play crucial roles in human mental activities, while glial contribution to mental activities has long been ignored. Recently, it has been suggested that microglia, glial cells with immunological/inflammatory functions, play important roles in psychiatric disorders. Newly revealed microglial roles, such as constant direct contact with synapses even in normal brain, have defied the common traditional belief that microglia do not contribution to neuronal networks. Recent human neuroeconomic investigations with healthy volunteers using minocycline, an antibiotic with inhibitory effects on microglial activation, suggest that microglia may unconsciously modulate human social behaviors as noise.We herein propose a novel unconscious mind structural system in the brain centering on microglia from a neuropsychoanalytic approach. At least to some extent, microglial activation in the brain may activate unconscious drives as psychological immune memory/reaction in the mind, and result in various emotions, traumatic reactions, psychiatric symptoms including suicidal behaviors, and (psychoanalytic transference during interpersonal relationships. Microglia have the potential to bridge the huge gap between neuroscience, biological psychiatry, psychology and psychoanalysis as a key player to connect the conscious and the unconscious world.

Left Brain to Right Brain: Notes from the Human Laboratory.

Science.gov (United States)

Baumli, Francis

1982-01-01

Examines the implications of the left brain-right brain theory on communications styles in male-female relationships. The author contends that women tend to use the vagueness of their emotional responses manipulatively. Men need to apply rational approaches to increase clarity in communication. (AM)

Does ECT alter brain structure?

Science.gov (United States)

Devanand, D P; Dwork, A J; Hutchinson, E R; Bolwig, T G; Sackeim, H A

1994-07-01

The purpose of this study was to evaluate whether ECT causes structural brain damage. The literature review covered the following areas: cognitive side effects, structural brain imaging, autopsies of patients who had received ECT, post-mortem studies of epileptic subjects, animal studies of electroconvulsive shock (ECS) and epilepsy, and the neuropathological effects of the passage of electricity, heat generation, and blood-brain barrier disruption. ECT-induced cognitive deficits are transient, although spotty memory loss may persist for events immediately surrounding the ECT course. Prospective computerized tomography and magnetic resonance imaging studies show no evidence of ECT-induced structural changes. Some early human autopsy case reports from the unmodified ECT era reported cerebrovascular lesions that were due to agonal changes or undiagnosed disease. In animal ECS studies that used a stimulus intensity and frequency comparable to human ECT, no neuronal loss was seen when appropriate control animals, blind ratings, and perfusion fixation techniques were employed. Controlled studies using quantitative cell counts have failed to show neuronal loss even after prolonged courses of ECS. Several well-controlled studies have demonstrated that neuronal loss occurs only after 1.5 to 2 hours of continuous seizure activity in primates, and adequate muscle paralysis and oxygenation further delay these changes. These conditions are not approached during ECT. Other findings indicate that the passage of electricity, thermal effects, and the transient disruption of the blood-brain barrier during ECS do not result in structural brain damage. There is no credible evidence that ECT causes structural brain damage.

Brain-to-text: Decoding spoken phrases from phone representations in the brain

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Christian eHerff

2015-06-01

Full Text Available It has long been speculated whether communication between humans and machines based on natural speech related cortical activity is possible. Over the past decade, studies have suggested that it is feasible to recognize isolated aspects of speech from neural signals, such as auditory features, phones or one of a few isolated words. However, until now it remained an unsolved challenge to decode continuously spoken speech from the neural substrate associated with speech and language processing. Here, we show for the first time that continuously spoken speech can be decoded into the expressed words from intracranial electrocorticographic (ECoG recordings. Specifically, we implemented a system, which we call Brain-To-Text that models single phones, employs techniques from automatic speech recognition (ASR, and thereby transforms brain activity while speaking into the corresponding textual representation. Our results demonstrate that our system achieved word error rates as low as 25% and phone error rates below 50%. Additionally, our approach contributes to the current understanding of the neural basis of continuous speech production by identifying those cortical regions that hold substantial information about individual phones. In conclusion, the Brain-To-Text system described in this paper represents an important step towards human-machine communication based on imagined speech.

Brain shaving: adaptive detection for brain PET data

International Nuclear Information System (INIS)

Grecchi, Elisabetta; Doyle, Orla M; Turkheimer, Federico E; Bertoldo, Alessandra; Pavese, Nicola

2014-01-01

The intricacy of brain biology is such that the variation of imaging end-points in health and disease exhibits an unpredictable range of spatial distributions from the extremely localized to the very diffuse. This represents a challenge for the two standard approaches to analysis, the mass univariate and the multivariate that exhibit either strong specificity but not as good sensitivity (the former) or poor specificity and comparatively better sensitivity (the latter). In this work, we develop an analytical methodology for positron emission tomography that operates an extraction (‘shaving’) of coherent patterns of signal variation while maintaining control of the type I error. The methodology operates two rotations on the image data, one local using the wavelet transform and one global using the singular value decomposition. The control of specificity is obtained by using the gap statistic that selects, within each eigenvector, a subset of significantly coherent elements. Face-validity of the algorithm is demonstrated using a paradigmatic data-set with two radiotracers, [ 11 C]-raclopride and [ 11 C]-(R)-PK11195, measured on the same Huntington's disease patients, a disorder with a genetic based diagnosis. The algorithm is able to detect the two well-known separate but connected processes of dopamine neuronal loss (localized in the basal ganglia) and neuroinflammation (diffusive around the whole brain). These processes are at the two extremes of the distributional envelope, one being very sparse and the latter being perfectly Gaussian and they are not adequately detected by the univariate and the multivariate approaches. (paper)

Brain shaving: adaptive detection for brain PET data

Science.gov (United States)

Grecchi, Elisabetta; Doyle, Orla M.; Bertoldo, Alessandra; Pavese, Nicola; Turkheimer, Federico E.

2014-05-01

The intricacy of brain biology is such that the variation of imaging end-points in health and disease exhibits an unpredictable range of spatial distributions from the extremely localized to the very diffuse. This represents a challenge for the two standard approaches to analysis, the mass univariate and the multivariate that exhibit either strong specificity but not as good sensitivity (the former) or poor specificity and comparatively better sensitivity (the latter). In this work, we develop an analytical methodology for positron emission tomography that operates an extraction (‘shaving’) of coherent patterns of signal variation while maintaining control of the type I error. The methodology operates two rotations on the image data, one local using the wavelet transform and one global using the singular value decomposition. The control of specificity is obtained by using the gap statistic that selects, within each eigenvector, a subset of significantly coherent elements. Face-validity of the algorithm is demonstrated using a paradigmatic data-set with two radiotracers, [11C]-raclopride and [11C]-(R)-PK11195, measured on the same Huntington's disease patients, a disorder with a genetic based diagnosis. The algorithm is able to detect the two well-known separate but connected processes of dopamine neuronal loss (localized in the basal ganglia) and neuroinflammation (diffusive around the whole brain). These processes are at the two extremes of the distributional envelope, one being very sparse and the latter being perfectly Gaussian and they are not adequately detected by the univariate and the multivariate approaches.

Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

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Ming-Xiong Huang

2014-01-01

Full Text Available Traumatic brain injury (TBI is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz that can be measured and localized by resting-state magnetoencephalography (MEG. In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes, our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes, blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI.

Immunotherapy targeting immune check-point(s) in brain metastases.

Science.gov (United States)

Di Giacomo, Anna Maria; Valente, Monica; Covre, Alessia; Danielli, Riccardo; Maio, Michele

2017-08-01

Immunotherapy with monoclonal antibodies (mAb) directed to different immune check-point(s) is showing a significant clinical impact in a growing number of human tumors of different histotype, both in terms of disease response and long-term survival patients. In this rapidly changing scenario, treatment of brain metastases remains an high unmeet medical need, and the efficacy of immunotherapy in these highly dismal clinical setting remains to be largely demonstrated. Nevertheless, up-coming observations are beginning to suggest a clinical potential of cancer immunotherapy also in brain metastases, regardless the underlying tumor histotype. These observations remain to be validated in larger clinical trials eventually designed also to address the efficacy of therapeutic mAb to immune check-point(s) within multimodality therapies for brain metastases. Noteworthy, the initial proofs of efficacy on immunotherapy in central nervous system metastases are already fostering clinical trials investigating its therapeutic potential also in primary brain tumors. We here review ongoing immunotherapeutic approaches to brain metastases and primary brain tumors, and the foreseeable strategies to overcome their main biologic hurdles and clinical challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electric Field Encephalography as a tool for functional brain research: a modeling study.

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Yury Petrov

Full Text Available We introduce the notion of Electric Field Encephalography (EFEG based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2-3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.

The effect of brain based learning with contextual approach viewed from adversity quotient

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Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi, R.

2018-05-01

The aim of this research was to find out the effect of Brain Based Learning (BBL) with contextual approach viewed from adversity quotient (AQ) on mathematics achievement. BBL-contextual is the model to optimize the brain in the new concept learning and real life problem solving by making the good environment. Adversity Quotient is the ability to response and faces the problems. In addition, it is also about how to turn the difficulties into chances. This AQ classified into quitters, campers, and climbers. The research method used in this research was quasi experiment by using 2x3 factorial designs. The sample was chosen by using stratified cluster random sampling. The instruments were test and questionnaire for the data of AQ. The results showed that (1) BBL-contextual is better than direct learning on mathematics achievement, (2) there is no significant difference between each types of AQ on mathematics achievement, and (3) there is no interaction between learning model and AQ on mathematics achievement.

Multiscale modeling and simulation of brain blood flow

Energy Technology Data Exchange (ETDEWEB)

Perdikaris, Paris, E-mail: parisp@mit.edu [Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Grinberg, Leopold, E-mail: leopoldgrinberg@us.ibm.com [IBM T.J Watson Research Center, 1 Rogers St, Cambridge, Massachusetts 02142 (United States); Karniadakis, George Em, E-mail: george-karniadakis@brown.edu [Division of Applied Mathematics, Brown University, Providence, Rhode Island 02912 (United States)

2016-02-15

The aim of this work is to present an overview of recent advances in multi-scale modeling of brain blood flow. In particular, we present some approaches that enable the in silico study of multi-scale and multi-physics phenomena in the cerebral vasculature. We discuss the formulation of continuum and atomistic modeling approaches, present a consistent framework for their concurrent coupling, and list some of the challenges that one needs to overcome in achieving a seamless and scalable integration of heterogeneous numerical solvers. The effectiveness of the proposed framework is demonstrated in a realistic case involving modeling the thrombus formation process taking place on the wall of a patient-specific cerebral aneurysm. This highlights the ability of multi-scale algorithms to resolve important biophysical processes that span several spatial and temporal scales, potentially yielding new insight into the key aspects of brain blood flow in health and disease. Finally, we discuss open questions in multi-scale modeling and emerging topics of future research.

Demonstration of cerebral abnormalities in cocaine abusers with SPECT perfusion brain scans

International Nuclear Information System (INIS)

Nagel, J.S.; Tumeh, S.S.; English, R.J.; Moore, M.; Lee, V.W.; Holman, L.B.

1989-01-01

This paper reports I-123 isopropyl iodoamphetamine (IMP) single-photon emission CT (SPECT) brain scans performed on cocaine users to investigate the effects of cocaine on the cerebral perfusion in a manner similar to previous CT, angiographic and positron-emission tomographic (PET) studies. Ten asymptomatic or mildly symptomatic cocaine users, two users with major neurovascular complications, and five normal subjects were studied with IMP SPECT. Rotating-brain images of the cerebral IMP uptake were displayed by using a distance-weighted surface-projection technique and were visually analyzed for focal cortical perfusion deficits. Eleven cocaine users had multiple scattered cortical IMP defects. Frontal lobe defects were most prominent. One user had confluent defects resembling swiss cheese. Concurrent CT scans available in nine patients were negative in seven and showed infarcts in two. No similar focal findings were visible in normals

Crossing the Blood-Brain Barrier: Recent Advances in Drug Delivery to the Brain.

Science.gov (United States)

Patel, Mayur M; Patel, Bhoomika M

2017-02-01

CNS disorders are on the rise despite advancements in our understanding of their pathophysiological mechanisms. A major hurdle to the treatment of these disorders is the blood-brain barrier (BBB), which serves as an arduous janitor to protect the brain. Many drugs are being discovered for CNS disorders, which, however fail to enter the market because of their inability to cross the BBB. This is a pronounced challenge for the pharmaceutical fraternity. Hence, in addition to the discovery of novel entities and drug candidates, scientists are also developing new formulations of existing drugs for brain targeting. Several approaches have been investigated to allow therapeutics to cross the BBB. As the molecular structure of the BBB is better elucidated, several key approaches for brain targeting include physiological transport mechanisms such as adsorptive-mediated transcytosis, inhibition of active efflux pumps, receptor-mediated transport, cell-mediated endocytosis, and the use of peptide vectors. Drug-delivery approaches comprise delivery from microspheres, biodegradable wafers, and colloidal drug-carrier systems (e.g., liposomes, nanoparticles, nanogels, dendrimers, micelles, nanoemulsions, polymersomes, exosomes, and quantum dots). The current review discusses the latest advancements in these approaches, with a major focus on articles published in 2015 and 2016. In addition, we also cover the alternative delivery routes, such as intranasal and convection-enhanced diffusion methods, and disruption of the BBB for brain targeting.

Data-driven forward model inference for EEG brain imaging

DEFF Research Database (Denmark)

Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

2016-01-01

Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

Contrast enhancement in EIT imaging of the brain

International Nuclear Information System (INIS)

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data. (paper)

Contrast enhancement in EIT imaging of the brain.

Science.gov (United States)

Nissinen, A; Kaipio, J P; Vauhkonen, M; Kolehmainen, V

2016-01-01

We consider electrical impedance tomography (EIT) imaging of the brain. The brain is surrounded by the poorly conducting skull which has low conductivity compared to the brain. The skull layer causes a partial shielding effect which leads to weak sensitivity for the imaging of the brain tissue. In this paper we propose an approach based on the Bayesian approximation error approach, to enhance the contrast in brain imaging. With this approach, both the (uninteresting) geometry and the conductivity of the skull are embedded in the approximation error statistics, which leads to a computationally efficient algorithm that is able to detect features such as internal haemorrhage with significantly increased sensitivity and specificity. We evaluate the approach with simulations and phantom data.

Scholastic performance and functional connectivity of brain networks in children.

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Laura Chaddock-Heyman

Full Text Available One of the keys to understanding scholastic success is to determine the neural processes involved in school performance. The present study is the first to use a whole-brain connectivity approach to explore whether functional connectivity of resting state brain networks is associated with scholastic performance in seventy-four 7- to 9-year-old children. We demonstrate that children with higher scholastic performance across reading, math and language have more integrated and interconnected resting state networks, specifically the default mode network, salience network, and frontoparietal network. To add specificity, core regions of the dorsal attention and visual networks did not relate to scholastic performance. The results extend the cognitive role of brain networks in children as well as suggest the importance of network connectivity in scholastic success.

Lutein and Brain Function

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John W. Erdman

2015-10-01

Full Text Available Lutein is one of the most prevalent carotenoids in nature and in the human diet. Together with zeaxanthin, it is highly concentrated as macular pigment in the foveal retina of primates, attenuating blue light exposure, providing protection from photo-oxidation and enhancing visual performance. Recently, interest in lutein has expanded beyond the retina to its possible contributions to brain development and function. Only primates accumulate lutein within the brain, but little is known about its distribution or physiological role. Our team has begun to utilize the rhesus macaque (Macaca mulatta model to study the uptake and bio-localization of lutein in the brain. Our overall goal has been to assess the association of lutein localization with brain function. In this review, we will first cover the evolution of the non-human primate model for lutein and brain studies, discuss prior association studies of lutein with retina and brain function, and review approaches that can be used to localize brain lutein. We also describe our approach to the biosynthesis of 13C-lutein, which will allow investigation of lutein flux, localization, metabolism and pharmacokinetics. Lastly, we describe potential future research opportunities.

Randomized trial of two swallowing assessment approaches in patients with acquired brain injury

DEFF Research Database (Denmark)

Kjaersgaard, Annette; Nielsen, Lars Hedemann; Sjölund, Bengt H.

2014-01-01

trial. SETTING: Specialized, national neurorehabilitation centre. SUBJECTS: Adult patients with acquired brain injury. Six hundred and seventy-nine patients were assessed for eligibility and 138 were randomly allocated between June 2009 and April 2011. INTERVENTIONS: Assessment by Facial-Oral Tract....... Seven patients were left for analysis, 4 of whom developed aspiration pneumonia within 10 days after initiating oral intake (1 control/3 interventions). CONCLUSION: In the presence of a structured clinical assessment with the Facial-Oral Tract Therapy approach, it is unnecessary to undertake...

Prospective memory after moderate-to-severe traumatic brain injury: a multinomial modeling approach.

Science.gov (United States)

Pavawalla, Shital P; Schmitter-Edgecombe, Maureen; Smith, Rebekah E

2012-01-01

Prospective memory (PM), which can be understood as the processes involved in realizing a delayed intention, is consistently found to be impaired after a traumatic brain injury (TBI). Although PM can be empirically dissociated from retrospective memory, it inherently involves both a prospective component (i.e., remembering that an action needs to be carried out) and retrospective components (i.e., remembering what action needs to be executed and when). This study utilized a multinomial processing tree model to disentangle the prospective (that) and retrospective recognition (when) components underlying PM after moderate-to-severe TBI. Seventeen participants with moderate to severe TBI and 17 age- and education-matched control participants completed an event-based PM task that was embedded within an ongoing computer-based color-matching task. The multinomial processing tree modeling approach revealed a significant group difference in the prospective component, indicating that the control participants allocated greater preparatory attentional resources to the PM task compared to the TBI participants. Participants in the TBI group were also found to be significantly more impaired than controls in the when aspect of the retrospective component. These findings indicated that the TBI participants had greater difficulty allocating the necessary preparatory attentional resources to the PM task and greater difficulty discriminating between PM targets and nontargets during task execution, despite demonstrating intact posttest recall and/or recognition of the PM tasks and targets.

Test of the 'glymphatic' hypothesis demonstrates diffusive and aquaporin-4-independent solute transport in rodent brain parenchyma.

Science.gov (United States)

Smith, Alex J; Yao, Xiaoming; Dix, James A; Jin, Byung-Ju; Verkman, Alan S

2017-08-21

Transport of solutes through brain involves diffusion and convection. The importance of convective flow in the subarachnoid and paravascular spaces has long been recognized; a recently proposed 'glymphatic' clearance mechanism additionally suggests that aquaporin-4 (AQP4) water channels facilitate convective transport through brain parenchyma. Here, the major experimental underpinnings of the glymphatic mechanism were re-examined by measurements of solute movement in mouse brain following intracisternal or intraparenchymal solute injection. We found that: (i) transport of fluorescent dextrans in brain parenchyma depended on dextran size in a manner consistent with diffusive rather than convective transport; (ii) transport of dextrans in the parenchymal extracellular space, measured by 2-photon fluorescence recovery after photobleaching, was not affected just after cardiorespiratory arrest; and (iii) Aqp4 gene deletion did not impair transport of fluorescent solutes from sub-arachnoid space to brain in mice or rats. Our results do not support the proposed glymphatic mechanism of convective solute transport in brain parenchyma.

Conscious brain-to-brain communication in humans using non-invasive technologies.

Science.gov (United States)

Grau, Carles; Ginhoux, Romuald; Riera, Alejandro; Nguyen, Thanh Lam; Chauvat, Hubert; Berg, Michel; Amengual, Julià L; Pascual-Leone, Alvaro; Ruffini, Giulio

2014-01-01

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Conscious brain-to-brain communication in humans using non-invasive technologies.

Directory of Open Access Journals (Sweden)

Carles Grau

Full Text Available Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI. These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B communication between subjects (hyperinteraction. Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG changes with a CBI inducing the conscious perception of phosphenes (light flashes through neuronavigated, robotized transcranial magnetic stimulation (TMS, with special care taken to block sensory (tactile, visual or auditory cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Selectionist and evolutionary approaches to brain function: a critical appraisal

Directory of Open Access Journals (Sweden)

Chrisantha Thomas Fernando

2012-04-01

Full Text Available We consider approaches to brain dynamics and function that have been claimed to be Darwinian. These include Edelman’s theory of neuronal group selection, Changeux’s theory of synaptic selection and selective stabilization of pre-representations, Seung’s Darwinian synapse, Loewenstein’s synaptic melioration, Adam’s selfish synapse and Calvin’s replicating activity patterns. Except for the last two, the proposed mechanisms are selectionist but not truly Darwinian, because no replicators with information transfer to copies and hereditary variation can be identified in them. All of them fit, however, a generalized selectionist framework conforming to the picture of Price’s covariance formulation, which deliberately was not specific even to selection in biology, and therefore does not imply an algorithmic picture of biological evolution. Bayesian models and reinforcement learning are formally in agreement with selection dynamics. A classification of search algorithms is shown to include Darwinian replicators (evolutionary units with multiplication, heredity and variability as the most powerful mechanism in a sparsely occupied search space. Examples of why parallel competitive search with information transfer among the units is efficient are given. Finally, we review our recent attempts to construct and analyze simple models of true Darwinian evolutionary units in the brain in terms of connectivity and activity copying of neuronal groups. Although none of the proposed neuronal replicators include miraculous mechanisms, their identification remains a challenge but also a great promise.

Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI

Science.gov (United States)

Fox, Michael D.; Qian, Tianyi; Madsen, Joseph R.; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-cong; Groppe, David M.; Mehta, Ashesh D.; Hong, Bo; Liu, Hesheng

2016-01-01

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20 years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach is demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. PMID:26408860

What a Brain!

Science.gov (United States)

Love, Kim

1997-01-01

Outlines basic concepts about how the brain develops and considers how Head Start teachers and parents can take full advantage of the brain's multisensory learning approach to develop more effective ways to interact with children. Focuses on the critical developmental period for stimulating neurons and developing neural connections. Suggests…

Brain spontaneous fluctuations in sensorimotor regions were directly related to eyes open and eyes closed: evidences from a machine learning approach

Directory of Open Access Journals (Sweden)

Bishan eLiang

2014-08-01

Full Text Available Previous studies have demonstrated that the difference between resting-state brain activations depends on whether the subject was eyes open (EO or eyes closed (EC. However, whether the spontaneous fluctuations are directly related to these two different resting states are still largely unclear. In the present study, we acquired resting-state functional magnetic resonance imaging data from 24 healthy subjects (11 males, 20.17 ± 2.74 years under the EO and EC states. The amplitude of the spontaneous brain activity in low-frequency band was subsequently investigated by using the metric of fractional amplitude of low frequency fluctuation (fALFF for each subject under each state. A support vector machine (SVM analysis was then applied to evaluate whether the category of resting states could be determined from the brain spontaneous fluctuations. We demonstrated that these two resting states could be decoded from the identified pattern of brain spontaneous fluctuations, predominantly based on fALFF in the sensorimotor module. Specifically, we observed prominent relationships between increased fALFF for EC and decreased fALFF for EO in sensorimotor regions. Overall, the present results indicate that a SVM performs well in the discrimination between the brain spontaneous fluctuations of distinct resting states and provide new insight into the neural substrate of the resting states during EC and EO.

The modular organization of human anatomical brain networks: Accounting for the cost of wiring

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Richard F. Betzel

2017-02-01

Full Text Available Brain networks are expected to be modular. However, existing techniques for estimating a network’s modules make it difficult to assess the influence of organizational principles such as wiring cost reduction on the detected modules. Here we present a modification of an existing module detection algorithm that allowed us to focus on connections that are unexpected under a cost-reduction wiring rule and to identify modules from among these connections. We applied this technique to anatomical brain networks and showed that the modules we detected differ from those detected using the standard technique. We demonstrated that these novel modules are spatially distributed, exhibit unique functional fingerprints, and overlap considerably with rich clubs, giving rise to an alternative and complementary interpretation of the functional roles of specific brain regions. Finally, we demonstrated that, using the modified module detection approach, we can detect modules in a developmental dataset that track normative patterns of maturation. Collectively, these findings support the hypothesis that brain networks are composed of modules and provide additional insight into the function of those modules.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

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Sofia D Karamintziou

Full Text Available Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

Algorithmic design of a noise-resistant and efficient closed-loop deep brain stimulation system: A computational approach.

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Karamintziou, Sofia D; Custódio, Ana Luísa; Piallat, Brigitte; Polosan, Mircea; Chabardès, Stéphan; Stathis, Pantelis G; Tagaris, George A; Sakas, Damianos E; Polychronaki, Georgia E; Tsirogiannis, George L; David, Olivier; Nikita, Konstantina S

2017-01-01

Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed. First, we propose an efficient method drawn from dynamical systems theory, for the reliable assessment of significant nonlinear coupling between beta and high-frequency subthalamic neuronal activity, as a biomarker for feedback control. Further, we present a model-based strategy through which optimal parameters of stimulation for minimum energy desynchronizing control of neuronal activity are being identified. The strategy integrates stochastic modeling and derivative-free optimization of neural dynamics based on quadratic modeling. On the basis of numerical simulations, we demonstrate the potential of the presented modeling approach to identify, at a relatively low computational cost, stimulation settings potentially associated with a significantly higher degree of efficiency and selectivity compared with stimulation settings determined post-operatively. Our data reinforce the hypothesis that model-based control strategies are crucial for the design of novel stimulation protocols at the backstage of clinical applications.

New approach to detect and classify stroke in skull CT images via analysis of brain tissue densities.

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Rebouças Filho, Pedro P; Sarmento, Róger Moura; Holanda, Gabriel Bandeira; de Alencar Lima, Daniel

2017-09-01

Cerebral vascular accident (CVA), also known as stroke, is an important health problem worldwide and it affects 16 million people worldwide every year. About 30% of those that have a stroke die and 40% remain with serious physical limitations. However, recovery in the damaged region is possible if treatment is performed immediately. In the case of a stroke, Computed Tomography (CT) is the most appropriate technique to confirm the occurrence and to investigate its extent and severity. Stroke is an emergency problem for which early identification and measures are difficult; however, computer-aided diagnoses (CAD) can play an important role in obtaining information imperceptible to the human eye. Thus, this work proposes a new method for extracting features based on radiological density patterns of the brain, called Analysis of Brain Tissue Density (ABTD). The proposed method is a specific approach applied to CT images to identify and classify the occurrence of stroke diseases. The evaluation of the results of the ABTD extractor proposed in this paper were compared with extractors already established in the literature, such as features from Gray-Level Co-Occurrence Matrix (GLCM), Local binary patterns (LBP), Central Moments (CM), Statistical Moments (SM), Hu's Moment (HM) and Zernike's Moments (ZM). Using a database of 420 CT images of the skull, each extractor was applied with the classifiers such as MLP, SVM, kNN, OPF and Bayesian to classify if a CT image represented a healthy brain or one with an ischemic or hemorrhagic stroke. ABTD had the shortest extraction time and the highest average accuracy (99.30%) when combined with OPF using the Euclidean distance. Also, the average accuracy values for all classifiers were higher than 95%. The relevance of the results demonstrated that the ABTD method is a useful algorithm to extract features that can potentially be integrated with CAD systems to assist in stroke diagnosis. Copyright © 2017 Elsevier B.V. All rights

Targeting Nanomedicine to Brain Tumors: Latest Progress and Achievements.

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Van't Root, Moniek; Lowik, Clemens; Mezzanotte, Laura

2017-01-01

Targeting nanomedicine to brain tumors is hampered by the heterogeneity of brain tumors and the blood brain barrier. These represent the main reasons of unsuccessful treatments. Nanomedicine based approaches hold promise for improved brain tissue distribution of drugs and delivery of combination therapies. In this review, we describe the recent advancements and latest achievements in the use of nanocarriers, virus and cell-derived nanoparticles for targeted therapy of brain tumors. We provide successful examples of nanomedicine based approaches for direct targeting of receptors expressed in brain tumor cells or modulation of pathways involved in cell survival as well as approaches for indirect targeting of cells in the tumor stroma and immunotherapies. Although the field is at its infancy, clinical trials involving nanomedicine based approaches for brain tumors are ongoing and many others will start in the near future. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

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Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

2016-01-01

Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches.

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Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Kozberg, Mariel G; Thibodeaux, David N; Zhao, Hanzhi T; Yu, Hang; Hillman, Elizabeth M C

2016-10-05

Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. © 2016 The Authors.

Meta-connectomics: human brain network and connectivity meta-analyses.

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Crossley, N A; Fox, P T; Bullmore, E T

2016-04-01

Abnormal brain connectivity or network dysfunction has been suggested as a paradigm to understand several psychiatric disorders. We here review the use of novel meta-analytic approaches in neuroscience that go beyond a summary description of existing results by applying network analysis methods to previously published studies and/or publicly accessible databases. We define this strategy of combining connectivity with other brain characteristics as 'meta-connectomics'. For example, we show how network analysis of task-based neuroimaging studies has been used to infer functional co-activation from primary data on regional activations. This approach has been able to relate cognition to functional network topology, demonstrating that the brain is composed of cognitively specialized functional subnetworks or modules, linked by a rich club of cognitively generalized regions that mediate many inter-modular connections. Another major application of meta-connectomics has been efforts to link meta-analytic maps of disorder-related abnormalities or MRI 'lesions' to the complex topology of the normative connectome. This work has highlighted the general importance of network hubs as hotspots for concentration of cortical grey-matter deficits in schizophrenia, Alzheimer's disease and other disorders. Finally, we show how by incorporating cellular and transcriptional data on individual nodes with network models of the connectome, studies have begun to elucidate the microscopic mechanisms underpinning the macroscopic organization of whole-brain networks. We argue that meta-connectomics is an exciting field, providing robust and integrative insights into brain organization that will likely play an important future role in consolidating network models of psychiatric disorders.

THE ROLE OF ANDROGENS AND ESTROGENS IN THE DEVELOPMENT OF BRAIN AND PERIPHERAL NERVOUS SYSTEM: APPROACHES TO DEVELOPING ANIMAL MODELS FOR SEXUALLY DIMORPHIC BEHAVIORS

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This presentation provides an overview of research on the effects of hormonally active chemicals on sexual differentiation of the brain including (a) research on the role of androgens and estrogens in the development of the brain and peripheral nervous system, (b) approaches to d...

3-D brain image registration using optimal morphological processing

International Nuclear Information System (INIS)

Loncaric, S.; Dhawan, A.P.

1994-01-01

The three-dimensional (3-D) registration of Magnetic Resonance (MR) and Positron Emission Tomographic (PET) images of the brain is important for analysis of the human brain and its diseases. A procedure for optimization of (3-D) morphological structuring elements, based on a genetic algorithm, is presented in the paper. The registration of the MR and PET images is done by means of a registration procedure in two major phases. In the first phase, the Iterative Principal Axis Transform (IPAR) is used for initial registration. In the second phase, the optimal shape description method based on the Morphological Signature Transform (MST) is used for final registration. The morphological processing is used to improve the accuracy of the basic IPAR method. The brain ventricle is used as a landmark for MST registration. A near-optimal structuring element obtained by means of a genetic algorithm is used in MST to describe the shape of the ventricle. The method has been tested on the set of brain images demonstrating the feasibility of approach. (author). 11 refs., 3 figs

Soft brain-machine interfaces for assistive robotics: A novel control approach.

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Schiatti, Lucia; Tessadori, Jacopo; Barresi, Giacinto; Mattos, Leonardo S; Ajoudani, Arash

2017-07-01

Robotic systems offer the possibility of improving the life quality of people with severe motor disabilities, enhancing the individual's degree of independence and interaction with the external environment. In this direction, the operator's residual functions must be exploited for the control of the robot movements and the underlying dynamic interaction through intuitive and effective human-robot interfaces. Towards this end, this work aims at exploring the potential of a novel Soft Brain-Machine Interface (BMI), suitable for dynamic execution of remote manipulation tasks for a wide range of patients. The interface is composed of an eye-tracking system, for an intuitive and reliable control of a robotic arm system's trajectories, and a Brain-Computer Interface (BCI) unit, for the control of the robot Cartesian stiffness, which determines the interaction forces between the robot and environment. The latter control is achieved by estimating in real-time a unidimensional index from user's electroencephalographic (EEG) signals, which provides the probability of a neutral or active state. This estimated state is then translated into a stiffness value for the robotic arm, allowing a reliable modulation of the robot's impedance. A preliminary evaluation of this hybrid interface concept provided evidence on the effective execution of tasks with dynamic uncertainties, demonstrating the great potential of this control method in BMI applications for self-service and clinical care.

Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

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Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

2017-09-01

The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

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So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

Directory of Open Access Journals (Sweden)

Nina So

Full Text Available Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing

Whole-brain radiation therapy for brain metastases: detrimental or beneficial?

International Nuclear Information System (INIS)

Gemici, Cengiz; Yaprak, Gokhan

2015-01-01

Stereotactic radiosurgery is frequently used, either alone or together with whole-brain radiation therapy to treat brain metastases from solid tumors. Certain experts and radiation oncology groups have proposed replacing whole-brain radiation therapy with stereotactic radiosurgery alone for the management of brain metastases. Although randomized trials have favored adding whole-brain radiation therapy to stereotactic radiosurgery for most end points, a recent meta-analysis demonstrated a survival disadvantage for patients treated with whole-brain radiation therapy and stereotactic radiosurgery compared with patients treated with stereotactic radiosurgery alone. However the apparent detrimental effect of adding whole-brain radiation therapy to stereotactic radiosurgery reported in this meta-analysis may be the result of inhomogeneous distribution of the patients with respect to tumor histologies, molecular histologic subtypes, and extracranial tumor stages between the groups rather than a real effect. Unfortunately, soon after this meta-analysis was published, even as an abstract, use of whole-brain radiation therapy in managing brain metastases has become controversial among radiation oncologists. The American Society of Radiation Oncology recently recommended, in their “Choose Wisely” campaign, against routinely adding whole-brain radiation therapy to stereotactic radiosurgery to treat brain metastases. However, this situation creates conflict for radiation oncologists who believe that there are enough high level of evidence for the effectiveness of whole-brain radiation therapy in the treatment of brain metastases

Neuropsychological assessment of individuals with brain tumor: Comparison of approaches used in the classification of impairment

Directory of Open Access Journals (Sweden)

Toni Maree Dwan

2015-03-01

Full Text Available Approaches to classifying neuropsychological impairment after brain tumor vary according to testing level (individual tests, domains or global index and source of reference (i.e., norms, controls and premorbid functioning. This study aimed to compare rates of impairment according to different classification approaches. Participants were 44 individuals (57% female with a primary brain tumor diagnosis (mean age = 45.6 years and 44 matched control participants (59% female, mean age = 44.5 years. All participants completed a test battery that assesses premorbid IQ (Wechsler Adult Reading Test, attention/processing speed (Digit Span, Trail Making Test A, memory (Hopkins Verbal Learning Test – Revised, Rey-Osterrieth Complex Figure-recall and executive function (Trail Making Test B, Rey-Osterrieth Complex Figure copy, Controlled Oral Word Association Test. Results indicated that across the different sources of reference, 86-93% of participants were classified as impaired at a test-specific level, 61-73% were classified as impaired at a domain-specific level, and 32-50% were classified as impaired at a global level. Rates of impairment did not significantly differ according to source of reference (p>.05; however, at the individual participant level, classification based on estimated premorbid IQ was often inconsistent with classification based on the norms or controls. Participants with brain tumor performed significantly poorer than matched controls on tests of neuropsychological functioning, including executive function (p=.001 and memory (p.05. These results highlight the need to examine individuals’ performance across a multi-faceted neuropsychological test battery to avoid over- or under-estimation of impairment.

Love songs, bird brains and diffusion tensor imaging.

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De Groof, Geert; Van der Linden, Annemie

2010-08-01

The song control system of songbirds displays a remarkable seasonal neuroplasticity in species in which song output also changes seasonally. Thus far, this song control system has been extensively analyzed by histological and electrophysiological methods. However, these approaches do not provide a global view of the brain and/or do not allow repeated measurements, which are necessary to establish causal correlations between alterations in neural substrate and behavior. Research has primarily been focused on the song nuclei themselves, largely neglecting their interconnections and other brain regions involved in seasonally changing behavior. In this review, we introduce and explore the song control system of songbirds as a natural model for brain plasticity. At the same time, we point out the added value of the songbird brain model for in vivo diffusion tensor techniques and its derivatives. A compilation of the diffusion tensor imaging (DTI) data obtained thus far in this system demonstrates the usefulness of this in vivo method for studying brain plasticity. In particular, it is shown to be a perfect tool for long-term studies of morphological and cellular changes of specific brain circuits in different endocrine/photoperiod conditions. The method has been successfully applied to obtain quantitative measurements of seasonal changes of fiber tracts and nuclei from the song control system. In addition, outside the song control system, changes have been discerned in the optic chiasm and in an interhemispheric connection. DTI allows the detection of seasonal changes in a region analogous to the mammalian secondary auditory cortex and in regions of the 'social behavior network', an interconnected group of structures that controls multiple social behaviors, including aggression and courtship. DTI allows the demonstration, for the first time, that the songbird brain in its entirety exhibits an extreme seasonal plasticity which is not merely limited to the song control

Systems Nutrigenomics Reveals Brain Gene Networks Linking Metabolic and Brain Disorders.

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Meng, Qingying; Ying, Zhe; Noble, Emily; Zhao, Yuqi; Agrawal, Rahul; Mikhail, Andrew; Zhuang, Yumei; Tyagi, Ethika; Zhang, Qing; Lee, Jae-Hyung; Morselli, Marco; Orozco, Luz; Guo, Weilong; Kilts, Tina M; Zhu, Jun; Zhang, Bin; Pellegrini, Matteo; Xiao, Xinshu; Young, Marian F; Gomez-Pinilla, Fernando; Yang, Xia

2016-05-01

Nutrition plays a significant role in the increasing prevalence of metabolic and brain disorders. Here we employ systems nutrigenomics to scrutinize the genomic bases of nutrient-host interaction underlying disease predisposition or therapeutic potential. We conducted transcriptome and epigenome sequencing of hypothalamus (metabolic control) and hippocampus (cognitive processing) from a rodent model of fructose consumption, and identified significant reprogramming of DNA methylation, transcript abundance, alternative splicing, and gene networks governing cell metabolism, cell communication, inflammation, and neuronal signaling. These signals converged with genetic causal risks of metabolic, neurological, and psychiatric disorders revealed in humans. Gene network modeling uncovered the extracellular matrix genes Bgn and Fmod as main orchestrators of the effects of fructose, as validated using two knockout mouse models. We further demonstrate that an omega-3 fatty acid, DHA, reverses the genomic and network perturbations elicited by fructose, providing molecular support for nutritional interventions to counteract diet-induced metabolic and brain disorders. Our integrative approach complementing rodent and human studies supports the applicability of nutrigenomics principles to predict disease susceptibility and to guide personalized medicine. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

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Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Current status and future role of brain PET/MRI in clinical and research settings

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Werner, P.; Barthel, H.; Sabri, O. [University Hospital Leipzig, Department of Nuclear Medicine, Leipzig (Germany); Drzezga, A. [University Hospital Cologne, Department of Nuclear Medicine, Koeln (Germany)

2015-01-09

Hybrid PET/MRI systematically offers a complementary combination of two modalities that has often proven itself superior to the single modality approach in the diagnostic work-up of many neurological and psychiatric diseases. Emerging PET tracers, technical advances in multiparametric MRI and obvious workflow advantages may lead to a significant improvement in the diagnosis of dementia disorders, neurooncological diseases, epilepsy and neurovascular diseases using PET/MRI. Moreover, simultaneous PET/MRI is well suited to complex studies of brain function in which fast fluctuations of brain signals (e.g. related to task processing or in response to pharmacological interventions) need to be monitored on multiple levels. Initial simultaneous studies have already demonstrated that these complementary measures of brain function can provide new insights into the functional and structural organization of the brain. (orig.)

Current status and future role of brain PET/MRI in clinical and research settings

International Nuclear Information System (INIS)

Werner, P.; Barthel, H.; Sabri, O.; Drzezga, A.

2015-01-01

Hybrid PET/MRI systematically offers a complementary combination of two modalities that has often proven itself superior to the single modality approach in the diagnostic work-up of many neurological and psychiatric diseases. Emerging PET tracers, technical advances in multiparametric MRI and obvious workflow advantages may lead to a significant improvement in the diagnosis of dementia disorders, neurooncological diseases, epilepsy and neurovascular diseases using PET/MRI. Moreover, simultaneous PET/MRI is well suited to complex studies of brain function in which fast fluctuations of brain signals (e.g. related to task processing or in response to pharmacological interventions) need to be monitored on multiple levels. Initial simultaneous studies have already demonstrated that these complementary measures of brain function can provide new insights into the functional and structural organization of the brain. (orig.)

Influences of brain development and ageing on cortical interactive networks.

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Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao

2011-02-01

To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

What Is the Optimal Treatment of Large Brain Metastases? An Argument for a Multidisciplinary Approach

International Nuclear Information System (INIS)

Choi, Clara Y.H.; Chang, Steven D.; Gibbs, Iris C.; Adler, John R.; Harsh, Griffith R.; Atalar, Banu; Lieberson, Robert E.; Soltys, Scott G.

2012-01-01

Purpose: Single-modality treatment of large brain metastases (>2 cm) with whole-brain irradiation, stereotactic radiosurgery (SRS) alone, or surgery alone is not effective, with local failure (LF) rates of 50% to 90%. Our goal was to improve local control (LC) by using multimodality therapy of surgery and adjuvant SRS targeting the resection cavity. Patients and Methods: We retrospectively evaluated 97 patients with brain metastases >2 cm in diameter treated with surgery and cavity SRS. Local and distant brain failure (DF) rates were analyzed with competing risk analysis, with death as a competing risk. The overall survival rate was calculated by the Kaplain-Meier product-limit method. Results: The median imaging follow-up duration for all patients was 10 months (range, 1–80 months). The 12-month cumulative incidence rates of LF, with death as a competing risk, were 9.3% (95% confidence interval [CI], 4.5%–16.1%), and the median time to LF was 6 months (range, 3–17 months). The 12-month cumulative incidence rate of DF, with death as a competing risk, was 53% (95% CI, 43%–63%). The median survival time for all patients was 15.6 months. The median survival times for recursive partitioning analysis classes 1, 2, and 3 were 33.8, 13.7, and 9.0 months, respectively (p = 0.022). On multivariate analysis, Karnofsky Performance Status (≥80 vs. <80; hazard ratio 0.54; 95% CI 0.31–0.94; p = 0.029) and maximum preoperative tumor diameter (hazard ratio 1.41; 95% CI 1.08–1.85; p = 0.013) were associated with survival. Five patients (5%) required intervention for Common Terminology Criteria for Adverse Events v4.02 grade 2 and 3 toxicity. Conclusion: Surgery and adjuvant resection cavity SRS yields excellent LC of large brain metastases. Compared with other multimodality treatment options, this approach allows patients to avoid or delay whole-brain irradiation without compromising LC.

Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device.

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McKinstry, Jeffrey L; Edelman, Gerald M

2013-01-01

Animal behavior often involves a temporally ordered sequence of actions learned from experience. Here we describe simulations of interconnected networks of spiking neurons that learn to generate patterns of activity in correct temporal order. The simulation consists of large-scale networks of thousands of excitatory and inhibitory neurons that exhibit short-term synaptic plasticity and spike-timing dependent synaptic plasticity. The neural architecture within each area is arranged to evoke winner-take-all (WTA) patterns of neural activity that persist for tens of milliseconds. In order to generate and switch between consecutive firing patterns in correct temporal order, a reentrant exchange of signals between these areas was necessary. To demonstrate the capacity of this arrangement, we used the simulation to train a brain-based device responding to visual input by autonomously generating temporal sequences of motor actions.

Combining task-evoked and spontaneous activity to improve pre-operative brain mapping with fMRI.

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Fox, Michael D; Qian, Tianyi; Madsen, Joseph R; Wang, Danhong; Li, Meiling; Ge, Manling; Zuo, Huan-Cong; Groppe, David M; Mehta, Ashesh D; Hong, Bo; Liu, Hesheng

2016-01-01

Noninvasive localization of brain function is used to understand and treat neurological disease, exemplified by pre-operative fMRI mapping prior to neurosurgical intervention. The principal approach for generating these maps relies on brain responses evoked by a task and, despite known limitations, has dominated clinical practice for over 20years. Recently, pre-operative fMRI mapping based on correlations in spontaneous brain activity has been demonstrated, however this approach has its own limitations and has not seen widespread clinical use. Here we show that spontaneous and task-based mapping can be performed together using the same pre-operative fMRI data, provide complimentary information relevant for functional localization, and can be combined to improve identification of eloquent motor cortex. Accuracy, sensitivity, and specificity of our approach are quantified through comparison with electrical cortical stimulation mapping in eight patients with intractable epilepsy. Broad applicability and reproducibility of our approach are demonstrated through prospective replication in an independent dataset of six patients from a different center. In both cohorts and every individual patient, we see a significant improvement in signal to noise and mapping accuracy independent of threshold, quantified using receiver operating characteristic curves. Collectively, our results suggest that modifying the processing of fMRI data to incorporate both task-based and spontaneous activity significantly improves functional localization in pre-operative patients. Because this method requires no additional scan time or modification to conventional pre-operative data acquisition protocols it could have widespread utility. Copyright © 2015. Published by Elsevier Inc.

Thermodynamic laws apply to brain function.

Science.gov (United States)

Salerian, Alen J

2010-02-01

Thermodynamic laws and complex system dynamics govern brain function. Thus, any change in brain homeostasis by an alteration in brain temperature, neurotransmission or content may cause region-specific brain dysfunction. This is the premise for the Salerian Theory of Brain built upon a new paradigm for neuropsychiatric disorders: the governing influence of neuroanatomy, neurophysiology, thermodynamic laws. The principles of region-specific brain function thermodynamics are reviewed. The clinical and supporting evidence including the paradoxical effects of various agents that alter brain homeostasis is demonstrated.

Robust generative asymmetric GMM for brain MR image segmentation.

Science.gov (United States)

Ji, Zexuan; Xia, Yong; Zheng, Yuhui

2017-11-01

Accurate segmentation of brain tissues from magnetic resonance (MR) images based on the unsupervised statistical models such as Gaussian mixture model (GMM) has been widely studied during last decades. However, most GMM based segmentation methods suffer from limited accuracy due to the influences of noise and intensity inhomogeneity in brain MR images. To further improve the accuracy for brain MR image segmentation, this paper presents a Robust Generative Asymmetric GMM (RGAGMM) for simultaneous brain MR image segmentation and intensity inhomogeneity correction. First, we develop an asymmetric distribution to fit the data shapes, and thus construct a spatial constrained asymmetric model. Then, we incorporate two pseudo-likelihood quantities and bias field estimation into the model's log-likelihood, aiming to exploit the neighboring priors of within-cluster and between-cluster and to alleviate the impact of intensity inhomogeneity, respectively. Finally, an expectation maximization algorithm is derived to iteratively maximize the approximation of the data log-likelihood function to overcome the intensity inhomogeneity in the image and segment the brain MR images simultaneously. To demonstrate the performances of the proposed algorithm, we first applied the proposed algorithm to a synthetic brain MR image to show the intermediate illustrations and the estimated distribution of the proposed algorithm. The next group of experiments is carried out in clinical 3T-weighted brain MR images which contain quite serious intensity inhomogeneity and noise. Then we quantitatively compare our algorithm to state-of-the-art segmentation approaches by using Dice coefficient (DC) on benchmark images obtained from IBSR and BrainWeb with different level of noise and intensity inhomogeneity. The comparison results on various brain MR images demonstrate the superior performances of the proposed algorithm in dealing with the noise and intensity inhomogeneity. In this paper, the RGAGMM

Remapping cortical modulation for electrocorticographic brain-computer interfaces: a somatotopy-based approach in individuals with upper-limb paralysis

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Degenhart, Alan D.; Hiremath, Shivayogi V.; Yang, Ying; Foldes, Stephen; Collinger, Jennifer L.; Boninger, Michael; Tyler-Kabara, Elizabeth C.; Wang, Wei

2018-04-01

Objective. Brain-computer interface (BCI) technology aims to provide individuals with paralysis a means to restore function. Electrocorticography (ECoG) uses disc electrodes placed on either the surface of the dura or the cortex to record field potential activity. ECoG has been proposed as a viable neural recording modality for BCI systems, potentially providing stable, long-term recordings of cortical activity with high spatial and temporal resolution. Previously we have demonstrated that a subject with spinal cord injury (SCI) could control an ECoG-based BCI system with up to three degrees of freedom (Wang et al 2013 PLoS One). Here, we expand upon these findings by including brain-control results from two additional subjects with upper-limb paralysis due to amyotrophic lateral sclerosis and brachial plexus injury, and investigate the potential of motor and somatosensory cortical areas to enable BCI control. Approach. Individuals were implanted with high-density ECoG electrode grids over sensorimotor cortical areas for less than 30 d. Subjects were trained to control a BCI by employing a somatotopic control strategy where high-gamma activity from attempted arm and hand movements drove the velocity of a cursor. Main results. Participants were capable of generating robust cortical modulation that was differentiable across attempted arm and hand movements of their paralyzed limb. Furthermore, all subjects were capable of voluntarily modulating this activity to control movement of a computer cursor with up to three degrees of freedom using the somatotopic control strategy. Additionally, for those subjects with electrode coverage of somatosensory cortex, we found that somatosensory cortex was capable of supporting ECoG-based BCI control. Significance. These results demonstrate the feasibility of ECoG-based BCI systems for individuals with paralysis as well as highlight some of the key challenges that must be overcome before such systems are translated to the clinical

Imaging brain plasticity after trauma

Institute of Scientific and Technical Information of China (English)

Zhifeng Kou; Armin Iraji

2014-01-01

The brain is highly plastic after stroke or epilepsy;however, there is a paucity of brain plasticity investigation after traumatic brain injury (TBI). This mini review summarizes the most recent evidence of brain plasticity in human TBI patients from the perspective of advanced magnetic resonance imaging. Similar to other forms of acquired brain injury, TBI patients also demonstrat-ed both structural reorganization as well as functional compensation by the recruitment of other brain regions. However, the large scale brain network alterations after TBI are still unknown, and the ifeld is still short of proper means on how to guide the choice of TBI rehabilitation or treat-ment plan to promote brain plasticity. The authors also point out the new direction of brain plas-ticity investigation.

Real-time fMRI using brain-state classification.

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LaConte, Stephen M; Peltier, Scott J; Hu, Xiaoping P

2007-10-01

We have implemented a real-time functional magnetic resonance imaging system based on multivariate classification. This approach is distinctly different from spatially localized real-time implementations, since it does not require prior assumptions about functional localization and individual performance strategies, and has the ability to provide feedback based on intuitive translations of brain state rather than localized fluctuations. Thus this approach provides the capability for a new class of experimental designs in which real-time feedback control of the stimulus is possible-rather than using a fixed paradigm, experiments can adaptively evolve as subjects receive brain-state feedback. In this report, we describe our implementation and characterize its performance capabilities. We observed approximately 80% classification accuracy using whole brain, block-design, motor data. Within both left and right motor task conditions, important differences exist between the initial transient period produced by task switching (changing between rapid left or right index finger button presses) and the subsequent stable period during sustained activity. Further analysis revealed that very high accuracy is achievable during stable task periods, and that the responsiveness of the classifier to changes in task condition can be much faster than signal time-to-peak rates. Finally, we demonstrate the versatility of this implementation with respect to behavioral task, suggesting that our results are applicable across a spectrum of cognitive domains. Beyond basic research, this technology can complement electroencephalography-based brain computer interface research, and has potential applications in the areas of biofeedback rehabilitation, lie detection, learning studies, virtual reality-based training, and enhanced conscious awareness. Wiley-Liss, Inc.

Global Proteomic Analysis of Brain Tissues in Transient Ischemia Brain Damage in Rats

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Jiann-Hwa Chen

2015-05-01

Full Text Available Ischemia-reperfusion injury resulting from arterial occlusion or hypotension in patients leads to tissue hypoxia with glucose deprivation, which causes endoplasmic reticulum (ER stress and neuronal death. A proteomic approach was used to identify the differentially expressed proteins in the brain of rats following a global ischemic stroke. The mechanisms involved the action in apoptotic and ER stress pathways. Rats were treated with ischemia-reperfusion brain injuries by the bilateral occlusion of the common carotid artery. The cortical neuron proteins from the stroke animal model (SAM and the control rats were separated using two-dimensional gel electrophoresis (2-DE to purify and identify the protein profiles. Our results demonstrated that the SAM rats experienced brain cell death in the ischemic core. Fifteen proteins were expressed differentially between the SAM rats and control rats, which were assayed and validated in vivo and in vitro. Interestingly, the set of differentially expressed, down-regulated proteins included catechol O-methyltransferase (COMT and cathepsin D (CATD, which are implicated in oxidative stress, inflammatory response and apoptosis. After an ischemic stroke, one protein spot, namely the calretinin (CALB2 protein, showed increased expression. It mediated the effects of SAM administration on the apoptotic and ER stress pathways. Our results demonstrate that the ischemic injury of neuronal cells increased cell cytoxicity and apoptosis, which were accompanied by sustained activation of the IRE1-alpha/TRAF2, JNK1/2, and p38 MAPK pathways. Proteomic analysis suggested that the differential expression of CALB2 during a global ischemic stroke could be involved in the mechanisms of ER stress-induced neuronal cell apoptosis, which occurred via IRE1-alpha/TRAF2 complex formation, with activation of JNK1/2 and p38 MAPK. Based on these results, we also provide the molecular evidence supporting the ischemia

Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving.

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Garcia, Javier O; Brooks, Justin; Kerick, Scott; Johnson, Tony; Mullen, Tim R; Vettel, Jean M

2017-04-15

Conventional neuroimaging analyses have ascribed function to particular brain regions, exploiting the power of the subtraction technique in fMRI and event-related potential analyses in EEG. Moving beyond this convention, many researchers have begun exploring network-based neurodynamics and coordination between brain regions as a function of behavioral parameters or environmental statistics; however, most approaches average evoked activity across the experimental session to study task-dependent networks. Here, we examined on-going oscillatory activity as measured with EEG and use a methodology to estimate directionality in brain-behavior interactions. After source reconstruction, activity within specific frequency bands (delta: 2-3Hz; theta: 4-7Hz; alpha: 8-12Hz; beta: 13-25Hz) in a priori regions of interest was linked to continuous behavioral measurements, and we used a predictive filtering scheme to estimate the asymmetry between brain-to-behavior and behavior-to-brain prediction using a variant of Granger causality. We applied this approach to a simulated driving task and examined directed relationships between brain activity and continuous driving performance (steering behavior or vehicle heading error). Our results indicated that two neuro-behavioral states may be explored with this methodology: a Proactive brain state that actively plans the response to the sensory information and is characterized by delta-beta activity, and a Reactive brain state that processes incoming information and reacts to environmental statistics primarily within the alpha band. Published by Elsevier Inc.

Crossed cerebellar diaschisis demonstrated by SPECT in hemiplegic children

International Nuclear Information System (INIS)

Hamano, Shin-ichiro; Nara, Takahiro; Nozaki, Hidetsugu; Fukushima, Kiyomi; Imai, Masayuki; Kumagai, Koumei; Maekawa, Kihei.

1991-01-01

Crossed cerebellar diaschisis (CCD) in twenty five children with hemiplegia were studied using single photon emission computed tomography (SPECT) with N-isopropyl-p-I-123-iodoamphetamine. Seven of twenty-five patients had cerebral palsy, and the others were impaired by acquired brain injury between ten months and fourteen years of age. CCD was demonstrated in five patients (20%), who were impaired by acquired brain injury after seven years of age. CCD could never be detected in patients with cerebral palsy. Ipsilateral cerebellar diaschisis was also demonstrated in two patients with cerebral palsy and three with early acquired brain injury before three years of age. It is suggested that diaschisis presents itself as a different form in a contralateral and ipsilateral cerebellum before three years of age from a form which presents after seven years of age. (author)

Patterns recognition of electric brain activity using artificial neural networks

Science.gov (United States)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

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

Science.gov (United States)

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.

Similarities and differences in neuroplasticity mechanisms between brain gliomas and nonlesional epilepsy.

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Bourdillon, Pierre; Apra, Caroline; Guénot, Marc; Duffau, Hugues

2017-12-01

To analyze the conceptual and practical implications of a hodotopic approach in neurosurgery, and to compare the similarities and the differences in neuroplasticity mechanisms between low-grade gliomas and nonlesional epilepsy. We review the recent data about the hodotopic organization of the brain connectome, alongside the organization of epileptic networks, and analyze how these two structures interact, suggesting therapeutic prospects. Then we focus on the mechanisms of neuroplasticity involved in glioma natural course and after glioma surgery. Comparing these mechanisms with those in action in an epileptic brain highlights their differences, but more importantly, gives an original perspective to the consequences of surgery on an epileptic brain and what could be expected after pathologic white matter removal. The organization of the brain connectome and the neuroplasticity is the same in all humans, but different pathologic mechanisms are involved, and specific therapeutic approaches have been developed in epilepsy and glioma surgery. We demonstrate that the "connectome" point of view can enrich epilepsy care. We also underscore how theoretical and practical tools commonly used in epilepsy investigations, such as invasive electroencephalography, can be of great help in awake surgery in general. Putting together advances in understanding of connectomics and neuroplasticity, leads to significant conceptual improvements in epilepsy surgery. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Contextualizing aquired brain damage

DEFF Research Database (Denmark)

Nielsen, Charlotte Marie Bisgaard

2014-01-01

Contextualizing aquired brain damage Traditional approaches study ’communicational problems’ often in a discourse of disabledness or deficitness. With an ontology of communcation as something unique and a presupposed uniqueness of each one of us, how could an integrational approach (Integrational...... for people with aquired brain injuries will be presented and comparatively discussed in a traditional versus an integrational perspective. Preliminary results and considerations on ”methods” and ”participation” from this study will be presented along with an overview of the project's empirical data....

Air pollution and detrimental effects on children's brain. The need for a multidisciplinary approach to the issue complexity and challenges.

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Calderón-Garcidueñas, Lilian; Torres-Jardón, Ricardo; Kulesza, Randy J; Park, Su-Bin; D'Angiulli, Amedeo

2014-01-01

Millions of children in polluted cities are showing brain detrimental effects. Urban children exhibit brain structural and volumetric abnormalities, systemic inflammation, olfactory, auditory, vestibular and cognitive deficits v low-pollution controls. Neuroinflammation and blood-brain-barrier (BBB) breakdown target the olfactory bulb, prefrontal cortex and brainstem, but are diffusely present throughout the brain. Urban adolescent Apolipoprotein E4 carriers significantly accelerate Alzheimer pathology. Neurocognitive effects of air pollution are substantial, apparent across all populations, and potentially clinically relevant as early evidence of evolving neurodegenerative changes. The diffuse nature of the neuroinflammation and neurodegeneration forces to employ a weight of evidence approach incorporating current clinical, cognitive, neurophysiological, radiological and epidemiological research. Pediatric air pollution research requires extensive multidisciplinary collaborations to accomplish a critical goal: to protect exposed children through multidimensional interventions having both broad impact and reach. Protecting children and teens from neural effects of air pollution should be of pressing importance for public health.

Quantitative mouse brain phenotyping based on single and multispectral MR protocols

Science.gov (United States)

Badea, Alexandra; Gewalt, Sally; Avants, Brian B.; Cook, James J.; Johnson, G. Allan

2013-01-01

Sophisticated image analysis methods have been developed for the human brain, but such tools still need to be adapted and optimized for quantitative small animal imaging. We propose a framework for quantitative anatomical phenotyping in mouse models of neurological and psychiatric conditions. The framework encompasses an atlas space, image acquisition protocols, and software tools to register images into this space. We show that a suite of segmentation tools (Avants, Epstein et al., 2008) designed for human neuroimaging can be incorporated into a pipeline for segmenting mouse brain images acquired with multispectral magnetic resonance imaging (MR) protocols. We present a flexible approach for segmenting such hyperimages, optimizing registration, and identifying optimal combinations of image channels for particular structures. Brain imaging with T1, T2* and T2 contrasts yielded accuracy in the range of 83% for hippocampus and caudate putamen (Hc and CPu), but only 54% in white matter tracts, and 44% for the ventricles. The addition of diffusion tensor parameter images improved accuracy for large gray matter structures (by >5%), white matter (10%), and ventricles (15%). The use of Markov random field segmentation further improved overall accuracy in the C57BL/6 strain by 6%; so Dice coefficients for Hc and CPu reached 93%, for white matter 79%, for ventricles 68%, and for substantia nigra 80%. We demonstrate the segmentation pipeline for the widely used C57BL/6 strain, and two test strains (BXD29, APP/TTA). This approach appears promising for characterizing temporal changes in mouse models of human neurological and psychiatric conditions, and may provide anatomical constraints for other preclinical imaging, e.g. fMRI and molecular imaging. This is the first demonstration that multiple MR imaging modalities combined with multivariate segmentation methods lead to significant improvements in anatomical segmentation in the mouse brain. PMID:22836174

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

Science.gov (United States)

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.

Proteomic approaches in brain research and neuropharmacology.

Science.gov (United States)

Vercauteren, Freya G G; Bergeron, John J M; Vandesande, Frans; Arckens, Lut; Quirion, Rémi

2004-10-01

Numerous applications of genomic technologies have enabled the assembly of unprecedented inventories of genes, expressed in cells under specific physiological and pathophysiological conditions. Complementing the valuable information generated through functional genomics with the integrative knowledge of protein expression and function should enable the development of more efficient diagnostic tools and therapeutic agents. Proteomic analyses are particularly suitable to elucidate posttranslational modifications, expression levels and protein-protein interactions of thousands of proteins at a time. In this review, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) investigations of brain tissues in neurodegenerative diseases such as Alzheimer's disease, Down syndrome and schizophrenia, and the construction of 2D-PAGE proteome maps of the brain are discussed. The role of the Human Proteome Organization (HUPO) as an international coordinating organization for proteomic efforts, as well as challenges for proteomic technologies and data analysis are also addressed. It is expected that the use of proteomic strategies will have significant impact in neuropharmacology over the coming decade.

Driving and driven architectures of directed small-world human brain functional networks.

Directory of Open Access Journals (Sweden)

Chaogan Yan

Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

Pseudotyped Lentiviral Vectors for Retrograde Gene Delivery into Target Brain Regions

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Kenta Kobayashi

2017-08-01

Full Text Available Gene transfer through retrograde axonal transport of viral vectors offers a substantial advantage for analyzing roles of specific neuronal pathways or cell types forming complex neural networks. This genetic approach may also be useful in gene therapy trials by enabling delivery of transgenes into a target brain region distant from the injection site of the vectors. Pseudotyping of a lentiviral vector based on human immunodeficiency virus type 1 (HIV-1 with various fusion envelope glycoproteins composed of different combinations of rabies virus glycoprotein (RV-G and vesicular stomatitis virus glycoprotein (VSV-G enhances the efficiency of retrograde gene transfer in both rodent and nonhuman primate brains. The most recently developed lentiviral vector is a pseudotype with fusion glycoprotein type E (FuG-E, which demonstrates highly efficient retrograde gene transfer in the brain. The FuG-E–pseudotyped vector permits powerful experimental strategies for more precisely investigating the mechanisms underlying various brain functions. It also contributes to the development of new gene therapy approaches for neurodegenerative disorders, such as Parkinson’s disease, by delivering genes required for survival and protection into specific neuronal populations. In this review article, we report the properties of the FuG-E–pseudotyped vector, and we describe the application of the vector to neural circuit analysis and the potential use of the FuG-E vector in gene therapy for Parkinson’s disease.

Approach and withdrawal motivation in schizophrenia: an examination of frontal brain asymmetric activity.

Science.gov (United States)

Horan, William P; Wynn, Jonathan K; Mathis, Ian; Miller, Gregory A; Green, Michael F

2014-01-01

Although motivational disturbances are common in schizophrenia, their neurophysiological and psychological basis is poorly understood. This electroencephalography (EEG) study examined the well-established motivational direction model of asymmetric frontal brain activity in schizophrenia. According to this model, relative left frontal activity in the resting EEG reflects enhanced approach motivation tendencies, whereas relative right frontal activity reflects enhanced withdrawal motivation tendencies. Twenty-five schizophrenia outpatients and 25 healthy controls completed resting EEG assessments of frontal asymmetry in the alpha frequency band (8-12 Hz), as well as a self-report measure of behavioral activation and inhibition system (BIS/BAS) sensitivity. Patients showed an atypical pattern of differences from controls. On the EEG measure patients failed to show the left lateralized activity that was present in controls, suggesting diminished approach motivation. On the self-report measure, patients reported higher BIS sensitivity than controls, which is typically interpreted as heightened withdrawal motivation. EEG asymmetry scores did not significantly correlate with BIS/BAS scores or with clinical symptom ratings among patients. The overall pattern suggests a motivational disturbance in schizophrenia characterized by elements of both diminished approach and elevated withdrawal tendencies.

Development of antibodies against the rat brain somatostatin receptor.

Science.gov (United States)

Theveniau, M; Rens-Domiano, S; Law, S F; Rougon, G; Reisine, T

1992-05-15

Somatostatin (SRIF) is a neurotransmitter in the brain involved in the regulation of motor activity and cognition. It induces its physiological actions by interacting with receptors. We have developed antibodies against the receptor to investigate its structural properties. Rabbit polyclonal antibodies were generated against the rat brain SRIF receptor. These antibodies (F4) were able to immunoprecipitate solubilized SRIF receptors from rat brain and the cell line AtT-20. The specificity of the interaction of these antibodies with SRIF receptors was further demonstrated by immunoblotting. F4 detected SRIF receptors of 60 kDa from rat brain and adrenal cortex and the cell lines AtT-20, GH3, and NG-108, which express high densities of SRIF receptors. They did not detect immunoreactive material from rat liver or COS-1, HEPG, or CRL cells, which do not express functional SRIF receptors. In rat brain, 60-kDa immunoreactivity was detected by F4 in the hippocampus, cerebral cortex, and striatum, which have high densities of SRIF receptors. However, F4 did not interact with proteins from cerebellum and brain stem, which express few SRIF receptors. Immunoreactive material cannot be detected in rat pancreas or pituitary, which have been reported to express a 90-kDa SRIF receptor subtype. The selective detection of 60-kDa SRIF receptors by F4 indicates that the 60- and 90-kDa SRIF receptor subtypes are immunologically distinct. The availability of antibodies that selectively detect native and denatured brain SRIF receptors provides us with a feasible approach to clone the brain SRIF receptor gene(s).

Brain Evolution and Human Neuropsychology: The Inferential Brain Hypothesis

Science.gov (United States)

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

Human brain imaging

International Nuclear Information System (INIS)

Kuhar, M.J.

1987-01-01

Just as there have been dramatic advances in the molecular biology of the human brain in recent years, there also have been remarkable advances in brain imaging. This paper reports on the development and broad application of microscopic imaging techniques which include the autoradiographic localization of receptors and the measurement of glucose utilization by autoradiography. These approaches provide great sensitivity and excellent anatomical resolution in exploring brain organization and function. The first noninvasive external imaging of receptor distributions in the living human brain was achieved by positron emission tomography (PET) scanning. Developments, techniques and applications continue to progress. Magnetic resonance imaging (MRI) is also becoming important. Its initial clinical applications were in examining the structure and anatomy of the brain. However, more recent uses, such as MRI spectroscopy, indicate the feasibility of exploring biochemical pathways in the brain, the metabolism of drugs in the brain, and also of examining some of these procedures at an anatomical resolution which is substantially greater than that obtainable by PET scanning. The issues will be discussed in greater detail

Endothelial progenitor cells physiology and metabolic plasticity in brain angiogenesis and blood-brain barrier modeling

Directory of Open Access Journals (Sweden)

Natalia Malinovskaya

2016-12-01

Full Text Available Currently, there is a considerable interest to the assessment of blood-brain barrier (BBB development as a part of cerebral angiogenesis developmental program. Embryonic and adult angiogenesis in the brain is governed by the coordinated activity of endothelial progenitor cells, brain microvascular endothelial cells, and non-endothelial cells contributing to the establishment of the BBB (pericytes, astrocytes, neurons. Metabolic and functional plasticity of endothelial progenitor cells controls their timely recruitment, precise homing to the brain microvessels, and efficient support of brain angiogenesis. Deciphering endothelial progenitor cells physiology would provide novel engineering approaches to establish adequate microfluidically-supported BBB models and brain microphysiological systems for translational studies.

Imaging Brain Development: Benefiting from Individual Variability

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Megha Sharda

2015-01-01

Full Text Available Human brain development is a complex process that evolves from early childhood to young adulthood. Major advances in brain imaging are increasingly being used to characterize the developing brain. These advances have further helped to elucidate the dynamic maturational processes that lead to the emergence of complex cognitive abilities in both typical and atypical development. However, conventional approaches involve categorical group comparison models and tend to disregard the role of widespread interindividual variability in brain development. This review highlights how this variability can inform our understanding of developmental processes. The latest studies in the field of brain development are reviewed, with a particular focus on the role of individual variability and the consequent heterogeneity in brain structural and functional development. This review also highlights how such heterogeneity might be utilized to inform our understanding of complex neuropsychiatric disorders and recommends the use of more dimensional approaches to study brain development.

Targeting the Brain with Nanomedicine.

Science.gov (United States)

Rueda, Felix; Cruz, Luis J

2017-01-01

Herein, we review innovative nanomedicine-based approaches for treating, preventing and diagnosing neurodegenerative diseases. We focus on nanoscale systems such as polymeric nanoparticles (NPs), liposomes, micelles and other vehicles (e.g. dendrimers, nanogels, nanoemulsions and nanosuspensions) for targeted delivery of bioactive molecules to the brain. To ensure maximum selectivity for optimal therapeutic or diagnostic results, researchers must employ delivery systems that are non-toxic, biodegradable and biocompatible. This entails: (i) use of "safe" materials, such as polymers or lipids; (ii) targeting to the brain and, specifically, to the desired active site within the brain; (iii) controlled release of the loaded agent; and (iv) use of agents that, once released into the brain, will exhibit the desired pharmacologic activity. Here, we explore the design and preclinical use of representative delivery systems that have been proposed to date. We then analyze the principal challenges that have delayed clinical application of these and other approaches. Lastly, we look at future developments in this area, addressing the needs for increased penetration of the blood brain barrier (BBB), enhanced targeting of specific brain sites, improved therapeutic efficacy and lower neurotoxicity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction

International Nuclear Information System (INIS)

Wels, Michael; Hornegger, Joachim; Zheng Yefeng; Comaniciu, Dorin; Huber, Martin

2011-01-01

We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average

A comprehensive survey of brain interface technology designs.

Science.gov (United States)

Mason, S G; Bashashati, A; Fatourechi, M; Navarro, K F; Birch, G E

2007-02-01

In this work we present the first comprehensive survey of Brain Interface (BI) technology designs published prior to January 2006. Detailed results from this survey, which was based on the Brain Interface Design Framework proposed by Mason and Birch, are presented and discussed to address the following research questions: (1) which BI technologies are directly comparable, (2) what technology designs exist, (3) which application areas (users, activities and environments) have been targeted in these designs, (4) which design approaches have received little or no research and are possible opportunities for new technology, and (5) how well are designs reported. The results of this work demonstrate that meta-analysis of high-level BI design attributes is possible and informative. The survey also produced a valuable, historical cross-reference where BI technology designers can identify what types of technology have been proposed and by whom.

Using brain-computer interfaces and brain-state dependent stimulation as tools in cognitive neuroscience

Directory of Open Access Journals (Sweden)

Ole eJensen

2011-05-01

Full Text Available Large efforts are currently being made to develop and improve online analysis of brain activity which can be used e.g. for brain-computer interfacing (BCI. A BCI allows a subject to control a device by willfully changing his/her own brain activity. BCI therefore holds the promise as a tool for aiding the disabled and for augmenting human performance. While technical developments obviously are important, we will here argue that new insight gained from cognitive neuroscience can be used to identify signatures of neural activation which reliably can be modulated by the subject at will. This review will focus mainly on oscillatory activity in the alpha band which is strongly modulated by changes in covert attention. Besides developing BCIs for their traditional purpose, they might also be used as a research tool for cognitive neuroscience. There is currently a strong interest in how brain state fluctuations impact cognition. These state fluctuations are partly reflected by ongoing oscillatory activity. The functional role of the brain state can be investigated by introducing stimuli in real time to subjects depending on the actual state of the brain. This principle of brain-state dependent stimulation may also be used as a practical tool for augmenting human behavior. In conclusion, new approaches based on online analysis of ongoing brain activity are currently in rapid development. These approaches are amongst others informed by new insight gained from EEG/MEG studies in cognitive neuroscience and hold the promise of providing new ways for investigating the brain at work.

Delayed radiation necrosis of the brain simulating a brain tumor

International Nuclear Information System (INIS)

Ikeda, Hiroya; Kanai, Nobuhiro; Kamikawa, Kiyoo

1976-01-01

Two cases of delayed radiation necrosis of the brain are reported. Case 1 was a 50-year-old man who had right hemiparesis and disorientation 26 months after Linac irradiation (5,000 rad), preceded by an operation for right maxillar carcinoma. A left carotid angiogram demonstrated a left temporal mass lesion, extending to the frontal lobe. Case 2 was a 41-year-old man who had previously had an operation for right intraorbital plasmocytoma, followed by two Co irradiations (6,400 rad, and 5,000 rad). He had the signs and symptoms of intracranial hypertension 36 months after his last irradiation. A left carotid angiogram demonstrated a left temporal mass lesion. Both cases were treated by administration of steroid hormone (which alleviated the signs and symptoms) and by temporal lobectomy. Microscopic examinations showed necrosis of the brain tissues associated with hyaline degeneration of blood vessel walls and perivascular cell infiltration. The signs and symptoms of intracranial hypertension subsided postoperatively. Thirteen other cases the same as ours were collected from literature. They showed the signs and symptoms simulating a brain tumor (like a metastatic brain tumor) after irradiation to extracranial malignant tumors. Diagnosis of radiation necrosis was made by operation or autopsy. A follow-up for a long time is necessary, because the pathological changes in the brain may be progressive and extending in some cases, although decompressive operations for mass lesions give excellent results. (auth.)

Robot Learning from Demonstration: A Task-level Planning Approach

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Staffan Ekvall

2008-09-01

Full Text Available In this paper, we deal with the problem of learning by demonstration, task level learning and planning for robotic applications that involve object manipulation. Preprogramming robots for execution of complex domestic tasks such as setting a dinner table is of little use, since the same order of subtasks may not be conceivable in the run time due to the changed state of the world. In our approach, we aim to learn the goal of the task and use a task planner to reach the goal given different initial states of the world. For some tasks, there are underlying constraints that must be fulfille, and knowing just the final goal is not sufficient. We propose two techniques for constraint identification. In the first case, the teacher can directly instruct the system about the underlying constraints. In the second case, the constraints are identified by the robot itself based on multiple observations. The constraints are then considered in the planning phase, allowing the task to be executed without violating any of them. We evaluate our work on a real robot performing pick-and-place tasks.

A novel approach to delayed-start analyses for demonstrating disease-modifying effects in Alzheimer's disease.

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Hong Liu-Seifert

Full Text Available One method for demonstrating disease modification is a delayed-start design, consisting of a placebo-controlled period followed by a delayed-start period wherein all patients receive active treatment. To address methodological issues in previous delayed-start approaches, we propose a new method that is robust across conditions of drug effect, discontinuation rates, and missing data mechanisms. We propose a modeling approach and test procedure to test the hypothesis of noninferiority, comparing the treatment difference at the end of the delayed-start period with that at the end of the placebo-controlled period. We conducted simulations to identify the optimal noninferiority testing procedure to ensure the method was robust across scenarios and assumptions, and to evaluate the appropriate modeling approach for analyzing the delayed-start period. We then applied this methodology to Phase 3 solanezumab clinical trial data for mild Alzheimer's disease patients. Simulation results showed a testing procedure using a proportional noninferiority margin was robust for detecting disease-modifying effects; conditions of high and moderate discontinuations; and with various missing data mechanisms. Using all data from all randomized patients in a single model over both the placebo-controlled and delayed-start study periods demonstrated good statistical performance. In analysis of solanezumab data using this methodology, the noninferiority criterion was met, indicating the treatment difference at the end of the placebo-controlled studies was preserved at the end of the delayed-start period within a pre-defined margin. The proposed noninferiority method for delayed-start analysis controls Type I error rate well and addresses many challenges posed by previous approaches. Delayed-start studies employing the proposed analysis approach could be used to provide evidence of a disease-modifying effect. This method has been communicated with FDA and has been

A Life-Long Approach to Physical Activity for Brain Health

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Helen Macpherson

2017-05-01

Full Text Available It is well established that engaging in lifelong Physical activity (PA can help delay the onset of many chronic lifestyle related and non-communicable diseases such as cardiovascular disease, type two diabetes, cancer and chronic respiratory diseases. Additionally, growing evidence also documents the importance of PA for brain health, with numerous studies indicating regular engagement in physical activities may be protective against cognitive decline and dementia in late life. Indeed, the link between PA and brain health may be different at each stage of life from childhood, mid-life and late life. Building on this emerging body of multidisciplinary research, this review aims to summarize the current body of evidence linking regular PA and brain health across the lifespan. Specifically, we will focus on the relationship between PA and brain health at three distinct stages of life: childhood and adolescence, mid-life, late life in cognitively healthy adults and later life in adults living with age-related neurodegenerative disorders such as Parkinson’s disease (PD and Alzheimer’s disease (AD.

Permeabilization of the blood-brain barrier via mucosal engrafting: implications for drug delivery to the brain.

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Bleier, Benjamin S; Kohman, Richie E; Feldman, Rachel E; Ramanlal, Shreshtha; Han, Xue

2013-01-01

Utilization of neuropharmaceuticals for central nervous system(CNS) disease is highly limited due to the blood-brain barrier(BBB) which restricts molecules larger than 500Da from reaching the CNS. The development of a reliable method to bypass the BBB would represent an enormous advance in neuropharmacology enabling the use of many potential disease modifying therapies. Previous attempts such as transcranial catheter implantation have proven to be temporary and associated with multiple complications. Here we describe a novel method of creating a semipermeable window in the BBB using purely autologous tissues to allow for high molecular weight(HMW) drug delivery to the CNS. This approach is inspired by recent advances in human endoscopic transnasal skull base surgical techniques and involves engrafting semipermeable nasal mucosa within a surgical defect in the BBB. The mucosal graft thereby creates a permanent transmucosal conduit for drugs to access the CNS. The main objective of this study was to develop a murine model of this technique and use it to evaluate transmucosal permeability for the purpose of direct drug delivery to the brain. Using this model we demonstrate that mucosal grafts allow for the transport of molecules up to 500 kDa directly to the brain in both a time and molecular weight dependent fashion. Markers up to 40 kDa were found within the striatum suggesting a potential role for this technique in the treatment of Parkinson's disease. This proof of principle study demonstrates that mucosal engrafting represents the first permanent and stable method of bypassing the BBB thereby providing a pathway for HMW therapeutics directly into the CNS.

A development architecture for serious games using BCI (brain computer interface) sensors.

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Sung, Yunsick; Cho, Kyungeun; Um, Kyhyun

2012-11-12

Games that use brainwaves via brain-computer interface (BCI) devices, to improve brain functions are known as BCI serious games. Due to the difficulty of developing BCI serious games, various BCI engines and authoring tools are required, and these reduce the development time and cost. However, it is desirable to reduce the amount of technical knowledge of brain functions and BCI devices needed by game developers. Moreover, a systematic BCI serious game development process is required. In this paper, we present a methodology for the development of BCI serious games. We describe an architecture, authoring tools, and development process of the proposed methodology, and apply it to a game development approach for patients with mild cognitive impairment as an example. This application demonstrates that BCI serious games can be developed on the basis of expert-verified theories.

Rough Sets and Stomped Normal Distribution for Simultaneous Segmentation and Bias Field Correction in Brain MR Images.

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Banerjee, Abhirup; Maji, Pradipta

2015-12-01

The segmentation of brain MR images into different tissue classes is an important task for automatic image analysis technique, particularly due to the presence of intensity inhomogeneity artifact in MR images. In this regard, this paper presents a novel approach for simultaneous segmentation and bias field correction in brain MR images. It integrates judiciously the concept of rough sets and the merit of a novel probability distribution, called stomped normal (SN) distribution. The intensity distribution of a tissue class is represented by SN distribution, where each tissue class consists of a crisp lower approximation and a probabilistic boundary region. The intensity distribution of brain MR image is modeled as a mixture of finite number of SN distributions and one uniform distribution. The proposed method incorporates both the expectation-maximization and hidden Markov random field frameworks to provide an accurate and robust segmentation. The performance of the proposed approach, along with a comparison with related methods, is demonstrated on a set of synthetic and real brain MR images for different bias fields and noise levels.

Educational professionals' understanding of childhood traumatic brain injury.

Science.gov (United States)

Linden, Mark A; Braiden, Hannah-Jane; Miller, Sarah

2013-01-01

To determine the understanding of educational professionals around the topic of childhood brain injury and explore the factor structure of the Common Misconceptions about Traumatic Brain Injury Questionnaire (CM-TBI). Cross-sectional postal survey. The CM-TBI was posted to all educational establishments in one region of the UK. One representative from each school was asked to complete and return the questionnaire (n = 388). Differences were demonstrated between those participants who knew someone with a brain injury and those who did not, with a similar pattern being shown for those educators who had taught a child with brain injury. Participants who had taught a child with brain injury demonstrated greater knowledge in areas such as seatbelts/prevention, brain damage, brain injury sequelae, amnesia, recovery and rehabilitation. Principal components analysis suggested the existence of four factors and the discarding of half the original items of the questionnaire. In the first European study to explore this issue, it is highlighted that teachers are ill-prepared to cope with children who have sustained a brain injury. Given the importance of a supportive school environment in return to life following hospitalization, the lack of understanding demonstrated by teachers in this research may significantly impact on a successful return to school.

Nutrition for the ageing brain: Towards evidence for an optimal diet.

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Vauzour, David; Camprubi-Robles, Maria; Miquel-Kergoat, Sophie; Andres-Lacueva, Cristina; Bánáti, Diána; Barberger-Gateau, Pascale; Bowman, Gene L; Caberlotto, Laura; Clarke, Robert; Hogervorst, Eef; Kiliaan, Amanda J; Lucca, Ugo; Manach, Claudine; Minihane, Anne-Marie; Mitchell, Ellen Siobhan; Perneczky, Robert; Perry, Hugh; Roussel, Anne-Marie; Schuermans, Jeroen; Sijben, John; Spencer, Jeremy P E; Thuret, Sandrine; van de Rest, Ondine; Vandewoude, Maurits; Wesnes, Keith; Williams, Robert J; Williams, Robin S B; Ramirez, Maria

2017-05-01

As people age they become increasingly susceptible to chronic and extremely debilitating brain diseases. The precise cause of the neuronal degeneration underlying these disorders, and indeed normal brain ageing remains however elusive. Considering the limits of existing preventive methods, there is a desire to develop effective and safe strategies. Growing preclinical and clinical research in healthy individuals or at the early stage of cognitive decline has demonstrated the beneficial impact of nutrition on cognitive functions. The present review is the most recent in a series produced by the Nutrition and Mental Performance Task Force under the auspice of the International Life Sciences Institute Europe (ILSI Europe). The latest scientific advances specific to how dietary nutrients and non-nutrient may affect cognitive ageing are presented. Furthermore, several key points related to mechanisms contributing to brain ageing, pathological conditions affecting brain function, and brain biomarkers are also discussed. Overall, findings are inconsistent and fragmented and more research is warranted to determine the underlying mechanisms and to establish dose-response relationships for optimal brain maintenance in different population subgroups. Such approaches are likely to provide the necessary evidence to develop research portfolios that will inform about new dietary recommendations on how to prevent cognitive decline. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Topological organization of the human brain functional connectome across the lifespan

Directory of Open Access Journals (Sweden)

Miao Cao

2014-01-01

Full Text Available Human brain function undergoes complex transformations across the lifespan. We employed resting-state functional MRI and graph-theory approaches to systematically chart the lifespan trajectory of the topological organization of human whole-brain functional networks in 126 healthy individuals ranging in age from 7 to 85 years. Brain networks were constructed by computing Pearson's correlations in blood-oxygenation-level-dependent temporal fluctuations among 1024 parcellation units followed by graph-based network analyses. We observed that the human brain functional connectome exhibited highly preserved non-random modular and rich club organization over the entire age range studied. Further quantitative analyses revealed linear decreases in modularity and inverted-U shaped trajectories of local efficiency and rich club architecture. Regionally heterogeneous age effects were mainly located in several hubs (e.g., default network, dorsal attention regions. Finally, we observed inverse trajectories of long- and short-distance functional connections, indicating that the reorganization of connectivity concentrates and distributes the brain's functional networks. Our results demonstrate topological changes in the whole-brain functional connectome across nearly the entire human lifespan, providing insights into the neural substrates underlying individual variations in behavior and cognition. These results have important implications for disease connectomics because they provide a baseline for evaluating network impairments in age-related neuropsychiatric disorders.

In vivo mapping of brain myo-inositol.

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Haris, Mohammad; Cai, Kejia; Singh, Anup; Hariharan, Hari; Reddy, Ravinder

2011-02-01

Myo-Inositol (MI) is one of the most abundant metabolites in the human brain located mainly in glial cells and functions as an osmolyte. The concentration of MI is altered in many brain disorders including Alzheimer's disease and brain tumors. Currently available magnetic resonance spectroscopy (MRS) methods for measuring MI are limited to low spatial resolution. Here, we demonstrate that the hydroxyl protons on MI exhibit chemical exchange with bulk water and saturation of these protons leads to reduction in bulk water signal through a mechanism known as chemical exchange saturation transfer (CEST). The hydroxyl proton exchange rate (k=600 s(-1)) is determined to be in the slow to intermediate exchange regime on the NMR time scale (chemical shift (∆ω)>k), suggesting that the CEST effect of MI (MICEST) can be imaged at high fields such as 7 T (∆ω=1.2×10(3)rad/s) and 9.4 T (∆ω=1.6×10(3) rad/s). Using optimized imaging parameters, concentration dependent broad CEST asymmetry between ~0.2 and 1.5 ppm with a peak at ~0.6 ppm from bulk water was observed. Further, it is demonstrated that MICEST detection is feasible in the human brain at ultra high fields (7 T) without exceeding the allowed limits on radiofrequency specific absorption rate. Results from healthy human volunteers (N=5) showed significantly higher (p=0.03) MICEST effect from white matter (5.2±0.5%) compared to gray matter (4.3±0.5%). The mean coefficient of variations for intra-subject MICEST contrast in WM and GM were 0.49 and 0.58 respectively. Potential overlap of CEST signals from other brain metabolites with the observed MICEST map is discussed. This noninvasive approach potentially opens the way to image MI in vivo and to monitor its alteration in many disease conditions. Copyright © 2010 Elsevier Inc. All rights reserved.

Orbitrap mass spectrometry characterization of hybrid chondroitin/dermatan sulfate hexasaccharide domains expressed in brain.

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Robu, Adrian C; Popescu, Laurentiu; Munteanu, Cristian V A; Seidler, Daniela G; Zamfir, Alina D

2015-09-15

In the central nervous system, chondroitin/dermatan sulfate (CS/DS) glycosaminoglycans (GAGs) modulate neurotrophic effects and glial cell maturation during brain development. Previous reports revealed that GAG composition could be responsible for CS/DS activities in brain. In this work, for the structural characterization of DS- and CS-rich domains in hybrid GAG chains extracted from neural tissue, we have developed an advanced approach based on high-resolution mass spectrometry (MS) using nanoelectrospray ionization Orbitrap in the negative ion mode. Our high-resolution MS and multistage MS approach was developed and applied to hexasaccharides obtained from 4- and 14-week-old mouse brains by GAG digestion with chondroitin B and in parallel with AC I lyase. The expression of DS- and CS-rich domains in the two tissues was assessed comparatively. The analyses indicated an age-related structural variability of the CS/DS motifs. The older brain was found to contain more structures and a higher sulfation of DS-rich regions, whereas the younger brain was found to be characterized by a higher sulfation of CS-rich regions. By multistage MS using collision-induced dissociation, we also demonstrated the incidence in mouse brain of an atypical [4,5-Δ-GlcAGalNAc(IdoAGalNAc)2], presenting a bisulfated CS disaccharide formed by 3-O-sulfate-4,5-Δ-GlcA and 6-O-sulfate-GalNAc moieties. Copyright © 2015 Elsevier Inc. All rights reserved.

Detection of Alzheimer’s disease amyloid-beta plaque deposition by deep brain impedance profiling

Science.gov (United States)

Béduer, Amélie; Joris, Pierre; Mosser, Sébastien; Fraering, Patrick C.; Renaud, Philippe

2015-04-01

Objective. Alzheimer disease (AD) is the most common form of neurodegenerative disease in elderly people. Toxic brain amyloid-beta (Aß) aggregates and ensuing cell death are believed to play a central role in the pathogenesis of the disease. In this study, we investigated if we could monitor the presence of these aggregates by performing in situ electrical impedance spectroscopy measurements in AD model mice brains. Approach. In this study, electrical impedance spectroscopy measurements were performed post-mortem in APPPS1 transgenic mice brains. This transgenic model is commonly used to study amyloidogenesis, a pathological hallmark of AD. We used flexible probes with embedded micrometric electrodes array to demonstrate the feasibility of detecting senile plaques composed of Aß peptides by localized impedance measurements. Main results. We particularly focused on deep brain structures, such as the hippocampus. Ex vivo experiments using brains from young and old APPPS1 mice lead us to show that impedance measurements clearly correlate with the percentage of Aβ plaque load in the brain tissues. We could monitor the effects of aging in the AD APPPS1 mice model. Significance. We demonstrated that a localized electrical impedance measurement constitutes a valuable technique to monitor the presence of Aβ-plaques, which is complementary with existing imaging techniques. This method does not require prior Aβ staining, precluding the risk of variations in tissue uptake of dyes or tracers, and consequently ensuring reproducible data collection.

miRNAs in brain development

International Nuclear Information System (INIS)

Petri, Rebecca; Malmevik, Josephine; Fasching, Liana; Åkerblom, Malin; Jakobsson, Johan

2014-01-01

MicroRNAs (miRNAs) are small, non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. In the brain, a large number of miRNAs are expressed and there is a growing body of evidence demonstrating that miRNAs are essential for brain development and neuronal function. Conditional knockout studies of the core components in the miRNA biogenesis pathway, such as Dicer and DGCR8, have demonstrated a crucial role for miRNAs during the development of the central nervous system. Furthermore, mice deleted for specific miRNAs and miRNA-clusters demonstrate diverse functional roles for different miRNAs during the development of different brain structures. miRNAs have been proposed to regulate cellular functions such as differentiation, proliferation and fate-determination of neural progenitors. In this review we summarise the findings from recent studies that highlight the importance of miRNAs in brain development with a focus on the mouse model. We also discuss the technical limitations of current miRNA studies that still limit our understanding of this family of non-coding RNAs and propose the use of novel and refined technologies that are needed in order to fully determine the impact of specific miRNAs in brain development. - Highlights: • miRNAs are essential for brain development and neuronal function. • KO of Dicer is embryonically lethal. • Conditional Dicer KO results in defective proliferation or increased apoptosis. • KO of individual miRNAs or miRNA families is necessary to determine function

Brain-computer interfaces

DEFF Research Database (Denmark)

Treder, Matthias S.; Miklody, Daniel; Blankertz, Benjamin

quality measure'. We were able to show that for stimuli close to the perceptual threshold, there was sometimes a discrepancy between overt responses and brain responses, shedding light on subjects using different response criteria (e.g., more liberal or more conservative). To conclude, brain-computer...... of perceptual and cognitive biases. Furthermore, subjects can only report on stimuli if they have a clear percept of them. On the other hand, the electroencephalogram (EEG), the electrical brain activity measured with electrodes on the scalp, is a more direct measure. It allows us to tap into the ongoing neural...... auditory processing stream. In particular, it can tap brain processes that are pre-conscious or even unconscious, such as the earliest brain responses to sounds stimuli in primary auditory cortex. In a series of studies, we used a machine learning approach to show that the EEG can accurately reflect...

Tracking the Reorganization of Module Structure in Time-Varying Weighted Brain Functional Connectivity Networks.

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Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert

2018-05-01

Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.

Ex vivo MR volumetry of human brain hemispheres.

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

2014-01-01

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. 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 antemortem and postmortem. This 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 intersubject volume variation. A close linear correspondence was detected between in vivo and ex vivo volumetric measurements. Regional brain volumes measured with this 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 this approach captures information linked to antemortem macrostructural brain characteristics. Copyright © 2013 Wiley Periodicals, Inc.

A data-driven approach for evaluating multi-modal therapy in traumatic brain injury.

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Haefeli, Jenny; Ferguson, Adam R; Bingham, Deborah; Orr, Adrienne; Won, Seok Joon; Lam, Tina I; Shi, Jian; Hawley, Sarah; Liu, Jialing; Swanson, Raymond A; Massa, Stephen M

2017-02-16

Combination therapies targeting multiple recovery mechanisms have the potential for additive or synergistic effects, but experimental design and analyses of multimodal therapeutic trials are challenging. To address this problem, we developed a data-driven approach to integrate and analyze raw source data from separate pre-clinical studies and evaluated interactions between four treatments following traumatic brain injury. Histologic and behavioral outcomes were measured in 202 rats treated with combinations of an anti-inflammatory agent (minocycline), a neurotrophic agent (LM11A-31), and physical therapy consisting of assisted exercise with or without botulinum toxin-induced limb constraint. Data was curated and analyzed in a linked workflow involving non-linear principal component analysis followed by hypothesis testing with a linear mixed model. Results revealed significant benefits of the neurotrophic agent LM11A-31 on learning and memory outcomes after traumatic brain injury. In addition, modulations of LM11A-31 effects by co-administration of minocycline and by the type of physical therapy applied reached statistical significance. These results suggest a combinatorial effect of drug and physical therapy interventions that was not evident by univariate analysis. The study designs and analytic techniques applied here form a structured, unbiased, internally validated workflow that may be applied to other combinatorial studies, both in animals and humans.

An ANOVA approach for statistical comparisons of brain networks.

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Fraiman, Daniel; Fraiman, Ricardo

2018-03-16

The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.

Investigations of primary blast-induced traumatic brain injury

Science.gov (United States)

Sawyer, T. W.; Josey, T.; Wang, Y.; Villanueva, M.; Ritzel, D. V.; Nelson, P.; Lee, J. J.

2018-01-01

The development of an advanced blast simulator (ABS) has enabled the reproducible generation of single-pulse shock waves that simulate free-field blast with high fidelity. Studies with rodents in the ABS demonstrated the necessity of head restraint during head-only exposures. When the head was not restrained, violent global head motion was induced by pressures that would not produce similar movement of a target the size and mass of a human head. This scaling artefact produced changes in brain function that were reminiscent of traumatic brain injury (TBI) due to impact-acceleration effects. Restraint of the rodent head eliminated these, but still produced subtle changes in brain biochemistry, showing that blast-induced pressure waves do cause brain deficits. Further experiments were carried out with rat brain cell aggregate cultures that enabled the conduct of studies without the gross movement encountered when using rodents. The suspension nature of this model was also exploited to minimize the boundary effects that complicate the interpretation of primary blast studies using surface cultures. Using this system, brain tissue was found not only to be sensitive to pressure changes, but also able to discriminate between the highly defined single-pulse shock waves produced by underwater blast and the complex pressure history exposures experienced by aggregates encased within a sphere and subjected to simulated air blast. The nature of blast-induced primary TBI requires a multidisciplinary research approach that addresses the fidelity of the blast insult, its accurate measurement and characterization, as well as the limitations of the biological models used.

Anatomical and functional assemblies of brain BOLD oscillations

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Baria, Alexis T.; Baliki, Marwan N.; Parrish, Todd; Apkarian, A. Vania

2011-01-01

Brain oscillatory activity has long been thought to have spatial properties, the details of which are unresolved. Here we examine spatial organizational rules for the human brain oscillatory activity as measured by blood oxygen level-dependent (BOLD). Resting state BOLD signal was transformed into frequency space (Welch’s method), averaged across subjects, and its spatial distribution studied as a function of four frequency bands, spanning the full bandwidth of BOLD. The brain showed anatomically constrained distribution of power for each frequency band. This result was replicated on a repository dataset of 195 subjects. Next, we examined larger-scale organization by parceling the neocortex into regions approximating Brodmann Areas (BAs). This indicated that BAs of simple function/connectivity (unimodal), vs. complex properties (transmodal), are dominated by low frequency BOLD oscillations, and within the visual ventral stream we observe a graded shift of power to higher frequency bands for BAs further removed from the primary visual cortex (increased complexity), linking frequency properties of BOLD to hodology. Additionally, BOLD oscillation properties for the default mode network demonstrated that it is composed of distinct frequency dependent regions. When the same analysis was performed on a visual-motor task, frequency-dependent global and voxel-wise shifts in BOLD oscillations could be detected at brain sites mostly outside those identified with general linear modeling. Thus, analysis of BOLD oscillations in full bandwidth uncovers novel brain organizational rules, linking anatomical structures and functional networks to characteristic BOLD oscillations. The approach also identifies changes in brain intrinsic properties in relation to responses to external inputs. PMID:21613505

Phenotypic integration of neurocranium and brain.

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Richtsmeier, Joan T; Aldridge, Kristina; DeLeon, Valerie B; Panchal, Jayesh; Kane, Alex A; Marsh, Jeffrey L; Yan, Peng; Cole, Theodore M

2006-07-15

Evolutionary history of Mammalia provides strong evidence that the morphology of skull and brain change jointly in evolution. Formation and development of brain and skull co-occur and are dependent upon a series of morphogenetic and patterning processes driven by genes and their regulatory programs. Our current concept of skull and brain as separate tissues results in distinct analyses of these tissues by most researchers. In this study, we use 3D computed tomography and magnetic resonance images of pediatric individuals diagnosed with premature closure of cranial sutures (craniosynostosis) to investigate phenotypic relationships between the brain and skull. It has been demonstrated previously that the skull and brain acquire characteristic dysmorphologies in isolated craniosynostosis, but relatively little is known of the developmental interactions that produce these anomalies. Our comparative analysis of phenotypic integration of brain and skull in premature closure of the sagittal and the right coronal sutures demonstrates that brain and skull are strongly integrated and that the significant differences in patterns of association do not occur local to the prematurely closed suture. We posit that the current focus on the suture as the basis for this condition may identify a proximate, but not the ultimate cause for these conditions. Given that premature suture closure reduces the number of cranial bones, and that a persistent loss of skull bones is demonstrated over the approximately 150 million years of synapsid evolution, craniosynostosis may serve as an informative model for evolution of the mammalian skull. Copyright 2006 Wiley-Liss, Inc.

Personal narrative approaches in rehabilitation following traumatic brain injury: A synthesis of qualitative research.

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D'Cruz, Kate; Douglas, Jacinta; Serry, Tanya

2017-08-09

Although narrative storytelling has been found to assist identity construction, there is little direct research regarding its application in rehabilitation following traumatic brain injury (TBI). The aim of this review was to identify published evidence on the use of personal narrative approaches in rehabilitation following TBI and to synthesise the findings across this literature. A systematic search of four databases was conducted in December 2016. No limit was set on the start date of the search. Personal narrative approaches were defined as direct client participation in sharing personal stories using written, spoken or visual methods. The search retrieved 12 qualitative research articles on the use of personal narrative approaches in TBI rehabilitation. Thematic synthesis of the narrative data and authors' reported findings of the 12 articles yielded an overall theme of building a strengths-based identity and four sub-themes: 1) expressing and communicating to others; 2) feeling validated by the act of someone listening; 3) reflecting and learning about oneself; and 4) being productive. The findings of this review support the use of personal narrative approaches in addressing loss of identity following TBI. Healthcare professionals and the community are encouraged to seek opportunities for survivors of TBI to share their stories.

Optical Methods and Instrumentation in Brain Imaging and Therapy

CERN Document Server

2013-01-01

This book provides a comprehensive up-to-date review of optical approaches used in brain imaging and therapy. It covers a variety of imaging techniques including diffuse optical imaging, laser speckle imaging, photoacoustic imaging and optical coherence tomography. A number of laser-based therapeutic approaches are reviewed, including photodynamic therapy, fluorescence guided resection and photothermal therapy. Fundamental principles and instrumentation are discussed for each imaging and therapeutic technique. Represents the first publication dedicated solely to optical diagnostics and therapeutics in the brain Provides a comprehensive review of the principles of each imaging/therapeutic modality Reviews the latest advances in instrumentation for optical diagnostics in the brain Discusses new optical-based therapeutic approaches for brain diseases

Dynamic Multi-Coil Technique (DYNAMITE) Shimming of the Rat Brain at 11.7 Tesla

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Juchem, Christoph; Herman, Peter; Sanganahalli, Basavaraju G.; Brown, Peter B.; McIntyre, Scott; Nixon, Terence W.; Green, Dan; Hyder, Fahmeed; de Graaf, Robin A.

2014-01-01

The in vivo rat model is a workhorse in neuroscience research, preclinical studies and drug development. A repertoire of MR tools has been developed for its investigation, however, high levels of B0 magnetic field homogeneity are required for meaningful results. The homogenization of magnetic fields in the rat brain, i.e. shimming, is a difficult task due to a multitude of complex, susceptibility-induced field distortions. Conventional shimming with spherical harmonic (SH) functions is capable of compensating shallow field distortions in limited areas, e.g. in the cortex, but performs poorly in difficult-to-shim subcortical structures or for the entire brain. Based on the recently introduced multi-coil approach for magnetic field modeling, the DYNAmic Multi-coIl TEchnique (DYNAMITE) is introduced for magnetic field shimming of the in vivo rat brain and its benefits for gradient-echo echo-planar imaging (EPI) are demonstrated. An integrated multi-coil/radio-frequency (MC/RF) system comprising 48 individual localized DC coils for B0 shimming and a surface transceive RF coil has been developed that allows MR investigations of the anesthetized rat brain in vivo. DYNAMITE shimming with this MC/RF setup is shown to reduce the B0 standard deviation to a third of that achieved with current shim technology employing static first through third order SH shapes. The EPI signal over the rat brain increased by 31% and a 24% gain in usable EPI voxels could be realized. DYNAMITE shimming is expected to critically benefit a wide range of preclinical and neuroscientific MR research. Improved magnetic field homogeneity, along with the achievable large brain coverage of this method will be crucial when signal pathways, cortical circuitry or the brain’s default network are studied. Along with the efficiency gains of MC-based shimming compared to SH approaches demonstrated recently, DYNAMITE shimming has the potential to replace conventional SH shim systems in small bore animal

Encoder-decoder optimization for brain-computer interfaces.

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Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam

2015-06-01

Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Encoder-decoder optimization for brain-computer interfaces.

Directory of Open Access Journals (Sweden)

Josh Merel

2015-06-01

Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.

Glutamate Efflux at the Blood-Brain Barrier

DEFF Research Database (Denmark)

Cederberg-Helms, Hans Christian; Uhd-Nielsen, Carsten; Brodin, Birger

2014-01-01

is well known, however endothelial cells may also play an important role through mediating brain-to-blood L-glutamate efflux. Expression of excitatory amino acid transporters has been demonstrated in brain endothelial cells of bovine, human, murine, rat and porcine origin. These can account for high...... affinity concentrative uptake of L-glutamate from the brain interstitial fluid into the capillary endothelial cells. The mechanisms in between L-glutamate uptake in the endothelial cells and L-glutamate appearing in the blood are still unclear and may involve a luminal transporter for L......-glutamate, metabolism of L-glutamate and transport of metabolites or a combination of the two. However, both in vitro and in vivo studies have demonstrated blood-to-brain transport of L-glutamate, at least during pathological events. This review summarizes the current knowledge on the brain-to-blood L-glutamate efflux...

Non-invasive brain-to-brain interface (BBI: establishing functional links between two brains.

Directory of Open Access Journals (Sweden)

Seung-Schik Yoo

Full Text Available Transcranial focused ultrasound (FUS is capable of modulating the neural activity of specific brain regions, with a potential role as a non-invasive computer-to-brain interface (CBI. In conjunction with the use of brain-to-computer interface (BCI techniques that translate brain function to generate computer commands, we investigated the feasibility of using the FUS-based CBI to non-invasively establish a functional link between the brains of different species (i.e. human and Sprague-Dawley rat, thus creating a brain-to-brain interface (BBI. The implementation was aimed to non-invasively translate the human volunteer's intention to stimulate a rat's brain motor area that is responsible for the tail movement. The volunteer initiated the intention by looking at a strobe light flicker on a computer display, and the degree of synchronization in the electroencephalographic steady-state-visual-evoked-potentials (SSVEP with respect to the strobe frequency was analyzed using a computer. Increased signal amplitude in the SSVEP, indicating the volunteer's intention, triggered the delivery of a burst-mode FUS (350 kHz ultrasound frequency, tone burst duration of 0.5 ms, pulse repetition frequency of 1 kHz, given for 300 msec duration to excite the motor area of an anesthetized rat transcranially. The successful excitation subsequently elicited the tail movement, which was detected by a motion sensor. The interface was achieved at 94.0±3.0% accuracy, with a time delay of 1.59±1.07 sec from the thought-initiation to the creation of the tail movement. Our results demonstrate the feasibility of a computer-mediated BBI that links central neural functions between two biological entities, which may confer unexplored opportunities in the study of neuroscience with potential implications for therapeutic applications.

Brain 3M--A New Approach to Learning about Brain, Behavior, and Cognition

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Li, Ping; Chaby, Lauren E.; Legault, Jennifer; Braithwaite, Victoria A.

2015-01-01

By combining emerging technologies with cognitive and education theories, we are capitalizing on recent findings from adaptive exploration and embodied learning research to address significant gaps in the education of brain sciences for school children and college level students. Through the development of virtual learning tools in combination…

Drug-induced trafficking of p-glycoprotein in human brain capillary endothelial cells as demonstrated by exposure to mitomycin C.

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Noack, Andreas; Noack, Sandra; Hoffmann, Andrea; Maalouf, Katia; Buettner, Manuela; Couraud, Pierre-Olivier; Romero, Ignacio A; Weksler, Babette; Alms, Dana; Römermann, Kerstin; Naim, Hassan Y; Löscher, Wolfgang

2014-01-01

P-glycoprotein (Pgp; ABCB1/MDR1) is a major efflux transporter at the blood-brain barrier (BBB), restricting the penetration of various compounds. In other tissues, trafficking of Pgp from subcellular stores to the cell surface has been demonstrated and may constitute a rapid way of the cell to respond to toxic compounds by functional membrane insertion of the transporter. It is not known whether drug-induced Pgp trafficking also occurs in brain capillary endothelial cells that form the BBB. In this study, trafficking of Pgp was investigated in human brain capillary endothelial cells (hCMEC/D3) that were stably transfected with a doxycycline-inducible MDR1-EGFP fusion plasmid. In the presence of doxycycline, these cells exhibited a 15-fold increase in Pgp-EGFP fusion protein expression, which was associated with an increased efflux of the Pgp substrate rhodamine 123 (Rho123). The chemotherapeutic agent mitomycin C (MMC) was used to study drug-induced trafficking of Pgp. Confocal fluorescence microscopy of single hCMEC/D3-MDR1-EGFP cells revealed that Pgp redistribution from intracellular pools to the cell surface occurred within 2 h of MMC exposure. Pgp-EGFP exhibited a punctuate pattern at the cell surface compatible with concentrated regions of the fusion protein in membrane microdomains, i.e., lipid rafts, which was confirmed by Western blot analysis of biotinylated cell surface proteins in Lubrol-resistant membranes. MMC exposure also increased the functionality of Pgp as assessed in three functional assays with Pgp substrates (Rho123, eFluxx-ID Gold, calcein-AM). However, this increase occurred with some delay after the increased Pgp expression and coincided with the release of Pgp from the Lubrol-resistant membrane complexes. Disrupting rafts by depleting the membrane of cholesterol increased the functionality of Pgp. Our data present the first direct evidence of drug-induced Pgp trafficking at the human BBB and indicate that Pgp has to be released from lipid

Drug-Induced Trafficking of P-Glycoprotein in Human Brain Capillary Endothelial Cells as Demonstrated by Exposure to Mitomycin C

Science.gov (United States)

Noack, Andreas; Noack, Sandra; Hoffmann, Andrea; Maalouf, Katia; Buettner, Manuela; Couraud, Pierre-Olivier; Romero, Ignacio A.; Weksler, Babette; Alms, Dana; Römermann, Kerstin; Naim, Hassan Y.; Löscher, Wolfgang

2014-01-01

P-glycoprotein (Pgp; ABCB1/MDR1) is a major efflux transporter at the blood-brain barrier (BBB), restricting the penetration of various compounds. In other tissues, trafficking of Pgp from subcellular stores to the cell surface has been demonstrated and may constitute a rapid way of the cell to respond to toxic compounds by functional membrane insertion of the transporter. It is not known whether drug-induced Pgp trafficking also occurs in brain capillary endothelial cells that form the BBB. In this study, trafficking of Pgp was investigated in human brain capillary endothelial cells (hCMEC/D3) that were stably transfected with a doxycycline-inducible MDR1-EGFP fusion plasmid. In the presence of doxycycline, these cells exhibited a 15-fold increase in Pgp-EGFP fusion protein expression, which was associated with an increased efflux of the Pgp substrate rhodamine 123 (Rho123). The chemotherapeutic agent mitomycin C (MMC) was used to study drug-induced trafficking of Pgp. Confocal fluorescence microscopy of single hCMEC/D3-MDR1-EGFP cells revealed that Pgp redistribution from intracellular pools to the cell surface occurred within 2 h of MMC exposure. Pgp-EGFP exhibited a punctuate pattern at the cell surface compatible with concentrated regions of the fusion protein in membrane microdomains, i.e., lipid rafts, which was confirmed by Western blot analysis of biotinylated cell surface proteins in Lubrol-resistant membranes. MMC exposure also increased the functionality of Pgp as assessed in three functional assays with Pgp substrates (Rho123, eFluxx-ID Gold, calcein-AM). However, this increase occurred with some delay after the increased Pgp expression and coincided with the release of Pgp from the Lubrol-resistant membrane complexes. Disrupting rafts by depleting the membrane of cholesterol increased the functionality of Pgp. Our data present the first direct evidence of drug-induced Pgp trafficking at the human BBB and indicate that Pgp has to be released from lipid

Glucose transporter 1 and monocarboxylate transporters 1, 2, and 4 localization within the glial cells of shark blood-brain-barriers.

Directory of Open Access Journals (Sweden)

Carolina Balmaceda-Aguilera

Full Text Available Although previous studies showed that glucose is used to support the metabolic activity of the cartilaginous fish brain, the distribution and expression levels of glucose transporter (GLUT isoforms remained undetermined. Optic/ultrastructural immunohistochemistry approaches were used to determine the expression of GLUT1 in the glial blood-brain barrier (gBBB. GLUT1 was observed solely in glial cells; it was primarily located in end-feet processes of the gBBB. Western blot analysis showed a protein with a molecular mass of 50 kDa, and partial sequencing confirmed GLUT1 identity. Similar approaches were used to demonstrate increased GLUT1 polarization to both apical and basolateral membranes in choroid plexus epithelial cells. To explore monocarboxylate transporter (MCT involvement in shark brain metabolism, the expression of MCTs was analyzed. MCT1, 2 and 4 were expressed in endothelial cells; however, only MCT1 and MCT4 were present in glial cells. In neurons, MCT2 was localized at the cell membrane whereas MCT1 was detected within mitochondria. Previous studies demonstrated that hypoxia modified GLUT and MCT expression in mammalian brain cells, which was mediated by the transcription factor, hypoxia inducible factor-1. Similarly, we observed that hypoxia modified MCT1 cellular distribution and MCT4 expression in shark telencephalic area and brain stem, confirming the role of these transporters in hypoxia adaptation. Finally, using three-dimensional ultrastructural microscopy, the interaction between glial end-feet and leaky blood vessels of shark brain was assessed in the present study. These data suggested that the brains of shark may take up glucose from blood using a different mechanism than that used by mammalian brains, which may induce astrocyte-neuron lactate shuttling and metabolic coupling as observed in mammalian brain. Our data suggested that the structural conditions and expression patterns of GLUT1, MCT1, MCT2 and MCT4 in shark

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip.

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Dauth, Stephanie; Maoz, Ben M; Sheehy, Sean P; Hemphill, Matthew A; Murty, Tara; Macedonia, Mary Kate; Greer, Angie M; Budnik, Bogdan; Parker, Kevin Kit

2017-03-01

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features. NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the

Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general.

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Zander, Thorsten O; Kothe, Christian

2011-04-01

Cognitive monitoring is an approach utilizing realtime brain signal decoding (RBSD) for gaining information on the ongoing cognitive user state. In recent decades this approach has brought valuable insight into the cognition of an interacting human. Automated RBSD can be used to set up a brain-computer interface (BCI) providing a novel input modality for technical systems solely based on brain activity. In BCIs the user usually sends voluntary and directed commands to control the connected computer system or to communicate through it. In this paper we propose an extension of this approach by fusing BCI technology with cognitive monitoring, providing valuable information about the users' intentions, situational interpretations and emotional states to the technical system. We call this approach passive BCI. In the following we give an overview of studies which utilize passive BCI, as well as other novel types of applications resulting from BCI technology. We especially focus on applications for healthy users, and the specific requirements and demands of this user group. Since the presented approach of combining cognitive monitoring with BCI technology is very similar to the concept of BCIs itself we propose a unifying categorization of BCI-based applications, including the novel approach of passive BCI.

Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy.

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Niu, Haijing; Wang, Jinhui; Zhao, Tengda; Shu, Ni; He, Yong

2012-01-01

The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.

Brain abscess mimicking lung cancer metastases; a case report.

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Asano, Michiko; Fujimoto, Nobukazu; Fuchimoto, Yasuko; Ono, Katsuichiro; Ozaki, Shinji; Kimura, Fumiaki; Kishimoto, Takumi

2013-01-01

A 76-year-old woman came to us because of staggering, fever, dysarthria, and appetite loss. Magnetic resonance imaging (MRI) of the brain revealed multiple masses with surrounding edema. Chest X-ray and computed tomography demonstrated a mass-like lesion in the left lung and left pleural effusion. Lung cancer and multiple brain metastases were suspected. However, the brain lesions demonstrated a high intensity through diffusion-weighted MRI. The finding was an important key to differentiate brain abscesses from lung cancer metastases. Copyright © 2013 Elsevier Inc. All rights reserved.

BrainAGE score indicates accelerated brain aging in schizophrenia, but not bipolar disorder.

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Nenadić, Igor; Dietzek, Maren; Langbein, Kerstin; Sauer, Heinrich; Gaser, Christian

2017-08-30

BrainAGE (brain age gap estimation) is a novel morphometric parameter providing a univariate score derived from multivariate voxel-wise analyses. It uses a machine learning approach and can be used to analyse deviation from physiological developmental or aging-related trajectories. Using structural MRI data and BrainAGE quantification of acceleration or deceleration of in individual aging, we analysed data from 45 schizophrenia patients, 22 bipolar I disorder patients (mostly with previous psychotic symptoms / episodes), and 70 healthy controls. We found significantly higher BrainAGE scores in schizophrenia, but not bipolar disorder patients. Our findings indicate significantly accelerated brain structural aging in schizophrenia. This suggests, that despite the conceptualisation of schizophrenia as a neurodevelopmental disorder, there might be an additional progressive pathogenic component. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Awareness of deficits in traumatic brain injury: a multidimensional approach to assessing metacognitive knowledge and online-awareness.

LENUS (Irish Health Repository)

O'Keeffe, Fiadhnait

2007-01-01

Recent models of impaired awareness in brain injury draw a distinction between metacognitive knowledge of difficulties and online awareness of errors (emergent and anticipatory). We examined performance of 31 Traumatic Brain Injury (TBI) participants and 31 healthy controls using a three-strand approach to assessing awareness. Metacognitive knowledge was assessed with an awareness interview and discrepancy scores on three questionnaires--Patient Competency Rating Scale, Frontal Systems Behavioral Scale and the Cognitive Failures Questionnaire. Online Emergent Awareness was assessed using an online error-monitoring task while participants performed tasks of sustained attention. Online anticipatory awareness was examined using prediction performance on two cognitive tasks. Results indicated that the TBI Low Self-Awareness (SA) group and High SA group did not differ in terms of severity, chronicity or standard neuropsychological tasks but those with Low SA were more likely to exhibit disinhibition, interpersonal problems and more difficulties in total competency. Sustained attention abilities were associated with both types of online awareness (emergent and anticipatory). There was a strong relationship between online emergent and online anticipatory awareness. Metacognitive knowledge did not correlate with the other two measures. This study highlights the necessity in adopting a multidimensional approach to assessing the multifaceted phenomenon of awareness of deficits.

Hypofractionation Regimens for Stereotactic Radiotherapy for Large Brain Tumors

International Nuclear Information System (INIS)

Yuan Jiankui; Wang, Jian Z.; Lo, Simon; Grecula, John C.; Ammirati, Mario; Montebello, Joseph F.; Zhang Hualin; Gupta, Nilendu; Yuh, William T.C.; Mayr, Nina A.

2008-01-01

Purpose: To investigate equivalent regimens for hypofractionated stereotactic radiotherapy (HSRT) for brain tumor treatment and to provide dose-escalation guidance to maximize the tumor control within the normal brain tolerance. Methods and Materials: The linear-quadratic model, including the effect of nonuniform dose distributions, was used to evaluate the HSRT regimens. The α/β ratio was estimated using the Gammaknife stereotactic radiosurgery (GKSRS) and whole-brain radiotherapy experience for large brain tumors. The HSRT regimens were derived using two methods: (1) an equivalent tumor control approach, which matches the whole-brain radiotherapy experience for many fractions and merges it with the GKSRS data for few fractions; and (2) a normal-tissue tolerance approach, which takes advantages of the dose conformity and fractionation of HSRT to approach the maximal dose tolerance of the normal brain. Results: A plausible α/β ratio of 12 Gy for brain tumor and a volume parameter n of 0.23 for normal brain were derived from the GKSRS and whole-brain radiotherapy data. The HSRT prescription regimens for the isoeffect of tumor irradiation were calculated. The normal-brain equivalent uniform dose decreased as the number of fractions increased, because of the advantage of fractionation. The regimens for potential dose escalation of HSRT within the limits of normal-brain tolerance were derived. Conclusions: The designed hypofractionated regimens could be used as a preliminary guide for HSRT dose prescription for large brain tumors to mimic the GKSRS experience and for dose escalation trials. Clinical studies are necessary to further tune the model parameters and validate these regimens

BrainNetVis: analysis and visualization of brain functional networks.

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Tsiaras, Vassilis; Andreou, Dimitris; Tollis, Ioannis G

2009-01-01

BrainNetVis is an application, written in Java, that displays and analyzes synchronization networks from brain signals. The program implements a number of network indices and visualization techniques. We demonstrate its use through a case study of left hand and foot motor imagery. The data sets were provided by the Berlin BCI group. Using this program we managed to find differences between the average left hand and foot synchronization networks by comparing them with the average idle state synchronization network.

Mapping effective connectivity in the human brain with concurrent intracranial electrical stimulation and BOLD-fMRI.

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Oya, Hiroyuki; Howard, Matthew A; Magnotta, Vincent A; Kruger, Anton; Griffiths, Timothy D; Lemieux, Louis; Carmichael, David W; Petkov, Christopher I; Kawasaki, Hiroto; Kovach, Christopher K; Sutterer, Matthew J; Adolphs, Ralph

2017-02-01

Understanding brain function requires knowledge of how one brain region causally influences another. This information is difficult to obtain directly in the human brain, and is instead typically inferred from resting-state fMRI. Here, we demonstrate the safety and scientific promise of a novel and complementary approach: concurrent electrical stimulation and fMRI (es-fMRI) at 3T in awake neurosurgical patients with implanted depth electrodes. We document the results of safety testing, actual experimental setup, and stimulation parameters, that safely and reliably evoke activation in distal structures through stimulation of amygdala, cingulate, or prefrontal cortex. We compare connectivity inferred from the evoked patterns of activation with that estimated from standard resting-state fMRI in the same patients: while connectivity patterns obtained with each approach are correlated, each method produces unique results. Response patterns were stable over the course of 11min of es-fMRI runs. COMPARISON WITH EXISTING METHOD: es-fMRI in awake humans yields unique information about effective connectivity, complementing resting-state fMRI. Although our stimulations were below the level of inducing any apparent behavioral or perceptual effects, a next step would be to use es-fMRI to modulate task performances. This would reveal the acute network-level changes induced by the stimulation that mediate the behavioral and cognitive effects seen with brain stimulation. es-fMRI provides a novel and safe approach for mapping effective connectivity in the human brain in a clinical setting, and will inform treatments for psychiatric and neurodegenerative disorders that use deep brain stimulation. Copyright © 2016 Elsevier B.V. All rights reserved.

Ex-vivo MR Volumetry of Human Brain Hemispheres

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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

Demonstration of statistical approaches to identify component's ageing by operational data analysis-A case study for the ageing PSA network

International Nuclear Information System (INIS)

Rodionov, Andrei; Atwood, Corwin L.; Kirchsteiger, Christian; Patrik, Milan

2008-01-01

The paper presents some results of a case study on 'Demonstration of statistical approaches to identify the component's ageing by operational data analysis', which was done in the frame of the EC JRC Ageing PSA Network. Several techniques: visual evaluation, nonparametric and parametric hypothesis tests, were proposed and applied in order to demonstrate the capacity, advantages and limitations of statistical approaches to identify the component's ageing by operational data analysis. Engineering considerations are out of the scope of the present study

Surprise responses in the human brain demonstrate statistical learning under high concurrent cognitive demand

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Garrido, Marta Isabel; Teng, Chee Leong James; Taylor, Jeremy Alexander; Rowe, Elise Genevieve; Mattingley, Jason Brett

2016-06-01

The ability to learn about regularities in the environment and to make predictions about future events is fundamental for adaptive behaviour. We have previously shown that people can implicitly encode statistical regularities and detect violations therein, as reflected in neuronal responses to unpredictable events that carry a unique prediction error signature. In the real world, however, learning about regularities will often occur in the context of competing cognitive demands. Here we asked whether learning of statistical regularities is modulated by concurrent cognitive load. We compared electroencephalographic metrics associated with responses to pure-tone sounds with frequencies sampled from narrow or wide Gaussian distributions. We showed that outliers evoked a larger response than those in the centre of the stimulus distribution (i.e., an effect of surprise) and that this difference was greater for physically identical outliers in the narrow than in the broad distribution. These results demonstrate an early neurophysiological marker of the brain's ability to implicitly encode complex statistical structure in the environment. Moreover, we manipulated concurrent cognitive load by having participants perform a visual working memory task while listening to these streams of sounds. We again observed greater prediction error responses in the narrower distribution under both low and high cognitive load. Furthermore, there was no reliable reduction in prediction error magnitude under high-relative to low-cognitive load. Our findings suggest that statistical learning is not a capacity limited process, and that it proceeds automatically even when cognitive resources are taxed by concurrent demands.

[Application of individually designed trans-fissure approach in brain surgery: analysis of 90 cases].

Science.gov (United States)

Zhao, Ji-Zong; Wang, Shuo; Zhang, Mao-Zhi; Wang, Lei; Wang, Rong; Tang, Ya-Juan

2009-01-06

To explore the feasibility and value of trans-fissure approaches in brain surgery through individually designed craniotomy. Ninety patients with intracranial space-occupying lesions, 47 males and 58 females, aged (43 +/- 14) (1 - 68), were treated by individualized trans-fissure approach surgeries. Linear scalp incision or "horseshoe shape" scalp incision were designed to perform the operation, with a bone flap 3 - 4 cm in diameter. The shortest approach to reach the lesion was decided under the guidance of neuro-navigation and real-time B-mode ultrasonography. Then the lesions were removed through natural cortical fissures. Another 79 patients with intracranial space-occupying lesions, 53 males and 51 females, aged (42 +/- 11) (15 -73), undergoing classical surgeries in the same period were used as control group. The average operation time, size of bone flap, amount of blood loss, hospitalization time, and hospitalization cost were compared between these 2 groups. The operation time of the individually designed trans-fissure approach group was (3.1 +/- 1.6) hours (1.33 - 10.83 hours), significantly shorter than that of the control group [(4.8 +/- 1.9) hrs, P trans-fissure approach group was (173 +/- 168) ml (20 m - 500 ml), significantly less than that of the control group [(410 +/- 61) ml, P trans-fissure approach group was (12 +/- 5) cm2 [(1 - 25) cm2], significantly smaller than that of the control group [(20. +/- 9) cm2, P trans-fissure approach group received retransfusion, compared to 15 in the control group, during operation. No infection or other significant complications occurred after operation in the individually designed trans-fissure approach group. The hospitalization time of the individually designed trans-fissure approach group was (20 +/- 6) days (9 - 39 days), significantly shorter than that of the control group [(24 +/- 7) days, P trans-fissure approach group was (23171 +/- 7280) yuan RMB; significantly lower than that of the control group

Brain tumor-targeted drug delivery strategies

Directory of Open Access Journals (Sweden)

Xiaoli Wei

2014-06-01

Full Text Available Despite the application of aggressive surgery, radiotherapy and chemotherapy in clinics, brain tumors are still a difficult health challenge due to their fast development and poor prognosis. Brain tumor-targeted drug delivery systems, which increase drug accumulation in the tumor region and reduce toxicity in normal brain and peripheral tissue, are a promising new approach to brain tumor treatments. Since brain tumors exhibit many distinctive characteristics relative to tumors growing in peripheral tissues, potential targets based on continuously changing vascular characteristics and the microenvironment can be utilized to facilitate effective brain tumor-targeted drug delivery. In this review, we briefly describe the physiological characteristics of brain tumors, including blood–brain/brain tumor barriers, the tumor microenvironment, and tumor stem cells. We also review targeted delivery strategies and introduce a systematic targeted drug delivery strategy to overcome the challenges.

Acute traumatic brain-stem hemorrhage produced by sudden caudal displacement of the brain

International Nuclear Information System (INIS)

Mirvis, S.E.; Wolf, A.L.; Thompson, R.K.

1990-01-01

This paper determines in an experimental canine study and a clinical review, whether acute caudal displacement of the brain following blunt trauma produces hemorrhage in the rostral anterior midline of the brain stem by tethering the basilar to the fixed carotid arteries. In four dogs, a balloon catheter was suddenly inflated over the frontal lobe; in two, the carotid-basilar vascular connections were severed prior to balloon inflation. ICP was monitored during and after balloon inflation. Hemorrhage was verified by MR imaging and direct inspection of the fixed brain specimens. Admission CT scans demonstrating acute traumatic brain stem hemorrhage (TBH) in human patients were reviewed to determine the site of TBH, predominant site of impact, and neurologic outcome

Enzymatic method for the sensitive demonstration of postnatal effects caused by prenatal X-irradiation in mouse brain

International Nuclear Information System (INIS)

Weber, L.W.D.; Schmahl, W.G.; Kriegel, H.

1982-01-01

We have investigated the activities (per gram of wet tissue) of mouse brain acetylcholinesterase and Na, K-ATPase, with respect to the effects brought about by a prenatal X-ray dose. Pregnant NMRI mice received an X-ray dose of 0.24, 0.49, 0.95 or 1.9 Gy each on the 12th day of gestation. Investigations on the offspring were performed on the day of birth and the postnatal days 2, 5, 8, 12, 16, 23, 34, 48 and 64, respectively. The brain weights were reduced by the X-ray treatment dose - dependently and without recovery. This was well discernible after 0.24 Gy and reached about 40% reduction after 1.9 Gy. There were significant differences between irradiated and control enzyme activities on most of the days examined. On the 48th postnatal day both enzymes' activities were thoroughly elevated after 0.24 and 0.49 Gy. This could be reproduced in another test series with 0.49 Gy, but vanished when enzyme activities were related to the brain protein contents. As a more reliable parameter of the developmental age brain weights were compared to the corresponding enzyme activities. (orig./MG)

Information technology for brain banking.

Science.gov (United States)

Schmitz, Peer

2018-01-01

Implementing and maintaining the information technology (IT) infrastructure of a brain bank can be a daunting task for any brain bank coordinator, particularly when access to both funds and IT professionals is limited. Many questions arise when attempting to determine which IT products are most suitable for a brain bank. The requirements of each brain bank must be assessed carefully to ensure that the chosen IT infrastructure will be able to meet those requirements successfully and will be able to expand and adapt as the size of the brain bank increases. This chapter provides some valuable insights to be considered when implementing the IT infrastructure for a brain bank and discusses the pros and cons of various approaches and products. Copyright © 2018 Elsevier B.V. All rights reserved.

Metallothioneins are multipurpose neuroprotectants during brain pathology

DEFF Research Database (Denmark)

Penkowa, Milena

2006-01-01

Metallothioneins (MTs) constitute a family of cysteine-rich metalloproteins involved in cytoprotection during pathology. In mammals there are four isoforms (MT-I - IV), of which MT-I and -II (MT-I + II) are the best characterized MT proteins in the brain. Accumulating studies have demonstrated MT......-I overexpression demonstrated the importance of MT-I + II for coping with brain pathology. In addition, exogenous MT-I or MT-II injected intraperitoneally is able to promote similar effects as those of endogenous MT-I + II, which indicates that MT-I + II have both extra- and intracellular actions. In injured brain...

Transgenerational epigenetic programming of the brain transcriptome and anxiety behavior.

Directory of Open Access Journals (Sweden)

Michael K Skinner

Full Text Available Embryonic exposure to the endocrine disruptor vinclozolin during gonadal sex determination promotes an epigenetic reprogramming of the male germ-line that is associated with transgenerational adult onset disease states. Further analysis of this transgenerational phenotype on the brain demonstrated reproducible changes in the brain transcriptome three generations (F3 removed from the exposure. The transgenerational alterations in the male and female brain transcriptomes were distinct. In the males, the expression of 92 genes in the hippocampus and 276 genes in the amygdala were transgenerationally altered. In the females, the expression of 1,301 genes in the hippocampus and 172 genes in the amygdala were transgenerationally altered. Analysis of specific gene sets demonstrated that several brain signaling pathways were influenced including those involved in axon guidance and long-term potentiation. An investigation of behavior demonstrated that the vinclozolin F3 generation males had a decrease in anxiety-like behavior, while the females had an increase in anxiety-like behavior. These observations demonstrate that an embryonic exposure to an environmental compound appears to promote a reprogramming of brain development that correlates with transgenerational sex-specific alterations in the brain transcriptomes and behavior. Observations are discussed in regards to environmental and transgenerational influences on the etiology of brain disease.

Remodeling the blood–brain barrier microenvironment by natural products for brain tumor therapy

Institute of Scientific and Technical Information of China (English)

Xiao Zhao; Rujing Chen; Mei Liu; Jianfang Feng; Jun Chen; Kaili Hu

2017-01-01

Brain tumor incidence shows an upward trend in recent years; brain tumors account for 5% of adult tumors, while in children, this figure has increased to 70%. Moreover, 20%–30% of malignant tumors will eventually metastasize into the brain. Both benign and malignant tumors can cause an increase in intracranial pressure and brain tissue compression, leading to central nervous system(CNS) damage which endangers the patients’ lives. Despite the many approaches to treating brain tumors and the progress that has been made, only modest gains in survival time of brain tumor patients have been achieved. At present, chemotherapy is the treatment of choice for many cancers, but the special structure of the blood–brain barrier(BBB) limits most chemotherapeutic agents from passing through the BBB and penetrating into tumors in the brain. The BBB microenvironment contains numerous cell types, including endothelial cells, astrocytes, peripheral cells and microglia, and extracellular matrix(ECM). Many chemical components of natural products are reported to regulate the BBB microenvironment near brain tumors and assist in their treatment. This review focuses on the composition and function of the BBB microenvironment under both physiological and pathological conditions, and the current research progress in regulating the BBB microenvironment by natural products to promote the treatment of brain tumors.

Brain Perfusion Changes in Intracerebral Hemorrhage

International Nuclear Information System (INIS)

Mititelu, R.; Mazilu, C.; Ghita, S.; Rimbu, A.; Marinescu, G.; Codorean, I.; Bajenaru, O.

2006-01-01

Full text: Purpose: Despite the latest advances in medical treatment and neuro critical care, patients suffering spontaneous intracerebral hemorrhage (SICH) still have a very poor prognosis, with a greater mortality and larger neurological deficits at the survivors than for ischemic stroke. Many authors have shown that there are many mechanisms involved in the pathology of SICH: edema, ischemia, inflammation, apoptosis. All of these factors are affecting brain tissue surrounding hematoma and are responsible of the progressive neurological deterioration; most of these damages are not revealed by anatomical imaging techniques. The aim of our study was to asses the role of brain perfusion SPECT in demonstrating perfusion changes in SICH patients. Method: 17 SICH pts were studied. All pts underwent same day CT and brain SPECT with 99mTcHMPAO, 24h-5d from onset of stroke. Results: 14/17 pts showed a larger perfusion defect than expected after CT. In 2 pts hematoma diameter was comparable on CT and SPECT; 1pt had quasinormal aspect of SPECT study. In pts with larger defects, SPECT revealed a large cold spot with similar size compared with CT, and a surrounding hypo perfused area. 6/17 pts revealed cortical hyper perfusion adjacent to hypo perfused area and corresponding to a normal-appearing brain tissue on CT. In 3 pts we found crossed cerebellar diaskisis.In 2 pts we found cortical hypo perfused area in the contralateral cortex, with normal appearing brain tissue on CT. Conclusions: Brain perfusion SPECT revealed different types of perfusion changes in the brain tissue surrounding hematoma. These areas contain viable brain tissue that may be a target for future ne uroprotective strategies. Further studies are definitely required to demonstrate prognostic significance of these changes, but we can conclude that brain perfusion SPECT can play an important role in SICH, by early demonstrating functional changes responsible of clinical deterioration, thus allowing prompt

Towards Developmental Connectomics of the Human Brain

Directory of Open Access Journals (Sweden)

Miao eCao

2016-03-01

Full Text Available Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and

Toward Developmental Connectomics of the Human Brain.

Science.gov (United States)

Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental

Toward Developmental Connectomics of the Human Brain

Science.gov (United States)

Cao, Miao; Huang, Hao; Peng, Yun; Dong, Qi; He, Yong

2016-01-01

Imaging connectomics based on graph theory has become an effective and unique methodological framework for studying structural and functional connectivity patterns of the developing brain. Normal brain development is characterized by continuous and significant network evolution throughout infancy, childhood, and adolescence, following specific maturational patterns. Disruption of these normal changes is associated with neuropsychiatric developmental disorders, such as autism spectrum disorders or attention-deficit hyperactivity disorder. In this review, we focused on the recent progresses regarding typical and atypical development of human brain networks from birth to early adulthood, using a connectomic approach. Specifically, by the time of birth, structural networks already exhibit adult-like organization, with global efficient small-world and modular structures, as well as hub regions and rich-clubs acting as communication backbones. During development, the structure networks are fine-tuned, with increased global integration and robustness and decreased local segregation, as well as the strengthening of the hubs. In parallel, functional networks undergo more dramatic changes during maturation, with both increased integration and segregation during development, as brain hubs shift from primary regions to high order functioning regions, and the organization of modules transitions from a local anatomical emphasis to a more distributed architecture. These findings suggest that structural networks develop earlier than functional networks; meanwhile functional networks demonstrate more dramatic maturational changes with the evolution of structural networks serving as the anatomical backbone. In this review, we also highlighted topologically disorganized characteristics in structural and functional brain networks in several major developmental neuropsychiatric disorders (e.g., autism spectrum disorders, attention-deficit hyperactivity disorder and developmental

A whole-brain computational modeling approach to explain the alterations in resting-state functional connectivity during progression of Alzheimer's disease

Directory of Open Access Journals (Sweden)

Murat Demirtaş

2017-01-01

Full Text Available Alzheimer's disease (AD is the most common dementia with dramatic consequences. The research in structural and functional neuroimaging showed altered brain connectivity in AD. In this study, we investigated the whole-brain resting state functional connectivity (FC of the subjects with preclinical Alzheimer's disease (PAD, mild cognitive impairment due to AD (MCI and mild dementia due to Alzheimer's disease (AD, the impact of APOE4 carriership, as well as in relation to variations in core AD CSF biomarkers. The synchronization in the whole-brain was monotonously decreasing during the course of the disease progression. Furthermore, in AD patients we found widespread significant decreases in functional connectivity (FC strengths particularly in the brain regions with high global connectivity. We employed a whole-brain computational modeling approach to study the mechanisms underlying these alterations. To characterize the causal interactions between brain regions, we estimated the effective connectivity (EC in the model. We found that the significant EC differences in AD were primarily located in left temporal lobe. Then, we systematically manipulated the underlying dynamics of the model to investigate simulated changes in FC based on the healthy control subjects. Furthermore, we found distinct patterns involving CSF biomarkers of amyloid-beta (Aβ1−42 total tau (t-tau and phosphorylated tau (p-tau. CSF Aβ1−42 was associated to the contrast between healthy control subjects and clinical groups. Nevertheless, tau CSF biomarkers were associated to the variability in whole-brain synchronization and sensory integration regions. These associations were robust across clinical groups, unlike the associations that were found for CSF Aβ1−42. APOE4 carriership showed no significant correlations with the connectivity measures.

The Brain as a Sensory-Motor Task Machine: What Did Visual Deprivation and Visual Substitution Studies Teach us About Brain (re-Organization

Directory of Open Access Journals (Sweden)

Amir Amedi

2011-10-01

Full Text Available About one-quarter of our brain “real estate” is devoted to the processing of vision. So what happens to this vast “vision” part of the brain when no visual input is received? We are working with novel high-tech multisensory ‘glasses’ that convert visual information from a tiny video camera into sensory signals that the blind can interpret. In this talk I will mainly highlight work done using The vOICe algorithm (Meijer et al 1992. We have devised a training program which teaches blind individuals to use such a device. Following approximately 30 hours of training, congenitally blind individuals can use this device to recognize what and where various objects are, for instance, within a room (like a chair, glass, and even people and their body posture; eg, see http://brain.huji.ac.il/press.asp. Additional training is given specifically for encouraging free “visual” orientation enabling blind individuals to walk in corridors while avoiding obstacles and applying hand-“eye” coordination (eg, playing bowling. A main focus of the project is using this unique “set-up” to study brain organization and brain flexibility. For example, we are elucidating how the subjects' brains use preserved functions on one hand and on the other hand, reorganize to enable to process this new sensory language (eg, See Amedi et al Nature Neurosience 2007; Stiem-Amit et al 2011; Reich et al 2011. I will also focus on novel spectral analysis approaches to study large-scale brain dynamics and to look into the binding problem: how we integrate information into a coherent percept, an old question in neuroscience which has relatively poor answers, especially in humans. On the rehabilitation front, we have demonstrated that visual training can create massive adult plasticity in the ‘visual’ cortex to process functions like recognizing objects and localizing where they are located, much like the original division of labor in the visual system in which the

Switches for multiple behavioral states and a viral-based approach to non-invasive whole-brain cargo delivery (Conference Presentation)

Science.gov (United States)

Gradinaru, Viviana

2017-05-01

Over the past years we have worked on: (1) Viral-based approaches to non-invasive whole-brain cargo delivery: Genetically-encoded tools that can be used to visualize, monitor, and modulate mammalian neurons are revolutionizing neuroscience. These tools are particularly powerful in rodents and invertebrate models where intersectional transgenic strategies are available to restrict their expression to defined cell populations. However, use of genetic tools in non-transgenic animals is often hindered by the lack of vectors capable of safe, efficient, and specific delivery to the desired cellular targets. To begin to address these challenges, we have developed an in vivo Cre-based selection platform (CREATE) for identifying adeno-associated viruses (AAVs) that more efficiently transduce genetically defined cell populations. Our platform's novelty and power arises from the additional selective pressure imparted by a recovery step that amplifies only those capsid variants that have functionally transduced a genetically-defined, Cre-expressing target cell population. The Cre-dependent capsid recovery works within heterogeneous tissue samples without the need for additional steps such as selective capsid recovery approaches that require cell sorting or secondary adenovirus infection. As a first test of the CREATE platform, we selected for viruses that transduced the brain after intravascular delivery and found a novel vector, AAV-PHP.B, that is 40- to 90-fold more efficient at transducing the brain than the current standard, AAV9. AAV-PHP.B transduces most neuronal types and glia across the brain. We also demonstrate here how whole-body tissue clearing can facilitate transduction maps of systemically delivered genes. Since CNS disorders are notoriously challenging due to the restrictive nature of the blood brain barrier our discovery that recombinant vectors can be engineered to overcome this barrier is enabling for the whole field. With the exciting advances in gene

Brain fat embolism

International Nuclear Information System (INIS)

Sugiura, Yoshihiro; Kawamura, Yasutaka; Suzuki, Hisato; Yanagimoto, Masahiro; Goto, Yukio

1994-01-01

Recently CT and MR imaging have demonstrated that cerebral edema is present in cases of fat embolism syndrome. To simulate this we have made a model of brain-fat embolism in rats under MR imaging. In 20 rats, we did intravenous injection of heparinized blood, 1.5 ml·kg -1 taken from femoral bone marrow cavity. Twenty four hours after the injection, we examined the MR images (1.5 tesla, spin-echo method) of brains and histologic findings of brains and lungs were obtained. In 5 of 20 rats, high signal intensity on T2-weighted images and low signal intensity on T1-weighted images were observed in the area of the unilateral cerebral cortex or hippocampus. These findings showed edema of the brains. They disappeared, however, one week later. Histologic examinations showed massive micro-fat emboli in capillaries of the deep cerebral cortex and substantia nigra, but no edematous findings of the brain were revealed in HE staining. In pulmonary arteries, we also found large fat emboli. We conclude that our model is a useful one for the study of brain fat embolism. (author)

Brain mesenchymal stem cells: The other stem cells of the brain?

Science.gov (United States)

Appaix, Florence; Nissou, Marie-France; van der Sanden, Boudewijn; Dreyfus, Matthieu; Berger, François; Issartel, Jean-Paul; Wion, Didier

2014-04-26

Multipotent mesenchymal stromal cells (MSC), have the potential to differentiate into cells of the mesenchymal lineage and have non-progenitor functions including immunomodulation. The demonstration that MSCs are perivascular cells found in almost all adult tissues raises fascinating perspectives on their role in tissue maintenance and repair. However, some controversies about the physiological role of the perivascular MSCs residing outside the bone marrow and on their therapeutic potential in regenerative medicine exist. In brain, perivascular MSCs like pericytes and adventitial cells, could constitute another stem cell population distinct to the neural stem cell pool. The demonstration of the neuronal potential of MSCs requires stringent criteria including morphological changes, the demonstration of neural biomarkers expression, electrophysiological recordings, and the absence of cell fusion. The recent finding that brain cancer stem cells can transdifferentiate into pericytes is another facet of the plasticity of these cells. It suggests that the perversion of the stem cell potential of pericytes might play an even unsuspected role in cancer formation and tumor progression.

Trojan Horse Transit Contributes to Blood-Brain Barrier Crossing of a Eukaryotic Pathogen.

Science.gov (United States)

Santiago-Tirado, Felipe H; Onken, Michael D; Cooper, John A; Klein, Robyn S; Doering, Tamara L

2017-01-31

The blood-brain barrier (BBB) protects the central nervous system (CNS) by restricting the passage of molecules and microorganisms. Despite this barrier, however, the fungal pathogen Cryptococcus neoformans invades the brain, causing a meningoencephalitis that is estimated to kill over 600,000 people annually. Cryptococcal infection begins in the lung, and experimental evidence suggests that host phagocytes play a role in subsequent dissemination, although this role remains ill defined. Additionally, the disparate experimental approaches that have been used to probe various potential routes of BBB transit make it impossible to assess their relative contributions, confounding any integrated understanding of cryptococcal brain entry. Here we used an in vitro model BBB to show that a "Trojan horse" mechanism contributes significantly to fungal barrier crossing and that host factors regulate this process independently of free fungal transit. We also, for the first time, directly imaged C. neoformans-containing phagocytes crossing the BBB, showing that they do so via transendothelial pores. Finally, we found that Trojan horse crossing enables CNS entry of fungal mutants that cannot otherwise traverse the BBB, and we demonstrate additional intercellular interactions that may contribute to brain entry. Our work elucidates the mechanism of cryptococcal brain invasion and offers approaches to study other neuropathogens. The fungal pathogen Cryptococcus neoformans invades the brain, causing a meningoencephalitis that kills hundreds of thousands of people each year. One route that has been proposed for this brain entry is a Trojan horse mechanism, whereby the fungus crosses the blood-brain barrier (BBB) as a passenger inside host phagocytes. Although indirect experimental evidence supports this intriguing mechanism, it has never been directly visualized. Here we directly image Trojan horse transit and show that it is regulated independently of free fungal entry, contributes

A Methodological Demonstration of Set-theoretical Approach to Social Media Maturity Models Using Necessary Condition Analysis

DEFF Research Database (Denmark)

Lasrado, Lester Allan; Vatrapu, Ravi; Andersen, Kim Normann

2016-01-01

Despite being widely accepted and applied across research domains, maturity models have been criticized for lacking academic rigor, especially methodologically rigorous and empirically grounded or tested maturity models are quite rare. Attempting to close this gap, we adopt a set-theoretic approach...... and evaluate some of arguments presented by previous conceptual focused social media maturity models....... by applying the Necessary Condition Analysis (NCA) technique to derive maturity stages and stage boundaries conditions. The ontology is to view stages (boundaries) in maturity models as a collection of necessary condition. Using social media maturity data, we demonstrate the strength of our approach...

BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment.

Science.gov (United States)

Kawahara, Jeremy; Brown, Colin J; Miller, Steven P; Booth, Brian G; Chau, Vann; Grunau, Ruth E; Zwicker, Jill G; Hamarneh, Ghassan

2017-02-01

We propose BrainNetCNN, a convolutional neural network (CNN) framework to predict clinical neurodevelopmental outcomes from brain networks. In contrast to the spatially local convolutions done in traditional image-based CNNs, our BrainNetCNN is composed of novel edge-to-edge, edge-to-node and node-to-graph convolutional filters that leverage the topological locality of structural brain networks. We apply the BrainNetCNN framework to predict cognitive and motor developmental outcome scores from structural brain networks of infants born preterm. Diffusion tensor images (DTI) of preterm infants, acquired between 27 and 46 weeks gestational age, were used to construct a dataset of structural brain connectivity networks. We first demonstrate the predictive capabilities of BrainNetCNN on synthetic phantom networks with simulated injury patterns and added noise. BrainNetCNN outperforms a fully connected neural-network with the same number of model parameters on both phantoms with focal and diffuse injury patterns. We then apply our method to the task of joint prediction of Bayley-III cognitive and motor scores, assessed at 18 months of age, adjusted for prematurity. We show that our BrainNetCNN framework outperforms a variety of other methods on the same data. Furthermore, BrainNetCNN is able to identify an infant's postmenstrual age to within about 2 weeks. Finally, we explore the high-level features learned by BrainNetCNN by visualizing the importance of each connection in the brain with respect to predicting the outcome scores. These findings are then discussed in the context of the anatomy and function of the developing preterm infant brain. Copyright © 2016 Elsevier Inc. All rights reserved.

Brain-inspired Stochastic Models and Implementations

KAUST Repository

Al-Shedivat, Maruan

2015-05-12

One of the approaches to building artificial intelligence (AI) is to decipher the princi- ples of the brain function and to employ similar mechanisms for solving cognitive tasks, such as visual perception or natural language understanding, using machines. The recent breakthrough, named deep learning, demonstrated that large multi-layer networks of arti- ficial neural-like computing units attain remarkable performance on some of these tasks. Nevertheless, such artificial networks remain to be very loosely inspired by the brain, which rich structures and mechanisms may further suggest new algorithms or even new paradigms of computation. In this thesis, we explore brain-inspired probabilistic mechanisms, such as neural and synaptic stochasticity, in the context of generative models. The two questions we ask here are: (i) what kind of models can describe a neural learning system built of stochastic components? and (ii) how can we implement such systems e ̆ciently? To give specific answers, we consider two well known models and the corresponding neural architectures: the Naive Bayes model implemented with a winner-take-all spiking neural network and the Boltzmann machine implemented in a spiking or non-spiking fashion. We propose and analyze an e ̆cient neuromorphic implementation of the stochastic neu- ral firing mechanism and study the e ̄ects of synaptic unreliability on learning generative energy-based models implemented with neural networks.

The impact of dietary isoflavonoids on malignant brain tumors

International Nuclear Information System (INIS)

Sehm, Tina; Fan, Zheng; Weiss, Ruth; Schwarz, Marc; Engelhorn, Tobias; Hore, Nirjhar; Doerfler, Arnd; Buchfelder, Michael; Eyüpoglu, IIker Y; Savaskan, Nic E

2014-01-01

Poor prognosis and limited therapeutic options render malignant brain tumors one of the most devastating diseases in clinical medicine. Current treatment strategies attempt to expand the therapeutic repertoire through the use of multimodal treatment regimens. It is here that dietary fibers have been recently recognized as a supportive natural therapy in augmenting the body's response to tumor growth. Here, we investigated the impact of isoflavonoids on primary brain tumor cells. First, we treated glioma cell lines and primary astrocytes with various isoflavonoids and phytoestrogens. Cell viability in a dose-dependent manner was measured for biochanin A (BCA), genistein (GST), and secoisolariciresinol diglucoside (SDG). Dose–response action for the different isoflavonoids showed that BCA is highly effective on glioma cells and nontoxic for normal differentiated brain tissues. We further investigated BCA in ex vivo and in vivo experimentations. Organotypic brain slice cultures were performed and treated with BCA. For in vivo experiments, BCA was intraperitoneal injected in tumor-implanted Fisher rats. Tumor size and edema were measured and quantified by magnetic resonance imaging (MRI) scans. In vascular organotypic glioma brain slice cultures (VOGIM) we found that BCA operates antiangiogenic and neuroprotective. In vivo MRI scans demonstrated that administered BCA as a monotherapy was effective in reducing significantly tumor-induced brain edema and showed a trend for prolonged survival. Our results revealed that dietary isoflavonoids, in particular BCA, execute toxicity toward glioma cells, antiangiogenic, and coevally neuroprotective properties, and therefore augment the range of state-of-the-art multimodal treatment approach

A Bayesian Model of Category-Specific Emotional Brain Responses

Science.gov (United States)

Wager, Tor D.; Kang, Jian; Johnson, Timothy D.; Nichols, Thomas E.; Satpute, Ajay B.; Barrett, Lisa Feldman

2015-01-01

Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories—fear, anger, disgust, sadness, or happiness—is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches. PMID:25853490

Management of Brain Metastases.

Science.gov (United States)

Jeyapalan, Suriya A.; Batchelor, Tracy

2004-07-01

Advances in neurosurgery and the development of stereotactic radiosurgery have expanded treatment options available for patients with brain metastases. However, despite several randomized clinical trials and multiple uncontrolled studies, there is not a uniform consensus on the best treatment strategy for all patients with brain metastases. The heterogeneity of this patient population in terms of functional status, types of underlying cancers, status of systemic disease control, and number and location of brain metastases make such consensus difficult. Nevertheless, in certain situations, there is Class I evidence that supports one approach or another. The primary objectives in the management of this patient population include improved duration and quality of survival. Very few patients achieve long-term survival after the diagnosis of a brain metastasis.

Tailoring Lipid and Polymeric Nanoparticles as siRNA Carriers towards the Blood-Brain Barrier - from Targeting to Safe Administration.

Science.gov (United States)

Gomes, Maria João; Fernandes, Carlos; Martins, Susana; Borges, Fernanda; Sarmento, Bruno

2017-03-01

Blood-brain barrier is a tightly packed layer of endothelial cells surrounding the brain that acts as the main obstacle for drugs enter the central nervous system (CNS), due to its unique features, as tight junctions and drug efflux systems. Therefore, since the incidence of CNS disorders is increasing worldwide, medical therapeutics need to be improved. Consequently, aiming to surpass blood-brain barrier and overcome CNS disabilities, silencing P-glycoprotein as a drug efflux transporter at brain endothelial cells through siRNA is considered a promising approach. For siRNA enzymatic protection and efficient delivery to its target, two different nanoparticles platforms, solid lipid (SLN) and poly-lactic-co-glycolic (PLGA) nanoparticles were used in this study. Polymeric PLGA nanoparticles were around 115 nm in size and had 50 % of siRNA association efficiency, while SLN presented 150 nm and association efficiency close to 52 %. Their surface was functionalized with a peptide-binding transferrin receptor, in a site-oriented manner confirmed by NMR, and their targeting ability against human brain endothelial cells was successfully demonstrated by fluorescence microscopy and flow cytometry. The interaction of modified nanoparticles with brain endothelial cells increased 3-fold compared to non-modified lipid nanoparticles, and 4-fold compared to non-modified PLGA nanoparticles, respectively. These nanosystems, which were also demonstrated to be safe for human brain endothelial cells, without significant cytotoxicity, bring a new hopeful breath to the future of brain diseases therapies.

The Effect of Group Works and Demonstrative Experiments Based on Conceptual Change Approach: Photosynthesis and Respiration

Science.gov (United States)

Cibik, Ayse Sert; Diken, Emine Hatun; Darcin, Emine Selcen

2008-01-01

The purpose of this study is to investigate the effect of the use of group works and demonstration experiments based on conceptual change approach in the elimination of misconception about the subject of photosynthesis and respiration in plants in pre-service science teachers. This study was conducted with 78 pre-service science teachers including…

The post-synaptic density of human postmortem brain tissues: an experimental study paradigm for neuropsychiatric illnesses.

Directory of Open Access Journals (Sweden)

Chang-Gyu Hahn

Full Text Available Recent molecular genetics studies have suggested various trans-synaptic processes for pathophysiologic mechanisms of neuropsychiatric illnesses. Examination of pre- and post-synaptic scaffolds in the brains of patients would greatly aid further investigation, yet such an approach in human postmortem tissue has yet to be tested. We have examined three methods using density gradient based purification of synaptosomes followed by detergent extraction (Method 1 and the pH based differential extraction of synaptic membranes (Methods 2 and 3. All three methods separated fractions from human postmortem brains that were highly enriched in typical PSD proteins, almost to the exclusion of pre-synaptic proteins. We examined these fractions using electron microscopy (EM and verified the integrity of the synaptic membrane and PSD fractions derived from human postmortem brain tissues. We analyzed protein composition of the PSD fractions using two dimensional liquid chromatography tandem mass spectrometry (2D LC-MS/MS and observed known PSD proteins by mass spectrometry. Immunoprecipitation and immunoblot studies revealed that expected protein-protein interactions and certain posttranscriptional modulations were maintained in PSD fractions. Our results demonstrate that PSD fractions can be isolated from human postmortem brain tissues with a reasonable degree of integrity. This approach may foster novel postmortem brain research paradigms in which the stoichiometry and protein composition of specific microdomains are examined.

Mechanistic positron emission tomography studies: demonstration of a deuterium isotope effect in the monoamine oxidase-catalyzed binding of (/sup 11/C)L-deprenyl in living baboon brain

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Fowler, J.S.; Wolf, A.P.; MacGregor, R.R.; Dewey, S.L.; Logan, J.; Schlyer, D.J.; Langstrom, B.

1988-11-01

The application of positron emission tomography (PET) to the study of biochemical transformations in the living human and animal body requires the development of highly selective radiotracers whose concentrations in tissue provide a record of a discrete metabolic process. L-N-(11C-methyl)Deprenyl ((11C)L-deprenyl), a suicide inactivator of monoamine oxidase (MAO) type B, has been developed as a radiotracer for mapping MAO B in the living human and animal brain. In this investigation, (11C)L-deprenyl (1) and (11C)L-deprenyl-alpha, alpha-2H2 (2) have been compared in three different baboons by PET measurement of carbon-11 uptake and retention in the brain and the measurement of the amount of unchanged tracer in the arterial plasma over a 90-min time interval. For one baboon, N-(11C-methyl-2H3)L-deprenyl (3) was also studied. Kinetic parameters calculated using a three-compartment model revealed a deuterium isotope effect of 3.8 +/- 1.1. Comparison of the two tracers (1 and 2) in mouse brain demonstrated that deuterium substitution significantly reduced the amount of radioactivity bound to protein. HPLC and GLC analysis of the soluble radioactivity in mouse brain after injection of (11C)L-deprenyl showed the presence of (11C)methamphetamine as a major product along with unidentified labeled products. Sodium dodecyl sulfate-polyacrylamide electrophoresis with carbon-14-labeled L-deprenyl showed that a protein of molecular weight 58,000 was labeled. These results establish that MAO-catalyzed cleavage of the alpha carbon-hydrogen bond on the propargyl group is the rate limiting (or a major rate contributing) step in the retention of carbon-11 in brain and that the in vivo detection of labeled products in brain after the injection of (11C)L-deprenyl provides a record of MAO activity.

A brain worth keeping? Waste, value and time in contemporary brain banking.

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Erslev, Thomas

2018-02-01

If a temporal rather than spatial concept of waste is adopted, novel categories emerge which are useful for identifying and understanding logics of temporality at play in determining what is kept in contemporary brain banks, and reveal that brain banks are constituted by more than stored materials. First, I apply the categories analytically on a recent UK brain banking discussion among professionals. This analysis highlights the importance of data in brain banks, as well as the centrality of ideas about pasts and futures in the discussions. Secondly, I investigate the case of a seven decades old, Danish brain bank which had been reduced to its physically stored material for 24 years, before being reinstituted in 2006. This case demonstrates the importance of material and conceptual infrastructures that co-constitute a collection, as they make up an experimental system that is crucial to maintaining the collection's continued relevance and usefulness as a scientific institution. Copyright © 2017 Elsevier Ltd. All rights reserved.

CT evaluation of cystic brain disease

International Nuclear Information System (INIS)

Kim, Joon Woo; Lee, Jin Woo; Joo, Yang Goo; Kim, Hong; Zeon, Seok Kil; Suh, Soo Jhi

1987-01-01

We retrospectively analysed CT findings of 47 cystic brain lesions of 44 patients, in which operation, biopsy or follow-up study was needed for their final diagnosis. The results were as follows: 1. The etiologic diseases of cystic brain lesions were 15 cases of brain abscess, 9 cases of astrocytoma, 5 cases of glioblastoma multiforme, 3 cases of meningioma, 5 cases of craniopharyngioma, 1 case of hemangioblastoma, 2 cases of dermoid cyst and 4 cases of metastasis. 2. We analyses the cystic lesions in view of their number, location, shape, perifocal edema, mass effect, wall and its thickness, evenness and characteristics of their inner and outer surfaces, mural nodule, calcification and contrast enhancement. a. 13.3% of brain abscess and 75% of metastases were multiple in number, but the remainder showed single lesion. b. The shape of cystic lesions were round or ovoid in 68%, lobulated in 8.5% and irregular in 23.5%, and no demonstrable difference of shape were noticed in different disease. c. In brain abscess, the wall of cystic lesions tend to be thin, even and smooth in inner surface, but the outer surfaces were equally smooth or irregular. d. Mural nodules were found in nearly half of the cases of astrocytoma, glioblastoma multiforme, metastasis and hemangioblastoma, but the brain abscess and dermoid cyst contained no mural nodule. e. Meningiomas were found to be attached to dura mater and showed thickening of the inner table of adjacent skull or of the falx. f. The presence of preceding infectious disease may be helpful in the diagnosis of brain abscess, but in 20% there were no demonstrable preceding infection. g. Lung cancer was confirmed as primary site in two of the cystic metastatic disease, but other 2 cases showed no demonstrable primary malignancy

CT evaluation of cystic brain disease

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Kim, Joon Woo; Lee, Jin Woo; Joo, Yang Goo; Kim, Hong; Zeon, Seok Kil; Suh, Soo Jhi [Keimyung University, School of Medicine, Daegu (Korea, Republic of)

1987-10-15

We retrospectively analysed CT findings of 47 cystic brain lesions of 44 patients, in which operation, biopsy or follow-up study was needed for their final diagnosis. The results were as follows: 1. The etiologic diseases of cystic brain lesions were 15 cases of brain abscess, 9 cases of astrocytoma, 5 cases of glioblastoma multiforme, 3 cases of meningioma, 5 cases of craniopharyngioma, 1 case of hemangioblastoma, 2 cases of dermoid cyst and 4 cases of metastasis. 2. We analyses the cystic lesions in view of their number, location, shape, perifocal edema, mass effect, wall and its thickness, evenness and characteristics of their inner and outer surfaces, mural nodule, calcification and contrast enhancement. a. 13.3% of brain abscess and 75% of metastases were multiple in number, but the remainder showed single lesion. b. The shape of cystic lesions were round or ovoid in 68%, lobulated in 8.5% and irregular in 23.5%, and no demonstrable difference of shape were noticed in different disease. c. In brain abscess, the wall of cystic lesions tend to be thin, even and smooth in inner surface, but the outer surfaces were equally smooth or irregular. d. Mural nodules were found in nearly half of the cases of astrocytoma, glioblastoma multiforme, metastasis and hemangioblastoma, but the brain abscess and dermoid cyst contained no mural nodule. e. Meningiomas were found to be attached to dura mater and showed thickening of the inner table of adjacent skull or of the falx. f. The presence of preceding infectious disease may be helpful in the diagnosis of brain abscess, but in 20% there were no demonstrable preceding infection. g. Lung cancer was confirmed as primary site in two of the cystic metastatic disease, but other 2 cases showed no demonstrable primary malignancy.

Evolutionarily Conserved Roles for Blood-Brain Barrier Xenobiotic Transporters in Endogenous Steroid Partitioning and Behavior.

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Hindle, Samantha J; Munji, Roeben N; Dolghih, Elena; Gaskins, Garrett; Orng, Souvinh; Ishimoto, Hiroshi; Soung, Allison; DeSalvo, Michael; Kitamoto, Toshihiro; Keiser, Michael J; Jacobson, Matthew P; Daneman, Richard; Bainton, Roland J

2017-10-31

Central nervous system (CNS) chemical protection depends upon discrete control of small-molecule access by the blood-brain barrier (BBB). Curiously, some drugs cause CNS side-effects despite negligible transit past the BBB. To investigate this phenomenon, we asked whether the highly BBB-enriched drug efflux transporter MDR1 has dual functions in controlling drug and endogenous molecule CNS homeostasis. If this is true, then brain-impermeable drugs could induce behavioral changes by affecting brain levels of endogenous molecules. Using computational, genetic, and pharmacologic approaches across diverse organisms, we demonstrate that BBB-localized efflux transporters are critical for regulating brain levels of endogenous steroids and steroid-regulated behaviors (sleep in Drosophila and anxiety in mice). Furthermore, we show that MDR1-interacting drugs are associated with anxiety-related behaviors in humans. We propose a general mechanism for common behavioral side effects of prescription drugs: pharmacologically challenging BBB efflux transporters disrupts brain levels of endogenous substrates and implicates the BBB in behavioral regulation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Concurrent whole brain radiotherapy and bortezomib for brain metastasis

International Nuclear Information System (INIS)

Lao, Christopher D; Hamstra, Daniel; Lawrence, Theodore; Hayman, James; Redman, Bruce G; Friedman, Judah; Tsien, Christina I; Normolle, Daniel P; Chapman, Christopher; Cao, Yue; Lee, Oliver; Schipper, Matt; Van Poznak, Catherine

2013-01-01

Survival of patients with brain metastasis particularly from historically more radio-resistant malignancies remains dismal. A phase I study of concurrent bortezomib and whole brain radiotherapy was conducted to determine the tolerance and safety of this approach in patients with previously untreated brain metastasis. A phase I dose escalation study evaluated the safety of bortezomib (0.9, 1.1, 1.3, 1.5, and 1.7 mg/m 2 ) given on days 1, 4, 8 and 11 of whole brain radiotherapy. Patients with confirmed brain metastasis were recruited for participation. The primary endpoint was the dose-limiting toxicity, defined as any ≥ grade 3 non-hematologic toxicity or grade ≥ 4 hematologic toxicity from the start of treatment to one month post irradiation. Time-to-Event Continual Reassessment Method (TITE-CRM) was used to determine dose escalation. A companion study of brain diffusion tensor imaging MRI was conducted on a subset of patients to assess changes in the brain that might predict delayed cognitive effects. Twenty-four patients were recruited and completed the planned therapy. Patients with melanoma accounted for 83% of all participants. The bortezomib dose was escalated as planned to the highest dose of 1.7 mg/m 2 /dose. No grade 4/5 toxicities related to treatment were observed. Two patients had grade 3 dose-limiting toxicities (hyponatremia and encephalopathy). A partial or minor response was observed in 38% of patients. Bortezomib showed greater demyelination in hippocampus-associated white matter structures on MRI one month after radiotherapy compared to patients not treated with bortezomib (increase in radial diffusivity +16.8% versus 4.8%; p = 0.0023). Concurrent bortezomib and whole brain irradiation for brain metastasis is well tolerated at one month follow-up, but MRI changes that have been shown to predict delayed cognitive function can be detected within one month of treatment

Cholecystokinin receptors: Biochemical demonstration and autoradiographical localization in rat brain and pancreas using [3H] cholecystokinin8 as radioligand

International Nuclear Information System (INIS)

Van Dijk, A.; Richards, J.G.; Trzeciak, A.; Gillessen, D.; Moehler, H.

1984-01-01

Since cholecystokinin8 (CCK8) seems to be the physiological ligand of CCK receptors in the brain, it would be the most suitable probe for the characterization of CCK receptors in radioligand binding studies. [ 3 H]CCK8 was synthetized with a specific radioactivity sufficient for the detection of high affinity binding sites. [ 3 H]CCK8 binds saturably and reversibly to distinct sites in rat brain and pancreas with nanomolar affinity. While the C-terminal tetrapeptide of CCK is the minimal structure required for nanomolar affinity in the brain, the entire octapeptide sequence is required for binding affinity in pancreas. Desulfated CCK8 and several gastrin-I peptides, which are likewise unsulfated, show virtually no affinity to the binding sites in pancreas but high affinity in cerebral cortex. The ligand specificity of the CCK peptides corresponds to their electrophysiological potency in the brain and their stimulation of secretion in pancreas, respectively. Autoradiographically, high densities of [ 3 H]CCK8 binding sites were found in cerebral cortex and olfactory bulb, medium levels in nucleus accumbens, hippocampus, dentate gyrus, and striatum with virtually no labeling in cerebellum. This pattern is similar to the distribution of CCK-like immunoreactivity in the brain. In pancreas, equally high levels of [ 3 H]CCK8 labeling were found in the exocrine and endocrine region. [ 3 H]CCK8 binding sites differ from those identified previously with [ 125 I]Bolton-Hunter-CCK33 by their sensitivity to guanyl nucleotides in the brain, their ion dependency in the brain, and pancreas, and their different autoradiographical localization in some parts of the brain. The distribution of CCK binding sites labeled with [ 3 H]CCK8 appears to correlate better with the CCK immunoreactivity than those labeled with [ 125 I]Bolton-Hunter-CCK33. Thus, [ 3 H]CCK8 appears to be the radioligand of choice for the investigation of CCK receptors

Anticipation-related brain connectivity in bipolar and unipolar depression: a graph theory approach.

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Manelis, Anna; Almeida, Jorge R C; Stiffler, Richelle; Lockovich, Jeanette C; Aslam, Haris A; Phillips, Mary L

2016-09-01

loss anticipation was characterized by denser top-down fronto-striatal and fronto-parietal connectivity in healthy control subjects, by bottom-up striatal-frontal connectivity in MDD, and by sparse connectivity lacking fronto-striatal connections in BDD. Win anticipation was characterized by dense connectivity of medial frontal with striatal and lateral frontal cortical regions in BDD, by sparser bottom-up striatum-medial frontal cortex connectivity in MDD, and by sparse connectivity in healthy control subjects. In summary, this is the first study to demonstrate that BDD and MDD with comparable levels of current depression differed from each other and healthy control subjects in density of connections, connectivity path length, and connectivity direction as a function of win or loss anticipation. These findings suggest that different neurobiological mechanisms may underlie aberrant anticipation processes in BDD and MDD, and that distinct therapeutic strategies may be required for these individuals to improve coping strategies during expectation of positive and negative outcomes. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Three-dimensional morphologic description and visualization of brain anatomy from MR images

International Nuclear Information System (INIS)

Kraske, W.; George, F.W.; Zee, C.S.; Colletti, P.M.; Halls, J.M.; Boswell, W.O.

1989-01-01

The USC VOXAR-MRI system incorporates MR tissue classification algorithms to provide dynamic three- dimensional volumetric visualization and discrimination of brain anatomy and pathology for precision diagnosis, staging, and treatment planning. The VOXAR-MRI approach to tissue classification employs the three-dimensional reconstruction of various intracranial features from gray-scale morphologic erosion and dilation (GMED)-derived skeleton representation of the MR acquisition. Case presentations include an array of VOXAR-MRI-demonstrated tumors, abscesses, hematomas, and other lesions

A Time-Frequency Approach to Feature Extraction for a Brain-Computer Interface with a Comparative Analysis of Performance Measures

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T. M. McGinnity

2005-11-01

Full Text Available The paper presents an investigation into a time-frequency (TF method for extracting features from the electroencephalogram (EEG recorded from subjects performing imagination of left- and right-hand movements. The feature extraction procedure (FEP extracts frequency domain information to form features whilst time-frequency resolution is attained by localising the fast Fourier transformations (FFTs of the signals to specific windows localised in time. All features are extracted at the rate of the signal sampling interval from a main feature extraction (FE window through which all data passes. Subject-specific frequency bands are selected for optimal feature extraction and intraclass variations are reduced by smoothing the spectra for each signal by an interpolation (IP process. The TF features are classified using linear discriminant analysis (LDA. The FE window has potential advantages for the FEP to be applied in an online brain-computer interface (BCI. The approach achieves good performance when quantified by classification accuracy (CA rate, information transfer (IT rate, and mutual information (MI. The information that these performance measures provide about a BCI system is analysed and the importance of this is demonstrated through the results.

Measurements of brain microstructure and connectivity with diffusion MRI

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Ching-Po Lin

2011-12-01

Full Text Available By probing direction-dependent diffusivity of water molecules, diffusion MRI has shown its capability to reflect the microstructural tissue status and to estimate the neural orientation and pathways in the living brain. This approach has supplied novel insights into in-vivo human brain connections. By detecting the connection patterns, anatomical architecture and structural integrity between cortical regions or subcortical nuclei in the living human brain can be easily identified. It thus opens a new window on brain connectivity studies and disease processes. During the past years, there is a growing interest in exploring the connectivity patterns of the human brain. Specifically, the utilities of noninvasive neuroimaging data and graph theoretical analysis have provided important insights into the anatomical connections and topological pattern of human brain structural networks in vivo. Here, we review the progress of this important technique and the recent methodological and application studies utilizing graph theoretical approaches on brain structural networks with structural MRI and diffusion MRI.

Specific binding of atrial natriuretic factor in brain microvessels

International Nuclear Information System (INIS)

Chabrier, P.E.; Roubert, P.; Braquet, P.

1987-01-01

Cerebral capillaries constitute the blood-brain barrier. Studies of specific receptors (neurotransmitters or hormones) located on this structure can be performed by means of radioligand-binding techniques on isolated brain microvessels. The authors examined on pure bovine cerebral microvessel preparations the binding of atrial natriuretic factor (ANF), using 125 I-labeled ANF. Saturation and competition experiments demonstrated the presence of a single class of ANF-binding sites with high affinity and with a binding capacity of 58 fmol/mg of protein. The binding of 125 I-labeled ANF to brain microvessels is specific, reversible, and time dependent, as is shown by association-dissociation experiments. The demonstration of specific ANF-binding sites on brain microvessels supposes a physiological role of ANF on brain microvasculature. The coexistence of ANF and angiotensin II receptors on this cerebrovascular tissue suggests that the two circulating peptides may act as mutual antagonists in the regulation of brain microcirculation and/or blood-brain barrier function

Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain

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Barrett, Lisa Feldman; Satpute, Ajay

2013-01-01

Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

Estrogenic effects of several BPA analogs in the developing zebrafish brain

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Joel eCano-Nicolau

2016-03-01

Full Text Available Important set of studies have demonstrated the endocrine disrupting activity of Bisphenol A (BPA. The present work aimed at defining estrogenic-like activity of several BPA structural analogs, including BPS, BPF, BPAF, and BPAP, on 4-day or 7-day post-fertilization (dpf zebrafish larva as an in vivo model. We measured the induction level of the estrogen-sensitive marker cyp19a1b gene (Aromatase B, expressed in the brain, using three different in situ/in vivo strategies: 1 Quantification of cyp19a1b transcripts using RT-qPCR in wild type 7-dpf larva brains exposed to bisphenols ; 2 Detection and distribution of cyp19a1b transcripts using in situ hybridization on 7-dpf brain sections (hypothalamus; and 3 Quantification of the cyp19a1b promoter activity in live cyp19a1b-GFP transgenic zebrafish (EASZY assay at 4-dpf larval stage. These three different experimental approaches demonstrated that BPS, BPF or BPAF exposure, similarly to BPA, significantly activates the expression of the estrogenic marker in the brain of developing zebrafish. In vitro experiments using both reporter gene assay in a glial cell context and competitive ligand binding assays strongly suggested that up-regulation of cyp19a1b is largely mediated by the zebrafish estrogen nuclear receptor alpha (zfERα. Importantly, and in contrast to other tested bisphenol A analogs, the bisphenol AP (BPAP did not show estrogenic activity in our model.

Even More Brain-Powered Science: Teaching and Learning with Discrepant Events. Brain-Powered Science Series

Science.gov (United States)

O'Brien, Thomas

2011-01-01

How can water and a penny demonstrate the power of mathematics and molecular theory? Do spelling and punctuation really matter to the human brain? The third of Thomas O'Brien's books designed for 5-12 grade science teachers, "Even More Brain-Powered Science" uses the questions above and 11 other inquiry-oriented discrepant events--experiments or…

A mathematical model of brain glucose homeostasis

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Kimura Hidenori

2009-11-01

Full Text Available Abstract Background The physiological fact that a stable level of brain glucose is more important than that of blood glucose suggests that the ultimate goal of the glucose-insulin-glucagon (GIG regulatory system may be homeostasis of glucose concentration in the brain rather than in the circulation. Methods In order to demonstrate the relationship between brain glucose homeostasis and blood hyperglycemia in diabetes, a brain-oriented mathematical model was developed by considering the brain as the controlled object while the remaining body as the actuator. After approximating the body compartmentally, the concentration dynamics of glucose, as well as those of insulin and glucagon, are described in each compartment. The brain-endocrine crosstalk, which regulates blood glucose level for brain glucose homeostasis together with the peripheral interactions among glucose, insulin and glucagon, is modeled as a proportional feedback control of brain glucose. Correlated to the brain, long-term effects of psychological stress and effects of blood-brain-barrier (BBB adaptation to dysglycemia on the generation of hyperglycemia are also taken into account in the model. Results It is shown that simulation profiles obtained from the model are qualitatively or partially quantitatively consistent with clinical data, concerning the GIG regulatory system responses to bolus glucose, stepwise and continuous glucose infusion. Simulations also revealed that both stress and BBB adaptation contribute to the generation of hyperglycemia. Conclusion Simulations of the model of a healthy person under long-term severe stress demonstrated that feedback control of brain glucose concentration results in elevation of blood glucose level. In this paper, we try to suggest that hyperglycemia in diabetes may be a normal outcome of brain glucose homeostasis.

Aluminum neurotoxicity in the rat brain

International Nuclear Information System (INIS)

Yumoto, S.; Ohashi, H.; Nagai, H.; Kakimi, S.; Ogawa, Y.; Iwata, Y.; Ishii, K.

1992-01-01

To investigate the etiology of Alzheimer's disease, we administered aluminum to healthy rats and examined the aluminum uptake in the brain and isolated brain cell nuclei by particle-induced X-ray emission (PIXE) analysis. Ten days after the last injection, Al was detected in the rat brain and in isolated brain cell nuclei by PIXE analysis. Al was also demonstrated in the brain after 15 months of oral aluminum administration. Moreover, Al was detected in the brain and isolated brain cell nuclei from the patients with Alzheimer's disease. Silver impregnation studies revealed that spines attached to the dendritic processes of cortical nerve cells decreased remarkably after aluminum administration. Electron microscopy revealed characteristic inclusion bodies in the hippocampal nerve cells 75 days after the injection. These morphological changes in the rat brain after the aluminum administration were similar to those reportedly observed in the brain of Alzheimer's disease patients. Our results indicate that Alzheimer's disease is caused by irreversible accumulation of aluminum in the brain, as well as in the nuclei of brain cells. (author)

Aluminum neurotoxicity in the rat brain

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Yumoto, S [Tokyo Univ. (Japan). Faculty of Medicine; Ohashi, H; Nagai, H; Kakimi, S; Ogawa, Y; Iwata, Y; Ishii, K

1993-12-31

To investigate the etiology of Alzheimer`s disease, we administered aluminum to healthy rats and examined the aluminum uptake in the brain and isolated brain cell nuclei by particle-induced X-ray emission (PIXE) analysis. Ten days after the last injection, Al was detected in the rat brain and in isolated brain cell nuclei by PIXE analysis. Al was also demonstrated in the brain after 15 months of oral aluminum administration. Moreover, Al was detected in the brain and isolated brain cell nuclei from the patients with Alzheimer`s disease. Silver impregnation studies revealed that spines attached to the dendritic processes of cortical nerve cells decreased remarkably after aluminum administration. Electron microscopy revealed characteristic inclusion bodies in the hippocampal nerve cells 75 days after the injection. These morphological changes in the rat brain after the aluminum administration were similar to those reportedly observed in the brain of Alzheimer`s disease patients. Our results indicate that Alzheimer`s disease is caused by irreversible accumulation of aluminum in the brain, as well as in the nuclei of brain cells. (author).

Segmentation of Brain Lesions in MRI and CT Scan Images: A Hybrid Approach Using k-Means Clustering and Image Morphology

Science.gov (United States)

Agrawal, Ritu; Sharma, Manisha; Singh, Bikesh Kumar

2018-04-01

Manual segmentation and analysis of lesions in medical images is time consuming and subjected to human errors. Automated segmentation has thus gained significant attention in recent years. This article presents a hybrid approach for brain lesion segmentation in different imaging modalities by combining median filter, k means clustering, Sobel edge detection and morphological operations. Median filter is an essential pre-processing step and is used to remove impulsive noise from the acquired brain images followed by k-means segmentation, Sobel edge detection and morphological processing. The performance of proposed automated system is tested on standard datasets using performance measures such as segmentation accuracy and execution time. The proposed method achieves a high accuracy of 94% when compared with manual delineation performed by an expert radiologist. Furthermore, the statistical significance test between lesion segmented using automated approach and that by expert delineation using ANOVA and correlation coefficient achieved high significance values of 0.986 and 1 respectively. The experimental results obtained are discussed in lieu of some recently reported studies.

Targeting Malignant Brain Tumors with Antibodies

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Rok Razpotnik

2017-09-01

Full Text Available Antibodies have been shown to be a potent therapeutic tool. However, their use for targeting brain diseases, including neurodegenerative diseases and brain cancers, has been limited, particularly because the blood–brain barrier (BBB makes brain tissue hard to access by conventional antibody-targeting strategies. In this review, we summarize new antibody therapeutic approaches to target brain tumors, especially malignant gliomas, as well as their potential drawbacks. Many different brain delivery platforms for antibodies have been studied such as liposomes, nanoparticle-based systems, cell-penetrating peptides (CPPs, and cell-based approaches. We have already shown the successful delivery of single-chain fragment variable (scFv with CPP as a linker between two variable domains in the brain. Antibodies normally face poor penetration through the BBB, with some variants sufficiently passing the barrier on their own. A “Trojan horse” method allows passage of biomolecules, such as antibodies, through the BBB by receptor-mediated transcytosis (RMT. Such examples of therapeutic antibodies are the bispecific antibodies where one binding specificity recognizes and binds a BBB receptor, enabling RMT and where a second binding specificity recognizes an antigen as a therapeutic target. On the other hand, cell-based systems such as stem cells (SCs are a promising delivery system because of their tumor tropism and ability to cross the BBB. Genetically engineered SCs can be used in gene therapy, where they express anti-tumor drugs, including antibodies. Different types and sources of SCs have been studied for the delivery of therapeutics to the brain; both mesenchymal stem cells (MSCs and neural stem cells (NSCs show great potential. Following the success in treatment of leukemias and lymphomas, the adoptive T-cell therapies, especially the chimeric antigen receptor-T cells (CAR-Ts, are making their way into glioma treatment as another type of cell

Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

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Subbaraju, Vigneshwaran; Suresh, Mahanand Belathur; Sundaram, Suresh; Narasimhan, Sundararajan

2017-01-01

This paper presents a new approach for detecting major differences in brain activities between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the resting state fMRI. Further the method also extracts discriminative features for an accurate diagnosis of ASD. The proposed approach determines a spatial filter that projects the covariance matrices of the Blood Oxygen Level Dependent (BOLD) time-series signals from both the ASD patients and neurotypical subjects in orthogonal directions such that they are highly separable. The inverse of this filter also provides a spatial pattern map within the brain that highlights those regions responsible for the distinguishable activities between the ASD patients and neurotypical subjects. For a better classification, highly discriminative log-variance features providing the maximum separation between the two classes are extracted from the projected BOLD time-series data. A detailed study has been carried out using the publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) consortium for the different gender and age-groups. The study results indicate that for all the above categories, the regional differences in resting state activities are more commonly found in the right hemisphere compared to the left hemisphere of the brain. Among males, a clear shift in activities to the prefrontal cortex is observed for ASD patients while other parts of the brain show diminished activities compared to neurotypical subjects. Among females, such a clear shift is not evident; however, several regions, especially in the posterior and medial portions of the brain show diminished activities due to ASD. Finally, the classification performance obtained using the log-variance features is found to be better when compared to earlier studies in the literature. Copyright © 2016 Elsevier B.V. All rights reserved.

Friends, not foes: Magnetoencephalography as a tool to uncover brain dynamics during transcranial alternating current stimulation.

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Neuling, Toralf; Ruhnau, Philipp; Fuscà, Marco; Demarchi, Gianpaolo; Herrmann, Christoph S; Weisz, Nathan

2015-09-01

Brain oscillations are supposedly crucial for normal cognitive functioning and alterations are associated with cognitive dysfunctions. To demonstrate their causal role on behavior, entrainment approaches in particular aim at driving endogenous oscillations via rhythmic stimulation. Within this context, transcranial electrical stimulation, especially transcranial alternating current stimulation (tACS), has received renewed attention. This is likely due to the possibility of defining oscillatory stimulation properties precisely. Also, measurements comparing pre-tACS with post-tACS electroencephalography (EEG) have shown impressive modulations. However, the period during tACS has remained a blackbox until now, due to the enormous stimulation artifact. By means of application of beamforming to magnetoencephalography (MEG) data, we successfully recovered modulations of the amplitude of brain oscillations during weak and strong tACS. Additionally, we demonstrate that also evoked responses to visual and auditory stimuli can be recovered during tACS. The main contribution of the present study is to provide critical evidence that during ongoing tACS, subtle modulations of oscillatory brain activity can be reconstructed even at the stimulation frequency. Future tACS experiments will be able to deliver direct physiological insights in order to further the understanding of the contribution of brain oscillations to cognition and behavior. Copyright © 2015. Published by Elsevier Inc.

Accelerated regression of brain metastases in patients receiving whole brain radiation and the topoisomerase II inhibitor, lucanthone

International Nuclear Information System (INIS)

Rowe, John D. del; Bello, Jacqueline; Mitnick, Robin; Sood, Brij; Filippi, Christopher; Moran, Justin Ph.D.; Freeman, Katherine; Mendez, Frances; Bases, Robert

1999-01-01

Purpose: To determine if lucanthone crossed the blood-brain barrier in experimental animals; and to determine accelerated tumor regression of human brain metastases treated jointly with lucanthone and whole brain radiation. Methods and Materials: The organ distribution of 3 H lucanthone in mice and 125 I lucanthone in rats was determined to learn if lucanthone crossed the blood-brain barrier. Size determinations were made of patients' brain metastases from magnetic resonance images or by computed tomography before and after treatment with 30 Gy whole brain radiation alone or with lucanthone. Results: The time course of lucanthone's distribution in brain was identical to that in muscle and heart after intraperitoneal or intravenous administration in experimental animals. Lucanthone, therefore, readily crossed the blood-brain barrier in experimental animals. Conclusion: Compared with radiation alone, the tumor regression in patients with brain metastases treated with lucanthone and radiation was accelerated, approaching significance using a permutation test at p = 0.0536

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

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Roy, Snehashis; He, Qing; Sweeney, Elizabeth; Carass, Aaron; Reich, Daniel S; Prince, Jerry L; Pham, Dzung L

2015-09-01

Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that uses a sparse dictionary learning approach and atlas priors. Training data for the method consists of an atlas MR image, prior information maps depicting where different tissues are expected to be located, and a hard segmentation. Unlike most atlas-based classification methods that require deformable registration of the atlas priors to the subject, only affine registration is required between the subject and training atlas. A subject-specific patch dictionary is created by learning relevant patches from the atlas. Then the subject patches are modeled as sparse combinations of learned atlas patches leading to tissue memberships at each voxel. The combination of prior information in an example-based framework enables us to distinguish tissues having similar intensities but different spatial locations. We demonstrate the efficacy of the approach on the application of whole-brain tissue segmentation in subjects with healthy anatomy and normal pressure hydrocephalus, as well as lesion segmentation in multiple sclerosis patients. For each application, quantitative comparisons are made against publicly available state-of-the art approaches.

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

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Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

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

Science.gov (United States)

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/).

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

Directory of Open Access Journals (Sweden)

Mingrui Xia

Full Text Available 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/.

Data integration through brain atlasing: Human Brain Project tools and strategies.

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Bjerke, Ingvild E; Øvsthus, Martin; Papp, Eszter A; Yates, Sharon C; Silvestri, Ludovico; Fiorilli, Julien; Pennartz, Cyriel M A; Pavone, Francesco S; Puchades, Maja A; Leergaard, Trygve B; Bjaalie, Jan G

2018-04-01

The Human Brain Project (HBP), an EU Flagship Initiative, is currently building an infrastructure that will allow integration of large amounts of heterogeneous neuroscience data. The ultimate goal of the project is to develop a unified multi-level understanding of the brain and its diseases, and beyond this to emulate the computational capabilities of the brain. Reference atlases of the brain are one of the key components in this infrastructure. Based on a new generation of three-dimensional (3D) reference atlases, new solutions for analyzing and integrating brain data are being developed. HBP will build services for spatial query and analysis of brain data comparable to current online services for geospatial data. The services will provide interactive access to a wide range of data types that have information about anatomical location tied to them. The 3D volumetric nature of the brain, however, introduces a new level of complexity that requires a range of tools for making use of and interacting with the atlases. With such new tools, neuroscience research groups will be able to connect their data to atlas space, share their data through online data systems, and search and find other relevant data through the same systems. This new approach partly replaces earlier attempts to organize research data based only on a set of semantic terminologies describing the brain and its subdivisions. Copyright © 2018 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Brain Sexual Differentiation and Requirement of SRY: Why or Why Not?

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Cheryl S. Rosenfeld

2017-11-01

Full Text Available Brain sexual differentiation is orchestrated by precise coordination of sex steroid hormones. In some species, programming of select male brain regions is dependent upon aromatization of testosterone to estrogen. In mammals, these hormones surge during the organizational and activational periods that occur during perinatal development and adulthood, respectively. In various fish and reptiles, incubation temperature during a critical embryonic period results in male or female sexual differentiation, but this can be overridden in males by early exposure to estrogenic chemicals. Testes development in mammals requires a Y chromosome and testis determining gene SRY (in humans/Sry (all other therian mammals, although there are notable exceptions. Two species of spiny rats: Amami spiny rat (Tokudaia osimensis and Tokunoshima spiny rat (Tokudaia tokunoshimensis and two species of mole voles (Ellobius lutescens and Ellobius tancrei, lack a Y chromosome/Sry and possess an XO chromosome system in both sexes. Such rodent species, prototherians (monotremes, who also lack Sry, and fish and reptile species that demonstrate temperature sex determination (TSD seemingly call into question the requirement of Sry for brain sexual differentiation. This review will consider brain regions expressing SRY/Sry in humans and rodents, respectively, and potential roles of SRY/Sry in the brain will be discussed. The evidence from various taxa disputing the requirement of Sry for brain sexual differentiation in mammals (therians and prototherians and certain fish and reptilian species will be examined. A comparative approach to address this question may elucidate other genes, pathways, and epigenetic modifications stimulating brain sexual differentiation in vertebrate species, including humans.

Topological isomorphisms of human brain and financial market networks

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Petra E Vértes

2011-09-01

Full Text Available Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the timeseries of 90 stocks from the New York Stock Exchange over a three-year period, and the fMRI-derived timeseries acquired from 90 brain regions over the course of a 10 min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimised for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph theoretically-mediated interface between systems neuroscience and the statistical physics of financial markets.

Topological isomorphisms of human brain and financial market networks.

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Vértes, Petra E; Nicol, Ruth M; Chapman, Sandra C; Watkins, Nicholas W; Robertson, Duncan A; Bullmore, Edward T

2011-01-01

Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets - the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular - more highly optimized for information processing - than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets.

Microwave beamforming for non-invasive patient-specific hyperthermia treatment of pediatric brain cancer

International Nuclear Information System (INIS)

Burfeindt, Matthew J; Zastrow, Earl; Hagness, Susan C; Van Veen, Barry D; Medow, Joshua E

2011-01-01

We present a numerical study of an array-based microwave beamforming approach for non-invasive hyperthermia treatment of pediatric brain tumors. The transmit beamformer is designed to achieve localized heating-that is, to achieve constructive interference and selective absorption of the transmitted electromagnetic waves at the desired focus location in the brain while achieving destructive interference elsewhere. The design process takes into account patient-specific and target-specific propagation characteristics at 1 GHz. We evaluate the effectiveness of the beamforming approach using finite-difference time-domain simulations of two MRI-derived child head models from the Virtual Family (IT'IS Foundation). Microwave power deposition and the resulting steady-state thermal distribution are calculated for each of several randomly chosen focus locations. We also explore the robustness of the design to mismatch between the assumed and actual dielectric properties of the patient. Lastly, we demonstrate the ability of the beamformer to suppress hot spots caused by pockets of cerebrospinal fluid (CSF) in the brain. Our results show that microwave beamforming has the potential to create localized heating zones in the head models for focus locations that are not surrounded by large amounts of CSF. These promising results suggest that the technique warrants further investigation and development.

Characterizing brain structures and remodeling after TBI based on information content, diffusion entropy.

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Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P; Zhang, Zheng Gang; Lehman, Norman L; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan

2013-01-01

To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease.

Characterizing Brain Structures and Remodeling after TBI Based on Information Content, Diffusion Entropy

Science.gov (United States)

Fozouni, Niloufar; Chopp, Michael; Nejad-Davarani, Siamak P.; Zhang, Zheng Gang; Lehman, Norman L.; Gu, Steven; Ueno, Yuji; Lu, Mei; Ding, Guangliang; Li, Lian; Hu, Jiani; Bagher-Ebadian, Hassan; Hearshen, David; Jiang, Quan

2013-01-01

Background To overcome the limitations of conventional diffusion tensor magnetic resonance imaging resulting from the assumption of a Gaussian diffusion model for characterizing voxels containing multiple axonal orientations, Shannon's entropy was employed to evaluate white matter structure in human brain and in brain remodeling after traumatic brain injury (TBI) in a rat. Methods Thirteen healthy subjects were investigated using a Q-ball based DTI data sampling scheme. FA and entropy values were measured in white matter bundles, white matter fiber crossing areas, different gray matter (GM) regions and cerebrospinal fluid (CSF). Axonal densities' from the same regions of interest (ROIs) were evaluated in Bielschowsky and Luxol fast blue stained autopsy (n = 30) brain sections by light microscopy. As a case demonstration, a Wistar rat subjected to TBI and treated with bone marrow stromal cells (MSC) 1 week after TBI was employed to illustrate the superior ability of entropy over FA in detecting reorganized crossing axonal bundles as confirmed by histological analysis with Bielschowsky and Luxol fast blue staining. Results Unlike FA, entropy was less affected by axonal orientation and more affected by axonal density. A significant agreement (r = 0.91) was detected between entropy values from in vivo human brain and histologically measured axonal density from post mortum from the same brain structures. The MSC treated TBI rat demonstrated that the entropy approach is superior to FA in detecting axonal remodeling after injury. Compared with FA, entropy detected new axonal remodeling regions with crossing axons, confirmed with immunohistological staining. Conclusions Entropy measurement is more effective in distinguishing axonal remodeling after injury, when compared with FA. Entropy is also more sensitive to axonal density than axonal orientation, and thus may provide a more accurate reflection of axonal changes that occur in neurological injury and disease

Treat the brain and treat the periphery: toward a holistic approach to major depressive disorder.

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Zheng, Xiao; Zhang, Xueli; Wang, Guangji; Hao, Haiping

2015-05-01

The limited medication for major depressive disorder (MDD) against an ever-rising disease burden presents an urgent need for therapeutic innovations. During recent years, studies looking at the systems regulation of mental health and disease have shown a remarkably powerful control of MDD by systemic signals. Meanwhile, the identification of a host of targets outside the brain opens the way to treat MDD by targeting systemic signals. We examine these emerging findings and consider the implications for current thinking regarding MDD pathogenesis and treatment. We highlight the opportunities and challenges of a periphery-targeting strategy and propose its incorporation into a holistic approach. Copyright © 2015 Elsevier Ltd. All rights reserved.

Murine cytomegalovirus infection of neural stem cells alters neurogenesis in the developing brain.

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Manohar B Mutnal

2011-01-01

Full Text Available Congenital cytomegalovirus (CMV brain infection causes serious neuro-developmental sequelae including: mental retardation, cerebral palsy, and sensorineural hearing loss. But, the mechanisms of injury and pathogenesis to the fetal brain are not completely understood. The present study addresses potential pathogenic mechanisms by which this virus injures the CNS using a neonatal mouse model that mirrors congenital brain infection. This investigation focused on, analysis of cell types infected with mouse cytomegalovirus (MCMV and the pattern of injury to the developing brain.We used our MCMV infection model and a multi-color flow cytometry approach to quantify the effect of viral infection on the developing brain, identifying specific target cells and the consequent effect on neurogenesis. In this study, we show that neural stem cells (NSCs and neuronal precursor cells are the principal target cells for MCMV in the developing brain. In addition, viral infection was demonstrated to cause a loss of NSCs expressing CD133 and nestin. We also showed that infection of neonates leads to subsequent abnormal brain development as indicated by loss of CD24(hi cells that incorporated BrdU. This neonatal brain infection was also associated with altered expression of Oct4, a multipotency marker; as well as down regulation of the neurotrophins BDNF and NT3, which are essential to regulate the birth and differentiation of neurons during normal brain development. Finally, we report decreased expression of doublecortin, a marker to identify young neurons, following viral brain infection.MCMV brain infection of newborn mice causes significant loss of NSCs, decreased proliferation of neuronal precursor cells, and marked loss of young neurons.

Reward sensitivity is associated with brain activity during erotic stimulus processing.

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Costumero, Victor; Barrós-Loscertales, Alfonso; Bustamante, Juan Carlos; Ventura-Campos, Noelia; Fuentes, Paola; Rosell-Negre, Patricia; Ávila, César

2013-01-01

The behavioral approach system (BAS) from Gray's reinforcement sensitivity theory is a neurobehavioral system involved in the processing of rewarding stimuli that has been related to dopaminergic brain areas. Gray's theory hypothesizes that the functioning of reward brain areas is modulated by BAS-related traits. To test this hypothesis, we performed an fMRI study where participants viewed erotic and neutral pictures, and cues that predicted their appearance. Forty-five heterosexual men completed the Sensitivity to Reward scale (from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire) to measure BAS-related traits. Results showed that Sensitivity to Reward scores correlated positively with brain activity during reactivity to erotic pictures in the left orbitofrontal cortex, left insula, and right ventral striatum. These results demonstrated a relationship between the BAS and reward sensitivity during the processing of erotic stimuli, filling the gap of previous reports that identified the dopaminergic system as a neural substrate for the BAS during the processing of other rewarding stimuli such as money and food.

Reward sensitivity is associated with brain activity during erotic stimulus processing.

Directory of Open Access Journals (Sweden)

Victor Costumero

Full Text Available The behavioral approach system (BAS from Gray's reinforcement sensitivity theory is a neurobehavioral system involved in the processing of rewarding stimuli that has been related to dopaminergic brain areas. Gray's theory hypothesizes that the functioning of reward brain areas is modulated by BAS-related traits. To test this hypothesis, we performed an fMRI study where participants viewed erotic and neutral pictures, and cues that predicted their appearance. Forty-five heterosexual men completed the Sensitivity to Reward scale (from the Sensitivity to Punishment and Sensitivity to Reward Questionnaire to measure BAS-related traits. Results showed that Sensitivity to Reward scores correlated positively with brain activity during reactivity to erotic pictures in the left orbitofrontal cortex, left insula, and right ventral striatum. These results demonstrated a relationship between the BAS and reward sensitivity during the processing of erotic stimuli, filling the gap of previous reports that identified the dopaminergic system as a neural substrate for the BAS during the processing of other rewarding stimuli such as money and food.

Adaptive deep brain stimulation in advanced Parkinson disease.

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Little, Simon; Pogosyan, Alex; Neal, Spencer; Zavala, Baltazar; Zrinzo, Ludvic; Hariz, Marwan; Foltynie, Thomas; Limousin, Patricia; Ashkan, Keyoumars; FitzGerald, James; Green, Alexander L; Aziz, Tipu Z; Brown, Peter

2013-09-01

Brain-computer interfaces (BCIs) could potentially be used to interact with pathological brain signals to intervene and ameliorate their effects in disease states. Here, we provide proof-of-principle of this approach by using a BCI to interpret pathological brain activity in patients with advanced Parkinson disease (PD) and to use this feedback to control when therapeutic deep brain stimulation (DBS) is delivered. Our goal was to demonstrate that by personalizing and optimizing stimulation in real time, we could improve on both the efficacy and efficiency of conventional continuous DBS. We tested BCI-controlled adaptive DBS (aDBS) of the subthalamic nucleus in 8 PD patients. Feedback was provided by processing of the local field potentials recorded directly from the stimulation electrodes. The results were compared to no stimulation, conventional continuous stimulation (cDBS), and random intermittent stimulation. Both unblinded and blinded clinical assessments of motor effect were performed using the Unified Parkinson's Disease Rating Scale. Motor scores improved by 66% (unblinded) and 50% (blinded) during aDBS, which were 29% (p = 0.03) and 27% (p = 0.005) better than cDBS, respectively. These improvements were achieved with a 56% reduction in stimulation time compared to cDBS, and a corresponding reduction in energy requirements (p random intermittent stimulation. BCI-controlled DBS is tractable and can be more efficient and efficacious than conventional continuous neuromodulation for PD. Copyright © 2013 American Neurological Association.

Information dynamics of brain-heart physiological networks during sleep

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Faes, L.; Nollo, G.; Jurysta, F.; Marinazzo, D.

2014-10-01

This study proposes an integrated approach, framed in the emerging fields of network physiology and information dynamics, for the quantitative analysis of brain-heart interaction networks during sleep. With this approach, the time series of cardiac vagal autonomic activity and brain wave activities measured respectively as the normalized high frequency component of heart rate variability and the EEG power in the δ, θ, α, σ, and β bands, are considered as realizations of the stochastic processes describing the dynamics of the heart system and of different brain sub-systems. Entropy-based measures are exploited to quantify the predictive information carried by each (sub)system, and to dissect this information into a part actively stored in the system and a part transferred to it from the other connected systems. The application of this approach to polysomnographic recordings of ten healthy subjects led us to identify a structured network of sleep brain-brain and brain-heart interactions, with the node described by the β EEG power acting as a hub which conveys the largest amount of information flowing between the heart and brain nodes. This network was found to be sustained mostly by the transitions across different sleep stages, as the information transfer was weaker during specific stages than during the whole night, and vanished progressively when moving from light sleep to deep sleep and to REM sleep.

Regulation of brain copper homeostasis by the brain barrier systems: Effects of Fe-overload and Fe-deficiency

International Nuclear Information System (INIS)

Monnot, Andrew D.; Behl, Mamta; Ho, Sanna; Zheng, Wei

2011-01-01

Maintaining brain Cu homeostasis is vital for normal brain function. The role of systemic Fe deficiency (FeD) or overload (FeO) due to metabolic diseases or environmental insults in Cu homeostasis in the cerebrospinal fluid (CSF) and brain tissues remains unknown. This study was designed to investigate how blood-brain barrier (BBB) and blood-SCF barrier (BCB) regulated Cu transport and how FeO or FeD altered brain Cu homeostasis. Rats received an Fe-enriched or Fe-depleted diet for 4 weeks. FeD and FeO treatment resulted in a significant increase (+ 55%) and decrease (− 56%) in CSF Cu levels (p < 0.05), respectively; however, neither treatment had any effect on CSF Fe levels. The FeD, but not FeO, led to significant increases in Cu levels in brain parenchyma and the choroid plexus. In situ brain perfusion studies demonstrated that the rate of Cu transport into the brain parenchyma was significantly faster in FeD rats (+ 92%) and significantly slower (− 53%) in FeO rats than in controls. In vitro two chamber Transwell transepithelial transport studies using primary choroidal epithelial cells revealed a predominant efflux of Cu from the CSF to blood compartment by the BCB. Further ventriculo-cisternal perfusion studies showed that Cu clearance by the choroid plexus in FeD animals was significantly greater than control (p < 0.05). Taken together, our results demonstrate that both the BBB and BCB contribute to maintain a stable Cu homeostasis in the brain and CSF. Cu appears to enter the brain primarily via the BBB and is subsequently removed from the CSF by the BCB. FeD has a more profound effect on brain Cu levels than FeO. FeD increases Cu transport at the brain barriers and prompts Cu overload in the CNS. The BCB plays a key role in removing the excess Cu from the CSF.

Regulation of brain copper homeostasis by the brain barrier systems: Effects of Fe-overload and Fe-deficiency

Energy Technology Data Exchange (ETDEWEB)

Monnot, Andrew D.; Behl, Mamta; Ho, Sanna; Zheng, Wei, E-mail: wzheng@purdue.edu

2011-11-15

Maintaining brain Cu homeostasis is vital for normal brain function. The role of systemic Fe deficiency (FeD) or overload (FeO) due to metabolic diseases or environmental insults in Cu homeostasis in the cerebrospinal fluid (CSF) and brain tissues remains unknown. This study was designed to investigate how blood-brain barrier (BBB) and blood-SCF barrier (BCB) regulated Cu transport and how FeO or FeD altered brain Cu homeostasis. Rats received an Fe-enriched or Fe-depleted diet for 4 weeks. FeD and FeO treatment resulted in a significant increase (+ 55%) and decrease (- 56%) in CSF Cu levels (p < 0.05), respectively; however, neither treatment had any effect on CSF Fe levels. The FeD, but not FeO, led to significant increases in Cu levels in brain parenchyma and the choroid plexus. In situ brain perfusion studies demonstrated that the rate of Cu transport into the brain parenchyma was significantly faster in FeD rats (+ 92%) and significantly slower (- 53%) in FeO rats than in controls. In vitro two chamber Transwell transepithelial transport studies using primary choroidal epithelial cells revealed a predominant efflux of Cu from the CSF to blood compartment by the BCB. Further ventriculo-cisternal perfusion studies showed that Cu clearance by the choroid plexus in FeD animals was significantly greater than control (p < 0.05). Taken together, our results demonstrate that both the BBB and BCB contribute to maintain a stable Cu homeostasis in the brain and CSF. Cu appears to enter the brain primarily via the BBB and is subsequently removed from the CSF by the BCB. FeD has a more profound effect on brain Cu levels than FeO. FeD increases Cu transport at the brain barriers and prompts Cu overload in the CNS. The BCB plays a key role in removing the excess Cu from the CSF.

The sleeping brain as a complex system.

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Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

2011-10-13

'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

Auditory Brain Stem Processing in Reptiles and Amphibians: Roles of Coupled Ears

DEFF Research Database (Denmark)

Willis, Katie L.; Christensen-Dalsgaard, Jakob; Carr, Catherine

2014-01-01

Comparative approaches to the auditory system have yielded great insight into the evolution of sound localization circuits, particularly within the nonmammalian tetrapods. The fossil record demonstrates multiple appearances of tympanic hearing, and examination of the auditory brain stem of various...... groups can reveal the organizing effects of the ear across taxa. If the peripheral structures have a strongly organizing influence on the neural structures, then homologous neural structures should be observed only in groups with a homologous tympanic ear. Therefore, the central auditory systems...... of anurans (frogs), reptiles (including birds), and mammals should all be more similar within each group than among the groups. Although there is large variation in the peripheral auditory system, there is evidence that auditory brain stem nuclei in tetrapods are homologous and have similar functions among...

Brain Science of Ethics: Present Status and the Future

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Aoki, Ryuta; Funane, Tsukasa; Koizumi, Hideaki

2010-01-01

Recent advances in technologies for neuroscientific research enable us to investigate the neurobiological substrates of the human ethical sense. This article introduces several findings in "the brain science of ethics" obtained through "brain-observation" and "brain-manipulation" approaches. Studies over the past decade have revealed that several…

Neuroscience, virtual reality and neurorehabilitation: brain repair as a validation of brain theory.

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Verschure, Paul F M J

2011-01-01

This paper argues that basing cybertherapy approaches on a theoretical understanding of the brain has advantages. On one hand it provides for a rational approach towards therapy design while on the other allowing for a direct validation of brain theory in the clinic. As an example this paper discusses how the Distributed Adaptive Control architecture, a theory of mind, brain and action, has given rise to a new paradigm in neurorehabilitation called the Rehabilitation Gaming System (RGS) and to novel neuroprosthetic systems. The neuroprosthetic system considered is developed to replace the function of cerebellar micro-circuits, expresses core aspects of the learning systems of DAC and has been successfully tested in in-vivo experiments. The Virtual reality based rehabilitation paradigm of RGS has been validated in the treatment of acute and chronic stroke and has been shown to be more effective than existing methods. RGS provides a foundation for integrated at-home therapy systems that can operate largely autonomously when also augmented with appropriate physiological monitoring and diagnostic devices. These examples provide first steps towards a science based medicine.

Early Detection of Poor Outcome after Mild Traumatic Brain Injury: Predictive Factors Using a Multidimensional Approach a Pilot Study

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Sophie Caplain

2017-12-01

Full Text Available Mild traumatic brain injury (MTBI is a common condition within the general population, usually with good clinical outcome. However, in 10–25% of cases, a post-concussive syndrome (PCS occurs. Identifying early prognostic factors for the development of PCS can ensure widespread clinical and economic benefits. The aim of this study was to demonstrate the potential value of a comprehensive neuropsychological evaluation to identify early prognostic factors following MTBI. We performed a multi-center open, prospective, longitudinal study that included 72 MTBI patients and 42 healthy volunteers matched for age, gender, and socioeconomic status. MTBI patients were evaluated 8–21 days after injury, and 6 months thereafter, with a full neurological and psychological examination and brain MRI. At 6 months follow-up, MTBI patients were categorized into two subgroups according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV as having either favorable or unfavorable evolution (UE, corresponding to the presence of major or mild neurocognitive disorder due to traumatic brain injury. Univariate and multivariate logistical regression analysis demonstrated the importance of patient complaints, quality of life, and cognition in the outcome of MTBI patients, but only 6/23 UE patients were detected early via the multivariate logistic regression model. Using several variables from each of these three categories of variables, we built a model that assigns a score to each patient presuming the possibility of UE. Statistical analyses showed this last model to be reliable and sensitive, allowing early identification of patients at risk of developing PCS with 95.7% sensitivity and 77.6% specificity.

A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface

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Charles Yaacoub

2017-01-01

Full Text Available Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5% while improving the accuracy, sensitivity, specificity, and precision of the classifier.

A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface.

Science.gov (United States)

Yaacoub, Charles; Mhanna, Georges; Rihana, Sandy

2017-01-23

Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5%) while improving the accuracy, sensitivity, specificity, and precision of the classifier.

MRI demonstration of subarachnoid neurocysticercosis simulating metastatic disease

International Nuclear Information System (INIS)

Lau, K.Y.; Roebuck, D.J.; Metreweli, C.; Mok, V.; Kay, R.; Ng, H.K.; Teo, J.G.C.; Lam, J.; Poon, W.

1998-01-01

We present a patient with neurocysticercosis with spinal subarachnoid spread who presented with lower back pain and progressive numbness and weakness of the left leg. MRI of the spine simulated metastasis. MRI of the brain demonstrated a ''bunch of grapes'' appearance in the basal cisterns, characteristic of cysticercosis. (orig.)

Stem Cell Technology for (Epi)genetic Brain Disorders.

Science.gov (United States)

Riemens, Renzo J M; Soares, Edilene S; Esteller, Manel; Delgado-Morales, Raul

2017-01-01

Despite the enormous efforts of the scientific community over the years, effective therapeutics for many (epi)genetic brain disorders remain unidentified. The common and persistent failures to translate preclinical findings into clinical success are partially attributed to the limited efficiency of current disease models. Although animal and cellular models have substantially improved our knowledge of the pathological processes involved in these disorders, human brain research has generally been hampered by a lack of satisfactory humanized model systems. This, together with our incomplete knowledge of the multifactorial causes in the majority of these disorders, as well as a thorough understanding of associated (epi)genetic alterations, has been impeding progress in gaining more mechanistic insights from translational studies. Over the last years, however, stem cell technology has been offering an alternative approach to study and treat human brain disorders. Owing to this technology, we are now able to obtain a theoretically inexhaustible source of human neural cells and precursors in vitro that offer a platform for disease modeling and the establishment of therapeutic interventions. In addition to the potential to increase our general understanding of how (epi)genetic alterations contribute to the pathology of brain disorders, stem cells and derivatives allow for high-throughput drugs and toxicity testing, and provide a cell source for transplant therapies in regenerative medicine. In the current chapter, we will demonstrate the validity of human stem cell-based models and address the utility of other stem cell-based applications for several human brain disorders with multifactorial and (epi)genetic bases, including Parkinson's disease (PD), Alzheimer's disease (AD), fragile X syndrome (FXS), Angelman syndrome (AS), Prader-Willi syndrome (PWS), and Rett syndrome (RTT).

Brain-Based Education: Its Pedagogical Implications and Research Relevance

Science.gov (United States)

Laxman, Kumar; Chin, Yap Kueh

2010-01-01

The brain, being the organ of learning, must be understood if classrooms are to be places of meaningful learning. Understanding the brain has the potential to alter the foundation of education, transform traditional classrooms to interactive learning environments and promote better instructional approaches amongst teachers. Brain-based education…

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

Science.gov (United States)

Luders, Eileen; Cherbuin, Nicolas; Gaser, Christian

2016-07-01

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

High-resolution whole-brain DCE-MRI using constrained reconstruction: Prospective clinical evaluation in brain tumor patients

International Nuclear Information System (INIS)

Guo, Yi; Zhu, Yinghua; Lingala, Sajan Goud; Nayak, Krishna; Lebel, R. Marc; Shiroishi, Mark S.; Law, Meng

2016-01-01

Purpose: To clinically evaluate a highly accelerated T1-weighted dynamic contrast-enhanced (DCE) MRI technique that provides high spatial resolution and whole-brain coverage via undersampling and constrained reconstruction with multiple sparsity constraints. Methods: Conventional (rate-2 SENSE) and experimental DCE-MRI (rate-30) scans were performed 20 minutes apart in 15 brain tumor patients. The conventional clinical DCE-MRI had voxel dimensions 0.9 × 1.3 × 7.0 mm 3 , FOV 22 × 22 × 4.2 cm 3 , and the experimental DCE-MRI had voxel dimensions 0.9 × 0.9 × 1.9 mm 3 , and broader coverage 22 × 22 × 19 cm 3 . Temporal resolution was 5 s for both protocols. Time-resolved images and blood–brain barrier permeability maps were qualitatively evaluated by two radiologists. Results: The experimental DCE-MRI scans showed no loss of qualitative information in any of the cases, while achieving substantially higher spatial resolution and whole-brain spatial coverage. Average qualitative scores (from 0 to 3) were 2.1 for the experimental scans and 1.1 for the conventional clinical scans. Conclusions: The proposed DCE-MRI approach provides clinically superior image quality with higher spatial resolution and coverage than currently available approaches. These advantages may allow comprehensive permeability mapping in the brain, which is especially valuable in the setting of large lesions or multiple lesions spread throughout the brain.

Test-retest assessment of cortical activation induced by repetitive transcranial magnetic stimulation with brain atlas-guided optical topography

Science.gov (United States)

Tian, Fenghua; Kozel, F. Andrew; Yennu, Amarnath; Croarkin, Paul E.; McClintock, Shawn M.; Mapes, Kimberly S.; Husain, Mustafa M.; Liu, Hanli

2012-11-01

Repetitive transcranial magnetic stimulation (rTMS) is a technology that stimulates neurons with rapidly changing magnetic pulses with demonstrated therapeutic applications for various neuropsychiatric disorders. Functional near-infrared spectroscopy (fNIRS) is a suitable tool to assess rTMS-evoked brain responses without interference from the magnetic or electric fields generated by the TMS coil. We have previously reported a channel-wise study of combined rTMS/fNIRS on the motor and prefrontal cortices, showing a robust decrease of oxygenated hemoglobin concentration (Δ[HbO2]) at the sites of 1-Hz rTMS and the contralateral brain regions. However, the reliability of this putative clinical tool is unknown. In this study, we develop a rapid optical topography approach to spatially characterize the rTMS-evoked hemodynamic responses on a standard brain atlas. A hemispherical approximation of the brain is employed to convert the three-dimensional topography on the complex brain surface to a two-dimensional topography in the spherical coordinate system. The test-retest reliability of the combined rTMS/fNIRS is assessed using repeated measurements performed two to three days apart. The results demonstrate that the Δ[HbO2] amplitudes have moderate-to-high reliability at the group level; and the spatial patterns of the topographic images have high reproducibility in size and a moderate degree of overlap at the individual level.

Functional brain laterality in adulthood ADHD : A dimensional approach

NARCIS (Netherlands)

Mohamed, Saleh

2017-01-01

The present thesis aimed to address functional brain laterality and symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD) in adults, from a dimensional perspective. The dimensional perspective assumes that ADHD symptoms are normally distributed in general population and those scoring at the

Mindboggle: Automated brain labeling with multiple atlases

International Nuclear Information System (INIS)

Klein, Arno; Mensh, Brett; Ghosh, Satrajit; Tourville, Jason; Hirsch, Joy

2005-01-01

To make inferences about brain structures or activity across multiple individuals, one first needs to determine the structural correspondences across their image data. We have recently developed Mindboggle as a fully automated, feature-matching approach to assign anatomical labels to cortical structures and activity in human brain MRI data. Label assignment is based on structural correspondences between labeled atlases and unlabeled image data, where an atlas consists of a set of labels manually assigned to a single brain image. In the present work, we study the influence of using variable numbers of individual atlases to nonlinearly label human brain image data. Each brain image voxel of each of 20 human subjects is assigned a label by each of the remaining 19 atlases using Mindboggle. The most common label is selected and is given a confidence rating based on the number of atlases that assigned that label. The automatically assigned labels for each subject brain are compared with the manual labels for that subject (its atlas). Unlike recent approaches that transform subject data to a labeled, probabilistic atlas space (constructed from a database of atlases), Mindboggle labels a subject by each atlas in a database independently. When Mindboggle labels a human subject's brain image with at least four atlases, the resulting label agreement with coregistered manual labels is significantly higher than when only a single atlas is used. Different numbers of atlases provide significantly higher label agreements for individual brain regions. Increasing the number of reference brains used to automatically label a human subject brain improves labeling accuracy with respect to manually assigned labels. Mindboggle software can provide confidence measures for labels based on probabilistic assignment of labels and could be applied to large databases of brain images

Reconstructing perceived faces from brain activations with deep adversarial neural decoding

NARCIS (Netherlands)

Güçlütürk, Y.; Güçlü, U.; Seeliger, K.; Bosch, S.E.; Lier, R.J. van; Gerven, M.A.J. van; Guyon, I.; Luxburg, U.V.; Bengio, S.; Wallach, H.; Fergus, R.; Vishwanathan, S.; Garnett, R.

2017-01-01

Here, we present a novel approach to solve the problem of reconstructing perceived stimuli from brain responses by combining probabilistic inference with deep learning. Our approach first inverts the linear transformation from latent features to brain responses with maximum a posteriori estimation

99mTc-HMPAO SPECT in brain death

International Nuclear Information System (INIS)

Tsuchida, Tatsuro; Sadato, Norihiro; Nishizawa, Sadahiko

1993-01-01

Brain single photon emission computed tomography (SPECT) with 99m Tc-d,l-hexamethyl-propyleneamine oxime (HMPAO) was performed twice in a 78-year-old man clinically diagnosed as brain death according to the standard criteria of the Japanese Ministry of Welfare. The first brain SPECT demonstrated the tracer accumulation in the brain, indicating preserved cerebral blood flow. The second brain SPECT performed 3 days later revealed cessation of the blood flow. In patients with preserved cerebral blood flow, the diagnosis of brain death cannot be made, even if they meet the existing criteria, because previous report noted the recovery in some of those patients. Brain perfusion SPECT plays an important role as a confirmatory test for the diagnosis of brain death. (author)

Whole-brain dynamic CT angiography and perfusion imaging

Energy Technology Data Exchange (ETDEWEB)

Orrison, W.W. [CHW Nevada Imaging Company, Nevada Imaging Centers, Spring Valley, Las Vegas, NV (United States); College of Osteopathic Medicine, Touro University Nevada, Henderson, NV (United States); Department of Health Physics and Diagnostic Sciences, University of Nevada Las Vegas, Las Vegas, NV (United States); Department of Medical Education, University of Nevada School of Medicine, Reno, NV (United States); Snyder, K.V.; Hopkins, L.N. [Department of Neurosurgery, Millard Fillmore Gates Circle Hospital, Buffalo, NY (United States); Roach, C.J. [School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV (United States); Advanced Medical Imaging and Genetics (Amigenics), Las Vegas, NV (United States); Ringdahl, E.N. [Department of Psychology, University of Nevada Las Vegas, Las Vegas, NV (United States); Nazir, R. [Shifa International Hospital, Islamabad (Pakistan); Hanson, E.H., E-mail: eric.hanson@amigenics.co [College of Osteopathic Medicine, Touro University Nevada, Henderson, NV (United States); Department of Health Physics and Diagnostic Sciences, University of Nevada Las Vegas, Las Vegas, NV (United States); Advanced Medical Imaging and Genetics (Amigenics), Las Vegas, NV (United States)

2011-06-15

The availability of whole brain computed tomography (CT) perfusion has expanded the opportunities for analysing the haemodynamic parameters associated with varied neurological conditions. Examples demonstrating the clinical utility of whole-brain CT perfusion imaging in selected acute and chronic ischaemic arterial neurovascular conditions are presented. Whole-brain CT perfusion enables the detection and focused haemodynamic analyses of acute and chronic arterial conditions in the central nervous system without the limitation of partial anatomical coverage of the brain.

Artefact in Physiological Data Collected from Patients with Brain Injury: Quantifying the Problem and Providing a Solution Using a Factorial Switching Linear Dynamical Systems Approach.

Science.gov (United States)

Georgatzis, Konstantinos; Lal, Partha; Hawthorne, Christopher; Shaw, Martin; Piper, Ian; Tarbert, Claire; Donald, Rob; Williams, Christopher K I

2016-01-01

High-resolution, artefact-free and accurately annotated physiological data are desirable in patients with brain injury both to inform clinical decision-making and for intelligent analysis of the data in applications such as predictive modelling. We have quantified the quality of annotation surrounding artefactual events and propose a factorial switching linear dynamical systems (FSLDS) approach to automatically detect artefact in physiological data collected in the neurological intensive care unit (NICU). Retrospective analysis of the BrainIT data set to discover potential hypotensive events corrupted by artefact and identify the annotation of associated clinical interventions. Training of an FSLDS model on clinician-annotated artefactual events in five patients with severe traumatic brain injury. In a subset of 187 patients in the BrainIT database, 26.5 % of potential hypotensive events were abandoned because of artefactual data. Only 30 % of these episodes could be attributed to an annotated clinical intervention. As assessed by the area under the receiver operating characteristic curve metric, FSLDS model performance in automatically identifying the events of blood sampling, arterial line damping and patient handling was 0.978, 0.987 and 0.765, respectively. The influence of artefact on physiological data collected in the NICU is a significant problem. This pilot study using an FSLDS approach shows real promise and is under further development.

History of aphasia: From brain to language

NARCIS (Netherlands)

Eling, P.A.T.M.; Whitaker, H.A.; Finger, S.; Boller, F.; Tyler, K.L.

2009-01-01

An historical overview is presented that focuses on the changes both in approach and topics with respect to language disturbances due to brain lesions. Early cases of language disorders were described without any theorizing about language or its relation to the brain. Also, three forms of speech

Evolutionarily Conserved Roles for Blood-Brain Barrier Xenobiotic Transporters in Endogenous Steroid Partitioning and Behavior

Directory of Open Access Journals (Sweden)

Samantha J. Hindle

2017-10-01

Full Text Available Summary: Central nervous system (CNS chemical protection depends upon discrete control of small-molecule access by the blood-brain barrier (BBB. Curiously, some drugs cause CNS side-effects despite negligible transit past the BBB. To investigate this phenomenon, we asked whether the highly BBB-enriched drug efflux transporter MDR1 has dual functions in controlling drug and endogenous molecule CNS homeostasis. If this is true, then brain-impermeable drugs could induce behavioral changes by affecting brain levels of endogenous molecules. Using computational, genetic, and pharmacologic approaches across diverse organisms, we demonstrate that BBB-localized efflux transporters are critical for regulating brain levels of endogenous steroids and steroid-regulated behaviors (sleep in Drosophila and anxiety in mice. Furthermore, we show that MDR1-interacting drugs are associated with anxiety-related behaviors in humans. We propose a general mechanism for common behavioral side effects of prescription drugs: pharmacologically challenging BBB efflux transporters disrupts brain levels of endogenous substrates and implicates the BBB in behavioral regulation. : Hindle et al. shed light on the curious finding that some drugs cause behavioral side-effects despite negligible access into the brain. These authors propose a unifying hypothesis that links blood-brain barrier drug transporter function and brain access of circulating steroids to common CNS adverse drug responses. Keywords: drug side effect mechanisms, central nervous system, blood brain barrier, behavior, toxicology, drug transporters, endobiotics, steroid hormones

Contrast enhanced susceptibility weighted imaging (CE-SWI) of the mouse brain using ultrasmall superparamagnetic ironoxide particles (USPIO)

International Nuclear Information System (INIS)

Hamans, B.C.; Heerschap, A.; Barth, M.; Leenders, W.P.

2006-01-01

Susceptibility weighted imaging (SWI) has been introduced as a novel approach to visualize the venous vasculature in the human brain. With SWI, small veins in the brain are depicted based on the susceptibility difference between deoxyhaemoglobin in the veins and surrounding tissue, which is further enhanced by the use of MR phase information. In this study we applied SWI in the mouse brain using an exogenous iron-based blood-pool contrast agent, with the aims of further enhancing the susceptibility effect and allowing the visualization of individual veins and arteries. Contrast enhanced (CE-) SWI of the brain was performed on healthy mice and mice carrying intracerebral glioma xenografts. This study demonstrates that detailed vascular information in the mouse brain can be obtained by using CE-SWI and is substantially enhanced compared to native SWI (i.e. without contrast agent). CE-SWI images of tumour-bearing mice were directly compared to histology, confirming that CE-SWI depicts the vessels supplying and draining the tumour. We propose that CE-SWI is a very promising tool for the characterization of tumour vasculature. (orig.)

Get Mobile – The Smartphone Brain Scanner

DEFF Research Database (Denmark)

Stahlhut, Carsten; Stopczynski, Arkadiusz; Petersen, Michael Kai

This demonstration will provide live-interaction with a smartphone brain scanner consisting of a low-cost wireless 14-channel EEG headset (Emotiv Epoc) and a mobile device. With our system it is possible to perform real-time functional brain imaging on a smartphone device, including stimulus...

Novel theory of the human brain: information-commutation basis of architecture and principles of operation

Directory of Open Access Journals (Sweden)

Bryukhovetskiy AS

2015-02-01

Full Text Available Andrey S Bryukhovetskiy Center for Biomedical Technologies, Federal Research and Clinical Center for Specialized Types of Medical Assistance and Medical Technologies of the Federal Medical Biological Agency, NeuroVita Clinic of Interventional and Restorative Neurology and Therapy, Moscow, Russia Abstract: Based on the methodology of the informational approach and research of the genome, proteome, and complete transcriptome profiles of different cells in the nervous tissue of the human brain, the author proposes a new theory of information-commutation organization and architecture of the human brain which is an alternative to the conventional systemic connective morphofunctional paradigm of the brain framework. Informational principles of brain operation are defined: the modular principle, holographic principle, principle of systematicity of vertical commutative connection and complexity of horizontal commutative connection, regulatory principle, relay principle, modulation principle, “illumination” principle, principle of personalized memory and intellect, and principle of low energy consumption. The author demonstrates that the cortex functions only as a switchboard and router of information, while information is processed outside the nervous tissue of the brain in the intermeningeal space. The main structural element of information-commutation in the brain is not the neuron, but information-commutation modules that are subdivided into receiver modules, transmitter modules, and subscriber modules, forming a vertical architecture of nervous tissue in the brain as information lines and information channels, and a horizontal architecture as central, intermediate, and peripheral information-commutation platforms. Information in information-commutation modules is transferred by means of the carriers that are characteristic to the specific information level from inductome to genome, transcriptome, proteome, metabolome, secretome, and magnetome

Targeting of deep-brain structures in nonhuman primates using MR and CT Images

Science.gov (United States)

Chen, Antong; Hines, Catherine; Dogdas, Belma; Bone, Ashleigh; Lodge, Kenneth; O'Malley, Stacey; Connolly, Brett; Winkelmann, Christopher T.; Bagchi, Ansuman; Lubbers, Laura S.; Uslaner, Jason M.; Johnson, Colena; Renger, John; Zariwala, Hatim A.

2015-03-01

In vivo gene delivery in central nervous systems of nonhuman primates (NHP) is an important approach for gene therapy and animal model development of human disease. To achieve a more accurate delivery of genetic probes, precise stereotactic targeting of brain structures is required. However, even with assistance from multi-modality 3D imaging techniques (e.g. MR and CT), the precision of targeting is often challenging due to difficulties in identification of deep brain structures, e.g. the striatum which consists of multiple substructures, and the nucleus basalis of meynert (NBM), which often lack clear boundaries to supporting anatomical landmarks. Here we demonstrate a 3D-image-based intracranial stereotactic approach applied toward reproducible intracranial targeting of bilateral NBM and striatum of rhesus. For the targeting we discuss the feasibility of an atlas-based automatic approach. Delineated originally on a high resolution 3D histology-MR atlas set, the NBM and the striatum could be located on the MR image of a rhesus subject through affine and nonrigid registrations. The atlas-based targeting of NBM was compared with the targeting conducted manually by an experienced neuroscientist. Based on the targeting, the trajectories and entry points for delivering the genetic probes to the targets could be established on the CT images of the subject after rigid registration. The accuracy of the targeting was assessed quantitatively by comparison between NBM locations obtained automatically and manually, and finally demonstrated qualitatively via post mortem analysis of slices that had been labelled via Evan Blue infusion and immunohistochemistry.

The Three-Dimensional Architecture of the Internal Capsule of the Human Brain Demonstrated by Fiber Dissection Technique

Directory of Open Access Journals (Sweden)

Cristina Goga

2015-01-01

Full Text Available The fiber dissection technique involves peeling away white matter fiber tracts of the brain to display its three-dimensional anatomic arrangement. The intricate three-dimensional configuration and structure of the internal capsule (IC is not well defined. By using the fiber dissection technique, our aim was to expose and study the IC to achieve a clearer conception of its configuration and relationships with neighboring white matter fibers and central nuclei. The lateral and medial aspects of the temporal lobes of twenty, previously frozen, formalin-fixed human brains were dissected under the operating microscope using the fiber dissection technique.

Brain MR imaging in child abuse

International Nuclear Information System (INIS)

Sato, Y.; Ellerbroek, C.J.; Alexander, R.; Kao, S.C.S.; Yuh, W.T.C.; Smith, W.L.

1988-01-01

Intracranial injuries represent the most severe manifestation of child abuse. CT of the brain is the current standard for evaluation of these infants; however, MR imaging offers several potential advantages. MR imaging and CT were performed in ten infants who suffered intracranial trauma owing to child abuse. CT was slightly better at demonstrating subarachnoid hemorrhage and had definite advantages for defining fractures. MR imaging was superior in the demonstration of subacute extraaxial hemorrhage, deep brain injuries owing to shearing effects from shaking, and anoxic injuries. MR imaging has a definite complementary role in the evaluation of acute intracranial trauma in child abuse victims

Aggression and Brain Asymmetries: A Theoretical Review

OpenAIRE

Rohlfs , Paloma; Ramirez, J. Martin

2006-01-01

The relationship between aggression and brain asymmetries has not been studied enough. The association between both concepts can be approached from two different perspectives. One perspective points to brain asymmetries underlying the emotion of anger and consequently aggression in normal people. Another one is concerned with the existence of brain asymmetries in aggressive people (e.g., in the case of suicides or psychopathies). Research on emotional processing points out the confusion betw...

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

Science.gov (United States)

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2016-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms

Migraine Subclassification via a Data-Driven Automated Approach Using Multimodality Factor Mixture Modeling of Brain Structure Measurements.

Science.gov (United States)

Schwedt, Todd J; Si, Bing; Li, Jing; Wu, Teresa; Chong, Catherine D

2017-07-01

The current subclassification of migraine is according to headache frequency and aura status. The variability in migraine symptoms, disease course, and response to treatment suggest the presence of additional heterogeneity or subclasses within migraine. The study objective was to subclassify migraine via a data-driven approach, identifying latent factors by jointly exploiting multiple sets of brain structural features obtained via magnetic resonance imaging (MRI). Migraineurs (n = 66) and healthy controls (n = 54) had brain MRI measurements of cortical thickness, cortical surface area, and volumes for 68 regions. A multimodality factor mixture model was used to subclassify MRIs and to determine the brain structural factors that most contributed to the subclassification. Clinical characteristics of subjects in each subgroup were compared. Automated MRI classification divided the subjects into two subgroups. Migraineurs in subgroup #1 had more severe allodynia symptoms during migraines (6.1 ± 5.3 vs. 3.6 ± 3.2, P = .03), more years with migraine (19.2 ± 11.3 years vs 13 ± 8.3 years, P = .01), and higher Migraine Disability Assessment (MIDAS) scores (25 ± 22.9 vs 15.7 ± 12.2, P = .04). There were not differences in headache frequency or migraine aura status between the two subgroups. Data-driven subclassification of brain MRIs based upon structural measurements identified two subgroups. Amongst migraineurs, the subgroups differed in allodynia symptom severity, years with migraine, and migraine-related disability. Since allodynia is associated with this imaging-based subclassification of migraine and prior publications suggest that allodynia impacts migraine treatment response and disease prognosis, future migraine diagnostic criteria could consider allodynia when defining migraine subgroups. © 2017 American Headache Society.

Agmatine Attenuates Brain Edema and Apoptotic Cell Death after Traumatic Brain Injury.

Science.gov (United States)

Kim, Jae Young; Lee, Yong Woo; Kim, Jae Hwan; Lee, Won Taek; Park, Kyung Ah; Lee, Jong Eun

2015-07-01

Traumatic brain injury (TBI) is associated with poor neurological outcome, including necrosis and brain edema. In this study, we investigated whether agmatine treatment reduces edema and apoptotic cell death after TBI. TBI was produced by cold injury to the cerebral primary motor cortex of rats. Agmatine was administered 30 min after injury and once daily until the end of the experiment. Animals were sacrificed for analysis at 1, 2, or 7 days after the injury. Various neurological analyses were performed to investigate disruption of the blood-brain barrier (BBB) and neurological dysfunction after TBI. To examine the extent of brain edema after TBI, the expression of aquaporins (AQPs), phosphorylation of mitogen-activated protein kinases (MAPKs), and nuclear translocation of nuclear factor-κB (NF-κB) were investigated. Our findings demonstrated that agmatine treatment significantly reduces brain edema after TBI by suppressing the expression of AQP1, 4, and 9. In addition, agmatine treatment significantly reduced apoptotic cell death by suppressing the phosphorylation of MAPKs and by increasing the nuclear translocation of NF-κB after TBI. These results suggest that agmatine treatment may have therapeutic potential for brain edema and neural cell death in various central nervous system diseases.

Précis of The brain and emotion.

Science.gov (United States)

Rolls, E T

2000-04-01

The topics treated in The brain and emotion include the definition, nature, and functions of emotion (Ch. 3); the neural bases of emotion (Ch. 4); reward, punishment, and emotion in brain design (Ch. 10); a theory of consciousness and its application to understanding emotion and pleasure (Ch. 9); and neural networks and emotion-related learning (Appendix). The approach is that emotions can be considered as states elicited by reinforcers (rewards and punishers). This approach helps with understanding the functions of emotion, with classifying different emotions, and in understanding what information-processing systems in the brain are involved in emotion, and how they are involved. The hypothesis is developed that brains are designed around reward- and punishment-evaluation systems, because this is the way that genes can build a complex system that will produce appropriate but flexible behavior to increase fitness (Ch. 10). By specifying goals rather than particular behavioral patterns of responses, genes leave much more open the possible behavioral strategies that might be required to increase fitness. The importance of reward and punishment systems in brain design also provides a basis for understanding the brain mechanisms of motivation, as described in Chapters 2 for appetite and feeding, 5 for brain-stimulation reward, 6 for addiction, 7 for thirst, and 8 for sexual behavior.

Near-infrared spectroscopy (NIRS - electroencephalography (EEG based brain-state dependent electrotherapy (BSDE: A computational approach based on excitation-inhibition balance hypothesis

Directory of Open Access Journals (Sweden)

Snigdha Dagar

2016-08-01

Full Text Available Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The post stroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG and functional-near-infrared spectroscopy (fNIRS can be leveraged for Brain State Dependent Electrotherapy (BSDE. In this hypothesis and theory article, we propose a computational approach based on excitation-inhibition (E-I balance hypothesis to objectively quantify the post stroke individual brain state using online fNIRS-EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local excitation-inhibition (that is the ratio of Glutamate/GABA which may be targeted with NIBS using a computational pipeline that includes individual forward models to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons which can be captured with excitation-inhibition based brain models. Furthermore, E-I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing which can then be implicated in changes in function. We first review evidence that shows how this local imbalance between excitation-inhibition leading to functional dysfunction can be restored in targeted sites with NIBS (Motor Cortex, Somatosensory Cortex resulting in large scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Secondly, we show evidence how BSDE based on inhibition–excitation balance hypothesis may target a specific brain site or network as an adjuvant treatment

OCT imaging of acute vascular changes following mild traumatic brain injury in mice (Conference Presentation)

Science.gov (United States)

Chico-Calero, Isabel; Shishkov, Milen; Welt, Jonathan; Blatter, Cedric; Vakoc, Benjamin J.

2016-03-01

While most people recover completely from mild traumatic brain injuries (mTBIs) and concussions, a subset develop lasting neurological disorders. Understanding the complex pathophysiology of these injuries is critical to developing improved prognostic and therapeutic approaches. Multiple studies have shown that the structure and perfusion of brain vessels are altered after mTBI. It is possible that these vascular injuries contribute to or trigger neurodegeneration. Intravital microscopy and mouse models of TBI offer a powerful platform to study the vascular component of mTBI. Because optical coherence tomography based angiography is based on perfusion contrast and is not significantly degraded by vessel leakage or blood brain barrier disruption, it is uniquely suited to studies of brain perfusion in the setting of trauma. However, existing TBI imaging models require surgical exposure of the brain at the time of injury which conflates TBI-related vascular changes with those caused by surgery. In this work, we describe a modified cranial window preparation based on a flexible, transparent polyurethane membrane. Impact injuries were delivered directly through this membrane, and imaging was performed immediately after injury without the need for additional surgical procedures. Using this model, we demonstrate that mTBI induces a transient cessation of flow in the capillaries and smaller vessels near the injury point. Reperfusion is observed in all animals within 3 hours of injury. This work describes new insight into the transient vascular changes induced by mTBI, and demonstrates more broadly the utility of the OCT/polyurethane window model platform in preclinical studies of mTBI.

Hemorrhagic brain metastases

International Nuclear Information System (INIS)

Takahashi, Motoichiro; Takekawa, S.D.; Suzuki, Kenzo

1986-01-01

Tumor hemorrhage on computed tomography (CT) was found in 14 patients with brain metastases (7 % of two hundred patients with brain metastases), from April 1979 to July 1983. Primary foci of these lesions were the lung (6 patients), breast (2), kidney (2), uterus (2), colon (1) and adrenal gland (1). ''Stroke'' syndrome was the initial presenting symptom in 3 patients; neurological focal sign or symptoms of increased intracranial pressure in the remaining patients. CT demonstrated peritumoral hemorrhage in all patients with solid mass, intratumoral hemorrhage in a few patients and also cerebral or ventricular hemorrhage, which was fatal complication, in 2 patients (colon and breast cancers). A cystic mass with fluid-blood level was noted in a patient with breast cancer. Several predisposing factors including chemotherapy, thrombocytopenia, radiotherapy or combination of these were recognized in 8 patients. Of these, chemotherapy was the most causative factor of tumor hemorrhage. Brain irradiation for hemorrhagic brain metastases was effective for prolongation of mean survival time of these patients as follows; 10 months in irradiated group, whereas 1.5 months in non-irradiated group. (author)

Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease

Directory of Open Access Journals (Sweden)

LIU Xue-na

2012-08-01

Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.

Mapping remodeling of thalamocortical projections in the living reeler mouse brain by diffusion tractography

Science.gov (United States)

Harsan, Laura-Adela; Dávid, Csaba; Reisert, Marco; Schnell, Susanne; Hennig, Jürgen; von Elverfeldt, Dominik; Staiger, Jochen F.

2013-01-01

A major challenge in neuroscience is to accurately decipher in vivo the entire brain circuitry (connectome) at a microscopic level. Currently, the only methodology providing a global noninvasive window into structural brain connectivity is diffusion tractography. The extent to which the reconstructed pathways reflect realistic neuronal networks depends, however, on data acquisition and postprocessing factors. Through a unique combination of approaches, we designed and evaluated herein a framework for reliable fiber tracking and mapping of the living mouse brain connectome. One important wiring scheme, connecting gray matter regions and passing fiber-crossing areas, was closely examined: the lemniscal thalamocortical (TC) pathway. We quantitatively validated the TC projections inferred from in vivo tractography with correlative histological axonal tracing in the same wild-type and reeler mutant mice. We demonstrated noninvasively that changes in patterning of the cortical sheet, such as highly disorganized cortical lamination in reeler, led to spectacular compensatory remodeling of the TC pathway. PMID:23610438

Brain Network Modelling

DEFF Research Database (Denmark)

Andersen, Kasper Winther

Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

Novel whole brain segmentation and volume estimation using quantitative MRI

International Nuclear Information System (INIS)

West, J.; Warntjes, J.B.M.; Lundberg, P.

2012-01-01

Brain segmentation and volume estimation of grey matter (GM), white matter (WM) and cerebro-spinal fluid (CSF) are important for many neurological applications. Volumetric changes are observed in multiple sclerosis (MS), Alzheimer's disease and dementia, and in normal aging. A novel method is presented to segment brain tissue based on quantitative magnetic resonance imaging (qMRI) of the longitudinal relaxation rate R 1 , the transverse relaxation rate R 2 and the proton density, PD. Previously reported qMRI values for WM, GM and CSF were used to define tissues and a Bloch simulation performed to investigate R 1 , R 2 and PD for tissue mixtures in the presence of noise. Based on the simulations a lookup grid was constructed to relate tissue partial volume to the R 1 -R 2 -PD space. The method was validated in 10 healthy subjects. MRI data were acquired using six resolutions and three geometries. Repeatability for different resolutions was 3.2% for WM, 3.2% for GM, 1.0% for CSF and 2.2% for total brain volume. Repeatability for different geometries was 8.5% for WM, 9.4% for GM, 2.4% for CSF and 2.4% for total brain volume. We propose a new robust qMRI-based approach which we demonstrate in a patient with MS. (orig.)

Novel whole brain segmentation and volume estimation using quantitative MRI

Energy Technology Data Exchange (ETDEWEB)

West, J. [Linkoeping University, Radiation Physics, Department of Medical and Health Sciences, Faculty of Health Sciences, Linkoeping (Sweden); Linkoeping University, Center for Medical Imaging Science and Visualization (CMIV), Linkoeping (Sweden); SyntheticMR AB, Linkoeping (Sweden); Warntjes, J.B.M. [Linkoeping University, Center for Medical Imaging Science and Visualization (CMIV), Linkoeping (Sweden); SyntheticMR AB, Linkoeping (Sweden); Linkoeping University and Department of Clinical Physiology UHL, County Council of Oestergoetland, Clinical Physiology, Department of Medical and Health Sciences, Faculty of Health Sciences, Linkoeping (Sweden); Lundberg, P. [Linkoeping University, Center for Medical Imaging Science and Visualization (CMIV), Linkoeping (Sweden); Linkoeping University and Department of Radiation Physics UHL, County Council of Oestergoetland, Radiation Physics, Department of Medical and Health Sciences, Faculty of Health Sciences, Linkoeping (Sweden); Linkoeping University and Department of Radiology UHL, County Council of Oestergoetland, Radiology, Department of Medical and Health Sciences, Faculty of Health Sciences, Linkoeping (Sweden)

2012-05-15

Brain segmentation and volume estimation of grey matter (GM), white matter (WM) and cerebro-spinal fluid (CSF) are important for many neurological applications. Volumetric changes are observed in multiple sclerosis (MS), Alzheimer's disease and dementia, and in normal aging. A novel method is presented to segment brain tissue based on quantitative magnetic resonance imaging (qMRI) of the longitudinal relaxation rate R{sub 1}, the transverse relaxation rate R{sub 2} and the proton density, PD. Previously reported qMRI values for WM, GM and CSF were used to define tissues and a Bloch simulation performed to investigate R{sub 1}, R{sub 2} and PD for tissue mixtures in the presence of noise. Based on the simulations a lookup grid was constructed to relate tissue partial volume to the R{sub 1}-R{sub 2}-PD space. The method was validated in 10 healthy subjects. MRI data were acquired using six resolutions and three geometries. Repeatability for different resolutions was 3.2% for WM, 3.2% for GM, 1.0% for CSF and 2.2% for total brain volume. Repeatability for different geometries was 8.5% for WM, 9.4% for GM, 2.4% for CSF and 2.4% for total brain volume. We propose a new robust qMRI-based approach which we demonstrate in a patient with MS. (orig.)

Frameless Stereotactic Insertion of Viewsite Brain Access System with Microscope-Mounted Tracking Device for Resection of Deep Brain Lesions: Technical Report

OpenAIRE

White, Tim; Chakraborty, Shamik; Lall, Rohan; Fanous, Andrew A; Boockvar, John; Langer, David J

2017-01-01

The surgical management of deep brain tumors is often challenging due to the limitations of stereotactic needle biopsies and the morbidity associated with transcortical approaches. We present a novel microscopic navigational technique utilizing the Viewsite Brain Access System (VBAS) (Vycor Medical, Boca Raton, FL, USA) for resection of a deep parietal periventricular high-grade glioma as well as another glioma and a cavernoma with no related morbidity. The approach utilized a navigational tr...

Transfection of rat brain endothelium in a primary culture model of the blood-brain barrier at different states of barrier maturity

DEFF Research Database (Denmark)

Larsen, Annette Burkhart; Thomsen, Louiza Bohn; Lichota, Jacek

Central nervous system diseases are becoming more prevalent. Unfortunately, the treatment of CNS diseases is often rendered complicated by the inability of many drugs of therapeutic relevance to cross the blood-brain barrier (BBB). In order to enhance drug delivery to the brain, different...... approaches have been developed. Gene therapy could be a promising and novel approach to overcome the restricting properties of the BBB to polypeptides and proteins. Gene therapy is based on the delivery of genetic material into brain capillary endothelial cells (BCECs), which, theoretically, will result...... in expression and secretion of the recombinant protein from the BCECs and into the brain, thus turning BCECs into small recombinant protein factories. In this study, the possibility of using BCECs as small factories for recombinant protein production was investigated. To mimic the in-vivo situation as closely...

Brain Stimulation and the Role of the Right Hemisphere in Aphasia Recovery.

Science.gov (United States)

Turkeltaub, Peter E

2015-11-01

Aphasia is a common consequence of left hemisphere stroke and causes a disabling loss of language and communication ability. Current treatments for aphasia are inadequate, leaving a majority of aphasia sufferers with ongoing communication difficulties for the rest of their lives. In the past decade, two forms of noninvasive brain stimulation, repetitive transcranial magnetic stimulation and transcranial direct current stimulation, have emerged as promising new treatments for aphasia. The most common brain stimulation protocols attempt to inhibit the intact right hemisphere based on the hypothesis that maladaptive activity in the right hemisphere limits language recovery in the left. There is now sufficient evidence to demonstrate that this approach, at least for repetitive transcranial magnetic stimulation, improves specific language abilities in aphasia. However, the biological mechanisms that produce these behavioral improvements remain poorly understood. Taken in the context of the larger neurobiological literature on aphasia recovery, the role of the right hemisphere in aphasia recovery remains unclear. Additional research is needed to understand biological mechanisms of recovery, in order to optimize brain stimulation treatments for aphasia. This article summarizes the current evidence on noninvasive brain stimulation methods for aphasia and the neuroscientific considerations surrounding treatments using right hemisphere inhibition. Suggestions are provided for further investigation and for clinicians whose patients ask about brain stimulation treatments for aphasia.

Management of melanoma brain metastases in the era of targeted therapy.

Science.gov (United States)

Shapiro, Daniela Gonsalves; Samlowski, Wolfram E

2011-01-01

Disseminated metastatic disease, including brain metastases, is commonly encountered in malignant melanoma. The classical treatment approach for melanoma brain metastases has been neurosurgical resection followed by whole brain radiotherapy. Traditionally, if lesions were either too numerous or surgical intervention would cause substantial neurologic deficits, patients were either treated with whole brain radiotherapy or referred to hospice and supportive care. Chemotherapy has not proven effective in treating brain metastases. Improvements in surgery, radiosurgery, and new drug discoveries have provided a wider range of treatment options. Additionally, recently discovered mutations in the melanoma genome have led to the development of "targeted therapy." These vastly improved options are resulting in novel treatment paradigms for approaching melanoma brain metastases in patients with and without systemic metastatic disease. It is therefore likely that improved survival can currently be achieved in at least a subset of melanoma patients with brain metastases.

Management of Melanoma Brain Metastases in the Era of Targeted Therapy

International Nuclear Information System (INIS)

Shapiro, D. G.; Samlowski, W. E.; Samlowski, W. E.; Samlowski, W. E.; Samlowski, W. E.

2011-01-01

Disseminated metastatic disease, including brain metastases, is commonly encountered in malignant melanoma. The classical treatment approach for melanoma brain metastases has been neurosurgical resection followed by whole brain radiotherapy. Traditionally, if lesions were either too numerous or surgical intervention would cause substantial neurologic deficits, patients were either treated with whole brain radiotherapy or referred to hospice and supportive care. Chemotherapy has not proven effective in treating brain metastases. Improvements in surgery, radiosurgery, and new drug discoveries have provided a wider range of treatment options. Additionally, recently discovered mutations in the melanoma genome have led to the development of "targeted therapy."These vastly improved options are resulting in novel treatment paradigms for approaching melanoma brain metastases in patients with and without systemic metastatic disease. It is therefore likely that improved survival can currently be achieved in at least a subset of melanoma patients with brain metastases.

Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach

Science.gov (United States)

Yu, Nanyang; Wei, Si; Li, Meiying; Yang, Jingping; Li, Kan; Jin, Ling; Xie, Yuwei; Giesy, John P.; Zhang, Xiaowei; Yu, Hongxia

2016-04-01

Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects.

A demonstration of a low cost approach to security at shipping facilities and ports

Science.gov (United States)

Huck, Robert C.; Al Akkoumi, Mouhammad K.; Herath, Ruchira W.; Sluss, James J., Jr.; Radhakrishnan, Sridhar; Landers, Thomas L.

2010-04-01

Government funding for the security at shipping facilities and ports is limited so there is a need for low cost scalable security systems. With over 20 million sea, truck, and rail containers entering the United States every year, these facilities pose a large risk to security. Securing these facilities and monitoring the variety of traffic that enter and leave is a major task. To accomplish this, the authors have developed and fielded a low cost fully distributed building block approach to port security at the inland Port of Catoosa in Oklahoma. Based on prior work accomplished in the design and fielding of an intelligent transportation system in the United States, functional building blocks, (e.g. Network, Camera, Sensor, Display, and Operator Console blocks) can be assembled, mixed and matched, and scaled to provide a comprehensive security system. The following functions are demonstrated and scaled through analysis and demonstration: Barge tracking, credential checking, container inventory, vehicle tracking, and situational awareness. The concept behind this research is "any operator on any console can control any device at any time."

Neuropeptide processing in regional brain slices: Effect of conformation and sequence

Energy Technology Data Exchange (ETDEWEB)

Li, Z.W.; Bijl, W.A.; van Nispen, J.W.; Brendel, K.; Davis, T.P. (Univ. of Arizona, Tucson (USA))

1990-05-01

The central enzymatic stability of des-enkephalin-gamma-endorphin and its synthetic analogs (cycloN alpha 6, C delta 11)beta-endorphin-(6-17) and (Pro7, Lys(Ac)9)-beta-endorphin(6-17) was studied in vitro using a newly developed, regionally dissected rat brain slice, time course incubation procedure. Tissue slice viability was estimated as the ability of the brain slice to take up or release gamma-(3H)aminobutyric acid after high K+ stimulation. Results demonstrated stability of uptake/release up to 5 hr of incubation, suggesting tissue viability over this period. The estimated half-life of peptides based on the results obtained in our incubation protocol suggest that the peptides studied are metabolized at different rates in the individual brain regions tested. A good correlation exists between the high enzyme activity of neutral endopeptidase and the rapid degradation of des-enkephalin-gamma-endorphin and (cycloN alpha 6, C delata 11)beta-endorphin-(6-17) in caudate putamen. Proline substitution combined with lysine acetylation appears to improve resistance to enzymatic metabolism in caudate putamen and hypothalamus. However, cyclization of des-enkephalin-gamma-endorphin forming an amide bond between the alpha-NH2 of the N-terminal threonine and the gamma-COOH of glutamic acid did not improve peptide stability in any brain region tested. The present study has shown that the brain slice technique is a valid and unique approach to study neuropeptide metabolism in small, discrete regions of rat brain where peptides, peptidases and receptors are colocalized and that specific structural modifications can improve peptide stability.

"Celebration of the Neurons": The Application of Brain Based Learning in Classroom Environment

Science.gov (United States)

Duman, Bilal

2007-01-01

The purpose of this study is to investigate approaches and techniques related to how brain based learning used in classroom atmosphere. This general purpose were answered following the questions: (1) What is the aim of brain based learning? (2) What are general approaches and techniques that brain based learning used? and (3) How should be used…

Mechanisms that determine the internal environment of the developing brain: a transcriptomic, functional and ultrastructural approach.

Science.gov (United States)

Liddelow, Shane A; Dziegielewska, Katarzyna M; Ek, C Joakim; Habgood, Mark D; Bauer, Hannelore; Bauer, Hans-Christian; Lindsay, Helen; Wakefield, Matthew J; Strazielle, Nathalie; Kratzer, Ingrid; Møllgård, Kjeld; Ghersi-Egea, Jean-François; Saunders, Norman R

2013-01-01

We provide comprehensive identification of embryonic (E15) and adult rat lateral ventricular choroid plexus transcriptome, with focus on junction-associated proteins, ionic influx transporters and channels. Additionally, these data are related to new structural and previously published permeability studies. Results reveal that most genes associated with intercellular junctions are expressed at similar levels at both ages. In total, 32 molecules known to be associated with brain barrier interfaces were identified. Nine claudins showed unaltered expression, while two claudins (6 and 8) were expressed at higher levels in the embryo. Expression levels for most cytoplasmic/regulatory adaptors (10 of 12) were similar at the two ages. A few junctional genes displayed lower expression in embryos, including 5 claudins, occludin and one junctional adhesion molecule. Three gap junction genes were enriched in the embryo. The functional effectiveness of these junctions was assessed using blood-delivered water-soluble tracers at both the light and electron microscopic level: embryo and adult junctions halted movement of both 286Da and 3kDa molecules into the cerebrospinal fluid (CSF). The molecular identities of many ion channel and transporter genes previously reported as important for CSF formation and secretion in the adult were demonstrated in the embryonic choroid plexus (and validated with immunohistochemistry of protein products), but with some major age-related differences in expression. In addition, a large number of previously unidentified ion channel and transporter genes were identified for the first time in plexus epithelium. These results, in addition to data obtained from electron microscopical and physiological permeability experiments in immature brains, indicate that exchange between blood and CSF is mainly transcellular, as well-formed tight junctions restrict movement of small water-soluble molecules from early in development. These data strongly indicate the

Significance of the Feuerstein approach in neurocognitive rehabilitation.

Science.gov (United States)

Lebeer, Jo

2016-06-18

procedure of learning propensity assessment device uses visuo-spatial and verbal tasks known from neuropsychological assessment (such as Rey's complex figure drawing), as well as a in a pre-test - brief intervention - post-test format. Cognitive activation is done in various ways: a paper-and-pencil relatively content-free program called "instrumental enrichment", with transfer of learned principles into daily life situations, followed by metacognitive feedback. Four case histories of acquired brain damage are analyzed: a 19 year old man with extensive post-astrocytoma frontotemporal brain lesions; a 19 year old man with bilateral frontal and right temporal and parieto-occipital parenchymatous destruction after a traumatic brain injury; a 24 year old man with hemispherectomy for intractable epilepsy because of Sturge-Weber syndrome; and a 30-year old man with left porencephalic cyst after cerebral hemorrhage. Structural cognitive improvement could be demonstrated in positive change scores in visuo-spatial memory, associative and verbal memory, abstract thinking, and organizing tasks, even more than 10 years post-TBI. In some cases a rise in IQ has been documented. Improvement in daily life functioning and academic skills (re)learning has also been seen. Though impossible to claim scientific evidence, the case histories nevertheless suggest the importance of interactive assessment in designing intervention programs which have sufficient intensity, frequency, duration and consistency of mediation; furthermore, an essential ingredient is the ecological approach which requires working with the patient and the whole network around; a firm "belief system" or that modifiability is possible even with severe brain damage and many years after the injury; a cognitive, metacognitive and executive approach, and a quality of interaction according to criteria of mediated learning. They suggest that Feuerstein approach may offer interesting perspectives to cognitive rehabilitation. More

A four quadrant whole brain approach in innovation and ...

African Journals Online (AJOL)

Engineering curricula traditionally favour the development of analytical and technical skills. There is a worldwide recognition that this bias needs to be addressed to also develop "non-technical" skills. During 1999 the Herrmann Brain Dominance Instrument (HBDI), by which human thinking style preferences can be ...

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions

DEFF Research Database (Denmark)

Thut, Gregor; Bergmann, Til Ole; Fröhlich, Flavio

2017-01-01

of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online...... and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned......Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension...

The Virtual Brain Integrates Computational Modeling and Multimodal Neuroimaging

Science.gov (United States)

Schirner, Michael; McIntosh, Anthony R.; Jirsa, Viktor K.

2013-01-01

Abstract Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected—ideally functionally relevant—aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) (www.thevirtualbrain.org), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept. PMID:23442172

Minireview of Stereoselective Brain Imaging

DEFF Research Database (Denmark)

Smith, Donald F.; Jakobsen, Steen

2014-01-01

Stereoselectivity is a fundamental principle in living systems. Stereoselectivity reflects the dependence of molecular processes on the spatial orientation of constituent atoms. Stereoselective processes govern many aspects of brain function and direct the course of many psychotropic drugs. Today......, modern imaging techniques such as SPECT and PET provide a means for studying stereoselective processes in the living brain. Chemists have prepared numerous radiolabelled stereoisomers for use in SPECT and PET in order to explore various molecular processes in the living brain of anesthetized laboratory...... animals and awake humans. The studies have demonstrated how many aspects of neurotransmission consist of crucial stereoselective events that can affect brain function in health and disease. Here, we present a brief account of those findings in hope of stimulating further interest in the vital topic....

A proteomic network approach across the ALS-FTD disease spectrum resolves clinical phenotypes and genetic vulnerability in human brain.

Science.gov (United States)

Umoh, Mfon E; Dammer, Eric B; Dai, Jingting; Duong, Duc M; Lah, James J; Levey, Allan I; Gearing, Marla; Glass, Jonathan D; Seyfried, Nicholas T

2018-01-01

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are neurodegenerative diseases with overlap in clinical presentation, neuropathology, and genetic underpinnings. The molecular basis for the overlap of these disorders is not well established. We performed a comparative unbiased mass spectrometry-based proteomic analysis of frontal cortical tissues from postmortem cases clinically defined as ALS, FTD, ALS and FTD (ALS/FTD), and controls. We also included a subset of patients with the C9orf72 expansion mutation, the most common genetic cause of both ALS and FTD Our systems-level analysis of the brain proteome integrated both differential expression and co-expression approaches to assess the relationship of these differences to clinical and pathological phenotypes. Weighted co-expression network analysis revealed 15 modules of co-expressed proteins, eight of which were significantly different across the ALS-FTD disease spectrum. These included modules associated with RNA binding proteins, synaptic transmission, and inflammation with cell-type specificity that showed correlation with TDP-43 pathology and cognitive dysfunction. Modules were also examined for their overlap with TDP-43 protein-protein interactions, revealing one module enriched with RNA-binding proteins and other causal ALS genes that increased in FTD/ALS and FTD cases. A module enriched with astrocyte and microglia proteins was significantly increased in ALS cases carrying the C9orf72 mutation compared to sporadic ALS cases, suggesting that the genetic expansion is associated with inflammation in the brain even without clinical evidence of dementia. Together, these findings highlight the utility of integrative systems-level proteomic approaches to resolve clinical phenotypes and genetic mechanisms underlying the ALS-FTD disease spectrum in human brain. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

Brain-computer interface for alertness estimation and improving

Science.gov (United States)

Hramov, Alexander; Maksimenko, Vladimir; Hramova, Marina

2018-02-01

Using wavelet analysis of the signals of electrical brain activity (EEG), we study the processes of neural activity, associated with perception of visual stimuli. We demonstrate that the brain can process visual stimuli in two scenarios: (i) perception is characterized by destruction of the alpha-waves and increase in the high-frequency (beta) activity, (ii) the beta-rhythm is not well pronounced, while the alpha-wave energy remains unchanged. The special experiments show that the motivation factor initiates the first scenario, explained by the increasing alertness. Based on the obtained results we build the brain-computer interface and demonstrate how the degree of the alertness can be estimated and controlled in real experiment.

A Development Architecture for Serious Games Using BCI (Brain Computer Interface Sensors

Directory of Open Access Journals (Sweden)

Kyhyun Um

2012-11-01

Full Text Available Games that use brainwaves via brain–computer interface (BCI devices, to improve brain functions are known as BCI serious games. Due to the difficulty of developing BCI serious games, various BCI engines and authoring tools are required, and these reduce the development time and cost. However, it is desirable to reduce the amount of technical knowledge of brain functions and BCI devices needed by game developers. Moreover, a systematic BCI serious game development process is required. In this paper, we present a methodology for the development of BCI serious games. We describe an architecture, authoring tools, and development process of the proposed methodology, and apply it to a game development approach for patients with mild cognitive impairment as an example. This application demonstrates that BCI serious games can be developed on the basis of expert-verified theories.

A Development Architecture for Serious Games Using BCI (Brain Computer Interface) Sensors

Science.gov (United States)

Sung, Yunsick; Cho, Kyungeun; Um, Kyhyun

2012-01-01

Games that use brainwaves via brain–computer interface (BCI) devices, to improve brain functions are known as BCI serious games. Due to the difficulty of developing BCI serious games, various BCI engines and authoring tools are required, and these reduce the development time and cost. However, it is desirable to reduce the amount of technical knowledge of brain functions and BCI devices needed by game developers. Moreover, a systematic BCI serious game development process is required. In this paper, we present a methodology for the development of BCI serious games. We describe an architecture, authoring tools, and development process of the proposed methodology, and apply it to a game development approach for patients with mild cognitive impairment as an example. This application demonstrates that BCI serious games can be developed on the basis of expert-verified theories. PMID:23202227

Brain inspired hardware architectures - Can they be used for particle physics ?

CERN Multimedia

CERN. Geneva

2016-01-01

After their inception in the 1940s and several decades of moderate success, artificial neural networks have recently demonstrated impressive achievements in analysing big data volumes. Wide and deep network architectures can now be trained using high performance computing systems, graphics card clusters in particular. Despite their successes these state-of-the-art approaches suffer from very long training times and huge energy consumption, in particular during the training phase. The biological brain can perform similar and superior classification tasks in the space and time domains, but at the same time exhibits very low power consumption, rapid unsupervised learning capabilities and fault tolerance. In the talk the differences between classical neural networks and neural circuits in the brain will be presented. Recent hardware implementations of neuromorphic computing systems and their applications will be shown. Finally, some initial ideas to use accelerated neural architectures as trigger processors i...

Insights into Brain Glycogen Metabolism: THE STRUCTURE OF HUMAN BRAIN GLYCOGEN PHOSPHORYLASE.

Science.gov (United States)

Mathieu, Cécile; Li de la Sierra-Gallay, Ines; Duval, Romain; Xu, Ximing; Cocaign, Angélique; Léger, Thibaut; Woffendin, Gary; Camadro, Jean-Michel; Etchebest, Catherine; Haouz, Ahmed; Dupret, Jean-Marie; Rodrigues-Lima, Fernando

2016-08-26

Brain glycogen metabolism plays a critical role in major brain functions such as learning or memory consolidation. However, alteration of glycogen metabolism and glycogen accumulation in the brain contributes to neurodegeneration as observed in Lafora disease. Glycogen phosphorylase (GP), a key enzyme in glycogen metabolism, catalyzes the rate-limiting step of glycogen mobilization. Moreover, the allosteric regulation of the three GP isozymes (muscle, liver, and brain) by metabolites and phosphorylation, in response to hormonal signaling, fine-tunes glycogenolysis to fulfill energetic and metabolic requirements. Whereas the structures of muscle and liver GPs have been known for decades, the structure of brain GP (bGP) has remained elusive despite its critical role in brain glycogen metabolism. Here, we report the crystal structure of human bGP in complex with PEG 400 (2.5 Å) and in complex with its allosteric activator AMP (3.4 Å). These structures demonstrate that bGP has a closer structural relationship with muscle GP, which is also activated by AMP, contrary to liver GP, which is not. Importantly, despite the structural similarities between human bGP and the two other mammalian isozymes, the bGP structures reveal molecular features unique to the brain isozyme that provide a deeper understanding of the differences in the activation properties of these allosteric enzymes by the allosteric effector AMP. Overall, our study further supports that the distinct structural and regulatory properties of GP isozymes contribute to the different functions of muscle, liver, and brain glycogen. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

TECHNOLOGIES OF BRAIN IMAGES PROCESSING