Exercise, Energy Intake, Glucose Homeostasis, and the Brain

PubMed Central

van Praag, Henriette; Fleshner, Monika; Schwartz, Michael W.

2014-01-01

Here we summarize topics covered in an SFN symposium that considered how and why exercise and energy intake affect neuroplasticity and, conversely, how the brain regulates peripheral energy metabolism. This article is not a comprehensive review of the subject, but rather a view of how the authors' findings fit into a broader context. Emerging findings elucidate cellular and molecular mechanisms by which exercise and energy intake modify the plasticity of neural circuits in ways that affect brain health. By enhancing neurogenesis, synaptic plasticity and neuronal stress robustness, exercise and intermittent energy restriction/fasting may optimize brain function and forestall metabolic and neurodegenerative diseases. Moreover, brain-centered glucoregulatory and immunomodulating systems that mediate peripheral health benefits of intermittent energetic challenges have recently been described. A better understanding of adaptive neural response pathways activated by energetic challenges will enable the development and optimization of interventions to reduce the burden of disease in our communities. PMID:25392482

Neuroanatomy and Global Neuroscience.

PubMed

DeFelipe, Javier

2017-07-05

Our brains are like a dense forest-a complex, seemingly impenetrable terrain of interacting cells mediating cognition and behavior. However, we should view the challenge of understanding the brain with optimism, provided that we choose appropriate strategies for the development of global neuroscience. Copyright © 2017 Elsevier Inc. All rights reserved.

Docosahexaenoic Acid and Cognition throughout the Lifespan

PubMed Central

Weiser, Michael J.; Butt, Christopher M.; Mohajeri, M. Hasan

2016-01-01

Docosahexaenoic acid (DHA) is the predominant omega-3 (n-3) polyunsaturated fatty acid (PUFA) found in the brain and can affect neurological function by modulating signal transduction pathways, neurotransmission, neurogenesis, myelination, membrane receptor function, synaptic plasticity, neuroinflammation, membrane integrity and membrane organization. DHA is rapidly accumulated in the brain during gestation and early infancy, and the availability of DHA via transfer from maternal stores impacts the degree of DHA incorporation into neural tissues. The consumption of DHA leads to many positive physiological and behavioral effects, including those on cognition. Advanced cognitive function is uniquely human, and the optimal development and aging of cognitive abilities has profound impacts on quality of life, productivity, and advancement of society in general. However, the modern diet typically lacks appreciable amounts of DHA. Therefore, in modern populations, maintaining optimal levels of DHA in the brain throughout the lifespan likely requires obtaining preformed DHA via dietary or supplemental sources. In this review, we examine the role of DHA in optimal cognition during development, adulthood, and aging with a focus on human evidence and putative mechanisms of action. PMID:26901223

Clinical implementation of stereotaxic brain implant optimization

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

Rosenow, U.F.; Wojcicka, J.B.

1991-03-01

This optimization method for stereotaxic brain implants is based on seed/strand configurations of the basic type developed for the National Cancer Institute (NCI) atlas of regular brain implants. Irregular target volume shapes are determined from delineation in a stack of contrast enhanced computed tomography scans. The neurosurgeon may then select up to ten directions, or entry points, of surgical approach of which the program finds the optimal one under the criterion of smallest target volume diameter. Target volume cross sections are then reconstructed in 5-mm-spaced planes perpendicular to the implantation direction defined by the entry point and the target volumemore » center. This information is used to define a closed line in an implant cross section along which peripheral seed strands are positioned and which has now an irregular shape. Optimization points are defined opposite peripheral seeds on the target volume surface to which the treatment dose rate is prescribed. Three different optimization algorithms are available: linear least-squares programming, quadratic programming with constraints, and a simplex method. The optimization routine is implemented into a commercial treatment planning system. It generates coordinate and source strength information of the optimized seed configurations for further dose rate distribution calculation with the treatment planning system, and also the coordinate settings for the stereotaxic Brown-Roberts-Wells (BRW) implantation device.« less

Summary of Research Findings on Children's Developmental Health = Resume des conclusions de la recherche sur la sante developpementale des effants.

ERIC Educational Resources Information Center

Bertrand, Jane

This kit is comprised of bilingual resources for child caregivers related to nourishing and nurturing a child's brain for optimal neurodevelopmental health. The kit is the result of a 30-month project to synthesize research on brain development and to develop resources in support of excellent caregiver practice in Canada. The kit contains the…

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

PubMed

Studholme, Colin

2011-08-15

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

Enhancing health leadership performance using neurotherapy.

PubMed

Swingle, Paul G; Hartney, Elizabeth

2018-05-01

The discovery of neuroplasticity means the brain can change, functionally, in response to the environment and to learning. While individuals can develop harmful patterns of brain activity in response to stressors, they can also learn to modify or control neurological conditions associated with specific behaviors. Neurotherapy is one way of changing brain functioning to modify troubling conditions which can impair leadership performance, through responding to feedback on their own brain activity, and enhancing optimal leadership functioning through learning to maximize such cognitive strengths as mental efficiency, focus, creativity, perseverance, and executive functioning. The present article outlines the application of the concept of optimal performance training to organizational leadership in a healthcare context, by describing approaches to neurotherapy and illustrating their application through a case study of a health leader learning to overcome the neurological and emotional sequelae of workplace stress and trauma.

Intraoperative virtual brain counseling

NASA Astrophysics Data System (ADS)

Jiang, Zhaowei; Grosky, William I.; Zamorano, Lucia J.; Muzik, Otto; Diaz, Fernando

1997-06-01

Our objective is to offer online real-tim e intelligent guidance to the neurosurgeon. Different from traditional image-guidance technologies that offer intra-operative visualization of medical images or atlas images, virtual brain counseling goes one step further. It can distinguish related brain structures and provide information about them intra-operatively. Virtual brain counseling is the foundation for surgical planing optimization and on-line surgical reference. It can provide a warning system that alerts the neurosurgeon if the chosen trajectory will pass through eloquent brain areas. In order to fulfill this objective, tracking techniques are involved for intra- operativity. Most importantly, a 3D virtual brian environment, different from traditional 3D digitized atlases, is an object-oriented model of the brain that stores information about different brain structures together with their elated information. An object-oriented hierarchical hyper-voxel space (HHVS) is introduced to integrate anatomical and functional structures. Spatial queries based on position of interest, line segment of interest, and volume of interest are introduced in this paper. The virtual brain environment is integrated with existing surgical pre-planning and intra-operative tracking systems to provide information for planning optimization and on-line surgical guidance. The neurosurgeon is alerted automatically if the planned treatment affects any critical structures. Architectures such as HHVS and algorithms, such as spatial querying, normalizing, and warping are presented in the paper. A prototype has shown that the virtual brain is intuitive in its hierarchical 3D appearance. It also showed that HHVS, as the key structure for virtual brain counseling, efficiently integrates multi-scale brain structures based on their spatial relationships.This is a promising development for optimization of treatment plans and online surgical intelligent guidance.

Commentary: physical approaches for the treatment of epilepsy: electrical and magnetic stimulation and cooling.

PubMed

Löscher, Wolfgang; Cole, Andrew J; McLean, Michael J

2009-04-01

Physical approaches for the treatment of epilepsy currently under study or development include electrical or magnetic brain stimulators and cooling devices, each of which may be implanted or applied externally. Some devices may stimulate peripheral structures, whereas others may be implanted directly into the brain. Stimulation may be delivered chronically, intermittently, or in response to either manual activation or computer-based detection of events of interest. Physical approaches may therefore ultimately be appropriate for seizure prophylaxis by causing a modification of the underlying substrate, presumably with a reduction in the intrinsic excitability of cerebral structures, or for seizure termination, by interfering with the spontaneous discharge of pathological neuronal networks. Clinical trials of device-based therapies are difficult due to ethical issues surrounding device implantation, problems with blinding, potential carryover effects that may occur in crossover designs if substrate modification occurs, and subject heterogeneity. Unresolved issues in the development of physical treatments include optimization of stimulation parameters, identification of the optimal volume of brain to be stimulated, development of adequate power supplies to stimulate the necessary areas, and a determination that stimulation itself does not promote epileptogenesis or adverse long-term effects on normal brain function.

How the Public Engages With Brain Optimization

PubMed Central

O’Connor, Cliodhna

2015-01-01

In the burgeoning debate about neuroscience’s role in contemporary society, the issue of brain optimization, or the application of neuroscientific knowledge and technologies to augment neurocognitive function, has taken center stage. Previous research has characterized media discourse on brain optimization as individualistic in ethos, pressuring individuals to expend calculated effort in cultivating culturally desirable forms of selves and bodies. However, little research has investigated whether the themes that characterize media dialogue are shared by lay populations. This article considers the relationship between the representations of brain optimization that surfaced in (i) a study of British press coverage between 2000 and 2012 and (ii) interviews with forty-eight London residents. Both data sets represented the brain as a resource that could be manipulated by the individual, with optimal brain function contingent on applying self-control in one’s lifestyle choices. However, these ideas emerged more sharply in the media than in the interviews: while most interviewees were aware of brain optimization practices, few were committed to carrying them out. The two data sets diverged in several ways: the media’s intense preoccupation with optimizing children’s brains was not apparent in lay dialogue, while interviewees elaborated beliefs about the underuse of brain tissue that showed no presence in the media. This article considers these continuities and discontinuities in light of their wider cultural significance and their implications for the media–mind relationship in public engagement with neuroscience. PMID:26336326

Computational Modeling of Micrometastatic Breast Cancer Radiation Dose Response

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

Smith, Daniel L.; Debeb, Bisrat G.; Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, Texas

Purpose: Prophylactic cranial irradiation (PCI) involves giving radiation to the entire brain with the goals of reducing the incidence of brain metastasis and improving overall survival. Experimentally, we have demonstrated that PCI prevents brain metastases in a breast cancer mouse model. We developed a computational model to expand on and aid in the interpretation of our experimental results. Methods and Materials: MATLAB was used to develop a computational model of brain metastasis and PCI in mice. Model input parameters were optimized such that the model output would match the experimental number of metastases per mouse from the unirradiated group. Anmore » independent in vivo–limiting dilution experiment was performed to validate the model. The effect of whole brain irradiation at different measurement points after tumor cells were injected was evaluated in terms of the incidence, number of metastases, and tumor burden and was then compared with the corresponding experimental data. Results: In the optimized model, the correlation between the number of metastases per mouse and the experimental fits was >95. Our attempt to validate the model with a limiting dilution assay produced 99.9% correlation with respect to the incidence of metastases. The model accurately predicted the effect of whole-brain irradiation given 3 weeks after cell injection but substantially underestimated its effect when delivered 5 days after cell injection. The model further demonstrated that delaying whole-brain irradiation until the development of gross disease introduces a dose threshold that must be reached before a reduction in incidence can be realized. Conclusions: Our computational model of mouse brain metastasis and PCI correlated strongly with our experiments with unirradiated mice. The results further suggest that early treatment of subclinical disease is more effective than irradiating established disease.« less

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2015-02-01

Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive neurological and...11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain injuries 15-17...To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing efforts include

Development of in Vivo Biomarkers for Progressive Tau Pathology after Traumatic Brain Injury

DTIC Science & Technology

2016-02-01

14. ABSTRACT Athletes in contact sports who have sustained multiple concussive traumatic brain injuries are at high risk for delayed, progressive...pugilistica 3, 11 or ‘punch drunk’ syndrome 9, 12. US military personnel 13, 14 and others who have sustained multiple concussive traumatic brain...Progress to date: To date, none of the attempts to model progressive tau pathology after repetitive concussive TBI in mice has been optimal. Ongoing

Exercise, energy intake, glucose homeostasis, and the brain.

PubMed

van Praag, Henriette; Fleshner, Monika; Schwartz, Michael W; Mattson, Mark P

2014-11-12

Here we summarize topics covered in an SFN symposium that considered how and why exercise and energy intake affect neuroplasticity and, conversely, how the brain regulates peripheral energy metabolism. This article is not a comprehensive review of the subject, but rather a view of how the authors' findings fit into a broader context. Emerging findings elucidate cellular and molecular mechanisms by which exercise and energy intake modify the plasticity of neural circuits in ways that affect brain health. By enhancing neurogenesis, synaptic plasticity and neuronal stress robustness, exercise and intermittent energy restriction/fasting may optimize brain function and forestall metabolic and neurodegenerative diseases. Moreover, brain-centered glucoregulatory and immunomodulating systems that mediate peripheral health benefits of intermittent energetic challenges have recently been described. A better understanding of adaptive neural response pathways activated by energetic challenges will enable the development and optimization of interventions to reduce the burden of disease in our communities. Copyright © 2014 the authors 0270-6474/14/3415139-11$15.00/0.

From early stress to 12-month development in very preterm infants: Preliminary findings on epigenetic mechanisms and brain growth.

PubMed

Fumagalli, Monica; Provenzi, Livio; De Carli, Pietro; Dessimone, Francesca; Sirgiovanni, Ida; Giorda, Roberto; Cinnante, Claudia; Squarcina, Letizia; Pozzoli, Uberto; Triulzi, Fabio; Brambilla, Paolo; Borgatti, Renato; Mosca, Fabio; Montirosso, Rosario

2018-01-01

Very preterm (VPT) infants admitted to Neonatal Intensive Care Unit (NICU) are at risk for altered brain growth and less-than-optimal socio-emotional development. Recent research suggests that early NICU-related stress contributes to socio-emotional impairments in VPT infants at 3 months through epigenetic regulation (i.e., DNA methylation) of the serotonin transporter gene (SLC6A4). In the present longitudinal study we assessed: (a) the effects of NICU-related stress and SLC6A4 methylation variations from birth to discharge on brain development at term equivalent age (TEA); (b) the association between brain volume at TEA and socio-emotional development (i.e., Personal-Social scale of Griffith Mental Development Scales, GMDS) at 12 months corrected age (CA). Twenty-four infants had complete data at 12-month-age. SLC6A4 methylation was measured at a specific CpG previously associated with NICU-related stress and socio-emotional stress. Findings confirmed that higher NICU-related stress associated with greater increase of SLC6A4 methylation at NICU discharge. Moreover, higher SLC6A4 discharge methylation was associated with reduced anterior temporal lobe (ATL) volume at TEA, which in turn was significantly associated with less-than-optimal GMDS Personal-Social scale score at 12 months CA. The reduced ATL volume at TEA mediated the pathway linking stress-related increase in SLC6A4 methylation at NICU discharge and socio-emotional development at 12 months CA. These findings suggest that early adversity-related epigenetic changes might contribute to the long-lasting programming of socio-emotional development in VPT infants through epigenetic regulation and structural modifications of the developing brain.

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

NASA Astrophysics Data System (ADS)

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

2008-06-01

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

Understand the cogs to understand cognition.

PubMed

Marblestone, Adam H; Wayne, Greg; Kording, Konrad P

2017-01-01

Lake et al. suggest that current AI systems lack the inductive biases that enable human learning. However, Lake et al.'s proposed biases may not directly map onto mechanisms in the developing brain. A convergence of fields may soon create a correspondence between biological neural circuits and optimization in structured architectures, allowing us to systematically dissect how brains learn.

[Experimental study of an antirabies vaccine from sheep brain tissue inactivated by UV rays (author's transl)].

PubMed

Pospeeva, N A; Morogova, V M; Gil'dina, S S; Nikolaeva, N V; Losev, M N

1975-01-01

The optimal regimen of sheep brain rabies vaccine inactivation with UV rays has been developed. The immunogenic activity of 22 experimental lots of UV-inactivated rabies vaccine was found to be considerably higher than that of commercial Fermi vaccine. The antigenic activity of the inactivated vaccine in animals was also high.

Development of solid-phase microextraction coupled with liquid chromatography for analysis of tramadol in brain tissue using its molecularly imprinted polymer.

PubMed

Habibi-Khorasani, Monireh; Mohammadpour, Amir Hooshang; Mohajeri, Seyed Ahmad

2017-02-01

In this work, performance of a molecularly imprinted polymer (MIP) as a selective solid-phase microextraction sorbent for the extraction and enrichment of tramadol in aqueous solution and rabbit brain tissue, is described. Binding properties of MIPs were studied in comparison with their nonimprinted polymer (NIP). Ten milligrams of the optimized MIP was then evaluated as a sorbent, for preconcentration, in molecularly imprinted solid-phase microextraction (MISPME) of tramadol from aqueous solution and rabbit brain tissue. The analytical method was calibrated in the range of 0.004 ppm (4 ng mL -1 ) and 10 ppm (10 μg mL -1 ) in aqueous media and in the ranges of 0.01 and 10 ppm in rabbit brain tissue, respectively. The results indicated significantly higher binding affinity of MIPs to tramadol, in comparison with NIP. The MISPME procedure was developed and optimized with a recovery of 81.12-107.54% in aqueous solution and 76.16-91.20% in rabbit brain tissue. The inter- and intra-day variation values were <8.24 and 5.06%, respectively. Finally the calibrated method was applied for determination of tramadol in real rabbit brain tissue samples after administration of a lethal dose. Our data demonstrated the potential of MISPME for rapid, sensitive and cost-effective sample analysis. Copyright © 2016 John Wiley & Sons, Ltd.

ACTIVITY-DEPENDENT, STRESS-RESPONSIVE BDNF SIGNALING AND THE QUEST FOR OPTIMAL BRAIN HEALTH AND RESILIENCE THROUGHOUT THE LIFESPAN

PubMed Central

Rothman, S. M.; Mattson, M. P.

2013-01-01

During development of the nervous system, the formation of connections (synapses) between neurons is dependent upon electrical activity in those neurons, and neurotrophic factors produced by target cells play a pivotal role in such activity-dependent sculpting of the neural networks. A similar interplay between neurotransmitter and neurotrophic factor signaling pathways mediates adaptive responses of neural networks to environmental demands in adult mammals, with the excitatory neurotransmitter glutamate and brain-derived neurotrophic factor (BDNF) being particularly prominent regulators of synaptic plasticity throughout the central nervous system. Optimal brain health throughout the lifespan is promoted by intermittent challenges such as exercise, cognitive stimulation and dietary energy restriction, that subject neurons to activity-related metabolic stress. At the molecular level, such challenges to neurons result in the production of proteins involved in neurogenesis, learning and memory and neuronal survival; examples include proteins that regulate mitochondrial biogenesis, protein quality control, and resistance of cells to oxidative, metabolic and proteotoxic stress. BDNF signaling mediates up-regulation of several such proteins including the protein chaperone GRP-78, antioxidant enzymes, the cell survival protein Bcl-2, and the DNA repair enzyme APE1. Insufficient exposure to such challenges, genetic factors may conspire to impair BDNF production and/or signaling resulting in the vulnerability of the brain to injury and neurodegenerative disorders including Alzheimer’s, Parkinson’s and Huntington’s diseases. Further, BDNF signaling is negatively regulated by glucocorticoids. Glucocorticoids impair synaptic plasticity in the brain by negatively regulating spine density, neurogenesis and long-term potentiation, effects that are potentially linked to glucocorticoid regulation of BDNF. Findings suggest that BDNF signaling in specific brain regions mediates some of the beneficial effects of exercise and energy restriction on peripheral energy metabolism and the cardiovascular system. Collectively, the findings described in this article suggest the possibility of developing prescriptions for optimal brain health based on activity-dependent BDNF signaling. PMID:23079624

Repetitive Concussions in Adolescent Athletes – Translating Clinical and Experimental Research into Perspectives on Rehabilitation Strategies

PubMed Central

Semple, Bridgette D.; Lee, Sangmi; Sadjadi, Raha; Fritz, Nora; Carlson, Jaclyn; Griep, Carrie; Ho, Vanessa; Jang, Patrice; Lamb, Annick; Popolizio, Beth; Saini, Sonia; Bazarian, Jeffrey J.; Prins, Mayumi L.; Ferriero, Donna M.; Basso, D. Michele; Noble-Haeusslein, Linda J.

2015-01-01

Sports-related concussions are particularly common during adolescence, a time when even mild brain injuries may disrupt ongoing brain maturation and result in long-term complications. A recent focus on the consequences of repetitive concussions among professional athletes has prompted the development of several new experimental models in rodents, as well as the revision of guidelines for best management of sports concussions. Here, we consider the utility of rodent models to understand the functional consequences and pathobiology of concussions in the developing brain, identifying the unique behavioral and pathological signatures of concussive brain injuries. The impact of repetitive concussions on behavioral consequences and injury progression is also addressed. In particular, we focus on the epidemiological, clinical, and experimental evidence underlying current recommendations for physical and cognitive rest after concussion, and highlight key areas in which further research is needed. Lastly, we consider how best to promote recovery after injury, recognizing that optimally timed, activity-based rehabilitative strategies may hold promise for the adolescent athlete who has sustained single or repetitive concussions. The purpose of this review is to inform the clinical research community as it strives to develop and optimize evidence-based guidelines for the concussed adolescent, in terms of both acute and long-term management. PMID:25883586

The maternal brain and its plasticity in humans

PubMed Central

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

2015-01-01

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

Vector-model-supported optimization in volumetric-modulated arc stereotactic radiotherapy planning for brain metastasis

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

Liu, Eva Sau Fan; Department of Health Technology and Informatics, The Hong Kong Polytechnic University; Wu, Vincent Wing Cheung

Long planning time in volumetric-modulated arc stereotactic radiotherapy (VMA-SRT) cases can limit its clinical efficiency and use. A vector model could retrieve previously successful radiotherapy cases that share various common anatomic features with the current case. The prsent study aimed to develop a vector model that could reduce planning time by applying the optimization parameters from those retrieved reference cases. Thirty-six VMA-SRT cases of brain metastasis (gender, male [n = 23], female [n = 13]; age range, 32 to 81 years old) were collected and used as a reference database. Another 10 VMA-SRT cases were planned with both conventional optimization and vector-model-supported optimization, followingmore » the oncologists' clinical dose prescriptions. Planning time and plan quality measures were compared using the 2-sided paired Wilcoxon signed rank test with a significance level of 0.05, with positive false discovery rate (pFDR) of less than 0.05. With vector-model-supported optimization, there was a significant reduction in the median planning time, a 40% reduction from 3.7 to 2.2 hours (p = 0.002, pFDR = 0.032), and for the number of iterations, a 30% reduction from 8.5 to 6.0 (p = 0.006, pFDR = 0.047). The quality of plans from both approaches was comparable. From these preliminary results, vector-model-supported optimization can expedite the optimization of VMA-SRT for brain metastasis while maintaining plan quality.« less

Study of the development of fetal baboon brain using magnetic resonance imaging at 3 Tesla

PubMed Central

Liu, Feng; Garland, Marianne; Duan, Yunsuo; Stark, Raymond I.; Xu, Dongrong; Dong, Zhengchao; Bansal, Ravi; Peterson, Bradley S.; Kangarlu, Alayar

2008-01-01

Direct observational data on the development of the brains of human and nonhuman primates is on remarkably scant, and most of our understanding of primate brain development is extrapolated from findings in rodent models. Magnetic resonance imaging (MRI) is a promising tool for the noninvasive, longitudinal study of the developing primate brain. We devised a protocol to scan pregnant baboons serially at 3 T for up to 3 h per session. Seven baboons were scanned 1–6 times, beginning as early as 56 days post-conceptional age, and as late as 185 days (term ~185 days). Successful scanning of the fetal baboon required careful animal preparation and anesthesia, in addition to optimization of the scanning protocol. We successfully acquired maps of relaxation times (T1 and T2) and high-resolution anatomical images of the brains of fetal baboons at multiple time points during the course of gestation. These images demonstrated the convergence of gray and white matter contrast near term, and furthermore demonstrated that the loss of contrast at that age is a consequence of the continuous change in relaxation times during fetal brain development. These data furthermore demonstrate that maps of relaxation times have clear advantages over the relaxation time weighted images for the tracking of the changes in brain structure during fetal development. This protocol for in utero MRI of fetal baboon brains will help to advance the use of nonhuman primate models to study fetal brain development longitudinally. PMID:18155925

MRI segmentation using dialectical optimization.

PubMed

dos Santos, Wellington P; de Assis, Francisco M; de Souza, Ricardo E

2009-01-01

Biology, Psychology and Social Sciences are intrinsically connected to the very roots of the development of algorithms and methods in Computational Intelligence, as it is easily seen in approaches like genetic algorithms, evolutionary programming and particle swarm optimization. In this work we propose a new optimization method based on dialectics using fuzzy membership functions to model the influence of interactions between integrating poles in the status of each pole. Poles are the basic units composing dialectical systems. In order to validate our proposal we designed a segmentation method based on the optimization of k-means using dialectics for the segmentation of MR images. As a case study we used 181 MR synthetic multispectral images composed by proton density, T(1)- and T(2)-weighted synthetic brain images of 181 slices with 1 mm, resolution of 1 mm(3), for a normal brain and a noiseless MR tomographic system without field inhomogeneities, amounting a total of 543 images, generated by the simulator BrainWeb [2]. Our principal target here is comparing our proposal to k-means, fuzzy c-means, and Kohonen's self-organized maps, concerning the quantization error, we proved that our method can improved results obtained using k-means.

SU-E-T-230: Creating a Large Number of Focused Beams with Variable Patient Head Tilt to Improve Dose Fall-Off for Brain Radiosurgery

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

Chiu, J; Ma, L

2015-06-15

Purpose: To develop a treatment delivery and planning strategy by increasing the number of beams to minimize dose to brain tissue surrounding a target, while maximizing dose coverage to the target. Methods: We analyzed 14 different treatment plans via Leksell PFX and 4C. For standardization, single tumor cases were chosen. Original treatment plans were compared with two optimized plans. The number of beams was increased in treatment plans by varying tilt angles of the patient head, while maintaining original isocenter and the beam positions in the x-, y- and z-axes, collimator size, and beam blocking. PFX optimized plans increased beammore » numbers with three pre-set tilt angles, 70, 90, 110, and 4C optimized plans increased beam numbers with tilt angles increasing arbitrarily from range of 30 to 150 degrees. Optimized treatment plans were compared dosimetrically with original treatment plans. Results: Comparing total normal tissue isodose volumes between original and optimized plans, the low-level percentage isodose volumes decreased in all plans. Despite the addition of multiple beams up to a factor of 25, beam-on times for 1 tilt angle versus 3 or more tilt angles were comparable (<1 min.). In 64% (9/14) of the studied cases, the volume percentage decrease by >5%, with the highest value reaching 19%. The addition of more tilt angles correlates to a greater decrease in normal brain irradiated volume. Selectivity and coverage for original and optimized plans remained comparable. Conclusion: Adding large number of additional focused beams with variable patient head tilt shows improvement for dose fall-off for brain radiosurgery. The study demonstrates technical feasibility of adding beams to decrease target volume.« less

Development of a high-throughput brain slice method for studying drug distribution in the central nervous system.

PubMed

Fridén, Markus; Ducrozet, Frederic; Middleton, Brian; Antonsson, Madeleine; Bredberg, Ulf; Hammarlund-Udenaes, Margareta

2009-06-01

New, more efficient methods of estimating unbound drug concentrations in the central nervous system (CNS) combine the amount of drug in whole brain tissue samples measured by conventional methods with in vitro estimates of the unbound brain volume of distribution (V(u,brain)). Although the brain slice method is the most reliable in vitro method for measuring V(u,brain), it has not previously been adapted for the needs of drug discovery research. The aim of this study was to increase the throughput and optimize the experimental conditions of this method. Equilibrium of drug between the buffer and the brain slice within the 4 to 5 h of incubation is a fundamental requirement. However, it is difficult to meet this requirement for many of the extensively binding, lipophilic compounds in drug discovery programs. In this study, the dimensions of the incubation vessel and mode of stirring influenced the equilibration time, as did the amount of brain tissue per unit of buffer volume. The use of cassette experiments for investigating V(u,brain) in a linear drug concentration range increased the throughput of the method. The V(u,brain) for the model compounds ranged from 4 to 3000 ml . g brain(-1), and the sources of variability are discussed. The optimized setup of the brain slice method allows precise, robust estimation of V(u,brain) for drugs with diverse properties, including highly lipophilic compounds. This is a critical step forward for the implementation of relevant measurements of CNS exposure in the drug discovery setting.

Perspectives from the symposium: The role of nutrition in infant and toddler brain and behavioral development.

PubMed

Rosales, Francisco J; Zeisel, Steven H

2008-06-01

This symposium examined current trends in neuroscience and developmental psychology as they apply to assessing the effects of nutrients on brain and behavioral development of 0-6-year-olds. Although the spectrum of nutrients with brain effects has not changed much in the last 25 years, there has been an explosion in new knowledge about the genetics, structure and function of the brain. This has helped to link the brain mechanistic pathway by which these nutrients act with cognitive functions. A clear example of this is linking of brain structural changes due to hypoglycemia versus hyperglycemia with cognitive functions by using magnetic resonance imaging (MRI) to assess changes in brain-region volumes in combination with cognitive test of intelligence, memory and processing speed. Another example is the use of event-related potential (ERP) studies to show that infants of diabetic mothers have impairments in memory from birth through 8 months of age that are consistent with alterations in mechanistic pathways of memory observed in animal models of perinatal iron deficiency. However, gaps remain in the understanding of how nutrients and neurotrophic factors interact with each other in optimizing brain development and function.

Behavioural medicine and gastrointestinal disorders: the promise of positive psychology.

PubMed

Keefer, Laurie

2018-04-12

Psychosocial risk factors linked to brain-gut dysregulation are prevalent across the spectrum of gastrointestinal disorders and are associated with poor patient outcomes. Robust and reproducible data in the areas of behavioural intervention science and the brain-gut axis have led to major advances in patient care, including the routine use of brain-gut psychotherapies to manage digestive symptoms and optimize coping. The logical next step for the emerging field of psychogastroenterology is to develop a scientific framework that enables the identification of those individual characteristics and coping styles that buffer patients against the negative psychological effects of chronic gastrointestinal disorders. A shift towards a strength-based, positive psychological science of gastrointestinal disorders could facilitate the integration of early, effective psychological care into gastroenterology practice. In this Perspective, I discuss the potential role of three human strengths with relevance to gastrointestinal health - resilience, optimism and self-regulation - and how these three constructs can be cultivated through existing or emerging brain-gut psychotherapies.

Dedicated mobile volumetric cone-beam computed tomography for human brain imaging: A phantom study.

PubMed

Ryu, Jong-Hyun; Kim, Tae-Hoon; Jeong, Chang-Won; Jun, Hong-Young; Heo, Dong-Woon; Lee, Jinseok; Kim, Kyong-Woo; Yoon, Kwon-Ha

2015-01-01

Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased (p < 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 μ m at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Non-pharmacological biological treatment approaches to difficult-to-treat depression.

PubMed

Fitzgerald, Paul B

2013-09-16

There has been substantial recent interest in novel brain stimulation treatments for difficult-to-treat depression. Electroconvulsive therapy (ECT) is a well established, effective treatment for severe depression. ECT's problematic side-effect profile and questions regarding optimal administration methods continue to be investigated. Magnetic seizure therapy, although very early in development, shows promise, with potentially similar efficacy to ECT but fewer side effects. Vagus nerve stimulation (VNS) and repetitive transcranial magnetic stimulation (rTMS) are clinically available in some countries. Limited research suggests VNS has potentially long-lasting antidepressant effects in a small group of patients. Considerable research supports the efficacy of rTMS. Both techniques require further study of optimal treatment parameters. Transcranial direct current stimulation may provide a low-cost antidepressant option if its efficacy is substantiated in larger samples. Deep brain stimulation is likely to remain reserved for patients with the most severe and difficult-to-treat depression, requiring further exploration of administration methods and its role in depression therapy. New and innovative forms of brain stimulation, including low-intensity ultrasound, low-field magnetic stimulation and epidural stimulation of the cortical surface, are in early stages of exploration and are yet to move into the clinical domain. Ongoing work is required to define which brain stimulation treatments are likely to be most useful, and in which patient groups. Clinical service development of brain stimulation treatments will likely be inconsistent and variable.

The association between resting functional connectivity and dispositional optimism.

PubMed

Ran, Qian; Yang, Junyi; Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism.

The association between resting functional connectivity and dispositional optimism

PubMed Central

Yang, Wenjing; Wei, Dongtao; Qiu, Jiang; Zhang, Dong

2017-01-01

Dispositional optimism is an individual characteristic that plays an important role in human experience. Optimists are people who tend to hold positive expectations for their future. Previous studies have focused on the neural basis of optimism, such as task response neural activity and brain structure volume. However, the functional connectivity between brain regions of the dispositional optimists are poorly understood. Previous study suggested that the ventromedial prefrontal cortex (vmPFC) are associated with individual differences in dispositional optimism, but it is unclear whether there are other brain regions that combine with the vmPFC to contribute to dispositional optimism. Thus, the present study used the resting-state functional connectivity (RSFC) approach and set the vmPFC as the seed region to examine if differences in functional brain connectivity between the vmPFC and other brain regions would be associated with individual differences in dispositional optimism. The results found that dispositional optimism was significantly positively correlated with the strength of the RSFC between vmPFC and middle temporal gyrus (mTG) and negativly correlated with RSFC between vmPFC and inferior frontal gyrus (IFG). These findings may be suggested that mTG and IFG which associated with emotion processes and emotion regulation also play an important role in the dispositional optimism. PMID:28700613

Media representations of early human development: protecting, feeding and loving the developing brain.

PubMed

O'Connor, Cliodhna; Joffe, Helene

2013-11-01

The public profile of neurodevelopmental research has expanded in recent years. This paper applies social representations theory to explore how early brain development was represented in the UK print media in the first decade of the 21st century. A thematic analysis was performed on 505 newspaper articles published between 2000 and 2010 that discussed early brain development. Media coverage centred around concern with 'protecting' the prenatal brain (identifying threats to foetal neurodevelopment), 'feeding' the infant brain (indicating the patterns of nutrition that enhance brain development) and 'loving' the young child's brain (elucidating the developmental significance of emotionally nurturing family environments). The media focused almost exclusively on the role of parental action in promoting optimal neurodevelopment, rarely acknowledging wider structural, cultural or political means of supporting child development. The significance of parental care was intensified by deterministic interpretations of critical periods, which implied that inappropriate parental input would produce profound and enduring neurobiological impairments. Neurodevelopmental research was also used to promulgate normative judgements concerning the acceptability of certain gender roles and family contexts. The paper argues that media representations of neurodevelopment stress parental responsibility for shaping a child's future while relegating the contributions of genetic or wider societal factors, and examines the consequences of these representations for society and family life. Copyright © 2012 Elsevier Ltd. All rights reserved.

A novel combinational approach of microstimulation and bioluminescence imaging to study the mechanisms of action of cerebral electrical stimulation in mice

PubMed Central

Arsenault, Dany; Drouin-Ouellet, Janelle; Saint-Pierre, Martine; Petrou, Petros; Dubois, Marilyn; Kriz, Jasna; Barker, Roger A; Cicchetti, Antonio; Cicchetti, Francesca

2015-01-01

Key points We have developed a unique prototype to perform brain stimulation in mice. This system presents a number of advantages and new developments: 1) all stimulation parameters can be adjusted, 2) both positive and negative current pulses can be generated, guaranteeing electrically balanced stimulation regimen, 3) which can be produced with both low and high impedance electrodes, 4) the developed electrodes ensure localized stimulation and 5) can be used to stimulate and/or record brain potential and 6) in vivo recording of electric pulses allows the detection of defective electrodes (wire breakage or short circuits). This new micro-stimulator device further allows simultaneous live bioluminescence imaging of the mouse brain, enabling real time assessment of the impact of stimulation on cerebral tissue. The use of this novel tool in various transgenic mouse models of disease opens up a whole new range of possibilities in better understanding brain stimulation. Abstract Deep brain stimulation (DBS) is used to treat a number of neurological conditions and is currently being tested to intervene in neuropsychiatric conditions. However, a better understanding of how it works would ensure that side effects could be minimized and benefits optimized. We have thus developed a unique device to perform brain stimulation (BS) in mice and to address fundamental issues related to this methodology in the pre-clinical setting. This new microstimulator prototype was specifically designed to allow simultaneous live bioluminescence imaging of the mouse brain, allowing real time assessment of the impact of stimulation on cerebral tissue. We validated the authenticity of this tool in vivo by analysing the expression of toll-like receptor 2 (TLR2), corresponding to the microglial response, in the stimulated brain regions of TLR2-fluc-GFP transgenic mice, which we further corroborated with post-mortem analyses in these animals as well as in human brains of patients who underwent DBS to treat their Parkinson's disease. In the present study, we report on the development of the first BS device that allows for simultaneous live in vivo imaging in mice. This tool opens up a whole new range of possibilities that allow a better understanding of BS and how to optimize its effects through its use in murine models of disease. PMID:25653107

Brain targeted oral delivery of doxycycline hydrochloride encapsulated Tween 80 coated chitosan nanoparticles against ketamine induced psychosis: behavioral, biochemical, neurochemical and histological alterations in mice.

PubMed

Yadav, Monu; Parle, Milind; Sharma, Nidhi; Dhingra, Sameer; Raina, Neha; Jindal, Deepak Kumar

2017-11-01

To develop statistically optimized brain targeted Tween 80 coated chitosan nanoparticulate formulation for oral delivery of doxycycline hydrochloride for the treatment of psychosis and to evaluate its protective effect on ketamine induced behavioral, biochemical, neurochemical and histological alterations in mice. 3 2 full factorial design was used to optimize the nanoparticulate formulation to minimize particle size and maximize entrapment efficiency, while independent variables chosen were concentration of chitosan and Tween 80. The optimized formulation was characterized by particle size, drug entrapment efficiency, Fourier transform infrared, Transmission electron microscopy analysis and drug release behavior. Pure doxycycline hydrochloride (25 and 50 mg/kg, p.o.) and optimized doxycycline hydrochloride encapsulated Tween 80 coated chitosan nanoparticles (DCNP opt ) (equivalent to 25 mg/kg doxycycline hydrochloride, p.o.) were explored against ketamine induced psychosis in mice. The experimental studies for DCNP opt , with mean particle size 237 nm and entrapment efficiency 78.16%, elucidated that the formulation successfully passed through blood brain barrier and exhibited significant antipsychotic activity. The underlying mechanism of action was further confirmed by behavioral, biochemical, neurochemical estimations and histopathological study. Significantly enhanced GABA and GSH level and diminished MDA, TNF-α and dopamine levels were observed after administration of DCNP opt at just half the dose of pure doxycycline hydrochloride, showing better penetration of doxycyline hydrochloride in the form of Tween 80 coated nanoparticles through blood brain barrier. This study demonstrates the hydrophilic drug doxycycline hydrochloride, loaded in Tween 80 coated chitosan nanoparticles, can be effectively brain targeted through oral delivery and therefore represents a suitable approach for the treatment of psychotic symptoms.

Individual Functional ROI Optimization via Maximization of Group-wise Consistency of Structural and Functional Profiles

PubMed Central

Li, Kaiming; Guo, Lei; Zhu, Dajiang; Hu, Xintao; Han, Junwei; Liu, Tianming

2013-01-01

Studying connectivities among functional brain regions and the functional dynamics on brain networks has drawn increasing interest. A fundamental issue that affects functional connectivity and dynamics studies is how to determine the best possible functional brain regions or ROIs (regions of interest) for a group of individuals, since the connectivity measurements are heavily dependent on ROI locations. Essentially, identification of accurate, reliable and consistent corresponding ROIs is challenging due to the unclear boundaries between brain regions, variability across individuals, and nonlinearity of the ROIs. In response to these challenges, this paper presents a novel methodology to computationally optimize ROIs locations derived from task-based fMRI data for individuals so that the optimized ROIs are more consistent, reproducible and predictable across brains. Our computational strategy is to formulate the individual ROI location optimization as a group variance minimization problem, in which group-wise consistencies in functional/structural connectivity patterns and anatomic profiles are defined as optimization constraints. Our experimental results from multimodal fMRI and DTI data show that the optimized ROIs have significantly improved consistency in structural and functional profiles across individuals. These improved functional ROIs with better consistency could contribute to further study of functional interaction and dynamics in the human brain. PMID:22281931

Brain penetrant kinase inhibitors: Learning from kinase neuroscience discovery.

PubMed

Shi, Yuan; Mader, Mary

2018-06-15

A recent review of kinase inhibitors in clinical trials for brain cancer noted differences in the properties of these compounds relative to the mean property parameters associated with drugs marketed for CNS-associated conditions. However, many of these kinase drugs arose from opportunistic observations of brain activity, rather than design or flow schemes focused on optimizing CNS penetration. Thus, this digest examines kinase inhibitors that have been developed specifically for neurodegenerative indications such as Alzheimer's or Parkinson's disease, and considers design, flow scheme, and the physicochemical properties associated with compounds that have demonstrated brain penetrance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimism and the brain: trait optimism mediates the protective role of the orbitofrontal cortex gray matter volume against anxiety.

PubMed

Dolcos, Sanda; Hu, Yifan; Iordan, Alexandru D; Moore, Matthew; Dolcos, Florin

2016-02-01

Converging evidence identifies trait optimism and the orbitofrontal cortex (OFC) as personality and brain factors influencing anxiety, but the nature of their relationships remains unclear. Here, the mechanisms underlying the protective role of trait optimism and of increased OFC volume against symptoms of anxiety were investigated in 61 healthy subjects, who completed measures of trait optimism and anxiety, and underwent structural scanning using magnetic resonance imaging. First, the OFC gray matter volume (GMV) was associated with increased optimism, which in turn was associated with reduced anxiety. Second, trait optimism mediated the relation between the left OFC volume and anxiety, thus demonstrating that increased GMV in this brain region protects against symptoms of anxiety through increased optimism. These results provide novel evidence about the brain-personality mechanisms protecting against anxiety symptoms in healthy functioning, and identify potential targets for preventive and therapeutic interventions aimed at reducing susceptibility and increasing resilience against emotional disturbances. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Language comprehension and brain function in individuals with an optimal outcome from autism.

PubMed

Eigsti, Inge-Marie; Stevens, Michael C; Schultz, Robert T; Barton, Marianne; Kelley, Elizabeth; Naigles, Letitia; Orinstein, Alyssa; Troyb, Eva; Fein, Deborah A

2016-01-01

Although Autism Spectrum Disorder (ASD) is generally a lifelong disability, a minority of individuals with ASD overcome their symptoms to such a degree that they are generally indistinguishable from their typically-developing peers. That is, they have achieved an Optimal Outcome (OO). The question addressed by the current study is whether this normalized behavior reflects normalized brain functioning, or alternatively, the action of compensatory systems. Either possibility is plausible, as most participants with OO received years of intensive therapy that could alter brain networks to align with typical function or work around ASD-related neural dysfunction. Individuals ages 8 to 21 years with high-functioning ASD (n = 23), OO (n = 16), or typical development (TD; n = 20) completed a functional MRI scan while performing a sentence comprehension task. Results indicated similar activations in frontal and temporal regions (left middle frontal, left supramarginal, and right superior temporal gyri) and posterior cingulate in OO and ASD groups, where both differed from the TD group. Furthermore, the OO group showed heightened "compensatory" activation in numerous left- and right-lateralized regions (left precentral/postcentral gyri, right precentral gyrus, left inferior parietal lobule, right supramarginal gyrus, left superior temporal/parahippocampal gyrus, left middle occipital gyrus) and cerebellum, relative to both ASD and TD groups. Behaviorally normalized language abilities in OO individuals appear to utilize atypical brain networks, with increased recruitment of language-specific as well as right homologue and other systems. Early intensive learning and experience may normalize behavioral language performance in OO, but some brain regions involved in language processing may continue to display characteristics that are more similar to ASD than typical development, while others show characteristics not like ASD or typical development.

Technology for Children With Brain Injury and Motor Disability: Executive Summary From Research Summit IV.

PubMed

Christy, Jennifer B; Lobo, Michele A; Bjornson, Kristie; Dusing, Stacey C; Field-Fote, Edelle; Gannotti, Mary; Heathcock, Jill C; OʼNeil, Margaret E; Rimmer, James H

Advances in technology show promise as tools to optimize functional mobility, independence, and participation in infants and children with motor disability due to brain injury. Although technologies are often used in adult rehabilitation, these have not been widely applied to rehabilitation of infants and children. In October 2015, the Academy of Pediatric Physical Therapy sponsored Research Summit IV, "Innovations in Technology for Children With Brain Insults: Maximizing Outcomes." The summit included pediatric physical therapist researchers, experts from other scientific fields, funding agencies, and consumers. Participants identified challenges in implementing technology in pediatric rehabilitation including accessibility, affordability, managing large data sets, and identifying relevant data elements. Participants identified 4 key areas for technology development: to determine (1) thresholds for learning, (2) appropriate transfer to independence, (3) optimal measurement of subtle changes, and (4) how to adapt to growth and changing abilities.

An ICA-based method for the identification of optimal FMRI features and components using combined group-discriminative techniques

PubMed Central

Sui, Jing; Adali, Tülay; Pearlson, Godfrey D.; Calhoun, Vince D.

2013-01-01

Extraction of relevant features from multitask functional MRI (fMRI) data in order to identify potential biomarkers for disease, is an attractive goal. In this paper, we introduce a novel feature-based framework, which is sensitive and accurate in detecting group differences (e.g. controls vs. patients) by proposing three key ideas. First, we integrate two goal-directed techniques: coefficient-constrained independent component analysis (CC-ICA) and principal component analysis with reference (PCA-R), both of which improve sensitivity to group differences. Secondly, an automated artifact-removal method is developed for selecting components of interest derived from CC-ICA, with an average accuracy of 91%. Finally, we propose a strategy for optimal feature/component selection, aiming to identify optimal group-discriminative brain networks as well as the tasks within which these circuits are engaged. The group-discriminating performance is evaluated on 15 fMRI feature combinations (5 single features and 10 joint features) collected from 28 healthy control subjects and 25 schizophrenia patients. Results show that a feature from a sensorimotor task and a joint feature from a Sternberg working memory (probe) task and an auditory oddball (target) task are the top two feature combinations distinguishing groups. We identified three optimal features that best separate patients from controls, including brain networks consisting of temporal lobe, default mode and occipital lobe circuits, which when grouped together provide improved capability in classifying group membership. The proposed framework provides a general approach for selecting optimal brain networks which may serve as potential biomarkers of several brain diseases and thus has wide applicability in the neuroimaging research community. PMID:19457398

The Role of Surgery, Radiosurgery and Whole Brain Radiation Therapy in the Management of Patients with Metastatic Brain Tumors

PubMed Central

Ellis, Thomas L.; Neal, Matthew T.; Chan, Michael D.

2012-01-01

Brain tumors constitute the most common intracranial tumor. Management of brain metastases has become increasingly complex as patients with brain metastases are living longer and more treatment options develop. The goal of this paper is to review the role of stereotactic radiosurgery (SRS), whole brain radiation therapy (WBRT), and surgery, in isolation and in combination, in the contemporary treatment of brain metastases. Surgery and SRS both offer management options that may help to optimize therapy in selected patients. WBRT is another option but can lead to late toxicity and suboptimal local control in longer term survivors. Improved prognostic indices will be critical for selecting the best therapies. Further prospective trials are necessary to continue to elucidate factors that will help triage patients to the proper brain-directed therapy for their cancer. PMID:22312545

Defining Optimal Brain Health in Adults: A Presidential Advisory From the American Heart Association/American Stroke Association.

PubMed

Gorelick, Philip B; Furie, Karen L; Iadecola, Costantino; Smith, Eric E; Waddy, Salina P; Lloyd-Jones, Donald M; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W; Girgus, Meighan; Howard, Virginia J; Lazar, Ronald M; Seshadri, Sudha; Testai, Fernando D; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-10-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA's Life's Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m 2 ) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer's Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA's Life's Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA's Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. © 2017 American Heart Association, Inc.

Defining Optimal Brain Health in Adults

PubMed Central

Gorelick, Philip B.; Furie, Karen L.; Iadecola, Costantino; Smith, Eric E.; Waddy, Salina P.; Lloyd-Jones, Donald M.; Bae, Hee-Joon; Bauman, Mary Ann; Dichgans, Martin; Duncan, Pamela W.; Girgus, Meighan; Howard, Virginia J.; Lazar, Ronald M.; Seshadri, Sudha; Testai, Fernando D.; van Gaal, Stephen; Yaffe, Kristine; Wasiak, Hank; Zerna, Charlotte

2017-01-01

Cognitive function is an important component of aging and predicts quality of life, functional independence, and risk of institutionalization. Advances in our understanding of the role of cardiovascular risks have shown them to be closely associated with cognitive impairment and dementia. Because many cardiovascular risks are modifiable, it may be possible to maintain brain health and to prevent dementia in later life. The purpose of this American Heart Association (AHA)/American Stroke Association presidential advisory is to provide an initial definition of optimal brain health in adults and guidance on how to maintain brain health. We identify metrics to define optimal brain health in adults based on inclusion of factors that could be measured, monitored, and modified. From these practical considerations, we identified 7 metrics to define optimal brain health in adults that originated from AHA’s Life’s Simple 7: 4 ideal health behaviors (nonsmoking, physical activity at goal levels, healthy diet consistent with current guideline levels, and body mass index <25 kg/m2) and 3 ideal health factors (untreated blood pressure <120/<80 mm Hg, untreated total cholesterol <200 mg/dL, and fasting blood glucose <100 mg/dL). In addition, in relation to maintenance of cognitive health, we recommend following previously published guidance from the AHA/American Stroke Association, Institute of Medicine, and Alzheimer’s Association that incorporates control of cardiovascular risks and suggest social engagement and other related strategies. We define optimal brain health but recognize that the truly ideal circumstance may be uncommon because there is a continuum of brain health as demonstrated by AHA’s Life’s Simple 7. Therefore, there is opportunity to improve brain health through primordial prevention and other interventions. Furthermore, although cardiovascular risks align well with brain health, we acknowledge that other factors differing from those related to cardiovascular health may drive cognitive health. Defining optimal brain health in adults and its maintenance is consistent with the AHA’s Strategic Impact Goal to improve cardiovascular health of all Americans by 20% and to reduce deaths resulting from cardiovascular disease and stroke by 20% by the year 2020. This work in defining optimal brain health in adults serves to provide the AHA/American Stroke Association with a foundation for a new strategic direction going forward in cardiovascular health promotion and disease prevention. PMID:28883125

Visual cortical areas of the mouse: comparison of parcellation and network structure with primates

PubMed Central

Laramée, Marie-Eve; Boire, Denis

2015-01-01

Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals. PMID:25620914

Visual cortical areas of the mouse: comparison of parcellation and network structure with primates.

PubMed

Laramée, Marie-Eve; Boire, Denis

2014-01-01

Brains have evolved to optimize sensory processing. In primates, complex cognitive tasks must be executed and evolution led to the development of large brains with many cortical areas. Rodents do not accomplish cognitive tasks of the same level of complexity as primates and remain with small brains both in relative and absolute terms. But is a small brain necessarily a simple brain? In this review, several aspects of the visual cortical networks have been compared between rodents and primates. The visual system has been used as a model to evaluate the level of complexity of the cortical circuits at the anatomical and functional levels. The evolutionary constraints are first presented in order to appreciate the rules for the development of the brain and its underlying circuits. The organization of sensory pathways, with their parallel and cross-modal circuits, is also examined. Other features of brain networks, often considered as imposing constraints on the development of underlying circuitry, are also discussed and their effect on the complexity of the mouse and primate brain are inspected. In this review, we discuss the common features of cortical circuits in mice and primates and see how these can be useful in understanding visual processing in these animals.

Targeted delivery of growth factors in ischemic stroke animal models.

PubMed

Rhim, Taiyoun; Lee, Minhyung

2016-01-01

Ischemic stroke is caused by reduced blood supply and leads to loss of brain function. The reduced oxygen and nutrient supply stimulates various physiological responses, including induction of growth factors. Growth factors prevent neuronal cell death, promote neovascularization, and induce cell growth. However, the concentration of growth factors is not sufficient to recover brain function after the ischemic damage, suggesting that delivery of growth factors into the ischemic brain may be a useful treatment for ischemic stroke. In this review, various approaches for the delivery of growth factors to ischemic brain tissue are discussed, including local and targeting delivery systems. To develop growth factor therapy for ischemic stroke, important considerations should be taken into account. First, growth factors may have possible side effects. Thus, concentration of growth factors should be restricted to the ischemic tissues by local administration or targeted delivery. Second, the duration of growth factor therapy should be optimized. Growth factor proteins may be degraded too fast to have a high enough therapeutic effect. Therefore, delivery systems for controlled release or gene delivery may be useful. Third, the delivery systems to the brain should be optimized according to the delivery route.

Fifty Years in the Development of a Glutaminergic-Dopaminergic Optimization Complex (KB220) to Balance Brain Reward Circuitry in Reward Deficiency Syndrome: A Pictorial

PubMed Central

Blum, K; Febo, M; Badgaiyan, RD

2016-01-01

Dopamine along with other chemical messengers like serotonin, cannabinoids, endorphins and glutamine, play significant roles in brain reward processing. There is a devastating opiate/opioid epidemicin the United States. According to the Centers for Disease Control and Prevention (CDC), at least 127 people, young and old, are dying every day due to narcotic overdose and alarmingly heroin overdose is on the rise. The Food and Drug Administration (FDA) has approved some Medication-Assisted Treatments (MATs) for alcoholism, opiate and nicotine dependence, but nothing for psychostimulant and cannabis abuse. While these pharmaceuticals are essential for the short-term induction of “psychological extinction,” in the long-term caution is necessary because their use favors blocking dopaminergic function indispensable for achieving normal satisfaction in life. The two institutions devoted to alcoholism and drug dependence (NIAAA & NIDA) realize that MATs are not optimal and continue to seek better treatment options. We review, herein, the history of the development of a glutaminergic-dopaminergic optimization complex called KB220 to provide for the possible eventual balancing of the brain reward system and the induction of “dopamine homeostasis.” This complex may provide substantial clinical benefit to the victims of Reward Deficiency Syndrome (RDS) and assist in recovery from iatrogenically induced addiction to unwanted opiates/opioids and other addictive behaviors. PMID:27840857

An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

2015-01-01

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

4D MEMRI atlas of neonatal FVB/N mouse brain development.

PubMed

Szulc, Kamila U; Lerch, Jason P; Nieman, Brian J; Bartelle, Benjamin B; Friedel, Miriam; Suero-Abreu, Giselle A; Watson, Charles; Joyner, Alexandra L; Turnbull, Daniel H

2015-09-01

The widespread use of the mouse as a model system to study brain development has created the need for noninvasive neuroimaging methods that can be applied to early postnatal mice. The goal of this study was to optimize in vivo three- (3D) and four-dimensional (4D) manganese (Mn)-enhanced MRI (MEMRI) approaches for acquiring and analyzing data from the developing mouse brain. The combination of custom, stage-dependent holders and self-gated (motion-correcting) 3D MRI sequences enabled the acquisition of high-resolution (100-μm isotropic), motion artifact-free brain images with a high level of contrast due to Mn-enhancement of numerous brain regions and nuclei. We acquired high-quality longitudinal brain images from two groups of FVB/N strain mice, six mice per group, each mouse imaged on alternate odd or even days (6 3D MEMRI images at each day) covering the developmental stages between postnatal days 1 to 11. The effects of Mn-exposure, anesthesia and MRI were assessed, showing small but significant transient effects on body weight and brain volume, which recovered with time and did not result in significant morphological differences when compared to controls. Metrics derived from deformation-based morphometry (DBM) were used for quantitative analysis of changes in volume and position of a number of brain regions. The cerebellum, a brain region undergoing significant changes in size and patterning at early postnatal stages, was analyzed in detail to demonstrate the spatiotemporal characterization made possible by this new atlas of mouse brain development. These results show that MEMRI is a powerful tool for quantitative analysis of mouse brain development, with great potential for in vivo phenotype analysis in mouse models of neurodevelopmental diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Robert's Rules for Optimal Learning: Model Development, Field Testing, Implications!

ERIC Educational Resources Information Center

McGinty, Robert L.

The value of accelerated learning techniques developed by the national organization for Suggestive Accelerated Learning Techniques (SALT) was tested in a study using Administrative Policy students taking the capstone course in the Eastern Washington University School of Business. Educators have linked the brain and how it functions to various…

Finding influential nodes for integration in brain networks using optimal percolation theory.

PubMed

Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

2018-06-11

Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

Whole brain inhomogeneous magnetization transfer (ihMT) imaging: Sensitivity enhancement within a steady-state gradient echo sequence.

PubMed

Mchinda, Samira; Varma, Gopal; Prevost, Valentin H; Le Troter, Arnaud; Rapacchi, Stanislas; Guye, Maxime; Pelletier, Jean; Ranjeva, Jean-Philippe; Alsop, David C; Duhamel, Guillaume; Girard, Olivier M

2018-05-01

To implement, characterize, and optimize an interleaved inhomogeneous magnetization transfer (ihMT) gradient echo sequence allowing for whole-brain imaging within a clinically compatible scan time. A general framework for ihMT modelling was developed based on the Provotorov theory of radiofrequency saturation, which accounts for the dipolar order underpinning the ihMT effect. Experimental studies and numerical simulations were performed to characterize and optimize the ihMT-gradient echo dependency with sequence timings, saturation power, and offset frequency. The protocol was optimized in terms of maximum signal intensity and the reproducibility assessed for a nominal resolution of 1.5 mm isotropic. All experiments were performed on healthy volunteers at 1.5T. An important mechanism driving signal optimization and leading to strong ihMT signal enhancement that relies on the dynamics of radiofrequency energy deposition has been identified. By taking advantage of the delay allowed for readout between ihMT pulse bursts, it was possible to boost the ihMT signal by almost 2-fold compared to previous implementation. Reproducibility of the optimal protocol was very good, with an intra-individual error < 2%. The proposed sensitivity-boosted and time-efficient steady-state ihMT-gradient echo sequence, implemented and optimized at 1.5T, allowed robust high-resolution 3D ihMT imaging of the whole brain within a clinically compatible scan time. Magn Reson Med 79:2607-2619, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Cross-entropy optimization for neuromodulation.

PubMed

Brar, Harleen K; Yunpeng Pan; Mahmoudi, Babak; Theodorou, Evangelos A

2016-08-01

This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller. With insufficient gains, the internal controller cannot provide enough feedback to the brain dynamics causing an increase in correlation between different brain sites. This increase in synchronization results in the destabilization of the brain dynamics, which is representative of an epileptic seizure. To provide compensation for an insufficient internal controller an external controller is designed using proportional-integral feedback control strategy. A cross-entropy optimization algorithm is applied to the chaotic oscillator network model to learn the optimal feedback gains for the external controller instead of hand-tuning the gains to provide sufficient control to the pathological brain and prevent seizure generation. The correlation between the dynamics of neural activity within different brain sites is calculated for experimental data to show similar dynamics of epileptic neural activity as simulated by the network of chaotic oscillators.

Adaptive optical microscope for brain imaging in vivo

NASA Astrophysics Data System (ADS)

Wang, Kai

2017-04-01

The optical heterogeneity of biological tissue imposes a major limitation to acquire detailed structural and functional information deep in the biological specimens using conventional microscopes. To restore optimal imaging performance, we developed an adaptive optical microscope based on direct wavefront sensing technique. This microscope can reliably measure and correct biological samples induced aberration. We demonstrated its performance and application in structural and functional brain imaging in various animal models, including fruit fly, zebrafish and mouse.

Biothermal Model of Patient and Automatic Control System of Brain Temperature for Brain Hypothermia Treatment

NASA Astrophysics Data System (ADS)

Wakamatsu, Hidetoshi; Gaohua, Lu

Various surface-cooling apparatus such as the cooling cap, muffler and blankets have been commonly used for the cooling of the brain to provide hypothermic neuro-protection for patients of hypoxic-ischemic encephalopathy. The present paper is aimed at the brain temperature regulation from the viewpoint of automatic system control, in order to help clinicians decide an optimal temperature of the cooling fluid provided for these three types of apparatus. At first, a biothermal model characterized by dynamic ambient temperatures is constructed for adult patient, especially on account of the clinical practice of hypothermia and anesthesia in the brain hypothermia treatment. Secondly, the model is represented by the state equation as a lumped parameter linear dynamic system. The biothermal model is justified from their various responses corresponding to clinical phenomena and treatment. Finally, the optimal regulator is tentatively designed to give clinicians some suggestions on the optimal temperature regulation of the patient’s brain. It suggests the patient’s brain temperature could be optimally controlled to follow-up the temperature process prescribed by the clinicians. This study benefits us a great clinical possibility for the automatic hypothermia treatment.

Escherichia coli K1 invasion of human brain microvascular endothelial cells.

PubMed

Loh, Lip Nam; Ward, Theresa H

2012-01-01

The pathogenic Escherichia coli strain E. coli K1 is a primary causative agent of neonatal meningitis. Understanding how these bacteria cross the blood-brain barrier is vital to develop therapeutics. Here, we describe the use of live-cell imaging techniques to study E. coli K1 interactions with cellular markers following infection of human brain microvascular endothelial cells, a model system of the blood-brain barrier. We also discuss optimization of endothelial cell transfection conditions using nonviral transfection technique, bacterial labeling techniques, and in vitro assays to screen for fluorescent bacteria that retain their ability to invade host cells. Copyright © 2012 Elsevier Inc. All rights reserved.

Optimized magnetic resonance diffusion protocol for ex-vivo whole human brain imaging with a clinical scanner

NASA Astrophysics Data System (ADS)

Scherrer, Benoit; Afacan, Onur; Stamm, Aymeric; Singh, Jolene; Warfield, Simon K.

2015-03-01

Diffusion-weighted magnetic resonance imaging (DW-MRI) provides a novel insight into the brain to facilitate our understanding of the brain connectivity and microstructure. While in-vivo DW-MRI enables imaging of living patients and longitudinal studies of brain changes, post-mortem ex-vivo DW-MRI has numerous advantages. Ex-vivo imaging benefits from greater resolution and sensitivity due to the lack of imaging time constraints; the use of tighter fitting coils; and the lack of movement artifacts. This allows characterization of normal and abnormal tissues with unprecedented resolution and sensitivity, facilitating our ability to investigate anatomical structures that are inaccessible in-vivo. This also offers the opportunity to develop today novel imaging biomarkers that will, with tomorrow's MR technology, enable improved in-vivo assessment of the risk of disease in an individual. Post-mortem studies, however, generally rely on the fixation of specimen to inhibit tissue decay which starts as soon as tissue is deprived from its blood supply. Unfortunately, fixation of tissues substantially alters tissue diffusivity profiles. In addition, ex-vivo DW-MRI requires particular care when packaging the specimen because the presence of microscopic air bubbles gives rise to geometric and intensity image distortion. In this work, we considered the specific requirements of post-mortem imaging and designed an optimized protocol for ex-vivo whole brain DW-MRI using a human clinical 3T scanner. Human clinical 3T scanners are available to a large number of researchers and, unlike most animal scanners, have a bore diameter large enough to image a whole human brain. Our optimized protocol will facilitate widespread ex-vivo investigations of large specimen.

Clinicopathological factors associated with survival in patients with breast cancer brain metastasis.

PubMed

Li, Rong; Zhang, Kui; Siegal, Gene P; Wei, Shi

2017-06-01

Brain metastasis from breast cancer generally represents a catastrophic event yet demonstrates substantial biological heterogeneity. There have been limited studies solely focusing on the prognosis of patients with such metastasis. In this study, we carried out a comprehensive analysis in 108 consecutive patients with breast cancer brain metastases between 1997 and 2012 to further define clinicopathological factors associated with early onset of brain metastasis and survival outcomes after development of them. We found that lobular carcinoma, higher clinical stages at diagnosis, and lack of coexisting bone metastasis were significantly associated with a worse brain relapse-free survival when compared with brain-only metastasis. High histologic grade, triple-negative breast cancer, and absence of visceral involvement were unfavorable prognostic factors after brain metastasis. Furthermore, high histologic grade, advanced tumor stages, and lack of coexisting bone involvement indicated a worse overall survival. Thus, the previously established prognostic factors in early stage or advanced breast cancers may not entirely apply to patients with brain metastases. Furthermore, the prognostic significance of the clinicopathological factors differed before and after a patient develops brain metastasis. This knowledge might help in establishing an algorithm to further stratify patients with breast cancer into prognostically significant categories for optimal prevention, screening, and treatment of their brain metastasis. Copyright © 2017 Elsevier Inc. All rights reserved.

Unusual developmental pattern of brain lateralization in young boys with autism spectrum disorder: Power analysis with child-sized magnetoencephalography.

PubMed

Hiraishi, Hirotoshi; Kikuchi, Mitsuru; Yoshimura, Yuko; Kitagawa, Sachiko; Hasegawa, Chiaki; Munesue, Toshio; Takesaki, Natsumi; Ono, Yasuki; Takahashi, Tsutomu; Suzuki, Michio; Higashida, Haruhiro; Asada, Minoru; Minabe, Yoshio

2015-03-01

Autism spectrum disorder (ASD) is often described as comprising an unusual brain growth pattern and aberrant brain lateralization. Although it is important to study the pathophysiology of the developing ASD cortex, examples of physiological brain lateralization in young children with ASD have yet to be well examined. Thirty-eight boys with ASD (aged 3-7 years) and 38 typically developing (TD) boys (aged 3-8 years) concentrated on video programs and their brain activities were measured non-invasively. We employed a customized child-sized magnetoencephalography system in which the sensors were located as close to the brain as possible for optimal recording in young children. To produce a credible laterality index of the brain oscillations, we defined two clusters of sensors corresponding to the right and left hemispheres. We focused on the laterality index ([left - right]/[left+right]) of the relative power band in seven frequency bands. The TD group displayed significantly rightward lateralized brain oscillations in the theta-1 frequency bands compared to the ASD group. This is the first study to demonstrate unusual brain lateralization of brain oscillations measured by magnetoencephalography in young children with ASD. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

Exosome delivered anticancer drugs across the blood-brain barrier for brain cancer therapy in Danio rerio.

PubMed

Yang, Tianzhi; Martin, Paige; Fogarty, Brittany; Brown, Alison; Schurman, Kayla; Phipps, Roger; Yin, Viravuth P; Lockman, Paul; Bai, Shuhua

2015-06-01

The blood-brain barrier (BBB) essentially restricts therapeutic drugs from entering into the brain. This study tests the hypothesis that brain endothelial cell derived exosomes can deliver anticancer drug across the BBB for the treatment of brain cancer in a zebrafish (Danio rerio) model. Four types of exosomes were isolated from brain cell culture media and characterized by particle size, morphology, total protein, and transmembrane protein markers. Transport mechanism, cell uptake, and cytotoxicity of optimized exosome delivery system were tested. Brain distribution of exosome delivered anticancer drugs was evaluated using transgenic zebrafish TG (fli1: GFP) embryos and efficacies of optimized formations were examined in a xenotransplanted zebrafish model of brain cancer model. Four exosomes in 30-100 diameters showed different morphologies and exosomes derived from brain endothelial cells expressed more CD63 tetraspanins transmembrane proteins. Optimized exosomes increased the uptake of fluorescent marker via receptor mediated endocytosis and cytotoxicity of anticancer drugs in cancer cells. Images of the zebrafish showed exosome delivered anticancer drugs crossed the BBB and entered into the brain. In the brain cancer model, exosome delivered anticancer drugs significantly decreased fluorescent intensity of xenotransplanted cancer cells and tumor growth marker. Brain endothelial cell derived exosomes could be potentially used as a carrier for brain delivery of anticancer drug for the treatment of brain cancer.

Intranasal brain-targeted clonazepam polymeric micelles for immediate control of status epilepticus: in vitro optimization, ex vivo determination of cytotoxicity, in vivo biodistribution and pharmacodynamics studies.

PubMed

Nour, Samia A; Abdelmalak, Nevine S; Naguib, Marianne J; Rashed, Hassan M; Ibrahim, Ahmed B

2016-11-01

Clonazepam (CZ) is an anti-epileptic drug used mainly in status epilepticus (SE). The drug belongs to Class II according to BCS classification with very limited solubility and high permeability and it suffers from extensive first-pass metabolism. The aim of the present study was to develop CZ-loaded polymeric micelles (PM) for direct brain delivery allowing immediate control of SE. PM were prepared via thin film hydration (TFH) technique adopting a central composite face-centered design (CCFD). The seventeen developed formulae were evaluated in terms of entrapment efficiency (EE), particle size (PS), polydispersity index (PDI), zeta potential (ZP), and in vitro release. For evaluating the in vivo behavior of the optimized formula, both biodistrbution using 99m Tc-radiolabeled CZ and pharmacodynamics studies were done in addition to ex vivo cytotoxicty. At a drug:Pluronic® P123:Pluronic® L121 ratio of 1:20:20 (PM7), a high EE, ZP, Q8h, and a low PDI was achieved. The biodistribution studies revealed that the optimized formula had significantly higher drug targeting efficiency (DTE = 242.3%), drug targeting index (DTI = 144.25), and nose-to-brain direct transport percentage (DTP = 99.30%) and a significant prolongation of protection from seizures in comparison to the intranasally administered solution with minor histopathological changes. The declared results reveal the ability of the developed PM to be a strong potential candidate for the emergency treatment of SE.

What has fMRI told us about the Development of Cognitive Control through Adolescence?

PubMed Central

Luna, Beatriz; Padmanabhan, Aarthi; O’Hearn, Kirsten

2009-01-01

Cognitive control, the ability to voluntarily guide our behavior, continues to improve throughout adolescence. Below we review the literature on age-related changes in brain function related to response inhibition and working memory, which support cognitive control. Findings from studies using functional magnetic imaging (fMRI) indicate that processing errors, sustaining a cognitive control state, and reaching adult levels of precision, persist through adolescence. Developmental changes in patterns of brain function suggest that core regions of the circuitry underlying cognitive control are on-line early in development. However, age-related changes in localized processes across the brain and in establishing long range connections that support top-down modulation of behavior may support more effective neural processing for optimal mature executive function. While great progress has been made in understanding the age-related changes in brain processes underlying cognitive development, there are still important challenges in developmental neuroimaging methods and the interpretation of data that need to be addressed. PMID:19765880

Optimized temporal pattern of brain stimulation designed by computational evolution

PubMed Central

Brocker, David T.; Swan, Brandon D.; So, Rosa Q.; Turner, Dennis A.; Gross, Robert E.; Grill, Warren M.

2017-01-01

Brain stimulation is a promising therapy for several neurological disorders, including Parkinson’s disease. Stimulation parameters are selected empirically and are limited to the frequency and intensity of stimulation. We used the temporal pattern of stimulation as a novel parameter of deep brain stimulation to ameliorate symptoms in a parkinsonian animal model and in humans with Parkinson’s disease. We used model-based computational evolution to optimize the stimulation pattern. The optimized pattern produced symptom relief comparable to that from standard high-frequency stimulation (a constant rate of 130 or 185 Hz) and outperformed frequency-matched standard stimulation in the parkinsonian rat and in patients. Both optimized and standard stimulation suppressed abnormal oscillatory activity in the basal ganglia of rats and humans. The results illustrate the utility of model-based computational evolution to design temporal pattern of stimulation to increase the efficiency of brain stimulation in Parkinson’s disease, thereby requiring substantially less energy than traditional brain stimulation. PMID:28053151

Live imaging of mitosis in the developing mouse embryonic cortex.

PubMed

Pilaz, Louis-Jan; Silver, Debra L

2014-06-04

Although of short duration, mitosis is a complex and dynamic multi-step process fundamental for development of organs including the brain. In the developing cerebral cortex, abnormal mitosis of neural progenitors can cause defects in brain size and function. Hence, there is a critical need for tools to understand the mechanisms of neural progenitor mitosis. Cortical development in rodents is an outstanding model for studying this process. Neural progenitor mitosis is commonly examined in fixed brain sections. This protocol will describe in detail an approach for live imaging of mitosis in ex vivo embryonic brain slices. We will describe the critical steps for this procedure, which include: brain extraction, brain embedding, vibratome sectioning of brain slices, staining and culturing of slices, and time-lapse imaging. We will then demonstrate and describe in detail how to perform post-acquisition analysis of mitosis. We include representative results from this assay using the vital dye Syto11, transgenic mice (histone H2B-EGFP and centrin-EGFP), and in utero electroporation (mCherry-α-tubulin). We will discuss how this procedure can be best optimized and how it can be modified for study of genetic regulation of mitosis. Live imaging of mitosis in brain slices is a flexible approach to assess the impact of age, anatomy, and genetic perturbation in a controlled environment, and to generate a large amount of data with high temporal and spatial resolution. Hence this protocol will complement existing tools for analysis of neural progenitor mitosis.

Determining Optimal Microwave Antigen Retrieval Conditions for Microtubule-Associated Protein 2 Immunohistochemistry in the Guinea Pig Brain

DTIC Science & Technology

2002-12-01

sections of formalin-fixed guinea pig brains using different MAP-2 monoclonal antibodies. Brain sections were boiled in sodium citrate, citric acid...citric acid solution at pH 6.0 is the optimal microwave-assisted AR method for immunolabeling MAP-2 in formalin-fixed, paraffin-processed guinea pig brain...studies on archival guinea pig brain paraffin blocks, ultimately relaxing the use of additional animals to evaluate changes in MAP-2 expression between chemical warfare nerve agent-treated and control samples.

The epidemiology of a specialist neurorehabilitation clinic: implications for clinical practice and regional service development.

PubMed

Seeley, Helen; Pickard, John; Allanson, Judith; Hutchinson, Peter

2014-01-01

To examine the epidemiology of referrals to a specialist neurotrauma clinic and explore and highlight implications for clinical practice and service development for persons with head injury/traumatic brain injury (HI/TBI). A retrospective population-based cohort study of all referrals to a specialist neurotrauma clinic over a 9-year period. Data from a specialist head injury database (which included all persons presenting to hospital with traumatic brain injury) were analysed. In total, 1235 new patients of all ages, severities of injury, both admitted and non-admitted were referred. Referrals have increased due to successful integration with new service developments and resulting optimization of resources. Data gathered from the cohort gives increased understanding of the characteristics and numbers of patients requiring rehabilitation and adds to the evidence-base. Integration with new and complementary service developments has optimized the function/aims of the clinic and enhanced its role in terms of patient service and outcome and as a research resource. The model provides principles which may be applied to planning, organizing and providing follow-up/rehabilitation services for HI/TBI.

Highly adaptive tests for group differences in brain functional connectivity.

PubMed

Kim, Junghi; Pan, Wei

2015-01-01

Resting-state functional magnetic resonance imaging (rs-fMRI) and other technologies have been offering evidence and insights showing that altered brain functional networks are associated with neurological illnesses such as Alzheimer's disease. Exploring brain networks of clinical populations compared to those of controls would be a key inquiry to reveal underlying neurological processes related to such illnesses. For such a purpose, group-level inference is a necessary first step in order to establish whether there are any genuinely disrupted brain subnetworks. Such an analysis is also challenging due to the high dimensionality of the parameters in a network model and high noise levels in neuroimaging data. We are still in the early stage of method development as highlighted by Varoquaux and Craddock (2013) that "there is currently no unique solution, but a spectrum of related methods and analytical strategies" to learn and compare brain connectivity. In practice the important issue of how to choose several critical parameters in estimating a network, such as what association measure to use and what is the sparsity of the estimated network, has not been carefully addressed, largely because the answers are unknown yet. For example, even though the choice of tuning parameters in model estimation has been extensively discussed in the literature, as to be shown here, an optimal choice of a parameter for network estimation may not be optimal in the current context of hypothesis testing. Arbitrarily choosing or mis-specifying such parameters may lead to extremely low-powered tests. Here we develop highly adaptive tests to detect group differences in brain connectivity while accounting for unknown optimal choices of some tuning parameters. The proposed tests combine statistical evidence against a null hypothesis from multiple sources across a range of plausible tuning parameter values reflecting uncertainty with the unknown truth. These highly adaptive tests are not only easy to use, but also high-powered robustly across various scenarios. The usage and advantages of these novel tests are demonstrated on an Alzheimer's disease dataset and simulated data.

Skull removal in MR images using a modified artificial bee colony optimization algorithm.

PubMed

Taherdangkoo, Mohammad

2014-01-01

Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.

Brain-computer interface analysis of a dynamic visuo-motor task.

PubMed

Logar, Vito; Belič, Aleš

2011-01-01

The area of brain-computer interfaces (BCIs) represents one of the more interesting fields in neurophysiological research, since it investigates the development of the machines that perform different transformations of the brain's "thoughts" to certain pre-defined actions. Experimental studies have reported some successful implementations of BCIs; however, much of the field still remains unexplored. According to some recent reports the phase coding of informational content is an important mechanism in the brain's function and cognition, and has the potential to explain various mechanisms of the brain's data transfer, but it has yet to be scrutinized in the context of brain-computer interface. Therefore, if the mechanism of phase coding is plausible, one should be able to extract the phase-coded content, carried by brain signals, using appropriate signal-processing methods. In our previous studies we have shown that by using a phase-demodulation-based signal-processing approach it is possible to decode some relevant information on the current motor action in the brain from electroencephalographic (EEG) data. In this paper the authors would like to present a continuation of their previous work on the brain-information-decoding analysis of visuo-motor (VM) tasks. The present study shows that EEG data measured during more complex, dynamic visuo-motor (dVM) tasks carries enough information about the currently performed motor action to be successfully extracted by using the appropriate signal-processing and identification methods. The aim of this paper is therefore to present a mathematical model, which by means of the EEG measurements as its inputs predicts the course of the wrist movements as applied by each subject during the task in simulated or real time (BCI analysis). However, several modifications to the existing methodology are needed to achieve optimal decoding results and a real-time, data-processing ability. The information extracted from the EEG could, therefore, be further used for the development of a closed-loop, non-invasive, brain-computer interface. For the case of this study two types of measurements were performed, i.e., the electroencephalographic (EEG) signals and the wrist movements were measured simultaneously, during the subject's performance of a dynamic visuo-motor task. Wrist-movement predictions were computed by using the EEG data-processing methodology of double brain-rhythm filtering, double phase demodulation and double principal component analyses (PCA), each with a separate set of parameters. For the movement-prediction model a fuzzy inference system was used. The results have shown that the EEG signals measured during the dVM tasks carry enough information about the subjects' wrist movements for them to be successfully decoded using the presented methodology. Reasonably high values of the correlation coefficients suggest that the validation of the proposed approach is satisfactory. Moreover, since the causality of the rhythm filtering and the PCA transformation has been achieved, we have shown that these methods can also be used in a real-time, brain-computer interface. The study revealed that using non-causal, optimized methods yields better prediction results in comparison with the causal, non-optimized methodology; however, taking into account that the causality of these methods allows real-time processing, the minor decrease in prediction quality is acceptable. The study suggests that the methodology that was proposed in our previous studies is also valid for identifying the EEG-coded content during dVM tasks, albeit with various modifications, which allow better prediction results and real-time data processing. The results have shown that wrist movements can be predicted in simulated or real time; however, the results of the non-causal, optimized methodology (simulated) are slightly better. Nevertheless, the study has revealed that these methods should be suitable for use in the development of a non-invasive, brain-computer interface. Copyright © 2010 Elsevier B.V. All rights reserved.

Development of a Plastic Embedding Method for Large-Volume and Fluorescent-Protein-Expressing Tissues

PubMed Central

Yang, Zhongqin; Hu, Bihe; Zhang, Yuhui; Luo, Qingming; Gong, Hui

2013-01-01

Fluorescent proteins serve as important biomarkers for visualizing both subcellular organelles in living cells and structural and functional details in large-volume tissues or organs. However, current techniques for plastic embedding are limited in their ability to preserve fluorescence while remaining suitable for micro-optical sectioning tomography of large-volume samples. In this study, we quantitatively evaluated the fluorescence preservation and penetration time of several commonly used resins in a Thy1-eYFP-H transgenic whole mouse brain, including glycol methacrylate (GMA), LR White, hydroxypropyl methacrylate (HPMA) and Unicryl. We found that HMPA embedding doubled the eYFP fluorescence intensity but required long durations of incubation for whole brain penetration. GMA, Unicryl and LR White each penetrated the brain rapidly but also led to variable quenching of eYFP fluorescence. Among the fast-penetrating resins, GMA preserved fluorescence better than LR White and Unicryl. We found that we could optimize the GMA formulation by reducing the polymerization temperature, removing 4-methoxyphenol and adjusting the pH of the resin solution to be alkaline. By optimizing the GMA formulation, we increased percentage of eYFP fluorescence preservation in GMA-embedded brains nearly two-fold. These results suggest that modified GMA is suitable for embedding large-volume tissues such as whole mouse brain and provide a novel approach for visualizing brain-wide networks. PMID:23577174

Thiamin deficiency on fetal brain development with and without prenatal alcohol exposure.

PubMed

Kloss, Olena; Eskin, N A Michael; Suh, Miyoung

2018-04-01

Adequate thiamin levels are crucial for optimal health through maintenance of homeostasis and viability of metabolic enzymes, which require thiamine as a co-factor. Thiamin deficiency occurs during pregnancy when the dietary intake is inadequate or excessive alcohol is consumed. Thiamin deficiency leads to brain dysfunction because thiamin is involved in the synthesis of myelin and neurotransmitters (e.g., acetylcholine, γ-aminobutyric acid, glutamate), and its deficiency increases oxidative stress by decreasing the production of reducing agents. Thiamin deficiency also leads to neural membrane dysfunction, because thiamin is a structural component of mitochondrial and synaptosomal membranes. Similarly, in-utero exposure to alcohol leads to fetal brain dysfunction, resulting in negative effects such as fetal alcohol spectrum disorder (FASD). Thiamin deficiency and prenatal exposure to alcohol could act synergistically to produce negative effects on fetal development; however, this area of research is currently under-studied. This minireview summarizes the evidence for the potential role of thiamin deficiency in fetal brain development, with or without prenatal exposure to alcohol. Such evidence may influence the development of new nutritional strategies for preventing or mitigating the symptoms of FASD.

Optimism and the brain: trait optimism mediates the protective role of the orbitofrontal cortex gray matter volume against anxiety

PubMed Central

Hu, Yifan; Iordan, Alexandru D.; Moore, Matthew; Dolcos, Florin

2016-01-01

Converging evidence identifies trait optimism and the orbitofrontal cortex (OFC) as personality and brain factors influencing anxiety, but the nature of their relationships remains unclear. Here, the mechanisms underlying the protective role of trait optimism and of increased OFC volume against symptoms of anxiety were investigated in 61 healthy subjects, who completed measures of trait optimism and anxiety, and underwent structural scanning using magnetic resonance imaging. First, the OFC gray matter volume (GMV) was associated with increased optimism, which in turn was associated with reduced anxiety. Second, trait optimism mediated the relation between the left OFC volume and anxiety, thus demonstrating that increased GMV in this brain region protects against symptoms of anxiety through increased optimism. These results provide novel evidence about the brain–personality mechanisms protecting against anxiety symptoms in healthy functioning, and identify potential targets for preventive and therapeutic interventions aimed at reducing susceptibility and increasing resilience against emotional disturbances. PMID:26371336

Exercise, cognition, and the adolescent brain.

PubMed

Herting, Megan M; Chu, Xiaofang

2017-12-01

Few adolescents engage in the recommended levels of physical activity, and daily exercise levels tend to drastically decrease throughout adolescence. Beyond physical health benefits, regular exercise may also have important implications for the teenage brain and cognitive and academic capabilities. This narrative review examines how physical activity and aerobic exercise relate to school performance, cognition, and brain structure and function. A number of studies have found that habitual exercise and physical activity are associated with academic performance, cognitive function, brain structure, and brain activity in adolescents. We also discuss how additional intervention studies that examine a wide range of neurological and cognitive outcomes are necessary, as well as characterizing the type, frequency, and dose of exercise and identifying individual differences that contribute to how exercise may benefit the teen brain. Routine exercise relates to adolescent brain structure and function as well as cognitive performance. Together, these studies suggest that physical activity and aerobic exercise may be important factors for optimal adolescent brain development. © 2017 Wiley Periodicals, Inc.

Novel treatment strategies for brain tumors and metastases

PubMed Central

El-Habashy, Salma E.; Nazief, Alaa M.; Adkins, Chris E.; Wen, Ming Ming; El-Kamel, Amal H.; Hamdan, Ahmed M.; Hanafy, Amira S.; Terrell, Tori O.; Mohammad, Afroz S.; Lockman, Paul R.; Nounou, Mohamed Ismail

2015-01-01

This review summarizes patent applications in the past 5 years for the management of brain tumors and metastases. Most of the recent patents discuss one of the following strategies: the development of new drug entities that specifically target the brain cells, the blood–brain barrier and the tumor cells, tailor-designing a novel carrier system that is able to perform multitasks and multifunction as a drug carrier, targeting vehicle and even as a diagnostic tool, direct conjugation of a US FDA approved drug with a targeting moiety, diagnostic moiety or PK modifying moiety, or the use of innovative nontraditional approaches such as genetic engineering, stem cells and vaccinations. Until now, there has been no optimal strategy to deliver therapeutic agents to the CNS for the treatment of brain tumors and metastases. Intensive research efforts are actively ongoing to take brain tumor targeting, and novel and targeted CNS delivery systems to potential clinical application. PMID:24998288

Bayesian Optimization for Neuroimaging Pre-processing in Brain Age Classification and Prediction

PubMed Central

Lancaster, Jenessa; Lorenz, Romy; Leech, Rob; Cole, James H.

2018-01-01

Neuroimaging-based age prediction using machine learning is proposed as a biomarker of brain aging, relating to cognitive performance, health outcomes and progression of neurodegenerative disease. However, even leading age-prediction algorithms contain measurement error, motivating efforts to improve experimental pipelines. T1-weighted MRI is commonly used for age prediction, and the pre-processing of these scans involves normalization to a common template and resampling to a common voxel size, followed by spatial smoothing. Resampling parameters are often selected arbitrarily. Here, we sought to improve brain-age prediction accuracy by optimizing resampling parameters using Bayesian optimization. Using data on N = 2003 healthy individuals (aged 16–90 years) we trained support vector machines to (i) distinguish between young (<22 years) and old (>50 years) brains (classification) and (ii) predict chronological age (regression). We also evaluated generalisability of the age-regression model to an independent dataset (CamCAN, N = 648, aged 18–88 years). Bayesian optimization was used to identify optimal voxel size and smoothing kernel size for each task. This procedure adaptively samples the parameter space to evaluate accuracy across a range of possible parameters, using independent sub-samples to iteratively assess different parameter combinations to arrive at optimal values. When distinguishing between young and old brains a classification accuracy of 88.1% was achieved, (optimal voxel size = 11.5 mm3, smoothing kernel = 2.3 mm). For predicting chronological age, a mean absolute error (MAE) of 5.08 years was achieved, (optimal voxel size = 3.73 mm3, smoothing kernel = 3.68 mm). This was compared to performance using default values of 1.5 mm3 and 4mm respectively, resulting in MAE = 5.48 years, though this 7.3% improvement was not statistically significant. When assessing generalisability, best performance was achieved when applying the entire Bayesian optimization framework to the new dataset, out-performing the parameters optimized for the initial training dataset. Our study outlines the proof-of-principle that neuroimaging models for brain-age prediction can use Bayesian optimization to derive case-specific pre-processing parameters. Our results suggest that different pre-processing parameters are selected when optimization is conducted in specific contexts. This potentially motivates use of optimization techniques at many different points during the experimental process, which may improve statistical sensitivity and reduce opportunities for experimenter-led bias. PMID:29483870

DARPA challenge: developing new technologies for brain and spinal injuries

NASA Astrophysics Data System (ADS)

Macedonia, Christian; Zamisch, Monica; Judy, Jack; Ling, Geoffrey

2012-06-01

The repair of traumatic injuries to the central nervous system remains among the most challenging and exciting frontiers in medicine. In both traumatic brain injury and spinal cord injuries, the ultimate goals are to minimize damage and foster recovery. Numerous DARPA initiatives are in progress to meet these goals. The PREventing Violent Explosive Neurologic Trauma program focuses on the characterization of non-penetrating brain injuries resulting from explosive blast, devising predictive models and test platforms, and creating strategies for mitigation and treatment. To this end, animal models of blast induced brain injury are being established, including swine and non-human primates. Assessment of brain injury in blast injured humans will provide invaluable information on brain injury associated motor and cognitive dysfunctions. The Blast Gauge effort provided a device to measure warfighter's blast exposures which will contribute to diagnosing the level of brain injury. The program Cavitation as a Damage Mechanism for Traumatic Brain Injury from Explosive Blast developed mathematical models that predict stresses, strains, and cavitation induced from blast exposures, and is devising mitigation technologies to eliminate injuries resulting from cavitation. The Revolutionizing Prosthetics program is developing an avant-garde prosthetic arm that responds to direct neural control and provides sensory feedback through electrical stimulation. The Reliable Neural-Interface Technology effort will devise technologies to optimally extract information from the nervous system to control next generation prosthetic devices with high fidelity. The emerging knowledge and technologies arising from these DARPA programs will significantly improve the treatment of brain and spinal cord injured patients.

Evaluation of Disease Lesions in the Developing Canine MPS IIIA Brain.

PubMed

Winner, Leanne K; Marshall, Neil R; Jolly, Robert D; Trim, Paul J; Duplock, Stephen K; Snel, Marten F; Hemsley, Kim M

2018-06-20

Mucopolysaccharidosis IIIA (MPS IIIA) is an inherited neurodegenerative disease of childhood that results in early death. Post-mortem studies have been carried out on human MPS IIIA brain, but little is known about early disease development. Here, we utilised the Huntaway dog model of MPS IIIA to evaluate disease lesion development from 2 to 24 weeks of age. A significant elevation in primarily stored heparan sulphate was observed in all brain regions assessed in MPS IIIA pups ≤9.5 weeks of age. There was a significant elevation in secondarily stored ganglioside (GM3 36:1) in ≤9.5-week-old MPS IIIA pup cerebellum, and other brain regions also exhibited accumulation of this lipid with time. The number of neural stem cells and neuronal precursor cells was essentially unchanged in MPS IIIA dog brain (c.f. unaffected) over the time course assessed, a finding corroborated by neuron cell counts. We observed early neuroinflammatory changes in young MPS IIIA pup brain, with significantly increased numbers of activated microglia recorded in all but one brain region in MPS IIIA pups ≤9.5 weeks of age (c.f. age-matched unaffected pups). In conclusion, infant-paediatric-stage MPS IIIA canine brain exhibits substantial and progressive primary and secondary substrate accumulation, coupled with early and robust microgliosis. Whilst early initiation of treatment is likely to be required to maintain optimal neurological function, the brain's neurodevelopmental potential appears largely unaffected by the disease process; further investigations confirming this are warranted.

The treatment of Parkinson's disease with deep brain stimulation: current issues.

PubMed

Moldovan, Alexia-Sabine; Groiss, Stefan Jun; Elben, Saskia; Südmeyer, Martin; Schnitzler, Alfons; Wojtecki, Lars

2015-07-01

Deep brain stimulation has become a well-established symptomatic treatment for Parkinson's disease during the last 25 years. Besides improving motor symptoms and long-term motor complications, positive effects on patients' mobility, activities of daily living, emotional well-being and health-related quality of life have been recognized. Apart from that, numerous clinical trials analyzed effects on non-motor symptoms and side effects of deep brain stimulation. Several technical issues and stimulation paradigms have been and are still being developed to optimize the therapeutic effects, minimize the side effects and facilitate handling. This review summarizes current therapeutic issues, i.e., patient and target selection, surgical procedure and programming paradigms. In addition it focuses on neuropsychological effects and side effects of deep brain stimulation.

Parallel workflow tools to facilitate human brain MRI post-processing

PubMed Central

Cui, Zaixu; Zhao, Chenxi; Gong, Gaolang

2015-01-01

Multi-modal magnetic resonance imaging (MRI) techniques are widely applied in human brain studies. To obtain specific brain measures of interest from MRI datasets, a number of complex image post-processing steps are typically required. Parallel workflow tools have recently been developed, concatenating individual processing steps and enabling fully automated processing of raw MRI data to obtain the final results. These workflow tools are also designed to make optimal use of available computational resources and to support the parallel processing of different subjects or of independent processing steps for a single subject. Automated, parallel MRI post-processing tools can greatly facilitate relevant brain investigations and are being increasingly applied. In this review, we briefly summarize these parallel workflow tools and discuss relevant issues. PMID:26029043

The free-energy principle: a unified brain theory?

PubMed

Friston, Karl

2010-02-01

A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories - optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.

Glial molecular alterations with mouse brain development and aging: up-regulation of the Kir4.1 and aquaporin-4.

PubMed

Gupta, Rajaneesh Kumar; Kanungo, Madhusudan

2013-02-01

Glial cells, besides participating as passive supporting matrix, are also proposed to be involved in the optimization of the interstitial space for synaptic transmission by tight control of ionic and water homeostasis. In adult mouse brain, inwardly rectifying K+ (Kir4.1) and aquaporin-4 (AQP4) channels localize to astroglial endfeets in contact with brain microvessels and glutamate synapses, optimizing clearance of extracellular K(+) and water from the synaptic layers. However, it is still unclear whether there is an age-dependent difference in the expressions of Kir4.1 and AQP4 channels specifically during postnatal development and aging when various marked changes occur in brain and if these changes region specific. RT-PCR and immunoblotting was conducted to compare the relative expression of Kir4.1 and AQP4 mRNA and protein in the early and mature postnatal (0-, 15-, 45-day), adult (20-week), and old age (70-week) mice cerebral and cerebellar cortices. Expressions of Kir4.1 and AQP4 mRNA and protein are very low at 0-day. A pronounced and continuous increase was observed by mature postnatal ages (15-, 45-days). However, in the 70-week-old mice, expressions are significantly up-regulated as compared to 20-week-old mice. Both genes follow the same age-related pattern in both cerebral and cerebellar cortices. The time course and expression pattern suggests that Kir4.1 and AQP4 channels may play an important role in brain K(+) and water homeostasis in early postnatal weeks after birth and during aging.

Thyroid-disrupting chemicals and brain development: an update

PubMed Central

Mughal, Bilal B; Fini, Jean-Baptiste; Demeneix, Barbara A

2018-01-01

This review covers recent findings on the main categories of thyroid hormone–disrupting chemicals and their effects on brain development. We draw mostly on epidemiological and experimental data published in the last decade. For each chemical class considered, we deal with not only the thyroid hormone–disrupting effects but also briefly mention the main mechanisms by which the same chemicals could modify estrogen and/or androgen signalling, thereby exacerbating adverse effects on endocrine-dependent developmental programmes. Further, we emphasize recent data showing how maternal thyroid hormone signalling during early pregnancy affects not only offspring IQ, but also neurodevelopmental disease risk. These recent findings add to established knowledge on the crucial importance of iodine and thyroid hormone for optimal brain development. We propose that prenatal exposure to mixtures of thyroid hormone–disrupting chemicals provides a plausible biological mechanism contributing to current increases in the incidence of neurodevelopmental disease and IQ loss. PMID:29572405

Insight from animal models of environmentally-driven epigenetic changes in the developing and adult brain

PubMed Central

Doherty, Tiffany S.; Roth, Tania L.

2017-01-01

The efforts of many neuroscientists are directed toward understanding the appreciable plasticity of the brain and behavior. In recent years, epigenetics has become a core of this focus as a prime mechanistic candidate for behavioral modifications. Animal models have been instrumental in advancing our understanding of environmentally-driven changes to the epigenome in the developing and adult brain. This review focuses mainly on such discoveries driven by adverse environments along with their associated behavioral outcomes. While much of the evidence discussed focuses on epigenetics within the central nervous system, several peripheral studies in humans who have experienced significant adversity are also highlighted. As we continue to unravel the link between epigenetics and phenotype, discerning the complexity and specificity of epigenetic changes induced by environments is an important step toward understanding optimal development and how to prevent or ameliorate behavioral deficits bred by disruptive environments. PMID:27687803

Development of a systems-based in situ multiplex biomarker screening approach for the assessment of immunopathology and neural tissue plasticity in male rats after traumatic brain injury.

PubMed

Bogoslovsky, Tanya; Bernstock, Joshua D; Bull, Greg; Gouty, Shawn; Cox, Brian M; Hallenbeck, John M; Maric, Dragan

2018-04-01

Traumatic brain injuries (TBIs) pose a massive burden of disease and continue to be a leading cause of morbidity and mortality throughout the world. A major obstacle in developing effective treatments is the lack of comprehensive understanding of the underlying mechanisms that mediate tissue damage and recovery after TBI. As such, our work aims to highlight the development of a novel experimental platform capable of fully characterizing the underlying pathobiology that unfolds after TBI. This platform encompasses an empirically optimized multiplex immunohistochemistry staining and imaging system customized to screen for a myriad of biomarkers required to comprehensively evaluate the extent of neuroinflammation, neural tissue damage, and repair in response to TBI. Herein, we demonstrate that our multiplex biomarker screening platform is capable of evaluating changes in both the topographical location and functional states of resident and infiltrating cell types that play a role in neuropathology after controlled cortical impact injury to the brain in male Sprague-Dawley rats. Our results demonstrate that our multiplex biomarker screening platform lays the groundwork for the comprehensive characterization of changes that occur within the brain after TBI. Such work may ultimately lead to the understanding of the governing pathobiology of TBI, thereby fostering the development of novel therapeutic interventions tailored to produce optimal tissue protection, repair, and/or regeneration with minimal side effects, and may ultimately find utility in a wide variety of other neurological injuries, diseases, and disorders that share components of TBI pathobiology. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

The kinematic architecture of the Active Headframe: A new head support for awake brain surgery.

PubMed

Malosio, Matteo; Negri, Simone Pio; Pedrocchi, Nicola; Vicentini, Federico; Cardinale, Francesco; Tosatti, Lorenzo Molinari

2012-01-01

This paper presents the novel hybrid kinematic structure of the Active Headframe, a robotic head support to be employed in brain surgery operations for an active and dynamic control of the patient's head position and orientation, particularly addressing awake surgery requirements. The topology has been conceived in order to satisfy all the installation, functional and dynamic requirements. A kinetostatic optimization has been performed to obtain the actual geometric dimensions of the prototype currently being developed.

Brain SPECT Imaging in Complex Psychiatric Cases: An Evidence-Based, Underutilized Tool

PubMed Central

Amen, Daniel G; Trujillo, Manuel; Newberg, Andrew; Willeumier, Kristen; Tarzwell, Robert; Wu, Joseph C; Chaitin, Barry

2011-01-01

Over the past 20 years brain Single Photon Emission Computed Tomography (SPECT) imaging has developed a substantial, evidence-based foundation and is now recommended by professional societies for numerous indications relevant to psychiatric practice. Unfortunately, SPECT in clinical practice is utilized by only a handful of clinicians. This article presents a rationale for a more widespread use of SPECT in clinical practice for complex cases, and includes seven clinical applications where it may help optimize patient care. PMID:21863144

Mapping White Matter Microstructure in the One Month Human Brain.

PubMed

Dean, D C; Planalp, E M; Wooten, W; Adluru, N; Kecskemeti, S R; Frye, C; Schmidt, C K; Schmidt, N L; Styner, M A; Goldsmith, H H; Davidson, R J; Alexander, A L

2017-08-29

White matter microstructure, essential for efficient and coordinated transmission of neural communications, undergoes pronounced development during the first years of life, while deviations to this neurodevelopmental trajectory likely result in alterations of brain connectivity relevant to behavior. Hence, systematic evaluation of white matter microstructure in the normative brain is critical for a neuroscientific approach to both typical and atypical early behavioral development. However, few studies have examined the infant brain in detail, particularly in infants under 3 months of age. Here, we utilize quantitative techniques of diffusion tensor imaging and neurite orientation dispersion and density imaging to investigate neonatal white matter microstructure in 104 infants. An optimized multiple b-value diffusion protocol was developed to allow for successful acquisition during non-sedated sleep. Associations between white matter microstructure measures and gestation corrected age, regional asymmetries, infant sex, as well as newborn growth measures were assessed. Results highlight changes of white matter microstructure during the earliest periods of development and demonstrate differential timing of developing regions and regional asymmetries. Our results contribute to a growing body of research investigating the neurobiological changes associated with neurodevelopment and suggest that characteristics of white matter microstructure are already underway in the weeks immediately following birth.

Determining Optimal Post-Stroke Exercise (DOSE)

ClinicalTrials.gov

2018-02-13

Cerebrovascular Accident; Stroke; Cerebral Infarction; Brain Infarction; Brain Ischemia; Cerebrovascular Disorders; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Vascular Diseases

The effect of nanoparticle size on the ability to cross the blood-brain barrier: an in vivo study.

PubMed

Betzer, Oshra; Shilo, Malka; Opochinsky, Renana; Barnoy, Eran; Motiei, Menachem; Okun, Eitan; Yadid, Gal; Popovtzer, Rachela

2017-07-01

Our goal was to develop an efficient nanoparticle-based system that can overcome the restrictive mechanism of the blood-brain barrier (BBB) by targeting insulin receptors and would thus enable drug delivery to the brain. Insulin-coated gold nanoparticles (INS-GNPs) were synthesized to serve as a BBB transport system. The effect of nanoparticle size (20, 50 and 70 nm) on their ability to cross the BBB was quantitatively investigated in Balb/C mice. The most widespread biodistribution and highest accumulation within the brain were observed using 20 nm INS-GNPs, 2 h post injection. In vivo CT imaging revealed that particles migrated to specific brain regions, which are involved in neurodegenerative and neuropsychiatric disorders. These findings promote the optimization of nanovehicles for transport of drugs through the BBB. The insulin coating of the particles enabled targeting of specific brain regions, suggesting the potential use of INS-GNPs for delivery of various treatments for brain-related disorders.

Early functional and morphological brain disturbances in late-onset intrauterine growth restriction.

PubMed

Starčević, Mirta; Predojević, Maja; Butorac, Dražan; Tumbri, Jasna; Konjevoda, Paško; Kadić, Aida Salihagić

2016-02-01

To determine whether the brain disturbances develop in late-onset intrauterine growth restriction (IUGR) before blood flow redistribution towards the fetal brain (detected by Doppler measurements in the middle cerebral artery and umbilical artery). Further, to evaluate predictive values of Doppler arterial indices and umbilical cord blood gases and pH for early functional and/or morphological brain disturbances in late-onset IUGR. This cohort study included 60 singleton term pregnancies with placental insufficiency caused late-onset IUGR (IUGR occurring after 34 gestational weeks). Umbilical artery resistance index (URI), middle cerebral artery resistance index (CRI), and cerebroumbilical (C/U) ratio (CRI/URI) were monitored once weekly. Umbilical blood cord samples (arterial and venous) were collected for the analysis of pO2, pCO2 and pH. Morphological neurological outcome was evaluated by cranial ultrasound (cUS), whereas functional neurological outcome by Amiel-Tison Neurological Assessment at Term (ATNAT). 50 fetuses had C/U ratio>1, and 10 had C/U ratio≤1; among these 10 fetuses, 9 had abnormal neonatal cUS findings and all 10 had non-optimal ATNAT. However, the total number of abnormal neurological findings was much higher. 32 neonates had abnormal cUS (53.37%), and 42 (70.00%) had non-optimal ATNAT. Furthermore, Doppler indices had higher predictive validity for early brain disturbances than umbilical cord blood gases and pH. C/U ratio had the highest predictive validity with threshold for adverse neurological outcome at value 1.13 (ROC analysis), i.e., 1.18 (party machine learning algorithm). Adverse neurological outcome at average values of C/U ratios>1 confirmed that early functional and/or structural brain disturbances in late-onset IUGR develop even before activation of fetal cardiovascular compensatory mechanisms, i.e., before Doppler signs of blood flow redistribution between the fetal brain and the placenta. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Reduced Cortical Activity Impairs Development and Plasticity after Neonatal Hypoxia Ischemia

PubMed Central

Ranasinghe, Sumudu; Or, Grace; Wang, Eric Y.; Ievins, Aiva; McLean, Merritt A.; Niell, Cristopher M.; Chau, Vann; Wong, Peter K. H.; Glass, Hannah C.; Sullivan, Joseph

2015-01-01

Survivors of preterm birth are at high risk of pervasive cognitive and learning impairments, suggesting disrupted early brain development. The limits of viability for preterm birth encompass the third trimester of pregnancy, a “precritical period” of activity-dependent development characterized by the onset of spontaneous and evoked patterned electrical activity that drives neuronal maturation and formation of cortical circuits. Reduced background activity on electroencephalogram (EEG) is a sensitive marker of brain injury in human preterm infants that predicts poor neurodevelopmental outcome. We studied a rodent model of very early hypoxic–ischemic brain injury to investigate effects of injury on both general background and specific patterns of cortical activity measured with EEG. EEG background activity is depressed transiently after moderate hypoxia–ischemia with associated loss of spindle bursts. Depressed activity, in turn, is associated with delayed expression of glutamate receptor subunits and transporters. Cortical pyramidal neurons show reduced dendrite development and spine formation. Complementing previous observations in this model of impaired visual cortical plasticity, we find reduced somatosensory whisker barrel plasticity. Finally, EEG recordings from human premature newborns with brain injury demonstrate similar depressed background activity and loss of bursts in the spindle frequency band. Together, these findings suggest that abnormal development after early brain injury may result in part from disruption of specific forms of brain activity necessary for activity-dependent circuit development. SIGNIFICANCE STATEMENT Preterm birth and term birth asphyxia result in brain injury from inadequate oxygen delivery and constitute a major and growing worldwide health problem. Poor outcomes are noted in a majority of very premature (<25 weeks gestation) newborns, resulting in death or life-long morbidity with motor, sensory, learning, behavioral, and language disabilities that limit academic achievement and well-being. Limited progress has been made to develop therapies that improve neurologic outcomes. The overall objective of this study is to understand the effect of early brain injury on activity-dependent brain development and cortical plasticity to develop new treatments that will optimize repair and recovery after brain injury. PMID:26311776

Design and optimization of an ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature.

PubMed

Rodrigues, Dario B; Maccarini, Paolo F; Salahi, Sara; Oliveira, Tiago R; Pereira, Pedro J S; Limao-Vieira, Paulo; Snow, Brent W; Reudink, Doug; Stauffer, Paul R

2014-07-01

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (η) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 °C of the measured brain phantom temperature when the brain phantom is lowered 10 °C and then returned to the original temperature (37 °C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Improved plan quality with automated radiotherapy planning for whole brain with hippocampus sparing: a comparison to the RTOG 0933 trial.

PubMed

Krayenbuehl, J; Di Martino, M; Guckenberger, M; Andratschke, N

2017-10-02

Whole-brain radiation therapy (WBRT) with hippocampus sparing (HS) has been investigated by the radiation oncology working group (RTOG) 0933 trial for patients with multiple brain metastases. They showed a decrease of adverse neurocognitive effects with HS WBRT compared to WBRT alone. With the development of automated treatment planning system (aTPS) in the last years, a standardization of the plan quality at a high level was achieved. The goal of this study was to evaluate the feasibility of using an aTPS for the treatment of HS WBRT and see if the RTOG 0933 dose constraints could be achieved and improved. Ten consecutive patients treated with HS WBRT were enrolled in this study. 10 × 3 Gy was prescribed according to the RTOG 0933 protocol to 92% of the target volume (whole-brain excluding the hippocampus expanded by 5 mm in 3-dimensions). In contrast to RTOG 0933, the maximum allowed point dose to normal brain was significantly lowered and restricted to 36.5 Gy. All patients were planned with volumetric modulated arc therapy (VMAT) technique using four arcs. Plans were optimized using Auto-Planning (AP) (Philips Radiation Oncology Systems) with one single AP template and optimization. All the constraints from the RTOG 0933 trial were achieved. A significant improvement for the maximal dose to 2% of the brain with a reduction of 4 Gy was achieved (33.5 Gy vs. RTOG 37.5 Gy) and the minimum hippocampus dose was reduced by 10% (8.1 Gy vs. RTOG 9 Gy). A steep dose gradient around the hippocampus was achieved with a mean dose of 27.3 Gy at a distance between 0.5 cm and 1 cm from the hippocampus. The effective working time to optimize a plan was kept below 6'. Automated treatment planning for HS WBRT was able to fulfil all the recommendations from the RTOG 0933 study while significantly improving dose homogeneity and decreasing unnecessary hot spot in the normal brain. With this approach, a standardization of plan quality was achieved and the effective time required for plan optimization was minimized.

Myelination, oligodendrocytes, and serious mental illness.

PubMed

Haroutunian, V; Katsel, P; Roussos, P; Davis, K L; Altshuler, L L; Bartzokis, G

2014-11-01

Historically, the human brain has been conceptually segregated from the periphery and further dichotomized into gray matter (GM) and white matter (WM) based on the whitish appearance of the exceptionally high lipid content of the myelin sheaths encasing neuronal axons. These simplistic dichotomies were unfortunately extended to conceptually segregate neurons from glia, cognition from behavior, and have been codified in the separation of clinical and scientific fields into medicine, psychiatry, neurology, pathology, etc. The discrete classifications have helped obscure the importance of continual dynamic communication between all brain cell types (neurons, astrocytes, microglia, oligodendrocytes, and precursor (NG2) cells) as well as between brain and periphery through multiple signaling systems. The signaling systems range from neurotransmitters to insulin, angiotensin, and multiple kinases such a glycogen synthase kinase 3 (GSK-3) that together help integrate metabolism, inflammation, and myelination processes and orchestrate the development, plasticity, maintenance, and repair that continually optimize function of neural networks. A more comprehensive, evolution-based, systems biology approach that integrates brain, body, and environmental interactions may ultimately prove more fruitful in elucidating the complexities of human brain function. The historic focus on neurons/GM is rebalanced herein by highlighting the importance of a systems-level understanding of the interdependent age-related shifts in both central and peripheral homeostatic mechanisms that can lead to remarkably prevalent and devastating neuropsychiatric diseases. Herein we highlight the role of glia, especially the most recently evolved oligodendrocytes and the myelin they produce, in achieving and maintaining optimal brain function. The human brain undergoes exceptionally protracted and pervasive myelination (even throughout its GM) and can thus achieve and maintain the rapid conduction and synchronous timing of neural networks on which optimal function depends. The continuum of increasing myelin vulnerability resulting from the human brain's protracted myelination underlies underappreciated communalities between different disease phenotypes ranging from developmental ones such as schizophrenia (SZ) and bipolar disorder (BD) to degenerative ones such as Alzheimer's disease (AD). These shared vulnerabilities also expose significant yet underexplored opportunities for novel treatment and prevention approaches that have the potential to considerably reduce the tremendous burden of neuropsychiatric disease. © 2014 Wiley Periodicals, Inc.

Point-based warping with optimized weighting factors of displacement vectors

NASA Astrophysics Data System (ADS)

Pielot, Ranier; Scholz, Michael; Obermayer, Klaus; Gundelfinger, Eckart D.; Hess, Andreas

2000-06-01

The accurate comparison of inter-individual 3D image brain datasets requires non-affine transformation techniques (warping) to reduce geometric variations. Constrained by the biological prerequisites we use in this study a landmark-based warping method with weighted sums of displacement vectors, which is enhanced by an optimization process. Furthermore, we investigate fast automatic procedures for determining landmarks to improve the practicability of 3D warping. This combined approach was tested on 3D autoradiographs of Gerbil brains. The autoradiographs were obtained after injecting a non-metabolized radioactive glucose derivative into the Gerbil thereby visualizing neuronal activity in the brain. Afterwards the brain was processed with standard autoradiographical methods. The landmark-generator computes corresponding reference points simultaneously within a given number of datasets by Monte-Carlo-techniques. The warping function is a distance weighted exponential function with a landmark- specific weighting factor. These weighting factors are optimized by a computational evolution strategy. The warping quality is quantified by several coefficients (correlation coefficient, overlap-index, and registration error). The described approach combines a highly suitable procedure to automatically detect landmarks in autoradiographical brain images and an enhanced point-based warping technique, optimizing the local weighting factors. This optimization process significantly improves the similarity between the warped and the target dataset.

An agenda for 21st century neurodevelopmental medicine: lessons from autism.

PubMed

Klin, A; Jones, W

2018-03-01

The future of neurodevelopmental medicine has the potential of situating child neurology at the forefront of a broad-based public health effort to optimize neurodevelopmental outcomes of children born with high-prevalence and diverse genetic, pre- and peri-natal, and environmental burdens compromising early brain development and leading to lifetime disabilities. Building on advancements in developmental social neuroscience and in implementation science, this shift is already occurring in the case of emblematic neurodevelopmental disorders such as autism. Capitalizing on early neuroplasticity and on quantification of trajectories of social-communicative development, new technologies are emerging for high-throughput and cost-effective diagnosis and for community-viable delivery of powerful treatments, in seamless integration across previously fragmented systems of healthcare delivery. These solutions could be deployed in the case of other groups of children at greater risk for autism and communication delays, such as those born extremely premature or with congenital heart disease. The galvanizing concept in this aspirational future is a public health focus on promoting optimal conditions for early brain development, not unlike current campaigns promoting pre-natal care, nutrition or vaccination.

Particle swarm optimization and its application in MEG source localization using single time sliced data

NASA Astrophysics Data System (ADS)

Lin, Juan; Liu, Chenglian; Guo, Yongning

2014-10-01

The estimation of neural active sources from the magnetoencephalography (MEG) data is a very critical issue for both clinical neurology and brain functions research. A widely accepted source-modeling technique for MEG involves calculating a set of equivalent current dipoles (ECDs). Depth in the brain is one of difficulties in MEG source localization. Particle swarm optimization(PSO) is widely used to solve various optimization problems. In this paper we discuss its ability and robustness to find the global optimum in different depths of the brain when using single equivalent current dipole (sECD) model and single time sliced data. The results show that PSO is an effective global optimization to MEG source localization when given one dipole in different depths.

Modeling Brain Dynamics in Brain Tumor Patients Using the Virtual Brain.

PubMed

Aerts, Hannelore; Schirner, Michael; Jeurissen, Ben; Van Roost, Dirk; Achten, Eric; Ritter, Petra; Marinazzo, Daniele

2018-01-01

Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong-Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

Optimization of SSVEP brain responses with application to eight-command Brain-Computer Interface.

PubMed

Bakardjian, Hovagim; Tanaka, Toshihisa; Cichocki, Andrzej

2010-01-18

This study pursues the optimization of the brain responses to small reversing patterns in a Steady-State Visual Evoked Potentials (SSVEP) paradigm, which could be used to maximize the efficiency of applications such as Brain-Computer Interfaces (BCI). We investigated the SSVEP frequency response for 32 frequencies (5-84 Hz), and the time dynamics of the brain response at 8, 14 and 28 Hz, to aid the definition of the optimal neurophysiological parameters and to outline the onset-delay and other limitations of SSVEP stimuli in applications such as our previously described four-command BCI system. Our results showed that the 5.6-15.3 Hz pattern reversal stimulation evoked the strongest responses, peaking at 12 Hz, and exhibiting weaker local maxima at 28 and 42 Hz. After stimulation onset, the long-term SSVEP response was highly non-stationary and the dynamics, including the first peak, was frequency-dependent. The evaluation of the performance of a frequency-optimized eight-command BCI system with dynamic neurofeedback showed a mean success rate of 98%, and a time delay of 3.4s. Robust BCI performance was achieved by all subjects even when using numerous small patterns clustered very close to each other and moving rapidly in 2D space. These results emphasize the need for SSVEP applications to optimize not only the analysis algorithms but also the stimuli in order to maximize the brain responses they rely on. (c) 2009 Elsevier Ireland Ltd. All rights reserved.

Pre-Adult MRI of Brain Cancer and Neurological Injury: Multivariate Analyses

PubMed Central

Levman, Jacob; Takahashi, Emi

2016-01-01

Brain cancer and neurological injuries, such as stroke, are life-threatening conditions for which further research is needed to overcome the many challenges associated with providing optimal patient care. Multivariate analysis (MVA) is a class of pattern recognition technique involving the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neuroimaging challenges, including identifying variables associated with patient outcomes; understanding an injury’s etiology, development, and progression; creating diagnostic tests; assisting in treatment monitoring; and more. Compared to adults, imaging of the developing brain has attracted less attention from MVA researchers, however, remarkable MVA growth has occurred in recent years. This paper presents the results of a systematic review of the literature focusing on MVA technologies applied to brain injury and cancer in neurological fetal, neonatal, and pediatric magnetic resonance imaging (MRI). With a wide variety of MRI modalities providing physiologically meaningful biomarkers and new biomarker measurements constantly under development, MVA techniques hold enormous potential toward combining available measurements toward improving basic research and the creation of technologies that contribute to improving patient care. PMID:27446888

Mid-sagittal plane and mid-sagittal surface optimization in brain MRI using a local symmetry measure

NASA Astrophysics Data System (ADS)

Stegmann, Mikkel B.; Skoglund, Karl; Ryberg, Charlotte

2005-04-01

This paper describes methods for automatic localization of the mid-sagittal plane (MSP) and mid-sagittal surface (MSS). The data used is a subset of the Leukoaraiosis And DISability (LADIS) study consisting of three-dimensional magnetic resonance brain data from 62 elderly subjects (age 66 to 84 years). Traditionally, the mid-sagittal plane is localized by global measures. However, this approach fails when the partitioning plane between the brain hemispheres does not coincide with the symmetry plane of the head. We instead propose to use a sparse set of profiles in the plane normal direction and maximize the local symmetry around these using a general-purpose optimizer. The plane is parameterized by azimuth and elevation angles along with the distance to the origin in the normal direction. This approach leads to solutions confirmed as the optimal MSP in 98 percent of the subjects. Despite the name, the mid-sagittal plane is not always planar, but a curved surface resulting in poor partitioning of the brain hemispheres. To account for this, this paper also investigates an optimization strategy which fits a thin-plate spline surface to the brain data using a robust least median of squares estimator. Albeit computationally more expensive, mid-sagittal surface fitting demonstrated convincingly better partitioning of curved brains into cerebral hemispheres.

Nutritional strategies to optimise cognitive function in the aging brain.

PubMed

Wahl, Devin; Cogger, Victoria C; Solon-Biet, Samantha M; Waern, Rosilene V R; Gokarn, Rahul; Pulpitel, Tamara; Cabo, Rafael de; Mattson, Mark P; Raubenheimer, David; Simpson, Stephen J; Le Couteur, David G

2016-11-01

Old age is the greatest risk factor for most neurodegenerative diseases. During recent decades there have been major advances in understanding the biology of aging, and the development of nutritional interventions that delay aging including calorie restriction (CR) and intermittent fasting (IF), and chemicals that influence pathways linking nutrition and aging processes. CR influences brain aging in many animal models and recent findings suggest that dietary interventions can influence brain health and dementia in older humans. The role of individual macronutrients in brain aging also has been studied, with conflicting results about the effects of dietary protein and carbohydrates. A new approach known as the Geometric Framework (GF) has been used to unravel the complex interactions between macronutrients (protein, fat, and carbohydrate) and total energy on outcomes such as aging. These studies have shown that low-protein, high-carbohydrate (LPHC) diets are optimal for lifespan in ad libitum fed animals, while total calories have minimal effect once macronutrients are taken into account. One of the primary purposes of this review is to explore the notion that macronutrients may have a more translational potential than CR and IF in humans, and therefore there is a pressing need to use GF to study the impact of diet on brain aging. Furthermore, given the growing recognition of the role of aging biology in dementia, such studies might provide a new approach for dietary interventions for optimizing brain health and preventing dementia in older people. Copyright © 2016 Elsevier B.V. All rights reserved.

Can brain impermeable BACE1 inhibitors serve as anti-CAA medicine?

PubMed

Li, Jian-Ming; Huang, Li-Ling; Liu, Fei; Tang, Bei-Sha; Yan, Xiao-Xin

2017-08-25

Cerebral amyloid angiopathy (CAA) is characterized by the deposition of ß-amyloid peptides (Aß) in and surrounding the wall of microvasculature in the central nervous system, together with parenchymal amyloid plaques collectively referred to as cerebral amyloidosis, which occurs in the brain commonly among the elderly and more frequently in patients with Alzheimer's disease (AD). CAA is associated with vascular injury and may cause devastating neurological outcomes. No therapeutic approach is available for this lesion to date. ß-Secretase 1 (BACE1) is the enzyme initiating Aß production. Brain permeable BACE1 inhibitors targeting primarily at the parenchymal plaque pathology are currently evaluated in clinical trials. This article presents findings in support of a role of BACE1 elevation in the development of CAA, in addition to plaque pathogenesis. The rationale, feasibility, benefit and strategic issues for developing BACE1 inhibitors against CAA are discussed. Brain impermeable compounds are considered preferable as they might exhibit sufficient anti-CAA efficacy without causing significant neuronal/synaptic side effects. Early pharmacological intervention to the pathogenesis of CAA is expected to provide significant protection for cerebral vascular health and hence brain health. Brain impermeable BACE1 inhibitors should be optimized and tested as potential anti-CAA therapeutics.

The treatment of Parkinson's disease with deep brain stimulation: current issues

PubMed Central

Moldovan, Alexia-Sabine; Groiss, Stefan Jun; Elben, Saskia; Südmeyer, Martin; Schnitzler, Alfons; Wojtecki, Lars

2015-01-01

Deep brain stimulation has become a well-established symptomatic treatment for Parkinson's disease during the last 25 years. Besides improving motor symptoms and long-term motor complications, positive effects on patients’ mobility, activities of daily living, emotional well-being and health-related quality of life have been recognized. Apart from that, numerous clinical trials analyzed effects on non-motor symptoms and side effects of deep brain stimulation. Several technical issues and stimulation paradigms have been and are still being developed to optimize the therapeutic effects, minimize the side effects and facilitate handling. This review summarizes current therapeutic issues, i.e., patient and target selection, surgical procedure and programming paradigms. In addition it focuses on neuropsychological effects and side effects of deep brain stimulation. PMID:26330809

Hardware enhance of brain computer interfaces

NASA Astrophysics Data System (ADS)

Wu, Jerry; Szu, Harold; Chen, Yuechen; Guo, Ran; Gu, Xixi

2015-05-01

The history of brain-computer interfaces (BCIs) starts with Hans Berger's discovery of the electrical activity of the human brain and the development of electroencephalography (EEG). Recent years, BCI researches are focused on Invasive, Partially invasive, and Non-invasive BCI. Furthermore, EEG can be also applied to telepathic communication which could provide the basis for brain-based communication using imagined speech. It is possible to use EEG signals to discriminate the vowels and consonants embedded in spoken and in imagined words and apply to military product. In this report, we begin with an example of using high density EEG with high electrode density and analysis the results by using BCIs. The BCIs in this work is enhanced by A field-programmable gate array (FPGA) board with optimized two dimension (2D) image Fast Fourier Transform (FFT) analysis.

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

PubMed

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

2018-02-26

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

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

PubMed Central

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

2018-01-01

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

Deformably registering and annotating whole CLARITY brains to an atlas via masked LDDMM

NASA Astrophysics Data System (ADS)

Kutten, Kwame S.; Vogelstein, Joshua T.; Charon, Nicolas; Ye, Li; Deisseroth, Karl; Miller, Michael I.

2016-04-01

The CLARITY method renders brains optically transparent to enable high-resolution imaging in the structurally intact brain. Anatomically annotating CLARITY brains is necessary for discovering which regions contain signals of interest. Manually annotating whole-brain, terabyte CLARITY images is difficult, time-consuming, subjective, and error-prone. Automatically registering CLARITY images to a pre-annotated brain atlas offers a solution, but is difficult for several reasons. Removal of the brain from the skull and subsequent storage and processing cause variable non-rigid deformations, thus compounding inter-subject anatomical variability. Additionally, the signal in CLARITY images arises from various biochemical contrast agents which only sparsely label brain structures. This sparse labeling challenges the most commonly used registration algorithms that need to match image histogram statistics to the more densely labeled histological brain atlases. The standard method is a multiscale Mutual Information B-spline algorithm that dynamically generates an average template as an intermediate registration target. We determined that this method performs poorly when registering CLARITY brains to the Allen Institute's Mouse Reference Atlas (ARA), because the image histogram statistics are poorly matched. Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically finds the brain boundary and learns the optimal deformation between the brain and atlas masks. Using Mask-LDDMM without an average template provided better results than the standard approach when registering CLARITY brains to the ARA. The LDDMM pipelines developed here provide a fast automated way to anatomically annotate CLARITY images; our code is available as open source software at http://NeuroData.io.

Mapping Epileptic Activity: Sources or Networks for the Clinicians?

PubMed Central

Pittau, Francesca; Mégevand, Pierre; Sheybani, Laurent; Abela, Eugenio; Grouiller, Frédéric; Spinelli, Laurent; Michel, Christoph M.; Seeck, Margitta; Vulliemoz, Serge

2014-01-01

Epileptic seizures of focal origin are classically considered to arise from a focal epileptogenic zone and then spread to other brain regions. This is a key concept for semiological electro-clinical correlations, localization of relevant structural lesions, and selection of patients for epilepsy surgery. Recent development in neuro-imaging and electro-physiology and combinations, thereof, have been validated as contributory tools for focus localization. In parallel, these techniques have revealed that widespread networks of brain regions, rather than a single epileptogenic region, are implicated in focal epileptic activity. Sophisticated multimodal imaging and analysis strategies of brain connectivity patterns have been developed to characterize the spatio-temporal relationships within these networks by combining the strength of both techniques to optimize spatial and temporal resolution with whole-brain coverage and directional connectivity. In this paper, we review the potential clinical contribution of these functional mapping techniques as well as invasive electrophysiology in human beings and animal models for characterizing network connectivity. PMID:25414692

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

Decentralized Multisensory Information Integration in Neural Systems.

PubMed

Zhang, Wen-Hao; Chen, Aihua; Rasch, Malte J; Wu, Si

2016-01-13

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that the decentralized system can integrate information optimally, with the reciprocal connections between processers determining the extent of cue integration. Our model reproduces known multisensory integration behaviors observed in experiments and sheds new light on our understanding of how information is integrated in the brain. Copyright © 2016 Zhang et al.

Decentralized Multisensory Information Integration in Neural Systems

PubMed Central

Zhang, Wen-hao; Chen, Aihua

2016-01-01

How multiple sensory cues are integrated in neural circuitry remains a challenge. The common hypothesis is that information integration might be accomplished in a dedicated multisensory integration area receiving feedforward inputs from the modalities. However, recent experimental evidence suggests that it is not a single multisensory brain area, but rather many multisensory brain areas that are simultaneously involved in the integration of information. Why many mutually connected areas should be needed for information integration is puzzling. Here, we investigated theoretically how information integration could be achieved in a distributed fashion within a network of interconnected multisensory areas. Using biologically realistic neural network models, we developed a decentralized information integration system that comprises multiple interconnected integration areas. Studying an example of combining visual and vestibular cues to infer heading direction, we show that such a decentralized system is in good agreement with anatomical evidence and experimental observations. In particular, we show that this decentralized system can integrate information optimally. The decentralized system predicts that optimally integrated information should emerge locally from the dynamics of the communication between brain areas and sheds new light on the interpretation of the connectivity between multisensory brain areas. SIGNIFICANCE STATEMENT To extract information reliably from ambiguous environments, the brain integrates multiple sensory cues, which provide different aspects of information about the same entity of interest. Here, we propose a decentralized architecture for multisensory integration. In such a system, no processor is in the center of the network topology and information integration is achieved in a distributed manner through reciprocally connected local processors. Through studying the inference of heading direction with visual and vestibular cues, we show that the decentralized system can integrate information optimally, with the reciprocal connections between processers determining the extent of cue integration. Our model reproduces known multisensory integration behaviors observed in experiments and sheds new light on our understanding of how information is integrated in the brain. PMID:26758843

MR imaging for diagnostic evaluation of encephalopathy in the newborn.

PubMed

Shroff, Manohar M; Soares-Fernandes, João P; Whyte, Hilary; Raybaud, Charles

2010-05-01

Magnetic resonance (MR) imaging is used with increasing frequency to evaluate the neonatal brain because it can provide important diagnostic and prognostic information that is needed for optimal treatment and appropriate counseling. Special care must be taken in preparing encephalopathic neonates for an MR study, transporting them from the intensive care unit, monitoring their vital signs, and optimizing MR sequences and protocols. Moreover, to accurately interpret the findings, specific knowledge is needed about the normal MR imaging appearances of the physiologic processes of myelination, cell migration, and sulcation, as well as patterns of injury, in the neonatal brain at various stages of gestational development. Hypoxic-ischemic injury, the most common cause of neonatal encephalopathy, has characteristic appearances that depend on the severity and duration of the insult as well as the stage of brain development. Diffusion-weighted MR imaging and MR spectroscopy depict abnormalities earlier than do conventional MR imaging sequences. However, diffusion-weighted imaging, if performed in the first 24 hours after the insult, might lead to underestimation of the extent of injury. When the MR findings are atypical, the differential diagnosis of neonatal encephalopathy also should include congenital and metabolic disorders and infectious diseases. Despite recent advances in the MR imaging-based characterization of these conditions, the clinical history must be borne in mind to achieve an accurate diagnosis.

Optimizing a Rodent Model of Parkinson's Disease for Exploring the Effects and Mechanisms of Deep Brain Stimulation

PubMed Central

Nowak, Karl; Mix, Eilhard; Gimsa, Jan; Strauss, Ulf; Sriperumbudur, Kiran Kumar; Benecke, Reiner; Gimsa, Ulrike

2011-01-01

Deep brain stimulation (DBS) has become a treatment for a growing number of neurological and psychiatric disorders, especially for therapy-refractory Parkinson's disease (PD). However, not all of the symptoms of PD are sufficiently improved in all patients, and side effects may occur. Further progress depends on a deeper insight into the mechanisms of action of DBS in the context of disturbed brain circuits. For this, optimized animal models have to be developed. We review not only charge transfer mechanisms at the electrode/tissue interface and strategies to increase the stimulation's energy-efficiency but also the electrochemical, electrophysiological, biochemical and functional effects of DBS. We introduce a hemi-Parkinsonian rat model for long-term experiments with chronically instrumented rats carrying a backpack stimulator and implanted platinum/iridium electrodes. This model is suitable for (1) elucidating the electrochemical processes at the electrode/tissue interface, (2) analyzing the molecular, cellular and behavioral stimulation effects, (3) testing new target regions for DBS, (4) screening for potential neuroprotective DBS effects, and (5) improving the efficacy and safety of the method. An outlook is given on further developments of experimental DBS, including the use of transgenic animals and the testing of closed-loop systems for the direct on-demand application of electric stimulation. PMID:21603182

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

PubMed

Aleksandrova, M A; Marey, M V

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

Mother-infant interactions and regional brain volumes in infancy: an MRI study.

PubMed

Sethna, Vaheshta; Pote, Inês; Wang, Siying; Gudbrandsen, Maria; Blasi, Anna; McCusker, Caroline; Daly, Eileen; Perry, Emily; Adams, Kerrie P H; Kuklisova-Murgasova, Maria; Busuulwa, Paula; Lloyd-Fox, Sarah; Murray, Lynne; Johnson, Mark H; Williams, Steven C R; Murphy, Declan G M; Craig, Michael C; McAlonan, Grainne M

2017-07-01

It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme environments in childhood. Less is understood about how normative variations in parent-child interactions are associated with the development of the infant brain in typical settings. To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother-infant interactions and regional brain volumes in a community sample of 3- to 6-month-old infants (N = 39). In addition, we examined whether this relationship differed in male and female infants. We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. These preliminary findings suggest that variations in mother-infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes.

Developing a de novo targeted knock-in method based on in utero electroporation into the mammalian brain.

PubMed

Tsunekawa, Yuji; Terhune, Raymond Kunikane; Fujita, Ikumi; Shitamukai, Atsunori; Suetsugu, Taeko; Matsuzaki, Fumio

2016-09-01

Genome-editing technology has revolutionized the field of biology. Here, we report a novel de novo gene-targeting method mediated by in utero electroporation into the developing mammalian brain. Electroporation of donor DNA with the CRISPR/Cas9 system vectors successfully leads to knock-in of the donor sequence, such as EGFP, to the target site via the homology-directed repair mechanism. We developed a targeting vector system optimized to prevent anomalous leaky expression of the donor gene from the plasmid, which otherwise often occurs depending on the donor sequence. The knock-in efficiency of the electroporated progenitors reached up to 40% in the early stage and 20% in the late stage of the developing mouse brain. Furthermore, we inserted different fluorescent markers into the target gene in each homologous chromosome, successfully distinguishing homozygous knock-in cells by color. We also applied this de novo gene targeting to the ferret model for the study of complex mammalian brains. Our results demonstrate that this technique is widely applicable for monitoring gene expression, visualizing protein localization, lineage analysis and gene knockout, all at the single-cell level, in developmental tissues. © 2016. Published by The Company of Biologists Ltd.

Optimizing the Usability of Brain-Computer Interfaces.

PubMed

Zhang, Yin; Chase, Steve M

2018-05-01

Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control. This question is complicated by the fact that learning, especially the long-term skill learning that accompanies weeks of practice, can allow subjects to improve performance over time. Typical approaches to this problem attempt to maximize the biomimetic properties of the device in order to limit the need for extensive training. However, it is unclear if this approach would ultimately be superior to performance that might be achieved with a nonbiomimetic device once the subject has engaged in extended practice and learned how to use it. Here we approach this problem using ideas from optimal control theory. Under the assumption that the brain acts as an optimal controller, we present a formal definition of the usability of a device and show that the optimal postlearning mapping can be written as the solution of a constrained optimization problem. We then derive the optimal mappings for particular cases common to most brain-computer interfaces. Our results suggest that the common approach of creating biomimetic interfaces may not be optimal when learning is taken into account. More broadly, our method provides a blueprint for optimal device design in general control-theoretic contexts.

Segregation of the Brain into Gray and White Matter: A Design Minimizing Conduction Delays

PubMed Central

Wen, Quan; Chklovskii, Dmitri B

2005-01-01

A ubiquitous feature of the vertebrate anatomy is the segregation of the brain into white and gray matter. Assuming that evolution maximized brain functionality, what is the reason for such segregation? To answer this question, we posit that brain functionality requires high interconnectivity and short conduction delays. Based on this assumption we searched for the optimal brain architecture by comparing different candidate designs. We found that the optimal design depends on the number of neurons, interneuronal connectivity, and axon diameter. In particular, the requirement to connect neurons with many fast axons drives the segregation of the brain into white and gray matter. These results provide a possible explanation for the structure of various regions of the vertebrate brain, such as the mammalian neocortex and neostriatum, the avian telencephalon, and the spinal cord. PMID:16389299

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain.

PubMed

Gilad, O; Horesh, L; Holder, D S

2007-07-01

For the novel application of recording of resistivity changes related to neuronal depolarization in the brain with electrical impedance tomography, optimal recording is with applied currents below 100 Hz, which might cause neural stimulation of skin or underlying brain. The purpose of this work was to develop a method for application of low frequency currents to the scalp, which delivered the maximum current without significant stimulation of skin or underlying brain. We propose a recessed electrode design which enabled current injection with an acceptable skin sensation to be increased from 100 muA using EEG electrodes, to 1 mA in 16 normal volunteers. The effect of current delivered to the brain was assessed with an anatomically realistic finite element model of the adult head. The modelled peak cerebral current density was 0.3 A/m(2), which was 5 to 25-fold less than the threshold for stimulation of the brain estimated from literature review.

Radiolabeled probes for imaging Alzheimer’s plaques

NASA Astrophysics Data System (ADS)

Kulkarni, P. V.; Arora, V.; Roney, A. C.; White, C.; Bennett, M.; Antich, P. P.; Bonte, F. J.

2005-12-01

Alzheimer's disease (AD) is a debilitating disease characterized by the presence of extra-cellular plaques and intra-cellular neurofibrillary tangles (NFTs) in the brain. The major protein component of these plaques is beta amyloid peptide (Aβ), a 40-42 amino acid peptide cleaved from amyloid precursor protein (APP) by β-secretase and a putative γ-secretase. We radioiodinated quinoline derivatives (clioquinol and oxine) and evaluated them as potential amyloid imaging agents based on their ability to cross the blood brain barrier (BBB) and on their selectivity to metal binding sites on amyloid plaques. The uptake of theses tracers in the brains of normal swiss-webster mice was rapid and so was the clearance. Selectivity was demonstrated by higher binding to AD brain homogenates compared to normal brain. Autoradiographic studies demonstrated the localization of the tracers in the plaque regions of the AD brain sections as well as in liver tissue with amyloidosis. Further optimization and evaluations would likely lead to development of these molecules as AD plaque imaging agents.

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

PubMed

Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

2017-08-21

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

PubMed

Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

2015-08-01

A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed to define brain network connectivity and neural network dynamics that vary at the individual patient level and vary over time.

Omega-3 fatty acids and brain resistance to ageing and stress: body of evidence and possible mechanisms.

PubMed

Denis, I; Potier, B; Vancassel, S; Heberden, C; Lavialle, M

2013-03-01

The increasing life expectancy in the populations of rich countries raises the pressing question of how the elderly can maintain their cognitive function. Cognitive decline is characterised by the loss of short-term memory due to a progressive impairment of the underlying brain cell processes. Age-related brain damage has many causes, some of which may be influenced by diet. An optimal diet may therefore be a practical way of delaying the onset of age-related cognitive decline. Nutritional investigations indicate that the ω-3 poyunsaturated fatty acid (PUFA) content of western diets is too low to provide the brain with an optimal supply of docosahexaenoic acid (DHA), the main ω-3 PUFA in cell membranes. Insufficient brain DHA has been associated with memory impairment, emotional disturbances and altered brain processes in rodents. Human studies suggest that an adequate dietary intake of ω-3 PUFA can slow the age-related cognitive decline and may also protect against the risk of senile dementia. However, despite the many studies in this domain, the beneficial impact of ω-3 PUFA on brain function has only recently been linked to specific mechanisms. This review examines the hypothesis that an optimal brain DHA status, conferred by an adequate ω-3 PUFA intake, limits age-related brain damage by optimizing endogenous brain repair mechanisms. Our analysis of the abundant literature indicates that an adequate amount of DHA in the brain may limit the impact of stress, an important age-aggravating factor, and influences the neuronal and astroglial functions that govern and protect synaptic transmission. This transmission, particularly glutamatergic neurotransmission in the hippocampus, underlies memory formation. The brain DHA status also influences neurogenesis, nested in the hippocampus, which helps maintain cognitive function throughout life. Although there are still gaps in our knowledge of the way ω-3 PUFA act, the mechanistic studies reviewed here indicate that ω-3 PUFA may be a promising tool for preventing age-related brain deterioration. Copyright © 2013 Elsevier B.V. All rights reserved.

Optimal Measurement Conditions for Spatiotemporal EEG/MEG Source Analysis.

ERIC Educational Resources Information Center

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

2002-01-01

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

Growth Cycles of Brain and Mind.

ERIC Educational Resources Information Center

Rose, Samuel P.; Fischer, Kurt W.

1998-01-01

Whereas prior conceptions treated cognitive development as a sequence of stages, current research points to recurring growth cycles between birth and age 30. Each recurrence produces a new capacity for thinking and learning grounded in an expanded, reorganized neural network. Cognitive spurts are evident only under optimal support conditions.…

Using the Wiener estimator to determine optimal imaging parameters in a synthetic-collimator SPECT system used for small animal imaging

NASA Astrophysics Data System (ADS)

Lin, Alexander; Johnson, Lindsay C.; Shokouhi, Sepideh; Peterson, Todd E.; Kupinski, Matthew A.

2015-03-01

In synthetic-collimator SPECT imaging, two detectors are placed at different distances behind a multi-pinhole aperture. This configuration allows for image detection at different magnifications and photon energies, resulting in higher overall sensitivity while maintaining high resolution. Image multiplexing the undesired overlapping between images due to photon origin uncertainty may occur in both detector planes and is often present in the second detector plane due to greater magnification. However, artifact-free image reconstruction is possible by combining data from both the front detector (little to no multiplexing) and the back detector (noticeable multiplexing). When the two detectors are used in tandem, spatial resolution is increased, allowing for a higher sensitivity-to-detector-area ratio. Due to variability in detector distances and pinhole spacings found in synthetic-collimator SPECT systems, a large parameter space must be examined to determine optimal imaging configurations. We chose to assess image quality based on the task of estimating activity in various regions of a mouse brain. Phantom objects were simulated using mouse brain data from the Magnetic Resonance Microimaging Neurological Atlas (MRM NeAt) and projected at different angles through models of a synthetic-collimator SPECT system, which was developed by collaborators at Vanderbilt University. Uptake in the different brain regions was modeled as being normally distributed about predetermined means and variances. We computed the performance of the Wiener estimator for the task of estimating activity in different regions of the mouse brain. Our results demonstrate the utility of the method for optimizing synthetic-collimator system design.

Learning-dependent plasticity with and without training in the human brain.

PubMed

Zhang, Jiaxiang; Kourtzi, Zoe

2010-07-27

Long-term experience through development and evolution and shorter-term training in adulthood have both been suggested to contribute to the optimization of visual functions that mediate our ability to interpret complex scenes. However, the brain plasticity mechanisms that mediate the detection of objects in cluttered scenes remain largely unknown. Here, we combine behavioral and functional MRI (fMRI) measurements to investigate the human-brain mechanisms that mediate our ability to learn statistical regularities and detect targets in clutter. We show two different routes to visual learning in clutter with discrete brain plasticity signatures. Specifically, opportunistic learning of regularities typical in natural contours (i.e., collinearity) can occur simply through frequent exposure, generalize across untrained stimulus features, and shape processing in occipitotemporal regions implicated in the representation of global forms. In contrast, learning to integrate discontinuities (i.e., elements orthogonal to contour paths) requires task-specific training (bootstrap-based learning), is stimulus-dependent, and enhances processing in intraparietal regions implicated in attention-gated learning. We propose that long-term experience with statistical regularities may facilitate opportunistic learning of collinear contours, whereas learning to integrate discontinuities entails bootstrap-based training for the detection of contours in clutter. These findings provide insights in understanding how long-term experience and short-term training interact to shape the optimization of visual recognition processes.

Normal variation in early parental sensitivity predicts child structural brain development.

PubMed

Kok, Rianne; Thijssen, Sandra; Bakermans-Kranenburg, Marian J; Jaddoe, Vincent W V; Verhulst, Frank C; White, Tonya; van IJzendoorn, Marinus H; Tiemeier, Henning

2015-10-01

Early caregiving can have an impact on brain structure and function in children. The influence of extreme caregiving experiences has been demonstrated, but studies on the influence of normal variation in parenting quality are scarce. Moreover, no studies to date have included the role of both maternal and paternal sensitivity in child brain maturation. This study examined the prospective relation between mothers' and fathers' sensitive caregiving in early childhood and brain structure later in childhood. Participants were enrolled in a population-based prenatal cohort. For 191 families, maternal and paternal sensitivity was repeatedly observed when the child was between 1 year and 4 years of age. Head circumference was assessed at 6 weeks, and brain structure was assessed using magnetic resonance imaging (MRI) measurements at 8 years of age. Higher levels of parental sensitivity in early childhood were associated with larger total brain volume (adjusted β = 0.15, p = .01) and gray matter volume (adjusted β = 0.16, p = .01) at 8 years, controlling for infant head size. Higher levels of maternal sensitivity in early childhood were associated with a larger gray matter volume (adjusted β = 0.13, p = .04) at 8 years, independent of infant head circumference. Associations with maternal versus paternal sensitivity were not significantly different. Normal variation in caregiving quality is related to markers of more optimal brain development in children. The results illustrate the important role of both mothers and fathers in child brain development. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Optimization of parameter values for complex pulse sequences by simulated annealing: application to 3D MP-RAGE imaging of the brain.

PubMed

Epstein, F H; Mugler, J P; Brookeman, J R

1994-02-01

A number of pulse sequence techniques, including magnetization-prepared gradient echo (MP-GRE), segmented GRE, and hybrid RARE, employ a relatively large number of variable pulse sequence parameters and acquire the image data during a transient signal evolution. These sequences have recently been proposed and/or used for clinical applications in the brain, spine, liver, and coronary arteries. Thus, the need for a method of deriving optimal pulse sequence parameter values for this class of sequences now exists. Due to the complexity of these sequences, conventional optimization approaches, such as applying differential calculus to signal difference equations, are inadequate. We have developed a general framework for adapting the simulated annealing algorithm to pulse sequence parameter value optimization, and applied this framework to the specific case of optimizing the white matter-gray matter signal difference for a T1-weighted variable flip angle 3D MP-RAGE sequence. Using our algorithm, the values of 35 sequence parameters, including the magnetization-preparation RF pulse flip angle and delay time, 32 flip angles in the variable flip angle gradient-echo acquisition sequence, and the magnetization recovery time, were derived. Optimized 3D MP-RAGE achieved up to a 130% increase in white matter-gray matter signal difference compared with optimized 3D RF-spoiled FLASH with the same total acquisition time. The simulated annealing approach was effective at deriving optimal parameter values for a specific 3D MP-RAGE imaging objective, and may be useful for other imaging objectives and sequences in this general class.

Intranasal agomelatine solid lipid nanoparticles to enhance brain delivery: formulation, optimization and in vivo pharmacokinetics

PubMed Central

Fatouh, Ahmed M; Elshafeey, Ahmed H; Abdelbary, Ahmed

2017-01-01

Purpose Agomelatine is a novel antidepressant drug suffering from an extensive first-pass metabolism leading to a diminished absolute bioavailability. The aim of the study is: first to enhance its absolute bioavailability, and second to increase its brain delivery. Methods To achieve these aims, the nasal route was adopted to exploit first its avoidance of the hepatic first-pass metabolism to increase the absolute bioavailability, and second the direct nose-to-brain pathway to enhance the brain drug delivery. Solid lipid nanoparticles were selected as a drug delivery system to enhance agomelatine permeability across the blood–brain barrier and therefore its brain delivery. Results The optimum solid lipid nanoparticles have a particle size of 167.70 nm ±0.42, zeta potential of −17.90 mV ±2.70, polydispersity index of 0.12±0.10, entrapment efficiency % of 91.25%±1.70%, the percentage released after 1 h of 35.40%±1.13% and the percentage released after 8 h of 80.87%±5.16%. The pharmacokinetic study of the optimized solid lipid nanoparticles revealed a significant increase in each of the plasma peak concentration, the AUC(0–360 min) and the absolute bioavailability compared to that of the oral suspension of Valdoxan® with the values of 759.00 ng/mL, 7,805.69 ng⋅min/mL and 44.44%, respectively. The optimized solid lipid nanoparticles gave a drug-targeting efficiency of 190.02, which revealed more successful brain targeting by the intranasal route compared with the intravenous route. The optimized solid lipid nanoparticles had a direct transport percentage of 47.37, which indicates a significant contribution of the direct nose-to-brain pathway in the brain drug delivery. Conclusion The intranasal administration of agomelatine solid lipid nanoparticles has effectively enhanced both the absolute bioavailability and the brain delivery of agomelatine. PMID:28684900

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

NASA Astrophysics Data System (ADS)

Abdulbaqi, Hayder Saad; Jafri, Mohd Zubir Mat; Omar, Ahmad Fairuz; Mustafa, Iskandar Shahrim Bin; Abood, Loay Kadom

2015-04-01

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

Long-Term Implanted cOFM Probe Causes Minimal Tissue Reaction in the Brain

PubMed Central

Hochmeister, Sonja; Asslaber, Martin; Kroath, Thomas; Pieber, Thomas R.; Sinner, Frank

2014-01-01

This study investigated the histological tissue reaction to long-term implanted cerebral open flow microperfusion (cOFM) probes in the frontal lobe of the rat brain. Most probe-based cerebral fluid sampling techniques are limited in application time due to the formation of a glial scar that hinders substance exchange between brain tissue and the probe. A glial scar not only functions as a diffusion barrier but also alters metabolism and signaling in extracellular brain fluid. cOFM is a recently developed probe-based technique to continuously sample extracellular brain fluid with an intact blood-brain barrier. After probe implantation, a 2 week healing period is needed for blood-brain barrier reestablishment. Therefore, cOFM probes need to stay in place and functional for at least 15 days after implantation to ensure functionality. Probe design and probe materials are optimized to evoke minimal tissue reaction even after a long implantation period. Qualitative and quantitative histological tissue analysis revealed no continuous glial scar formation around the cOFM probe 30 days after implantation and only a minor tissue reaction regardless of perfusion of the probe. PMID:24621608

Vitamin D and the omega-3 fatty acids control serotonin synthesis and action, part 2: relevance for ADHD, bipolar disorder, schizophrenia, and impulsive behavior.

PubMed

Patrick, Rhonda P; Ames, Bruce N

2015-06-01

Serotonin regulates a wide variety of brain functions and behaviors. Here, we synthesize previous findings that serotonin regulates executive function, sensory gating, and social behavior and that attention deficit hyperactivity disorder, bipolar disorder, schizophrenia, and impulsive behavior all share in common defects in these functions. It has remained unclear why supplementation with omega-3 fatty acids and vitamin D improve cognitive function and behavior in these brain disorders. Here, we propose mechanisms by which serotonin synthesis, release, and function in the brain are modulated by vitamin D and the 2 marine omega-3 fatty acids, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Brain serotonin is synthesized from tryptophan by tryptophan hydroxylase 2, which is transcriptionally activated by vitamin D hormone. Inadequate levels of vitamin D (∼70% of the population) and omega-3 fatty acids are common, suggesting that brain serotonin synthesis is not optimal. We propose mechanisms by which EPA increases serotonin release from presynaptic neurons by reducing E2 series prostaglandins and DHA influences serotonin receptor action by increasing cell membrane fluidity in postsynaptic neurons. We propose a model whereby insufficient levels of vitamin D, EPA, or DHA, in combination with genetic factors and at key periods during development, would lead to dysfunctional serotonin activation and function and may be one underlying mechanism that contributes to neuropsychiatric disorders and depression. This model suggests that optimizing vitamin D and marine omega-3 fatty acid intake may help prevent and modulate the severity of brain dysfunction. © FASEB.

A testbed for optimizing electrodes embedded in the skull or in artificial skull replacement pieces used after injury

PubMed Central

Jiang, JingLe; Marathe, Amar R.; Keene, Jennifer C.; Taylor, Dawn M.

2016-01-01

Background Custom-fitted skull replacement pieces are often used after a head injury or surgery to replace damaged bone. Chronic brain recordings are beneficial after injury/surgery for monitoring brain health and seizure development. Embedding electrodes directly in these artificial skull replacement pieces would be a novel, low-risk way to perform chronic brain monitoring in these patients. Similarly, embedding electrodes directly in healthy skull would be a viable minimally-invasive option for many other neuroscience and neurotechnology applications requiring chronic brain recordings. New Method We demonstrate a preclinical testbed that can be used for refining electrode designs embedded in artificial skull replacement pieces or for embedding directly into the skull itself. Options are explored to increase the surface area of the contacts without increasing recording contact diameter to maximize recording resolution. Results Embedding electrodes in real or artificial skull allows one to lower electrode impedance without increasing the recording contact diameter by making use of conductive channels that extend into the skull. The higher density of small contacts embedded in the artificial skull in this testbed enables one to optimize electrode spacing for use in real bone. Comparison with Existing Methods For brain monitoring applications, skull-embedded electrodes fill a gap between electroencephalograms recorded on the scalp surface and the more invasive epidural or subdural electrode sheets. Conclusions Embedding electrodes into the skull or in skull replacement pieces may provide a safe, convenient, minimally-invasive alternative for chronic brain monitoring. The manufacturing methods described here will facilitate further testing of skull-embedded electrodes in animal models. PMID:27979758

A testbed for optimizing electrodes embedded in the skull or in artificial skull replacement pieces used after injury.

PubMed

Jiang, JingLe; Marathe, Amar R; Keene, Jennifer C; Taylor, Dawn M

2017-02-01

Custom-fitted skull replacement pieces are often used after a head injury or surgery to replace damaged bone. Chronic brain recordings are beneficial after injury/surgery for monitoring brain health and seizure development. Embedding electrodes directly in these artificial skull replacement pieces would be a novel, low-risk way to perform chronic brain monitoring in these patients. Similarly, embedding electrodes directly in healthy skull would be a viable minimally-invasive option for many other neuroscience and neurotechnology applications requiring chronic brain recordings. We demonstrate a preclinical testbed that can be used for refining electrode designs embedded in artificial skull replacement pieces or for embedding directly into the skull itself. Options are explored to increase the surface area of the contacts without increasing recording contact diameter to maximize recording resolution. Embedding electrodes in real or artificial skull allows one to lower electrode impedance without increasing the recording contact diameter by making use of conductive channels that extend into the skull. The higher density of small contacts embedded in the artificial skull in this testbed enables one to optimize electrode spacing for use in real bone. For brain monitoring applications, skull-embedded electrodes fill a gap between electroencephalograms recorded on the scalp surface and the more invasive epidural or subdural electrode sheets. Embedding electrodes into the skull or in skull replacement pieces may provide a safe, convenient, minimally-invasive alternative for chronic brain monitoring. The manufacturing methods described here will facilitate further testing of skull-embedded electrodes in animal models. Published by Elsevier B.V.

WE-AB-209-09: Optimization of Rotational Arc Station Parameter Optimized Radiation Therapy

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

Dong, P; Xing, L; Ungun, B

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of improving VMAT in both plan quality and delivery efficiency. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based Proximal Operator Graph Solver (POGS) within seconds. Apertures with zero or low weight were thrown out. Tomore » avoid being trapped in a local minimum, a stochastic gradient descent method was employed which also greatly increased the convergence rate of the objective function. The above procedure repeated until the plan could not be improved any further. A weighting factor associated with the total plan MU also indirectly controlled the complexities of aperture shapes. The number of apertures for VMAT and SPORT was confined to 180. The SPORT allowed the coexistence of multiple apertures in a single SP. The optimization technique was assessed by using three clinical cases (prostate, H&N and brain). Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. Prostate case: the volume of the 50% prescription dose was decreased by 22% for the rectum. H&N case: SPORT improved the mean dose for the left and right parotids by 15% each. Brain case: the doses to the eyes, chiasm and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the H&N case. Conclusion: The superior dosimetric quality and delivery efficiency presented here indicates that SPORT is an intriguing alternative treatment modality.« less

Brain Imaging and Human Nutrition: Which Measures to Use in Intervention Studies?12

PubMed Central

Sizonenko, Stéphane V.; Babiloni, Claudio; Sijben, John W.; Walhovd, Kristine B.

2013-01-01

Throughout the life span, the brain is a metabolically highly active organ that uses a large proportion of total nutrient and energy intake. Furthermore, the development and repair of neural tissue depend on the proper intake of essential structural nutrients, minerals, and vitamins. Therefore, what we eat, or refrain from eating, may have an important impact on our cognitive ability and mental performance. Two of the key areas in which diet is thought to play an important role are in optimizing neurodevelopment in children and in preventing neurodegeneration and cognitive decline during aging. From early development to aging, brain imaging can detect structural, functional, and metabolic changes in humans and modifications due to altered nutrition or to additional nutritional supplementation. Inclusion of imaging measures in clinical studies can increase understanding with regard to the modification of brain structure, metabolism, and functional endpoints and may provide early sensitive measures of long-term effects. In this symposium, the utility of existing brain imaging technologies to assess the effects of nutritional intervention in humans is described. Examples of current research showing the utility of these markers are reviewed. PMID:24038255

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.

PubMed

Dmochowski, Jacek P; Koessler, Laurent; Norcia, Anthony M; Bikson, Marom; Parra, Lucas C

2017-08-15

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4-7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation

PubMed Central

Dmochowski, Jacek P.; Koessler, Laurent; Norcia, Anthony M.; Bikson, Marom; Parra, Lucas C.

2018-01-01

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4–7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation. PMID:28578130

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

PubMed

Blessy, S A Praylin Selva; Sulochana, C Helen

2015-01-01

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

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

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

Dong, P; Xing, L; Ma, L

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs tomore » pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment efficiency.« less

The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development.

PubMed

Howell, Brittany R; Styner, Martin A; Gao, Wei; Yap, Pew-Thian; Wang, Li; Baluyot, Kristine; Yacoub, Essa; Chen, Geng; Potts, Taylor; Salzwedel, Andrew; Li, Gang; Gilmore, John H; Piven, Joseph; Smith, J Keith; Shen, Dinggang; Ugurbil, Kamil; Zhu, Hongtu; Lin, Weili; Elison, Jed T

2018-03-22

The human brain undergoes extensive and dynamic growth during the first years of life. The UNC/UMN Baby Connectome Project (BCP), one of the Lifespan Connectome Projects funded by NIH, is an ongoing study jointly conducted by investigators at the University of North Carolina at Chapel Hill and the University of Minnesota. The primary objective of the BCP is to characterize brain and behavioral development in typically developing infants across the first 5 years of life. The ultimate goals are to chart emerging patterns of structural and functional connectivity during this period, map brain-behavior associations, and establish a foundation from which to further explore trajectories of health and disease. To accomplish these goals, we are combining state of the art MRI acquisition and analysis techniques, including high-resolution structural MRI (T1-and T2-weighted images), diffusion imaging (dMRI), and resting state functional connectivity MRI (rfMRI). While the overall design of the BCP largely is built on the protocol developed by the Lifespan Human Connectome Project (HCP), given the unique age range of the BCP cohort, additional optimization of imaging parameters and consideration of an age appropriate battery of behavioral assessments were needed. Here we provide the overall study protocol, including approaches for subject recruitment, strategies for imaging typically developing children 0-5 years of age without sedation, imaging protocol and optimization, a description of the battery of behavioral assessments, and QA/QC procedures. Combining HCP inspired neuroimaging data with well-established behavioral assessments during this time period will yield an invaluable resource for the scientific community. Copyright © 2018 Elsevier Inc. All rights reserved.

Cerebrovascular Pressure Reactivity in Children With Traumatic Brain Injury.

PubMed

Lewis, Philip M; Czosnyka, Marek; Carter, Bradley G; Rosenfeld, Jeffrey V; Paul, Eldho; Singhal, Nitesh; Butt, Warwick

2015-10-01

Traumatic brain injury is a significant cause of morbidity and mortality in children. Cerebral autoregulation disturbance after traumatic brain injury is associated with worse outcome. Pressure reactivity is a fundamental component of cerebral autoregulation that can be estimated using the pressure-reactivity index, a correlation between slow arterial blood pressure, and intracranial pressure fluctuations. Pressure-reactivity index has shown prognostic value in adult traumatic brain injury, with one study confirming this in children. Pressure-reactivity index can identify a cerebral perfusion pressure range within which pressure reactivity is optimal. An increasing difference between optimal cerebral perfusion pressure and cerebral perfusion pressure is associated with worse outcome in adult traumatic brain injury; however, this has not been investigated in children. Our objective was to study pressure-reactivity index and optimal cerebral perfusion pressure in pediatric traumatic brain injury, including associations with outcome, age, and cerebral perfusion pressure. Prospective observational study. ICU, Royal Children's Hospital, Melbourne, Australia. Patients with traumatic brain injury who are 6 months to 16 years old, are admitted to the ICU, and require arterial blood pressure and intracranial pressure monitoring. None. Arterial blood pressure, intracranial pressure, and end-tidal CO2 were recorded electronically until ICU discharge or monitoring cessation. Pressure-reactivity index and optimal cerebral perfusion pressure were computed according to previously published methods. Clinical data were collected from electronic medical records. Outcome was assessed 6 months post discharge using the modified Glasgow Outcome Score. Thirty-six patients were monitored, with 30 available for follow-up. Pressure-reactivity index correlated with modified Glasgow Outcome Score (Spearman ρ = 0.42; p = 0.023) and was higher in patients with unfavorable outcome (0.23 vs -0.09; p = 0.0009). A plot of pressure-reactivity index averaged within 5 mm Hg cerebral perfusion pressure bins showed a U-shape, reaffirming the concept of cerebral perfusion pressure optimization in children. Optimal cerebral perfusion pressure increased with age (ρ = 0.40; p = 0.02). Both the duration and magnitude of negative deviations in the difference between cerebral perfusion pressure and optimal cerebral perfusion pressure were associated with unfavorable outcome. In pediatric patients with traumatic brain injury, pressure-reactivity index has prognostic value and can identify cerebral perfusion pressure targets that may differ from treatment protocols. Our results suggest but do not confirm that cerebral perfusion pressure targeting using pressure-reactivity index as a guide may positively impact on outcome. This question should be addressed by a prospective clinical study.

Optimization of flow-sensitive alternating inversion recovery (FAIR) for perfusion functional MRI of rodent brain.

PubMed

Nasrallah, Fatima A; Lee, Eugene L Q; Chuang, Kai-Hsiang

2012-11-01

Arterial spin labeling (ASL) MRI provides a noninvasive method to image perfusion, and has been applied to map neural activation in the brain. Although pulsed labeling methods have been widely used in humans, continuous ASL with a dedicated neck labeling coil is still the preferred method in rodent brain functional MRI (fMRI) to maximize the sensitivity and allow multislice acquisition. However, the additional hardware is not readily available and hence its application is limited. In this study, flow-sensitive alternating inversion recovery (FAIR) pulsed ASL was optimized for fMRI of rat brain. A practical challenge of FAIR is the suboptimal global inversion by the transmit coil of limited dimensions, which results in low effective labeling. By using a large volume transmit coil and proper positioning to optimize the body coverage, the perfusion signal was increased by 38.3% compared with positioning the brain at the isocenter. An additional 53.3% gain in signal was achieved using optimized repetition and inversion times compared with a long TR. Under electrical stimulation to the forepaws, a perfusion activation signal change of 63.7 ± 6.3% can be reliably detected in the primary somatosensory cortices using single slice or multislice echo planar imaging at 9.4 T. This demonstrates the potential of using pulsed ASL for multislice perfusion fMRI in functional and pharmacological applications in rat brain. Copyright © 2012 John Wiley & Sons, Ltd.

Autism BrainNet: A network of postmortem brain banks established to facilitate autism research.

PubMed

Amaral, David G; Anderson, Matthew P; Ansorge, Olaf; Chance, Steven; Hare, Carolyn; Hof, Patrick R; Miller, Melissa; Nagakura, Ikue; Pickett, Jane; Schumann, Cynthia; Tamminga, Carol

2018-01-01

Autism spectrum disorder (ASD or autism) is a neurodevelopmental condition that affects over 1% of the population worldwide. Developing effective preventions and treatments for autism will depend on understanding the genetic perturbations and underlying neuropathology of the disorder. While evidence from magnetic resonance imaging and other noninvasive techniques points to altered development and organization of the autistic brain, these tools lack the resolution for identifying the cellular and molecular underpinnings of the disorder. Postmortem studies of high-quality human brain tissue currently represent the only viable option to pursuing these types of studies. However, the availability of high-quality ASD brain tissue has been extremely limited. Here we describe the establishment of a privately funded tissue bank, Autism BrainNet, a network of brain collection sites that work in a coordinated fashion to develop an adequate library of human postmortem brain tissues. Autism BrainNet was initiated as a collaboration between the Simons Foundation and Autism Speaks, and is currently funded by the Simons Foundation Autism Research Initiative. Autism BrainNet has collection sites (nodes) in California, Texas, New York, and Massachusetts; an affiliated, international node is located in Oxford, England. All donations to this network become part of a consolidated pool of tissue that is distributed to qualified investigators worldwide to carry out autism research. An essential component of this program is a widespread outreach program that highlights the need for postmortem brain donations to families affected by autism, led by the Autism Science Foundation. Challenges include an outreach campaign that deals with a disorder beginning in early childhood, collecting an adequate number of donations to deal with the high level of biologic heterogeneity of autism, and preparing this limited resource for optimal distribution to the greatest number of investigators. Copyright © 2018 Elsevier B.V. All rights reserved.

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

Docosahexaenoic acid and human brain development: evidence that a dietary supply is needed for optimal development.

PubMed

Brenna, J Thomas; Carlson, Susan E

2014-12-01

Humans evolved a uniquely large brain among terrestrial mammals. Brain and nervous tissue is rich in the omega-3 polyunsaturated fatty acid (PUFA) docosahexaenoic acid (DHA). Docosahexaenoic acid is required for lower and high order functions in humans because of understood and emerging molecular mechanisms. Among brain components that depend on dietary components, DHA is limiting because its synthesis from terrestrial plant food precursors is low but its utilization when consumed in diet is very efficient. Negligible DHA is found in terrestrial plants, but in contrast, DHA is plentiful at the shoreline where it is made by single-celled organisms and plants, and in the seas supports development of very large marine mammal brains. Modern human brains accumulate DHA up to age 18, most aggressively from about half-way through gestation to about two years of age. Studies in modern humans and non-human primates show that modern infants consuming infant formulas that include only DHA precursors have lower DHA levels than for those with a source of preformed DHA. Functional measures show that infants consuming preformed DHA have improved visual and cognitive function. Dietary preformed DHA in the breast milk of modern mothers supports many-fold greater breast milk DHA than is found in the breast milk of vegans, a phenomenon linked to consumption of shore-based foods. Most current evidence suggests that the DHA-rich human brain required an ample and sustained source of dietary DHA to reach its full potential. Copyright © 2014 Elsevier Ltd. All rights reserved.

Very high-energy electron (VHEE) beams in radiation therapy; Treatment plan comparison between VHEE, VMAT, and PPBS.

PubMed

Schüler, Emil; Eriksson, Kjell; Hynning, Elin; Hancock, Steven L; Hiniker, Susan M; Bazalova-Carter, Magdalena; Wong, Tony; Le, Quynh-Thu; Loo, Billy W; Maxim, Peter G

2017-06-01

The aim of this study was to evaluate the performance of very high-energy electron beams (VHEE) in comparison to clinically derived treatment plans generated with volumetric modulated arc therapy (VMAT) and proton pencil beam scanning (PPBS) technology. We developed a custom optimization script that could be applied automatically across modalities to eliminate operator bias during IMRT optimization. Four clinical cases were selected (prostate cancer, lung cancer, pediatric brain tumor, and head and neck cancer (HNC)). The VHEE beams were calculated in the EGSnrc/DOSXYZnrc Monte Carlo code for 100 and 200 MeV beams. Treatment plans with VHEE, VMAT, and PPBS were optimized in a research version of RayStation using an in-house developed script to minimize operator bias between the different techniques. The in-house developed script generated similar or superior plans to the clinically used plans. In the comparisons between the modalities, the integral dose was lowest for the PPBS-generated plans in all cases. For the prostate case, the 200 MeV VHEE plan showed reduced integral dose and reduced organ at risk (OAR) dose compared to the VMAT plan. For all other cases, both the 100 and the 200 MeV VHEE plans were superior to the VMAT plans, and the VHEE plans showed better conformity and lower spinal cord dose in the pediatric brain case and lower brain stem dose in the HNC case when compared to the PPBS plan. The automated optimization developed in this study generated similar or superior plans as compared to the clinically used plan and represents an unbiased approach to compare treatment plans generated for different modalities. In the present study, we also show that VHEE plans are similar or superior to VMAT plans with reduced mean OAR dose and increased target conformity for a variety of clinical cases, and VHEE plans can even achieve reductions in OAR doses compared to PPBS plans for shallow targets. With increased VHEE energy, better conformity and even higher reductions in mean OAR doses are achieved. On the whole, VHEE was intermediate between photon VMAT and PPBS for OAR sparing. © 2017 American Association of Physicists in Medicine.

Whole brain radiotherapy for brain metastasis

PubMed Central

McTyre, Emory; Scott, Jacob; Chinnaiyan, Prakash

2013-01-01

Whole brain radiotherapy (WBRT) is a mainstay of treatment in patients with both identifiable brain metastases and prophylaxis for microscopic disease. The use of WBRT has decreased somewhat in recent years due to both advances in radiation technology, allowing for a more localized delivery of radiation, and growing concerns regarding the late toxicity profile associated with WBRT. This has prompted the development of several recent and ongoing prospective studies designed to provide Level I evidence to guide optimal treatment approaches for patients with intracranial metastases. In addition to defining the role of WBRT in patients with brain metastases, identifying methods to improve WBRT is an active area of investigation, and can be classified into two general categories: Those designed to decrease the morbidity of WBRT, primarily by reducing late toxicity, and those designed to improve the efficacy of WBRT. Both of these areas of research show diversity and promise, and it seems feasible that in the near future, the efficacy/toxicity ratio may be improved, allowing for a more diverse clinical application of WBRT. PMID:23717795

Renewal Processes in the Critical Brain

NASA Astrophysics Data System (ADS)

Allegrini, Paolo; Paradisi, Paolo; Menicucci, Danilo; Gemignani, Angelo

We describe herein a multidisciplinary research, as it developes and applies concepts of the theory of complexity, in turn stemming from recent advancements of statistical physics, onto cognitive neuroscience. We discuss (define) complexity, and how the human brain is a paradigm of it. We discuss how the hypothesis of brain activity dynamically behaving as a critical system is taking momentum in literature, then we focus on a feature of critical systems (hence of the brain), which is the intermittent passage between metastable states, marked by events, locally resetting the memory, but giving rise to correlation functions with infinite correlation times. The events, extracted from multi-channel ElectroEncephaloGrams, mark (are interpreted as) a birth/death process of cooperation, namely of system elements being recruited into collective states. Finally we discuss a recently discovered form of control (in the form of a new Linear Response Theory), that allows an optimized information transmission between complex systems, named Complexity Matching.

Mapping Cortical Laminar Structure in the 3D BigBrain.

PubMed

Wagstyl, Konrad; Lepage, Claude; Bludau, Sebastian; Zilles, Karl; Fletcher, Paul C; Amunts, Katrin; Evans, Alan C

2018-07-01

Histological sections offer high spatial resolution to examine laminar architecture of the human cerebral cortex; however, they are restricted by being 2D, hence only regions with sufficiently optimal cutting planes can be analyzed. Conversely, noninvasive neuroimaging approaches are whole brain but have relatively low resolution. Consequently, correct 3D cross-cortical patterns of laminar architecture have never been mapped in histological sections. We developed an automated technique to identify and analyze laminar structure within the high-resolution 3D histological BigBrain. We extracted white matter and pial surfaces, from which we derived histologically verified surfaces at the layer I/II boundary and within layer IV. Layer IV depth was strongly predicted by cortical curvature but varied between areas. This fully automated 3D laminar analysis is an important requirement for bridging high-resolution 2D cytoarchitecture and in vivo 3D neuroimaging. It lays the foundation for in-depth, whole-brain analyses of cortical layering.

Quantitative mouse brain phenotyping based on single and multispectral MR protocols

PubMed Central

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

SU-E-T-587: Optimal Volumetric Modulated Arc Radiotherapy Treatment Planning Technique for Multiple Brain Metastases with Increasing Number of Arcs

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

Keeling, V; Hossain, S; Hildebrand, K

Purpose: To show improvements in dose conformity and normal brain tissue sparing using an optimal planning technique (OPT) against clinically acceptable planning technique (CAP) in the treatment of multiple brain metastases. Methods: A standardized international benchmark case with12 intracranial tumors was planned using two different VMAT optimization methods. Plans were split into four groups with 3, 6, 9, and 12 targets each planned with 3, 5, and 7 arcs using Eclipse TPS. The beam geometries were 1 full coplanar and half non-coplanar arcs. A prescription dose of 20Gy was used for all targets. The following optimization criteria was used (OPTmore » vs. CAP): (No upper limit vs.108% upper limit for target volume), (priority 140–150 vs. 75–85 for normal-brain-tissue), and (selection of automatic sparing Normal-Tissue-Objective (NTO) vs. Manual NTO). Both had priority 50 to critical structures such as brainstem and optic-chiasm, and both had an NTO priority 150. Normal-brain-tissue doses along with Paddick Conformity Index (PCI) were evaluated. Results: In all cases PCI was higher for OPT plans. The average PCI (OPT,CAP) for all targets was (0.81,0.64), (0.81,0.63), (0.79,0.57), and (0.72,0.55) for 3, 6, 9, and 12 target plans respectively. The percent decrease in normal brain tissue volume (OPT/CAP*100) achieved by OPT plans was (reported as follows: V4, V8, V12, V16, V20) (184, 343, 350, 294, 371%), (192, 417, 380, 299, 360%), and (235, 390, 299, 281, 502%) for the 3, 5, 7 arc 12 target plans, respectively. The maximum brainstem dose decreased for the OPT plan by 4.93, 4.89, and 5.30 Gy for 3, 5, 7 arc 12 target plans, respectively. Conclusion: Substantial increases in PCI, critical structure sparing, and decreases in normal brain tissue dose were achieved by eliminating upper limits from optimization, using automatic sparing of normal tissue function with high priority, and a high priority to normal brain tissue.« less

Metric Optimization for Surface Analysis in the Laplace-Beltrami Embedding Space

PubMed Central

Lai, Rongjie; Wang, Danny J.J.; Pelletier, Daniel; Mohr, David; Sicotte, Nancy; Toga, Arthur W.

2014-01-01

In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects. PMID:24686245

Brain Dominance & Self-Actualization.

ERIC Educational Resources Information Center

Bernhoft, Franklin O.

Numerous areas associated with brain dominance have been researched since Bogen and Sperry's work with split-brain patients in the 1960s, but only slight attention has been given to the connection between brain dominance and personality. No study appears in the literature seeking to understand optimal mental health as defined by Maslow's…

Protein functionalized tramadol-loaded PLGA nanoparticles: preparation, optimization, stability and pharmacodynamic studies.

PubMed

Lalani, Jigar; Rathi, Mohan; Lalan, Manisha; Misra, Ambikanandan

2013-06-01

Poly (d,l-lactide-co-glycolide acid) (PLGA) Nanoparticles (NPs) with sustained drug release and enhanced circulation time presents widely explored non-invasive approach for drug delivery to brain. However, blood-brain barrier (BBB) limits the drug delivery to brain. This can be overcome by anchoring endogenous ligand like Transferrin (Tf) and Lactoferrin (Lf) on the surface of NPs, allowing efficient brain delivery via receptor-mediated endocytosis. The aim of the present investigation was preparation, optimization, characterization and comparative evaluation of targeting efficiency of Tf- vs. Lf-conjugated NPs. Tramadol-loaded PLGA NPs were prepared by nanoprecipitation techniques and optimized using 3(3) factorial design. The effect of polymer concentration, stabilizer concentration and organic:aqueous phase ratio were evaluated on particle size (PS) and entrapment efficiency (EE). The formulation was optimized based on desirability for lower PS (<150 nm) and higher EE (>70%). Optimized PLGA NPs were conjugated with Tf and Lf, characterized and evaluated for stability study. Pharmacodynamic study was performed in rat after intravenous administration. The optimized formulation had 100 mg of PLGA, 1% polyvinyl alcohol (PVA) and 1:2 acetone:water ratio. The Lf and Tf conjugation to PLGA NPs was estimated to 186 Tf and 185 Lf molecules per NPs. Lyophilization was optimized at 1:2 ratio of NPs:trehalose. The NPs were found stable for 6 months at refrigerated condition. Pharmacodynamic study demonstrated enhanced efficacy of ligand-conjugated NPs against unconjugated NPs. Conjugated NPs demonstrated significantly higher pharmacological effect over a period of 24 h. Furthermore Lf functionalized NPs exhibited better antinociceptive effect as compared to Tf functionalized NPs.

Waking up too early - the consequences of preterm birth on sleep development.

PubMed

Bennet, Laura; Walker, David W; Horne, Rosemary S C

2018-04-24

Good quality sleep of sufficient duration is vital for optimal physiological function and our health. Sleep deprivation is associated with impaired neurocognitive function and emotional control, and increases the risk for cardiometabolic diseases, obesity and cancer. Sleep develops during fetal life with the emergence of a recognisable pattern of sleep states in the preterm fetus associated with the development, maturation, and connectivity within neural networks in the brain. Despite the physiological importance of sleep, surprisingly little is known about how sleep develops in individuals born preterm. Globally, an estimated 15 million babies are born preterm (<37 weeks gestation), and these babies are at significant risk of neural injury and impaired brain development. This review discusses how sleep develops during fetal and neonatal life, how preterm birth impacts on sleep development to adulthood, and the factors which may contribute to impaired brain and sleep development, leading to altered neurocognitive, behavioural and motor capabilities in the infant and child. Going forward, the challenge is to identify specific risk factors for impaired sleep development in preterm babies to allow for the design of interventions that will improve the quality and quantity of sleep throughout life. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Recurring ventriculitis due to Citrobacter diversus: clinical and bacteriologic analysis.

PubMed

Eppes, S C; Woods, C R; Mayer, A S; Klein, J D

1993-09-01

Neonatal meningitis due to Citrobacter diversus is usually accompanied by the development of brain abscesses and tends to have high rates of morbidity and mortality. We report a case of a newborn with C. diversus meningitis and brain abscesses who relapsed after initial antibiotic therapy and from whom C. diversus was recovered from cerebrospinal fluid 4 years later during a neurosurgical procedure. Genetic differences in the early and late isolates were discovered, and explanations for this phenomenon are suggested. Possible mechanisms for prolonged persistence in the central nervous system are explored. This unusual case and the analysis of the organisms illustrate the unique features of C. diversus as a pathogen and underscore the need for developing optimal therapeutic strategies.

Image guided constitutive modeling of the silicone brain phantom

NASA Astrophysics Data System (ADS)

Puzrin, Alexander; Skrinjar, Oskar; Ozan, Cem; Kim, Sihyun; Mukundan, Srinivasan

2005-04-01

The goal of this work is to develop reliable constitutive models of the mechanical behavior of the in-vivo human brain tissue for applications in neurosurgery. We propose to define the mechanical properties of the brain tissue in-vivo, by taking the global MR or CT images of a brain response to ventriculostomy - the relief of the elevated intracranial pressure. 3D image analysis translates these images into displacement fields, which by using inverse analysis allow for the constitutive models of the brain tissue to be developed. We term this approach Image Guided Constitutive Modeling (IGCM). The presented paper demonstrates performance of the IGCM in the controlled environment: on the silicone brain phantoms closely simulating the in-vivo brain geometry, mechanical properties and boundary conditions. The phantom of the left hemisphere of human brain was cast using silicon gel. An inflatable rubber membrane was placed inside the phantom to model the lateral ventricle. The experiments were carried out in a specially designed setup in a CT scanner with submillimeter isotropic voxels. The non-communicative hydrocephalus and ventriculostomy were simulated by consequently inflating and deflating the internal rubber membrane. The obtained images were analyzed to derive displacement fields, meshed, and incorporated into ABAQUS. The subsequent Inverse Finite Element Analysis (based on Levenberg-Marquardt algorithm) allowed for optimization of the parameters of the Mooney-Rivlin non-linear elastic model for the phantom material. The calculated mechanical properties were consistent with those obtained from the element tests, providing justification for the future application of the IGCM to in-vivo brain tissue.

Regional Delivery of Chimeric Antigen Receptor-Engineered T Cells Effectively Targets HER2+ Breast Cancer Metastasis to the Brain.

PubMed

Priceman, Saul J; Tilakawardane, Dileshni; Jeang, Brook; Aguilar, Brenda; Murad, John P; Park, Anthony K; Chang, Wen-Chung; Ostberg, Julie R; Neman, Josh; Jandial, Rahul; Portnow, Jana; Forman, Stephen J; Brown, Christine E

2018-01-01

Purpose: Metastasis to the brain from breast cancer remains a significant clinical challenge, and may be targeted with CAR-based immunotherapy. CAR design optimization for solid tumors is crucial due to the absence of truly restricted antigen expression and potential safety concerns with "on-target off-tumor" activity. Here, we have optimized HER2-CAR T cells for the treatment of breast to brain metastases, and determined optimal second-generation CAR design and route of administration for xenograft mouse models of breast metastatic brain tumors, including multifocal and leptomeningeal disease. Experimental Design: HER2-CAR constructs containing either CD28 or 4-1BB intracellular costimulatory signaling domains were compared for functional activity in vitro by measuring cytokine production, T-cell proliferation, and tumor killing capacity. We also evaluated HER2-CAR T cells delivered by intravenous, local intratumoral, or regional intraventricular routes of administration using in vivo human xenograft models of breast cancer that have metastasized to the brain. Results: Here, we have shown that HER2-CARs containing the 4-1BB costimulatory domain confer improved tumor targeting with reduced T-cell exhaustion phenotype and enhanced proliferative capacity compared with HER2-CARs containing the CD28 costimulatory domain. Local intracranial delivery of HER2-CARs showed potent in vivo antitumor activity in orthotopic xenograft models. Importantly, we demonstrated robust antitumor efficacy following regional intraventricular delivery of HER2-CAR T cells for the treatment of multifocal brain metastases and leptomeningeal disease. Conclusions: Our study shows the importance of CAR design in defining an optimized CAR T cell, and highlights intraventricular delivery of HER2-CAR T cells for treating multifocal brain metastases. Clin Cancer Res; 24(1); 95-105. ©2017 AACR . ©2017 American Association for Cancer Research.

Treatment Planning for Accelerator-Based Boron Neutron Capture Therapy

NASA Astrophysics Data System (ADS)

Herrera, María S.; González, Sara J.; Minsky, Daniel M.; Kreiner, Andrés J.

2010-08-01

Glioblastoma multiforme and metastatic melanoma are frequent brain tumors in adults and presently still incurable diseases. Boron Neutron Capture Therapy (BNCT) is a promising alternative for this kind of pathologies. Accelerators have been proposed for BNCT as a way to circumvent the problem of siting reactors in hospitals and for their relative simplicity and lower cost among other advantages. Considerable effort is going into the development of accelerator-based BNCT neutron sources in Argentina. Epithermal neutron beams will be produced through appropriate proton-induced nuclear reactions and optimized beam shaping assemblies. Using these sources, computational dose distributions were evaluated in a real patient with diagnosed glioblastoma treated with BNCT. The simulated irradiation was delivered in order to optimize dose to the tumors within the normal tissue constraints. Using Monte Carlo radiation transport calculations, dose distributions were generated for brain, skin and tumor. Also, the dosimetry was studied by computing cumulative dose-volume histograms for volumes of interest. The results suggest acceptable skin average dose and a significant dose delivered to tumor with low average whole brain dose for irradiation times less than 60 minutes, indicating a good performance of an accelerator-based BNCT treatment.

Treatment Planning for Accelerator-Based Boron Neutron Capture Therapy

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

Herrera, Maria S.; Gonzalez, Sara J.; Minsky, Daniel M.

2010-08-04

Glioblastoma multiforme and metastatic melanoma are frequent brain tumors in adults and presently still incurable diseases. Boron Neutron Capture Therapy (BNCT) is a promising alternative for this kind of pathologies. Accelerators have been proposed for BNCT as a way to circumvent the problem of siting reactors in hospitals and for their relative simplicity and lower cost among other advantages. Considerable effort is going into the development of accelerator-based BNCT neutron sources in Argentina. Epithermal neutron beams will be produced through appropriate proton-induced nuclear reactions and optimized beam shaping assemblies. Using these sources, computational dose distributions were evaluated in a realmore » patient with diagnosed glioblastoma treated with BNCT. The simulated irradiation was delivered in order to optimize dose to the tumors within the normal tissue constraints. Using Monte Carlo radiation transport calculations, dose distributions were generated for brain, skin and tumor. Also, the dosimetry was studied by computing cumulative dose-volume histograms for volumes of interest. The results suggest acceptable skin average dose and a significant dose delivered to tumor with low average whole brain dose for irradiation times less than 60 minutes, indicating a good performance of an accelerator-based BNCT treatment.« less

A New Predictive Tool for Optimization of the Treatment of Brain Metastases from Colorectal Cancer After Stereotactic Radiosurgery.

PubMed

Rades, Dirk; Dahlke, Markus; Gebauer, Niklas; Bartscht, Tobias; Hornung, Dagmar; Trang, Ngo Thuy; Phuong, Pham Cam; Khoa, Mai Trong; Gliemroth, Jan

2015-10-01

To develop a predictive tool for survival after stereotactic radiosurgery of brain metastases from colorectal cancer. Out of nine factors analyzed for survival, those showing significance (p<0.05) or a trend (p≤0.06) were included. For each factor, 0 (worse survival) or 1 (better survival) point was assigned. Total scores represented the sum of the factor scores. Performance status (p=0.010) and interval from diagnosis of colorectal cancer until radiosurgery (p=0.026) achieved significance, extracranial metastases showed a trend (p=0.06). These factors were included in the tool. Total scores were 0-3 points. Six-month survival rates were 17% for patients with 0, 25% for those with 1, 67% for those with 2 and 100% for those with 3 points; 12-month rates were 0%, 0%, 33% and 67%, respectively. Two groups were created: 0-1 and 2-3 points. Six- and 12-month survival rates were 20% vs. 78% and 0% vs. 44% (p=0.002), respectively. This tool helps optimize the treatment of patients after stereotactic radiosurgery for brain metastases from colorectal cancer. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

A Novel Multilayer Correlation Maximization Model for Improving CCA-Based Frequency Recognition in SSVEP Brain-Computer Interface.

PubMed

Jiao, Yong; Zhang, Yu; Wang, Yu; Wang, Bei; Jin, Jing; Wang, Xingyu

2018-05-01

Multiset canonical correlation analysis (MsetCCA) has been successfully applied to optimize the reference signals by extracting common features from multiple sets of electroencephalogram (EEG) for steady-state visual evoked potential (SSVEP) recognition in brain-computer interface application. To avoid extracting the possible noise components as common features, this study proposes a sophisticated extension of MsetCCA, called multilayer correlation maximization (MCM) model for further improving SSVEP recognition accuracy. MCM combines advantages of both CCA and MsetCCA by carrying out three layers of correlation maximization processes. The first layer is to extract the stimulus frequency-related information in using CCA between EEG samples and sine-cosine reference signals. The second layer is to learn reference signals by extracting the common features with MsetCCA. The third layer is to re-optimize the reference signals set in using CCA with sine-cosine reference signals again. Experimental study is implemented to validate effectiveness of the proposed MCM model in comparison with the standard CCA and MsetCCA algorithms. Superior performance of MCM demonstrates its promising potential for the development of an improved SSVEP-based brain-computer interface.

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

PubMed Central

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

2013-01-01

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

An accurate segmentation method for volumetry of brain tumor in 3D MRI

NASA Astrophysics Data System (ADS)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

Intranasal delivery of quercetin-loaded mucoadhesive nanoemulsion for treatment of cerebral ischaemia.

PubMed

Ahmad, Niyaz; Ahmad, Rizwan; Naqvi, Atta Abbas; Alam, Md Aftab; Ashafaq, Mohammad; Abdur Rub, Rehan; Ahmad, Farhan Jalees

2018-06-01

Quercetin (QUR), as an antioxidant flavonoid, exhibits potential role in the amelioration of cerebral ischaemia; however, poor solubility as well as oral absorption results low serum and tissue levels for this drug. To enhance bioavailability, this study aims to prepare QUR nanoemulsions and administer via non-invasive nasal route in order to evaluate the drug targeting in brain. Quercetin mucoadhesive nanoemulsion (QMNE) was prepared (ionic gelation method) and optimized using various parameters, that is, particle size, entrapment efficiency, zeta potential and ex vivo permeation study. The results observed for optimized QMNE were as follows: mean globule size (91.63 ± 4.36 nm), zeta potential (-17.26 ± 1.04 mV), drug content (99.84 ± 0.34%) and viscosity (121 ± 13 cp). To evaluate the extent of bioavailability for QMNE via post-intranasal (i.n.) administration, Ultra performance liquid chromatography-mass spectroscopy (UPLC-ESI-Q-TOF-MS/MS)-based bioanalytical method was developed and validated for pharmacokinetics, biodistribution, brain-targeting efficiency (9333.33 ± 39.39%) and brain drug-targeting potential (2181.83 ± 5.69%) which revealed enhanced QUR brain bioavailability as compared to intravenous administration (i.v.). Furthermore, improved neurobehavioral activity (locomotor and grip strength), histopathology and reduced infarction volume effects were observed in middle cerebral artery occlusion (MCAO)-induced cerebral ischemic rats model after i.n. administration of QMNE. This study supports a significant role for QMNE in terms of high brain-targeting potential and formulation efficiency due to ease of access and effective targeting in brain.

Encoder-Decoder Optimization for Brain-Computer Interfaces

PubMed Central

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

2015-01-01

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. PMID:26029919

Encoder-decoder optimization for brain-computer interfaces.

PubMed

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.

Optimal-mass-transfer-based estimation of glymphatic transport in living brain

NASA Astrophysics Data System (ADS)

Ratner, Vadim; Zhu, Liangjia; Kolesov, Ivan; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2015-03-01

It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial fluid exchange system designated the `glymphatic pathway' plays a key role in removing waste products from the brain, similarly to the lymphatic system in other body organs . It is therefore important to study the flow patterns of glymphatic transport through the live brain in order to better understand its functionality in normal and pathological states. Unlike blood, the CSF does not flow rapidly through a network of dedicated vessels, but rather through para-vascular channels and brain parenchyma in a slower time-domain, and thus conventional fMRI or other blood-flow sensitive MRI sequences do not provide much useful information about the desired flow patterns. We have accordingly analyzed a series of MRI images, taken at different times, of the brain of a live rat, which was injected with a paramagnetic tracer into the CSF via the lumbar intrathecal space of the spine. Our goal is twofold: (a) find glymphatic (tracer) flow directions in the live rodent brain; and (b) provide a model of a (healthy) brain that will allow the prediction of tracer concentrations given initial conditions. We model the liquid flow through the brain by the diffusion equation. We then use the Optimal Mass Transfer (OMT) approach to derive the glymphatic flow vector field, and estimate the diffusion tensors by analyzing the (changes in the) flow. Simulations show that the resulting model successfully reproduces the dominant features of the experimental data. Keywords: inverse problem, optimal mass transport, diffusion equation, cerebrospinal fluid flow in brain, optical flow, liquid flow modeling, Monge Kantorovich problem, diffusion tensor estimation

A method to predict different mechanisms for blood-brain barrier permeability of CNS activity compounds in Chinese herbs using support vector machine.

PubMed

Jiang, Ludi; Chen, Jiahua; He, Yusu; Zhang, Yanling; Li, Gongyu

2016-02-01

The blood-brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB prior to their target site, so the prediction research on BBB permeability is a fundamental and significant research direction in neuropharmacology. In this study, we combed through the available data and then with the help of support vector machine (SVM), we established an experiment process for discovering potential CNS compounds and investigating the mechanisms of BBB permeability of them to advance the research in this field four types of prediction models, referring to CNS activity, BBB permeability, passive diffusion and efflux transport, were obtained in the experiment process. The first two models were used to discover compounds which may have CNS activity and also cross the BBB at the same time; the latter two were used to elucidate the mechanism of BBB permeability of those compounds. Three optimization parameter methods, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), were used to optimize the SVM models. Then, four optimal models were selected with excellent evaluation indexes (the accuracy, sensitivity and specificity of each model were all above 85%). Furthermore, discrimination models were utilized to study the BBB properties of the known CNS activity compounds in Chinese herbs and this may guide the CNS drug development. With the relatively systematic and quick approach, the application rationality of traditional Chinese medicines for treating nervous system disease in the clinical practice will be improved.

Developmental Perspectives on Optimizing Educational and Vocational Outcomes in Child and Adult Survivors of Cancer

ERIC Educational Resources Information Center

Rey-Casserly, Celiane; Meadows, Mary Ellen

2008-01-01

Over the last few decades, long-term survival rates of children diagnosed with the two most common forms of childhood cancer, acute lymphoblastic leukemia (ALL) and brain tumors have improved substantially. Neurodevelopmental and psychosocial sequelae resulting from these diseases and their treatment have a direct impact on the developing brain…

Opportunity Knocks! Inquiry, the New National Social Studies and Science Standards, and You

ERIC Educational Resources Information Center

Ratzer, Mary Boyd

2014-01-01

To be recognized and adopted, the promise and potential of national standards must validate the instructional role of the school librarian and build formative knowledge through authentic process and products. Inquiry is a direct link to those dimensions. Standards that are rigorous and relevant optimize the developing brain's affinity for building…

Stereotactic radiosurgery alone for multiple brain metastases? A review of clinical and technical issues

PubMed Central

Ruschin, Mark; Ma, Lijun; Verbakel, Wilko; Larson, David; Brown, Paul D.

2017-01-01

Abstract Over the past three decades several randomized trials have enabled evidence-based practice for patients presenting with limited brain metastases. These trials have focused on the role of surgery or stereotactic radiosurgery (SRS) with or without whole brain radiation therapy (WBRT). As a result, it is clear that local control should be optimized with surgery or SRS in patients with optimal prognostic factors presenting with up to 4 brain metastases. The routine use of adjuvant WBRT remains debatable, as although greater distant brain control rates are observed, there is no impact on survival, and modern outcomes suggest adverse effects from WBRT on patient cognition and quality of life. With dramatic technologic advances in radiation oncology facilitating the adoption of SRS into mainstream practice, the optimal management of patients with multiple brain metastases is now being put forward. Practice is evolving to SRS alone in these patients despite a lack of level 1 evidence to support a clinical departure from WBRT. The purpose of this review is to summarize the current state of the evidence for patients presenting with limited and multiple metastases, and to present an in-depth analysis of the technology and dosimetric issues specific to the treatment of multiple metastases. PMID:28380635

Ultrasound effects on brain-targeting mannosylated liposomes: in vitro and blood-brain barrier transport investigations.

PubMed

Zidan, Ahmed S; Aldawsari, Hibah

2015-01-01

Delivering drugs to intracerebral regions can be accomplished by improving the capacity of transport through blood-brain barrier. Using sertraline as model drug for brain targeting, the current study aimed at modifying its liposomal vesicles with mannopyranoside. Box-Behnken design was employed to statistically optimize the ultrasound parameters, namely ultrasound amplitude, time, and temperature, for maximum mannosylation capacity, sertraline entrapment, and surface charge while minimizing vesicular size. Moreover, in vitro blood-brain barrier transport model was established to assess the transendothelial capacity of the optimized mannosylated vesicles. Results showed a dependence of vesicular size, mannosylation capacity, and sertraline entrapment on cavitation and bubble implosion events that were related to ultrasound power amplitude, temperature. However, short ultrasound duration was required to achieve >90% mannosylation with nanosized vesicles (<200 nm) of narrow size distribution. Optimized ultrasound parameters of 65°C, 27%, and 59 seconds for ultrasound temperature, amplitude, and time were elucidated to produce 81.1%, 46.6 nm, and 77.6% sertraline entrapment, vesicular size, and mannosylation capacity, respectively. Moreover, the transendothelial ability was significantly increased by 2.5-fold by mannosylation through binding with glucose transporters. Hence, mannosylated liposomes processed by ultrasound could be a promising approach for manufacturing and scale-up of brain-targeting liposomes.

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

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

Abdulbaqi, Hayder Saad; Department of Physics, College of Education, University of Al-Qadisiya, Al-Qadisiya; Jafri, Mohd Zubir Mat

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introducemore » a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.« less

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

Toward a preoperative planning tool for brain tumor resection therapies.

PubMed

Coffey, Aaron M; Miga, Michael I; Chen, Ishita; Thompson, Reid C

2013-01-01

Neurosurgical procedures involving tumor resection require surgical planning such that the surgical path to the tumor is determined to minimize the impact on healthy tissue and brain function. This work demonstrates a predictive tool to aid neurosurgeons in planning tumor resection therapies by finding an optimal model-selected patient orientation that minimizes lateral brain shift in the field of view. Such orientations may facilitate tumor access and removal, possibly reduce the need for retraction, and could minimize the impact of brain shift on image-guided procedures. In this study, preoperative magnetic resonance images were utilized in conjunction with pre- and post-resection laser range scans of the craniotomy and cortical surface to produce patient-specific finite element models of intraoperative shift for 6 cases. These cases were used to calibrate a model (i.e., provide general rules for the application of patient positioning parameters) as well as determine the current model-based framework predictive capabilities. Finally, an objective function is proposed that minimizes shift subject to patient position parameters. Patient positioning parameters were then optimized and compared to our neurosurgeon as a preliminary study. The proposed model-driven brain shift minimization objective function suggests an overall reduction of brain shift by 23 % over experiential methods. This work recasts surgical simulation from a trial-and-error process to one where options are presented to the surgeon arising from an optimization of surgical goals. To our knowledge, this is the first realization of an evaluative tool for surgical planning that attempts to optimize surgical approach by means of shift minimization in this manner.

Exact solution for the optimal neuronal layout problem.

PubMed

Chklovskii, Dmitri B

2004-10-01

Evolution perfected brain design by maximizing its functionality while minimizing costs associated with building and maintaining it. Assumption that brain functionality is specified by neuronal connectivity, implemented by costly biological wiring, leads to the following optimal design problem. For a given neuronal connectivity, find a spatial layout of neurons that minimizes the wiring cost. Unfortunately, this problem is difficult to solve because the number of possible layouts is often astronomically large. We argue that the wiring cost may scale as wire length squared, reducing the optimal layout problem to a constrained minimization of a quadratic form. For biologically plausible constraints, this problem has exact analytical solutions, which give reasonable approximations to actual layouts in the brain. These solutions make the inverse problem of inferring neuronal connectivity from neuronal layout more tractable.

Brain temperature measurement: A study of in vitro accuracy and stability of smart catheter temperature sensors.

PubMed

Li, Chunyan; Wu, Pei-Ming; Wu, Zhizhen; Ahn, Chong H; LeDoux, David; Shutter, Lori A; Hartings, Jed A; Narayan, Raj K

2012-02-01

The injured brain is vulnerable to increases in temperature after severe head injury. Therefore, accurate and reliable measurement of brain temperature is important to optimize patient outcome. In this work, we have fabricated, optimized and characterized temperature sensors for use with a micromachined smart catheter for multimodal intracranial monitoring. Developed temperature sensors have resistance of 100.79 ± 1.19Ω and sensitivity of 67.95 mV/°C in the operating range from15-50°C, and time constant of 180 ms. Under the optimized excitation current of 500 μA, adequate signal-to-noise ratio was achieved without causing self-heating, and changes in immersion depth did not introduce clinically significant errors of measurements (<0.01°C). We evaluated the accuracy and long-term drift (5 days) of twenty temperature sensors in comparison to two types of commercial temperature probes (USB Reference Thermometer, NIST-traceable bulk probe with 0.05°C accuracy; and IT-21, type T type clinical microprobe with guaranteed 0.1°C accuracy) under controlled laboratory conditions. These in vitro experimental data showed that the temperature measurement performance of our sensors was accurate and reliable over the course of 5 days. The smart catheter temperature sensors provided accuracy and long-term stability comparable to those of commercial tissue-implantable microprobes, and therefore provide a means for temperature measurement in a microfabricated, multimodal cerebral monitoring device.

A new wrinkle on the brain

NASA Astrophysics Data System (ADS)

Taber, Larry A.

2018-05-01

The folded structure of the human brain is a hallmark of our intelligence — an optimized packing of neurons into a confined space. Similar wrinkling in brain-on-a-chip experiments provides a way of understanding the physics of how this occurs.

Cerebral cortex three-dimensional profiling in human fetuses by magnetic resonance imaging

PubMed Central

Sbarbati, Andrea; Pizzini, Francesca; Fabene, Paolo F; Nicolato, Elena; Marzola, Pasquina; Calderan, Laura; Simonati, Alessandro; Longo, Laura; Osculati, Antonio; Beltramello, Alberto

2004-01-01

Seven human fetuses of crown/rump length corresponding to gestational ages ranging from the 12th to the 16th week were studied using a paradigm based on three-dimensional reconstruction of the brain obtained by magnetic resonance imaging (MRI). The aim of the study was to evaluate brain morphology in situ and to describe developmental dynamics during an important period of fetal morphogenesis. Three-dimensional MRI showed the increasing degree of maturation of the brains; fronto-occipital distance, bitemporal distance and occipital angle were examined in all the fetuses. The data were interpreted by correlation with the internal structure as visualized using high-spatial-resolution MRI, acquired using a 4.7-T field intensity magnet with a gradient power of 20 G cm−1. The spatial resolution was sufficient for a detailed detection of five layers, and the contrast was optimized using sequences with different degrees of T1 and T2 weighting. Using the latter, it was possible to visualize the subplate and marginal zones. The cortical thickness was mapped on to the hemispheric surface, describing the thickness gradient from the insular cortex to the periphery of the hemispheres. The study demonstrates the utility of MRI for studying brain development. The method provides a quantitative profiling of the brain, which allows the calculation of important morphological parameters, and it provides informative regarding transient features of the developing brain. PMID:15198688

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

Use of High Resolution 3D Diffusion Tensor Imaging to Study Brain White Matter Development in Live Neonatal Rats

PubMed Central

Cai, Yu; McMurray, Matthew S.; Oguz, Ipek; Yuan, Hong; Styner, Martin A.; Lin, Weili; Johns, Josephine M.; An, Hongyu

2011-01-01

High resolution diffusion tensor imaging (DTI) can provide important information on brain development, yet it is challenging in live neonatal rats due to the small size of neonatal brain and motion-sensitive nature of DTI. Imaging in live neonatal rats has clear advantages over fixed brain scans, as longitudinal and functional studies would be feasible to understand neuro-developmental abnormalities. In this study, we developed imaging strategies that can be used to obtain high resolution 3D DTI images in live neonatal rats at postnatal day 5 (PND5) and PND14, using only 3 h of imaging acquisition time. An optimized 3D DTI pulse sequence and appropriate animal setup to minimize physiological motion artifacts are the keys to successful high resolution 3D DTI imaging. Thus, a 3D rapid acquisition relaxation enhancement DTI sequence with twin navigator echoes was implemented to accelerate imaging acquisition time and minimize motion artifacts. It has been suggested that neonatal mammals possess a unique ability to tolerate mild-to-moderate hypothermia and hypoxia without long term impact. Thus, we additionally utilized this ability to minimize motion artifacts in magnetic resonance images by carefully suppressing the respiratory rate to around 15/min for PND5 and 30/min for PND14 using mild-to-moderate hypothermia. These imaging strategies have been successfully implemented to study how the effect of cocaine exposure in dams might affect brain development in their rat pups. Image quality resulting from this in vivo DTI study was comparable to ex vivo scans. fractional anisotropy values were also similar between the live and fixed brain scans. The capability of acquiring high quality in vivo DTI imaging offers a valuable opportunity to study many neurological disorders in brain development in an authentic living environment. PMID:22013426

The gastrointestinal-brain axis in humans as an evolutionary advance of the root-leaf axis in plants: A hypothesis linking quantum effects of light on serotonin and auxin.

PubMed

Tonello, Lucio; Gashi, Bekim; Scuotto, Alessandro; Cappello, Glenda; Cocchi, Massimo; Gabrielli, Fabio; Tuszynski, Jack A

2018-01-01

Living organisms tend to find viable strategies under ambient conditions that optimize their search for, and utilization of, life-sustaining resources. For plants, a leading role in this process is performed by auxin, a plant hormone that drives morphological development, dynamics, and movement to optimize the absorption of light (through branches and leaves) and chemical "food" (through roots). Similarly to auxin in plants, serotonin seems to play an important role in higher animals, especially humans. Here, it is proposed that morphological and functional similarities between (i) plant leaves and the animal/human brain and (ii) plant roots and the animal/human gastro-intestinal tract have general features in common. Plants interact with light and use it for biological energy, whereas, neurons in the central nervous system seem to interact with bio-photons and use them for proper brain function. Further, as auxin drives roots "arborescence" within the soil, similarly serotonin seems to facilitate enteric nervous system connectivity within the human gastro-intestinal tract. This auxin/serotonin parallel suggests the root-branches axis in plants may be an evolutionary precursor to the gastro-intestinal-brain axis in humans. Finally, we hypothesize that light might be an important factor, both in gastro-intestinal dynamics and brain function. Such a comparison may indicate a key role for the interaction of light and serotonin in neuronal physiology (possibly in both the central nervous system and the enteric nervous system), and according to recent work, mind and consciousness.

Effect of Boric Acid Supplementation on the Expression of BDNF in African Ostrich Chick Brain.

PubMed

Tang, Juan; Zheng, Xing-ting; Xiao, Ke; Wang, Kun-lun; Wang, Jing; Wang, Yun-xiao; Wang, Ke; Wang, Wei; Lu, Shun; Yang, Ke-li; Sun, Peng-Peng; Khaliq, Haseeb; Zhong, Juming; Peng, Ke-Mei

2016-03-01

The degree of brain development can be expressed by the levels of brain brain-derived neurotrophic factor (BDNF). BDNF plays an irreplaceable role in the process of neuronal development, protection, and restoration. The aim of the present study was to evaluate the effects of boric acid supplementation in water on the ostrich chick neuronal development. One-day-old healthy animals were supplemented with boron in drinking water at various concentrations, and the potential effects of boric acid on brain development were tested by a series of experiments. The histological changes in brain were observed by hematoxylin and eosin (HE) staining and Nissl staining. Expression of BDNF was analyzed by immunohistochemistry, quantitative real-time PCR (QRT-PCR), and enzyme linked immunosorbent assay (ELISA). Apoptosis was evaluated with Dutp-biotin nick end labeling (TUNEL) reaction, and caspase-3 was detected with QRT-PCR. The results were as follows: (1) under the light microscope, the neuron structure was well developed with abundance of neurites and intact cell morphology when animals were fed with less than 160 mg/L of boric acid (groups II, III, IV). Adversely, when boric acid doses were higher than 320 mg/L(groups V, VI), the high-dose boric acid neuron structure was damaged with less neurites, particularly at 640 mg/L; (2) the quantity of BDNF expression in groups II, III, and IV was increased while it was decreased in groups V and VI when compared with that in group I; (3) TUNEL reaction and the caspase-3 mRNA level showed that the amount of cell apoptosis in group II, group III, and group IV were decreased, but increased in group V and group VI significantly. These results indicated that appropriate supplementation of boric acid, especially at 160 mg/L, could promote ostrich chicks' brain development by promoting the BDNF expression and reducing cell apoptosis. Conversely, high dose of boric acid particularly in 640 mg/L would damage the neuron structure of ostrich chick brain by inhibiting the BDNF expression and increasing cell apoptosis. Taken together, the 160 mg/L boric acid supplementation may be the optimal dose for the brain development of ostrich chicks.

SU-E-T-664: Radiobiological Modeling of Prophylactic Cranial Irradiation in Mice

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

Smith, D; Debeb, B; Woodward, W

Purpose: Prophylactic cranial irradiation (PCI) is a clinical technique used to reduce the incidence of brain metastasis and improve overall survival in select patients with ALL and SCLC, and we have shown the potential of PCI in select breast cancer patients through a mouse model (manuscript in preparation). We developed a computational model using our experimental results to demonstrate the advantage of treating brain micro-metastases early. Methods: MATLAB was used to develop the computational model of brain metastasis and PCI in mice. The number of metastases per mouse and the volume of metastases from four- and eight-week endpoints were fitmore » to normal and log-normal distributions, respectively. Model input parameters were optimized so that model output would match the experimental number of metastases per mouse. A limiting dilution assay was performed to validate the model. The effect of radiation at different time points was computationally evaluated through the endpoints of incidence, number of metastases, and tumor burden. Results: The correlation between experimental number of metastases per mouse and the Gaussian fit was 87% and 66% at the two endpoints. The experimental volumes and the log-normal fit had correlations of 99% and 97%. In the optimized model, the correlation between number of metastases per mouse and the Gaussian fit was 96% and 98%. The log-normal volume fit and the model agree 100%. The model was validated by a limiting dilution assay, where the correlation was 100%. The model demonstrates that cells are very sensitive to radiation at early time points, and delaying treatment introduces a threshold dose at which point the incidence and number of metastases decline. Conclusion: We have developed a computational model of brain metastasis and PCI in mice that is highly correlated to our experimental data. The model shows that early treatment of subclinical disease is highly advantageous.« less

The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study.

PubMed

Cai, Lin; Dong, Qi; Niu, Haijing

2018-04-01

Early childhood (7-8 years old) and early adolescence (11-12 years old) constitute two landmark developmental stages that comprise considerable changes in neural cognition. However, very limited information from functional neuroimaging studies exists on the functional topological configuration of the human brain during specific developmental periods. In the present study, we utilized continuous resting-state functional near-infrared spectroscopy (rs-fNIRS) imaging data to examine topological changes in network organization during development from early childhood and early adolescence to adulthood. Our results showed that the properties of small-worldness and modularity were not significantly different across development, demonstrating the developmental maturity of important functional brain organization in early childhood. Intriguingly, young children had a significantly lower global efficiency than early adolescents and adults, which revealed that the integration of the distributed networks strengthens across the developmental stages underlying cognitive development. Moreover, local efficiency of young children and adolescents was significantly lower than that of adults, while there was no difference between these two younger groups. This finding demonstrated that functional segregation remained relatively steady from early childhood to early adolescence, and the brain in these developmental periods possesses no optimal network configuration. Furthermore, we found heterogeneous developmental patterns in the regional nodal properties in various brain regions, such as linear increased nodal properties in the frontal cortex, indicating increasing cognitive capacity over development. Collectively, our results demonstrated that significant topological changes in functional network organization occurred during these two critical developmental stages, and provided a novel insight into elucidating subtle changes in brain functional networks across development. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Altered resting-state whole-brain functional networks of neonates with intrauterine growth restriction.

PubMed

Batalle, Dafnis; Muñoz-Moreno, Emma; Tornador, Cristian; Bargallo, Nuria; Deco, Gustavo; Eixarch, Elisenda; Gratacos, Eduard

2016-04-01

The feasibility to use functional MRI (fMRI) during natural sleep to assess low-frequency basal brain activity fluctuations in human neonates has been demonstrated, although its potential to characterise pathologies of prenatal origin has not yet been exploited. In the present study, we used intrauterine growth restriction (IUGR) as a model of altered neurodevelopment due to prenatal condition to show the suitability of brain networks to characterise functional brain organisation at neonatal age. Particularly, we analysed resting-state fMRI signal of 20 neonates with IUGR and 13 controls, obtaining whole-brain functional networks based on correlations of blood oxygen level-dependent (BOLD) signal in 90 grey matter regions of an anatomical atlas (AAL). Characterisation of the networks obtained with graph theoretical features showed increased network infrastructure and raw efficiencies but reduced efficiency after normalisation, demonstrating hyper-connected but sub-optimally organised IUGR functional brain networks. Significant association of network features with neurobehavioral scores was also found. Further assessment of spatiotemporal dynamics displayed alterations into features associated to frontal, cingulate and lingual cortices. These findings show the capacity of functional brain networks to characterise brain reorganisation from an early age, and their potential to develop biomarkers of altered neurodevelopment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Structured illumination diffuse optical tomography for noninvasive functional neuroimaging in mice.

PubMed

Reisman, Matthew D; Markow, Zachary E; Bauer, Adam Q; Culver, Joseph P

2017-04-01

Optical intrinsic signal (OIS) imaging has been a powerful tool for capturing functional brain hemodynamics in rodents. Recent wide field-of-view implementations of OIS have provided efficient maps of functional connectivity from spontaneous brain activity in mice. However, OIS requires scalp retraction and is limited to superficial cortical tissues. Diffuse optical tomography (DOT) techniques provide noninvasive imaging, but previous DOT systems for rodent neuroimaging have been limited either by sparse spatial sampling or by slow speed. Here, we develop a DOT system with asymmetric source-detector sampling that combines the high-density spatial sampling (0.4 mm) detection of a scientific complementary metal-oxide-semiconductor camera with the rapid (2 Hz) imaging of a few ([Formula: see text]) structured illumination (SI) patterns. Analysis techniques are developed to take advantage of the system's flexibility and optimize trade-offs among spatial sampling, imaging speed, and signal-to-noise ratio. An effective source-detector separation for the SI patterns was developed and compared with light intensity for a quantitative assessment of data quality. The light fall-off versus effective distance was also used for in situ empirical optimization of our light model. We demonstrated the feasibility of this technique by noninvasively mapping the functional response in the somatosensory cortex of the mouse following electrical stimulation of the forepaw.

Fitted hyperelastic parameters for Human brain tissue from reported tension, compression, and shear tests.

PubMed

Moran, Richard; Smith, Joshua H; García, José J

2014-11-28

The mechanical properties of human brain tissue are the subject of interest because of their use in understanding brain trauma and in developing therapeutic treatments and procedures. To represent the behavior of the tissue, we have developed hyperelastic mechanical models whose parameters are fitted in accordance with experimental test results. However, most studies available in the literature have fitted parameters with data of a single type of loading, such as tension, compression, or shear. Recently, Jin et al. (Journal of Biomechanics 46:2795-2801, 2013) reported data from ex vivo tests of human brain tissue under tension, compression, and shear loading using four strain rates and four different brain regions. However, they do not report parameters of energy functions that can be readily used in finite element simulations. To represent the tissue behavior for the quasi-static loading conditions, we aimed to determine the best fit of the hyperelastic parameters of the hyperfoam, Ogden, and polynomial strain energy functions available in ABAQUS for the low strain rate data, while simultaneously considering all three loading modes. We used an optimization process conducted in MATLAB, calling iteratively three finite element models developed in ABAQUS that represent the three loadings. Results showed a relatively good fit to experimental data in all loading modes using two terms in the energy functions. Values for the shear modulus obtained in this analysis (897-1653Pa) are in the range of those presented in other studies. These energy-function parameters can be used in brain tissue simulations using finite element models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Postprandial changes in leptin concentrations of cerebrospinal fluid in dogs during development of obesity.

PubMed

Nishii, Naohito; Nodake, Hiroyuki; Takasu, Masaki; Soe, Okkar; Ohba, Yasunori; Maeda, Sadatoshi; Ohtsuka, Yoshihiko; Honjo, Tsutomu; Saito, Masayuki; Kitagawa, Hitoshi

2006-12-01

To evaluate postprandial changes in the leptin concentration of CSF in dogs during development of obesity. 4 male Beagles. Weight gain was induced and assessments were made when the dogs were in thin, optimal, and obese body conditions (BCs). The fat area at the level of the L3 vertebra was measured via computed tomography to assess the degree of obesity. Dogs were evaluated in fed and unfed states. Dogs in the fed state received food at 9 AM. Blood and CSF samples were collected at 8 AM, 4 PM, and 10 PM. Baseline CSF leptin concentrations in the thin, optimal, and obese dogs were 24.3 +/- 2.7 pg/mL, 86.1 +/- 14.7 pg/mL, and 116.2 +/- 47.3 pg/mL, respectively. In the thin BC, CSF leptin concentration transiently increased at 4 PM. In the optimal BC, baseline CSF leptin concentration was maintained until 10 PM. In the obese BC, CSF leptin concentration increased from baseline value at 4 PM and 10 PM. Correlation between CSF leptin concentration and fat area was good at all time points. There was a significant negative correlation between the CSF leptin concentration-to-serum leptin concentration ratio and fat area at 4 PM; this correlation was not significant at 8 AM and 10 PM. Decreased transport of leptin at the blood-brain barrier may be 1 mechanism of leptin resistance in dogs. However, leptin resistance at the blood-brain barrier may not be important in development of obesity in dogs.

3D printing of layered brain-like structures using peptide modified gellan gum substrates.

PubMed

Lozano, Rodrigo; Stevens, Leo; Thompson, Brianna C; Gilmore, Kerry J; Gorkin, Robert; Stewart, Elise M; in het Panhuis, Marc; Romero-Ortega, Mario; Wallace, Gordon G

2015-10-01

The brain is an enormously complex organ structured into various regions of layered tissue. Researchers have attempted to study the brain by modeling the architecture using two dimensional (2D) in vitro cell culturing methods. While those platforms attempt to mimic the in vivo environment, they do not truly resemble the three dimensional (3D) microstructure of neuronal tissues. Development of an accurate in vitro model of the brain remains a significant obstacle to our understanding of the functioning of the brain at the tissue or organ level. To address these obstacles, we demonstrate a new method to bioprint 3D brain-like structures consisting of discrete layers of primary neural cells encapsulated in hydrogels. Brain-like structures were constructed using a bio-ink consisting of a novel peptide-modified biopolymer, gellan gum-RGD (RGD-GG), combined with primary cortical neurons. The ink was optimized for a modified reactive printing process and developed for use in traditional cell culturing facilities without the need for extensive bioprinting equipment. Furthermore the peptide modification of the gellan gum hydrogel was found to have a profound positive effect on primary cell proliferation and network formation. The neural cell viability combined with the support of neural network formation demonstrated the cell supportive nature of the matrix. The facile ability to form discrete cell-containing layers validates the application of this novel printing technique to form complex, layered and viable 3D cell structures. These brain-like structures offer the opportunity to reproduce more accurate 3D in vitro microstructures with applications ranging from cell behavior studies to improving our understanding of brain injuries and neurodegenerative diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Surface modified PLGA nanoparticles for brain targeting of Bacoside-A.

PubMed

Jose, S; Sowmya, S; Cinu, T A; Aleykutty, N A; Thomas, S; Souto, E B

2014-10-15

The present paper focuses on the development and in vitro/in vivo characterization of nanoparticles composed of poly-(D,L)-Lactide-co-Glycolide (PLGA) loading Bacoside-A, as a new approach for the brain delivery of the neuroprotective drug for the treatment of neurodegenerative disorders (e.g. Alzheimer Disease). Bacoside-A-loaded PLGA nanoparticles were prepared via o/w emulsion solvent evaporation technique. Surface of the nanoparticles were modified by coating with polysorbate 80 to facilitate the crossing of the blood brain barrier (BBB), and the processing parameters (i.e. sonication time, the concentration of polymer (PLGA) and surfactant (polysorbate 80), and drug-polymer ratio) were optimized with the aim to achieve a high production yield. Brain targeting potential of the nanoparticles was evaluated by in vivo studies using Wistar albino rats. The nanoparticles produced by optimal formulation were within the nanosized range (70-200 nm) with relatively low polydispersity index (0.391 ± 1.2). The encapsulation efficiency of Bacoside-A in PLGA nanoparticles was 57.11 ± 7.11%, with a drug loading capacity of 20.5 ± 1.98%. SEM images showed the spherical shape of the PLGA nanoparticles, whereas their low crystallinity was demonstrated by X-ray studies, which also confirmed no chemical interactions between the drug and polymer molecules. The in vitro release of Bacoside-A from the PLGA nanoparticles followed a sustained release pattern with a maximum release of up to 83.04 ± 2.55% in 48 h. When compared to pure drug solution (2.56 ± 1.23 μg/g tissue), in vivo study demonstrated higher brain concentration of Bacoside-A (23.94 ± 1.74 μg/g tissue) suggesting a significant role of surface coated nanoparticles on brain targeting. The results indicate the potential of surface modified PLGA nanoparticles for the delivery of Bacoside-A to the brain. Copyright © 2014 Elsevier B.V. All rights reserved.

Biomarkers of Brain Damage and Postoperative Cognitive Disorders in Orthopedic Patients: An Update.

PubMed

Tomaszewski, Dariusz

2015-01-01

The incidence of postoperative cognitive dysfunction (POCD) in orthopedic patients varies from 16% to 45%, although it can be as high as 72%. As a consequence, the hospitalization time of patients who developed POCD was longer, the outcome and quality of life were worsened, and prolonged medical and social assistance were necessary. In this review the short description of such biomarkers of brain damage as the S100B protein, NSE, GFAP, Tau protein, metalloproteinases, ubiquitin C terminal hydrolase, microtubule-associated protein, myelin basic protein, α-II spectrin breakdown products, and microRNA was made. The role of thromboembolic material in the development of cognitive decline was also discussed. Special attention was paid to optimization of surgical and anesthetic procedures in the prevention of postoperative cognitive decline.

Interpreting CARS images of tissue within the C-H-stretching region

NASA Astrophysics Data System (ADS)

Dietzek, Benjamin; Meyer, Tobias; Medyukhina, Anna; Bergner, Norbert; Krafft, Christoph; Romeike, Bernd F. M.; Reichart, Rupert; Kalff, Rolf; Schmitt, Michael; Popp, Jürgen

2014-03-01

Single band coherent anti-Stokes Raman scattering (CARS) microscopy within the CH-stretching region is applied to detect individual cells and nuclei of human brain tissue and brain tumors - an information which allows for histopathologic grading of the tissue. The CARS image contrast within the C-H-stretching region correlated to the tissue composition. Based on the specific application example of identifying nuclei within (coherent) Raman images of neurotissue sections, we shall derive general design parameters for lasers optimally suited to serve in a clinical environment and discuss the potential of recently developed methods to analyze spectrally resolved CARS images and image segmentation algorithms.

Optimal Achievable Encoding for Brain Machine Interface

DTIC Science & Technology

2017-12-22

dictionary-based encoding approach to translate a visual image into sequential patterns of electrical stimulation in real time , in a manner that...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...networks, and by applying linear decoding to complete recorded populations of retinal ganglion cells for the first time . Third, we developed a greedy

Characterization of electroencephalography signals for estimating saliency features in videos.

PubMed

Liang, Zhen; Hamada, Yasuyuki; Oba, Shigeyuki; Ishii, Shin

2018-05-12

Understanding the functions of the visual system has been one of the major targets in neuroscience formany years. However, the relation between spontaneous brain activities and visual saliency in natural stimuli has yet to be elucidated. In this study, we developed an optimized machine learning-based decoding model to explore the possible relationships between the electroencephalography (EEG) characteristics and visual saliency. The optimal features were extracted from the EEG signals and saliency map which was computed according to an unsupervised saliency model ( Tavakoli and Laaksonen, 2017). Subsequently, various unsupervised feature selection/extraction techniques were examined using different supervised regression models. The robustness of the presented model was fully verified by means of ten-fold or nested cross validation procedure, and promising results were achieved in the reconstruction of saliency features based on the selected EEG characteristics. Through the successful demonstration of using EEG characteristics to predict the real-time saliency distribution in natural videos, we suggest the feasibility of quantifying visual content through measuring brain activities (EEG signals) in real environments, which would facilitate the understanding of cortical involvement in the processing of natural visual stimuli and application developments motivated by human visual processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

Nanoparticle-mediated growth factor delivery systems: A new way to treat Alzheimer's disease.

PubMed

Lauzon, Marc-Antoine; Daviau, Alex; Marcos, Bernard; Faucheux, Nathalie

2015-05-28

The number of people diagnosed with Alzheimer's disease (AD) is increasing steadily as the world population ages, thus creating a huge socio-economic burden. Current treatments have only transient effects and concentrate on a single aspect of AD. There is much evidence suggesting that growth factors (GFs) have a great therapeutic potential and can play on all AD hallmarks. Because GFs are prone to denaturation and clearance, a delivery system is required to ensure protection and a sustainable delivery. This review provides information about the latest advances in the development of GF delivery systems (GFDS) targeting the brain in terms of in vitro and in vivo effects in the context of AD and discusses new strategies designed to increase the availability and the specificity of GFs to the brain. This paper also discusses, on a mechanistic level, the different delivery hurdles encountered by the carrier or the GF itself from its injection site up to the brain tissue. The major mass transport phenomena influencing the delivery systems targeting the brain are addressed and insights are given about how mechanistic mathematical frameworks can be developed to use and optimize them. Copyright © 2015. Published by Elsevier B.V.

Mapping brain development during childhood, adolescence and young adulthood

NASA Astrophysics Data System (ADS)

Guo, Xiaojuan; Jin, Zhen; Chen, Kewei; Peng, Danling; Li, Yao

2009-02-01

Using optimized voxel-based morphometry (VBM), this study systematically investigated the differences and similarities of brain structural changes during the early three developmental periods of human lives: childhood, adolescence and young adulthood. These brain changes were discussed in relationship to the corresponding cognitive function development during these three periods. Magnetic Resonance Imaging (MRI) data from 158 Chinese healthy children, adolescents and young adults, aged 7.26 to 22.80 years old, were included in this study. Using the customized brain template together with the gray matter/white matter/cerebrospinal fluid prior probability maps, we found that there were more age-related positive changes in the frontal lobe, less in hippocampus and amygdala during childhood, but more in bilateral hippocampus and amygdala and left fusiform gyrus during adolescence and young adulthood. There were more age-related negative changes near to central sulcus during childhood, but these changes extended to the frontal and parietal lobes, mainly in the parietal lobe, during adolescence and young adulthood, and more in the prefrontal lobe during young adulthood. So gray matter volume in the parietal lobe significantly decreased from childhood and continued to decrease till young adulthood. These findings may aid in understanding the age-related differences in cognitive function.

Microsurgery Simulator of Cerebral Aneurysm Clipping with Interactive Cerebral Deformation Featuring a Virtual Arachnoid.

PubMed

Shono, Naoyuki; Kin, Taichi; Nomura, Seiji; Miyawaki, Satoru; Saito, Toki; Imai, Hideaki; Nakatomi, Hirofumi; Oyama, Hiroshi; Saito, Nobuhito

2018-05-01

A virtual reality simulator for aneurysmal clipping surgery is an attractive research target for neurosurgeons. Brain deformation is one of the most important functionalities necessary for an accurate clipping simulator and is vastly affected by the status of the supporting tissue, such as the arachnoid membrane. However, no virtual reality simulator implementing the supporting tissue of the brain has yet been developed. To develop a virtual reality clipping simulator possessing interactive brain deforming capability closely dependent on arachnoid dissection and apply it to clinical cases. Three-dimensional computer graphics models of cerebral tissue and surrounding structures were extracted from medical images. We developed a new method for modifiable cerebral tissue complex deformation by incorporating a nonmedical image-derived virtual arachnoid/trabecula in a process called multitissue integrated interactive deformation (MTIID). MTIID made it possible for cerebral tissue complexes to selectively deform at the site of dissection. Simulations for 8 cases of actual clipping surgery were performed before surgery and evaluated for their usefulness in surgical approach planning. Preoperatively, each operative field was precisely reproduced and visualized with the virtual brain retraction defined by users. The clear visualization of the optimal approach to treating the aneurysm via an appropriate arachnoid incision was possible with MTIID. A virtual clipping simulator mainly focusing on supporting tissues and less on physical properties seemed to be useful in the surgical simulation of cerebral aneurysm clipping. To our knowledge, this article is the first to report brain deformation based on supporting tissues.

Intracranial pressure increases during exposure to a shock wave.

PubMed

Leonardi, Alessandra Dal Cengio; Bir, Cynthia A; Ritzel, Dave V; VandeVord, Pamela J

2011-01-01

Traumatic brain injuries (TBI) caused by improvised explosive devices (IEDs) affect a significant percentage of surviving soldiers wounded in Iraq and Afghanistan. The extent of a blast TBI, especially initially, is difficult to diagnose, as internal injuries are frequently unrecognized and therefore underestimated, yet problems develop over time. Therefore it is paramount to resolve the physical mechanisms by which critical stresses are inflicted on brain tissue from blast wave encounters with the head. This study recorded direct pressure within the brains of male Sprague-Dawley rats during exposure to blast. The goal was to understand pressure wave dynamics through the brain. In addition, we optimized in vivo methods to ensure accurate measurement of intracranial pressure (ICP). Our results demonstrate that proper sealing techniques lead to a significant increase in ICP values, compared to the outside overpressure generated by the blast. Further, the values seem to have a direct relation to a rat's size and age: heavier, older rats had the highest ICP readings. These findings suggest that a global flexure of the skull by the transient shockwave is an important mechanism of pressure transmission inside the brain.

TH-A-18C-09: Ultra-Fast Monte Carlo Simulation for Cone Beam CT Imaging of Brain Trauma

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

Sisniega, A; Zbijewski, W; Stayman, J

Purpose: Application of cone-beam CT (CBCT) to low-contrast soft tissue imaging, such as in detection of traumatic brain injury, is challenged by high levels of scatter. A fast, accurate scatter correction method based on Monte Carlo (MC) estimation is developed for application in high-quality CBCT imaging of acute brain injury. Methods: The correction involves MC scatter estimation executed on an NVIDIA GTX 780 GPU (MC-GPU), with baseline simulation speed of ~1e7 photons/sec. MC-GPU is accelerated by a novel, GPU-optimized implementation of variance reduction (VR) techniques (forced detection and photon splitting). The number of simulated tracks and projections is reduced formore » additional speed-up. Residual noise is removed and the missing scatter projections are estimated via kernel smoothing (KS) in projection plane and across gantry angles. The method is assessed using CBCT images of a head phantom presenting a realistic simulation of fresh intracranial hemorrhage (100 kVp, 180 mAs, 720 projections, source-detector distance 700 mm, source-axis distance 480 mm). Results: For a fixed run-time of ~1 sec/projection, GPU-optimized VR reduces the noise in MC-GPU scatter estimates by a factor of 4. For scatter correction, MC-GPU with VR is executed with 4-fold angular downsampling and 1e5 photons/projection, yielding 3.5 minute run-time per scan, and de-noised with optimized KS. Corrected CBCT images demonstrate uniformity improvement of 18 HU and contrast improvement of 26 HU compared to no correction, and a 52% increase in contrast-tonoise ratio in simulated hemorrhage compared to “oracle” constant fraction correction. Conclusion: Acceleration of MC-GPU achieved through GPU-optimized variance reduction and kernel smoothing yields an efficient (<5 min/scan) and accurate scatter correction that does not rely on additional hardware or simplifying assumptions about the scatter distribution. The method is undergoing implementation in a novel CBCT dedicated to brain trauma imaging at the point of care in sports and military applications. Research grant from Carestream Health. JY is an employee of Carestream Health.« less

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

PubMed

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

2013-01-01

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

Phosphatidylcholine supplementation in pregnant women consuming moderate-choline diets does not enhance infant cognitive function: a randomized, double-blind, placebo-controlled trial123

PubMed Central

Goldman, Barbara Davis; Fischer, Leslie M; da Costa, Kerry-Ann; Reznick, J Steven; Zeisel, Steven H

2012-01-01

Background: Choline is essential for fetal brain development, and it is not known whether a typical American diet contains enough choline to ensure optimal brain development. Objective: The study was undertaken to determine whether supplementing pregnant women with phosphatidylcholine (the main dietary source of choline) improves the cognitive abilities of their offspring. Design: In a double-blind, randomized controlled trial, 140 pregnant women were randomly assigned to receive supplemental phosphatidylcholine (750 mg) or a placebo (corn oil) from 18 wk gestation through 90 d postpartum. Their infants (n = 99) were tested for short-term visuospatial memory, long-term episodic memory, language development, and global development at 10 and 12 mo of age. Results: The women studied ate diets that delivered ∼360 mg choline/d in foods (∼80% of the recommended intake for pregnant women, 65% of the recommended intake for lactating women). The phosphatidylcholine supplements were well tolerated. Groups did not differ significantly in global development, language development, short-term visuospatial memory, or long-term episodic memory. Conclusions: Phosphatidylcholine supplementation of pregnant women eating diets containing moderate amounts of choline did not enhance their infants’ brain function. It is possible that a longer follow-up period would reveal late-emerging effects. Moreover, future studies should determine whether supplementing mothers eating diets much lower in choline content, such as those consumed in several low-income countries, would enhance infant brain development. This trial was registered at clinicaltrials.gov as NCT00678925. PMID:23134891

A Well Designed School Environment Facilitates Brain Learning.

ERIC Educational Resources Information Center

Chan, Tak Cheung; Petrie, Garth

2000-01-01

Examines how school design facilitates learning by complementing how the brain learns. How the brain learns is discussed and how an artistic environment, spaciousness in the learning areas, color and lighting, and optimal thermal and acoustical environments aid student learning. School design suggestions conclude the article. (GR)

Traumatic Brain Injury Inpatient Rehabilitation

ERIC Educational Resources Information Center

Im, Brian; Schrer, Marcia J.; Gaeta, Raphael; Elias, Eileen

2010-01-01

Traumatic brain injuries (TBI) can cause multiple medical and functional problems. As the brain is involved in regulating nearly every bodily function, a TBI can affect any part of the body and aspect of cognitive, behavioral, and physical functioning. However, TBI affects each individual differently. Optimal management requires understanding the…

A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

PubMed

Lu, Siyuan; Qiu, Xin; Shi, Jianping; Li, Na; Lu, Zhi-Hai; Chen, Peng; Yang, Meng-Meng; Liu, Fang-Yuan; Jia, Wen-Juan; Zhang, Yudong

2017-01-01

It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magnetic resonance (MR) imaging is the most suitable for brain, and it is now widely applied in hospitals, because it is helpful in the four ways of diagnosis, prognosis, pre-surgical, and postsurgical procedures. There are automatic detection methods; however they suffer from low accuracy. Therefore, we proposed a novel approach which employed 2D discrete wavelet transform (DWT), and calculated the entropies of the subbands as features. Then, a bat algorithm optimized extreme learning machine (BA-ELM) was trained to identify pathological brains from healthy controls. A 10x10-fold cross validation was performed to evaluate the out-of-sample performance. The method achieved a sensitivity of 99.04%, a specificity of 93.89%, and an overall accuracy of 98.33% over 132 MR brain images. The experimental results suggest that the proposed approach is accurate and robust in pathological brain detection. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Riemannian Metric Optimization on Surfaces (RMOS) for Intrinsic Brain Mapping in the Laplace-Beltrami Embedding Space

PubMed Central

Gahm, Jin Kyu; Shi, Yonggang

2018-01-01

Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer’s disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. PMID:29574399

Physical activity as a model for health neuroscience.

PubMed

Stillman, Chelsea M; Erickson, Kirk I

2018-05-06

Health neuroscience is a new interdisciplinary field that combines theories and techniques from health psychology and cognitive and social-affective neuroscience in order to understand how the brain affects and is affected by health behaviors. Physical activity (PA) research can serve as a useful model for various ways in which the brain can be incorporated into health neuroscience studies to better understand variability in the adoption and maintenance of, as well as benefits gained from, health behaviors. Here, we summarize evidence linking PA to brain and cognitive performance from studies conceptualizing the brain as either an outcome or mediator of cognitive change. We then discuss an emerging body of studies using a brain as a predictor approach. We discuss how studies using this approach complement existing PA studies and provide insight into a major source of variability in the outcomes of PA interventions, above and beyond the variability accounted for by known biological and demographic moderators. A more complete understanding of the bidirectional relationships between brain and behaviors, such as PA, could provide valuable insight into how to tailor interventions to optimally affect individuals, identify key barriers, and inform the development of novel policies to promote public health. © 2018 New York Academy of Sciences.

Automatic Incubator-type Temperature Control System for Brain Hypothermia Treatment

NASA Astrophysics Data System (ADS)

Gaohua, Lu; Wakamatsu, Hidetoshi

An automatic air-cooling incubator is proposed to replace the manual water-cooling blanket to control the brain tissue temperature for brain hypothermia treatment. Its feasibility is theoretically discussed as follows: First, an adult patient with the cooling incubator is modeled as a linear dynamical patient-incubator biothermal system. The patient is represented by an 18-compartment structure and described by its state equations. The air-cooling incubator provides almost same cooling effect as the water-cooling blanket, if a light breeze of speed around 3 m/s is circulated in the incubator. Then, in order to control the brain temperature automatically, an adaptive-optimal control algorithm is adopted, while the patient-blanket therapeutic system is considered as a reference model. Finally, the brain temperature of the patient-incubator biothermal system is controlled to follow up the given reference temperature course, in which an adaptive algorithm is confirmed useful for unknown environmental change and/or metabolic rate change of the patient in the incubating system. Thus, the present work ensures the development of the automatic air-cooling incubator for a better temperature regulation of the brain hypothermia treatment in ICU.

Current approaches to the treatment of metastatic brain tumours

PubMed Central

Owonikoko, Taofeek K.; Arbiser, Jack; Zelnak, Amelia; Shu, Hui-Kuo G.; Shim, Hyunsuk; Robin, Adam M.; Kalkanis, Steven N.; Whitsett, Timothy G.; Salhia, Bodour; Tran, Nhan L.; Ryken, Timothy; Moore, Michael K.; Egan, Kathleen M.; Olson, Jeffrey J.

2014-01-01

Metastatic tumours involving the brain overshadow primary brain neoplasms in frequency and are an important complication in the overall management of many cancers. Importantly, advances are being made in understanding the molecular biology underlying the initial development and eventual proliferation of brain metastases. Surgery and radiation remain the cornerstones of the therapy for symptomatic lesions; however, image-based guidance is improving surgical technique to maximize the preservation of normal tissue, while more sophisticated approaches to radiation therapy are being used to minimize the long-standing concerns over the toxicity of whole-brain radiation protocols used in the past. Furthermore, the burgeoning knowledge of tumour biology has facilitated the entry of systemically administered therapies into the clinic. Responses to these targeted interventions have ranged from substantial toxicity with no control of disease to periods of useful tumour control with no decrement in performance status of the treated individual. This experience enables recognition of the limits of targeted therapy, but has also informed methods to optimize this approach. This Review focuses on the clinically relevant molecular biology of brain metastases, and summarizes the current applications of these data to imaging, surgery, radiation therapy, cytotoxic chemotherapy and targeted therapy. PMID:24569448

WINCS Harmoni: Closed-loop dynamic neurochemical control of therapeutic interventions

NASA Astrophysics Data System (ADS)

Lee, Kendall H.; Lujan, J. Luis; Trevathan, James K.; Ross, Erika K.; Bartoletta, John J.; Park, Hyung Ook; Paek, Seungleal Brian; Nicolai, Evan N.; Lee, Jannifer H.; Min, Hoon-Ki; Kimble, Christopher J.; Blaha, Charles D.; Bennet, Kevin E.

2017-04-01

There has been significant progress in understanding the role of neurotransmitters in normal and pathologic brain function. However, preclinical trials aimed at improving therapeutic interventions do not take advantage of real-time in vivo neurochemical changes in dynamic brain processes such as disease progression and response to pharmacologic, cognitive, behavioral, and neuromodulation therapies. This is due in part to a lack of flexible research tools that allow in vivo measurement of the dynamic changes in brain chemistry. Here, we present a research platform, WINCS Harmoni, which can measure in vivo neurochemical activity simultaneously across multiple anatomical targets to study normal and pathologic brain function. In addition, WINCS Harmoni can provide real-time neurochemical feedback for closed-loop control of neurochemical levels via its synchronized stimulation and neurochemical sensing capabilities. We demonstrate these and other key features of this platform in non-human primate, swine, and rodent models of deep brain stimulation (DBS). Ultimately, systems like the one described here will improve our understanding of the dynamics of brain physiology in the context of neurologic disease and therapeutic interventions, which may lead to the development of precision medicine and personalized therapies for optimal therapeutic efficacy.

Optimizing Experimental Design for Comparing Models of Brain Function

PubMed Central

Daunizeau, Jean; Preuschoff, Kerstin; Friston, Karl; Stephan, Klaas

2011-01-01

This article presents the first attempt to formalize the optimization of experimental design with the aim of comparing models of brain function based on neuroimaging data. We demonstrate our approach in the context of Dynamic Causal Modelling (DCM), which relates experimental manipulations to observed network dynamics (via hidden neuronal states) and provides an inference framework for selecting among candidate models. Here, we show how to optimize the sensitivity of model selection by choosing among experimental designs according to their respective model selection accuracy. Using Bayesian decision theory, we (i) derive the Laplace-Chernoff risk for model selection, (ii) disclose its relationship with classical design optimality criteria and (iii) assess its sensitivity to basic modelling assumptions. We then evaluate the approach when identifying brain networks using DCM. Monte-Carlo simulations and empirical analyses of fMRI data from a simple bimanual motor task in humans serve to demonstrate the relationship between network identification and the optimal experimental design. For example, we show that deciding whether there is a feedback connection requires shorter epoch durations, relative to asking whether there is experimentally induced change in a connection that is known to be present. Finally, we discuss limitations and potential extensions of this work. PMID:22125485

The effect of mannitol on intraoperative brain relaxation in patients undergoing supratentorial tumor surgery: study protocol for a randomized controlled trial

PubMed Central

2014-01-01

Background The risk of brain swelling after dural opening is high in patients with midline shift undergoing supratentorial tumor surgery. Brain swelling may result in increased intracranial pressure, impeded tumor exposure, and adverse outcomes. Mannitol is recommended as a first-line dehydration treatment to reduce brain edema and enable brain relaxation during neurosurgery. Research has indicated that mannitol enhanced brain relaxation in patients undergoing supratentorial tumor surgery; however, these results need further confirmation, and the optimal mannitol dose has not yet been established. We propose to examine whether different doses of 20% mannitol improve brain relaxation in a dose-dependent manner when administered at the time of incision. We will examine patients with preexisting mass effects and midline shift undergoing elective supratentorial brain tumor surgery. Methods This is a single-center, randomized controlled, parallel group trial that will be carried out at Beijing Tiantan Hospital, Capital Medical University. Randomization will be achieved using a computer-generated table. The study will include 220 patients undergoing supratentorial tumor surgery whose preoperative computed tomography/magnetic resonance imaging results indicate a brain midline shift. Patients in group A, group B, and group C will receive dehydration treatment at incision with 20% mannitol solutions of 0.7, 1.0, and 1.4 g/kg, respectively, at a rate of 600 mL/h. The patients in the control group will not receive mannitol. The primary outcome is an improvement in intraoperative brain relaxation and dura tension after dehydration with mannitol. Secondary outcomes are postoperative outcomes and the incidence of mannitol side effects. Discussion The aim of this study is to determine the optimal dose of 20% mannitol for intraoperative infusion. We will examine brain relaxation and outcome in patients undergoing supratentorial tumor surgery. If our results are positive, the study will indicate the optimal dose of mannitol to improve brain relaxation and avoid side effects during brain tumor surgery. Trial registration The study is registered with the registry website http://www.chictr.org with the registration number ChiCTRTRC13003984 (17 December 2013). PMID:24884731

ALL OUR SONS: THE DEVELOPMENTAL NEUROBIOLOGY AND NEUROENDOCRINOLOGY OF BOYS AT RISK.

PubMed

Schore, Allan N

2017-01-01

Why are boys at risk? To address this question, I use the perspective of regulation theory to offer a model of the deeper psychoneurobiological mechanisms that underlie the vulnerability of the developing male. The central thesis of this work dictates that significant gender differences are seen between male and female social and emotional functions in the earliest stages of development, and that these result from not only differences in sex hormones and social experiences but also in rates of male and female brain maturation, specifically in the early developing right brain. I present interdisciplinary research which indicates that the stress-regulating circuits of the male brain mature more slowly than those of the female in the prenatal, perinatal, and postnatal critical periods, and that this differential structural maturation is reflected in normal gender differences in right-brain attachment functions. Due to this maturational delay, developing males also are more vulnerable over a longer period of time to stressors in the social environment (attachment trauma) and toxins in the physical environment (endocrine disruptors) that negatively impact right-brain development. In terms of differences in gender-related psychopathology, I describe the early developmental neuroendocrinological and neurobiological mechanisms that are involved in the increased vulnerability of males to autism, early onset schizophrenia, attention deficit hyperactivity disorder, and conduct disorders as well as the epigenetic mechanisms that can account for the recent widespread increase of these disorders in U.S. culture. I also offer a clinical formulation of early assessments of boys at risk, discuss the impact of early childcare on male psychopathogenesis, and end with a neurobiological model of optimal adult male socioemotional functions. © 2017 Michigan Association for Infant Mental Health.

Using event-related potentials to study perinatal nutrition and brain development in infants of diabetic mothers.

PubMed

deRegnier, Raye-Ann; Long, Jeffrey D; Georgieff, Michael K; Nelson, Charles A

2007-01-01

Proper prenatal and postnatal nutrition is essential for optimal brain development and function. The early use of event-related potentials enables neuroscientists to study the development of cognitive function from birth and to evaluate the role of specific nutrients in development. Perinatal iron deficiency occurs in severely affected infants of diabetic mothers. In animal models, severe perinatal iron deficiency targets the explicit memory system of the brain. Cross-sectional ERP studies have shown that infants of diabetic mothers have impairments in recognition memory from birth through 8 months of age. The purpose of this study was to evaluate longitudinal development of recognition memory using ERPs in infants of diabetic mothers compared with control infants. Infants of diabetic mothers were divided into high and low risk status based upon their birth weights and iron status and compared with healthy control infants. Infants were tested in the newborn period for auditory recognition memory, at 6 months for visual recognition memory and at 8 months for cross modal memory. ERPs were evaluated for developmental changes in the slow waves that are thought to reflect memory and the Nc component that is thought to reflect attention. The results of the study showed differences in development between the IDMs and control infants in the development of the slow waves over the left anterior temporal leads and age-related patterns of development in the NC component. These results are consistent with animal models showing that perinatal iron deficiency affects the development of the memory networks of the brain. This study highlights the value of using ERPs to translate basic science information obtained from animal models to the development of the human infant.

Using Event-Related Potentials to Study Perinatal Nutrition and Brain Development in Infants of Diabetic Mothers

PubMed Central

deRegnier, Raye-Ann; Long, Jeffrey D.; Georgieff, Michael K.; Nelson, Charles A.

2009-01-01

Proper prenatal and postnatal nutrition is essential for optimal brain development and function. The early use of event-related potentials enables neuroscientists to study the development of cognitive function from birth and to evaluate the role of specific nutrients in development. Perinatal iron deficiency occurs in severely affected infants of diabetic mothers. In animal models, severe perinatal iron deficiency targets the explicit memory system of the brain. Cross-sectional ERP studies have shown that infants of diabetic mothers have impairments in recognition memory from birth through 8 months of age. The purpose of this study was to evaluate longitudinal development of recognition memory using ERPs in infants of diabetic mothers compared with control infants. Infants of diabetic mothers were divided into high and low risk status based upon their birthweights and iron status and compared with healthy control infants. Infants were tested in the newborn period for auditory recognition memory, at 6 months for visual recognition memory and at 8 months for cross modal memory. ERPs were evaluated for developmental changes in the slow waves that are thought to reflect memory and the Nc component that is thought to reflect attention. The results of the study showed differences in development between the IDMs and control infants in the development of the slow waves over the left anterior temporal leads and age-related patterns of development in the NC component. These results are consistent with animal models showing that perinatal iron deficiency affects the development of the memory networks of the brain. This study highlights the value of using ERPs to translate basic science information obtained from animal models to the development of the human infant. PMID:17559331

Graph theoretical analysis of complex networks in the brain

PubMed Central

Stam, Cornelis J; Reijneveld, Jaap C

2007-01-01

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning.

PubMed

Davatzikos, Christos

2016-10-01

The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. Copyright © 2016. Published by Elsevier B.V.

Soldier Health Habits and the Metabolically Optimized Brain.

PubMed

Friedl, Karl E; Breivik, Torbjorn J; Carter, Robert; Leyk, Dieter; Opstad, Per Kristian; Taverniers, John; Trousselard, Marion

2016-11-01

Human performance enhancement was the subject of a NATO workshop that considered the direct benefits of individual soldier health and fitness habits to brain health and performance. Some of the important health and fitness include physical activity and purposeful exercise, nutritional intake, sleep and rest behaviors, psychological outlook and mindfulness, and other physiologically based systemic challenges such as thermal exposure. These influences were considered in an integrated framework with insights contributed by each of five participating NATO member countries using representative research to highlight relevant interrelationships. Key conclusions are that (1) understanding the neurobiological bases and consequences of personal health behaviors is a priority for soldier performance research, and this also involves long-term brain health consequences to veterans and (2) health and fitness habits have been underappreciated as reliably effective performance enhancers and these should be preferred targets in the development of scientifically based recommendations for soldier brain health and performance. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Computational neuroanatomy using brain deformations: From brain parcellation to multivariate pattern analysis and machine learning

PubMed Central

Davatzikos, Christos

2017-01-01

The past 20 years have seen a mushrooming growth of the field of computational neuroanatomy. Much of this work has been enabled by the development and refinement of powerful, high-dimensional image warping methods, which have enabled detailed brain parcellation, voxel-based morphometric analyses, and multivariate pattern analyses using machine learning approaches. The evolution of these 3 types of analyses over the years has overcome many challenges. We present the evolution of our work in these 3 directions, which largely follows the evolution of this field. We discuss the progression from single-atlas, single-registration brain parcellation work to current ensemble-based parcellation; from relatively basic mass-univariate t-tests to optimized regional pattern analyses combining deformations and residuals; and from basic application of support vector machines to generative-discriminative formulations of multivariate pattern analyses, and to methods dealing with heterogeneity of neuroanatomical patterns. We conclude with discussion of some of the future directions and challenges. PMID:27514582

Semi-automatic segmentation of brain tumors using population and individual information.

PubMed

Wu, Yao; Yang, Wei; Jiang, Jun; Li, Shuanqian; Feng, Qianjin; Chen, Wufan

2013-08-01

Efficient segmentation of tumors in medical images is of great practical importance in early diagnosis and radiation plan. This paper proposes a novel semi-automatic segmentation method based on population and individual statistical information to segment brain tumors in magnetic resonance (MR) images. First, high-dimensional image features are extracted. Neighborhood components analysis is proposed to learn two optimal distance metrics, which contain population and patient-specific information, respectively. The probability of each pixel belonging to the foreground (tumor) and the background is estimated by the k-nearest neighborhood classifier under the learned optimal distance metrics. A cost function for segmentation is constructed through these probabilities and is optimized using graph cuts. Finally, some morphological operations are performed to improve the achieved segmentation results. Our dataset consists of 137 brain MR images, including 68 for training and 69 for testing. The proposed method overcomes segmentation difficulties caused by the uneven gray level distribution of the tumors and even can get satisfactory results if the tumors have fuzzy edges. Experimental results demonstrate that the proposed method is robust to brain tumor segmentation.

Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE).

PubMed

Zhu, Chengcheng; Tian, Bing; Chen, Luguang; Eisenmenger, Laura; Raithel, Esther; Forman, Christoph; Ahn, Sinyeob; Laub, Gerhard; Liu, Qi; Lu, Jianping; Liu, Jing; Hess, Christopher; Saloner, David

2018-06-01

Develop and optimize an accelerated, high-resolution (0.5 mm isotropic) 3D black blood MRI technique to reduce scan time for whole-brain intracranial vessel wall imaging. A 3D accelerated T 1 -weighted fast-spin-echo prototype sequence using compressed sensing (CS-SPACE) was developed at 3T. Both the acquisition [echo train length (ETL), under-sampling factor] and reconstruction parameters (regularization parameter, number of iterations) were first optimized in 5 healthy volunteers. Ten patients with a variety of intracranial vascular disease presentations (aneurysm, atherosclerosis, dissection, vasculitis) were imaged with SPACE and optimized CS-SPACE, pre and post Gd contrast. Lumen/wall area, wall-to-lumen contrast ratio (CR), enhancement ratio (ER), sharpness, and qualitative scores (1-4) by two radiologists were recorded. The optimized CS-SPACE protocol has ETL 60, 20% k-space under-sampling, 0.002 regularization factor with 20 iterations. In patient studies, CS-SPACE and conventional SPACE had comparable image scores both pre- (3.35 ± 0.85 vs. 3.54 ± 0.65, p = 0.13) and post-contrast (3.72 ± 0.58 vs. 3.53 ± 0.57, p = 0.15), but the CS-SPACE acquisition was 37% faster (6:48 vs. 10:50). CS-SPACE agreed with SPACE for lumen/wall area, ER measurements and sharpness, but marginally reduced the CR. In the evaluation of intracranial vascular disease, CS-SPACE provides a substantial reduction in scan time compared to conventional T 1 -weighted SPACE while maintaining good image quality.

Parallel updating and weighting of multiple spatial maps for visual stability during whole body motion

PubMed Central

Medendorp, W. P.

2015-01-01

It is known that the brain uses multiple reference frames to code spatial information, including eye-centered and body-centered frames. When we move our body in space, these internal representations are no longer in register with external space, unless they are actively updated. Whether the brain updates multiple spatial representations in parallel, or whether it restricts its updating mechanisms to a single reference frame from which other representations are constructed, remains an open question. We developed an optimal integration model to simulate the updating of visual space across body motion in multiple or single reference frames. To test this model, we designed an experiment in which participants had to remember the location of a briefly presented target while being translated sideways. The behavioral responses were in agreement with a model that uses a combination of eye- and body-centered representations, weighted according to the reliability in which the target location is stored and updated in each reference frame. Our findings suggest that the brain simultaneously updates multiple spatial representations across body motion. Because both representations are kept in sync, they can be optimally combined to provide a more precise estimate of visual locations in space than based on single-frame updating mechanisms. PMID:26490289

Fetal Therapy for Down Syndrome: Report of Three Cases and a Review of the Literature.

PubMed

Baggot, Patrick James; Baggot, Rocel Medina

2017-01-01

Down syndrome (trisomy 21) is a well-known cause of mental retardation. It can be diagnosed in early pregnancy. Scientists have made great strides in outlining the pathophysiologic mechanisms of mental retardation in Down syndrome. Much less has been published on human therapy. To our knowledge, these are the first published cases of fetal therapy for Down syndrome. Reports of three cases. In all cases, treatment was both biochemical (e.g. nutritional) and educational. In all cases, treatment was both before and after birth. All children lacked the characteristic faces usually seen in the children with Down syndrome. This suggests a treatment effect before birth. All children had better than expected development. Enhancement of development is proposed as a new therapeutic principle. Developing neurons exchange neurotrophic factors during development when they give or receive stimulation from other neurons. Neurons which receive neurotrophic stimulation survive, and those, which do not, are lost to apoptosis. The developmental therapeutic principle seeks to optimize brain development. Biochemical inputs (neurotransmitters, drugs, hormones, nutrients) and functional stimulation are integrated to optimize the growth and survival of neurons individually; other cells; subcellular organelles; and the brain as a whole. Treatment may be before and after birth, both biochemical and functional. These principles may be applied to Down syndrome, other conditions, and normal fetuses or children. Baggot PJ and Baggot RM (2014). Fetal Therapy for Down Syndrome: Report of three cases and review of the literature. J Am Phys Surg 19(1):20-24.

Formulation, Optimization, Characterization, and Pharmacokinetics of Progesterone Intravenous Lipid Emulsion for Traumatic Brain Injury Therapy.

PubMed

Zhao, Jin; Yuan, Quan; Cai, WeiHui; Sun, Pan; Ding, LiYan; Jin, Fang

2017-07-01

Traumatic brain injury (TBI) is a major cause of mortality and disability throughout the world. Progesterone (PROG) plays an important role in neurologic treatment. The aim of this study was to develop a progesterone formulation with good physical and chemical stability. Progesterone intravenous lipid emulsion (PILE) was prepared based on one-factor-at-a-time experiments and orthogonal design. The optimal PILE was evaluated for mean particle size, particle size distribution, zeta potential, morphology, pH, osmolarity, entrapment efficiency, storage stability, and pharmacokinetics in ICR mice compared with the commercial progesterone products. The droplets of PILE had the smallest possible diameters of 218.0 ± 1.8 nm and adequate zeta potential of -41.1 ± 0.9 mV. The volume percentage of droplets exceeding 5 μm (PFAT 5 ) of PILE was 0.003 ± 0.0015% and much less than the specified standard. The TEM imaging proved that emulsion droplets had a smooth spherical appearance. Chemically and physically stable PILE was obtained with excellent entrapment efficiency that was up to 95.23%, with suitable pH at 7.15 ± 0.01 and osmolarity at 301.3 ± 1.2 mOsmol/l. Storage stability tests indicated that the emulsion was stable long term under ambient temperature conditions. Animal studies demonstrated that the emulsion was more effective with the higher progesterone concentration in the brain compared with commercial products. Therefore, the optimized PILE would offer great promise as a means of progesterone delivery for TBI therapy.

Characterization of a Raman spectroscopy probe system for intraoperative brain tissue classification

PubMed Central

Desroches, Joannie; Jermyn, Michael; Mok, Kelvin; Lemieux-Leduc, Cédric; Mercier, Jeanne; St-Arnaud, Karl; Urmey, Kirk; Guiot, Marie-Christine; Marple, Eric; Petrecca, Kevin; Leblond, Frédéric

2015-01-01

A detailed characterization study is presented of a Raman spectroscopy system designed to maximize the volume of resected cancer tissue in glioma surgery based on in vivo molecular tissue characterization. It consists of a hand-held probe system measuring spectrally resolved inelastically scattered light interacting with tissue, designed and optimized for in vivo measurements. Factors such as linearity of the signal with integration time and laser power, and their impact on signal to noise ratio, are studied leading to optimal data acquisition parameters. The impact of ambient light sources in the operating room is assessed and recommendations made for optimal operating conditions. In vivo Raman spectra of normal brain, cancer and necrotic tissue were measured in 10 patients, demonstrating that real-time inelastic scattering measurements can distinguish necrosis from vital tissue (including tumor and normal brain tissue) with an accuracy of 87%, a sensitivity of 84% and a specificity of 89%. PMID:26203368

Self-organization, free energy minimization, and optimal grip on a field of affordances

PubMed Central

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system “brain-body-landscape of affordances.” Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients. PMID:25161615

Self-organization, free energy minimization, and optimal grip on a field of affordances.

PubMed

Bruineberg, Jelle; Rietveld, Erik

2014-01-01

In this paper, we set out to develop a theoretical and conceptual framework for the new field of Radical Embodied Cognitive Neuroscience. This framework should be able to integrate insights from several relevant disciplines: theory on embodied cognition, ecological psychology, phenomenology, dynamical systems theory, and neurodynamics. We suggest that the main task of Radical Embodied Cognitive Neuroscience is to investigate the phenomenon of skilled intentionality from the perspective of the self-organization of the brain-body-environment system, while doing justice to the phenomenology of skilled action. In previous work, we have characterized skilled intentionality as the organism's tendency toward an optimal grip on multiple relevant affordances simultaneously. Affordances are possibilities for action provided by the environment. In the first part of this paper, we introduce the notion of skilled intentionality and the phenomenon of responsiveness to a field of relevant affordances. Second, we use Friston's work on neurodynamics, but embed a very minimal version of his Free Energy Principle in the ecological niche of the animal. Thus amended, this principle is helpful for understanding the embeddedness of neurodynamics within the dynamics of the system "brain-body-landscape of affordances." Next, we show how we can use this adjusted principle to understand the neurodynamics of selective openness to the environment: interacting action-readiness patterns at multiple timescales contribute to the organism's selective openness to relevant affordances. In the final part of the paper, we emphasize the important role of metastable dynamics in both the brain and the brain-body-environment system for adequate affordance-responsiveness. We exemplify our integrative approach by presenting research on the impact of Deep Brain Stimulation on affordance responsiveness of OCD patients.

Pilot study assessing the feasibility of applying bilateral subthalamic nucleus deep brain stimulation in very early stage Parkinson's disease: study design and rationale.

PubMed

Charles, David; Tolleson, Christopher; Davis, Thomas L; Gill, Chandler E; Molinari, Anna L; Bliton, Mark J; Tramontana, Michael G; Salomon, Ronald M; Kao, Chris; Wang, Lily; Hedera, Peter; Phibbs, Fenna T; Neimat, Joseph S; Konrad, Peter E

2012-01-01

Deep brain stimulation provides significant symptomatic benefit for people with advanced Parkinson's disease whose symptoms are no longer adequately controlled with medication. Preliminary evidence suggests that subthalamic nucleus stimulation may also be efficacious in early Parkinson's disease, and results of animal studies suggest that it may spare dopaminergic neurons in the substantia nigra. We report the methodology and design of a novel Phase I clinical trial testing the safety and tolerability of deep brain stimulation in early Parkinson's disease and discuss previous failed attempts at neuroprotection. We recently conducted a prospective, randomized, parallel-group, single-blind pilot clinical trial of deep brain stimulation in early Parkinson's disease. Subjects were randomized to receive either optimal drug therapy or deep brain stimulation plus optimal drug therapy. Follow-up visits occurred every six months for a period of two years and included week-long therapy washouts. Thirty subjects with Hoehn & Yahr Stage II idiopathic Parkinson's disease were enrolled over a period of 32 months. Twenty-nine subjects completed all follow-up visits; one patient in the optimal drug therapy group withdrew from the study after baseline. Baseline characteristics for all thirty patients were not significantly different. This study demonstrates that it is possible to recruit and retain subjects in a clinical trial testing deep brain stimulation in early Parkinson's disease. The results of this trial will be used to support the design of a Phase III, multicenter trial investigating the efficacy of deep brain stimulation in early Parkinson's disease.

Pilot Study Assessing the Feasibility of Applying Bilateral Subthalamic Nucleus Deep Brain Stimulation in Very Early Stage Parkinson's Disease: Study design and rationale

PubMed Central

Charles, David; Tolleson, Christopher; Davis, Thomas L.; Gill, Chandler E.; Molinari, Anna L.; Bliton, Mark J.; Tramontana, Michael G.; Salomon, Ronald M.; Kao, Chris; Wang, Lily; Hedera, Peter; Phibbs, Fenna T.; Neimat, Joseph S.; Konrad, Peter E.

2014-01-01

Background Deep brain stimulation provides significant symptomatic benefit for people with advanced Parkinson's disease whose symptoms are no longer adequately controlled with medication. Preliminary evidence suggests that subthalamic nucleus stimulation may also be efficacious in early Parkinson's disease, and results of animal studies suggest that it may spare dopaminergic neurons in the substantia nigra. Objective We report the methodology and design of a novel Phase I clinical trial testing the safety and tolerability of deep brain stimulation in early Parkinson's disease and discuss previous failed attempts at neuroprotection. Methods We recently conducted a prospective, randomized, parallel-group, single-blind pilot clinical trial of deep brain stimulation in early Parkinson's disease. Subjects were randomized to receive either optimal drug therapy or deep brain stimulation plus optimal drug therapy. Follow-up visits occurred every six months for a period of two years and included week-long therapy washouts. Results Thirty subjects with Hoehn & Yahr Stage II idiopathic Parkinson's disease were enrolled over a period of 32 months. Twenty-nine subjects completed all follow-up visits; one patient in the optimal drug therapy group withdrew from the study after baseline. Baseline characteristics for all thirty patients were not significantly different. Conclusions This study demonstrates that it is possible to recruit and retain subjects in a clinical trial testing deep brain stimulation in early Parkinson's disease. The results of this trial will be used to support the design of a Phase III, multicenter trial investigating the efficacy of deep brain stimulation in early Parkinson's disease. PMID:23938229

Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration

PubMed Central

Cole, Michael W.

2016-01-01

The human brain is able to exceed modern computers on multiple computational demands (e.g., language, planning) using a small fraction of the energy. The mystery of how the brain can be so efficient is compounded by recent evidence that all brain regions are constantly active as they interact in so-called resting-state networks (RSNs). To investigate the brain's ability to process complex cognitive demands efficiently, we compared functional connectivity (FC) during rest and multiple highly distinct tasks. We found previously that RSNs are present during a wide variety of tasks and that tasks only minimally modify FC patterns throughout the brain. Here, we tested the hypothesis that, although subtle, these task-evoked FC updates from rest nonetheless contribute strongly to behavioral performance. One might expect that larger changes in FC reflect optimization of networks for the task at hand, improving behavioral performance. Alternatively, smaller changes in FC could reflect optimization for efficient (i.e., small) network updates, reducing processing demands to improve behavioral performance. We found across three task domains that high-performing individuals exhibited more efficient brain connectivity updates in the form of smaller changes in functional network architecture between rest and task. These smaller changes suggest that individuals with an optimized intrinsic network configuration for domain-general task performance experience more efficient network updates generally. Confirming this, network update efficiency correlated with general intelligence. The brain's reconfiguration efficiency therefore appears to be a key feature contributing to both its network dynamics and general cognitive ability. SIGNIFICANCE STATEMENT The brain's network configuration varies based on current task demands. For example, functional brain connections are organized in one way when one is resting quietly but in another way if one is asked to make a decision. We found that the efficiency of these updates in brain network organization is positively related to general intelligence, the ability to perform a wide variety of cognitively challenging tasks well. Specifically, we found that brain network configuration at rest was already closer to a wide variety of task configurations in intelligent individuals. This suggests that the ability to modify network connectivity efficiently when task demands change is a hallmark of high intelligence. PMID:27535904

Understanding Optimal Decision-Making in Wargaming III

DTIC Science & Technology

2015-10-01

attention - deficit / hyperactivity disorder assessed by the Keio version of the Wisconsin card sorting test. Brain and Development, 34(5), 354-359...immediate feedback regarding friendly, enemy, and total damage. In addition to latency response (LR), attention to feedback also was measured by...measures can detect poor attention allocation. This material is based upon work supported in part by the Army Research Office (62626- NS). The

The development and investigation of a prototype three-dimensional compensator for whole brain radiation therapy

NASA Astrophysics Data System (ADS)

Keall, Paul; Arief, Isti; Shamas, Sofia; Weiss, Elisabeth; Castle, Steven

2008-05-01

Whole brain radiation therapy (WBRT) is the standard treatment for patients with brain metastases, and is often used in conjunction with stereotactic radiotherapy for patients with a limited number of brain metastases, as well as prophylactic cranial irradiation. The use of open fields (conventionally used for WBRT) leads to higher doses to the brain periphery if dose is prescribed to the brain center at the largest lateral radius. These dose variations potentially compromise treatment efficacy and translate to increased side effects. The goal of this research was to design and construct a 3D 'brain wedge' to compensate dose heterogeneities in WBRT. Radiation transport theory was invoked to calculate the desired shape of a wedge to achieve a uniform dose distribution at the sagittal plane for an ellipsoid irradiated medium. The calculations yielded a smooth 3D wedge design to account for the missing tissue at the peripheral areas of the brain. A wedge was machined based on the calculation results. Three ellipsoid phantoms, spanning the mean and ± two standard deviations from the mean cranial dimensions were constructed, representing 95% of the adult population. Film was placed at the sagittal plane for each of the three phantoms and irradiated with 6 MV photons, with the wedge in place. Sagittal plane isodose plots for the three phantoms demonstrated the feasibility of this wedge to create a homogeneous distribution with similar results observed for the three phantom sizes, indicating that a single wedge may be sufficient to cover 95% of the adult population. The sagittal dose is a reasonable estimate of the off-axis dose for whole brain radiation therapy. Comparing the dose with and without the wedge the average minimum dose was higher (90% versus 86%), the maximum dose was lower (107% versus 113%) and the dose variation was lower (one standard deviation 2.7% versus 4.6%). In summary, a simple and effective 3D wedge for whole brain radiotherapy has been developed. The wedge gives a more uniform dose distribution than commonly used techniques. Further development and shape optimization may be necessary prior to clinical implementation.

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

Beltran, C; Kamal, H

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatmentmore » planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.« less

Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays

PubMed Central

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-01-01

Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts. PMID:28068291

Particle swarm optimization for programming deep brain stimulation arrays

NASA Astrophysics Data System (ADS)

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-02-01

Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Lighting up the brain: genetically encoded fluorescent sensors for imaging neurotransmitters and neuromodulators.

PubMed

Wang, Huan; Jing, Miao; Li, Yulong

2018-06-01

Measuring the precise dynamics of specific neurotransmitters and neuromodulators in the brain is essential for understanding how information is transmitted and processed. Thanks to the development and optimization of various genetically encoded sensors, we are approaching the stage in which a few key neurotransmitters/neuromodulators can be imaged with high cell specificity and good signal-to-noise ratio. Here, we summarize recent progress regarding these sensors, focusing on their design principles, properties, potential applications, and current limitations. We also highlight the G protein-coupled receptor (GPCR) scaffold as a promising platform that may enable the scalable development of the next generation of sensors, enabling the rapid, sensitive, and specific detection of a large repertoire of neurotransmitters/neuromodulators in vivo at cellular or even subcellular resolution. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of image and information management system for Korean standard brain

NASA Astrophysics Data System (ADS)

Chung, Soon Cheol; Choi, Do Young; Tack, Gye Rae; Sohn, Jin Hun

2004-04-01

The purpose of this study is to establish a reference for image acquisition for completing a standard brain for diverse Korean population, and to develop database management system that saves and manages acquired brain images and personal information of subjects. 3D MP-RAGE (Magnetization Prepared Rapid Gradient Echo) technique which has excellent Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) as well as reduces image acquisition time was selected for anatomical image acquisition, and parameter values were obtained for the optimal image acquisition. Using these standards, image data of 121 young adults (early twenties) were obtained and stored in the system. System was designed to obtain, save, and manage not only anatomical image data but also subjects' basic demographic factors, medical history, handedness inventory, state-trait anxiety inventory, A-type personality inventory, self-assessment depression inventory, mini-mental state examination, intelligence test, and results of personality test via a survey questionnaire. Additionally this system was designed to have functions of saving, inserting, deleting, searching, and printing image data and personal information of subjects, and to have accessibility to them as well as automatic connection setup with ODBC. This newly developed system may have major contribution to the completion of a standard brain for diverse Korean population since it can save and manage their image data and personal information.

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

PubMed

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 in the future.

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

PubMed Central

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

2017-01-01

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 in the future. PMID:28167896

Spontaneous cortical activity reveals hallmarks of an optimal internal model of the environment.

PubMed

Berkes, Pietro; Orbán, Gergo; Lengyel, Máté; Fiser, József

2011-01-07

The brain maintains internal models of its environment to interpret sensory inputs and to prepare actions. Although behavioral studies have demonstrated that these internal models are optimally adapted to the statistics of the environment, the neural underpinning of this adaptation is unknown. Using a Bayesian model of sensory cortical processing, we related stimulus-evoked and spontaneous neural activities to inferences and prior expectations in an internal model and predicted that they should match if the model is statistically optimal. To test this prediction, we analyzed visual cortical activity of awake ferrets during development. Similarity between spontaneous and evoked activities increased with age and was specific to responses evoked by natural scenes. This demonstrates the progressive adaptation of internal models to the statistics of natural stimuli at the neural level.

Differential vulnerability to adverse nutritional conditions in male and female rats: Modulatory role of estradiol during development.

PubMed

Pinos, Helena; Carrillo, Beatriz; Díaz, Francisca; Chowen, Julie A; Collado, Paloma

2018-01-01

Many studies have shown the importance of an adequate nutritional environment during development to optimally establish the neurohormonal circuits that regulate feeding behavior. Under- or over-nutrition during early stages of life can lead to alterations in the physiology and brain networks that control food intake, resulting in a greater vulnerability to suffer maladjustments in energy metabolism in adulthood. These alterations produced by under- or over-nourishment during development differ between males and females, as does the modulatory action that estradiol exerts on the alterations produced by malnutrition. Estradiol regulates metabolism and brain metabolic circuits through the same transcription factor pathway, STAT3, that leptin and ghrelin use to program feeding circuits. Although more research is needed to disentangle the actual role of estradiol during development on the programming of feeding circuits, a synergistic role together with leptin and/or ghrelin might be hypothesized. Copyright © 2017 Elsevier Inc. All rights reserved.

Mission-based Scenario Research: Experimental Design And Analysis

DTIC Science & Technology

2012-01-01

neurotechnologies called Brain-Computer Interaction Technologies. 15. SUBJECT TERMS neuroimaging, EEG, task loading, neurotechnologies , ground... neurotechnologies called Brain-Computer Interaction Technologies. INTRODUCTION Imagine a system that can identify operator fatigue during a long-term...BCIT), a class of neurotechnologies , that aim to improve task performance by incorporating measures of brain activity to optimize the interactions

Boosting Your Baby's Brain Power

ERIC Educational Resources Information Center

Engel-Smothers, Holly; Heim, Susan M.

2009-01-01

With more than 100 billion neurons that would stretch more than 60,000 miles, a newborn baby's brain is quite phenomenal! These neurons must generally form connections within the first eight months of a baby's life to foster optimal brain growth and lifelong learning. Mommies, daddies, and caregivers are extremely vital to ensuring babies reach…

Childhood Brain and Spinal Cord Tumors Treatment Overview (PDQ®)—Health Professional Version

Cancer.gov

Treatment for children with brain and spinal cord tumors is based on histology and location within the brain. For most of these tumors, an optimal regimen has not been determined, and enrollment onto clinical trials is encouraged. Get detailed information about these tumors in this clinician summary.

Late-stage optimization of a tercyclic class of S1P3-sparing, S1P1 receptor agonists.

PubMed

Horan, Joshua C; Kuzmich, Daniel; Liu, Pingrong; DiSalvo, Darren; Lord, John; Mao, Can; Hopkins, Tamara D; Yu, Hui; Harcken, Christian; Betageri, Raj; Hill-Drzewi, Melissa; Patenaude, Lori; Patel, Monica; Fletcher, Kimberly; Terenzzio, Donna; Linehan, Brian; Xia, Heather; Patel, Mita; Studwell, Debbie; Miller, Craig; Hickey, Eugene; Levin, Jeremy I; Smith, Dustin; Kemper, Raymond A; Modis, Louise K; Bannen, Lynne C; Chan, Diva S; Mac, Morrison B; Ng, Stephanie; Wang, Yong; Xu, Wei; Lemieux, René M

2016-01-15

Poor solubility and cationic amphiphilic drug-likeness were liabilities identified for a lead series of S1P3-sparing, S1P1 agonists originally developed from a high-throughput screening campaign. This work describes the subsequent optimization of these leads by balancing potency, selectivity, solubility and overall molecular charge. Focused SAR studies revealed favorable structural modifications that, when combined, produced compounds with overall balanced profiles. The low brain exposure observed in rat suggests that these compounds would be best suited for the potential treatment of peripheral autoimmune disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

Preliminary pilot fMRI study of neuropostural optimization with a noninvasive asymmetric radioelectric brain stimulation protocol in functional dysmetria

PubMed Central

Mura, Marco; Castagna, Alessandro; Fontani, Vania; Rinaldi, Salvatore

2012-01-01

Purpose This study assessed changes in functional dysmetria (FD) and in brain activation observable by functional magnetic resonance imaging (fMRI) during a leg flexion-extension motor task following brain stimulation with a single radioelectric asymmetric conveyer (REAC) pulse, according to the precisely defined neuropostural optimization (NPO) protocol. Population and methods Ten healthy volunteers were assessed using fMRI conducted during a simple motor task before and immediately after delivery of a single REAC-NPO pulse. The motor task consisted of a flexion-extension movement of the legs with the knees bent. FD signs and brain activation patterns were compared before and after REAC-NPO. Results A single 250-millisecond REAC-NPO treatment alleviated FD, as evidenced by patellar asymmetry during a sit-up motion, and modulated activity patterns in the brain, particularly in the cerebellum, during the performance of the motor task. Conclusion Activity in brain areas involved in motor control and coordination, including the cerebellum, is altered by administration of a REAC-NPO treatment and this effect is accompanied by an alleviation of FD. PMID:22536071

Organotypic Slice Cultures for Studies of Postnatal Neurogenesis

PubMed Central

Mosa, Adam J.; Wang, Sabrina; Tan, Yao Fang; Wojtowicz, J. Martin

2015-01-01

Here we describe a technique for studying hippocampal postnatal neurogenesis in the rodent brain using the organotypic slice culture technique. This method maintains the characteristic topographical morphology of the hippocampus while allowing direct application of pharmacological agents to the developing hippocampal dentate gyrus. Additionally, slice cultures can be maintained for up to 4 weeks and thus, allow one to study the maturation process of newborn granule neurons. Slice cultures allow for efficient pharmacological manipulation of hippocampal slices while excluding complex variables such as uncertainties related to the deep anatomic location of the hippocampus as well as the blood brain barrier. For these reasons, we sought to optimize organotypic slice cultures specifically for postnatal neurogenesis research. PMID:25867138

Timing reproduction in teleost fish: cues and mechanisms

PubMed Central

Juntti, Scott A; Fernald, Russell D

2016-01-01

Fish comprise half of extant vertebrate species and use a rich variety of reproductive strategies that have yielded insights into the basic mechanisms that evolved for sex. To maximize the chances of fertilization and survival of offspring, fish species time reproduction to occur at optimal times. For years, ethologists have performed painstaking experiments to identify sensory inputs and behavioral outputs of the brain during mating. Here we review known mechanisms that generate sexual behavior, focusing on the factors that govern the timing of these displays. The development of new technologies, including high-throughput sequencing and genome engineering, have the potential to provide novel insights into how the vertebrate brain consummates mating at the appropriate time. PMID:26952366

Multicriteria plan optimization in the hands of physicians: a pilot study in prostate cancer and brain tumors.

PubMed

Müller, Birgit S; Shih, Helen A; Efstathiou, Jason A; Bortfeld, Thomas; Craft, David

2017-11-06

The purpose of this study was to demonstrate the feasibility of physician driven planning in intensity modulated radiotherapy (IMRT) with a multicriteria optimization (MCO) treatment planning system and template based plan optimization. Exploiting the full planning potential of MCO navigation, this alternative planning approach intends to improve planning efficiency and individual plan quality. Planning was retrospectively performed on 12 brain tumor and 10 post-prostatectomy prostate patients previously treated with MCO-IMRT. For each patient, physicians were provided with a template-based generated Pareto surface of optimal plans to navigate, using the beam angles from the original clinical plans. We compared physician generated plans to clinically delivered plans (created by dosimetrists) in terms of dosimetric differences, physician preferences and planning times. Plan qualities were similar, however physician generated and clinical plans differed in the prioritization of clinical goals. Physician derived prostate plans showed significantly better sparing of the high dose rectum and bladder regions (p(D1) < 0.05; D1: dose received by 1% of the corresponding structure). Physicians' brain tumor plans indicated higher doses for targets and brainstem (p(D1) < 0.05). Within blinded plan comparisons physicians preferred the clinical plans more often (brain: 6:3 out of 12, prostate: 2:6 out of 10) (not statistically significant). While times of physician involvement were comparable for prostate planning, the new workflow reduced the average involved time for brain cases by 30%. Planner times were reduced for all cases. Subjective benefits, such as a better understanding of planning situations, were observed by clinicians through the insight into plan optimization and experiencing dosimetric trade-offs. We introduce physician driven planning with MCO for brain and prostate tumors as a feasible planning workflow. The proposed approach standardizes the planning process by utilizing site specific templates and integrates physicians more tightly into treatment planning. Physicians' navigated plan qualities were comparable to the clinical plans. Given the reduction of planning time of the planner and the equal or lower planning time of physicians, this approach has the potential to improve departmental efficiencies.

CUDA-based acceleration and BPN-assisted automation of bilateral filtering for brain MR image restoration.

PubMed

Chang, Herng-Hua; Chang, Yu-Ning

2017-04-01

Bilateral filters have been substantially exploited in numerous magnetic resonance (MR) image restoration applications for decades. Due to the deficiency of theoretical basis on the filter parameter setting, empirical manipulation with fixed values and noise variance-related adjustments has generally been employed. The outcome of these strategies is usually sensitive to the variation of the brain structures and not all the three parameter values are optimal. This article is in an attempt to investigate the optimal setting of the bilateral filter, from which an accelerated and automated restoration framework is developed. To reduce the computational burden of the bilateral filter, parallel computing with the graphics processing unit (GPU) architecture is first introduced. The NVIDIA Tesla K40c GPU with the compute unified device architecture (CUDA) functionality is specifically utilized to emphasize thread usages and memory resources. To correlate the filter parameters with image characteristics for automation, optimal image texture features are subsequently acquired based on the sequential forward floating selection (SFFS) scheme. Subsequently, the selected features are introduced into the back propagation network (BPN) model for filter parameter estimation. Finally, the k-fold cross validation method is adopted to evaluate the accuracy of the proposed filter parameter prediction framework. A wide variety of T1-weighted brain MR images with various scenarios of noise levels and anatomic structures were utilized to train and validate this new parameter decision system with CUDA-based bilateral filtering. For a common brain MR image volume of 256 × 256 × 256 pixels, the speed-up gain reached 284. Six optimal texture features were acquired and associated with the BPN to establish a "high accuracy" parameter prediction system, which achieved a mean absolute percentage error (MAPE) of 5.6%. Automatic restoration results on 2460 brain MR images received an average relative error in terms of peak signal-to-noise ratio (PSNR) less than 0.1%. In comparison with many state-of-the-art filters, the proposed automation framework with CUDA-based bilateral filtering provided more favorable results both quantitatively and qualitatively. Possessing unique characteristics and demonstrating exceptional performances, the proposed CUDA-based bilateral filter adequately removed random noise in multifarious brain MR images for further study in neurosciences and radiological sciences. It requires no prior knowledge of the noise variance and automatically restores MR images while preserving fine details. The strategy of exploiting the CUDA to accelerate the computation and incorporating texture features into the BPN to completely automate the bilateral filtering process is achievable and validated, from which the best performance is reached. © 2017 American Association of Physicists in Medicine.

Riemannian metric optimization on surfaces (RMOS) for intrinsic brain mapping in the Laplace-Beltrami embedding space.

PubMed

Gahm, Jin Kyu; Shi, Yonggang

2018-05-01

Surface mapping methods play an important role in various brain imaging studies from tracking the maturation of adolescent brains to mapping gray matter atrophy patterns in Alzheimer's disease. Popular surface mapping approaches based on spherical registration, however, have inherent numerical limitations when severe metric distortions are present during the spherical parameterization step. In this paper, we propose a novel computational framework for intrinsic surface mapping in the Laplace-Beltrami (LB) embedding space based on Riemannian metric optimization on surfaces (RMOS). Given a diffeomorphism between two surfaces, an isometry can be defined using the pullback metric, which in turn results in identical LB embeddings from the two surfaces. The proposed RMOS approach builds upon this mathematical foundation and achieves general feature-driven surface mapping in the LB embedding space by iteratively optimizing the Riemannian metric defined on the edges of triangular meshes. At the core of our framework is an optimization engine that converts an energy function for surface mapping into a distance measure in the LB embedding space, which can be effectively optimized using gradients of the LB eigen-system with respect to the Riemannian metrics. In the experimental results, we compare the RMOS algorithm with spherical registration using large-scale brain imaging data, and show that RMOS achieves superior performance in the prediction of hippocampal subfields and cortical gyral labels, and the holistic mapping of striatal surfaces for the construction of a striatal connectivity atlas from substantia nigra. Copyright © 2018 Elsevier B.V. All rights reserved.

A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.

PubMed

Zhou, Bangyan; Wu, Xiaopei; Lv, Zhao; Zhang, Lei; Guo, Xiaojin

2016-01-01

Independent component analysis (ICA) as a promising spatial filtering method can separate motor-related independent components (MRICs) from the multichannel electroencephalogram (EEG) signals. However, the unpredictable burst interferences may significantly degrade the performance of ICA-based brain-computer interface (BCI) system. In this study, we proposed a new algorithm frame to address this issue by combining the single-trial-based ICA filter with zero-training classifier. We developed a two-round data selection method to identify automatically the badly corrupted EEG trials in the training set. The "high quality" training trials were utilized to optimize the ICA filter. In addition, we proposed an accuracy-matrix method to locate the artifact data segments within a single trial and investigated which types of artifacts can influence the performance of the ICA-based MIBCIs. Twenty-six EEG datasets of three-class motor imagery were used to validate the proposed methods, and the classification accuracies were compared with that obtained by frequently used common spatial pattern (CSP) spatial filtering algorithm. The experimental results demonstrated that the proposed optimizing strategy could effectively improve the stability, practicality and classification performance of ICA-based MIBCI. The study revealed that rational use of ICA method may be crucial in building a practical ICA-based MIBCI system.

Systematic Optimization of Long Gradient Chromatography Mass Spectrometry for Deep Analysis of Brain Proteome

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

Wang, Hong; Yang, Yanling; Li, Yuxin

2015-02-06

Development of high resolution liquid chromatography (LC) is essential for improving the sensitivity and throughput of mass spectrometry (MS)-based proteomics. Here we present systematic optimization of a long gradient LC-MS/MS platform to enhance protein identification from a complex mixture. The platform employed an in-house fabricated, reverse phase column (100 μm x 150 cm) coupled with Q Exactive MS. The column was capable of achieving a peak capacity of approximately 700 in a 720 min gradient of 10-45% acetonitrile. The optimal loading level was about 6 micrograms of peptides, although the column allowed loading as many as 20 micrograms. Gas phasemore » fractionation of peptide ions further increased the number of peptide identification by ~10%. Moreover, the combination of basic pH LC pre-fractionation with the long gradient LC-MS/MS platform enabled the identification of 96,127 peptides and 10,544 proteins at 1% protein false discovery rate in a postmortem brain sample of Alzheimer’s disease. As deep RNA sequencing of the same specimen suggested that ~16,000 genes were expressed, current analysis covered more than 60% of the expressed proteome. Further improvement strategies of the LC/LC-MS/MS platform were also discussed.« less

Visual recognition and visually guided action after early bilateral lesion of occipital cortex: a behavioral study of a 4.6-year-old girl.

PubMed

Amicuzi, Ileana; Stortini, Massimo; Petrarca, Maurizio; Di Giulio, Paola; Di Rosa, Giuseppe; Fariello, Giuseppe; Longo, Daniela; Cannatà, Vittorio; Genovese, Elisabetta; Castelli, Enrico

2006-10-01

We report the case of a 4.6-year-old girl born pre-term with early bilateral occipital damage. It was revealed that the child had non-severely impaired basic visual abilities and ocular motility, a selective perceptual deficit of figure-ground segregation, impaired visual recognition and abnormal navigating through space. Even if the child's visual functioning was not optimal, this was the expression of adaptive anatomic and functional brain modifications that occurred following the early lesion. Anatomic brain structure was studied with anatomic MRI and Diffusor Tensor Imaging (DTI)-MRI. This behavioral study may provide an important contribution to understanding the impact of an early lesion of the visual system on the development of visual functions and on the immature brain's potential for reorganisation related to when the damage occurred.

Simple wavefront correction framework for two-photon microscopy of in-vivo brain

PubMed Central

Galwaduge, P. T.; Kim, S. H.; Grosberg, L. E.; Hillman, E. M. C.

2015-01-01

We present an easily implemented wavefront correction scheme that has been specifically designed for in-vivo brain imaging. The system can be implemented with a single liquid crystal spatial light modulator (LCSLM), which makes it compatible with existing patterned illumination setups, and provides measurable signal improvements even after a few seconds of optimization. The optimization scheme is signal-based and does not require exogenous guide-stars, repeated image acquisition or beam constraint. The unconstrained beam approach allows the use of Zernike functions for aberration correction and Hadamard functions for scattering correction. Low order corrections performed in mouse brain were found to be valid up to hundreds of microns away from the correction location. PMID:26309763

An image warping technique for rodent brain MRI-histology registration based on thin-plate splines with landmark optimization

NASA Astrophysics Data System (ADS)

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

2009-02-01

Coregistration of in vivo magnetic resonance imaging (MRI) with histology provides validation of disease biomarker and pathobiology studies. Although thin-plate splines are widely used in such image registration, point landmark selection is error prone and often time-consuming. We present a technique to optimize landmark selection for thin-plate splines and demonstrate its usefulness in warping rodent brain MRI to histological sections. In this technique, contours are drawn on the corresponding MRI slices and images of histological sections. The landmarks are extracted from the contours by equal spacing then optimized by minimizing a cost function consisting of the landmark displacement and contour curvature. The technique was validated using simulation data and brain MRI-histology coregistration in a murine model of HIV-1 encephalitis. Registration error was quantified by calculating target registration error (TRE). The TRE of approximately 8 pixels for 20-80 landmarks without optimization was stable at different landmark numbers. The optimized results were more accurate at low landmark numbers (TRE of approximately 2 pixels for 50 landmarks), while the accuracy decreased (TRE approximately 8 pixels for larger numbers of landmarks (70- 80). The results demonstrated that registration accuracy decreases with the increasing landmark numbers offering more confidence in MRI-histology registration using thin-plate splines.

SNR-optimized phase-sensitive dual-acquisition turbo spin echo imaging: a fast alternative to FLAIR.

PubMed

Lee, Hyunyeol; Park, Jaeseok

2013-07-01

Phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo imaging was recently introduced, producing high-resolution isotropic cerebrospinal fluid attenuated brain images without long inversion recovery preparation. Despite the advantages, the weighted-averaging-based technique suffers from noise amplification resulting from different levels of cerebrospinal fluid signal modulations over the two acquisitions. The purpose of this work is to develop a signal-to-noise ratio-optimized version of the phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo. Variable refocusing flip angles in the first acquisition are calculated using a three-step prescribed signal evolution while those in the second acquisition are calculated using a two-step pseudo-steady state signal transition with a high flip-angle pseudo-steady state at a later portion of the echo train, balancing the levels of cerebrospinal fluid signals in both the acquisitions. Low spatial frequency signals are sampled during the high flip-angle pseudo-steady state to further suppress noise. Numerical simulations of the Bloch equations were performed to evaluate signal evolutions of brain tissues along the echo train and optimize imaging parameters. In vivo studies demonstrate that compared with conventional phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo, the proposed optimization yields 74% increase in apparent signal-to-noise ratio for gray matter and 32% decrease in imaging time. The proposed method can be a potential alternative to conventional fluid-attenuated imaging. Copyright © 2012 Wiley Periodicals, Inc.

Muscle coordination is habitual rather than optimal.

PubMed

de Rugy, Aymar; Loeb, Gerald E; Carroll, Timothy J

2012-05-23

When sharing load among multiple muscles, humans appear to select an optimal pattern of activation that minimizes costs such as the effort or variability of movement. How the nervous system achieves this behavior, however, is unknown. Here we show that contrary to predictions from optimal control theory, habitual muscle activation patterns are surprisingly robust to changes in limb biomechanics. We first developed a method to simulate joint forces in real time from electromyographic recordings of the wrist muscles. When the model was altered to simulate the effects of paralyzing a muscle, the subjects simply increased the recruitment of all muscles to accomplish the task, rather than recruiting only the useful muscles. When the model was altered to make the force output of one muscle unusually noisy, the subjects again persisted in recruiting all muscles rather than eliminating the noisy one. Such habitual coordination patterns were also unaffected by real modifications of biomechanics produced by selectively damaging a muscle without affecting sensory feedback. Subjects naturally use different patterns of muscle contraction to produce the same forces in different pronation-supination postures, but when the simulation was based on a posture different from the actual posture, the recruitment patterns tended to agree with the actual rather than the simulated posture. The results appear inconsistent with computation of motor programs by an optimal controller in the brain. Rather, the brain may learn and recall command programs that result in muscle coordination patterns generated by lower sensorimotor circuitry that are functionally "good-enough."

AAV viral vector delivery to the brain by shape-conforming MR-guided infusions.

PubMed

Bankiewicz, Krystof S; Sudhakar, Vivek; Samaranch, Lluis; San Sebastian, Waldy; Bringas, John; Forsayeth, John

2016-10-28

Gene transfer technology offers great promise as a potential therapeutic approach to the brain but has to be viewed as a very complex technology. Success of ongoing clinical gene therapy trials depends on many factors such as selection of the correct genetic and anatomical target in the brain. In addition, selection of the viral vector capable of transfer of therapeutic gene into target cells, along with long-term expression that avoids immunotoxicity has to be established. As with any drug development strategy, delivery of gene therapy has to be consistent and predictable in each study subject. Failed drug and vector delivery will lead to failed clinical trials. In this article, we describe our experience with AAV viral vector delivery system, that allows us to optimize and monitor in real time viral vector administration into affected regions of the brain. In addition to discussing MRI-guided technology for administration of AAV vectors we have developed and now employ in current clinical trials, we also describe ways in which infusion cannula design and stereotactic trajectory may be used to maximize the anatomical coverage by using fluid backflow. This innovative approach enables more precise coverage by fitting the shape of the infusion to the shape of the anatomical target. Copyright © 2016 Elsevier B.V. All rights reserved.

The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan.

PubMed

Moran, Rosalyn J; Symmonds, Mkael; Dolan, Raymond J; Friston, Karl J

2014-01-01

The aging brain shows a progressive loss of neuropil, which is accompanied by subtle changes in neuronal plasticity, sensory learning and memory. Neurophysiologically, aging attenuates evoked responses--including the mismatch negativity (MMN). This is accompanied by a shift in cortical responsivity from sensory (posterior) regions to executive (anterior) regions, which has been interpreted as a compensatory response for cognitive decline. Theoretical neurobiology offers a simpler explanation for all of these effects--from a Bayesian perspective, as the brain is progressively optimized to model its world, its complexity will decrease. A corollary of this complexity reduction is an attenuation of Bayesian updating or sensory learning. Here we confirmed this hypothesis using magnetoencephalographic recordings of the mismatch negativity elicited in a large cohort of human subjects, in their third to ninth decade. Employing dynamic causal modeling to assay the synaptic mechanisms underlying these non-invasive recordings, we found a selective age-related attenuation of synaptic connectivity changes that underpin rapid sensory learning. In contrast, baseline synaptic connectivity strengths were consistently strong over the decades. Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.

Multimodality Monitoring for Cerebral Perfusion Pressure Optimization in Comatose Patients with Intracerebral Hemorrhage

PubMed Central

Ko, Sang-Bae; Choi, H. Alex; Parikh, Gunjan; Helbok, Raimund; Schmidt, J. Michael; Lee, Kiwon; Badjatia, Neeraj; Claassen, Jan; Connolly, E. Sander; Mayer, Stephan A.

2011-01-01

Background and Purpose Limited data exists to recommend specific cerebral perfusion pressure (CPP) targets in patients with intracerebral hemorrhage (ICH). We sought to determine the feasibility of brain multimodality monitoring (MMM) for optimizing CPP and potentially reducing secondary brain injury after ICH. Methods We retrospectively analyzed brain MMM data targeted at perihematomal brain tissue in 18 comatose ICH patients (median monitoring: 164 hours). Physiological measures were averaged over one-hour intervals corresponding to each microdialysis sample. Metabolic crisis (MC) was defined as a lactate/pyruvate ratio (LPR) >40 with a brain glucose concentration <0.7 mmol/L. Brain tissue hypoxia (BTH) was defined as PbtO2 <15 mm Hg. Pressure reactivity index (PRx) and oxygen reactivity index (ORx) were calculated. Results Median age was 59 years, median GCS score 6, and median ICH volume was 37.5 ml. The risk of BTH, and to a lesser extent MC, increased with lower CPP values. Multivariable analyses showed that CPP <80 mm Hg was associated with a greater risk of BTH (OR 1.5, 95% CI 1.1–2.1, P=0.01) compared to CPP >100 mm Hg as a reference range. Six patients died (33%). Survivors had significantly higher CPP and PbtO2 and lower ICP values starting on post-bleed day 4, whereas LPR and PRx values were lower, indicating preservation of aerobic metabolism and pressure autoregulation. Conclusions PbtO2 monitoring can be used to identify CPP targets for optimal brain tissue oxygenation. In patients who do not undergo MMM, maintaining CPP >80 mm Hg may reduce the risk of BTH. PMID:21852615

Verification of intensity modulated radiation therapy beams using a tissue equivalent plastic scintillator dosimetry system

NASA Astrophysics Data System (ADS)

Petric, Martin Peter

This thesis describes the development and implementation of a novel method for the dosimetric verification of intensity modulated radiation therapy (IMRT) fields with several advantages over current techniques. Through the use of a tissue equivalent plastic scintillator sheet viewed by a charge-coupled device (CCD) camera, this method provides a truly tissue equivalent dosimetry system capable of efficiently and accurately performing field-by-field verification of IMRT plans. This work was motivated by an initial study comparing two IMRT treatment planning systems. The clinical functionality of BrainLAB's BrainSCAN and Varian's Helios IMRT treatment planning systems were compared in terms of implementation and commissioning, dose optimization, and plan assessment. Implementation and commissioning revealed differences in the beam data required to characterize the beam prior to use with the BrainSCAN system requiring higher resolution data compared to Helios. This difference was found to impact on the ability of the systems to accurately calculate dose for highly modulated fields, with BrainSCAN being more successful than Helios. The dose optimization and plan assessment comparisons revealed that while both systems use considerably different optimization algorithms and user-control interfaces, they are both capable of producing substantially equivalent dose plans. The extensive use of dosimetric verification techniques in the IMRT treatment planning comparison study motivated the development and implementation of a novel IMRT dosimetric verification system. The system consists of a water-filled phantom with a tissue equivalent plastic scintillator sheet built into the top surface. Scintillation light is reflected by a plastic mirror within the phantom towards a viewing window where it is captured using a CCD camera. Optical photon spread is removed using a micro-louvre optical collimator and by deconvolving a glare kernel from the raw images. Characterization of this new dosimetric verification system indicates excellent dose response and spatial linearity, high spatial resolution, and good signal uniformity and reproducibility. Dosimetric results from square fields, dynamic wedged fields, and a 7-field head and neck IMRT treatment plan indicate good agreement with film dosimetry distributions. Efficiency analysis of the system reveals a 50% reduction in time requirements for field-by-field verification of a 7-field IMRT treatment plan compared to film dosimetry.

Dynamic Granger-Geweke causality modeling with application to interictal spike propagation

PubMed Central

Lin, Fa-Hsuan; Hara, Keiko; Solo, Victor; Vangel, Mark; Belliveau, John W.; Stufflebeam, Steven M.; Hamalainen, Matti S.

2010-01-01

A persistent problem in developing plausible neurophysiological models of perception, cognition, and action is the difficulty of characterizing the interactions between different neural systems. Previous studies have approached this problem by estimating causal influences across brain areas activated during cognitive processing using Structural Equation Modeling and, more recently, with Granger-Geweke causality. While SEM is complicated by the need for a priori directional connectivity information, the temporal resolution of dynamic Granger-Geweke estimates is limited because the underlying autoregressive (AR) models assume stationarity over the period of analysis. We have developed a novel optimal method for obtaining data-driven directional causality estimates with high temporal resolution in both time and frequency domains. This is achieved by simultaneously optimizing the length of the analysis window and the chosen AR model order using the SURE criterion. Dynamic Granger-Geweke causality in time and frequency domains is subsequently calculated within a moving analysis window. We tested our algorithm by calculating the Granger-Geweke causality of epileptic spike propagation from the right frontal lobe to the left frontal lobe. The results quantitatively suggested the epileptic activity at the left frontal lobe was propagated from the right frontal lobe, in agreement with the clinical diagnosis. Our novel computational tool can be used to help elucidate complex directional interactions in the human brain. PMID:19378280

Role of neurotrophic factors in attention deficit hyperactivity disorder.

PubMed

Tsai, Shih-Jen

2017-04-01

Neurotrophins (NTs), a family of proteins including nerve growth factor, brain-derived neurotrophic factor (BDNF), neurotrophin-3, and neurotrophin-4, are essential for neural growth, survival, and differentiation, and are therefore crucial for brain development. Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by problems of inattention and/or hyperactivity-impulsivity. ADHD is one of the most common childhood onset psychiatric disorders. Studies have suggested that both genetic and environmental factors influence the development of the disorder, although the precise causes of ADHD have not yet been identified. In this review, we assess the role of NTs in the pathophysiology of ADHD. Preclinical evidence indicates that BDNF knockout mice are hyperactive, and an ADHD rodent model exhibited decreased cerebral BDNF levels. Several lines of evidence from clinical studies, including blood level and genetic studies, have suggested that NTs are involved in the pathogenesis of ADHD and in the mechanism of biological treatments for ADHD. Future directions for research are proposed, such as using blood NTs as ADHD biomarkers, optimizing NT genetic studies in ADHD, considering NTs as a link between ADHD and other comorbid mental disorders, and investigating methods for optimally modulating NT signaling to discover novel therapeutics for treating ADHD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal waist-to-hip ratios in women activate neural reward centers in men.

PubMed

Platek, Steven M; Singh, Devendra

2010-02-05

Secondary sexual characteristics convey information about reproductive potential. In the same way that facial symmetry and masculinity, and shoulder-to-hip ratio convey information about reproductive/genetic quality in males, waist-to-hip-ratio (WHR) is a phenotypic cue to fertility, fecundity, neurodevelopmental resources in offspring, and overall health, and is indicative of "good genes" in women. Here, using fMRI, we found that males show activation in brain reward centers in response to naked female bodies when surgically altered to express an optimal (approximately 0.7) WHR with redistributed body fat, but relatively unaffected body mass index (BMI). Relative to presurgical bodies, brain activation to postsurgical bodies was observed in bilateral orbital frontal cortex. While changes in BMI only revealed activation in visual brain substrates, changes in WHR revealed activation in the anterior cingulate cortex, an area associated with reward processing and decision-making. When regressing ratings of attractiveness on brain activation, we observed activation in forebrain substrates, notably the nucleus accumbens, a forebrain nucleus highly involved in reward processes. These findings suggest that an hourglass figure (i.e., an optimal WHR) activates brain centers that drive appetitive sociality/attention toward females that represent the highest-quality reproductive partners. This is the first description of a neural correlate implicating WHR as a putative honest biological signal of female reproductive viability and its effects on men's neurological processing.

Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain.

PubMed

Rivera-Alba, Marta; Vitaladevuni, Shiv N; Mishchenko, Yuriy; Mischenko, Yuriy; Lu, Zhiyuan; Takemura, Shin-Ya; Scheffer, Lou; Meinertzhagen, Ian A; Chklovskii, Dmitri B; de Polavieja, Gonzalo G

2011-12-06

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement. Copyright © 2011 Elsevier Ltd. All rights reserved.

Finite element simulations of the head-brain responses to the top impacts of a construction helmet: Effects of the neck and body mass.

PubMed

Wu, John Z; Pan, Christopher S; Wimer, Bryan M; Rosen, Charles L

2017-01-01

Traumatic brain injuries are among the most common severely disabling injuries in the United States. Construction helmets are considered essential personal protective equipment for reducing traumatic brain injury risks at work sites. In this study, we proposed a practical finite element modeling approach that would be suitable for engineers to optimize construction helmet design. The finite element model includes all essential anatomical structures of a human head (i.e. skin, scalp, skull, cerebrospinal fluid, brain, medulla, spinal cord, cervical vertebrae, and discs) and all major engineering components of a construction helmet (i.e. shell and suspension system). The head finite element model has been calibrated using the experimental data in the literature. It is technically difficult to precisely account for the effects of the neck and body mass on the dynamic responses, because the finite element model does not include the entire human body. An approximation approach has been developed to account for the effects of the neck and body mass on the dynamic responses of the head-brain. Using the proposed model, we have calculated the responses of the head-brain during a top impact when wearing a construction helmet. The proposed modeling approach would provide a tool to improve the helmet design on a biomechanical basis.

Labeling and tracking exosomes within the brain using gold nanoparticles

NASA Astrophysics Data System (ADS)

Betzer, Oshra; Perets, Nisim; Barnoy, Eran; Offen, Daniel; Popovtzer, Rachela

2018-02-01

Cell-to-cell communication system involves Exosomes, small, membrane-enveloped nanovesicles. Exosomes are evolving as effective therapeutic tools for different pathologies. These extracellular vesicles can bypass biological barriers such as the blood-brain barrier, and can function as powerful nanocarriers for drugs, proteins and gene therapeutics. However, to promote exosomes' therapy development, especially for brain pathologies, a better understanding of their mechanism of action, trafficking, pharmacokinetics and bio-distribution is needed. In this research, we established a new method for non-invasive in-vivo neuroimaging of mesenchymal stem cell (MSC)-derived exosomes, based on computed tomography (CT) imaging with glucose-coated gold nanoparticle (GNP) labeling. We demonstrated that the exosomes were efficiently and directly labeled with GNPs, via an energy-dependent mechanism. Additionally, we found the optimal parameters for exosome labeling and neuroimaging, wherein 5 nm GNPs enhanced labeling, and intranasal administration produced superior brain accumulation. We applied our technique in a mouse model of focal ischemia. Imaging and tracking of intranasally-administered GNP-labeled exosomes revealed specific accumulation and prolonged presence at the lesion area, up to 24 hrs. We propose that this novel exosome labeling and in-vivo neuroimaging technique can serve as a general platform for brain theranostics.

Whole brain myelin mapping using T1- and T2-weighted MR imaging data

PubMed Central

Ganzetti, Marco; Wenderoth, Nicole; Mantini, Dante

2014-01-01

Despite recent advancements in MR imaging, non-invasive mapping of myelin in the brain still remains an open issue. Here we attempted to provide a potential solution. Specifically, we developed a processing workflow based on T1-w and T2-w MR data to generate an optimized myelin enhanced contrast image. The workflow allows whole brain mapping using the T1-w/T2-w technique, which was originally introduced as a non-invasive method for assessing cortical myelin content. The hallmark of our approach is a retrospective calibration algorithm, applied to bias-corrected T1-w and T2-w images, that relies on image intensities outside the brain. This permits standardizing the intensity histogram of the ratio image, thereby allowing for across-subject statistical analyses. Quantitative comparisons of image histograms within and across different datasets confirmed the effectiveness of our normalization procedure. Not only did the calibrated T1-w/T2-w images exhibit a comparable intensity range, but also the shape of the intensity histograms was largely corresponding. We also assessed the reliability and specificity of the ratio image compared to other MR-based techniques, such as magnetization transfer ratio (MTR), fractional anisotropy (FA), and fluid-attenuated inversion recovery (FLAIR). With respect to these other techniques, T1-w/T2-w had consistently high values, as well as low inter-subject variability, in brain structures where myelin is most abundant. Overall, our results suggested that the T1-w/T2-w technique may be a valid tool supporting the non-invasive mapping of myelin in the brain. Therefore, it might find important applications in the study of brain development, aging and disease. PMID:25228871

Glycemic extremes in youth with T1DM: the structural and functional integrity of the developing brain.

PubMed

Arbelaez, Ana Maria; Semenkovich, Katherine; Hershey, Tamara

2013-12-01

The adult brain accounts for a disproportionally large percentage of the body’s total energy consumption (1). However, during brain development,energy demand is even higher, reaching the adult rate by age 2 and increasing to nearly twice the adult rate by age 10, followed by gradual reduction toward adult levels in the next decade (1,2). The dramatic changes in brain metabolism occurring over the first two decades of life coincide with the initial proliferation and then pruning of synapses to adult levels.The brain derives its energy almost exclusively from glucose and is largely driven by neuronal signaling, biosynthesis, and neuroprotection (3–6).Glucose homeostasis in the body is tightly regulated by a series of hormones and physiologic responses. As a result, hypoglycemia and hyperglycemia are rare occurrences in normal individuals, but they occur commonly inpatients with type 1 diabetes mellitus (T1DM) due to a dysfunction of peripheral glucose-insulin-glucagon responses and non-physiologic doses of exogenous insulin, which imperfectly mimic normal physiology. These extremes can occur more frequently in children and adolescents with T1DM due to the inadequacies of insulin replacement therapy, events leading to the diagnosis [prolonged untreated hyperglycemia and diabetic ketoacidosis (DKA)], and to behavioral factors interfering with optimal treatment. When faced with fluctuations in glucose supply the metabolism of the body and brain change dramatically, largely to conserve resources and, at a cost to other organs, to preserve brain function (7). However,if the normal physiological mechanisms that prevent these severe glucose fluctuations and maintain homeostasis are impaired, neuronal function and potentially viability can be affected (8–11).

Development of a novel niosomal system for oral delivery of Ginkgo biloba extract

PubMed Central

Jin, Ye; Wen, Jingyuan; Garg, Sanjay; Liu, Da; Zhou, Yulin; Teng, Lirong; Zhang, Weiyu

2013-01-01

Background The aim of this study was to develop an optimal niosomal system to deliver Ginkgo biloba extract (GbE) with improved oral bioavailability and to replace the conventional GbE tablets. Methods In this study, the film dispersion-homogenization method was used to prepare GbE niosomes. The resulting GbE niosome suspension was freeze-dried or spray-dried to improve the stability of the niosomes. GbE-loaded niosomes were formulated and characterized in terms of their morphology, particle size, zeta potential, entrapment efficiency, and angle of repose, and differential scanning calorimetry analysis was performed. In vitro release and in vivo distribution studies were also carried out. Results The particle size of the optimal delivery system prepared with Tween 80, Span 80, and cholesterol was about 141 nm. There was a significant difference (P < 0.05) in drug entrapment efficiency between the spray-drying method (about 77.5%) and the freeze-drying method (about 50.1%). The stability study revealed no significant change in drug entrapment efficiency for the GbE niosomes at 4°C and 25°C after 3 months. The in vitro release study suggested that GbE niosomes can prolong the release of flavonoid glycosides in phosphate-buffered solution (pH 6.8) for up to 48 hours. The in vivo distribution study showed that the flavonoid glycoside content in the heart, lung, kidney, brain, and blood of rats treated with the GbE niosome carrier system was greater than in the rats treated with the oral GbE tablet (P < 0.01). No flavonoid glycosides were detected in the brain tissue of rats given the oral GbE tablets, but they were detected in the brain tissue of rats given the GbE niosomes. Conclusion Niosomes are a promising oral system for delivery of GbE to the brain. PMID:23378764

Management of Brain Metastases in Tyrosine Kinase Inhibitor-Naïve Epidermal Growth Factor Receptor-Mutant Non-Small-Cell Lung Cancer: A Retrospective Multi-Institutional Analysis.

PubMed

Magnuson, William J; Lester-Coll, Nataniel H; Wu, Abraham J; Yang, T Jonathan; Lockney, Natalie A; Gerber, Naamit K; Beal, Kathryn; Amini, Arya; Patil, Tejas; Kavanagh, Brian D; Camidge, D Ross; Braunstein, Steven E; Boreta, Lauren C; Balasubramanian, Suresh K; Ahluwalia, Manmeet S; Rana, Niteshkumar G; Attia, Albert; Gettinger, Scott N; Contessa, Joseph N; Yu, James B; Chiang, Veronica L

2017-04-01

Purpose Stereotactic radiosurgery (SRS), whole-brain radiotherapy (WBRT), and epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are treatment options for brain metastases in patients with EGFR-mutant non-small-cell lung cancer (NSCLC). This multi-institutional analysis sought to determine the optimal management of patients with EGFR-mutant NSCLC who develop brain metastases and have not received EGFR-TKI. Materials and Methods A total of 351 patients from six institutions with EGFR-mutant NSCLC developed brain metastases and met inclusion criteria for the study. Exclusion criteria included prior EGFR-TKI use, EGFR-TKI resistance mutation, failure to receive EGFR-TKI after WBRT/SRS, or insufficient follow-up. Patients were treated with SRS followed by EGFR-TKI, WBRT followed by EGFR-TKI, or EGFR-TKI followed by SRS or WBRT at intracranial progression. Overall survival (OS) and intracranial progression-free survival were measured from the date of brain metastases. Results The median OS for the SRS (n = 100), WBRT (n = 120), and EGFR-TKI (n = 131) cohorts was 46, 30, and 25 months, respectively ( P < .001). On multivariable analysis, SRS versus EGFR-TKI, WBRT versus EGFR-TKI, age, performance status, EGFR exon 19 mutation, and absence of extracranial metastases were associated with improved OS. Although the SRS and EGFR-TKI cohorts shared similar prognostic features, the WBRT cohort was more likely to have a less favorable prognosis ( P = .001). Conclusion This multi-institutional analysis demonstrated that the use of upfront EGFR-TKI, and deferral of radiotherapy, is associated with inferior OS in patients with EGFR-mutant NSCLC who develop brain metastases. SRS followed by EGFR-TKI resulted in the longest OS and allowed patients to avoid the potential neurocognitive sequelae of WBRT. A prospective, multi-institutional randomized trial of SRS followed by EGFR-TKI versus EGFR-TKI followed by SRS at intracranial progression is urgently needed.

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

NASA Astrophysics Data System (ADS)

Goodfellow, M.; Rummel, C.; Abela, E.; Richardson, M. P.; Schindler, K.; Terry, J. R.

2016-07-01

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

Embedded sparse representation of fMRI data via group-wise dictionary optimization

NASA Astrophysics Data System (ADS)

Zhu, Dajiang; Lin, Binbin; Faskowitz, Joshua; Ye, Jieping; Thompson, Paul M.

2016-03-01

Sparse learning enables dimension reduction and efficient modeling of high dimensional signals and images, but it may need to be tailored to best suit specific applications and datasets. Here we used sparse learning to efficiently represent functional magnetic resonance imaging (fMRI) data from the human brain. We propose a novel embedded sparse representation (ESR), to identify the most consistent dictionary atoms across different brain datasets via an iterative group-wise dictionary optimization procedure. In this framework, we introduced additional criteria to make the learned dictionary atoms more consistent across different subjects. We successfully identified four common dictionary atoms that follow the external task stimuli with very high accuracy. After projecting the corresponding coefficient vectors back into the 3-D brain volume space, the spatial patterns are also consistent with traditional fMRI analysis results. Our framework reveals common features of brain activation in a population, as a new, efficient fMRI analysis method.

Impact of Blood-Brain Barrier Integrity on Tumor Growth and Therapy Response in Brain Metastases.

PubMed

Osswald, Matthias; Blaes, Jonas; Liao, Yunxiang; Solecki, Gergely; Gömmel, Miriam; Berghoff, Anna S; Salphati, Laurent; Wallin, Jeffrey J; Phillips, Heidi S; Wick, Wolfgang; Winkler, Frank

2016-12-15

The role of blood-brain barrier (BBB) integrity for brain tumor biology and therapy is a matter of debate. We developed a new experimental approach using in vivo two-photon imaging of mouse brain metastases originating from a melanoma cell line to investigate the growth kinetics of individual tumor cells in response to systemic delivery of two PI3K/mTOR inhibitors over time, and to study the impact of microregional vascular permeability. The two drugs are closely related but differ regarding a minor chemical modification that greatly increases brain penetration of one drug. Both inhibitors demonstrated a comparable inhibition of downstream targets and melanoma growth in vitro In vivo, increased BBB permeability to sodium fluorescein was associated with accelerated growth of individual brain metastases. Melanoma metastases with permeable microvessels responded similarly to equivalent doses of both inhibitors. In contrast, metastases with an intact BBB showed an exclusive response to the brain-penetrating inhibitor. The latter was true for macro- and micrometastases, and even single dormant melanoma cells. Nuclear morphology changes and single-cell regression patterns implied that both inhibitors, if extravasated, target not only perivascular melanoma cells but also those distant to blood vessels. Our study provides the first direct evidence that nonpermeable brain micro- and macrometastases can effectively be targeted by a drug designed to cross the BBB. Small-molecule inhibitors with these optimized properties are promising agents in preventing or treating brain metastases in patients. Clin Cancer Res; 22(24); 6078-87. ©2016 AACRSee related commentary by Steeg et al., p. 5953. ©2016 American Association for Cancer Research.

Validation of model-based brain shift correction in neurosurgery via intraoperative magnetic resonance imaging: preliminary results

NASA Astrophysics Data System (ADS)

Luo, Ma; Frisken, Sarah F.; Weis, Jared A.; Clements, Logan W.; Unadkat, Prashin; Thompson, Reid C.; Golby, Alexandra J.; Miga, Michael I.

2017-03-01

The quality of brain tumor resection surgery is dependent on the spatial agreement between preoperative image and intraoperative anatomy. However, brain shift compromises the aforementioned alignment. Currently, the clinical standard to monitor brain shift is intraoperative magnetic resonance (iMR). While iMR provides better understanding of brain shift, its cost and encumbrance is a consideration for medical centers. Hence, we are developing a model-based method that can be a complementary technology to address brain shift in standard resections, with resource-intensive cases as referrals for iMR facilities. Our strategy constructs a deformation `atlas' containing potential deformation solutions derived from a biomechanical model that account for variables such as cerebrospinal fluid drainage and mannitol effects. Volumetric deformation is estimated with an inverse approach that determines the optimal combinatory `atlas' solution fit to best match measured surface deformation. Accordingly, preoperative image is updated based on the computed deformation field. This study is the latest development to validate our methodology with iMR. Briefly, preoperative and intraoperative MR images of 2 patients were acquired. Homologous surface points were selected on preoperative and intraoperative scans as measurement of surface deformation and used to drive the inverse problem. To assess the model accuracy, subsurface shift of targets between preoperative and intraoperative states was measured and compared to model prediction. Considering subsurface shift above 3 mm, the proposed strategy provides an average shift correction of 59% across 2 cases. While further improvements in both the model and ability to validate with iMR are desired, the results reported are encouraging.

Design and validation of a microfluidic device for blood-brain barrier monitoring and transport studies

NASA Astrophysics Data System (ADS)

Ugolini, Giovanni Stefano; Occhetta, Paola; Saccani, Alessandra; Re, Francesca; Krol, Silke; Rasponi, Marco; Redaelli, Alberto

2018-04-01

In vitro blood-brain barrier models are highly relevant for drug screening and drug development studies, due to the challenging task of understanding the transport mechanism of drug molecules through the blood-brain barrier towards the brain tissue. In this respect, microfluidics holds potential for providing microsystems that require low amounts of cells and reagent and can be potentially multiplexed for increasing the ease and throughput of the drug screening process. We here describe the design, development and validation of a microfluidic device for endothelial blood-brain barrier cell transport studies. The device comprises of two microstructured layers (top culture chamber and bottom collection chamber) sandwiching a porous membrane for the cell culture. Microstructured layers include two pairs of physical electrodes, embedded into the device layers by geometrically defined guiding channels with computationally optimized positions. These electrodes allow the use of commercial electrical measurement systems for monitoring trans-endothelial electrical resistance (TEER). We employed the designed device for performing preliminary assessment of endothelial barrier formation with murine brain endothelial cells (Br-bEnd5). Results demonstrate that cellular junctional complexes effectively form in the cultures (expression of VE-Cadherin and ZO-1) and that the TEER monitoring systems effectively detects an increase of resistance of the cultured cell layers indicative of tight junction formation. Finally, we validate the use of the described microsystem for drug transport studies demonstrating that Br-bEnd5 cells significantly hinder the transport of molecules (40 kDa and 4 kDa dextran) from the top culture chamber to the bottom collection chamber.

Delivery of Chemotherapeutics Across the Blood–Brain Barrier: Challenges and Advances

PubMed Central

Doolittle, Nancy D.; Muldoon, Leslie L.; Culp, Aliana Y.; Neuwelt, Edward A.

2017-01-01

The blood–brain barrier (BBB) limits drug delivery to brain tumors. We utilize intraarterial infusion of hyperosmotic mannitol to reversibly open the BBB by shrinking endothelial cells and opening tight junctions between the cells. This approach transiently increases the delivery of chemotherapy, antibodies, and nanoparticles to brain. Our preclinical studies have optimized the BBB disruption (BBBD) technique and clinical studies have shown its safety and efficacy. The delivery of methotrexate-based chemotherapy in conjunction with BBBD provides excellent outcomes in primary central nervous system lymphoma (PCNSL) including stable or improved cognitive function in survivors a median of 12 years (range 2–26 years) after diagnosis. The addition of rituximab to chemotherapy with BBBD for PCNSL can be safely accomplished with excellent overall survival. Our translational studies of thiol agents to protect against platinum-induced toxicities led to the development of a two-compartment model in brain tumor patients. We showed that delayed high-dose sodium thiosulfate protects against carboplatin-induced hearing loss, providing the framework for large cooperative group trials of hearing chemoprotection. Neuroimaging studies have identified that ferumoxytol, an iron oxide nanoparticle blood pool agent, appears to be a superior contrast agent to accurately assess therapy-induced changes in brain tumor vasculature, in brain tumor response to therapy, and in differentiating central nervous system lesions with inflammatory components. This chapter reviews the breakthroughs, challenges, and future directions for BBBD. PMID:25307218

Classifying EEG for Brain-Computer Interface: Learning Optimal Filters for Dynamical System Features

PubMed Central

Song, Le; Epps, Julien

2007-01-01

Classification of multichannel EEG recordings during motor imagination has been exploited successfully for brain-computer interfaces (BCI). In this paper, we consider EEG signals as the outputs of a networked dynamical system (the cortex), and exploit synchronization features from the dynamical system for classification. Herein, we also propose a new framework for learning optimal filters automatically from the data, by employing a Fisher ratio criterion. Experimental evaluations comparing the proposed dynamical system features with the CSP and the AR features reveal their competitive performance during classification. Results also show the benefits of employing the spatial and the temporal filters optimized using the proposed learning approach. PMID:18364986

Design, optimization, and biological evaluation of novel keto-benzimidazoles as potent and selective inhibitors of phosphodiesterase 10A (PDE10A).

PubMed

Hu, Essa; Kunz, Roxanne K; Chen, Ning; Rumfelt, Shannon; Siegmund, Aaron; Andrews, Kristin; Chmait, Samer; Zhao, Sharon; Davis, Carl; Chen, Hang; Lester-Zeiner, Dianna; Ma, Ji; Biorn, Christopher; Shi, Jianxia; Porter, Amy; Treanor, James; Allen, Jennifer R

2013-11-14

Our development of PDE10A inhibitors began with an HTS screening hit (1) that exhibited both high p-glycoprotein (P-gp) efflux ratios in rat and human and poor metabolic stability. On the basis of cocrystal structure of 1 in human PDE10A enzyme, we designed a novel keto-benzimidazole 26 with comparable PDE10A potency devoid of efflux liabilities. On target in vivo coverage of PDE10A in rat brain was assessed using our previously reported LC-MS/MS receptor occupancy (RO) technology. Compound 26 achieved 55% RO of PDE10A at 30 mg/kg po and covered PDE10A receptors in rat brain in a dose-dependent manner. Cocrystal structure of 26 in PDE10A confirmed the binding mode of the novel scaffold. Further optimization resulted in the identification of keto-benzimidazole 34, which showed an increased in vivo efficacy of 57% RO in rats at 10 mg/kg po and an improved in vivo rat clearance and oral bioavailability.

Fast three-dimensional inner volume excitations using parallel transmission and optimized k-space trajectories.

PubMed

Davids, Mathias; Schad, Lothar R; Wald, Lawrence L; Guérin, Bastien

2016-10-01

To design short parallel transmission (pTx) pulses for excitation of arbitrary three-dimensional (3D) magnetization patterns. We propose a joint optimization of the pTx radiofrequency (RF) and gradient waveforms for excitation of arbitrary 3D magnetization patterns. Our optimization of the gradient waveforms is based on the parameterization of k-space trajectories (3D shells, stack-of-spirals, and cross) using a small number of shape parameters that are well-suited for optimization. The resulting trajectories are smooth and sample k-space efficiently with few turns while using the gradient system at maximum performance. Within each iteration of the k-space trajectory optimization, we solve a small tip angle least-squares RF pulse design problem. Our RF pulse optimization framework was evaluated both in Bloch simulations and experiments on a 7T scanner with eight transmit channels. Using an optimized 3D cross (shells) trajectory, we were able to excite a cube shape (brain shape) with 3.4% (6.2%) normalized root-mean-square error in less than 5 ms using eight pTx channels and a clinical gradient system (Gmax  = 40 mT/m, Smax  = 150 T/m/s). This compared with 4.7% (41.2%) error for the unoptimized 3D cross (shells) trajectory. Incorporation of B0 robustness in the pulse design significantly altered the k-space trajectory solutions. Our joint gradient and RF optimization approach yields excellent excitation of 3D cube and brain shapes in less than 5 ms, which can be used for reduced field of view imaging and fat suppression in spectroscopy by excitation of the brain only. Magn Reson Med 76:1170-1182, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Fabrication and Optimal Design of Biodegradable Polymeric Stents for Aneurysms Treatments

PubMed Central

Han, Xue; Wu, Xia; Kelly, Michael; Chen, Xiongbiao

2017-01-01

An aneurysm is a balloon-like bulge in the wall of blood vessels, occurring in major arteries of the heart and brain. Biodegradable polymeric stent-assisted coiling is expected to be the ideal treatment of wide-neck complex aneurysms. This paper presents the development of methods to fabricate and optimally design biodegradable polymeric stents for aneurysms treatment. Firstly, a dispensing-based rapid prototyping (DBRP) system was developed to fabricate coil and zigzag structures of biodegradable polymeric stents. Then, compression testing was carried out to characterize the radial deformation of the stents fabricated with the coil or zigzag structure. The results illustrated the stent with a zigzag structure has a stronger radial stiffness than the one with a coil structure. On this basis, the stent with a zigzag structure was chosen for the development of a finite element model for simulating the real compression tests. The result showed the finite element model of biodegradable polymeric stents is acceptable within a range of radial deformation around 20%. Furthermore, the optimization of the zigzag structure was performed with ANSYS DesignXplorer, and the results indicated that the total deformation could be decreased by 35.7% by optimizing the structure parameters, which would represent a significant advance of the radial stiffness of biodegradable polymeric stents. PMID:28264515

Neutron beam optimization based on a 7Li(p,n)7Be reaction for treatment of deep-seated brain tumors by BNCT

NASA Astrophysics Data System (ADS)

Zahra Ahmadi, Ganjeh; S. Farhad, Masoudi

2014-10-01

Neutron beam optimization for accelerator-based Boron Neutron Capture Therapy (BNCT) is investigated using a 7Li(p,n)7Be reaction. Design and optimization have been carried out for the target, cooling system, moderator, filter, reflector, and collimator to achieve a high flux of epithermal neutron and satisfy the IAEA criteria. Also, the performance of the designed beam in tissue is assessed by using a simulated Snyder head phantom. The results show that the optimization of the collimator and reflector is critical to finding the best neutron beam based on the 7Li(p,n)7Be reaction. Our designed beam has 2.49×109n/cm2s epithermal neutron flux and is suitable for BNCT of deep-seated brain tumors.

Bipolar electrode selection for a motor imagery based brain computer interface

NASA Astrophysics Data System (ADS)

Lou, Bin; Hong, Bo; Gao, Xiaorong; Gao, Shangkai

2008-09-01

A motor imagery based brain-computer interface (BCI) provides a non-muscular communication channel that enables people with paralysis to control external devices using their motor imagination. Reducing the number of electrodes is critical to improving the portability and practicability of the BCI system. A novel method is proposed to reduce the number of electrodes to a total of four by finding the optimal positions of two bipolar electrodes. Independent component analysis (ICA) is applied to find the source components of mu and alpha rhythms, and optimal electrodes are chosen by comparing the projection weights of sources on each channel. The results of eight subjects demonstrate the better classification performance of the optimal layout compared with traditional layouts, and the stability of this optimal layout over a one week interval was further verified.

B Vitamins and the Brain: Mechanisms, Dose and Efficacy—A Review

PubMed Central

Kennedy, David O.

2016-01-01

The B-vitamins comprise a group of eight water soluble vitamins that perform essential, closely inter-related roles in cellular functioning, acting as co-enzymes in a vast array of catabolic and anabolic enzymatic reactions. Their collective effects are particularly prevalent to numerous aspects of brain function, including energy production, DNA/RNA synthesis/repair, genomic and non-genomic methylation, and the synthesis of numerous neurochemicals and signaling molecules. However, human epidemiological and controlled trial investigations, and the resultant scientific commentary, have focused almost exclusively on the small sub-set of vitamins (B9/B12/B6) that are the most prominent (but not the exclusive) B-vitamins involved in homocysteine metabolism. Scant regard has been paid to the other B vitamins. This review describes the closely inter-related functions of the eight B-vitamins and marshals evidence suggesting that adequate levels of all members of this group of micronutrients are essential for optimal physiological and neurological functioning. Furthermore, evidence from human research clearly shows both that a significant proportion of the populations of developed countries suffer from deficiencies or insufficiencies in one or more of this group of vitamins, and that, in the absence of an optimal diet, administration of the entire B-vitamin group, rather than a small sub-set, at doses greatly in excess of the current governmental recommendations, would be a rational approach for preserving brain health. PMID:26828517

B Vitamins and the Brain: Mechanisms, Dose and Efficacy--A Review.

PubMed

Kennedy, David O

2016-01-27

The B-vitamins comprise a group of eight water soluble vitamins that perform essential, closely inter-related roles in cellular functioning, acting as co-enzymes in a vast array of catabolic and anabolic enzymatic reactions. Their collective effects are particularly prevalent to numerous aspects of brain function, including energy production, DNA/RNA synthesis/repair, genomic and non-genomic methylation, and the synthesis of numerous neurochemicals and signaling molecules. However, human epidemiological and controlled trial investigations, and the resultant scientific commentary, have focused almost exclusively on the small sub-set of vitamins (B9/B12/B6) that are the most prominent (but not the exclusive) B-vitamins involved in homocysteine metabolism. Scant regard has been paid to the other B vitamins. This review describes the closely inter-related functions of the eight B-vitamins and marshals evidence suggesting that adequate levels of all members of this group of micronutrients are essential for optimal physiological and neurological functioning. Furthermore, evidence from human research clearly shows both that a significant proportion of the populations of developed countries suffer from deficiencies or insufficiencies in one or more of this group of vitamins, and that, in the absence of an optimal diet, administration of the entire B-vitamin group, rather than a small sub-set, at doses greatly in excess of the current governmental recommendations, would be a rational approach for preserving brain health.

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Mutagenicity, anticancer activity and blood brain barrier: similarity and dissimilarity of molecular alerts.

PubMed

Toropov, Andrey A; Toropova, Alla P; Benfenati, Emilio; Salmona, Mario

2018-06-01

The aim of the present work is an attempt to define computable measure of similarity between different endpoints. The similarity of structural alerts of different biochemical endpoints can be used to solve tasks of medicinal chemistry. Optimal descriptors are a tool to build up models for different endpoints. The optimal descriptor is calculated with simplified molecular input-line entry system (SMILES). A group of elements (single symbol or pair of symbols) can represent any SMILES. Each element of SMILES can be represented by so-called correlation weight i.e. coefficient that should be used to calculate descriptor. Numerical data on the correlation weights are calculated by the Monte Carlo method, i.e. by optimization procedure, which gives maximal correlation coefficient between the optimal descriptor and endpoint for the training set. Statistically stable correlation weights observed in several runs of the optimization can be examined as structural alerts, which are promoters of the increase or the decrease of a biochemical activity of a substance. Having data on several runs of the optimization correlation weights, one can extract list of promoters of increase and list of promoters of decrease for an endpoint. The study of similarity and dissimilarity of the above lists has been carried out for the following pairs of endpoints: (i) mutagenicity and anticancer activity; (ii) mutagenicity and blood brain barrier; and (iii) blood brain barrier and anticancer activity. The computational experiment confirms that similarity and dissimilarity for pairs of endpoints can be measured.

Three-dimensional brain MRI for DBS patients within ultra-low radiofrequency power limits.

PubMed

Sarkar, Subhendra N; Papavassiliou, Efstathios; Hackney, David B; Alsop, David C; Shih, Ludy C; Madhuranthakam, Ananth J; Busse, Reed F; La Ruche, Susan; Bhadelia, Rafeeque A

2014-04-01

For patients with deep brain stimulators (DBS), local absorbed radiofrequency (RF) power is unknown and is much higher than what the system estimates. We developed a comprehensive, high-quality brain magnetic resonance imaging (MRI) protocol for DBS patients utilizing three-dimensional (3D) magnetic resonance sequences at very low RF power. Six patients with DBS were imaged (10 sessions) using a transmit/receive head coil at 1.5 Tesla with modified 3D sequences within ultra-low specific absorption rate (SAR) limits (0.1 W/kg) using T2 , fast fluid-attenuated inversion recovery (FLAIR) and T1 -weighted image contrast. Tissue signal and tissue contrast from the low-SAR images were subjectively and objectively compared with routine clinical images of six age-matched controls. Low-SAR images of DBS patients demonstrated tissue contrast comparable to high-SAR images and were of diagnostic quality except for slightly reduced signal. Although preliminary, we demonstrated diagnostic quality brain MRI with optimized, volumetric sequences in DBS patients within very conservative RF safety guidelines offering a greater safety margin. © 2014 International Parkinson and Movement Disorder Society.

Traumatic brain injury.

PubMed

Barlow, Karen Maria

2013-01-01

In childhood, traumatic brain injury (TBI) poses the unique challenges of an injury to a developing brain and the dynamic pattern of recovery over time, inflicted TBI and its medicolegal ramifications. The mechanisms of injury vary with age, as do the mechanisms that lead to the primary brain injury. As it is common, and is the leading cause of death and disability in the USA and Canada, prevention is the key, and we may need increased legislation to facilitate this. Despite its prevalence, there is an almost urgent need for research to help guide the optimal management and improve outcomes. Indeed, contrary to common belief, children with severe TBI have a worse outcome and many of the consequences present in teenage years or later. The treatment needs, therefore, to be multifaceted and starts at the scene of the injury and extends into the home and school. In order to do this, the care needs to be multidisciplinary from specialists with a specific interest in TBI and to involve the family, and will often span many decades. Copyright © 2013 Elsevier B.V. All rights reserved.

Central thalamic deep brain stimulation for support of forebrain arousal regulation in the minimally conscious state.

PubMed

Schiff, Nicholas D

2013-01-01

This chapter considers the use of central thalamic deep brain stimulation (CT/DBS) to support arousal regulation mechanisms in the minimally conscious state (MCS). CT/DBS for selected patients in a MCS is first placed in the historical context of prior efforts to use thalamic electrical brain stimulation to treat the unconscious clinical conditions of coma and vegetative state. These previous studies and a proof of concept result from a single-subject study of a patient in a MCS are reviewed against the background of new population data providing benchmarks of the natural history of vegetative and MCSs. The conceptual foundations for CT/DBS in selected patients in a MCS are then presented with consideration of both circuit and cellular mechanisms underlying recovery of consciousness identified from empirical studies. Directions for developing future generalizable criteria for CT/DBS that focus on the integrity of necessary brain systems and behavioral profiles in patients in a MCS that may optimally response to support of arousal regulation mechanisms are proposed. © 2013 Elsevier B.V. All rights reserved.

User-customized brain computer interfaces using Bayesian optimization

NASA Astrophysics Data System (ADS)

Bashashati, Hossein; Ward, Rabab K.; Bashashati, Ali

2016-04-01

Objective. The brain characteristics of different people are not the same. Brain computer interfaces (BCIs) should thus be customized for each individual person. In motor-imagery based synchronous BCIs, a number of parameters (referred to as hyper-parameters) including the EEG frequency bands, the channels and the time intervals from which the features are extracted should be pre-determined based on each subject’s brain characteristics. Approach. To determine the hyper-parameter values, previous work has relied on manual or semi-automatic methods that are not applicable to high-dimensional search spaces. In this paper, we propose a fully automatic, scalable and computationally inexpensive algorithm that uses Bayesian optimization to tune these hyper-parameters. We then build different classifiers trained on the sets of hyper-parameter values proposed by the Bayesian optimization. A final classifier aggregates the results of the different classifiers. Main Results. We have applied our method to 21 subjects from three BCI competition datasets. We have conducted rigorous statistical tests, and have shown the positive impact of hyper-parameter optimization in improving the accuracy of BCIs. Furthermore, We have compared our results to those reported in the literature. Significance. Unlike the best reported results in the literature, which are based on more sophisticated feature extraction and classification methods, and rely on prestudies to determine the hyper-parameter values, our method has the advantage of being fully automated, uses less sophisticated feature extraction and classification methods, and yields similar or superior results compared to the best performing designs in the literature.

Quantifying Motor Experience in the Infant Brain: EEG Power, Coherence, and Mu Desynchronization

PubMed Central

Gonzalez, Sandy L.; Reeb-Sutherland, Bethany C.; Nelson, Eliza L.

2016-01-01

The emergence of new motor skills, such as reaching and walking, dramatically changes how infants engage with the world socially and cognitively. Several examples of how motor experience can cascade into cognitive and social development have been documented, yet a significant knowledge gap remains in our understanding of whether these observed behavioral changes are accompanied by underlying neural changes. We propose that electroencephalography (EEG) measures such as power, coherence, and mu desynchronization are optimal tools to quantify motor experience in the infant brain. In this mini-review, we will summarize existing infant research that has separately assessed the relation between motor, cognitive, or social development with coherence, power, or mu desynchronization. We will discuss how the reviewed neural changes seen in seemingly separate developmental domains may be linked based on existing behavioral evidence. We will further propose that power, coherence, and mu desynchronization be used in research exploring the links between motor experience and cognitive and social development. PMID:26925022

Trajectory optimization for dynamic couch rotation during volumetric modulated arc radiotherapy

NASA Astrophysics Data System (ADS)

Smyth, Gregory; Bamber, Jeffrey C.; Evans, Philip M.; Bedford, James L.

2013-11-01

Non-coplanar radiation beams are often used in three-dimensional conformal and intensity modulated radiotherapy to reduce dose to organs at risk (OAR) by geometric avoidance. In volumetric modulated arc radiotherapy (VMAT) non-coplanar geometries are generally achieved by applying patient couch rotations to single or multiple full or partial arcs. This paper presents a trajectory optimization method for a non-coplanar technique, dynamic couch rotation during VMAT (DCR-VMAT), which combines ray tracing with a graph search algorithm. Four clinical test cases (partial breast, brain, prostate only, and prostate and pelvic nodes) were used to evaluate the potential OAR sparing for trajectory-optimized DCR-VMAT plans, compared with standard coplanar VMAT. In each case, ray tracing was performed and a cost map reflecting the number of OAR voxels intersected for each potential source position was generated. The least-cost path through the cost map, corresponding to an optimal DCR-VMAT trajectory, was determined using Dijkstra’s algorithm. Results show that trajectory optimization can reduce dose to specified OARs for plans otherwise comparable to conventional coplanar VMAT techniques. For the partial breast case, the mean heart dose was reduced by 53%. In the brain case, the maximum lens doses were reduced by 61% (left) and 77% (right) and the globes by 37% (left) and 40% (right). Bowel mean dose was reduced by 15% in the prostate only case. For the prostate and pelvic nodes case, the bowel V50 Gy and V60 Gy were reduced by 9% and 45% respectively. Future work will involve further development of the algorithm and assessment of its performance over a larger number of cases in site-specific cohorts.

Polymer Nanoparticles as Smart Carriers for the Enhanced Release of Therapeutic Agents to the CNS.

PubMed

Gagliardi, Mariacristina; Borri, Claudia

2017-01-01

The brain is the most protected organ in the human body; its protective shield, relying on a complex system of cells, proteins and transporters, prevents potentially harmful substances from entering the brain from the bloodstream but, on the other hand, it also stops drugs administered via the systemic route. To improve the efficacy of pharmacological treatments, targeted drug delivery by means of polymer nanoparticles is a challenging but, at the same time, efficient strategy. Thanks to a highly multidisciplinary approach, several ways to overcome the brain protection have provided effective solutions to treat a large number of diseases. Important advances in polymer science, together with the development of novel techniques for nanocarrier preparation, and the discovery of novel targeting ligands and molecules, allow a fine-tuning of size, shape, chemicophysical properties and surface chemistry of functional particulate systems; it enables the improvement of the therapeutic performances for several drugs, also toward districts that are difficult to be treated, such as the brain. This review focuses on the great strides made from scientists and doctors in the development of polymer nano-sized drug delivery systems for brain diseases. Even though the optimal nanocarrier was not yet discovered, important advances were made to strive for safer, performant and successful systems, with the expectation to find soon better solutions to cure some still untreatable pathologies. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Absence of gender effect on children with attention-deficit/hyperactivity disorder as assessed by optimized voxel-based morphometry.

PubMed

Yang, Pinchen; Wang, Pei-Ning; Chuang, Kai-Hsiang; Jong, Yuh-Jyh; Chao, Tzu-Cheng; Wu, Ming-Ting

2008-12-30

Brain abnormalities, as determined by structural magnetic resonance imaging (MRI), have been reported in patients with attention-deficit hyperactivity disorder (ADHD); however, female subjects have been underrepresented in previous reports. In this study, we used optimized voxel-based morphometry to compare the total and regional gray matter volumes between groups of 7- to 17-year-old ADHD and healthy children (total 114 subjects). Fifty-seven children with ADHD (n=57, 35 males and 22 females) and healthy children (n=57) received MRI scans. Segmented brain MRI images were normalized into standardized stereotactic space, modulated to allow volumetric analysis, smoothed and compared at the voxel level with statistical parametric mapping. Global volumetric comparisons between groups revealed that the total brain volumes of ADHD children were smaller than those of the control children. As for the regional brain analysis, the brain volumes of ADHD children were found to be bilaterally smaller in the following regions as compared with normal control values: the caudate nucleus and the cerebellum. There were two clusters of regional decrease in the female brain, left posterior cingulum and right precuneus, as compared with the male brain. Brain regions showing the interaction effect of diagnosis and gender were negligible. These results were consistent with the hypothesized dysfunctional systems in ADHD, and they also suggested that neuroanatomical abnormalities in ADHD were not influenced by gender.

Moment-to-Moment BOLD Signal Variability Reflects Regional Changes in Neural Flexibility across the Lifespan.

PubMed

Nomi, Jason S; Bolt, Taylor S; Ezie, C E Chiemeka; Uddin, Lucina Q; Heller, Aaron S

2017-05-31

Variability of neuronal responses is thought to underlie flexible and optimal brain function. Because previous work investigating BOLD signal variability has been conducted within task-based fMRI contexts on adults and older individuals, very little is currently known regarding regional changes in spontaneous BOLD signal variability in the human brain across the lifespan. The current study used resting-state fMRI data from a large sample of male and female human participants covering a wide age range (6-85 years) across two different fMRI acquisition parameters (TR = 0.645 and 1.4 s). Variability in brain regions including a key node of the salience network (anterior insula) increased linearly across the lifespan across datasets. In contrast, variability in most other large-scale networks decreased linearly over the lifespan. These results demonstrate unique lifespan trajectories of BOLD variability related to specific regions of the brain and add to a growing literature demonstrating the importance of identifying normative trajectories of functional brain maturation. SIGNIFICANCE STATEMENT Although brain signal variability has traditionally been considered a source of unwanted noise, recent work demonstrates that variability in brain signals during task performance is related to brain maturation in old age as well as individual differences in behavioral performance. The current results demonstrate that intrinsic fluctuations in resting-state variability exhibit unique maturation trajectories in specific brain regions and systems, particularly those supporting salience detection. These results have implications for investigations of brain development and aging, as well as interpretations of brain function underlying behavioral changes across the lifespan. Copyright © 2017 the authors 0270-6474/17/375539-10$15.00/0.

Two-photon microscope for multisite microphotolysis of caged neurotransmitters in acute brain slices

PubMed Central

Losavio, Bradley E.; Iyer, Vijay; Saggau, Peter

2009-01-01

We developed a two-photon microscope optimized for physiologically manipulating single neurons through their postsynaptic receptors. The optical layout fulfills the stringent design criteria required for high-speed, high-resolution imaging in scattering brain tissue with minimal photodamage. We detail the practical compensation of spectral and temporal dispersion inherent in fast laser beam scanning with acousto-optic deflectors, as well as a set of biological protocols for visualizing nearly diffraction-limited structures and delivering physiological synaptic stimuli. The microscope clearly resolves dendritic spines and evokes electrophysiological transients in single neurons that are similar to endogenous responses. This system enables the study of multisynaptic integration and will assist our understanding of single neuron function and dendritic computation. PMID:20059271

Oiling the brain: a review of randomized controlled trials of omega-3 fatty acids in psychopathology across the lifespan.

PubMed

Sinn, Natalie; Milte, Catherine; Howe, Peter R C

2010-02-01

Around one in four people suffer from mental illness at some stage in their lifetime. There is increasing awareness of the importance of nutrition, particularly omega-3 polyunsaturated fatty acids (n-3 PUFA), for optimal brain development and function. Hence in recent decades, researchers have explored effects of n-3 PUFA on mental health problems over the lifespan, from developmental disorders in childhood, to depression, aggression, and schizophrenia in adulthood, and cognitive decline, dementia and Alzheimer's disease in late adulthood. This review provides an updated overview of the published and the registered clinical trials that investigate effects of n-3 PUFA supplementation on mental health and behavior, highlighting methodological differences and issues.

Quantification of transient increase of the blood–brain barrier permeability to macromolecules by optimized focused ultrasound combined with microbubbles

PubMed Central

Shi, Lingyan; Palacio-Mancheno, Paolo; Badami, Joseph; Shin, Da Wi; Zeng, Min; Cardoso, Luis; Tu, Raymond; Fu, Bingmei M

2014-01-01

Radioimmunotherapy using a radiolabeled monoclonal antibody that targets tumor cells has been shown to be efficient for the treatment of many malignant cancers, with reduced side effects. However, the blood–brain barrier (BBB) inhibits the transport of intravenous antibodies to tumors in the brain. Recent studies have demonstrated that focused ultrasound (FUS) combined with microbubbles (MBs) is a promising method to transiently disrupt the BBB for the drug delivery to the central nervous system. To find the optimal FUS and MBs that can induce reversible increase in the BBB permeability, we employed minimally invasive multiphoton microscopy to quantify the BBB permeability to dextran-155 kDa with similar molecular weight to an antibody by applying different doses of FUS in the presence of MBs with an optimal size and concentration. The cerebral microcirculation was observed through a section of frontoparietal bone thinned with a micro-grinder. About 5 minutes after applying the FUS on the thinned skull in the presence of MBs for 1 minute, TRITC (tetramethylrhodamine isothiocyanate)-dextran-155 kDa in 1% bovine serum albumin in mammalian Ringer’s solution was injected into the cerebral circulation via the ipsilateral carotid artery by a syringe pump. Simultaneously, the temporal images were collected from the brain parenchyma ~100–200 μm below the pia mater. Permeability was determined from the rate of tissue solute accumulation around individual microvessels. After several trials, we found the optimal dose of FUS. At the optimal dose, permeability increased by ~14-fold after 5 minutes post-FUS, and permeability returned to the control level after 25 minutes. FUS without MBs or MBs injected without FUS did not change the permeability. Our method provides an accurate in vivo assessment for the transient BBB permeability change under the treatment of FUS. The optimal FUS dose found for the reversible BBB permeability increase without BBB disruption is reliable and can be applied to future clinical trials. PMID:25258533

IV. The cognitive implications of obesity and nutrition in childhood.

PubMed

Khan, Naiman A; Raine, Lauren B; Donovan, Sharon M; Hillman, Charles H

2014-12-01

The prevalence of childhood obesity in the United States has tripled since the 1980s and is strongly linked to the early onset of several metabolic diseases. Recent studies indicate that lower cognitive function may be another complication of childhood obesity. This review considers the research to date on the role of obesity and nutrition on childhood cognition and brain health. Although a handful of studies point to a maladaptive relationship between obesity and aspects of cognitive control, remarkably little is known regarding the impact of fat mass on brain development and cognitive function. Further, missing from the literature is the role of nutrition in the obesity-cognition interaction. Nutrition may directly or indirectly influence cognitive performance via several pathways including provision of key substrates for optimal brain health, modulation of gut microbiota, and alterations in systemic energy balance. However, in the absence of malnutrition, the functional benefits of specific nutrient intake on particular cognitive domains are not well characterized. Here, we examine the literature linking childhood obesity and cognition while considering the effects of nutritional intake. Possible mechanisms for these relationships are discussed and suggestions are made for future study topics. Although childhood obesity prevalence rates in some developed countries have recently stabilized, significant disparities remain among groups based on sex and socioeconomic status. Given that the elevated prevalence of pediatric overweight and obesity may persist for the foreseeable future, it is crucial to develop a comprehensive understanding of the influence of obesity and nutrition on cognition and brain health in the pediatric population. © 2014 The Society for Research in Child Development, Inc.

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

PubMed

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

2017-04-15

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

New frontiers in developmental neuropharmacology: Can long-term therapeutic effects of drugs be optimized through carefully timed early intervention?

PubMed Central

Andersen, Susan L.; Navalta, Carryl P.

2010-01-01

Our aim is to present a working model that may serve as a valuable heuristic to predict enduring effects of drugs when administered during development. Our primary tenet is that a greater understanding of neurodevelopment can lead to improved treatment that intervenes early in the progression of a given disorder and prevents symptoms from manifesting. The immature brain undergoes significant changes during the transitions between childhood, adolescence, and adulthood. Such changes in innervation, neurotransmitter levels, and their respective signaling mechanisms have profound and observable changes on typical behavior, but also increase vulnerability to psychiatric disorders when the maturational process goes awry. Given the remarkable plasticity of the immature brain to adapt to its external milieu, preventive interventions may be possible. We intend for this review to initiate a discussion of how currently used psychotropic agents can influence brain development. Drug exposure during sensitive periods may have beneficial long-term effects, but harmful delayed consequences may be possible as well. Regardless of the outcome, this information needs to be used to improve or develop alternative approaches for the treatment of childhood disorders. With this framework in mind, we present what is known about the effects of stimulants, antidepressants, and antipsychotics on brain maturation (including animal studies that use more clinically-relevant dosing paradigms or relevant animal models). We endeavor to provocatively set the stage for altering treatment approaches for improving mental health in non-adult populations. PMID:21309771

Computational neuroanatomy: mapping cell-type densities in the mouse brain, simulations from the Allen Brain Atlas

NASA Astrophysics Data System (ADS)

Grange, Pascal

2015-09-01

The Allen Brain Atlas of the adult mouse (ABA) consists of digitized expression profiles of thousands of genes in the mouse brain, co-registered to a common three-dimensional template (the Allen Reference Atlas).This brain-wide, genome-wide data set has triggered a renaissance in neuroanatomy. Its voxelized version (with cubic voxels of side 200 microns) is available for desktop computation in MATLAB. On the other hand, brain cells exhibit a great phenotypic diversity (in terms of size, shape and electrophysiological activity), which has inspired the names of some well-studied cell types, such as granule cells and medium spiny neurons. However, no exhaustive taxonomy of brain cell is available. A genetic classification of brain cells is being undertaken, and some cell types have been chraracterized by their transcriptome profiles. However, given a cell type characterized by its transcriptome, it is not clear where else in the brain similar cells can be found. The ABA can been used to solve this region-specificity problem in a data-driven way: rewriting the brain-wide expression profiles of all genes in the atlas as a sum of cell-type-specific transcriptome profiles is equivalent to solving a quadratic optimization problem at each voxel in the brain. However, the estimated brain-wide densities of 64 cell types published recently were based on one series of co-registered coronal in situ hybridization (ISH) images per gene, whereas the online ABA contains several image series per gene, including sagittal ones. In the presented work, we simulate the variability of cell-type densities in a Monte Carlo way by repeatedly drawing a random image series for each gene and solving the optimization problem. This yields error bars on the region-specificity of cell types.

Targeted delivery of antibody-based therapeutic and imaging agents to CNS tumors: Crossing the blood-brain-barrier divide

PubMed Central

Chacko, Ann-Marie; Li, Chunsheng; Pryma, Daniel A.; Brem, Steven; Coukos, George; Muzykantov, Vladimir R.

2014-01-01

Introduction Brain tumors are inherently difficult to treat in large part due to the cellular blood-brain barriers (BBB) that limit the delivery of therapeutics to the tumor tissue from the systemic circulation. Virtually no large-molecules, including antibody-based proteins, can penetrate the BBB. With antibodies fast becoming attractive ligands for highly specific molecular targeting to tumor antigens, a variety of methods are being investigated to enhance the access of these agents to intracranial tumors for imaging or therapeutic applications. Areas covered This review describes the characteristics of the BBB and the vasculature in brain tumors, described as the blood-brain tumor barrier (BBTB). Antibodies targeted to molecular markers of CNS tumors will be highlighted, and current strategies for enhancing the delivery of antibodies across these cellular barriers into the brain parenchyma to the tumor will be discussed. Non-invasive imaging approaches to assess BBB/BBTB permeability and/or antibody targeting will be presented as a means of guiding the optimal delivery of targeted agents to brain tumors. Expert Opinion Pre-clinical and clinical studies highlight the potential of several approaches in increasing brain tumor delivery across the blood-brain barrier divide. However, each carries its own risks and challenges. There is tremendous potential in using neuroimaging strategies to assist in understanding and defining the challenges to translating and optimizing molecularly-targeted antibody delivery to CNS tumors to improve clinical outcomes. PMID:23751126

Optimal-mass-transfer-based estimation of glymphatic transport in living brain.

PubMed

Ratner, Vadim; Zhu, Liangjia; Kolesov, Ivan; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2015-02-21

It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial fluid exchange system designated the 'glymphatic pathway' plays a key role in removing waste products from the brain, similarly to the lymphatic system in other body organs 1,2 . It is therefore important to study the flow patterns of glymphatic transport through the live brain in order to better understand its functionality in normal and pathological states. Unlike blood, the CSF does not flow rapidly through a network of dedicated vessels, but rather through para-vascular channels and brain parenchyma in a slower time-domain, and thus conventional fMRI or other blood-flow sensitive MRI sequences do not provide much useful information about the desired flow patterns. We have accordingly analyzed a series of MRI images, taken at different times, of the brain of a live rat, which was injected with a paramagnetic tracer into the CSF via the lumbar intrathecal space of the spine. Our goal is twofold: (a) find glymphatic (tracer) flow directions in the live rodent brain; and (b) provide a model of a (healthy) brain that will allow the prediction of tracer concentrations given initial conditions. We model the liquid flow through the brain by the diffusion equation. We then use the Optimal Mass Transfer (OMT) approach 3 to derive the glymphatic flow vector field, and estimate the diffusion tensors by analyzing the (changes in the) flow. Simulations show that the resulting model successfully reproduces the dominant features of the experimental data.

Sleep, Memory & Brain Rhythms

PubMed Central

Watson, Brendon O.; Buzsáki, György

2015-01-01

Sleep occupies roughly one-third of our lives, yet the scientific community is still not entirely clear on its purpose or function. Existing data point most strongly to its role in memory and homeostasis: that sleep helps maintain basic brain functioning via a homeostatic mechanism that loosens connections between overworked synapses, and that sleep helps consolidate and re-form important memories. In this review, we will summarize these theories, but also focus on substantial new information regarding the relation of electrical brain rhythms to sleep. In particular, while REM sleep may contribute to the homeostatic weakening of overactive synapses, a prominent and transient oscillatory rhythm called “sharp-wave ripple” seems to allow for consolidation of behaviorally relevant memories across many structures of the brain. We propose that a theory of sleep involving the division of labor between two states of sleep–REM and non-REM, the latter of which has an abundance of ripple electrical activity–might allow for a fusion of the two main sleep theories. This theory then postulates that sleep performs a combination of consolidation and homeostasis that promotes optimal knowledge retention as well as optimal waking brain function. PMID:26097242

Convection-enhanced drug delivery to the brain: therapeutic potential and neuropathological considerations.

PubMed

Barua, Neil U; Gill, Steven S; Love, Seth

2014-03-01

Convection-enhanced delivery (CED) describes a direct method of drug delivery to the brain through intraparenchymal microcatheters. By establishing a pressure gradient at the tip of the infusion catheter in order to exploit bulk flow through the interstitial spaces of the brain, CED offers a number of advantages over conventional drug delivery methods-bypass of the blood-brain barrier, targeted distribution through large brain volumes and minimization of systemic side effects. Despite showing early promise, CED is yet to fulfill its potential as a mainstream strategy for the treatment of neurological disease. Substantial research effort has been dedicated to optimize the technology for CED and identify the parameters, which govern successful drug distribution. It seems likely that successful clinical translation of CED will depend on suitable catheter technology being used in combination with drugs with optimal physicochemical characteristics, and on neuropathological analysis in appropriate preclinical models. In this review, we consider the factors most likely to influence the success or failure of CED, and review its application to the treatment of high-grade glioma, Parkinson's disease (PD) and Alzheimer's disease (AD). © 2013 International Society of Neuropathology.

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Slice-to-Volume Nonrigid Registration of Histological Sections to MR Images of the Human Brain

PubMed Central

Osechinskiy, Sergey; Kruggel, Frithjof

2011-01-01

Registration of histological images to three-dimensional imaging modalities is an important step in quantitative analysis of brain structure, in architectonic mapping of the brain, and in investigation of the pathology of a brain disease. Reconstruction of histology volume from serial sections is a well-established procedure, but it does not address registration of individual slices from sparse sections, which is the aim of the slice-to-volume approach. This study presents a flexible framework for intensity-based slice-to-volume nonrigid registration algorithms with a geometric transformation deformation field parametrized by various classes of spline functions: thin-plate splines (TPS), Gaussian elastic body splines (GEBS), or cubic B-splines. Algorithms are applied to cross-modality registration of histological and magnetic resonance images of the human brain. Registration performance is evaluated across a range of optimization algorithms and intensity-based cost functions. For a particular case of histological data, best results are obtained with a TPS three-dimensional (3D) warp, a new unconstrained optimization algorithm (NEWUOA), and a correlation-coefficient-based cost function. PMID:22567290

Sleep, Memory & Brain Rhythms.

PubMed

Watson, Brendon O; Buzsáki, György

2015-01-01

Sleep occupies roughly one-third of our lives, yet the scientific community is still not entirely clear on its purpose or function. Existing data point most strongly to its role in memory and homeostasis: that sleep helps maintain basic brain functioning via a homeostatic mechanism that loosens connections between overworked synapses, and that sleep helps consolidate and re-form important memories. In this review, we will summarize these theories, but also focus on substantial new information regarding the relation of electrical brain rhythms to sleep. In particular, while REM sleep may contribute to the homeostatic weakening of overactive synapses, a prominent and transient oscillatory rhythm called "sharp-wave ripple" seems to allow for consolidation of behaviorally relevant memories across many structures of the brain. We propose that a theory of sleep involving the division of labor between two states of sleep-REM and non-REM, the latter of which has an abundance of ripple electrical activity-might allow for a fusion of the two main sleep theories. This theory then postulates that sleep performs a combination of consolidation and homeostasis that promotes optimal knowledge retention as well as optimal waking brain function.

Straight trajectory planning for keyhole neurosurgery in sheep with automatic brain structures segmentation

NASA Astrophysics Data System (ADS)

Favaro, Alberto; Lad, Akash; Formenti, Davide; Zani, Davide Danilo; De Momi, Elena

2017-03-01

In a translational neuroscience/neurosurgery perspective, sheep are considered good candidates to study because of the similarity between their brain and the human one. Automatic planning systems for safe keyhole neurosurgery maximize the probe/catheter distance from vessels and risky structures. This work consists in the development of a trajectories planner for straight catheters placement intended to be used for investigating the drug diffusivity mechanisms in sheep brain. Automatic brain segmentation of gray matter, white matter and cerebrospinal fluid is achieved using an online available sheep atlas. Ventricles, midbrain and cerebellum segmentation have been also carried out. The veterinary surgeon is asked to select a target point within the white matter to be reached by the probe and to define an entry area on the brain cortex. To mitigate the risk of hemorrhage during the insertion process, which can prevent the success of the insertion procedure, the trajectory planner performs a curvature analysis of the brain cortex and wipes out from the poll of possible entry points the sulci, as part of brain cortex where superficial blood vessels are naturally located. A limited set of trajectories is then computed and presented to the surgeon, satisfying an optimality criteria based on a cost function which considers the distance from critical brain areas and the whole trajectory length. The planner proved to be effective in defining rectilinear trajectories accounting for the safety constraints determined by the brain morphology. It also demonstrated a short computational time and good capability in segmenting gyri and sulci surfaces.

Disrupted Structural Brain Network in AD and aMCI: A Finding of Long Fiber Degeneration.

PubMed

Fang, Rong; Yan, Xiao-Xiao; Wu, Zhi-Yuan; Sun, Yu; Yin, Qi-Hua; Wang, Ying; Tang, Hui-Dong; Sun, Jun-Feng; Miao, Fei; Chen, Sheng-Di

2015-01-01

Although recent evidence has emerged that Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) patients show both regional brain abnormalities and topological degeneration in brain networks, our understanding of the effects of white matter fiber aberrations on brain network topology in AD and aMCI is still rudimentary. In this study, we investigated the regional volumetric aberrations and the global topological abnormalities in AD and aMCI patients. The results showed a widely distributed atrophy in both gray and white matters in the AD and aMCI groups. In particular, AD patients had weaker connectivity with long fiber length than aMCI and normal control (NC) groups, as assessed by fractional anisotropy (FA). Furthermore, the brain networks of all three groups exhibited prominent economical small-world properties. Interestingly, the topological characteristics estimated from binary brain networks showed no significant group effect, indicating a tendency of preserving an optimal topological architecture in AD and aMCI during degeneration. However, significantly longer characteristic path length was observed in the FA weighted brain networks of AD and aMCI patients, suggesting dysfunctional global integration. Moreover, the abnormality of the characteristic path length was negatively correlated with the clinical ratings of cognitive impairment. Thus, the results therefore suggested that the topological alterations in weighted brain networks of AD are induced by the loss of connectivity with long fiber lengths. Our findings provide new insights into the alterations of the brain network in AD and may indicate the predictive value of the network metrics as biomarkers of disease development.

Automated MRI segmentation for individualized modeling of current flow in the human head.

PubMed

Huang, Yu; Dmochowski, Jacek P; Su, Yuzhuo; Datta, Abhishek; Rorden, Christopher; Parra, Lucas C

2013-12-01

High-definition transcranial direct current stimulation (HD-tDCS) and high-density electroencephalography require accurate models of current flow for precise targeting and current source reconstruction. At a minimum, such modeling must capture the idiosyncratic anatomy of the brain, cerebrospinal fluid (CSF) and skull for each individual subject. Currently, the process to build such high-resolution individualized models from structural magnetic resonance images requires labor-intensive manual segmentation, even when utilizing available automated segmentation tools. Also, accurate placement of many high-density electrodes on an individual scalp is a tedious procedure. The goal was to develop fully automated techniques to reduce the manual effort in such a modeling process. A fully automated segmentation technique based on Statical Parametric Mapping 8, including an improved tissue probability map and an automated correction routine for segmentation errors, was developed, along with an automated electrode placement tool for high-density arrays. The performance of these automated routines was evaluated against results from manual segmentation on four healthy subjects and seven stroke patients. The criteria include segmentation accuracy, the difference of current flow distributions in resulting HD-tDCS models and the optimized current flow intensities on cortical targets. The segmentation tool can segment out not just the brain but also provide accurate results for CSF, skull and other soft tissues with a field of view extending to the neck. Compared to manual results, automated segmentation deviates by only 7% and 18% for normal and stroke subjects, respectively. The predicted electric fields in the brain deviate by 12% and 29% respectively, which is well within the variability observed for various modeling choices. Finally, optimized current flow intensities on cortical targets do not differ significantly. Fully automated individualized modeling may now be feasible for large-sample EEG research studies and tDCS clinical trials.

GRAPE: a graphical pipeline environment for image analysis in adaptive magnetic resonance imaging.

PubMed

Gabr, Refaat E; Tefera, Getaneh B; Allen, William J; Pednekar, Amol S; Narayana, Ponnada A

2017-03-01

We present a platform, GRAphical Pipeline Environment (GRAPE), to facilitate the development of patient-adaptive magnetic resonance imaging (MRI) protocols. GRAPE is an open-source project implemented in the Qt C++ framework to enable graphical creation, execution, and debugging of real-time image analysis algorithms integrated with the MRI scanner. The platform provides the tools and infrastructure to design new algorithms, and build and execute an array of image analysis routines, and provides a mechanism to include existing analysis libraries, all within a graphical environment. The application of GRAPE is demonstrated in multiple MRI applications, and the software is described in detail for both the user and the developer. GRAPE was successfully used to implement and execute three applications in MRI of the brain, performed on a 3.0-T MRI scanner: (i) a multi-parametric pipeline for segmenting the brain tissue and detecting lesions in multiple sclerosis (MS), (ii) patient-specific optimization of the 3D fluid-attenuated inversion recovery MRI scan parameters to enhance the contrast of brain lesions in MS, and (iii) an algebraic image method for combining two MR images for improved lesion contrast. GRAPE allows graphical development and execution of image analysis algorithms for inline, real-time, and adaptive MRI applications.

Do you believe in brain training? A questionnaire about expectations of computerised cognitive training.

PubMed

Rabipour, Sheida; Davidson, Patrick S R

2015-12-15

"Brain training" (i.e., enhancing, rehabilitating, or simply maintaining cognitive function through deliberate cognitive exercise) is growing rapidly in popularity, yet remains highly controversial. Among the greatest problems in current research is the lack of a measure of participants' expectations, which can influence the degree to which they improve over training (i.e., the placebo effect). Here we created a questionnaire to measure the perceived effectiveness of brain-training software. Given the growth in advertising of these programmes, we sought to determine whether even a brief positive (or negative) message about brain training would increase (or decrease) the reported optimism of participants. We measured participants' expectations at baseline, and then following exposure to separate, brief messages that such programmes have either high or low effectiveness. Based on the knowledge they have gleaned from advertising and other real-world sources, people are relatively optimistic about brain training. However, brief messages can influence reported expectations about brain-training results: Reading a brief positive message can increase reported optimism, whereas reading a brief negative message can decrease it. Older adults appear more optimistic about brain training than young adults, especially when they report being knowledgeable about brain training and computers. These data indicate that perceptions of brain training are malleable to at least some extent, and may vary depending on age and other factors. Our questionnaire can serve as a simple, easily-incorporated tool to assess the face validity of brain training interventions and to create a covariate to account for expectations in statistical analyses. Copyright © 2015 Elsevier B.V. All rights reserved.

Nanomedicine in Central Nervous System (CNS) Disorders: A Present and Future Prospective

PubMed Central

Soni, Shringika; Ruhela, Rakesh Kumar; Medhi, Bikash

2016-01-01

Purpose: For the past few decades central nervous system disorders were considered as a major strike on human health and social system of developing countries. The natural therapeutic methods for CNS disorders limited for many patients. Moreover, nanotechnology-based drug delivery to the brain may an exciting and promising platform to overcome the problem of BBB crossing. In this review, first we focused on the role of the blood-brain barrier in drug delivery; and second, we summarized synthesis methods of nanomedicine and their role in different CNS disorder. Method: We reviewed the PubMed databases and extracted several kinds of literature on neuro nanomedicines using keywords, CNS disorders, nanomedicine, and nanotechnology. The inclusion criteria included chemical and green synthesis methods for synthesis of nanoparticles encapsulated drugs and, their in-vivo and in-vitro studies. We excluded nanomedicine gene therapy and nanomaterial in brain imaging. Results: In this review, we tried to identify a highly efficient method for nanomedicine synthesis and their efficacy in neuronal disorders. SLN and PNP encapsulated drugs reported highly efficient by easily crossing BBB. Although, these neuro-nanomedicine play significant role in therapeutics but some metallic nanoparticles reported the adverse effect on developing the brain. Conclusion: Although impressive advancement has made via innovative potential drug development, but their efficacy is still moderate due to limited brain permeability. To overcome this constraint,powerful tool in CNS therapeutic intervention provided by nanotechnology-based drug delivery methods. Due to its small and biofunctionalization characteristics, nanomedicine can easily penetrate and facilitate the drug through the barrier. But still, understanding of their toxicity level, optimization and standardization are a long way to go. PMID:27766216

Perinatal programming of emotional brain circuits: an integrative view from systems to molecules

PubMed Central

Bock, Jörg; Rether, Kathy; Gröger, Nicole; Xie, Lan; Braun, Katharina

2014-01-01

Environmental influences such as perinatal stress have been shown to program the developing organism to adapt brain and behavioral functions to cope with daily life challenges. Evidence is now accumulating that the specific and individual effects of early life adversity on the functional development of brain and behavior emerge as a function of the type, intensity, timing and the duration of the adverse environment, and that early life stress (ELS) is a major risk factor for developing behavioral dysfunctions and mental disorders. Results from clinical as well as experimental studies in animal models support the hypothesis that ELS can induce functional “scars” in prefrontal and limbic brain areas, regions that are essential for emotional control, learning and memory functions. On the other hand, the concept of “stress inoculation” is emerging from more recent research, which revealed positive functional adaptations in response to ELS resulting in resilience against stress and other adversities later in life. Moreover, recent studies indicate that early life experiences and the resulting behavioral consequences can be transmitted to the next generation, leading to a transgenerational cycle of adverse or positive adaptations of brain function and behavior. In this review we propose a unifying view of stress vulnerability and resilience by connecting genetic predisposition and programming sensitivity to the context of experience-expectancy and transgenerational epigenetic traits. The adaptive maturation of stress responsive neural and endocrine systems requires environmental challenges to optimize their functions. Repeated environmental challenges can be viewed within the framework of the match/mismatch hypothesis, the outcome, psychopathology or resilience, depends on the respective predisposition and on the context later in life. PMID:24550772

Brain-penetrating 2-aminobenzimidazole H(1)-antihistamines for the treatment of insomnia.

PubMed

Coon, Timothy; Moree, Wilna J; Li, Binfeng; Yu, Jinghua; Zamani-Kord, Said; Malany, Siobhan; Santos, Mark A; Hernandez, Lisa M; Petroski, Robert E; Sun, Aixia; Wen, Jenny; Sullivan, Sue; Haelewyn, Jason; Hedrick, Michael; Hoare, Samuel J; Bradbury, Margaret J; Crowe, Paul D; Beaton, Graham

2009-08-01

The benzimidazole core of the selective non-brain-penetrating H(1)-antihistamine mizolastine was used to identify a series of brain-penetrating H(1)-antihistamines for the potential treatment of insomnia. Using cassette PK studies, brain-penetrating H(1)-antihistamines were identified and in vivo efficacy was demonstrated in a rat EEG/EMG model. Further optimization focused on strategies to attenuate an identified hERG liability, leading to the discovery of 4i with a promising in vitro profile.

Evolutionary algorithm optimization of biological learning parameters in a biomimetic neuroprosthesis

PubMed Central

Dura-Bernal, S.; Neymotin, S. A.; Kerr, C. C.; Sivagnanam, S.; Majumdar, A.; Francis, J. T.; Lytton, W. W.

2017-01-01

Biomimetic simulation permits neuroscientists to better understand the complex neuronal dynamics of the brain. Embedding a biomimetic simulation in a closed-loop neuroprosthesis, which can read and write signals from the brain, will permit applications for amelioration of motor, psychiatric, and memory-related brain disorders. Biomimetic neuroprostheses require real-time adaptation to changes in the external environment, thus constituting an example of a dynamic data-driven application system. As model fidelity increases, so does the number of parameters and the complexity of finding appropriate parameter configurations. Instead of adapting synaptic weights via machine learning, we employed major biological learning methods: spike-timing dependent plasticity and reinforcement learning. We optimized the learning metaparameters using evolutionary algorithms, which were implemented in parallel and which used an island model approach to obtain sufficient speed. We employed these methods to train a cortical spiking model to utilize macaque brain activity, indicating a selected target, to drive a virtual musculoskeletal arm with realistic anatomical and biomechanical properties to reach to that target. The optimized system was able to reproduce macaque data from a comparable experimental motor task. These techniques can be used to efficiently tune the parameters of multiscale systems, linking realistic neuronal dynamics to behavior, and thus providing a useful tool for neuroscience and neuroprosthetics. PMID:29200477

Optimization of Evans blue quantitation in limited rat tissue samples

PubMed Central

Wang, Hwai-Lee; Lai, Ted Weita

2014-01-01

Evans blue dye (EBD) is an inert tracer that measures plasma volume in human subjects and vascular permeability in animal models. Quantitation of EBD can be difficult when dye concentration in the sample is limited, such as when extravasated dye is measured in the blood-brain barrier (BBB) intact brain. The procedure described here used a very small volume (30 µl) per sample replicate, which enabled high-throughput measurements of the EBD concentration based on a standard 96-well plate reader. First, ethanol ensured a consistent optic path length in each well and substantially enhanced the sensitivity of EBD fluorescence spectroscopy. Second, trichloroacetic acid (TCA) removed false-positive EBD measurements as a result of biological solutes and partially extracted EBD into the supernatant. Moreover, a 1:2 volume ratio of 50% TCA ([TCA final] = 33.3%) optimally extracted EBD from the rat plasma protein-EBD complex in vitro and in vivo, and 1:2 and 1:3 weight-volume ratios of 50% TCA optimally extracted extravasated EBD from the rat brain and liver, respectively, in vivo. This procedure is particularly useful in the detection of EBD extravasation into the BBB-intact brain, but it can also be applied to detect dye extravasation into tissues where vascular permeability is less limiting. PMID:25300427

Optimization of Evans blue quantitation in limited rat tissue samples

NASA Astrophysics Data System (ADS)

Wang, Hwai-Lee; Lai, Ted Weita

2014-10-01

Evans blue dye (EBD) is an inert tracer that measures plasma volume in human subjects and vascular permeability in animal models. Quantitation of EBD can be difficult when dye concentration in the sample is limited, such as when extravasated dye is measured in the blood-brain barrier (BBB) intact brain. The procedure described here used a very small volume (30 µl) per sample replicate, which enabled high-throughput measurements of the EBD concentration based on a standard 96-well plate reader. First, ethanol ensured a consistent optic path length in each well and substantially enhanced the sensitivity of EBD fluorescence spectroscopy. Second, trichloroacetic acid (TCA) removed false-positive EBD measurements as a result of biological solutes and partially extracted EBD into the supernatant. Moreover, a 1:2 volume ratio of 50% TCA ([TCA final] = 33.3%) optimally extracted EBD from the rat plasma protein-EBD complex in vitro and in vivo, and 1:2 and 1:3 weight-volume ratios of 50% TCA optimally extracted extravasated EBD from the rat brain and liver, respectively, in vivo. This procedure is particularly useful in the detection of EBD extravasation into the BBB-intact brain, but it can also be applied to detect dye extravasation into tissues where vascular permeability is less limiting.

SAR and scan-time optimized 3D whole-brain double inversion recovery imaging at 7T.

PubMed

Pracht, Eberhard D; Feiweier, Thorsten; Ehses, Philipp; Brenner, Daniel; Roebroeck, Alard; Weber, Bernd; Stöcker, Tony

2018-05-01

The aim of this project was to implement an ultra-high field (UHF) optimized double inversion recovery (DIR) sequence for gray matter (GM) imaging, enabling whole brain coverage in short acquisition times ( ≈5 min, image resolution 1 mm 3 ). A 3D variable flip angle DIR turbo spin echo (TSE) sequence was optimized for UHF application. We implemented an improved, fast, and specific absorption rate (SAR) efficient TSE imaging module, utilizing improved reordering. The DIR preparation was tailored to UHF application. Additionally, fat artifacts were minimized by employing water excitation instead of fat saturation. GM images, covering the whole brain, were acquired in 7 min scan time at 1 mm isotropic resolution. SAR issues were overcome by using a dedicated flip angle calculation considering SAR and SNR efficiency. Furthermore, UHF related artifacts were minimized. The suggested sequence is suitable to generate GM images with whole-brain coverage at UHF. Due to the short total acquisition times and overall robustness, this approach can potentially enable DIR application in a routine setting and enhance lesion detection in neurological diseases. Magn Reson Med 79:2620-2628, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A National Network of Neurotechnology Centers for the BRAIN Initiative

PubMed Central

Alivisatos, A. Paul; Chun, Miyoung; Church, George M.; Greenspan, Ralph J.; Roukes, Michael L.; Yuste, Rafael

2017-01-01

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As “brain observatories,” these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them. PMID:26481036

ABC transporters P-gp and Bcrp do not limit the brain uptake of the novel antipsychotic and anticonvulsant drug cannabidiol in mice

PubMed Central

Brzozowska, Natalia; Li, Kong M.; Wang, Xiao Suo; Booth, Jessica; Stuart, Jordyn; McGregor, Iain S.

2016-01-01

Cannabidiol (CBD) is currently being investigated as a novel therapeutic for the treatment of CNS disorders like schizophrenia and epilepsy. ABC transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp) mediate pharmacoresistance in these disorders. P-gp and Bcrp are expressed at the blood brain barrier (BBB) and reduce the brain uptake of substrate drugs including various antipsychotics and anticonvulsants. It is therefore important to assess whether CBD is prone to treatment resistance mediated by P-gp and Bcrp. Moreover, it has become common practice in the drug development of CNS agents to screen against ABC transporters to help isolate lead compounds with optimal pharmacokinetic properties. The current study aimed to assess whether P-gp and Bcrp impacts the brain transport of CBD by comparing CBD tissue concentrations in wild-type (WT) mice versus mice devoid of ABC transporter genes. P-gp knockout (Abcb1a/b−∕−), Bcrp knockout (Abcg2−∕−), combined P-gp/Bcrp knockout (Abcb1a/b−∕−Abcg2−∕−) and WT mice were injected with CBD, before brain and plasma samples were collected at various time-points. CBD results were compared with the positive control risperidone and 9-hydroxy risperidone, antipsychotic drugs that are established ABC transporter substrates. Brain and plasma concentrations of CBD were not greater in P-gp, Bcrp or P-gp/Bcrp knockout mice than WT mice. In comparison, the brain/plasma concentration ratios of risperidone and 9-hydroxy risperidone were profoundly higher in P-gp knockout mice than WT mice. These results suggest that CBD is not a substrate of P-gp or Bcrp and may be free from the complication of reduced brain uptake by these transporters. Such findings provide favorable evidence for the therapeutic development of CBD in the treatment of various CNS disorders. PMID:27257556

ABC transporters P-gp and Bcrp do not limit the brain uptake of the novel antipsychotic and anticonvulsant drug cannabidiol in mice.

PubMed

Brzozowska, Natalia; Li, Kong M; Wang, Xiao Suo; Booth, Jessica; Stuart, Jordyn; McGregor, Iain S; Arnold, Jonathon C

2016-01-01

Cannabidiol (CBD) is currently being investigated as a novel therapeutic for the treatment of CNS disorders like schizophrenia and epilepsy. ABC transporters such as P-glycoprotein (P-gp) and breast cancer resistance protein (Bcrp) mediate pharmacoresistance in these disorders. P-gp and Bcrp are expressed at the blood brain barrier (BBB) and reduce the brain uptake of substrate drugs including various antipsychotics and anticonvulsants. It is therefore important to assess whether CBD is prone to treatment resistance mediated by P-gp and Bcrp. Moreover, it has become common practice in the drug development of CNS agents to screen against ABC transporters to help isolate lead compounds with optimal pharmacokinetic properties. The current study aimed to assess whether P-gp and Bcrp impacts the brain transport of CBD by comparing CBD tissue concentrations in wild-type (WT) mice versus mice devoid of ABC transporter genes. P-gp knockout (Abcb1a/b (-∕-)), Bcrp knockout (Abcg2 (-∕-)), combined P-gp/Bcrp knockout (Abcb1a/b (-∕-) Abcg2 (-∕-)) and WT mice were injected with CBD, before brain and plasma samples were collected at various time-points. CBD results were compared with the positive control risperidone and 9-hydroxy risperidone, antipsychotic drugs that are established ABC transporter substrates. Brain and plasma concentrations of CBD were not greater in P-gp, Bcrp or P-gp/Bcrp knockout mice than WT mice. In comparison, the brain/plasma concentration ratios of risperidone and 9-hydroxy risperidone were profoundly higher in P-gp knockout mice than WT mice. These results suggest that CBD is not a substrate of P-gp or Bcrp and may be free from the complication of reduced brain uptake by these transporters. Such findings provide favorable evidence for the therapeutic development of CBD in the treatment of various CNS disorders.

Whole Brain Irradiation With Hippocampal Sparing and Dose Escalation on Multiple Brain Metastases: A Planning Study on Treatment Concepts

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

Prokic, Vesna, E-mail: vesna.prokic@uniklinik-freiburg.de; Wiedenmann, Nicole; Fels, Franziska

2013-01-01

Purpose: To develop a new treatment planning strategy in patients with multiple brain metastases. The goal was to perform whole brain irradiation (WBI) with hippocampal sparing and dose escalation on multiple brain metastases. Two treatment concepts were investigated: simultaneously integrated boost (SIB) and WBI followed by stereotactic fractionated radiation therapy sequential concept (SC). Methods and Materials: Treatment plans for both concepts were calculated for 10 patients with 2-8 brain metastases using volumetric modulated arc therapy. In the SIB concept, the prescribed dose was 30 Gy in 12 fractions to the whole brain and 51 Gy in 12 fractions to individualmore » brain metastases. In the SC concept, the prescription was 30 Gy in 12 fractions to the whole brain followed by 18 Gy in 2 fractions to brain metastases. All plans were optimized for dose coverage of whole brain and lesions, simultaneously minimizing dose to the hippocampus. The treatment plans were evaluated on target coverage, homogeneity, and minimal dose to the hippocampus and organs at risk. Results: The SIB concept enabled more successful sparing of the hippocampus; the mean dose to the hippocampus was 7.55 {+-} 0.62 Gy and 6.29 {+-} 0.62 Gy, respectively, when 5-mm and 10-mm avoidance regions around the hippocampus were used, normalized to 2-Gy fractions. In the SC concept, the mean dose to hippocampus was 9.8 {+-} 1.75 Gy. The mean dose to the whole brain (excluding metastases) was 33.2 {+-} 0.7 Gy and 32.7 {+-} 0.96 Gy, respectively, in the SIB concept, for 5-mm and 10-mm hippocampus avoidance regions, and 37.23 {+-} 1.42 Gy in SC. Conclusions: Both concepts, SIB and SC, were able to achieve adequate whole brain coverage and radiosurgery-equivalent dose distributions to individual brain metastases. The SIB technique achieved better sparing of the hippocampus, especially when a10-mm hippocampal avoidance region was used.« less

A D-D/D-T fusion reaction based neutron generator system for liver tumor BNCT

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

Koivunoro, H.; Lou, T.P.; Leung, K. N.

2003-04-02

Boron-neutron capture therapy (BNCT) is an experimental radiation treatment modality used for highly malignant tumor treatments. Prior to irradiation with low energetic neutrons, a 10B compound is located selectively in the tumor cells. The effect of the treatment is based on the high LET radiation released in the {sup 10}B(n,{alpha}){sup 7}Li reaction with thermal neutrons. BNCT has been used experimentally for brain tumor and melanoma treatments. Lately applications of other severe tumor type treatments have been introduced. Results have shown that liver tumors can also be treated by BNCT. At Lawrence Berkeley National Laboratory, various compact neutron generators based onmore » D-D or D-T fusion reactions are being developed. The earlier theoretical studies of the D-D or D-T fusion reaction based neutron generators have shown that the optimal moderator and reflector configuration for brain tumor BNCT can be created. In this work, the applicability of 2.5 MeV neutrons for liver tumor BNCT application was studied. The optimal neutron energy for external liver treatments is not known. Neutron beams of different energies (1eV < E < 100 keV) were simulated and the dose distribution in the liver was calculated with the MCNP simulation code. In order to obtain the optimal neutron energy spectrum with the D-D neutrons, various moderator designs were performed using MCNP simulations. In this article the neutron spectrum and the optimized beam shaping assembly for liver tumor treatments is presented.« less

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

PubMed

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

2018-05-01

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

Test-Retest Reliability of fMRI Brain Activity during Memory Encoding

PubMed Central

Brandt, David J.; Sommer, Jens; Krach, Sören; Bedenbender, Johannes; Kircher, Tilo; Paulus, Frieder M.; Jansen, Andreas

2013-01-01

The mechanisms underlying hemispheric specialization of memory are not completely understood. Functional magnetic resonance imaging (fMRI) can be used to develop and test models of hemispheric specialization. In particular for memory tasks however, the interpretation of fMRI results is often hampered by the low reliability of the data. In the present study we therefore analyzed the test-retest reliability of fMRI brain activation related to an implicit memory encoding task, with a particular focus on brain activity of the medial temporal lobe (MTL). Fifteen healthy subjects were scanned with fMRI on two sessions (average retest interval 35 days) using a commonly applied novelty encoding paradigm contrasting known and unknown stimuli. To assess brain lateralization, we used three different stimuli classes that differed in their verbalizability (words, scenes, fractals). Test-retest reliability of fMRI brain activation was assessed by an intraclass-correlation coefficient (ICC), describing the stability of inter-individual differences in the brain activation magnitude over time. We found as expected a left-lateralized brain activation network for the words paradigm, a bilateral network for the scenes paradigm, and predominantly right-hemispheric brain activation for the fractals paradigm. Although these networks were consistently activated in both sessions on the group level, across-subject reliabilities were only poor to fair (ICCs ≤ 0.45). Overall, the highest ICC values were obtained for the scenes paradigm, but only in strongly activated brain regions. In particular the reliability of brain activity of the MTL was poor for all paradigms. In conclusion, for novelty encoding paradigms the interpretation of fMRI results on a single subject level is hampered by its low reliability. More studies are needed to optimize the retest reliability of fMRI activation for memory tasks. PMID:24367338

Experimental missile wound to the brain.

PubMed

Carey, M E; Sarna, G S; Farrell, J B; Happel, L T

1989-11-01

Among civilians in the United States, 33,000 gunshot wound deaths occur each year; probably half of these involve the head. In combat, head wounds account for approximately half of the immediate mortality when death can be attributed to a single wound. No significant reduction in the neurosurgical mortality associated with these wounds has occurred between World War II and the Vietnam conflict, and very little research into missile wounds of the brain has been undertaken. An experimental model has been developed in the anesthetized cat whereby a ballistic injury to the brain may be painlessly reproduced in order that the pathophysiological effects of brain wounding may be studied and better treatments may be designed to lower the mortality and morbidity rates associated with gunshot wounds. Prominent among physiological effects observed in this model was respiratory arrest even though the missile did not injure the brain stem directly. The incidence of prolonged respiratory arrest increased with increasing missile energy, but arrest was often reversible provided respiratory support was given. It is possible that humans who receive a brain wound die from missile-induced apnea instead of brain damage per se. The mortality rate in humans with brain wounding might be reduced by prompt respiratory support. Brain wounding was associated with persistently increased intracranial pressure and reduced cerebral perfusion pressure not entirely attributable to intracranial bleeding. The magnitude of these derangements appeared to be missile energy-dependent and approached dangerous levels in higher-energy wounds. All wounded cats exhibited postwounding increases in blood glucose concentrations consistent with a generalized stress reaction. A transient rise in hematocrit also occurred immediately after wounding. Both of these phenomena could prove deleterious to optimal brain function after injury.

Enhanced Delivery of Galanin Conjugates to the Brain through Bioengineering of the Anti-Transferrin Receptor Antibody OX26.

PubMed

Thom, George; Burrell, Matthew; Haqqani, Arsalan S; Yogi, Alvaro; Lessard, Etienne; Brunette, Eric; Delaney, Christie; Baumann, Ewa; Callaghan, Deborah; Rodrigo, Natalia; Webster, Carl I; Stanimirovic, Danica B

2018-04-02

The blood-brain barrier (BBB) is a formidable obstacle for brain delivery of therapeutic antibodies. However, antibodies against the transferrin receptor (TfR), enriched in brain endothelial cells, have been developed as delivery carriers of therapeutic cargoes into the brain via a receptor-mediated transcytosis pathway. In vitro and in vivo studies demonstrated that either a low-affinity or monovalent binding of these antibodies to the TfR improves their release on the abluminal side of the BBB and target engagement in brain parenchyma. However, these studies have been performed with mouse-selective TfR antibodies that recognize different TfR epitopes and have varied binding characteristics. In this study, we evaluated serum pharmacokinetics and brain and CSF exposure of the rat TfR-binding antibody OX26 affinity variants, having K D s of 5 nM, 76 nM, 108 nM, and 174 nM, all binding the same epitope in bivalent format. Pharmacodynamic responses were tested in the Hargreaves chronic pain model after conjugation of OX26 affinity variants with the analgesic and antiepileptic peptide, galanin. OX26 variants with affinities of 76 nM and 108 nM showed enhanced brain and cerebrospinal fluid (CSF) exposure and higher potency in the Hargreaves model, compared to a 5 nM affinity variant; lowering affinity to 174 nM resulted in prolonged serum pharmacokinetics, but reduced brain and CSF exposure. The study demonstrates that binding affinity optimization of TfR-binding antibodies could improve their brain and CSF exposure even in the absence of monovalent TfR engagement.

Optimized retrograde cerebral perfusion reduces ischemic energy depletion.

PubMed

Oda, Teiji; Kimura, Tetsuhiro; Ogata, Yoshitaka; Fujise, Yutaka

2004-01-01

It has been reported that retrograde cerebral perfusion (RCP) provides minimal capillary flow; however, the extent to which RCP can provide aerobic metabolic support is unknown. We evaluated whether perfusate composition optimization for RCP would preserve brain energy metabolism during hypothermic circulatory arrest (HCA) at 20 degrees C in rats. Three types of perfusates were prepared: hemoglobin-free saline, rat red blood cells, and artificial blood substitute (liposome-encapsulated hemoglobin); perfusates were made hypertonic, cooled to 20 degrees C, and oxygenated and CO(2) was administered (pH-stat management). Circulatory arrest was induced in 24 pH-stat-ventilated Wistar rats that had been surface cooled to 20 degrees C; 18 were assigned to the RCP group in which one of the three ( n = 6 each) perfusates was administered via the maxillary vein, and 6 received no perfusion. In two similarly surface-cooled rats (controls), brains were excised when the temperature reached 20 degrees C. After 20 min of RCP or HCA, brains were excised and immediately frozen; brain high-energy phosphates, adenosine, and water content were measured. The liposome-encapsulated hemoglobin perfusate preserved levels of brain tissue adenosine triphosphates and energy charge, but not significantly better than rat red blood cells. Both maintained significantly higher levels than perfusion with oxygenated saline or hypothermic circulatory arrest alone ( P = 0.0419-0.0001), under which regimes high-energy phosphates and energy charge declined to similar low values. RCP with hypertonic solution prevented brain edema. RCP with optimized composition perfusate (pH-stat, hypertonic rat red blood cells or liposome-encapsulated hemoglobin) reduced ischemic energy depletion during 20 min of HCA at 20 degrees C in rats.

Stochastic resonance in attention control

NASA Astrophysics Data System (ADS)

Kitajo, K.; Yamanaka, K.; Ward, L. M.; Yamamoto, Y.

2006-12-01

We investigated the beneficial role of noise in a human higher brain function, namely visual attention control. We asked subjects to detect a weak gray-level target inside a marker box either in the left or the right visual field. Signal detection performance was optimized by presenting a low level of randomly flickering gray-level noise between and outside the two possible target locations. Further, we found that an increase in eye movement (saccade) rate helped to compensate for the usual deterioration in detection performance at higher noise levels. To our knowledge, this is the first experimental evidence that noise can optimize a higher brain function which involves distinct brain regions above the level of primary sensory systems -- switching behavior between multi-stable attention states -- via the mechanism of stochastic resonance.

The Myth of Optimality in Clinical Neuroscience.

PubMed

Holmes, Avram J; Patrick, Lauren M

2018-03-01

Clear evidence supports a dimensional view of psychiatric illness. Within this framework the expression of disorder-relevant phenotypes is often interpreted as a breakdown or departure from normal brain function. Conversely, health is reified, conceptualized as possessing a single ideal state. We challenge this concept here, arguing that there is no universally optimal profile of brain functioning. The evolutionary forces that shape our species select for a staggering diversity of human behaviors. To support our position we highlight pervasive population-level variability within large-scale functional networks and discrete circuits. We propose that, instead of examining behaviors in isolation, psychiatric illnesses can be best understood through the study of domains of functioning and associated multivariate patterns of variation across distributed brain systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

The Affective Core of Emotion: Linking Pleasure, Subjective Well-Being, and Optimal Metastability in the Brain

PubMed Central

Kringelbach, Morten L.; Berridge, Kent C.

2017-01-01

Arguably, emotion is always valenced—either pleasant or unpleasant—and dependent on the pleasure system. This system serves adaptive evolutionary functions; relying on separable wanting, liking, and learning neural mechanisms mediated by mesocorticolimbic networks driving pleasure cycles with appetitive, consummatory, and satiation phases. Liking is generated in a small set of discrete hedonic hotspots and coldspots, while wanting is linked to dopamine and to larger distributed brain networks. Breakdown of the pleasure system can lead to anhedonia and other features of affective disorders. Eudaimonia and well-being are difficult to study empirically, yet whole-brain computational models could offer novel insights (e.g., routes to eudaimonia such as caregiving of infants or music) potentially linking eudaimonia to optimal metastability in the pleasure system. PMID:28943891

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

PubMed

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

1999-04-01

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

Neural connections foster social connections: a diffusion-weighted imaging study of social networks

PubMed Central

Hampton, William H.; Unger, Ashley; Von Der Heide, Rebecca J.

2016-01-01

Although we know the transition from childhood to adulthood is marked by important social and neural development, little is known about how social network size might affect neurocognitive development or vice versa. Neuroimaging research has identified several brain regions, such as the amygdala, as key to this affiliative behavior. However, white matter connectivity among these regions, and its behavioral correlates, remain unclear. Here we tested two hypotheses: that an amygdalocentric structural white matter network governs social affiliative behavior and that this network changes during adolescence and young adulthood. We measured social network size behaviorally, and white matter microstructure using probabilistic diffusion tensor imaging in a sample of neurologically normal adolescents and young adults. Our results suggest amygdala white matter microstructure is key to understanding individual differences in social network size, with connectivity to other social brain regions such as the orbitofrontal cortex and anterior temporal lobe predicting much variation. In addition, participant age correlated with both network size and white matter variation in this network. These findings suggest the transition to adulthood may constitute a critical period for the optimization of structural brain networks underlying affiliative behavior. PMID:26755769

Rat brain gamma-secretase activity is highly influenced by detergents.

PubMed

Frånberg, Jenny; Welander, Hedvig; Aoki, Mikio; Winblad, Bengt; Tjernberg, Lars O; Frykman, Susanne

2007-06-26

Gamma-secretase is important for the development of Alzheimer's disease, since it is a crucial enzyme for the generation of the pathogenic amyloid beta-peptide (Abeta). Most data on gamma-secretase is derived from studies in cell lines overexpressing gamma-secretase components or amyloid precursor protein (APP), and since gamma-secretase is a transmembrane protein complex, detergents have been frequently used to facilitate the studies. However, no extensive comparison of the influence of different detergents at different concentrations on gamma-secretase activity in preparations from brain has been made. Here, we establish the optimal conditions for gamma-secretase activity in rat brain, using an activity assay detecting endogenous production of the APP intracellular domain, which is generated when gamma-secretase cleaves the APP C-terminal fragments. We performed a subcellular fractionation and noted the highest gamma-secretase activity in the 100000g pellet and that the optimal pH was around 7. We found that gamma-secretase was active for at least 16 h at 37 degrees C and that the endogenous substrate levels were sufficient for activity measurements. The highest activity was obtained in 0.4% CHAPSO, which is slightly below the critical micelle concentration (0.5%) for this detergent, but the complex was not solubilized efficiently at this concentration. On the other hand, 1% CHAPSO solubilized a substantial amount of the gamma-secretase components, but the activity was low. The activity was fully restored by diluting the sample to 0.4% CHAPSO. Therefore, using 1% CHAPSO for solubilization and subsequently diluting the sample to 0.4% is an appropriate procedure for obtaining a soluble, highly active gamma-secretase from rat brain.

The role of angiogenesis in damage and recovery from ischemic stroke.

PubMed

Arenillas, Juan F; Sobrino, Tomás; Castillo, José; Dávalos, Antoni

2007-06-01

Ischemic stroke is burdened with a high morbidity and mortality in our society. However, there are few effective and largely available therapies for this devastating disease. In additon to advancing acute reperfusion therapies, there is a need to develop treatments aimed to promote repair and regeneration of brain tissue damaged by ischemia (neurorecovery). Therapeutic angiogenesis and vasculogenesis represent novel approaches of regenerative medicine that may help in the cure of patients with acute ischemic stroke. Translation of our knowledge about these processes from the bench to bedside is still underway. Although angiogenesis (the sprouting of new blood vessels from pre-existing vascular structures) is likely to contribute to neurorepair, the finality of the angiogenic response in acute ischemic stroke has not been fully elucidated. The first therapeutic approach to angiogenesis after ischemic stroke would be the modulation of the endogenous angiogenic response. In this setting, early instauration of physical activity, statins, and peroxisome proliferator-activated receptor-gamma agonists may enhance angiogenesis and neuroregeneration. Gene therapy with vascular growth factors has been successfully tested in patients affected by chronic myocardial and peripheral ischemia. Regarding brain ischemia, experiments in animal models have shown that the effect of these growth factors is critically affected by the dosage, route of delivery, and time of administration in relation to stroke onset. In addition, the optimal angiogenic substance is unknown. Finally, vectors for gene transfer should be further optimized. Therapeutic vasculogenesis consists of the administration of exogenous endothelial progenitor cells in order to enhance brain repair processes. Endothelial progenitor cells may be recruited in response to cerebral ischemia and participate in reparative vasculogenesis after acute ischemic stroke. Further research is needed to clarify their role and therapeutic applicability in human brain ischemia.

Optical dosimetry probes to validate Monte Carlo and empirical-method-based NIR dose planning in the brain.

PubMed

Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M

2016-12-01

A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R²0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.

Neonatal Seizures: Advances in Mechanisms and Management

PubMed Central

Glass, Hannah C.

2013-01-01

Synopsis Seizures occur in approximately 1–5 per 1,000 live births, and are among the most common neurologic conditions managed by a neonatal neurocritical care service. There are several, age-specific factors that are particular to the developing brain, which influence excitability and seizure generation, response to medications, and impact of seizures on brain structure and function. Neonatal seizures are often associated with serious underlying brain injury such as hypoxia-ischemia, stroke or hemorrhage. Conventional, prolonged, continuous video-electroencephalogram (cEEG) is the gold standard for detecting seizures, whereas amplitude-integrated EEG (aEEG) is a convenient and useful bedside tool. Evaluation of neonatal seizures involves a thorough search for the etiology of the seizures, and includes detailed clinical history, routine chemistries, neuroimaging (and preferably magnetic resonance imaging, MRI), and specialized testing such as screening for inborn errors of metabolism if no structural cause is identified and seizures persist after correction of transient metabolic deficits. Expert opinion supports rapid medical treatment to abolish electrographic seizures, however the relative risk versus benefit for aggressive medical treatment of neonatal seizures is not known. While there is increasing evidence to support a harmful effect of seizures on the developing brain, there is also evidence that commonly used medications are potentially neurotoxic in animal models. Newer agents appear less harmful, but data are lacking regarding optimal dosing and efficacy. PMID:24524454

[Monitoring of brain function].

PubMed

Doi, Matsuyuki

2012-01-01

Despite being the most important of organs, the brain is disproportionately unmonitored compared to other systems such as cardiorespiratory in anesthesia settings. In order to optimize level of anesthesia, it is important to quantify the brain activity suppressed by anesthetic agents. Adverse cerebral outcomes remain a continued problem in patients undergoing various surgical procedures. By providing information on a range of physiologic parameters, brain monitoring may contribute to improve perioperative outcomes. This article addresses the various brain monitoring equipments including bispectral index (BIS), auditory evoked potentials (AEP), near-infrared spectroscopy (NIRS), transcranial Doppler ultrasonography (TCD) and oxygen saturation of the jugular vein (Sjv(O2)).

Neurobiology of KB220Z-Glutaminergic-Dopaminergic Optimization Complex [GDOC] as a Liquid Nano: Clinical Activation of Brain in a Highly Functional Clinician Improving Focus, Motivation and Overall Sensory Input Following Chronic Intake.

PubMed

Duquette, Lucien L; Mattiace, Frank; Blum, Kenneth; Waite, Roger L; Boland, Teresa; McLaughlin, Thomas; Dushaj, Kristina; Febo, Marcelo; Badgaiyan, Rajendra D

2016-01-01

With neurogenetic and epigenetic tools utilized in research and neuroimaging, we are unraveling the mysteries of brain function, especially as it relates to Reward Deficiency (RDS). We encourage the development of pharmaceuticals or nutraceuticals that promote a reduction in dopamine resistance and balance brain neurochemistry, leading to dopamine homeostasis. We disclose self-assessment of a highly functional professional under work-related stress following KB220Z use, a liquid (aqua) nano glutaminergic-dopaminergic optimization complex (GDOC). Subject took GDOC for one month. Subject self-administered GDOC using one-half-ounce twice a day. During first three days, unique brain activation occurred; resembling white noise after 30 minutes and sensation was strong for 45 minutes and then dissipated. He described effect as if his eyesight improved slightly and pointed out that his sense of smell and sleep greatly improved. Subject experienced a calming effect similar to meditation that could be linked to dopamine release. He also reported control of going over the edge after a hard day's work, which was coupled with a slight increase in energy, increased motivation to work, increased focus and multi-tasking, with clearer purpose of task at hand. Subject felt less inhibited in a social setting and suggested Syndrome that GDOC increased his Behavior Activating System (reward), while having a decrease in the Behavior Inhibition System (caution). These results and other related studies reveal an improved mood, work-related focus, and sleep. These effects as a subjective feeling of brain activation maybe due to direct or indirect dopaminergic interaction. While this case is encouraging, we must await more research in a larger randomized placebo-controlled study to map the role of GDOC, especially in a nano-sized product, to determine the possible effects on circuit inhibitory control and memory banks and the induction of dopamine homeostasis independent of either hypo- or hyper-dopaminergic traits/states.

Restoring Behavior via Inverse Neurocontroller in a Lesioned Cortical Spiking Model Driving a Virtual Arm

PubMed Central

Dura-Bernal, Salvador; Li, Kan; Neymotin, Samuel A.; Francis, Joseph T.; Principe, Jose C.; Lytton, William W.

2016-01-01

Neural stimulation can be used as a tool to elicit natural sensations or behaviors by modulating neural activity. This can be potentially used to mitigate the damage of brain lesions or neural disorders. However, in order to obtain the optimal stimulation sequences, it is necessary to develop neural control methods, for example by constructing an inverse model of the target system. For real brains, this can be very challenging, and often unfeasible, as it requires repeatedly stimulating the neural system to obtain enough probing data, and depends on an unwarranted assumption of stationarity. By contrast, detailed brain simulations may provide an alternative testbed for understanding the interactions between ongoing neural activity and external stimulation. Unlike real brains, the artificial system can be probed extensively and precisely, and detailed output information is readily available. Here we employed a spiking network model of sensorimotor cortex trained to drive a realistic virtual musculoskeletal arm to reach a target. The network was then perturbed, in order to simulate a lesion, by either silencing neurons or removing synaptic connections. All lesions led to significant behvaioral impairments during the reaching task. The remaining cells were then systematically probed with a set of single and multiple-cell stimulations, and results were used to build an inverse model of the neural system. The inverse model was constructed using a kernel adaptive filtering method, and was used to predict the neural stimulation pattern required to recover the pre-lesion neural activity. Applying the derived neurostimulation to the lesioned network improved the reaching behavior performance. This work proposes a novel neurocontrol method, and provides theoretical groundwork on the use biomimetic brain models to develop and evaluate neurocontrollers that restore the function of damaged brain regions and the corresponding motor behaviors. PMID:26903796

Delivery of chemotherapeutics across the blood-brain barrier: challenges and advances.

PubMed

Doolittle, Nancy D; Muldoon, Leslie L; Culp, Aliana Y; Neuwelt, Edward A

2014-01-01

The blood-brain barrier (BBB) limits drug delivery to brain tumors. We utilize intraarterial infusion of hyperosmotic mannitol to reversibly open the BBB by shrinking endothelial cells and opening tight junctions between the cells. This approach transiently increases the delivery of chemotherapy, antibodies, and nanoparticles to brain. Our preclinical studies have optimized the BBB disruption (BBBD) technique and clinical studies have shown its safety and efficacy. The delivery of methotrexate-based chemotherapy in conjunction with BBBD provides excellent outcomes in primary central nervous system lymphoma (PCNSL) including stable or improved cognitive function in survivors a median of 12 years (range 2-26 years) after diagnosis. The addition of rituximab to chemotherapy with BBBD for PCNSL can be safely accomplished with excellent overall survival. Our translational studies of thiol agents to protect against platinum-induced toxicities led to the development of a two-compartment model in brain tumor patients. We showed that delayed high-dose sodium thiosulfate protects against carboplatin-induced hearing loss, providing the framework for large cooperative group trials of hearing chemoprotection. Neuroimaging studies have identified that ferumoxytol, an iron oxide nanoparticle blood pool agent, appears to be a superior contrast agent to accurately assess therapy-induced changes in brain tumor vasculature, in brain tumor response to therapy, and in differentiating central nervous system lesions with inflammatory components. This chapter reviews the breakthroughs, challenges, and future directions for BBBD. © 2014 Elsevier Inc. All rights reserved.

How the Brain Repairs Stuttering

ERIC Educational Resources Information Center

Kell, Christian A.; Neumann, Katrin; von Kriegstein, Katharina; Posenenske, Claudia; von Gudenberg, Alexander W.; Euler, Harald; Giraud, Anne-Lise

2009-01-01

Stuttering is a neurodevelopmental disorder associated with left inferior frontal structural anomalies. While children often recover, stuttering may also spontaneously disappear much later after years of dysfluency. These rare cases of unassisted recovery in adulthood provide a model of optimal brain repair outside the classical windows of…

Optimization of Glial Fibrillary Acidic Protein Immunoreactivity in Formalin-fixed, Paraffin-Embedded Guinea Pig Brain Sections

DTIC Science & Technology

2003-09-01

fixed, paraffin-embedded guinea pig brain sections using a variety of commercially available GFAP antibody clones. Of the 7 clones tested for cross...determining neuropathological consequences in the guinea pig following exposure to chemical warfare nerve agent.

A quest for antipsychotic drug actions in the brain: personal experiences from 50 years of neuropsychiatric research at Karolinska Institutet.

PubMed

Sedvall, Göran

2007-09-10

The exploration of physiological and molecular actions of psychoactive drugs in the brain represents a fundamental approach to the understanding of emerging psychological phenomena. The author gives a personal account of his medical training and research career at Karolinska Institutet over the past 50 years. The paper aims at illustrating how a broad medical education and the integration of basic and clinical neuroscience research is a fruitful ground for the development of new methods and knowledge in this complicated field. Important aspects for an optimal research environment are recruitment of well-educated students, a high intellectual identity of teachers and active researchers, international input and collaboration in addition to good physical resources. In depth exploration of specific signaling pathways as well as an integrative analysis of genes, molecules and systems using multivariate modeling, and bioinformatics, brain mechanisms behind mental phenomena may be understood at a basic level and will ultimately be used for the alleviation and treatment of mental disorders.

Pan-neuronal calcium imaging with cellular resolution in freely swimming zebrafish.

PubMed

Kim, Dal Hyung; Kim, Jungsoo; Marques, João C; Grama, Abhinav; Hildebrand, David G C; Gu, Wenchao; Li, Jennifer M; Robson, Drew N

2017-11-01

Calcium imaging with cellular resolution typically requires an animal to be tethered under a microscope, which substantially restricts the range of behaviors that can be studied. To expand the behavioral repertoire amenable to imaging, we have developed a tracking microscope that enables whole-brain calcium imaging with cellular resolution in freely swimming larval zebrafish. This microscope uses infrared imaging to track a target animal in a behavior arena. On the basis of the predicted trajectory of the animal, we applied optimal control theory to a motorized stage system to cancel brain motion in three dimensions. We combined this motion-cancellation system with differential illumination focal filtering, a variant of HiLo microscopy, which enabled us to image the brain of a freely swimming larval zebrafish for more than an hour. This work expands the repertoire of natural behaviors that can be studied with cellular-resolution calcium imaging to potentially include spatial navigation, social behavior, feeding and reward.

Endurance Exercise as an “Endogenous” Neuro-enhancement Strategy to Facilitate Motor Learning

PubMed Central

Taubert, Marco; Villringer, Arno; Lehmann, Nico

2015-01-01

Endurance exercise improves cardiovascular and musculoskeletal function and may also increase the information processing capacities of the brain. Animal and human research from the past decade demonstrated widespread exercise effects on brain structure and function at the systems-, cellular-, and molecular level of brain organization. These neurobiological mechanisms may explain the well-established positive influence of exercise on performance in various behavioral domains but also its contribution to improved skill learning and neuroplasticity. With respect to the latter, only few empirical and theoretical studies are available to date. The aim of this review is (i) to summarize the existing neurobiological and behavioral evidence arguing for endurance exercise-induced improvements in motor learning and (ii) to develop hypotheses about the mechanistic link between exercise and improved learning. We identify major knowledge gaps that need to be addressed by future research projects to advance our understanding of how exercise should be organized to optimize motor learning. PMID:26834602

Parallel Radiofrequency Transmission for the Reduction of Heating in Deep Brain Stimulation Leads at 3T

NASA Astrophysics Data System (ADS)

McElcheran, Clare

Deep Brain Stimulation (DBS) is increasingly used to treat a variety of brain diseases by sending electrical impulses to deep brain nuclei through long, electrically conductive leads. Magnetic resonance imaging (MRI) of patients pre- and post-implantation is desirable to target and position the implant, to evaluate possible side-effects and to examine DBS patients who have other health conditions. Although MRI is the preferred modality for pre-operative planning, MRI post-implantation is limited due to the risk of high local power deposition, and therefore tissue heating, at the tip of the lead. The localized power deposition arises from currents induced in the leads caused by coupling with the radiofrequency (RF) transmission field during imaging. In this thesis, parallel RF transmission (pTx) is used to tailor the RF electric field to suppress coupling effects. Three pTx coil configurations with 2-elements, 4-elements, and 8-elements, respectively, were investigated. Optimal input voltages to minimize coupling, while maintaining RF magnetic field homogeneity, were determined using a Nelder-Mead optimization algorithm. Resulting electric and magnetic fields were compared to that of a 16-rung birdcage coil. Experimental validation was performed with a custom-built 4-element pTx coil. Three cases were investigated to develop and evaluate this technique. First, a Proof-of-Concept study was performed to investigate the case of a simple, uniform cylindrical phantom with a straight, perfectly conducting wire. Second, a heterogeneous subject with bilateral, curved implanted wires was investigated. Finally, the third case investigated realistic patient lead-trajectories obtained from intra-operative CT scans. In all three cases, specific absorption rate (SAR), a metric used to quantify power deposition which results in heating, was reduced by over 90%. Maximal reduction in SAR was obtained with the 8-element pTx coil. Magnetic field homogeneity was comparable to the birdcage coil for the 4- and 8-element pTx configurations. Although further research is required before clinical implementation, these initial results suggest that the concept of optimizing pTx to reduce DBS heating effects holds considerable promise.

Lifelong Brain Health is a Lifelong Challenge: From Evolutionary Principles to Empirical Evidence

PubMed Central

Mattson, Mark P.

2015-01-01

Although the human brain is exceptional in size and information processing capabilities, it is similar to other mammals with regards to the factors that promote its optimal performance. Three such factors are the challenges of physical exercise, food deprivation/fasting, and social/intellectual engagement. Because it evolved, in part, for success in seeking and acquiring food, the brain functions best when the individual is hungry and physically active, as typified by the hungry lion stalking and chasing its prey. Indeed, studies of animal models and human subjects demonstrate robust beneficial effects of regular exercise and intermittent energy restriction/fasting on cognitive function and mood, particularly in the contexts of aging and associated neurodegenerative disorders. Unfortunately, the agricultural revolution and the invention of effort-sparing technologies have resulted in a dramatic reduction or elimination of vigorous exercise and fasting, leaving only intellectual challenges to bolster brain function. In addition to disengaging beneficial adaptive responses in the brain, sedentary overindulgent lifestyles promote obesity, diabetes and cardiovascular disease, all of which may increase the risk of cognitive impairment and Alzheimer’s disease. It is therefore important to embrace the reality of the requirements for exercise, intermittent fasting and critical thinking for optimal brain health throughout life, and to recognize the dire consequences for our aging population of failing to implement such brain-healthy lifestyles. PMID:25576651

Lifelong brain health is a lifelong challenge: from evolutionary principles to empirical evidence.

PubMed

Mattson, Mark P

2015-03-01

Although the human brain is exceptional in size and information processing capabilities, it is similar to other mammals with regard to the factors that promote its optimal performance. Three such factors are the challenges of physical exercise, food deprivation/fasting, and social/intellectual engagement. Because it evolved, in part, for success in seeking and acquiring food, the brain functions best when the individual is hungry and physically active, as typified by the hungry lion stalking and chasing its prey. Indeed, studies of animal models and human subjects demonstrate robust beneficial effects of regular exercise and intermittent energy restriction/fasting on cognitive function and mood, particularly in the contexts of aging and associated neurodegenerative disorders. Unfortunately, the agricultural revolution and the invention of effort-sparing technologies have resulted in a dramatic reduction or elimination of vigorous exercise and fasting, leaving only intellectual challenges to bolster brain function. In addition to disengaging beneficial adaptive responses in the brain, sedentary overindulgent lifestyles promote obesity, diabetes and cardiovascular disease, all of which may increase the risk of cognitive impairment and Alzheimer's disease. It is therefore important to embrace the reality of the requirements for exercise, intermittent fasting and critical thinking for optimal brain health throughout life, and to recognize the dire consequences for our aging population of failing to implement such brain-healthy lifestyles. Published by Elsevier B.V.

Is it time to turn our attention toward central mechanisms for post-exertional recovery strategies and performance?

PubMed Central

Rattray, Ben; Argus, Christos; Martin, Kristy; Northey, Joseph; Driller, Matthew

2015-01-01

Key Points Central fatigue is accepted as a contributor to overall athletic performance, yet little research directly investigates post-exercise recovery strategies targeting the brainCurrent post-exercise recovery strategies likely impact on the brain through a range of mechanisms, but improvements to these strategies is neededResearch is required to optimize post-exercise recovery with a focus on the brain Post-exercise recovery has largely focused on peripheral mechanisms of fatigue, but there is growing acceptance that fatigue is also contributed to through central mechanisms which demands that attention should be paid to optimizing recovery of the brain. In this narrative review we assemble evidence for the role that many currently utilized recovery strategies may have on the brain, as well as potential mechanisms for their action. The review provides discussion of how common nutritional strategies as well as physical modalities and methods to reduce mental fatigue are likely to interact with the brain, and offer an opportunity for subsequent improved performance. We aim to highlight the fact that many recovery strategies have been designed with the periphery in mind, and that refinement of current methods are likely to provide improvements in minimizing brain fatigue. Whilst we offer a number of recommendations, it is evident that there are many opportunities for improving the research, and practical guidelines in this area. PMID:25852568

A microfluidic brain slice perfusion chamber for multisite recording using penetrating electrodes.

PubMed

Blake, Alexander J; Rodgers, Frank C; Bassuener, Anna; Hippensteel, Joseph A; Pearce, Thomas M; Pearce, Timothy R; Zarnowska, Ewa D; Pearce, Robert A; Williams, Justin C

2010-05-30

To analyze the spatiotemporal dynamics of network activity in a brain tissue slice, it is useful to record simultaneously from multiple locations. When obtained from laminar structures such as the hippocampus or neocortex, multisite recordings also yield information about subcellular current distributions via current source density analysis. Multisite probes developed for in vivo recordings could serve these purposes in vitro, allowing recordings to be obtained from brain slices at sites deeper within the tissue than currently available surface recording methods permit. However, existing recording chambers do not allow for the insertion of lamina-spanning probes that enter through the edges of brain slices. Here, we present a novel brain slice recording chamber design that accomplishes this goal. The device provides a stable microfluidic perfusion environment in which tissue health is optimized by superfusing both surfaces of the slice. Multichannel electrodes can be inserted parallel to the surface of the slice, at any depth relative to the surface. Access is also provided from above for the insertion of additional recording or stimulating electrodes. We illustrate the utility of this recording configuration by measuring current sources and sinks during theta burst stimuli that lead to the induction of long-term potentiation in hippocampal slices. (c) 2010 Elsevier B.V. All rights reserved.

The Relationship of Docosahexaenoic Acid (DHA) with Learning and Behavior in Healthy Children: A Review

PubMed Central

Kuratko, Connye N.; Barrett, Erin Cernkovich; Nelson, Edward B.; Norman, Salem

2013-01-01

Childhood is a period of brain growth and maturation. The long chain omega-3 fatty acid, docosahexaenoic acid (DHA), is a major lipid in the brain recognized as essential for normal brain function. In animals, low brain DHA results in impaired learning and behavior. In infants, DHA is important for optimal visual and cognitive development. The usual intake of DHA among toddlers and children is low and some studies show improvements in cognition and behavior as the result of supplementation with polyunsaturated fatty acids including DHA. The purpose of this review was to identify and evaluate current knowledge regarding the relationship of DHA with measures of learning and behavior in healthy school-age children. A systematic search of the literature identified 15 relevant publications for review. The search found studies which were diverse in purpose and design and without consistent conclusions regarding the treatment effect of DHA intake or biomarker status on specific cognitive tests. However, studies of brain activity reported benefits of DHA supplementation and over half of the studies reported a favorable role for DHA or long chain omega-3 fatty acids in at least one area of cognition or behavior. Studies also suggested an important role for DHA in school performance. PMID:23877090

Cholesterol as a modifying agent of the neurovascular unit structure and function under physiological and pathological conditions.

PubMed

Czuba, Ewelina; Steliga, Aleksandra; Lietzau, Grażyna; Kowiański, Przemysław

2017-08-01

The brain, demanding constant level of cholesterol, precisely controls its synthesis and homeostasis. The brain cholesterol pool is almost completely separated from the rest of the body by the functional blood-brain barrier (BBB). Only a part of cholesterol pool can be exchanged with the blood circulation in the form of the oxysterol metabolites such, as 27-hydroxycholesterol (27-OHC) and 24S-hydroxycholesterol (24S-OHC). Not only neurons but also blood vessels and neuroglia, constituting neurovascular unit (NVU), are crucial for the brain cholesterol metabolism and undergo precise regulation by numerous modulators, metabolites and signal molecules. In physiological conditions maintaining the optimal cholesterol concentration is important for the energetic metabolism, composition of cell membranes and myelination. However, a growing body of evidence indicates the consequences of the cholesterol homeostasis dysregulation in several pathophysiological processes. There is a causal relationship between hypercholesterolemia and 1) development of type 2 diabetes due to long-term high-fat diet consumption, 2) significance of the oxidative stress consequences for cerebral amyloid angiopathy and neurodegenerative diseases, 3) insulin resistance on progression of the neurodegenerative brain diseases. In this review, we summarize the current state of knowledge concerning the cholesterol influence upon functioning of the NVU under physiological and pathological conditions.

Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks

ERIC Educational Resources Information Center

Nikelshpur, Dmitry O.

2014-01-01

Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…

Dynamical foundations of the neural circuit for bayesian decision making.

PubMed

Morita, Kenji

2009-07-01

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

Electrode-electrolyte interface model of tripolar concentric ring electrode and electrode paste.

PubMed

Nasrollaholhosseini, Seyed Hadi; Steele, Preston; Besio, Walter G

2016-08-01

Electrodes are used to transform ionic currents to electrical currents in biological systems. Modeling the electrode-electrolyte interface could help to optimize the performance of the electrode interface to achieve higher signal to noise ratios. There are previous reports of accurate models for single-element biomedical electrodes. In this paper we develop a model for the electrode-electrolyte interface for tripolar concentric ring electrodes (TCRE) that are used to record brain signals.

Multivariate Approach for Alzheimer's Disease Detection Using Stationary Wavelet Entropy and Predator-Prey Particle Swarm Optimization.

PubMed

Zhang, Yudong; Wang, Shuihua; Sui, Yuxiu; Yang, Ming; Liu, Bin; Cheng, Hong; Sun, Junding; Jia, Wenjuan; Phillips, Preetha; Gorriz, Juan Manuel

2017-07-17

The number of patients with Alzheimer's disease is increasing rapidly every year. Scholars often use computer vision and machine learning methods to develop an automatic diagnosis system. In this study, we developed a novel machine learning system that can make diagnoses automatically from brain magnetic resonance images. First, the brain imaging was processed, including skull stripping and spatial normalization. Second, one axial slice was selected from the volumetric image, and stationary wavelet entropy (SWE) was done to extract the texture features. Third, a single-hidden-layer neural network was used as the classifier. Finally, a predator-prey particle swarm optimization was proposed to train the weights and biases of the classifier. Our method used 4-level decomposition and yielded 13 SWE features. The classification yielded an overall accuracy of 92.73±1.03%, a sensitivity of 92.69±1.29%, and a specificity of 92.78±1.51%. The area under the curve is 0.95±0.02. Additionally, this method only cost 0.88 s to identify a subject in online stage, after its volumetric image is preprocessed. In terms of classification performance, our method performs better than 10 state-of-the-art approaches and the performance of human observers. Therefore, this proposed method is effective in the detection of Alzheimer's disease.

Optimal-mass-transfer-based estimation of glymphatic transport in living brain

PubMed Central

Zhu, Liangjia; Kolesov, Ivan; Nedergaard, Maiken; Benveniste, Helene; Tannenbaum, Allen

2016-01-01

It was recently shown that the brain-wide cerebrospinal fluid (CSF) and interstitial fluid exchange system designated the ‘glymphatic pathway’ plays a key role in removing waste products from the brain, similarly to the lymphatic system in other body organs1,2. It is therefore important to study the flow patterns of glymphatic transport through the live brain in order to better understand its functionality in normal and pathological states. Unlike blood, the CSF does not flow rapidly through a network of dedicated vessels, but rather through para-vascular channels and brain parenchyma in a slower time-domain, and thus conventional fMRI or other blood-flow sensitive MRI sequences do not provide much useful information about the desired flow patterns. We have accordingly analyzed a series of MRI images, taken at different times, of the brain of a live rat, which was injected with a paramagnetic tracer into the CSF via the lumbar intrathecal space of the spine. Our goal is twofold: (a) find glymphatic (tracer) flow directions in the live rodent brain; and (b) provide a model of a (healthy) brain that will allow the prediction of tracer concentrations given initial conditions. We model the liquid flow through the brain by the diffusion equation. We then use the Optimal Mass Transfer (OMT) approach3 to derive the glymphatic flow vector field, and estimate the diffusion tensors by analyzing the (changes in the) flow. Simulations show that the resulting model successfully reproduces the dominant features of the experimental data. PMID:26877579

Rotating single-shot acquisition (RoSA) with composite reconstruction for fast high-resolution diffusion imaging.

PubMed

Wen, Qiuting; Kodiweera, Chandana; Dale, Brian M; Shivraman, Giri; Wu, Yu-Chien

2018-01-01

To accelerate high-resolution diffusion imaging, rotating single-shot acquisition (RoSA) with composite reconstruction is proposed. Acceleration was achieved by acquiring only one rotating single-shot blade per diffusion direction, and high-resolution diffusion-weighted (DW) images were reconstructed by using similarities of neighboring DW images. A parallel imaging technique was implemented in RoSA to further improve the image quality and acquisition speed. RoSA performance was evaluated by simulation and human experiments. A brain tensor phantom was developed to determine an optimal blade size and rotation angle by considering similarity in DW images, off-resonance effects, and k-space coverage. With the optimal parameters, RoSA MR pulse sequence and reconstruction algorithm were developed to acquire human brain data. For comparison, multishot echo planar imaging (EPI) and conventional single-shot EPI sequences were performed with matched scan time, resolution, field of view, and diffusion directions. The simulation indicated an optimal blade size of 48 × 256 and a 30 ° rotation angle. For 1 × 1 mm 2 in-plane resolution, RoSA was 12 times faster than the multishot acquisition with comparable image quality. With the same acquisition time as SS-EPI, RoSA provided superior image quality and minimum geometric distortion. RoSA offers fast, high-quality, high-resolution diffusion images. The composite image reconstruction is model-free and compatible with various diffusion computation approaches including parametric and nonparametric analyses. Magn Reson Med 79:264-275, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A National Network of Neurotechnology Centers for the BRAIN Initiative.

PubMed

Alivisatos, A Paul; Chun, Miyoung; Church, George M; Greenspan, Ralph J; Roukes, Michael L; Yuste, Rafael

2015-11-04

We propose the creation of a national network of neurotechnology centers to enhance and accelerate the BRAIN Initiative and optimally leverage the effort and creativity of individual laboratories involved in it. As "brain observatories," these centers could provide the critical interdisciplinary environment both for realizing ambitious and complex technologies and for providing individual investigators with access to them. Copyright © 2015 Elsevier Inc. All rights reserved.

New clinical trial to study long-term progression of brain and spine cancers | Center for Cancer Research

Cancer.gov

Dr. Mark Gilbert, Chief, Neuro-Oncology Branch, describes an ambitious new clinical trial that, for the first time, will study the long-term progression of brain and spine cancers. The 10,000 patient trial is the largest of its kind and will follow patients throughout the course of their disease. In addition to identifying optimal treatments for common brain and spine cancers,

On the relationship between head circumference, brain size, prenatal long-chain PUFA/5-methyltetrahydrofolate supplementation and cognitive abilities during childhood.

PubMed

Catena, Andrés; Martínez-Zaldívar, Cristina; Diaz-Piedra, Carolina; Torres-Espínola, Francisco J; Brandi, Pilar; Pérez-García, Miguel; Decsi, Tamás; Koletzko, Berthold; Campoy, Cristina

2017-03-29

Head circumference in infants has been reported to predict brain size, total grey matter volume (GMV) and neurocognitive development. However, it is unknown whether it has predictive value on regional and subcortical brain volumes. We aimed to explore the relationship between several head circumference measurements since birth and distributions of GMV and subcortical volumes at later childhood. We examined seventy-four, Caucasian, singleton, term-born infants born to mothers randomised to receive fish oil and/or 5-methyltetrahydrofolate or placebo prenatal supplementation. We assessed head circumference at birth and at 4 and 10 years of age and cognitive abilities at 7 years of age. We obtained brain MRI at 10 years of age, on which we performed voxel-based morphometry, cortical surface extraction and subcortical segmentation. Analyses were controlled for sex, age, height, weight, family status, laterality and total intracranial volume. Prenatal supplementation did not affect head circumference at any age, cognitive abilities or total brain volumes. Head circumference at 4 years presented the highest correlation with total GMV, white matter volume and brain surface area, and was also strongly associated with GMV of frontal, temporal and occipital areas, as well as with caudate nucleus, globus pallidus, putamen and thalamus volumes. As relationships between brain volumes in childhood and several outcomes extend into adulthood, we have found that ages between 0 and 4 years as the optimal time for brain growth; postnatal factors might have the most relevant impact on structural maturation of certain cortical areas and subcortical nuclei, independent of prenatal supplementation.

Importance of dose intensity in neuro-oncology clinical trials: summary report of the Sixth Annual Meeting of the Blood-Brain Barrier Disruption Consortium.

PubMed

Doolittle, N D; Anderson, C P; Bleyer, W A; Cairncross, J G; Cloughesy, T; Eck, S L; Guastadisegni, P; Hall, W A; Muldoon, L L; Patel, S J; Peereboom, D; Siegal, T; Neuwelt, E A

2001-01-01

Therapeutic options for the treatment of malignant brain tumors have been limited, in part, because of the presence of the blood-brain barrier. For this reason, the Sixth Annual Meeting of the Blood-Brain Barrier Disruption Consortium, the focus of which was the "Importance of Dose Intensity in Neuro-Oncology Clinical Trials," was convened in April 2000, at Government Camp, Mount Hood, Oregon. This meeting, which was supported by the National Cancer Institute, the National Institute of Neurological Disorders and Stroke, and the National Institute of Deafness and Other Communication Disorders, brought together clinicians and basic scientists from across the U.S. to discuss the role of dose intensity and enhanced chemotherapy delivery in the treatment of malignant brain tumors and to design multicenter clinical trials. Optimizing chemotherapy delivery to the CNS is crucial, particularly in view of recent progress identifying certain brain tumors as chemosensitive. The discovery that specific constellations of genetic alterations can predict which tumors are chemoresponsive, and can therefore more accurately predict prognosis, has important implications for delivery of intensive, effective chemotherapy regimens with acceptable toxicities. This report summarizes the discussions, future directions, and key questions regarding dose-intensive treatment of primary CNS lymphoma, CNS relapse of systemic non-Hodgkin's lymphoma, anaplastic oligodendroglioma, high-grade glioma, and metastatic cancer of the brain. The promising role of cytoenhancers and chemoprotectants as part of dose-intensive regimens for chemosensitive brain tumors and development of improved gene therapies for malignant gliomas are discussed.

MO-F-CAMPUS-T-02: Optimizing Orientations of Hundreds of Intensity-Modulated Beams to Treat Multiple Brain Targets

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

Ma, L; Dong, P; Larson, D

Purpose: To investigate a new modulated beam orientation optimization (MBOO) approach maximizing treatment planning quality for the state-of-the-art flattening filter free (FFF) beam that has enabled rapid treatments of multiple brain targets. Methods: MBOO selects and optimizes a large number of intensity-modulated beams (400 or more) from all accessible beam angles surrounding a patient’s skull. The optimization algorithm was implemented on a standalone system that interfaced with the 3D Dicom images and structure sets. A standard published data set that consisted of 1 to 12 metastatic brain tumor combinations was selected for MBOO planning. The planning results from various coplanarmore » and non-coplanar configurations via MBOO were then compared with the results obtained from a clinical volume modulated arc therapy (VMAT) delivery system (Truebeam RapidArc, Varian Oncology). Results: When planning a few number of targets (n<4), MBOO produced results equivalent to non-coplanar multi-arc VMAT planning in terms of target volume coverage and normal tissue sparing. For example, the 12-Gy and 4-Gy normal brain volumes for the 3-target plans differed by less than 1 mL ( 3.0 mLvs 3.8 mL; and 35.2 mL vs 36.3 mL, respectively) for MBOO versus VMAT. However, when planning a larger number of targets (n≥4), MBOO significantly reduced the dose to the normal brain as compared to VMAT, though the target volume coverage was equivalent. For example, the 12-Gy and 4-Gy normal brain volumes for the 12-target plans were 10.8 mL vs. 18.0 mL and 217.9 mL vs. 390.0 mL, respectively for the non-coplanar MBOO versus the non-coplanar VMAT treatment plans, yielding a reduction in volume of more than 60% for the case. Conclusion: MBOO is a unique approach for maximizing normal tissue sparing when treating a large number (n≥4) of brain tumors with FFF linear accelerators. Dr Ma and Dr Sahgal are currently on the board of international society of stereotactic radiosurgery. Dr Sahgal has received support for educational presentations from Elekta company.« less

Laser speckle-imaging of blood microcirculation in the brain cortex of laboratory rats in stress

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

Vilensky, M A; Semyachkina-Glushkovskaya, Oxana V; Timoshina, P A

2012-06-30

The results of experimental approbation of the method of laser full-field speckle-imaging for monitoring the changes in blood microcirculation state of the brain cortex of laboratory rats under the conditions of developing stroke and administration of vasodilating and vasoconstrictive agents are presented. The studies aimed at the choice of the optimal conditions of speckle-image formation and recording were performed and the software implementing an adaptive algorithm for processing the data of measurements was created. The transfer of laser radiation to the probed region of the biotissue was implemented by means of a silica-polymer optical fibre. The problems and prospects ofmore » speckle-imaging of cerebral microcirculation of blood in laboratory and clinical conditions are discussed.« less

A Natural Language Processing-based Model to Automate MRI Brain Protocol Selection and Prioritization.

PubMed

Brown, Andrew D; Marotta, Thomas R

2017-02-01

Incorrect imaging protocol selection can contribute to increased healthcare cost and waste. To help healthcare providers improve the quality and safety of medical imaging services, we developed and evaluated three natural language processing (NLP) models to determine whether NLP techniques could be employed to aid in clinical decision support for protocoling and prioritization of magnetic resonance imaging (MRI) brain examinations. To test the feasibility of using an NLP model to support clinical decision making for MRI brain examinations, we designed three different medical imaging prediction tasks, each with a unique outcome: selecting an examination protocol, evaluating the need for contrast administration, and determining priority. We created three models for each prediction task, each using a different classification algorithm-random forest, support vector machine, or k-nearest neighbor-to predict outcomes based on the narrative clinical indications and demographic data associated with 13,982 MRI brain examinations performed from January 1, 2013 to June 30, 2015. Test datasets were used to calculate the accuracy, sensitivity and specificity, predictive values, and the area under the curve. Our optimal results show an accuracy of 82.9%, 83.0%, and 88.2% for the protocol selection, contrast administration, and prioritization tasks, respectively, demonstrating that predictive algorithms can be used to aid in clinical decision support for examination protocoling. NLP models developed from the narrative clinical information provided by referring clinicians and demographic data are feasible methods to predict the protocol and priority of MRI brain examinations. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

The microbiota-gut-brain axis as a key regulator of neural function and the stress response: Implications for human and animal health.

PubMed

Wiley, N C; Dinan, T G; Ross, R P; Stanton, C; Clarke, G; Cryan, J F

2017-07-01

The brain-gut-microbiota axis comprises an extensive communication network between the brain, the gut, and the microbiota residing there. Development of a diverse gut microbiota is vital for multiple features of behavior and physiology, as well as many fundamental aspects of brain structure and function. Appropriate early-life assembly of the gut microbiota is also believed to play a role in subsequent emotional and cognitive development. If the composition, diversity, or assembly of the gut microbiota is impaired, this impairment can have a negative impact on host health and lead to disorders such as obesity, diabetes, inflammatory diseases, and even potentially neuropsychiatric illnesses, including anxiety and depression. Therefore, much research effort in recent years has focused on understanding the potential of targeting the intestinal microbiota to prevent and treat such disorders. This review aims to explore the influence of the gut microbiota on host neural function and behavior, particularly those of relevance to stress-related disorders. The involvement of microbiota in diverse neural functions such as myelination, microglia function, neuronal morphology, and blood-brain barrier integrity across the life span, from early life to adolescence to old age, will also be discussed. Nurturing an optimal gut microbiome may also prove beneficial in animal science as a means to manage stressful situations and to increase productivity of farm animals. The implications of these observations are manifold, and researchers are hopeful that this promising body of preclinical work can be successfully translated to the clinic and beyond.

Mapping subcortical brain maturation during adolescence: evidence of hemisphere- and sex-specific longitudinal changes.

PubMed

Dennison, Meg; Whittle, Sarah; Yücel, Murat; Vijayakumar, Nandita; Kline, Alexandria; Simmons, Julian; Allen, Nicholas B

2013-09-01

Early to mid-adolescence is an important developmental period for subcortical brain maturation, but longitudinal studies of these neurodevelopmental changes are lacking. The present study acquired repeated magnetic resonance images from 60 adolescent subjects (28 female) at ages 12.5 and 16.5 years to map changes in subcortical structure volumes. Automated segmentation techniques optimized for longitudinal measurement were used to delineate volumes of the caudate, putamen, nucleus accumbens, pallidum, hippocampus, thalamus and the whole brain. Amygdala volumes were described using manual tracing methods. The results revealed heterogeneous maturation across the regions of interest (ROIs), and change was differentially moderated by sex and hemisphere. The caudate, thalamus and putamen declined in volume, more for females relative to males, and decreases in the putamen and thalamus were greater in the left hemisphere. The pallidum increased in size, but more so in the left hemisphere. While the left nucleus accumbens increased in size, the right accumbens decreased in size over the follow-up period. Increases in hippocampal volume were greater in the right hemisphere. While amygdala volume did not change over time, the left hemisphere was consistently larger than the right. These results suggest that subcortical brain development from early to middle adolescence is characterized by striking hemispheric specialization and sexual dimorphisms, and provide a framework for interpreting normal and abnormal changes in cognition, affect and behavior. Moreover, the differences in findings compared to previous cross-sectional research emphasize the importance of within-subject assessment of brain development during adolescence. © 2013 John Wiley & Sons Ltd.

Prepartum and Postpartum Maternal Depressive Symptoms Are Related to Children's Brain Structure in Preschool.

PubMed

Lebel, Catherine; Walton, Matthew; Letourneau, Nicole; Giesbrecht, Gerald F; Kaplan, Bonnie J; Dewey, Deborah

2016-12-01

Perinatal maternal depression is a serious health concern with potential lasting negative consequences for children. Prenatal depression is associated with altered brain gray matter in children, though relations between postpartum depression and children's brains and the role of white matter are unclear. We studied 52 women who provided Edinburgh Postnatal Depression Scale (EPDS) scores during each trimester of pregnancy and at 3 months postpartum and their children who underwent magnetic resonance imaging at age 2.6 to 5.1 years. Associations between maternal depressive symptoms and magnetic resonance imaging measures of cortical thickness and white matter structure in the children were investigated. Women's second trimester EPDS scores negatively correlated with children's cortical thickness in right inferior frontal and middle temporal regions and with radial and mean diffusivity in white matter emanating from the inferior frontal area. Cortical thickness, but not diffusivity, correlations survived correction for postpartum EPDS. Postpartum EPDS scores negatively correlated with children's right superior frontal cortical thickness and with diffusivity in white matter originating from that region, even after correcting for prenatal EPDS. Higher maternal depressive symptoms prenatally and postpartum are associated with altered gray matter structure in children; the observed white matter correlations appear to be uniquely related to the postpartum period. The reduced thickness and diffusivity suggest premature brain development in children exposed to higher maternal perinatal depressive symptoms. These results highlight the importance of ensuring optimal women's mental health throughout the perinatal period, because maternal depressive symptoms appear to increase children's vulnerability to nonoptimal brain development. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

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

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

PubMed

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

2017-01-01

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

Optimal Symmetric Multimodal Templates and Concatenated Random Forests for Supervised Brain Tumor Segmentation (Simplified) with ANTsR.

PubMed

Tustison, Nicholas J; Shrinidhi, K L; Wintermark, Max; Durst, Christopher R; Kandel, Benjamin M; Gee, James C; Grossman, Murray C; Avants, Brian B

2015-04-01

Segmenting and quantifying gliomas from MRI is an important task for diagnosis, planning intervention, and for tracking tumor changes over time. However, this task is complicated by the lack of prior knowledge concerning tumor location, spatial extent, shape, possible displacement of normal tissue, and intensity signature. To accommodate such complications, we introduce a framework for supervised segmentation based on multiple modality intensity, geometry, and asymmetry feature sets. These features drive a supervised whole-brain and tumor segmentation approach based on random forest-derived probabilities. The asymmetry-related features (based on optimal symmetric multimodal templates) demonstrate excellent discriminative properties within this framework. We also gain performance by generating probability maps from random forest models and using these maps for a refining Markov random field regularized probabilistic segmentation. This strategy allows us to interface the supervised learning capabilities of the random forest model with regularized probabilistic segmentation using the recently developed ANTsR package--a comprehensive statistical and visualization interface between the popular Advanced Normalization Tools (ANTs) and the R statistical project. The reported algorithmic framework was the top-performing entry in the MICCAI 2013 Multimodal Brain Tumor Segmentation challenge. The challenge data were widely varying consisting of both high-grade and low-grade glioma tumor four-modality MRI from five different institutions. Average Dice overlap measures for the final algorithmic assessment were 0.87, 0.78, and 0.74 for "complete", "core", and "enhanced" tumor components, respectively.

Optimal hemodynamic response model for functional near-infrared spectroscopy

PubMed Central

Kamran, Muhammad A.; Jeong, Myung Yung; Mannan, Malik M. N.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650–950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > tcritical and p-value < 0.05). PMID:26136668

Optimal hemodynamic response model for functional near-infrared spectroscopy.

PubMed

Kamran, Muhammad A; Jeong, Myung Yung; Mannan, Malik M N

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > t critical and p-value < 0.05).

Multifunctional System for Observing, Measuring and Analyzing Stimulation-Evoked Neurochemical Signaling

PubMed Central

Kimble, Christopher J.; Boesche, Joshua B.; Eaker, Diane R.; Kressin, Kenneth R.; Trevathan, James K.; Paek, Seungleal; Asp, Anders J.; McIntosh, Malcolm B.; Lujan, J. Luis

2017-01-01

The ability to measure neurotransmitter activity using implanted electrochemical sensors offers researchers a potent technique for analyzing neural activity across specific neural circuitry. We have developed a wirelessly controlled device, WINCS Harmoni, to observe and measure neurotransmitter dynamics at up to four separate sensors, with high temporal and spatial resolution. WINCS Harmoni also incorporates a versatile neurostimulator that can be synchronized with electrochemical recording. The WINCS Harmoni platform is thus optimally suited for probing the neurochemical effects of neurostimulation, and may in turn enable the development of personalized therapies for multiple brain disorders. PMID:29202131

Intentionality and "free-will" from a neurodevelopmental perspective.

PubMed

Leisman, Gerry; Machado, Calixto; Melillo, Robert; Mualem, Raed

2012-01-01

The nature of free-will as a subset of intentionality and probabilistic and deterministic function is explored with the indications being that human behavior is highly predictable which in turn, should compromise the notion of free-will. Data supports the notion that age relates to the ability to progressively effectively establish goals performed by fixed action patterns and that these FAPs produce outcomes that in turn modify choices (free-will) for which FAPs need to be employed. Early goals require behaviors that require greater automation in terms of FAPs that lead to goals being achieved or not; if not, then one can change behavior and that in turn is free-will. Goals change with age based on experience which is similar to the way in which movement functions. We hypothesize that human prefrontal cortex development was a natural expansion of the evolutionarily earlier developed areas of the frontal lobe and that goal-directed movements and behavior, including choice and free-will, provided for an expansion of those areas. The same regions of the human central nervous system that were already employed for better control, coordination, and timing of movements, expanded in parallel with the frontal cortex. The initial focus of the frontal lobes was the control of motor activity, but as the movements became more goal-directed, greater cognitive control over movement was necessitated leading to voluntary control of FAPs or free-will. The paper reviews the neurobiology, neurohistology, and electrophysiology of brain connectivities developmentally, along with the development of those brain functions linked to decision-making from a developmental viewpoint. The paper reviews the neurological development of the frontal lobes and inter-regional brain connectivities in the context of optimization of communication systems within the brain and nervous system and its relation to free-will.

Late development of cue integration is linked to sensory fusion in cortex.

PubMed

Dekker, Tessa M; Ban, Hiroshi; van der Velde, Bauke; Sereno, Martin I; Welchman, Andrew E; Nardini, Marko

2015-11-02

Adults optimize perceptual judgements by integrating different types of sensory information [1, 2]. This engages specialized neural circuits that fuse signals from the same [3-5] or different [6] modalities. Whereas young children can use sensory cues independently, adult-like precision gains from cue combination only emerge around ages 10 to 11 years [7-9]. Why does it take so long to make best use of sensory information? Existing data cannot distinguish whether this (1) reflects surprisingly late changes in sensory processing (sensory integration mechanisms in the brain are still developing) or (2) depends on post-perceptual changes (integration in sensory cortex is adult-like, but higher-level decision processes do not access the information) [10]. We tested visual depth cue integration in the developing brain to distinguish these possibilities. We presented children aged 6-12 years with displays depicting depth from binocular disparity and relative motion and made measurements using psychophysics, retinotopic mapping, and pattern classification fMRI. Older children (>10.5 years) showed clear evidence for sensory fusion in V3B, a visual area thought to integrate depth cues in the adult brain [3-5]. By contrast, in younger children (<10.5 years), there was no evidence for sensory fusion in any visual area. This significant age difference was paired with a shift in perceptual performance around ages 10 to 11 years and could not be explained by motion artifacts, visual attention, or signal quality differences. Thus, whereas many basic visual processes mature early in childhood [11, 12], the brain circuits that fuse cues take a very long time to develop. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Late Development of Cue Integration Is Linked to Sensory Fusion in Cortex

PubMed Central

Dekker, Tessa M.; Ban, Hiroshi; van der Velde, Bauke; Sereno, Martin I.; Welchman, Andrew E.; Nardini, Marko

2015-01-01

Summary Adults optimize perceptual judgements by integrating different types of sensory information [1, 2]. This engages specialized neural circuits that fuse signals from the same [3, 4, 5] or different [6] modalities. Whereas young children can use sensory cues independently, adult-like precision gains from cue combination only emerge around ages 10 to 11 years [7, 8, 9]. Why does it take so long to make best use of sensory information? Existing data cannot distinguish whether this (1) reflects surprisingly late changes in sensory processing (sensory integration mechanisms in the brain are still developing) or (2) depends on post-perceptual changes (integration in sensory cortex is adult-like, but higher-level decision processes do not access the information) [10]. We tested visual depth cue integration in the developing brain to distinguish these possibilities. We presented children aged 6–12 years with displays depicting depth from binocular disparity and relative motion and made measurements using psychophysics, retinotopic mapping, and pattern classification fMRI. Older children (>10.5 years) showed clear evidence for sensory fusion in V3B, a visual area thought to integrate depth cues in the adult brain [3, 4, 5]. By contrast, in younger children (<10.5 years), there was no evidence for sensory fusion in any visual area. This significant age difference was paired with a shift in perceptual performance around ages 10 to 11 years and could not be explained by motion artifacts, visual attention, or signal quality differences. Thus, whereas many basic visual processes mature early in childhood [11, 12], the brain circuits that fuse cues take a very long time to develop. PMID:26480841

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

PubMed

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

2017-05-15

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

Homeostasis and the concept of 'interstitial fluids hierarchy': Relevance of cerebrospinal fluid sodium concentrations and brain temperature control (Review).

PubMed

Agnati, Luigi F; Marcoli, Manuela; Leo, Giuseppina; Maura, Guido; Guidolin, Diego

2017-03-01

In this review, the aspects and further developments of the concept of homeostasis are discussed also in the perspective of their possible impact in the clinical practice, particularly as far as psychic homeostasis is concerned. A brief historical survey and comments on the concept of homeostasis and allostasis are presented to introduce our proposal that is based on the classical assumption of the interstitial fluid (ISF) as the internal medium for multicellular organisms. However, the new concept of a hierarchic role of ISF of the various organs is introduced. Additionally, it is suggested that particularly for some chemico‑physical parameters, oscillatory rhythms within their proper set‑ranges should be considered a fundamental component of homeostasis. Against this background, we propose that the brain ISF has the highest hierarchic role in human beings, providing the optimal environment, not simply for brain cell survival, but also for brain complex functions and the oscillatory rhythms of some parameters, such as cerebrospinal fluid sodium and brain ISF pressure waves, which may play a crucial role in brain physio‑pathological states. Thus, according to this proposal, the brain ISF represents the real internal medium since the maintenance of its dynamic intra-set-range homeostasis is the main factor for a free and independent life of higher vertebrates. Furthermore, the evolutionary links between brain and kidney and their synergistic role in H2O/Na balance and brain temperature control are discussed. Finally, it is surmised that these two interrelated parameters have deep effects on the Central Nervous System (CNS) higher integrative actions such those linked to psychic homeostasis.

Homeostasis and the concept of 'interstitial fluids hierarchy': Relevance of cerebrospinal fluid sodium concentrations and brain temperature control (Review)

PubMed Central

Agnati, Luigi F.; Marcoli, Manuela; Leo, Giuseppina; Maura, Guido; Guidolin, Diego

2017-01-01

In this review, the aspects and further developments of the concept of homeostasis are discussed also in the perspective of their possible impact in the clinical practice, particularly as far as psychic homeostasis is concerned. A brief historical survey and comments on the concept of homeostasis and allostasis are presented to introduce our proposal that is based on the classical assumption of the interstitial fluid (ISF) as the internal medium for multicellular organisms. However, the new concept of a hierarchic role of ISF of the various organs is introduced. Additionally, it is suggested that particularly for some chemico-physical parameters, oscillatory rhythms within their proper set-ranges should be considered a fundamental component of homeostasis. Against this background, we propose that the brain ISF has the highest hierarchic role in human beings, providing the optimal environment, not simply for brain cell survival, but also for brain complex functions and the oscillatory rhythms of some parameters, such as cerebrospinal fluid sodium and brain ISF pressure waves, which may play a crucial role in brain physio-pathological states. Thus, according to this proposal, the brain ISF represents the real internal medium since the maintenance of its dynamic intra-set-range homeostasis is the main factor for a free and independent life of higher vertebrates. Furthermore, the evolutionary links between brain and kidney and their synergistic role in H2O/Na balance and brain temperature control are discussed. Finally, it is surmised that these two interrelated parameters have deep effects on the Central Nervous System (CNS) higher integrative actions such those linked to psychic homeostasis. PMID:28204813

Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

PubMed

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu

2017-10-01

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

Clinical application of 'Justification' and 'Optimization' principle of ALARA in pediatric CT imaging: "How many children can be protected from unnecessary radiation?".

PubMed

Sodhi, Kushaljit S; Krishna, Satheesh; Saxena, Akshay K; Sinha, Anindita; Khandelwal, Niranjan; Lee, Edward Y

2015-09-01

Practice of ALARA (as low as reasonably achievable) principle in the developed world is currently well established. However, there is striking lack of published data regarding such experience in the developing countries. Therefore, the goal of this study is to prospectively evaluate CT request forms to assess how many children could be protected from harmful radiation exposure if 'Justification' and 'Optimization' principles of ALARA are applied before obtaining CT imaging in a developing country. This can save children from potential radiation risks including development of brain cancer and leukemia. Consecutive CT request forms over a six month study period (May 16, 2013 to November 15, 2013) in a tertiary pediatric children's hospital in India were prospectively reviewed by two pediatric radiologists before obtaining CT imaging. First, 'Justification' of CT was evaluated and then 'Optimization' was applied for evaluation of appropriateness of the requested CT studies. The number (and percentage) of CT studies avoided by applying 'Justification' and 'Optimization' principle of ALARA were calculated. The difference in number of declined and optimized CT requests between CT requests from inpatient and outpatient departments was compared using Chi-Square test. A total of 1302 consecutive CT request forms were received during the study period. Some of the request forms (n=86; 6.61%) had requests for more than one (multiple) anatomical regions, hence, a total of 1392 different anatomical CT requests were received. Based on evaluation of the CT request forms for 'Justification' and 'Optimization' principle of ALARA by pediatric radiology reviewers, 111 individual anatomic part CT requests from 105 pediatric patients were avoided. Therefore, 8.06% (105 out of 1302 pediatric patients) were protected from unnecessary or additional radiation exposure.The rates of declined or optimized CT requests from inpatient department was significantly higher than that from outpatient departments (p<0.05). A substantial number of pediatric patients, particularly coming from outpatient departments, can be protected from unnecessary or additional radiation exposure from CT imaging when 'Justification' and 'Optimization' principle of ALARA are applied before obtaining CT imaging in a developing country. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout

PubMed Central

Clery, Stephane; Cumming, Bruce G.

2017-01-01

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal “noise” correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. SIGNIFICANCE STATEMENT Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. PMID:28100751

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

PubMed

Meyniel, Florent; Dehaene, Stanislas

2017-05-09

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

Pre-clinical therapeutic development of a series of metalloporphyrins for Parkinson's disease

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

Liang, Li-Ping

Reactive oxygen species are a well-defined therapeutic target for Parkinson's disease (PD) and pharmacological agents that catalytically scavenge reactive species are promising neuroprotective strategies for treatment. Metalloporphyrins are synthetic catalytic antioxidants that mimic the body's own antioxidant enzymes i.e. superoxide dismutases and catalase. The goal of this study was to determine if newly designed metalloporphyrins have enhanced pharmacodynamics including oral bioavailability, longer plasma elimination half-lives, penetrate the blood brain barrier, and show promise for PD treatment. Three metalloporphyrins (AEOL 11216, AEOL 11203 and AEOL 11114) were identified in this study as potential candidates for further pre-clinical development. Each of thesemore » compounds demonstrated blood brain barrier permeability by the i.p. route and two of three compounds (AEOL 11203 and AEOL 11114) were orally bioavailable. All of these compounds protected against 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced neurotoxicity, including dopamine depletion in the striatum, dopaminergic neuronal loss in the substantial nigra, and increased oxidative/nitrative stress indices (glutathione disulfide and 3-nitrotyrosine) in the ventral midbrain of the mice without inhibiting MPTP metabolism. Daily therapeutic dosing of these metalloporphyrins were well tolerated without accumulation of brain manganese levels or behavioral alterations assessed by open field and rotarod tests. The study identified two orally active metalloporphyrins and one injectable metalloporphyrin as clinical candidates for further development in PD. - Highlights: • A series of metalloporphyrins were optimized in a mouse model of parkinsonism. • Two novel orally active, brain permeable antioxidant metalloporphyrins were identified. • The identified metalloporphyrins were well tolerated.« less

Optimization of focality and direction in dense electrode array transcranial direct current stimulation (tDCS)

NASA Astrophysics Data System (ADS)

Guler, Seyhmus; Dannhauer, Moritz; Erem, Burak; Macleod, Rob; Tucker, Don; Turovets, Sergei; Luu, Phan; Erdogmus, Deniz; Brooks, Dana H.

2016-06-01

Objective. Transcranial direct current stimulation (tDCS) aims to alter brain function non-invasively via electrodes placed on the scalp. Conventional tDCS uses two relatively large patch electrodes to deliver electrical current to the brain region of interest (ROI). Recent studies have shown that using dense arrays containing up to 512 smaller electrodes may increase the precision of targeting ROIs. However, this creates a need for methods to determine effective and safe stimulus patterns as the number of degrees of freedom is much higher with such arrays. Several approaches to this problem have appeared in the literature. In this paper, we describe a new method for calculating optimal electrode stimulus patterns for targeted and directional modulation in dense array tDCS which differs in some important aspects with methods reported to date. Approach. We optimize stimulus pattern of dense arrays with fixed electrode placement to maximize the current density in a particular direction in the ROI. We impose a flexible set of safety constraints on the current power in the brain, individual electrode currents, and total injected current, to protect subject safety. The proposed optimization problem is convex and thus efficiently solved using existing optimization software to find unique and globally optimal electrode stimulus patterns. Main results. Solutions for four anatomical ROIs based on a realistic head model are shown as exemplary results. To illustrate the differences between our approach and previously introduced methods, we compare our method with two of the other leading methods in the literature. We also report on extensive simulations that show the effect of the values chosen for each proposed safety constraint bound on the optimized stimulus patterns. Significance. The proposed optimization approach employs volume based ROIs, easily adapts to different sets of safety constraints, and takes negligible time to compute. An in-depth comparison study gives insight into the relationship between different objective criteria and optimized stimulus patterns. In addition, the analysis of the interaction between optimized stimulus patterns and safety constraint bounds suggests that more precise current localization in the ROI, with improved safety criterion, may be achieved by careful selection of the constraint bounds.

Understanding and enhancing motor recovery after stroke using transcranial magnetic stimulation

PubMed Central

Hoyer, Erik H.; Celnik, Pablo A.

2013-01-01

Stroke is the leading cause of long-term disability. Understanding how people recover from stroke and other brain lesions remain one of the biggest conundrums in neuroscience. As a result, concerted efforts in recent years have focused on investigating the neurophysiological changes that occur in the brain after stroke, and in developing novel strategies to enhance motor recovery. In particular, transcranial magnetic stimulation (TMS) is a non-invasive tool that has been used to investigate the brain plasticity changes resulting from stroke and as a therapeutic modality to safely improve motor function. In this review, we discuss the contributions of TMS to understand how different motor areas, such as the ipsilesional hemisphere, secondary motor areas, and contralesional hemisphere are involved in motor recovery. We also consider recent studies using repetitive TMS (rTMS) in stroke patients to enhance upper extremity function. Although further studies are needed, these investigations provide an important starting point to understand the stimulation parameters and patient characteristics that may influence the optimal response to non-invasive brain stimulation. Future directions of rTMS are discussed in the context of post-stroke motor recovery. PMID:22124033

Optimization of rotational arc station parameter optimized radiation therapy.

PubMed

Dong, P; Ungun, B; Boyd, S; Xing, L

2016-09-01

To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.

Optimization of rotational arc station parameter optimized radiation therapy

PubMed Central

Dong, P.; Ungun, B.; Boyd, S.; Xing, L.

2016-01-01

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trapped in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. Conclusions: The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future. PMID:27587028

Optimization of rotational arc station parameter optimized radiation therapy

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

Dong, P.; Ungun, B.

Purpose: To develop a fast optimization method for station parameter optimized radiation therapy (SPORT) and show that SPORT is capable of matching VMAT in both plan quality and delivery efficiency by using three clinical cases of different disease sites. Methods: The angular space from 0° to 360° was divided into 180 station points (SPs). A candidate aperture was assigned to each of the SPs based on the calculation results using a column generation algorithm. The weights of the apertures were then obtained by optimizing the objective function using a state-of-the-art GPU based proximal operator graph solver. To avoid being trappedmore » in a local minimum in beamlet-based aperture selection using the gradient descent algorithm, a stochastic gradient descent was employed here. Apertures with zero or low weight were thrown out. To find out whether there was room to further improve the plan by adding more apertures or SPs, the authors repeated the above procedure with consideration of the existing dose distribution from the last iteration. At the end of the second iteration, the weights of all the apertures were reoptimized, including those of the first iteration. The above procedure was repeated until the plan could not be improved any further. The optimization technique was assessed by using three clinical cases (prostate, head and neck, and brain) with the results compared to that obtained using conventional VMAT in terms of dosimetric properties, treatment time, and total MU. Results: Marked dosimetric quality improvement was demonstrated in the SPORT plans for all three studied cases. For the prostate case, the volume of the 50% prescription dose was decreased by 22% for the rectum and 6% for the bladder. For the head and neck case, SPORT improved the mean dose for the left and right parotids by 15% each. The maximum dose was lowered from 72.7 to 71.7 Gy for the mandible, and from 30.7 to 27.3 Gy for the spinal cord. The mean dose for the pharynx and larynx was reduced by 8% and 6%, respectively. For the brain case, the doses to the eyes, chiasm, and inner ears were all improved. SPORT shortened the treatment time by ∼1 min for the prostate case, ∼0.5 min for brain case, and ∼0.2 min for the head and neck case. Conclusions: The dosimetric quality and delivery efficiency presented here indicate that SPORT is an intriguing alternative treatment modality. With the widespread adoption of digital linac, SPORT should lead to improved patient care in the future.« less

Neural Bases of Recovery after Brain Injury

ERIC Educational Resources Information Center

Nudo, Randolph J.

2011-01-01

Substantial data have accumulated over the past decade indicating that the adult brain is capable of substantial structural and functional reorganization after stroke. While some limited recovery is known to occur spontaneously, especially within the first month post-stroke, there is currently significant optimism that new interventions based on…

MIT - Massachusetts Institute of Technology

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Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis.

PubMed

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first. work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method.

Shape Classification Using Wasserstein Distance for Brain Morphometry Analysis

PubMed Central

Su, Zhengyu; Zeng, Wei; Wang, Yalin; Lu, Zhong-Lin; Gu, Xianfeng

2015-01-01

Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optimal mass transport theory. By Poincare uniformization theorem, all shapes can be conformally deformed to one of the three canonical spaces: the unit sphere, the Euclidean plane or the hyperbolic plane. The uniformization map will distort the surface area elements. The area-distortion factor gives a probability measure on the canonical uniformization space. All the probability measures on a Riemannian manifold form the Wasserstein space. Given any 2 probability measures, there is a unique optimal mass transport map between them, the transportation cost defines the Wasserstein distance between them. Wasserstein distance gives a Riemannian metric for the Wasserstein space. It intrinsically measures the dissimilarities between shapes and thus has the potential for shape classification. To the best of our knowledge, this is the first work to introduce the optimal mass transport map to general Riemannian manifolds. The method is based on geodesic power Voronoi diagram. Comparing to the conventional methods, our approach solely depends on Riemannian metrics and is invariant under rigid motions and scalings, thus it intrinsically measures shape distance. Experimental results on classifying brain cortical surfaces with different intelligence quotients demonstrated the efficiency and efficacy of our method. PMID:26221691

Optimization of brain metastases radiotherapy with TomoHDA

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

Yartsev, Slav, E-mail: slav.yartsev@lhsc.on.ca; Bauman, Glenn

An upgrade of the helical tomotherapy technology by introducing variable fan-field width (dynamic jaws) reduced the penumbra in superior-inferior direction for the target. Possible implementation of this upgrade even for the cases of the targets with different dose prescriptions is proposed. An example of brain metastasis in proximity to the optical apparatus in need of the whole brain irradiation of 30 Gy and higher dose to the lesion is considered.

Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

PubMed Central

Bhagat, Nikunj A.; Venkatakrishnan, Anusha; Abibullaev, Berdakh; Artz, Edward J.; Yozbatiran, Nuray; Blank, Amy A.; French, James; Karmonik, Christof; Grossman, Robert G.; O'Malley, Marcia K.; Francisco, Gerard E.; Contreras-Vidal, Jose L.

2016-01-01

This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected −367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration. PMID:27065787

Development and evaluation of polymer nanoparticles for oral delivery of estradiol to rat brain in a model of Alzheimer's pathology.

PubMed

Mittal, G; Carswell, H; Brett, R; Currie, S; Kumar, M N V Ravi

2011-03-10

The purpose of this study was to develop tween 80 (T-80) coated polylactide-co-glycolide (PLGA) nanoparticles that can deliver estradiol to the brain upon oral administration. Estradiol containing nanoparticles were made by a single emulsion technique and T-80 coating was achieved by incubating the re-constituted nanoparticles at different concentrations of T-80. The process of T-80 coating on the nanoparticles was optimized and the pharmacokinetics of estradiol nanoparticles was studied as a function of T-80 coating. The nanoparticles were then evaluated in an ovariectomized (OVX) rat model of Alzheimer's disease (AD) that mimics the postmenopausal conditions. The nanoparticles bound T-80 were found to proportionally increase from 9.72 ± 1.07 mg to 63.84 ± 3.59 mg with an increase in the initial concentration T-80 from 1% to 5% and were stable in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). Orally administered T-80 coated nanoparticles resulted in significantly higher brain estradiol levels after 24h (1.969 ± 0.197 ng/g tissue) as compared to uncoated ones (1.105 ± 0.136 ng/g tissue) at a dose of 0.2mg/rat, suggesting a significant role of surface coating. Moreover, these brain estradiol levels were almost similar to those obtained after administration of the same dose of drug suspension via 100% bioavailable intramuscular route (2.123 ± 0.370 ng/g tissue), indicating the increased fraction of bioavailable drug reaching the brain when administered orally. Also, the nanoparticle treated group was successful in preventing the expression of amyloid beta-42 (Aβ42) immunoreactivity in the hippocampus region of brain. Together, the results indicate the potential of nanoparticles for oral delivery of estradiol to brain. Copyright © 2010 Elsevier B.V. All rights reserved.

Micro Electrochemical pH Sensor Applicable for Real-Time Ratiometric Monitoring of pH Values in Rat Brains.

PubMed

Zhou, Jie; Zhang, Limin; Tian, Yang

2016-02-16

To develop in vivo monitoring meter for pH measurements is still the bottleneck for understanding the role of pH plays in the brain diseases. In this work, a selective and sensitive electrochemical pH meter was developed for real-time ratiometric monitoring of pH in different regions of rat brains upon ischemia. First, 1,2-naphthoquinone (1,2-NQ) was employed and optimized as a selective pH recognition element to establish a 2H(+)/2e(-) approach over a wide range of pH from 5.8 to 8.0. The pH meter demonstrated remarkable selectivity toward pH detection against metal ions, amino acids, reactive oxygen species, and other biological species in the brain. Meanwhile, an inner reference, 6-(ferrocenyl)hexanethiol (FcHT), was selected as a built-in correction to avoid the environmental effect through coimmobilization with 1,2-NQ. In addition, three-dimensional gold nanoleaves were electrodeposited onto the electrode surface to amplify the signal by ∼4.0-fold and the measurement was achieved down to 0.07 pH. Finally, combined with the microelectrode technique, the microelectrochemical pH meter was directly implanted into brain regions including the striatum, hippocampus, and cortex and successfully applied in real-time monitoring of pH values in these regions of brain followed by global cerebral ischemia. The results demonstrated that pH values were estimated to 7.21 ± 0.05, 7.13 ± 0.09, and 7.27 ± 0.06 in the striatum, hippocampus, and cortex in the rat brains, respectively, in normal conditions. However, pH decreased to 6.75 ± 0.07 and 6.52 ± 0.03 in the striatum and hippocampus, upon global cerebral ischemia, while a negligible pH change was obtained in the cortex.

Auditory brain development in premature infants: the importance of early experience.

PubMed

McMahon, Erin; Wintermark, Pia; Lahav, Amir

2012-04-01

Preterm infants in the neonatal intensive care unit (NICU) often close their eyes in response to bright lights, but they cannot close their ears in response to loud sounds. The sudden transition from the womb to the overly noisy world of the NICU increases the vulnerability of these high-risk newborns. There is a growing concern that the excess noise typically experienced by NICU infants disrupts their growth and development, putting them at risk for hearing, language, and cognitive disabilities. Preterm neonates are especially sensitive to noise because their auditory system is at a critical period of neurodevelopment, and they are no longer shielded by maternal tissue. This paper discusses the developmental milestones of the auditory system and suggests ways to enhance the quality control and type of sounds delivered to NICU infants. We argue that positive auditory experience is essential for early brain maturation and may be a contributing factor for healthy neurodevelopment. Further research is needed to optimize the hospital environment for preterm newborns and to increase their potential to develop into healthy children. © 2012 New York Academy of Sciences.

Multimodal optical imaging database from tumour brain human tissue: endogenous fluorescence from glioma, metastasis and control tissues

NASA Astrophysics Data System (ADS)

Poulon, Fanny; Ibrahim, Ali; Zanello, Marc; Pallud, Johan; Varlet, Pascale; Malouki, Fatima; Abi Lahoud, Georges; Devaux, Bertrand; Abi Haidar, Darine

2017-02-01

Eliminating time-consuming process of conventional biopsy is a practical improvement, as well as increasing the accuracy of tissue diagnoses and patient comfort. We addressed these needs by developing a multimodal nonlinear endomicroscope that allows real-time optical biopsies during surgical procedure. It will provide immediate information for diagnostic use without removal of tissue and will assist the choice of the optimal surgical strategy. This instrument will combine several means of contrast: non-linear fluorescence, second harmonic generation signal, reflectance, fluorescence lifetime and spectral analysis. Multimodality is crucial for reliable and comprehensive analysis of tissue. Parallel to the instrumental development, we currently improve our understanding of the endogeneous fluorescence signal with the different modalities that will be implemented in the stated. This endeavor will allow to create a database on the optical signature of the diseased and control brain tissues. This proceeding will present the preliminary results of this database on three types of tissues: cortex, metastasis and glioblastoma.

Metastatic non-gestational choriocarcinoma to the brain: a case report and proposed treatment recommendations.

PubMed

Duong, Jason; Ghanchi, Hammad; Miulli, Dan; Kahlon, Avneet

2018-04-17

Non-gestational choriocarcinoma (NGC) is a rare germ cell tumor, reported less than 0.6% of all gestational tumors, and has a poor prognosis when metastasized. NGC is even less reported with metastasis to the brain. Gestational choriocarcinoma (GC) when metastasized to the brain has a higher morbidity and mortality but has been known to be a chemosensitive and radiosensitive lesion, and NGC is chemoresistant with an even worse prognosis. Currently, there is no consensus for treatment for metastatic NGC to the brain. 66 year-old post-menopausal female presents with left upper extremity weakness more pronounced in her hand, and work up demonstrating a hemorrhagic lesion over the right frontal parietal lobe. Her metastatic work up was negative, leading to a craniotomy for resection of the mass. The pathology was consistent with metastatic gestational choriocarcinoma, non-gestational in origin. Because of its chemosensitive nature, reports of optimal metastatic GC treatment include radiation alone, chemotherapy without radiation, surgical resection, or combined multimodal therapy. No recommendations for NGC metastatic to the brain have been reported. We propose a systematic work up for hemorrhagic brain lesions to include the proposed imaging modalities and serum markers including β-hCG to aid with early diagnosis. With review of literature, we recommend surgical resection with adjuvant therapy for accessible symptomatic metastatic GC and NGC to the brain for optimal patient outcomes. Chemotherapy and radiation alone without surgical resection can be considered for asymptomatic GC metastasis to the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

'Who is the ideal candidate?': decisions and issues relating to visual neuroprosthesis development, patient testing and neuroplasticity

NASA Astrophysics Data System (ADS)

Merabet, Lotfi B.; Rizzo, Joseph F., III; Pascual-Leone, Alvaro; Fernandez, Eduardo

2007-03-01

Appropriate delivery of electrical stimulation to intact visual structures can evoke patterned sensations of light in individuals who have been blind for many years. This pivotal finding has lent credibility to the concept of restoring functional vision by artificial means. As numerous groups worldwide pursue human clinical testing with visual prosthetic devices, it is becoming increasingly clear that there remains a considerable gap between the challenges of prosthetic device development and the rehabilitative strategies needed to implement this new technology in patients. An important area of future work will be the development of appropriate pre- and post-implantation measures of performance and establishing candidate selection criteria in order to quantify technical advances, guide future device design and optimize therapeutic success. We propose that the selection of an 'ideal' candidate should also be considered within the context of the variable neuroplastic changes that follow vision loss. Specifically, an understanding of the adaptive and compensatory changes that occur within the brain could assist in guiding the development of post-implantation rehabilitative strategies and optimize behavioral outcomes.

In Vivo Fiber-Optic Raman Mapping Of Metastases In Mouse Brains

NASA Astrophysics Data System (ADS)

Stelling, A.; Kirsch, M.; Steiner, G.; Krafft, C.; Schackert, G.; Salzer, R.

2010-08-01

Vibrational spectroscopy, in particular Raman spectroscopy, has potential applications in the field of in vivo diagnostics. Raman and FT-IR spectroscopy analyze the complete biochemical information at any given pixel within the visual field. Here we demonstrate the feasibility of performing Raman spectroscopic measurements on living mice brains using a fiber-optic probe with a nominal spatial resolution of 60 μm. The objectives of this study were to 1) evaluate preclinical models, namely murine brain slices containing experimental tumors, 2) optimize the preparation of pristine brain tissue to obtain reference information, to 3) optimize the conditions for introducing a fiber-optic probe to acquire Raman maps in vivo, and 4) to transfer results obtained from human brain tumors to an animal model. Disseminated brain metastases of malignant melanomas were induced by injecting tumor cells into the carotid artery of mice. The procedure mimicked hematogenous tumor spread in one brain hemisphere while the other hemisphere remained tumor free. Three series of sections were prepared consecutively from whole mouse brains: pristine, 2-mm thick sections for Raman mapping and dried, thin sections for FT-IR imaging, hematoxylin and eosin-stained thin sections for histopathological assessment. Raman maps were collected serially using a spectrometer coupled to a fiber-optic probe. FT-IR images were recorded using a spectrometer with a multi-channel detector. The FT-IR images and the Raman maps were evaluated by multivariate data analysis. The results obtained from the thin section studies were employed to guide measurements of murine brains in vivo. Raman maps with an acquisition time of over an hour could be performed on the living animals. No damage to the tissue was observed.

Neuropathological biomarker candidates in brain tumors: key issues for translational efficiency.

PubMed

Hainfellner, J A; Heinzl, H

2010-01-01

Brain tumors comprise a large spectrum of rare malignancies in children and adults that are often associated with severe neurological symptoms and fatal outcome. Neuropathological tumor typing provides both prognostic and predictive tissue information which is the basis for optimal postoperative patient management and therapy. Molecular biomarkers may extend and refine prognostic and predictive information in a brain tumor case, providing more individualized and optimized treatment options. In the recent past a few neuropathological brain tumor biomarkers have translated smoothly into clinical use whereas many candidates show protracted translation. We investigated the causes of protracted translation of candidate brain tumor biomarkers. Considering the research environment from personal, social and systemic perspectives we identified eight determinants of translational success: methodology, funding, statistics, organization, phases of research, cooperation, self-reflection, and scientific progeny. Smoothly translating biomarkers are associated with low degrees of translational complexity whereas biomarkers with protracted translation are associated with high degrees. Key issues for translational efficiency of neuropathological brain tumor biomarker research seem to be related to (i) the strict orientation to the mission of medical research, that is the improval of medical practice as primordial purpose of research, (ii) definition of research priorities according to clinical needs, and (iii) absorption of translational complexities by means of operatively beneficial standards. To this end, concrete actions should comprise adequate scientific education of young investigators, and shaping of integrative diagnostics and therapy research both on the local level and the level of influential international brain tumor research platforms.

Joint brain connectivity estimation from diffusion and functional MRI data

NASA Astrophysics Data System (ADS)

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

2015-03-01

Estimating brain wiring patterns is critical to better understand the brain organization and function. Anatomical brain connectivity models axonal pathways, while the functional brain connectivity characterizes the statistical dependencies and correlation between the activities of various brain regions. The synchronization of brain activity can be inferred through the variation of blood-oxygen-level dependent (BOLD) signal from functional MRI (fMRI) and the neural connections can be estimated using tractography from diffusion MRI (dMRI). Functional connections between brain regions are supported by anatomical connections, and the synchronization of brain activities arises through sharing of information in the form of electro-chemical signals on axon pathways. Jointly modeling fMRI and dMRI data may improve the accuracy in constructing anatomical connectivity as well as functional connectivity. Such an approach may lead to novel multimodal biomarkers potentially able to better capture functional and anatomical connectivity variations. We present a novel brain network model which jointly models the dMRI and fMRI data to improve the anatomical connectivity estimation and extract the anatomical subnetworks associated with specific functional modes by constraining the anatomical connections as structural supports to the functional connections. The key idea is similar to a multi-commodity flow optimization problem that minimizes the cost or maximizes the efficiency for flow configuration and simultaneously fulfills the supply-demand constraint for each commodity. In the proposed network, the nodes represent the grey matter (GM) regions providing brain functionality, and the links represent white matter (WM) fiber bundles connecting those regions and delivering information. The commodities can be thought of as the information corresponding to brain activity patterns as obtained for instance by independent component analysis (ICA) of fMRI data. The concept of information flow is introduced and used to model the propagation of information between GM areas through WM fiber bundles. The link capacity, i.e., ability to transfer information, is characterized by the relative strength of fiber bundles, e.g., fiber count gathered from the tractography of dMRI data. The node information demand is considered to be proportional to the correlation between neural activity at various cortical areas involved in a particular functional mode (e.g. visual, motor, etc.). These two properties lead to the link capacity and node demand constraints in the proposed model. Moreover, the information flow of a link cannot exceed the demand from either end node. This is captured by the feasibility constraints. Two different cost functions are considered in the optimization formulation in this paper. The first cost function, the reciprocal of fiber strength represents the unit cost for information passing through the link. In the second cost function, a min-max (minimizing the maximal link load) approach is used to balance the usage of each link. Optimizing the first cost function selects the pathway with strongest fiber strength for information propagation. In the second case, the optimization procedure finds all the possible propagation pathways and allocates the flow proportionally to their strength. Additionally, a penalty term is incorporated with both the cost functions to capture the possible missing and weak anatomical connections. With this set of constraints and the proposed cost functions, solving the network optimization problem recovers missing and weak anatomical connections supported by the functional information and provides the functional-associated anatomical subnetworks. Feasibility is demonstrated using realistic diffusion and functional MRI phantom data. It is shown that the proposed model recovers the maximum number of true connections, with fewest number of false connections when compared with the connectivity derived from a joint probabilistic model using the expectation-maximization (EM) algorithm presented in a prior work. We also apply the proposed method to data provided by the Human Connectome Project (HCP).

Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.

PubMed

Yang, Zhang; Shufan, Ye; Li, Guo; Weifeng, Ding

2016-01-01

The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method.

Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm

PubMed Central

Yang, Zhang; Li, Guo; Weifeng, Ding

2016-01-01

The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428

Repeated assessment of orthotopic glioma pO2 by multi-site EPR oximetry: A technique with the potential to guide therapeutic optimization by repeated measurements of oxygen

PubMed Central

Khan, Nadeem; Mupparaju, Sriram; Hou, Huagang; Williams, Benjamin B.; Swartz, Harold

2011-01-01

Tumor hypoxia plays a vital role in therapeutic resistance. Consequently, measurements of tumor pO2 could be used to optimize the outcome of oxygen-dependent therapies, such as, chemoradiation. However, the potential optimizations are restricted by the lack of methods to repeatedly and quantitatively assess tumor pO2 during therapies, particularly in gliomas. We describe the procedures for repeated measurements of orthotopic glioma pO2 by multi-site electron paramagnetic resonance (EPR) oximetry. This oximetry approach provides simultaneous measurements of pO2 at more than one site in the glioma and contralateral cerebral tissue. The pO2 of intracerebral 9L, C6, F98 and U251 tumors, as well as contralateral brain, were measured repeatedly for five consecutive days. The 9L glioma was well oxygenated with pO2 of 27 - 36 mm Hg, while C6, F98 and U251 glioma were hypoxic with pO2 of 7 - 12 mm Hg. The potential of multi-site EPR oximetry to assess temporal changes in tissue pO2 was investigated in rats breathing 100% O2. A significant increase in F98 tumor and contralateral brain pO2 was observed on day 1 and day 2, however, glioma oxygenation declined on subsequent days. In conclusion, EPR oximetry provides the capability to repeatedly assess temporal changes in orthotopic glioma pO2. This information could be used to test and optimize the methods being developed to modulate tumor hypoxia. Furthermore, EPR oximetry could be potentially used to enhance the outcome of chemoradiation by scheduling treatments at times of increase in glioma pO2. PMID:22079559

Cognitive state monitoring and the design of adaptive instruction in digital environments: lessons learned from cognitive workload assessment using a passive brain-computer interface approach

PubMed Central

Gerjets, Peter; Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Zander, Thorsten O.

2014-01-01

According to Cognitive Load Theory (CLT), one of the crucial factors for successful learning is the type and amount of working-memory load (WML) learners experience while studying instructional materials. Optimal learning conditions are characterized by providing challenges for learners without inducing cognitive over- or underload. Thus, presenting instruction in a way that WML is constantly held within an optimal range with regard to learners' working-memory capacity might be a good method to provide these optimal conditions. The current paper elaborates how digital learning environments, which achieve this goal can be developed by combining approaches from Cognitive Psychology, Neuroscience, and Computer Science. One of the biggest obstacles that needs to be overcome is the lack of an unobtrusive method of continuously assessing learners' WML in real-time. We propose to solve this problem by applying passive Brain-Computer Interface (BCI) approaches to realistic learning scenarios in digital environments. In this paper we discuss the methodological and theoretical prospects and pitfalls of this approach based on results from the literature and from our own research. We present a strategy on how several inherent challenges of applying BCIs to WML and learning can be met by refining the psychological constructs behind WML, by exploring their neural signatures, by using these insights for sophisticated task designs, and by optimizing algorithms for analyzing electroencephalography (EEG) data. Based on this strategy we applied machine-learning algorithms for cross-task classifications of different levels of WML to tasks that involve studying realistic instructional materials. We obtained very promising results that yield several recommendations for future work. PMID:25538544

Active SAmpling Protocol (ASAP) to Optimize Individual Neurocognitive Hypothesis Testing: A BCI-Inspired Dynamic Experimental Design.

PubMed

Sanchez, Gaëtan; Lecaignard, Françoise; Otman, Anatole; Maby, Emmanuel; Mattout, Jérémie

2016-01-01

The relatively young field of Brain-Computer Interfaces has promoted the use of electrophysiology and neuroimaging in real-time. In the meantime, cognitive neuroscience studies, which make extensive use of functional exploration techniques, have evolved toward model-based experiments and fine hypothesis testing protocols. Although these two developments are mostly unrelated, we argue that, brought together, they may trigger an important shift in the way experimental paradigms are being designed, which should prove fruitful to both endeavors. This change simply consists in using real-time neuroimaging in order to optimize advanced neurocognitive hypothesis testing. We refer to this new approach as the instantiation of an Active SAmpling Protocol (ASAP). As opposed to classical (static) experimental protocols, ASAP implements online model comparison, enabling the optimization of design parameters (e.g., stimuli) during the course of data acquisition. This follows the well-known principle of sequential hypothesis testing. What is radically new, however, is our ability to perform online processing of the huge amount of complex data that brain imaging techniques provide. This is all the more relevant at a time when physiological and psychological processes are beginning to be approached using more realistic, generative models which may be difficult to tease apart empirically. Based upon Bayesian inference, ASAP proposes a generic and principled way to optimize experimental design adaptively. In this perspective paper, we summarize the main steps in ASAP. Using synthetic data we illustrate its superiority in selecting the right perceptual model compared to a classical design. Finally, we briefly discuss its future potential for basic and clinical neuroscience as well as some remaining challenges.

Repeated assessment of orthotopic glioma pO(2) by multi-site EPR oximetry: a technique with the potential to guide therapeutic optimization by repeated measurements of oxygen.

PubMed

Khan, Nadeem; Mupparaju, Sriram; Hou, Huagang; Williams, Benjamin B; Swartz, Harold

2012-02-15

Tumor hypoxia plays a vital role in therapeutic resistance. Consequently, measurements of tumor pO(2) could be used to optimize the outcome of oxygen-dependent therapies, such as, chemoradiation. However, the potential optimizations are restricted by the lack of methods to repeatedly and quantitatively assess tumor pO(2) during therapies, particularly in gliomas. We describe the procedures for repeated measurements of orthotopic glioma pO(2) by multi-site electron paramagnetic resonance (EPR) oximetry. This oximetry approach provides simultaneous measurements of pO(2) at more than one site in the glioma and contralateral cerebral tissue. The pO(2) of intracerebral 9L, C6, F98 and U251 tumors, as well as contralateral brain, were measured repeatedly for five consecutive days. The 9L glioma was well oxygenated with pO(2) of 27-36 mm Hg, while C6, F98 and U251 glioma were hypoxic with pO(2) of 7-12mm Hg. The potential of multi-site EPR oximetry to assess temporal changes in tissue pO(2) was investigated in rats breathing 100% O(2). A significant increase in F98 tumor and contralateral brain pO(2) was observed on day 1 and day 2, however, glioma oxygenation declined on subsequent days. In conclusion, EPR oximetry provides the capability to repeatedly assess temporal changes in orthotopic glioma pO(2). This information could be used to test and optimize the methods being developed to modulate tumor hypoxia. Furthermore, EPR oximetry could be potentially used to enhance the outcome of chemoradiation by scheduling treatments at times of increase in glioma pO(2). Copyright © 2011 Elsevier B.V. All rights reserved.

[Peroperative risks in cerebral aneurysm surgery].

PubMed

Mustaki, J P; Bissonnette, B; Archer, D; Boulard, G; Ravussin, P

1996-01-01

The perioperative complications associated with cerebral aneurysm surgery require a specific anaesthetic management. Four major perioperative accidents are discussed in this review. The anaesthetic and surgical management in case of rebleeding subsequent to the re-rupture of the aneurysm is mainly prophylactic. It includes haemodynamic stability assurance, maintenance of mean arterial pressure (MAP) between 80-90 mmHg during stimulation of the patient such as endotracheal intubation, application of the skull-pin head-holder, incision, and craniotomy. The aneurysmal transmural pressure should be adequately maintained by avoiding an aggressive decrease of intracranial pressure. Once the skull is open, the brain must be kept slack in order to decrease pressure under the retractors and avoid the risks of stretching and tearing of the adjacent vessels. If, despite these precautions, the aneurysm ruptures again. MAP should be decreased to 60 mmHg and the brain rendered more slack, in order to allow direct clipping of the aneurysm, or temporary clipping of the adjacent vessels. The optimal agents in this situation are isoflurane (which decreases CMRO2), intravenous anaesthetic agents (inspite their negative inotropic effect, they may potentially protect the brain) and sodium nitroprusside. Vasospasm occurs usually between the 3rd and the 7th day after subarachnoid haemorrhage. It may be seen peroperatively. The optimal treatment, as well as prophylaxis, is moderate controlled hypertension (MAP > 100 mmHg), associated with hypervolaemia and haemodilution, the so-called triple H therapy, with strict control of the filling pressures. Other beneficial therapies are calcium antagonists (nimodipine and nicardipine), the removal of the blood accumulated around the brain and in the cisternae, and possibly local administration of papaverine. Abrupt MAP increases are controlled in order to maintain adequate aneurysmal transmural pressure. Beta-blockers, local anaesthetics administered locally or intravenously, a carefully titrated level of anaesthesia, a maintained volaemia play a protective role. Cerebral oedema is sometimes already present at the opening of the skull or may arise later, due to a high pressure under the retractors, to the surgical manipulations of the brain or to brain ischaemia subsequent to temporary clipping. Its treatment is aggressive, with intravenous agents, mannitol, deep hypocapnia and/or lumbar drainage. Prophylaxis, according to the "brain homeostasis concept", is the preferred method to avoid these four peroperative accidents. It includes normal blood volume, normoglycaemia, moderate hypocapnia, normotension, soft manipulation of the brain and optimal brain relaxation.

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

PubMed

Fissler, Patrick; Kolassa, Iris-Tatjana; Schrader, Claudia

2015-01-01

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.

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

PubMed Central

Fissler, Patrick; Kolassa, Iris-Tatjana; Schrader, Claudia

2015-01-01

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. PMID:26257697

Optimization of PET instrumentation for brain activation studies

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

Dahlbom, M.; Cherry, S.R.; Hoffman, E.J.

By performing cerebral blood flow studies with positron emission tomography (PET), and comparing blood flow images of different states of activation, functional mapping of the brain is possible. The ability of current commercial instruments to perform such studies is investigated in this work, based on a comparison of noise equivalent count (NEC) rates. Differences in the NEC performance of the different scanners in conjunction with scanner design parameters, provide insights into the importance of block design (size, dead time, crystal thickness) and overall scanner design (sensitivity and scatter fraction) for optimizing data from activation studies. The newer scanners with removablemore » septa, operating with 3-D acquisition, have much higher sensitivity, but require new methodology for optimized operation. Only by administering multiple low doses (fractionation) of the flow tracer can the high sensitivity be utilized.« less

Targeting blood–brain barrier changes during inflammatory pain: an opportunity for optimizing CNS drug delivery

PubMed Central

Ronaldson, Patrick T; Davis, Thomas P

2012-01-01

The blood–brain barrier (BBB) is the most significant obstacle to effective CNS drug delivery. It possesses structural and biochemical features (i.e., tight-junction protein complexes and, influx and efflux transporters) that restrict xenobiotic permeation. Pathophysiological stressors (i.e., peripheral inflammatory pain) can alter BBB tight junctions and transporters, which leads to drug-permeation changes. This is especially critical for opioids, which require precise CNS concentrations to be safe and effective analgesics. Recent studies have identified molecular targets (i.e., endogenous transporters and intracellular signaling systems) that can be exploited for optimization of CNS drug delivery. This article summarizes current knowledge in this area and emphasizes those targets that present the greatest opportunity for controlling drug permeation and/or drug transport across the BBB in an effort to achieve optimal CNS opioid delivery. PMID:22468221

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

PubMed

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.

A preliminary study of the effects of working memory training on brain function.

PubMed

Stevens, Michael C; Gaynor, Alexandra; Bessette, Katie L; Pearlson, Godfrey D

2016-06-01

Working memory (WM) training improves WM ability in Attention-Deficit/Hyperactivity Disorder (ADHD), but its efficacy for non-cognitive ADHD impairments ADHD has been sharply debated. The purpose of this preliminary study was to characterize WM training-related changes in ADHD brain function and see if they were linked to clinical improvement. We examined 18 adolescents diagnosed with DSM-IV Combined-subtype ADHD before and after 25 sessions of WM training using a frequently employed approach (Cogmed™) using a nonverbal Sternberg WM fMRI task, neuropsychological tests, and participant- and parent-reports of ADHD symptom severity and associated functional impairment. Whole brain SPM8 analyses identified ADHD activation deficits compared to 18 non-ADHD control participants, then tested whether impaired ADHD frontoparietal brain activation would increase following WM training. Post hoc tests examined the relationships between neural changes and neurocognitive or clinical improvements. As predicted, WM training increased WM performance, ADHD clinical functioning, and WM-related ADHD brain activity in several frontal, parietal and temporal lobe regions. Increased left inferior frontal sulcus region activity was seen in all Encoding, Maintenance, and Retrieval Sternberg task phases. ADHD symptom severity improvements were most often positively correlated with activation gains in brain regions known to be engaged for WM-related executive processing; improvement of different symptom types had different neural correlates. The responsiveness of both amodal WM frontoparietal circuits and executive process-specific WM brain regions was altered by WM training. The latter might represent a promising, relatively unexplored treatment target for researchers seeking to optimize clinical response in ongoing ADHD WM training development efforts.

Image segmentation by EM-based adaptive pulse coupled neural networks in brain magnetic resonance imaging.

PubMed

Fu, J C; Chen, C C; Chai, J W; Wong, S T C; Li, I C

2010-06-01

We propose an automatic hybrid image segmentation model that integrates the statistical expectation maximization (EM) model and the spatial pulse coupled neural network (PCNN) for brain magnetic resonance imaging (MRI) segmentation. In addition, an adaptive mechanism is developed to fine tune the PCNN parameters. The EM model serves two functions: evaluation of the PCNN image segmentation and adaptive adjustment of the PCNN parameters for optimal segmentation. To evaluate the performance of the adaptive EM-PCNN, we use it to segment MR brain image into gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). The performance of the adaptive EM-PCNN is compared with that of the non-adaptive EM-PCNN, EM, and Bias Corrected Fuzzy C-Means (BCFCM) algorithms. The result is four sets of boundaries for the GM and the brain parenchyma (GM+WM), the two regions of most interest in medical research and clinical applications. Each set of boundaries is compared with the golden standard to evaluate the segmentation performance. The adaptive EM-PCNN significantly outperforms the non-adaptive EM-PCNN, EM, and BCFCM algorithms in gray mater segmentation. In brain parenchyma segmentation, the adaptive EM-PCNN significantly outperforms the BCFCM only. However, the adaptive EM-PCNN is better than the non-adaptive EM-PCNN and EM on average. We conclude that of the three approaches, the adaptive EM-PCNN yields the best results for gray matter and brain parenchyma segmentation. Copyright 2009 Elsevier Ltd. All rights reserved.

Care pathways for organ donation after brain death: guidance from available literature?

PubMed

Hoste, Pieter; Vanhaecht, Kris; Ferdinande, Patrick; Rogiers, Xavier; Eeckloo, Kristof; Blot, Stijn; Hoste, Eric; Vogelaers, Dirk; Vandewoude, Koenraad

2016-10-01

A discussion of the literature concerning the impact of care pathways in the complex and by definition multidisciplinary process of organ donation following brain death. Enhancing the quality and safety of organs for transplantation has become a central concern for governmental and professional organizations. At the local hospital level, a donor coordinator can use a range of interventions to improve the donation and procurement process. Care pathways have been proven to represent an effective intervention in several settings for optimizing processes and outcomes. A discussion paper. A systematic review of the Medline, CINAHL, EMBASE and The Cochrane Library databases was conducted for articles published until June 2015, using the keywords donation after brain death and care pathways. Each paper was reviewed to investigate the effects of existing care pathways for donation after brain death. An additional search for unpublished information was conducted. Although literature supports care pathways as an effective intervention in several settings, few studies have explored its use and effectiveness for complex care processes such as donation after brain death. Nurses should be aware of their role in the donation process. Care pathways have the potential to support them, but their effectiveness has been insufficiently explored. Further research should focus on the development and standardization of the clinical content of a care pathway for donation after brain death and the identification of quality indicators. These should be used in a prospective effectiveness assessment of the proposed pathway. © 2016 John Wiley & Sons Ltd.

Hierarchical probabilistic Gabor and MRF segmentation of brain tumours in MRI volumes.

PubMed

Subbanna, Nagesh K; Precup, Doina; Collins, D Louis; Arbel, Tal

2013-01-01

In this paper, we present a fully automated hierarchical probabilistic framework for segmenting brain tumours from multispectral human brain magnetic resonance images (MRIs) using multiwindow Gabor filters and an adapted Markov Random Field (MRF) framework. In the first stage, a customised Gabor decomposition is developed, based on the combined-space characteristics of the two classes (tumour and non-tumour) in multispectral brain MRIs in order to optimally separate tumour (including edema) from healthy brain tissues. A Bayesian framework then provides a coarse probabilistic texture-based segmentation of tumours (including edema) whose boundaries are then refined at the voxel level through a modified MRF framework that carefully separates the edema from the main tumour. This customised MRF is not only built on the voxel intensities and class labels as in traditional MRFs, but also models the intensity differences between neighbouring voxels in the likelihood model, along with employing a prior based on local tissue class transition probabilities. The second inference stage is shown to resolve local inhomogeneities and impose a smoothing constraint, while also maintaining the appropriate boundaries as supported by the local intensity difference observations. The method was trained and tested on the publicly available MICCAI 2012 Brain Tumour Segmentation Challenge (BRATS) Database [1] on both synthetic and clinical volumes (low grade and high grade tumours). Our method performs well compared to state-of-the-art techniques, outperforming the results of the top methods in cases of clinical high grade and low grade tumour core segmentation by 40% and 45% respectively.

The construction of MRI brain/head templates for Chinese children from 7 to 16 years of age

PubMed Central

Xie, Wanze; Richards, John E.; Lei, Du; Zhu, Hongyan; Lee, Kang; Gong, Qiyong

2015-01-01

Population-specific brain templates that provide detailed brain information are beneficial to both structural and functional neuroimaging research. However, age-specific MRI templates have not been constructed for Chinese or any Asian developmental populations. This study developed novel T1-weighted average brain and head templates for Chinese children from 7 to 16 years of age in two-year increments using high quality magnetic resonance imaging (MRI) and well-validated image analysis techniques. A total of 138 Chinese children (51 F/87 M) were included in this study. The internally and externally validated registrations show that these Chinese age-specific templates fit Chinese children’s MR images significantly better than age-specific templates created from U.S. children, or adult templates based on either Chinese or North American adults. It implies that age-inappropriate (e.g., the Chinese56 template, the US20–24 template) and nationality-inappropriate brain templates (e.g., U.S. children’s templates, the US20–24 template) do not provide optimal reference MRIs for processing MR brain images of Chinese pediatric populations. Thus, our age-specific MRI templates are the first of the kind and should be useful in neuroimaging studies with children from Chinese or other Asian populations. These templates can also serve as the foundations for the construction of more comprehensive sets of nationality-specific templates for Asian developmental populations. These templates are available for use in our database. PMID:26343862

Pharmacokinetic/Pharmacodynamic Relationship of Gabapentin in a CFA-induced Inflammatory Hyperalgesia Rat Model.

PubMed

Larsen, Malte Selch; Keizer, Ron; Munro, Gordon; Mørk, Arne; Holm, René; Savic, Rada; Kreilgaard, Mads

2016-05-01

Gabapentin displays non-linear drug disposition, which complicates dosing for optimal therapeutic effect. Thus, the current study was performed to elucidate the pharmacokinetic/pharmacodynamic (PKPD) relationship of gabapentin's effect on mechanical hypersensitivity in a rat model of CFA-induced inflammatory hyperalgesia. A semi-mechanistic population-based PKPD model was developed using nonlinear mixed-effects modelling, based on gabapentin plasma and brain extracellular fluid (ECF) time-concentration data and measurements of CFA-evoked mechanical hyperalgesia following administration of a range of gabapentin doses (oral and intravenous). The plasma/brain ECF concentration-time profiles of gabapentin were adequately described with a two-compartment plasma model with saturable intestinal absorption rate (K m  = 44.1 mg/kg, V max  = 41.9 mg/h∙kg) and dose-dependent oral bioavailability linked to brain ECF concentration through a transit compartment. Brain ECF concentration was directly linked to a sigmoid E max function describing reversal of hyperalgesia (EC 50, plasma  = 16.7 μg/mL, EC 50, brain  = 3.3 μg/mL). The proposed semi-mechanistic population-based PKPD model provides further knowledge into the understanding of gabapentin's non-linear pharmacokinetics and the link between plasma/brain disposition and anti-hyperalgesic effects. The model suggests that intestinal absorption is the primary source of non-linearity and that the investigated rat model provides reasonable predictions of clinically effective plasma concentrations for gabapentin.

Battery-Less Electroencephalogram System Architecture Optimization

DTIC Science & Technology

2016-12-01

disorders, especially in real-world situations, such as when a Soldier is in theater. There are several methods to study the electrical activity in the brain...to measure the electrical activity in the brain that can still be used to study brain activity. Currently, most EEGs are recorded in highly controlled...base to build a larger system as its power consumption would allow it to operate from a AA battery for more than 72 h. While this might be acceptable

Novel and sensitive reversed-phase high-pressure liquid chromatography method with electrochemical detection for the simultaneous and fast determination of eight biogenic amines and metabolites in human brain tissue.

PubMed

Van Dam, Debby; Vermeiren, Yannick; Aerts, Tony; De Deyn, Peter Paul

2014-08-01

A fast and simple RP-HPLC method with electrochemical detection (ECD) and ion pair chromatography was developed, optimized and validated in order to simultaneously determine eight different biogenic amines and metabolites in post-mortem human brain tissue in a single-run analytical approach. The compounds of interest are the indolamine serotonin (5-hydroxytryptamine, 5-HT), the catecholamines dopamine (DA) and (nor)epinephrine ((N)E), as well as their respective metabolites, i.e. 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA), 5-hydroxy-3-indoleacetic acid (5-HIAA) and 3-methoxy-4-hydroxyphenylglycol (MHPG). A two-level fractional factorial experimental design was applied to study the effect of five experimental factors (i.e. the ion-pair counter concentration, the level of organic modifier, the pH of the mobile phase, the temperature of the column, and the voltage setting of the detector) on the chromatographic behaviour. The cross effect between the five quantitative factors and the capacity and separation factors of the analytes were then analysed using a Standard Least Squares model. The optimized method was fully validated according to the requirements of SFSTP (Société Française des Sciences et Techniques Pharmaceutiques). Our human brain tissue sample preparation procedure is straightforward and relatively short, which allows samples to be loaded onto the HPLC system within approximately 4h. Additionally, a high sample throughput was achieved after optimization due to a total runtime of maximally 40min per sample. The conditions and settings of the HPLC system were found to be accurate with high intra and inter-assay repeatability, recovery and accuracy rates. The robust analytical method results in very low detection limits and good separation for all of the eight biogenic amines and metabolites in this complex mixture of biological analytes. Copyright © 2014 Elsevier B.V. All rights reserved.

Red and NIR light dosimetry in the human deep brain

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Constructing and assessing brain templates from Chinese pediatric MRI data using SPM

NASA Astrophysics Data System (ADS)

Yin, Qingjie; Ye, Qing; Yao, Li; Chen, Kewei; Jin, Zhen; Liu, Gang; Wu, Xingchun; Wang, Tingting

2005-04-01

Spatial normalization is a very important step in the processing of magnetic resonance imaging (MRI) data. So the quality of brain templates is crucial for the accuracy of MRI analysis. In this paper, using the classical protocol and the optimized protocol plus nonlinear deformation, we constructed the T1 whole brain templates and apriori brain tissue data from 69 Chinese pediatric MRI data (age 7-16 years). Then we proposed a new assessment method to evaluate our templates. 10 pediatric subjects were chosen to do the assessment as the following steps. First, the cerebellum region, the region of interest (ROI), was located on both the pediatric volume and the template volume by an experienced neuroanatomist. Second, the pediatric whole brain was mapped to the template with affine and nonlinear deformation. Third, the parameter, derived from the second step, was used to only normalize the ROI of the child to the ROI of the template. Last, the overlapping ratio, which described the overlapping rate between the ROI of the template and the normalized ROI of the child, was calculated. The mean of overlapping ratio normalized to the classical template was 0.9687, and the mean normalized to the optimized template was 0.9713. The results show that the two Chinese pediatric brain templates are comparable and their accuracy is adequate to our studies.

Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases

PubMed Central

Fox, Michael D.; Buckner, Randy L.; Liu, Hesheng; Chakravarty, M. Mallar; Lozano, Andres M.; Pascual-Leone, Alvaro

2014-01-01

Brain stimulation, a therapy increasingly used for neurological and psychiatric disease, traditionally is divided into invasive approaches, such as deep brain stimulation (DBS), and noninvasive approaches, such as transcranial magnetic stimulation. The relationship between these approaches is unknown, therapeutic mechanisms remain unclear, and the ideal stimulation site for a given technique is often ambiguous, limiting optimization of the stimulation and its application in further disorders. In this article, we identify diseases treated with both types of stimulation, list the stimulation sites thought to be most effective in each disease, and test the hypothesis that these sites are different nodes within the same brain network as defined by resting-state functional-connectivity MRI. Sites where DBS was effective were functionally connected to sites where noninvasive brain stimulation was effective across diseases including depression, Parkinson's disease, obsessive-compulsive disorder, essential tremor, addiction, pain, minimally conscious states, and Alzheimer’s disease. A lack of functional connectivity identified sites where stimulation was ineffective, and the sign of the correlation related to whether excitatory or inhibitory noninvasive stimulation was found clinically effective. These results suggest that resting-state functional connectivity may be useful for translating therapy between stimulation modalities, optimizing treatment, and identifying new stimulation targets. More broadly, this work supports a network perspective toward understanding and treating neuropsychiatric disease, highlighting the therapeutic potential of targeted brain network modulation. PMID:25267639

Atlas of optimal coil orientation and position for TMS: A computational study.

PubMed

Gomez-Tames, Jose; Hamasaka, Atsushi; Laakso, Ilkka; Hirata, Akimasa; Ugawa, Yoshikazu

2018-04-17

Transcranial magnetic stimulation (TMS) activates target brain structures in a non-invasive manner. The optimal orientation of the TMS coil for the motor cortex is well known and can be estimated using motor evoked potentials. However, there are no easily measurable responses for activation of other cortical areas and the optimal orientation for these areas is currently unknown. This study investigated the electric field strength, optimal coil orientation, and relative locations to optimally stimulate the target cortex based on computed electric field distributions. A total of 518,616 stimulation scenarios were studied using realistic head models (2401 coil locations × 12 coil angles × 18 head models). Inter-subject registration methods were used to generate an atlas of optimized TMS coil orientations on locations on the standard brain. We found that the maximum electric field strength is greater in primary somatosensory cortex and primary motor cortex than in other cortical areas. Additionally, a universal optimal coil orientation applicable to most subjects is more feasible at the primary somatosensory cortex and primary motor cortex. We confirmed that optimal coil angle follows the anatomical shape of the hand motor area to realize personalized optimization of TMS. Finally, on average, the optimal coil positions for TMS on the scalp deviated 5.5 mm from the scalp points with minimum cortex-scalp distance. This deviation was minimal at the premotor cortex and primary motor cortex. Personalized optimal coil orientation is preferable for obtaining the most effective stimulation. Copyright © 2018. Published by Elsevier Inc.

How the prior information shapes couplings in neural fields performing optimal multisensory integration

NASA Astrophysics Data System (ADS)

Wang, He; Zhang, Wen-Hao; Wong, K. Y. Michael; Wu, Si

Extensive studies suggest that the brain integrates multisensory signals in a Bayesian optimal way. However, it remains largely unknown how the sensory reliability and the prior information shape the neural architecture. In this work, we propose a biologically plausible neural field model, which can perform optimal multisensory integration and encode the whole profile of the posterior. Our model is composed of two modules, each for one modality. The crosstalks between the two modules can be carried out through feedforwad cross-links and reciprocal connections. We found that the reciprocal couplings are crucial to optimal multisensory integration in that the reciprocal coupling pattern is shaped by the correlation in the joint prior distribution of the sensory stimuli. A perturbative approach is developed to illustrate the relation between the prior information and features in coupling patterns quantitatively. Our results show that a decentralized architecture based on reciprocal connections is able to accommodate complex correlation structures across modalities and utilize this prior information in optimal multisensory integration. This work is supported by the Research Grants Council of Hong Kong (N_HKUST606/12 and 605813) and National Basic Research Program of China (2014CB846101) and the Natural Science Foundation of China (31261160495).

The brain-penetrant clinical ATM inhibitor AZD1390 radiosensitizes and improves survival of preclinical brain tumor models.

PubMed

Durant, Stephen T; Zheng, Li; Wang, Yingchun; Chen, Kan; Zhang, Lingli; Zhang, Tianwei; Yang, Zhenfan; Riches, Lucy; Trinidad, Antonio G; Fok, Jacqueline H L; Hunt, Tom; Pike, Kurt G; Wilson, Joanne; Smith, Aaron; Colclough, Nicola; Reddy, Venkatesh Pilla; Sykes, Andrew; Janefeldt, Annika; Johnström, Peter; Varnäs, Katarina; Takano, Akihiro; Ling, Stephanie; Orme, Jonathan; Stott, Jonathan; Roberts, Caroline; Barrett, Ian; Jones, Gemma; Roudier, Martine; Pierce, Andrew; Allen, Jasmine; Kahn, Jenna; Sule, Amrita; Karlin, Jeremy; Cronin, Anna; Chapman, Melissa; Valerie, Kristoffer; Illingworth, Ruth; Pass, Martin

2018-06-01

Poor survival rates of patients with tumors arising from or disseminating into the brain are attributed to an inability to excise all tumor tissue (if operable), a lack of blood-brain barrier (BBB) penetration of chemotherapies/targeted agents, and an intrinsic tumor radio-/chemo-resistance. Ataxia-telangiectasia mutated (ATM) protein orchestrates the cellular DNA damage response (DDR) to cytotoxic DNA double-strand breaks induced by ionizing radiation (IR). ATM genetic ablation or pharmacological inhibition results in tumor cell hypersensitivity to IR. We report the primary pharmacology of the clinical-grade, exquisitely potent (cell IC 50 , 0.78 nM), highly selective [>10,000-fold over kinases within the same phosphatidylinositol 3-kinase-related kinase (PIKK) family], orally bioavailable ATM inhibitor AZD1390 specifically optimized for BBB penetration confirmed in cynomolgus monkey brain positron emission tomography (PET) imaging of microdosed 11 C-labeled AZD1390 ( K p,uu , 0.33). AZD1390 blocks ATM-dependent DDR pathway activity and combines with radiation to induce G 2 cell cycle phase accumulation, micronuclei, and apoptosis. AZD1390 radiosensitizes glioma and lung cancer cell lines, with p53 mutant glioma cells generally being more radiosensitized than wild type. In in vivo syngeneic and patient-derived glioma as well as orthotopic lung-brain metastatic models, AZD1390 dosed in combination with daily fractions of IR (whole-brain or stereotactic radiotherapy) significantly induced tumor regressions and increased animal survival compared to IR treatment alone. We established a pharmacokinetic-pharmacodynamic-efficacy relationship by correlating free brain concentrations, tumor phospho-ATM/phospho-Rad50 inhibition, apoptotic biomarker (cleaved caspase-3) induction, tumor regression, and survival. On the basis of the data presented here, AZD1390 is now in early clinical development for use as a radiosensitizer in central nervous system malignancies.

Effect of shivering on brain tissue oxygenation during induced normothermia in patients with severe brain injury.

PubMed

Oddo, Mauro; Frangos, Suzanne; Maloney-Wilensky, Eileen; Andrew Kofke, W; Le Roux, Peter D; Levine, Joshua M

2010-02-01

We analyzed the impact of shivering on brain tissue oxygenation (PbtO(2)) during induced normothermia in patients with severe brain injury. We studied patients with severe brain injury who developed shivering during induced normothermia. Induced normothermia was applied to treat refractory fever (body temperature [BT] > or =38.3 degrees C, refractory to conventional treatment) using a surface cooling device with computerized adjustment of patient BT target to 37 +/- 0.5 degrees C. PbtO(2), intracranial pressure, mean arterial pressure, cerebral perfusion pressure, and BT were monitored continuously. Circulating water temperature of the device system was measured to assess the intensity of cooling. Fifteen patients (10 with severe traumatic brain injury, 5 with aneurysmal subarachnoid hemorrhage) were treated with induced normothermia for an average of 5 +/- 2 days. Shivering caused a significant decrease in PbtO(2) levels both in SAH and TBI patients. Compared to baseline, shivering was associated with an overall reduction of PbtO(2) from 34.1 +/- 7.3 to 24.4 +/- 5.5 mmHg (P < 0.001). A significant correlation was found between the magnitude of shivering-associated decrease of PbtO(2) (DeltaPbtO(2)) and circulating water temperature (R = 0.82, P < 0.001). In patients with severe brain injury treated with induced normothermia, shivering was associated with a significant decrease of PbtO(2), which correlated with the intensity of cooling. Monitoring of therapeutic cooling with computerized thermoregulatory systems may help prevent shivering and optimize the management of induced normothermia. The clinical significance of shivering-induced decrease in brain tissue oxygenation remains to be determined.

The brain-penetrant clinical ATM inhibitor AZD1390 radiosensitizes and improves survival of preclinical brain tumor models

PubMed Central

Wang, Yingchun; Chen, Kan; Zhang, Lingli; Zhang, Tianwei; Yang, Zhenfan; Riches, Lucy; Trinidad, Antonio G.; Pike, Kurt G.; Wilson, Joanne; Smith, Aaron; Colclough, Nicola; Johnström, Peter; Varnäs, Katarina; Takano, Akihiro; Ling, Stephanie; Orme, Jonathan; Stott, Jonathan; Barrett, Ian; Jones, Gemma; Allen, Jasmine; Kahn, Jenna; Sule, Amrita; Cronin, Anna; Chapman, Melissa; Illingworth, Ruth; Pass, Martin

2018-01-01

Poor survival rates of patients with tumors arising from or disseminating into the brain are attributed to an inability to excise all tumor tissue (if operable), a lack of blood-brain barrier (BBB) penetration of chemotherapies/targeted agents, and an intrinsic tumor radio-/chemo-resistance. Ataxia-telangiectasia mutated (ATM) protein orchestrates the cellular DNA damage response (DDR) to cytotoxic DNA double-strand breaks induced by ionizing radiation (IR). ATM genetic ablation or pharmacological inhibition results in tumor cell hypersensitivity to IR. We report the primary pharmacology of the clinical-grade, exquisitely potent (cell IC50, 0.78 nM), highly selective [>10,000-fold over kinases within the same phosphatidylinositol 3-kinase–related kinase (PIKK) family], orally bioavailable ATM inhibitor AZD1390 specifically optimized for BBB penetration confirmed in cynomolgus monkey brain positron emission tomography (PET) imaging of microdosed 11C-labeled AZD1390 (Kp,uu, 0.33). AZD1390 blocks ATM-dependent DDR pathway activity and combines with radiation to induce G2 cell cycle phase accumulation, micronuclei, and apoptosis. AZD1390 radiosensitizes glioma and lung cancer cell lines, with p53 mutant glioma cells generally being more radiosensitized than wild type. In in vivo syngeneic and patient-derived glioma as well as orthotopic lung-brain metastatic models, AZD1390 dosed in combination with daily fractions of IR (whole-brain or stereotactic radiotherapy) significantly induced tumor regressions and increased animal survival compared to IR treatment alone. We established a pharmacokinetic-pharmacodynamic-efficacy relationship by correlating free brain concentrations, tumor phospho-ATM/phospho-Rad50 inhibition, apoptotic biomarker (cleaved caspase-3) induction, tumor regression, and survival. On the basis of the data presented here, AZD1390 is now in early clinical development for use as a radiosensitizer in central nervous system malignancies. PMID:29938225

Region specific optimization of continuous linear attenuation coefficients based on UTE (RESOLUTE): application to PET/MR brain imaging

NASA Astrophysics Data System (ADS)

Ladefoged, Claes N.; Benoit, Didier; Law, Ian; Holm, Søren; Kjær, Andreas; Højgaard, Liselotte; Hansen, Adam E.; Andersen, Flemming L.

2015-10-01

The reconstruction of PET brain data in a PET/MR hybrid scanner is challenging in the absence of transmission sources, where MR images are used for MR-based attenuation correction (MR-AC). The main challenge of MR-AC is to separate bone and air, as neither have a signal in traditional MR images, and to assign the correct linear attenuation coefficient to bone. The ultra-short echo time (UTE) MR sequence was proposed as a basis for MR-AC as this sequence shows a small signal in bone. The purpose of this study was to develop a new clinically feasible MR-AC method with patient specific continuous-valued linear attenuation coefficients in bone that provides accurate reconstructed PET image data. A total of 164 [18F]FDG PET/MR patients were included in this study, of which 10 were used for training. MR-AC was based on either standard CT (reference), UTE or our method (RESOLUTE). The reconstructed PET images were evaluated in the whole brain, as well as regionally in the brain using a ROI-based analysis. Our method segments air, brain, cerebral spinal fluid, and soft tissue voxels on the unprocessed UTE TE images, and uses a mapping of R2* values to CT Hounsfield Units (HU) to measure the density in bone voxels. The average error of our method in the brain was 0.1% and less than 1.2% in any region of the brain. On average 95% of the brain was within  ±10% of PETCT, compared to 72% when using UTE. The proposed method is clinically feasible, reducing both the global and local errors on the reconstructed PET images, as well as limiting the number and extent of the outliers.

Dynamic variation in forebrain estradiol levels during song learning

PubMed Central

Chao, Andrew; Paon, Ashley; Remage-Healey, Luke

2014-01-01

Estrogens shape brain circuits during development, and the capacity to synthesize estrogens locally has consequences for both sexual differentiation and the acute modulation of circuits during early learning. A recently-optimized method to detect and quantify fluctuations in brain estrogens in vivo provides a direct means to explore how brain estrogen production contributes to both differentiation and neuromodulation during development. Here, we use this method to test the hypothesis that neuroestrogens are sexually-differentiated as well as dynamically responsive to song tutoring (via passive video/audio playback) during the period of song learning in juvenile zebra finches. Our results show that baseline neuroestradiol levels in the caudal forebrain do not differ between males and females during an early critical masculinization window. Instead, we observe a prominent difference between males and females in baseline neuroestradiol that emerges during the subadult stage as animals approach sexual maturity. Second, we observe that fluctuating neuroestradiol levels during periods of passive song tutoring exhibit a markedly different profile in juveniles as compared to adults. Specifically, neuroestrogens in the caudal forebrain are elevated following (rather than during) tutor song exposure in both juvenile males and females, suggesting an important role for the early consolidation of tutor song memories. These results further reveal a circadian influence on the fluctuations in local neuroestrogens during sensory/cognitive tasks. Taken together, these findings uncover several unexpected features of brain estrogen synthesis in juvenile animals that may have implications for secondary masculinization as well as the consolidation of recent sensory experiences. PMID:25205304

Brain and Surface Warping via Minimizing Lipschitz Extensions (PREPRINT)

DTIC Science & Technology

2006-01-01

Angenent, S. Haker , A. Tannenbaum, and R. Kikinis, “Conformal geometry and brain flattening,” Proc. MICCAI, pp. 271-278, 1999. 1 [2] G. Aronsson, M...surface mapping,” IEEE Transactions on Medical Imaging, 23:7, 2004. 1 [17] S. Haker , L. Zhu, A. Tannenbaum, and S. An- genent, “Optimal mass transport for

Skull Base Tumors

NASA Astrophysics Data System (ADS)

Schulz-Ertner, Daniela

In skull base tumors associated with a low radiosensitivity for conventional radiotherapy (RT), irradiation with proton or carbon ion beams facilitates a safe and accurate application of high tumor doses due to the favorable beam localization properties of these particle beams. Cranial nerves, the brain stem and normal brain tissue can at the same time be optimally spared.

The Sodium-Activated Potassium Channel Slack Is Required for Optimal Cognitive Flexibility in Mice

ERIC Educational Resources Information Center

Bausch, Anne E.; Dieter, Rebekka; Nann, Yvette; Hausmann, Mario; Meyerdierks, Nora; Kaczmarek, Leonard K.; Ruth, Peter; Lukowski, Robert

2015-01-01

"Kcnt1" encoded sodium-activated potassium channels (Slack channels) are highly expressed throughout the brain where they modulate the firing patterns and general excitability of many types of neurons. Increasing evidence suggests that Slack channels may be important for higher brain functions such as cognition and normal intellectual…

Spirocyclic β-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitors: from hit to lowering of cerebrospinal fluid (CSF) amyloid β in a higher species.

PubMed

Hunt, Kevin W; Cook, Adam W; Watts, Ryan J; Clark, Christopher T; Vigers, Guy; Smith, Darin; Metcalf, Andrew T; Gunawardana, Indrani W; Burkard, Michael; Cox, April A; Geck Do, Mary K; Dutcher, Darrin; Thomas, Allen A; Rana, Sumeet; Kallan, Nicholas C; DeLisle, Robert K; Rizzi, James P; Regal, Kelly; Sammond, Douglas; Groneberg, Robert; Siu, Michael; Purkey, Hans; Lyssikatos, Joseph P; Marlow, Allison; Liu, Xingrong; Tang, Tony P

2013-04-25

A hallmark of Alzheimer's disease is the brain deposition of amyloid beta (Aβ), a peptide of 36-43 amino acids that is likely a primary driver of neurodegeneration. Aβ is produced by the sequential cleavage of APP by BACE1 and γ-secretase; therefore, inhibition of BACE1 represents an attractive therapeutic target to slow or prevent Alzheimer's disease. Herein we describe BACE1 inhibitors with limited molecular flexibility and molecular weight that decrease CSF Aβ in vivo, despite efflux. Starting with spirocycle 1a, we explore structure-activity relationships of core changes, P3 moieties, and Asp binding functional groups in order to optimize BACE1 affinity, cathepsin D selectivity, and blood-brain barrier (BBB) penetration. Using wild type guinea pig and rat, we demonstrate a PK/PD relationship between free drug concentrations in the brain and CSF Aβ lowering. Optimization of brain exposure led to the discovery of (R)-50 which reduced CSF Aβ in rodents and in monkey.

Simultaneous detection of resolved glutamate, glutamine, and γ-aminobutyric acid at 4 T

NASA Astrophysics Data System (ADS)

Hu, Jiani; Yang, Shaolin; Xuan, Yang; Jiang, Quan; Yang, Yihong; Haacke, E. Mark

2007-04-01

A new approach is introduced to simultaneously detect resolved glutamate (Glu), glutamine (Gln), and γ-aminobutyric acid (GABA) using a standard STEAM localization pulse sequence with the optimized sequence timing parameters. This approach exploits the dependence of the STEAM spectra of the strongly coupled spin systems of Glu, Gln, and GABA on the echo time TE and the mixing time TM at 4 T to find an optimized sequence parameter set, i.e., {TE, TM}, where the outer-wings of the Glu C4 multiplet resonances around 2.35 ppm, the Gln C4 multiplet resonances around 2.45 ppm, and the GABA C2 multiplet resonance around 2.28 ppm are significantly suppressed and the three resonances become virtual singlets simultaneously and thus resolved. Spectral simulation and optimization were conducted to find the optimized sequence parameters, and phantom and in vivo experiments (on normal human brains, one patient with traumatic brain injury, and one patient with brain tumor) were carried out for verification. The results have demonstrated that the Gln, Glu, and GABA signals at 2.2-2.5 ppm can be well resolved using a standard STEAM sequence with the optimized sequence timing parameters around {82 ms, 48 ms} at 4 T, while the other main metabolites, such as N-acetyl aspartate (NAA), choline (tCho), and creatine (tCr), are still preserved in the same spectrum. The technique can be easily implemented and should prove to be a useful tool for the basic and clinical studies associated with metabolism of Glu, Gln, and/or GABA.

Hippocampal brain-network coordination during volitional exploratory behavior enhances learning

PubMed Central

Voss, Joel L.; Gonsalves, Brian D.; Federmeier, Kara D.; Tranel, Daniel; Cohen, Neal J.

2010-01-01

Exploratory behaviors during learning determine what is studied and when, helping to optimize subsequent memory performance. We manipulated how much control subjects had over the position of a moving window through which they studied objects and their locations, in order to elucidate the cognitive and neural determinants of exploratory behaviors. Our behavioral, neuropsychological, and neuroimaging data indicate volitional control benefits memory performance, and is linked to a brain network centered on the hippocampus. Increases in correlated activity between the hippocampus and other areas were associated with specific aspects of memory, suggesting that volitional control optimizes interactions among specialized neural systems via the hippocampus. Memory is therefore an active process intrinsically linked to behavior. Furthermore, brain structures typically seen as passive participants in memory encoding (e.g., the hippocampus) are actually part of an active network that controls behavior dynamically as it unfolds. PMID:21102449

[AWAKE CRANIOTOMY: IN SEARCH FOR OPTIMAL SEDATION].

PubMed

Kulikova, A S; Sel'kov, D A; Kobyakov, G L; Shmigel'skiy, A V; Lubnin, A Yu

2015-01-01

Awake craniotomy is a "gold standard"for intraoperative brain language mapping. One of the main anesthetic challenge of awake craniotomy is providing of optimal sedation for initial stages of intervention. The goal of this study was comparison of different technics of anesthesia for awake craniotomy. Materials and methods: 162 operations were divided in 4 groups: 76 cases with propofol sedation (2-4mg/kg/h) without airway protection; 11 cases with propofol sedation (4-5 mg/kg/h) with MV via LMA; 36 cases of xenon anesthesia; and 39 cases with dexmedetomidine sedation without airway protection. Results and discussion: brain language mapping was successful in 90% of cases. There was no difference between groups in successfulness of brain mapping. However in the first group respiratory complications were more frequent. Three other technics were more safer Xenon anesthesia was associated with ultrafast awakening for mapping (5±1 min). Dexmedetomidine sedation provided high hemodynamic and respiratory stability during the procedure.

Hippocampal brain-network coordination during volitional exploratory behavior enhances learning.

PubMed

Voss, Joel L; Gonsalves, Brian D; Federmeier, Kara D; Tranel, Daniel; Cohen, Neal J

2011-01-01

Exploratory behaviors during learning determine what is studied and when, helping to optimize subsequent memory performance. To elucidate the cognitive and neural determinants of exploratory behaviors, we manipulated the control that human subjects had over the position of a moving window through which they studied objects and their locations. Our behavioral, neuropsychological and neuroimaging data indicate that volitional control benefits memory performance and is linked to a brain network that is centered on the hippocampus. Increases in correlated activity between the hippocampus and other areas were associated with specific aspects of memory, which suggests that volitional control optimizes interactions among specialized neural systems through the hippocampus. Memory is therefore an active process that is intrinsically linked to behavior. Furthermore, brain structures that are typically seen as passive participants in memory encoding (for example, the hippocampus) are actually part of an active network that controls behavior dynamically as it unfolds.

Optimization of a Small Tropomyosin-related Kinase B (TrkB) Agonist 7,8-Dihydroxyflavone Active in Mouse Models of Depression

PubMed Central

Liu, Xia; Chan, Chi-Bun; Qi, Qi; Xiao, Ge; Luo, Hongbo R.; He, Xiaolin; Ye, Keqiang

2012-01-01

Structure-activity relationship study shows that the catechol group in 7,8-dihdyroxyflavone, a selective small TrkB receptor agonist, is critical for the agonistic activity. To improve the poor pharmacokinetic profiles intrinsic to catechol-containing molecules and elevate the agonistic effect of the lead compound, we initiated the lead optimization campaign by synthesizing various bioisosteric derivatives. Here we show that the optimized 2-methyl-8-(4′-(pyrrolidin-1-yl)phenyl)chromeno[7,8-d]imidazol-6(1H)-one derivative possesses the enhanced TrkB stimulatory activity. Chronic oral administration of this compound significantly reduces the immobility in forced swim test and tail suspension test, two classical antidepressant behavioral animal models, which is accompanied by robust TrkB activation in hippocampus of mouse brain. Further, in vitro ADMET studies demonstrate that this compound possesses the improved features compared to the previous lead compound. Hence, this optimized compound may act as a promising lead candidate for in-depth drug development for treating various neurological disorders including depression. PMID:22984948

Wavelength, beam size and type dependences of cerebral low-level light therapy: A Monte Carlo study on visible Chinese human

NASA Astrophysics Data System (ADS)

Li, Ting; Zhao, Yue; Duan, Meixue; Sun, Yunlong; Li, Kai

2014-02-01

Low level light therapy (LLLT) has been clinically utilized for many indications in medicine requiring protection from cell/tissue death, stimulation of healing and repair of injuries, pain reduction, swelling and inflammation. Presently, use of LLLT to treat stroke, traumatic brain injury, and cognitive dysfunction is attracting growing interest. Near-infrared light can penetrate into the brain tissue, allowing noninvasive treatment to be carried out with few treatment-related adverse events. Optimization of LLLT treatment effect is one key issue of the field; however, only a few experimental tests on mice for wavelength selection have been reported. We addressed this issue by low-cost, straightforward and quantitative comparisons on light dosage distribution in Visible Chinese human head with Monte Carlo modeling of light propagation. Optimized selection in wavelength, beam type and size were given based on comparisons among frequently-used setups (i.e., wavelengths: 660 nm, 810 nm, 980 nm; beam type: Gaussian and flat beam; beam diameter: 2 cm, 4 cm, 6cm).This study provided an efficient way to guide optimization of LLLT setup and selection on wavelength, beam type and size for clinical brain LLLT.

Transcranial direct current stimulation in obsessive-compulsive disorder: emerging clinical evidence and considerations for optimal montage of electrodes.

PubMed

Senço, Natasha M; Huang, Yu; D'Urso, Giordano; Parra, Lucas C; Bikson, Marom; Mantovani, Antonio; Shavitt, Roseli G; Hoexter, Marcelo Q; Miguel, Eurípedes C; Brunoni, André R

2015-07-01

Neuromodulation techniques for obsessive-compulsive disorder (OCD) treatment have expanded with greater understanding of the brain circuits involved. Transcranial direct current stimulation (tDCS) might be a potential new treatment for OCD, although the optimal montage is unclear. To perform a systematic review on meta-analyses of repetitive transcranianal magnetic stimulation (rTMS) and deep brain stimulation (DBS) trials for OCD, aiming to identify brain stimulation targets for future tDCS trials and to support the empirical evidence with computer head modeling analysis. Systematic reviews of rTMS and DBS trials on OCD in Pubmed/MEDLINE were searched. For the tDCS computational analysis, we employed head models with the goal of optimally targeting current delivery to structures of interest. Only three references matched our eligibility criteria. We simulated four different electrodes montages and analyzed current direction and intensity. Although DBS, rTMS and tDCS are not directly comparable and our theoretical model, based on DBS and rTMS targets, needs empirical validation, we found that the tDCS montage with the cathode over the pre-supplementary motor area and extra-cephalic anode seems to activate most of the areas related to OCD.

MR brain volumetric measurements are predictive of neurobehavioral impairment in the HIV-1 transgenic rat.

PubMed

Casas, Rafael; Muthusamy, Siva; Wakim, Paul G; Sinharay, Sanhita; Lentz, Margaret R; Reid, William C; Hammoud, Dima A

2018-01-01

HIV infection is known to be associated with brain volume loss, even in optimally treated patients. In this study, we assessed whether dynamic brain volume changes over time are predictive of neurobehavorial performance in the HIV-1 transgenic (Tg) rat, a model of treated HIV-positive patients. Cross-sectional brain MRI imaging was first performed comparing Tg and wild type (WT) rats at 3 and 19 months of age. Longitudinal MRI and neurobehavioral testing of another group of Tg and WT rats was then performed from 5 to 23 weeks of age. Whole brain and subregional image segmentation was used to assess the rate of brain growth over time. We used repeated-measures mixed models to assess differences in brain volumes and to establish how predictive the volume differences are of specific neurobehavioral deficits. Cross-sectional imaging showed smaller whole brain volumes in Tg compared to WT rats at 3 and at 19 months of age. Longitudinally, Tg brain volumes were smaller than age-matched WT rats at all time points, starting as early as 5 weeks of age. The Tg striatal growth rate delay between 5 and 9 weeks of age was greater than that of the whole brain. Striatal volume in combination with genotype was the most predictive of rota-rod scores and in combination with genotype and age was the most predictive of total exploratory activity scores in the Tg rats. The disproportionately delayed striatal growth compared to whole brain between 5 and 9 weeks of age and the role of striatal volume in predicting neurobehavioral deficits suggest an important role of the dopaminergic system in HIV associated neuropathology. This might explain problems with motor coordination and executive decisions in this animal model. Smaller brain and subregional volumes and neurobehavioral deficits were seen as early as 5 weeks of age, suggesting an early brain insult in the Tg rat. Neuroprotective therapy testing in this model should thus target this early stage of development, before brain damage becomes irreversible.

The development and modeling of devices and paradigms for transcranial magnetic stimulation

PubMed Central

Goetz, Stefan M.; Deng, Zhi-De

2017-01-01

Magnetic stimulation is a noninvasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modeling. PMID:28443696

The development and modelling of devices and paradigms for transcranial magnetic stimulation.

PubMed

Goetz, Stefan M; Deng, Zhi-De

2017-04-01

Magnetic stimulation is a non-invasive neurostimulation technique that can evoke action potentials and modulate neural circuits through induced electric fields. Biophysical models of magnetic stimulation have become a major driver for technological developments and the understanding of the mechanisms of magnetic neurostimulation and neuromodulation. Major technological developments involve stimulation coils with different spatial characteristics and pulse sources to control the pulse waveform. While early technological developments were the result of manual design and invention processes, there is a trend in both stimulation coil and pulse source design to mathematically optimize parameters with the help of computational models. To date, macroscopically highly realistic spatial models of the brain, as well as peripheral targets, and user-friendly software packages enable researchers and practitioners to simulate the treatment-specific and induced electric field distribution in the brains of individual subjects and patients. Neuron models further introduce the microscopic level of neural activation to understand the influence of activation dynamics in response to different pulse shapes. A number of models that were designed for online calibration to extract otherwise covert information and biomarkers from the neural system recently form a third branch of modelling.

Drugs in development for toxoplasmosis: advances, challenges, and current status.

PubMed

Alday, P Holland; Doggett, Joseph Stone

2017-01-01

Toxoplasma gondii causes fatal and debilitating brain and eye diseases. Medicines that are currently used to treat toxoplasmosis commonly have toxic side effects and require prolonged courses that range from weeks to more than a year. The need for long treatment durations and the risk of relapsing disease are in part due to the lack of efficacy against T. gondii tissue cysts. The challenges for developing a more effective treatment for toxoplasmosis include decreasing toxicity, achieving therapeutic concentrations in the brain and eye, shortening duration, eliminating tissue cysts from the host, safety in pregnancy, and creating a formulation that is inexpensive and practical for use in resource-poor areas of the world. Over the last decade, significant progress has been made in identifying and developing new compounds for the treatment of toxoplasmosis. Unlike clinically used medicines that were repurposed for toxoplasmosis, these compounds have been optimized for efficacy against toxoplasmosis during preclinical development. Medicines with enhanced efficacy as well as features that address the unique aspects of toxoplasmosis have the potential to greatly improve toxoplasmosis therapy. This review discusses the facets of toxoplasmosis that are pertinent to drug design and the advances, challenges, and current status of preclinical drug research for toxoplasmosis.

[The Role of Physician In Enhancement of Rehabilitation of Disabled Children].

PubMed

Nizova, L M; Kislisyna, I G

2017-09-01

The national and international experience of rehabilitation of disabled children was investigated. On the basis of monitoring data problem of increasing of number of children with diagnosis of infantile cerebral paralysis, including necessity of development of new methods of their rehabilitation was established. The comparative dynamics of nosology of disabled children permitted to detect diseases of nervous system and congenital abnormalities (malformations), deformations and chromosomal disorders, psychological disorders and behavioral disorders mostly specific for urban and rural area. The model of institutional environment of rehabilitation of disabled children was developed including system of formal (state, legislative acts, health institutions, organizations of social support of population)and non-formal (public, non-commercial and social psychological organizations) institutions impacted by economic, social,legal and demographic factors. The role of physician is substantiated concerning increasing of quality of rehabilitation services: diagnostic of disordered functions, detection of optimal volume of medical, psychological and pedagogue activities in patients with severe speech disorders, motoric and and neuro-censorial disorders developed as a result of early organic damage of brain, neuro-infections, strokes, and other affection of brain. The adequate curative rehabilitative complex programs were developed of social everyday and social labor rehabilitation.

Drugs in development for toxoplasmosis: advances, challenges, and current status

PubMed Central

Alday, P Holland; Doggett, Joseph Stone

2017-01-01

Toxoplasma gondii causes fatal and debilitating brain and eye diseases. Medicines that are currently used to treat toxoplasmosis commonly have toxic side effects and require prolonged courses that range from weeks to more than a year. The need for long treatment durations and the risk of relapsing disease are in part due to the lack of efficacy against T. gondii tissue cysts. The challenges for developing a more effective treatment for toxoplasmosis include decreasing toxicity, achieving therapeutic concentrations in the brain and eye, shortening duration, eliminating tissue cysts from the host, safety in pregnancy, and creating a formulation that is inexpensive and practical for use in resource-poor areas of the world. Over the last decade, significant progress has been made in identifying and developing new compounds for the treatment of toxoplasmosis. Unlike clinically used medicines that were repurposed for toxoplasmosis, these compounds have been optimized for efficacy against toxoplasmosis during preclinical development. Medicines with enhanced efficacy as well as features that address the unique aspects of toxoplasmosis have the potential to greatly improve toxoplasmosis therapy. This review discusses the facets of toxoplasmosis that are pertinent to drug design and the advances, challenges, and current status of preclinical drug research for toxoplasmosis. PMID:28182168

Prediction of movement intention using connectivity within motor-related network: An electrocorticography study.

PubMed

Kang, Byeong Keun; Kim, June Sic; Ryun, Seokyun; Chung, Chun Kee

2018-01-01

Most brain-machine interface (BMI) studies have focused only on the active state of which a BMI user performs specific movement tasks. Therefore, models developed for predicting movements were optimized only for the active state. The models may not be suitable in the idle state during resting. This potential maladaptation could lead to a sudden accident or unintended movement resulting from prediction error. Prediction of movement intention is important to develop a more efficient and reasonable BMI system which could be selectively operated depending on the user's intention. Physical movement is performed through the serial change of brain states: idle, planning, execution, and recovery. The motor networks in the primary motor cortex and the dorsolateral prefrontal cortex are involved in these movement states. Neuronal communication differs between the states. Therefore, connectivity may change depending on the states. In this study, we investigated the temporal dynamics of connectivity in dorsolateral prefrontal cortex and primary motor cortex to predict movement intention. Movement intention was successfully predicted by connectivity dynamics which may reflect changes in movement states. Furthermore, dorsolateral prefrontal cortex is crucial in predicting movement intention to which primary motor cortex contributes. These results suggest that brain connectivity is an excellent approach in predicting movement intention.

Drug Delivery Systems, CNS Protection, and the Blood Brain Barrier

PubMed Central

Upadhyay, Ravi Kant

2014-01-01

Present review highlights various drug delivery systems used for delivery of pharmaceutical agents mainly antibiotics, antineoplastic agents, neuropeptides, and other therapeutic substances through the endothelial capillaries (BBB) for CNS therapeutics. In addition, the use of ultrasound in delivery of therapeutic agents/biomolecules such as proline rich peptides, prodrugs, radiopharmaceuticals, proteins, immunoglobulins, and chimeric peptides to the target sites in deep tissue locations inside tumor sites of brain has been explained. In addition, therapeutic applications of various types of nanoparticles such as chitosan based nanomers, dendrimers, carbon nanotubes, niosomes, beta cyclodextrin carriers, cholesterol mediated cationic solid lipid nanoparticles, colloidal drug carriers, liposomes, and micelles have been discussed with their recent advancements. Emphasis has been given on the need of physiological and therapeutic optimization of existing drug delivery methods and their carriers to deliver therapeutic amount of drug into the brain for treatment of various neurological diseases and disorders. Further, strong recommendations are being made to develop nanosized drug carriers/vehicles and noninvasive therapeutic alternatives of conventional methods for better therapeutics of CNS related diseases. Hence, there is an urgent need to design nontoxic biocompatible drugs and develop noninvasive delivery methods to check posttreatment clinical fatalities in neuropatients which occur due to existing highly toxic invasive drugs and treatment methods. PMID:25136634

A physiologically based pharmacokinetic (PBPK) model for predicting the efficacy of drug overdose treatment with liposomes in man.

PubMed

Howell, Brett A; Chauhan, Anuj

2010-08-01

Physiologically based pharmacokinetic (PBPK) models were developed for design and optimization of liposome therapy for treatment of overdoses of tricyclic antidepressants and local anesthetics. In vitro drug-binding data for pegylated, anionic liposomes and published mechanistic equations for partition coefficients were used to develop the models. The models were proven reliable through comparisons to intravenous data. The liposomes were predicted to be highly effective at treating amitriptyline overdoses, with reductions in the area under the concentration versus time curves (AUC) of 64% for the heart and brain. Peak heart and brain drug concentrations were predicted to drop by 20%. Bupivacaine AUC and peak concentration reductions were lower at 15.4% and 17.3%, respectively, for the heart and brain. The predicted pharmacokinetic profiles following liposome administration agreed well with data from clinical studies where protein fragments were administered to patients for overdose treatment. Published data on local cardiac function were used to relate the predicted concentrations in the body to local pharmacodynamic effects in the heart. While the results offer encouragement for future liposome therapies geared toward overdose, it is imperative to point out that animal experiments and phase I clinical trials are the next steps to ensuring the efficacy of the treatment. (c) 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Development and Design of Next-Generation Head-Mounted Ambulatory Microdose Positron-Emission Tomography (AM-PET) System.

PubMed

Melroy, Samantha; Bauer, Christopher; McHugh, Matthew; Carden, Garret; Stolin, Alexander; Majewski, Stan; Brefczynski-Lewis, Julie; Wuest, Thorsten

2017-05-19

Several applications exist for a whole brain positron-emission tomography (PET) brain imager designed as a portable unit that can be worn on a patient's head. Enabled by improvements in detector technology, a lightweight, high performance device would allow PET brain imaging in different environments and during behavioral tasks. Such a wearable system that allows the subjects to move their heads and walk-the Ambulatory Microdose PET (AM-PET)-is currently under development. This imager will be helpful for testing subjects performing selected activities such as gestures, virtual reality activities and walking. The need for this type of lightweight mobile device has led to the construction of a proof of concept portable head-worn unit that uses twelve silicon photomultiplier (SiPM) PET module sensors built into a small ring which fits around the head. This paper is focused on the engineering design of mechanical support aspects of the AM-PET project, both of the current device as well as of the coming next-generation devices. The goal of this work is to optimize design of the scanner and its mechanics to improve comfort for the subject by reducing the effect of weight, and to enable diversification of its applications amongst different research activities.

Development and Design of Next-Generation Head-Mounted Ambulatory Microdose Positron-Emission Tomography (AM-PET) System

PubMed Central

Melroy, Samantha; Bauer, Christopher; McHugh, Matthew; Carden, Garret; Stolin, Alexander; Majewski, Stan; Brefczynski-Lewis, Julie; Wuest, Thorsten

2017-01-01

Several applications exist for a whole brain positron-emission tomography (PET) brain imager designed as a portable unit that can be worn on a patient’s head. Enabled by improvements in detector technology, a lightweight, high performance device would allow PET brain imaging in different environments and during behavioral tasks. Such a wearable system that allows the subjects to move their heads and walk—the Ambulatory Microdose PET (AM-PET)—is currently under development. This imager will be helpful for testing subjects performing selected activities such as gestures, virtual reality activities and walking. The need for this type of lightweight mobile device has led to the construction of a proof of concept portable head-worn unit that uses twelve silicon photomultiplier (SiPM) PET module sensors built into a small ring which fits around the head. This paper is focused on the engineering design of mechanical support aspects of the AM-PET project, both of the current device as well as of the coming next-generation devices. The goal of this work is to optimize design of the scanner and its mechanics to improve comfort for the subject by reducing the effect of weight, and to enable diversification of its applications amongst different research activities. PMID:28534848

A Real-Time Brain-Machine Interface Combining Motor Target and Trajectory Intent Using an Optimal Feedback Control Design

PubMed Central

Shanechi, Maryam M.; Williams, Ziv M.; Wornell, Gregory W.; Hu, Rollin C.; Powers, Marissa; Brown, Emery N.

2013-01-01

Real-time brain-machine interfaces (BMI) have focused on either estimating the continuous movement trajectory or target intent. However, natural movement often incorporates both. Additionally, BMIs can be modeled as a feedback control system in which the subject modulates the neural activity to move the prosthetic device towards a desired target while receiving real-time sensory feedback of the state of the movement. We develop a novel real-time BMI using an optimal feedback control design that jointly estimates the movement target and trajectory of monkeys in two stages. First, the target is decoded from neural spiking activity before movement initiation. Second, the trajectory is decoded by combining the decoded target with the peri-movement spiking activity using an optimal feedback control design. This design exploits a recursive Bayesian decoder that uses an optimal feedback control model of the sensorimotor system to take into account the intended target location and the sensory feedback in its trajectory estimation from spiking activity. The real-time BMI processes the spiking activity directly using point process modeling. We implement the BMI in experiments consisting of an instructed-delay center-out task in which monkeys are presented with a target location on the screen during a delay period and then have to move a cursor to it without touching the incorrect targets. We show that the two-stage BMI performs more accurately than either stage alone. Correct target prediction can compensate for inaccurate trajectory estimation and vice versa. The optimal feedback control design also results in trajectories that are smoother and have lower estimation error. The two-stage decoder also performs better than linear regression approaches in offline cross-validation analyses. Our results demonstrate the advantage of a BMI design that jointly estimates the target and trajectory of movement and more closely mimics the sensorimotor control system. PMID:23593130

Emerging Trends in the Management of Brain Metastases from Non-small Cell Lung Cancer.

PubMed

Churilla, Thomas M; Weiss, Stephanie E

2018-05-07

To summarize current approaches in the management of brain metastases from non-small cell lung cancer (NSCLC). Local treatment has evolved from whole-brain radiotherapy (WBRT) to increasing use of stereotactic radiosurgery (SRS) alone for patients with limited (1-4) brain metastases. Trials have established post-operative SRS as an alternative to adjuvant WBRT following resection of brain metastases. Second-generation TKIs for ALK rearranged NSCLC have demonstrated improved CNS penetration and activity. Current brain metastasis trials are focused on reducing cognitive toxicity: hippocampal sparing WBRT, SRS for 5-15 metastases, pre-operative SRS, and use of systemic targeted agents or immunotherapy. The role for radiotherapy in the management of brain metastases is becoming better defined with local treatment shifting from WBRT to SRS alone for limited brain metastases and post-operative SRS for resected metastases. Further trials are warranted to define the optimal integration of newer systemic agents with local therapies.

Information properties of morphologically complex words modulate brain activity during word reading.

PubMed

Hakala, Tero; Hultén, Annika; Lehtonen, Minna; Lagus, Krista; Salmelin, Riitta

2018-06-01

Neuroimaging studies of the reading process point to functionally distinct stages in word recognition. Yet, current understanding of the operations linked to those various stages is mainly descriptive in nature. Approaches developed in the field of computational linguistics may offer a more quantitative approach for understanding brain dynamics. Our aim was to evaluate whether a statistical model of morphology, with well-defined computational principles, can capture the neural dynamics of reading, using the concept of surprisal from information theory as the common measure. The Morfessor model, created for unsupervised discovery of morphemes, is based on the minimum description length principle and attempts to find optimal units of representation for complex words. In a word recognition task, we correlated brain responses to word surprisal values derived from Morfessor and from other psycholinguistic variables that have been linked with various levels of linguistic abstraction. The magnetoencephalography data analysis focused on spatially, temporally and functionally distinct components of cortical activation observed in reading tasks. The early occipital and occipito-temporal responses were correlated with parameters relating to visual complexity and orthographic properties, whereas the later bilateral superior temporal activation was correlated with whole-word based and morphological models. The results show that the word processing costs estimated by the statistical Morfessor model are relevant for brain dynamics of reading during late processing stages. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Connecting the Brain to Itself through an Emulation

PubMed Central

Serruya, Mijail D.

2017-01-01

Pilot clinical trials of human patients implanted with devices that can chronically record and stimulate ensembles of hundreds to thousands of individual neurons offer the possibility of expanding the substrate of cognition. Parallel trains of firing rate activity can be delivered in real-time to an array of intermediate external modules that in turn can trigger parallel trains of stimulation back into the brain. These modules may be built in software, VLSI firmware, or biological tissue as in vitro culture preparations or in vivo ectopic construct organoids. Arrays of modules can be constructed as early stage whole brain emulators, following canonical intra- and inter-regional circuits. By using machine learning algorithms and classic tasks known to activate quasi-orthogonal functional connectivity patterns, bedside testing can rapidly identify ensemble tuning properties and in turn cycle through a sequence of external module architectures to explore which can causatively alter perception and behavior. Whole brain emulation both (1) serves to augment human neural function, compensating for disease and injury as an auxiliary parallel system, and (2) has its independent operation bootstrapped by a human-in-the-loop to identify optimal micro- and macro-architectures, update synaptic weights, and entrain behaviors. In this manner, closed-loop brain-computer interface pilot clinical trials can advance strong artificial intelligence development and forge new therapies to restore independence in children and adults with neurological conditions. PMID:28713235

Dehydroepiandrosterone impacts working memory by shaping cortico-hippocampal structural covariance during development.

PubMed

Nguyen, Tuong-Vi; Wu, Mia; Lew, Jimin; Albaugh, Matthew D; Botteron, Kelly N; Hudziak, James J; Fonov, Vladimir S; Collins, D Louis; Campbell, Benjamin C; Booij, Linda; Herba, Catherine; Monnier, Patricia; Ducharme, Simon; McCracken, James T

2017-12-01

Existing studies suggest that dehydroepiandrosterone (DHEA) may be important for human brain development and cognition. For example, molecular studies have hinted at the critical role of DHEA in enhancing brain plasticity. Studies of human brain development also support the notion that DHEA is involved in preserving cortical plasticity. Further, some, though not all, studies show that DHEA administration may lead to improvements in working memory in adults. Yet these findings remain limited by an incomplete understanding of the specific neuroanatomical mechanisms through which DHEA may impact the CNS during development. Here we examined associations between DHEA, cortico-hippocampal structural covariance, and working memory (216 participants [female=123], age range 6-22 years old, mean age: 13.6 +/-3.6 years, each followed for a maximum of 3 visits over the course of 4 years). In addition to administering performance-based, spatial working memory tests to these children, we also collected ecological, parent ratings of working memory in everyday situations. We found that increasingly higher DHEA levels were associated with a shift toward positive insular-hippocampal and occipito-hippocampal structural covariance. In turn, DHEA-related insular-hippocampal covariance was associated with lower spatial working memory but higher overall working memory as measured by the ecological parent ratings. Taken together with previous research, these results support the hypothesis that DHEA may optimize cortical functions related to general attentional and working memory processes, but impair the development of bottom-up, hippocampal-to-cortical connections, resulting in impaired encoding of spatial cues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimized optical clearing method for imaging central nervous system

NASA Astrophysics Data System (ADS)

Yu, Tingting; Qi, Yisong; Gong, Hui; Luo, Qingming; Zhu, Dan

2015-03-01

The development of various optical clearing methods provides a great potential for imaging entire central nervous system by combining with multiple-labelling and microscopic imaging techniques. These methods had made certain clearing contributions with respective weaknesses, including tissue deformation, fluorescence quenching, execution complexity and antibody penetration limitation that makes immunostaining of tissue blocks difficult. The passive clarity technique (PACT) bypasses those problems and clears the samples with simple implementation, excellent transparency with fine fluorescence retention, but the passive tissue clearing method needs too long time. In this study, we not only accelerate the clearing speed of brain blocks but also preserve GFP fluorescence well by screening an optimal clearing temperature. The selection of proper temperature will make PACT more applicable, which evidently broaden the application range of this method.

Maternal nutrient deprivation induces sex-specific changes in thyroid hormone receptor and deiodinase expression in the fetal guinea pig brain

PubMed Central

Chan, Shiao Y; Andrews, Marcus H; Lingas, Rania; McCabe, Chris J; Franklyn, Jayne A; Kilby, Mark D; Matthews, Stephen G

2005-01-01

Thyroid hormone deprivation during fetal life has been implicated in neurodevelopmental morbidity. In humans, poor growth in utero is also associated with fetal hypothyroxinaemia. In guinea pigs, a short period (48 h) of maternal nutrient deprivation at gestational day (gd) 50 results in fetuses with hypothyroxinaemia and increased brain/body weight ratios. Thyroid hormone action is mediated by nuclear thyroid hormone receptors (TRs) and is dependent upon the prereceptor regulation of supply of triiodothyronine (T3) by deiodinase enzymes. Examination of fetal guinea pig brains using in situ hybridization demonstrated widespread expression of mRNAs encoding TRα1, α2 and β1, with regional colocalization of deiodinase type 2 (D2) mRNA in the developing forebrain, limbic structures, brainstem and cerebellum at gd52. With maternal nutrient deprivation, TRα1 and β1 mRNA expression was significantly increased in the male, but decreased in the female fetal hippocampus and cerebellum and other areas showing high TR expression under euthyroid conditions. Maternal nutrient deprivation resulted in elevated D2 mRNA expression in males and females. Deiodinase type 3 (D3) mRNA expression was confined to the shell of the nucleus accumbens, the posterior amygdalohippocampal area, brainstem and cerebellum, and did not change with maternal nutrient deprivation. In conclusion, maternal nutrient deprivation resulted in sex-specific changes in TR mRNA expression and a generalized increase in D2 mRNAs within the fetal brain. These changes may represent a protective mechanism to maintain appropriate thyroid hormone action in the face of fetal hypothyroxinaemia in order to optimize brain development. PMID:15878952

Smaller Cerebellar Growth and Poorer Neurodevelopmental Outcomes in Very Preterm Infants Exposed to Neonatal Morphine.

PubMed

Zwicker, Jill G; Miller, Steven P; Grunau, Ruth E; Chau, Vann; Brant, Rollin; Studholme, Colin; Liu, Mengyuan; Synnes, Anne; Poskitt, Kenneth J; Stiver, Mikaela L; Tam, Emily W Y

2016-05-01

To examine the relationship between morphine exposure and growth of the cerebellum and cerebrum in very preterm neonates from early in life to term-equivalent age, as well as to examine morphine exposure and brain volumes in relation to neurodevelopmental outcomes at 18 months corrected age (CA). A prospective cohort of 136 very preterm neonates (24-32 weeks gestational age) was serially scanned with magnetic resonance imaging near birth and at term-equivalent age for volumetric measurements of the cerebellum and cerebrum. Motor outcomes were assessed with the Peabody Developmental Motor Scales, Second Edition and cognitive outcomes with the Bayley Scales of Infant and Toddler Development, Third Edition at 18 months CA. Generalized least squares models and linear regression models were used to assess relationships between morphine exposure, brain volumes, and neurodevelopmental outcomes. A 10-fold increase in morphine exposure was associated with a 5.5% decrease in cerebellar volume, after adjustment for multiple clinical confounders and total brain volume (P = .04). When infants exposed to glucocorticoids were excluded, the association of morphine was more pronounced, with an 8.1% decrease in cerebellar volume. Morphine exposure was not associated with cerebral volume (P = .30). Greater morphine exposure also predicted poorer motor (P < .001) and cognitive outcomes (P = .006) at 18 months CA, an association mediated, in part, by slower brain growth. Morphine exposure in very preterm neonates is independently associated with impaired cerebellar growth in the neonatal period and poorer neurodevelopmental outcomes in early childhood. Alternatives to better manage pain in preterm neonates that optimize brain development and functional outcomes are urgently needed. Copyright © 2016 Elsevier Inc. All rights reserved.

Smaller Cerebellar Growth and Poorer Neurodevelopmental Outcomes in Very Preterm Infants exposed to morphine

PubMed Central

Zwicker, Jill G; Miller, Steven P; Grunau, Ruth E; Chau, Vann; Brant, Rollin; Studholme, Colin; Liu, Mengyuan; Synnes, Anne; Poskitt, Kenneth J; Stiver, Mikaela L; Tam, Emily WY

2017-01-01

Objective To examine the relationship between morphine exposure and growth of the cerebellum and cerebrum in very preterm neonates from early in life to term-equivalent age, as well as to examine morphine exposure and brain volumes in relation to neurodevelopmental outcomes at 18 months corrected age (CA). Study design A prospective cohort of 136 very preterm neonates (24–32 weeks gestational age) was serially scanned with MRI near birth and at term-equivalent age for volumetric measurements of the cerebellum and cerebrum. Motor outcomes were assessed with the Peabody Scales of Motor Development-2 and cognitive outcomes with the Bayley-III at 18 months CA. Generalized least squares models and linear regression models were used to assess relationships between morphine exposure, brain volumes, and neurodevelopmental outcomes. Results A 10-fold increase in morphine exposure was associated with a 5.5% decrease in cerebellar volume, after adjustment for multiple clinical confounders and total brain volume (P=0.04). When infants exposed to glucocorticoids were excluded, the association of morphine was more pronounced, with an 8.2% decrease in cerebellar volume. Morphine exposure was not associated with cerebral volume (P=0.30). Greater morphine exposure also predicted poorer motor (P<0.001) and cognitive outcomes (P=0.006) at 18 months CA, an association mediated, in part, by slower brain growth. Conclusions Morphine exposure in very preterm neonates is independently associated with impaired cerebellar growth in the neonatal period and poorer neurodevelopmental outcomes in early childhood. Alternatives to better manage pain in preterm neonates that optimize brain development and functional outcomes are urgently needed. PMID:26763312